page 4 editors note vol 6 no 2 editor’s note vol 6, no 2 (2016) user perspectives on business intelligence the research articles in this issue are related to business intelligence in one way or another. the article by salmasi, talebpour and homayounvala is entitled “identification and classification of organizational level competencies for bi success”. in their research the authors have identified competencies that can be used as a measure to evaluate an organization’s status with regards to business intelligence success. since the study done by adamala and cidrin (2011) this journal has shown a strong interest in user evaluations of business intelligence systems. the article by ghasemi and rowshan presents a new approach to the early warning literature. entrepreneurs are the group that more than anyone else are seeking out early insights and also rewarded by their ability to look ahead. in the literature this is known as “entrepreneurial alertness.” science can never accept that some people are simply born entrepreneurs or have “eureka” moments: we want to understand why and how. from an intelligence perspective picking up early signals can be seen as a signal for which entrepreneurs to follow and listen to. the ability to gather data from social media through the use of bi tools should make this possible once these entrepreneurs are identified. the article by ghasemi and rowshan does not go in this direction, but such research would be welcome in the future. the article by avner entitled “study on competitive intelligence in isreal: 2016 update” is a status report for competitive intelligence within israeli firms. the results are compared with a study conducted by the same author in 2006. the study shows that there has been no significant change in ci practices in israel during the past ten years. it also confirms that competitive intelligence is primarily a tool used by larger organizations. this means that israeli companies have been slower to adopt new business intelligence software, and this is something that respondents see as a problem. the article by solberg søilen entitled “users’ perception of data as a service (daas)” is an investigation into a new market related to business intelligence. on one hand this is a survey addressing one particular type of users—namely market intelligence (mi), competitive intelligence (ci) and business intelligence (bi) professionals and experts—and their preferences. on the other hand, this is a critical analysis about the consequences of the issues addressed by users. it is also an attempt to present daas in a shorter historical perspective. the case study on qoros automotive manufacturing by ahmadinia and karim is an analysis of how the company could enter the european market. it has now been more than a year since jisib decided to publish case studies as articles. the qorors case is not only a good teaching case, but is also a good illustration of how intelligence topics can be tied to marketing questions and the larger question about competitive advantage. as always, we would above all like to thank the authors for their contributions to this issue of jisib. since the beginning of the year the journal has been supported by a three year grant from the swedish research council (vr). this has allowed us to increase the quality in layout design and review the english grammar. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2016 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 6, no 2 (2016) p. 4 open access: freely available at: https://ojs.hh.se/ page 4 editors note vol 8 no 1 editor’s note vol 8, no 1 (2018) the disciplines of management and it have indeed merged: new empirical data advancement in the intelligence field can only be achieved through new observations and the presentation of new empirical data. this is a continuous process and includes how we as employees engage with software and technical solutions. just as it is impossible to teach or learn anything in marketing today without a deep understanding of digital marketing, in the same way is it impossible to make advancements in intelligence studies without first-hand experience with business intelligence software and new it-equipment. management and it have indeed merged. this understanding has been an integrated part of jisib since the journal started some eight years ago. and as always, we are less interested in how new technologies are developed (for that there are excellent technical journals) than about the management practice of these developments. this issue follows very much on this track. the article by fatma fourati-jamoussi, claude-narcisse niamba and julien duquennoy entitled “an evaluation of competitive and technological intelligence tools: a cluster analysis of users’ perceptions” is an evaluation of competitive and technological intelligence (cti) tools by students to help designers get the best efficiency out of a monitoring process. the paper finds that user perception is greater than expected and that designers of cti tools must take this in account when developing new products. the authors argue that this is a major reason why new software implementation fails in organizations. the article by ahmad abbaspour, amir hussein amirkhani, ali asghar pour ezzat, and mohammad javad hozori is entitled “identifying and describing sub-processes in strategic intelligence process by qualitative content analysis in inductive way”. the authors set out to identify and describe the sub-processes of the strategic intelligence process in organizational analysis. fourteen main sub-processes are identified to describe the strategic intelligence process. the results give new insight into the strategic intelligence process implementations in organizations. the article by mourad oubrich, abdelati hakmaoui, robert bierwolf and mouna haddani entitled “development of a competitive intelligence maturity model-insights from moroccan companies” identifies six ci dimensions (ci culture of an organization, ci deliverables, ci sourcing, ci cycle, ci investment in terms of resources, ci users and ci application) in ci implantation at three different ci levels (early, mid, world class). the article by avner barnea entitled “israeli start-ups – especially in cyber: can a new model enhance their survival rate?” concludes that the high percentage of failures of israeli start-ups is due to the difficulties in comprehending the competitive landscape. barnea draws this conclusion from having worked and interviewed a number of companies for years. he introduces what he calls the competitive review model to help small companies better prepare themselves for intense competition, especially relevant for the cyber security industry. this issue also features a book review of tetlock and gardner’s superforecasting: the art and science of prediction (2015, crown publishers, new york, ny). as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2017 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 8, no 1 (2018) p. 4 open access: freely available at: https://ojs.hh.se/ page 4 editors note vol 8 no 2 editor’s note vol 8, no 2 (2018) social media intelligence web-intelligence is not new to intelligence studies. it plus intelligence has been the most frequent topic of the issues published the past years. thus vol 8, no 1 (2018) is entitled “the disciplines of management and it have indeed merged: new empirical data”, vol 7, no 1 (2017) “business intelligence, big data and theory” and vol 6, no 3 (2016) “what role does technology play for intelligence studies at the start of the 21st century?”. special issues have looked at the problem of it failures in relation to business intelligence: “how companies succeed and fail to succeed with the implementation of intelligence systems”, vol 7, no 3 (2017) and “how companies work and fail to work with business intelligence, vol 7, no 2 (2017). during the past years companies have indeed learned from their failures. maybe this phase was inevitable as a part of growing up. we see the same development on e-commerce sites: they mostly work well now, but didn’t just a few years ago. a certain difference between countries still exists, but the industry is getting there. closely related to failures of implementation are user perspectives on business intelligence systems, which have resulted in numerous research articles. a well-cited article by adamala and cidrin (2011) led to the development of several models and theories as presented, for example, in vol 6, no 2 (2016) entitled “user perspectives on business intelligence”. the focus in jisib is always technology. it is more a question of which aspect of technology we focus on. in this issue, it is social media or social media intelligence. the paper by gioti and ponis entitled “social business intelligence: review and research directions” is a literature review exploring the new direction of social business intelligence (sbi), where social media meets bi. the last paper is entitled “business intelligence for social media interaction in the travel industry in indonesia”. the authors, yulianto, girsang and rumagit propose a way to develop a data warehouse to analyze data from social media, such as likes, comments and sentiment, applied to the travel industry in indonesia. another aspect of the journal maintains the tradition of intelligence studies in general. intelligence studies must always be broad to be relevant and not to miss important pieces. specialization is a necessity and a curse at the same time. vol 6, no 1 (2016) in entitled “the width and scope of intelligence studies in business”. a part of this width and critique has involved self-reflection. thus earlier articles in jisib often discussed methods. case studies (by country or industry) were always a favorite. in vol 4, no 3 (2014) jisib continued this tradition of publishing case studies. in vol 3, no 2 (2013), the whole issue is dedicated to one country; brazil. analyzing patents analysis has also been a frequent and reoccurring topic. in this issue both of these directions are represented. the third article is entitled “investigating the competitive ıntelligence practices of peruvian fresh grapes exporters,” written by bisson, mercedes, and tong. the authors suggest a number of changes for peruvian grapes exporters to become more competitive based on a ci approach. the fourth paper by shaikh and singhal entitled “an analysis of ip management strategies of ict companies based on patent filings” tries to identify the strategies of five us and indian it companies by analyzing their patents. the first paper by nuortimo is entitled “measuring public acceptance with opinion mining: the case of the energy industry with long-term coal r&d investment projects” and is part of his dissertation in science communication at the faculty of humanities at the university of oulu. the paper shows how opinion mining can be used effectively, and was one of a series presented at the ici conference in bad nauheim this year. many of the earlier papers in jisib came directly from academic or practitioners’ conferences. in vol 2, no 1 (2012) it said: “the journal works in symbioses with a number of conferences. it relies heavily on the contributions of scientific papers presented at these conferences, in particular for these first issues. among these we would in particular like to mention the more scholarly conferences, like vsst, ecis, icticti and siie. in the near future we also hope to receive contributions journal of intelligence studies in business vol. 8, no 2 (2018) p. 4-5 open access: freely available at: https://ojs.hh.se/ from inosa and eckm. we also receive support from members in the more professional conferences related to intelligence studies like ici and scip” (p. 4). and vol 3, no 3 (2013): “the journal continues to draw mainly on articles presented at academic conferences on topics related to competitive intelligence. in 2013 scip organized a first conference in south africa, under the leadership of asa du toit, the journal’s editor for africa.”. and in vol 2, no 3 (2012): “most contributions continue to come from the best papers from a number of conferences related to intelligence studies. two out of five articles come from eckm 2012, which was held 6-7 september in cartagena, spain.” and in vol 2, no 2 (2012) echoed a similar sentiment. today the number of conferences has been reduced for different reasons, which it takes too long to get into here and now. the last group of articles worth mentioning is opinion pieces. these are non-empirical articles. today they are less frequent, but at the beginning they served another role, as pointed out in vol 4, no 1 (2014): “in this issue of jisib we have admitted a large number of opinion pieces. opinion pieces are important to allow for a broader perspective of the field in terms of policies, adaptions of ci in foreign countries and general interest in the form of debates. it also shows the normative qualities that are present in any social science discipline”. at the very beginning it was also made clear that the goal was always to be relevant for practitioners. thus in vol 1, no 1 (2011) we read: “the final aim of the journal is to be of use to practitioners. we are not interested in theory for the sake of theory, and we do not want to publish solutions to small problems which will have no real impact in the intelligence field.”. with your help we try to keep with that goal. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. a special congratulation goes to rainer michaeli for having taken the ici conference to its 10th anniversary. well done, and thank you for the ongoing cooperation. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2018 jisib, halmstad university. all rights reserved. issn: 2001-015x v o l 5 , n o 1 ( 2 0 1 5 ) c o n t e n t s yves barlette, katherine gundolf, annabelle jaouen toward a better understanding of smb ceos' information security behavior: insights from threat or coping appraisal pp. 5-17 abdesamad zouine, pierre fenies a new evaluation model of erp system success pp. 18-39 vincent grèzes the definition of competitive intelligence needs through a synthesis model pp. 40-56 jonathan calof 1 , laurent mirabeau 1 , greg richards 1 towards an environmental awareness model integrating formal and informal mechanisms – lessons learned from the demise of nortel pp. 57-69 o p i n i o n s e c t i o n jean-maurice bruneau, pascal frion revisiting sun tzu in the information overload age for applied intelligence education: stop answering, find good questions pp. 70-89 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: prof. dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2015 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india associate professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain associate professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, hedin intelligence & strategy consultancy, sweden mourad oubrich, president of ciems, morocco javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, may 25th 2015 e d i t o r i a l n o t e v o l 5 , n o 1 ( 2 0 1 5 ) in this issue of jisib we bring you articles from two different conferences held this spring. the first was the 7 th international competitive intelligence (ici) conference held in strasburg 25-26 th march. the second was the it management annual (aim) conference held in rabat may 20-22. the journal would like to thank the organizers of these conferences for a fruitful cooperation, where jisib editors have served as reviewers of scientific track papers and best paper awards. to keep up with the journals new aim to publish case studies calof et al. present the story of nortel, a canadian telecommunications and data networking equipment manufacturer which went bankrupt in 2009. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen editor-in-chief halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 https://en.wikipedia.org/wiki/telecommunications https://en.wikipedia.org/wiki/networking_equipment issn: 2001-015x v o l 2 , n o 2 ( 2 0 1 2 ) c o n t e n t s brigitte gay competitive intelligence and complex systems pp. 5-14 scott erickson and helen rothberg balancing knowledge management and competitive intelligence, initial insights pp. 15-22 jihene chebbi ghannay and zeineb ben ammar mamlouk zeineb synergy between competitive intelligence and knowledge management a key for competitive advantage pp. 23-34 olivier mamawi foundations of competitive intelligence system to form business coalitions pp. 35-41 gabriela lópez, steve eldridge, salomón montejano and patricia silva competiveness from contextualisation of supply chain knowledge pp. 42-50 mattias nyblom, jenny behrami, tung nikkilä and klaus solberg søilen an evaluation of business intelligence software systems in smes – a case study pp. 51-57 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2011 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : arik johnson, chairman aurora wdc, united states raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden dr. sofiane saadi, directeur général du laboratoire en organisation et gestion des entreprises (loge) algeria. managing director nt2s consulting inc. north vancouver, bc, canada javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, september 30 2012 e d i t o r i a l n o t e v o l 2 , n o 2 ( 2 0 1 2 ) the third issue of jisib marks the journal’s first anniversary. again we are delighted to welcome contributions by academics from all over the world, from so many different backgrounds. we also delighted to have contributions from a large number of female authors. this together shows, we believe, that the field of intelligence studies has a truly global reach. most contributions continue to come from best papers from a number of conferences related to intelligence studies. for the articles in this issue we would like to thank in particular our american editor, prof. g. scott erickson. four out of six articles this time come from eckm 2012, which was held 6-7 september in cartagena, spain. track co-chairs for the mini track on competitive intelligence and km was g. scott erickson, ithaca college, ithaca, ny and helen n. rothberg, marist college, poughkeepsie, new york. the article by brigitte gay shows how graphs can be used to illustrate and understand relations between organizations and companies. it illustrates well the degree to which the field of competitive intelligence relies heavily today on the development of new software. the article by scott ericson and helen rothberg clarifies much around the importance of knowledge assets and the study of knowledge management with that of competitive intelligence. few have done more to understand this area than these two authors. their findings have also been published in a new book this year, “intelligence in action” (palgrave macmillan). the contribution by jihene chebbi ghannay and zeineb ben ammar mamlouk zeineb is a literature review that shows the same interdependence between ci and km. the article by olivier mamavi shows what you can do with graphs to identify and understand networks for problems containing big data, in this case companies who have obtained french procurement contracts. the article by gabriela lópez, steve eldridge, salomón montejano and patricia silva shows how to improve supply chain knowledge by a continuous evaluation and contextualization of a company’s own practices. the last article by mattias nyblom, jenny behrami, tung nikkilä and klaus solberg søilen is an investigation into what kind of business intelligence software is used by smes, why, and how companies evaluate their systems. as such its aim is to narrow a gap between theory and practice. on behalf of the editorial board, sincerely yours, dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 page 4 editors note vol 8 no 3 editor’s note vol 8, no 3 (2018) why you should be interested in intelligence studies in this issue most articles are reflections (bibliometrics, scientometrics) on what has been done in intelligence studies in business (is) and more particularly in competitive intelligence (ci) and business intelligence (bi), so some reflections and analysis on the subject proper seems to be appropriate for these notes. almost all articles in is (ci, competitor intelligence, market intelligence (mi), bi, and competitive technical intelligence (cti)) are empirical contributions that show how to work more effectively with need to know information in business. authors submit empirical articles that solve new and specific problems. it can be a new method, the introduction of a new model or the application of some new technology. during the past eight years, since the journal started, i have written articles on what customers expect from bi (sabanovic & søilen, 2012), about what vendors do to differentiate themselves in bi (søilen & hasslinger, 2012b), and i have done an analysis of previous and similar articles in journal of competitive intelligence & management (jcim) and competitive intelligence review (cir), two journals that in many ways are the predecessors of the journal of intelligence studies in business (jisib) (søilen, 2013). in agostino et al. (2013) we studied how both customers and vendors think about cloud solutions to bi. in søilen (2014) i did a spot check to see if the journal was writing about the topics that practitioners were concerned about, or interested in. the survey showed that jisib was more or less on the right track here, but that practitioners prefer case studies to empirical research articles, which the journal is now soliciting more actively and also publishing. good extensive cases are hard to obtain, but the journal has been publishing a number of empirical articles in the form of industry analysis connected to different countries around the world. in vriens & søilen (2014b) we show how the process of gathering intelligence for disruptive innovation is distinct from other forms of intelligence gathering. in søilen (2015) i try to show some problems that ci has had in the past; with agreeing upon clear definitions, but more fundamentally by clearly showing how the field is different from other disciplines studying information, like the more established journals in management and information systems. the study shows that respondents could not list any analysis that is not used by other areas of study and that a majority of the analyses the respondents think are unique to their own study actually come from the area of strategy and military intelligence. instead it is suggested in the article that what is different is that that intelligence studies bring a number of unique dimensions and perspectives to the social sciences, a new way of seeing and studying business which is an adaptation from military intelligence. in the next article (søilen, 2016) i suggest a research agenda for intelligence studies. i go deeper into the conclusion suggested in søilen (2015): it is suggested that the difference between information science in business, businessand market research and intelligence studies is mainly one of perspective and scope and less one about the content of problems or scientific methods used. intelligence studies in business see the organization much like an intelligence organization, the offspring of the study of state and military intelligence, where the aim is to find information that affect the business as a whole (as in “surrounding world analysis” or in swedish “omvärldsanalys”). a study of intelligence studies –management information or information sciences that does not explain what outside events affect the business becomes sterile and uninteresting. the essence of intelligence is to scan the world for relevant developments, to find out what is going on that effect our organization (need-to-know, strong signals, trends). how to do this should be the focus of the subjects’ research agenda and what sets it apart from other disciplines studying information in a business context. journal of intelligence studies in business vol. 8, no 3 (2018) p. 4-8 open access: freely available at: https://ojs.hh.se/ 5 sometimes this goal seems far away as when reading about how a new technique is applied to an industry in a specific market. sometimes i miss hearing about how basic methods like traveling to foreign countries (the spirit of marco polo) and reading books may be the best methods for understanding what affects an organization. we must always remember that the technology is only there to facilitate the process, it never explains why things happen and it seldom helps us in the actual understanding of the data. statistical analysis does not explain why or how things occur: at best it summarizes what has happened. authors of articles i read in other journals too often miss the difference between correlation and causation. what is then so special and different with intelligence studies? intelligence studies at the present at least are less a series of theories than a new perspective on (micro and macro) economics. intelligence studies is not exclusively about management, but also about economics as it’s just as relevant for how nation states become competitive. it is the suggestion that competitive organizations of all sizes are best organized as intelligence organizations, focusing on the process of gathering, analyzing and delivering need to know information to decision makers. this is a different way of looking at organizations and what they do. competitive organizations today all basically work with information. it is how they work with this information that decides whether or not they will succeed. the importance of building a formal intelligence organization was realized more than two hundred years ago in the military domain with the prussian and russian armies. in the study of business this was first realized with the shift in thinking that came with the information age and the development of computers, the realization that competitive advantage is more about what you know than what machinery you own or how much money you have in your accounts. if the introduction of it represented the 1.0 version of this development, then the introduction of the internet represents the 2.0. many saw this development coming. some experts thought that it would not only lead to intelligence studies being introduced as a special function in the organization but that we would see the implementation of separate departments of intelligence, or that the whole current division and structure of business activities, into marketing hrm, finance, would be abandoned for functions of intelligence gathering. when this did not materialize many started to question the value of the approach all together. many still think that the approach failed, that the perspective has passed and been surpassed by other subjects and disciplines. i disagree. even though things have not happened as quickly as many expected or hoped, we are still moving in that direction now more than ever. b2b digital marketing is a good example. today it is less about push marketing and sales and more about gathering and distributing valuable information to potential customers. when customers see that we are knowledgeable not only about our products but also about the industry we are in, they start to trust us and we are able to build a customer relationship. this is not only changing how b2b marketing is done, but also the competences needed to succeed in b2b marketing. on the state or macro level we are living in a period of (neo-) mercantilism and geoeconomics where intelligence is key. the states that are succeeding economically today are countries like china, singapore, and south korea, but also norway. these are representatives of state capitalism, not free market liberalism. the individualist, liberalist model supported by neoclassical economics and its foundation in the writing of adam smith (not always fairly interpreted, so i prefer to call them the marginalist school), walras, marshall and samuelsson, have greater difficulty convincing readers today. as piketty showed in his vast empirical project about capital, their (our) societies led to an extreme wealth being assembled at the very top with very little trickle-down effects. when the crises came it was the rest of society had to take the hit, while the elites bailed themselves out to save a dysfunctional system. after a period of prosperity, which lasted for some four generations (and was only extended during the past two generations through massive debt), the populations in the western world are experiencing a decline in their standard of living. these causes were all missed by the marginalist school whose members have been advising governments for more than half a century. the consequences of these policies have been massive protests and disbelief almost hatred of their own elites as in the us, but also in france, the uk and italy. the point is that our leading social science paradigms and especially our economic and 6 management theories that brought us here by not being relevant and, worse, by supporting the wrong policies; regardless of the good intentions, which many of my colleagues even doubt. mainstream economics combined with too narrowly and fragmented studies of management obsessed with a method of small empirical investigations have become the supporters, not only of an elite – the status quobut more worryingly of an uncompetitive society. now, for business studies that is almost what we should call a contradiction. our reigning business theories and research are making us less competitive. the new economic powers in the east have copied what has been done well in the west, but it is unlikely that they will copy our leading social science paradigm. it is the message china sends out when it says “…with chinese characteristics”. chinese leaders are following the thinking of drucker, schumpeter, and michael porter; more so than the winners of the nobel prize in economics and their schools of thinking. they are not reading our thousands of small business journals, even though their own scholars are taking a larger part in the work of running them and contributing to them. instead they are first and foremost inspired by their own values, their own history and their own thinkers of strategy and philosophy. china is already a superpower of intelligence gathering, which they see as essential for strategy. not only have our theories of political science been contested, but there is now clear critic of western moralism. there are hardly any independent thinkers outside the western world who believe in the good intentions of western political and economic interferences anymore. as we in the west have failed to keep up the living standard of our middle classes (our promise to the voters) “eastern arguments” are starting to convince a large part of our own populations in the west. the failure of the western world to compete becomes a confirmation of the weaknesses of our strategic thinking (the weakness in our political system to make plans), and in our ideas which at the end is a critic of our reigning social science projects. eastern ideas will be closer to practice. the west is left with a number of paradoxes. for all our interest in strategy during the past two decades we have no strategy, no long term thinking and no major infrastructural projects. instead we are consumed with our immediate problems and crisis handling. we are so obsessed with the critic of china as a dictatorship that we refuse to see that they are undertaking the largest infrastructural project in world history (the belt and road initiative, or bri), that their mercantilist ideas are engulfing our markets but also helping to improve the living standard of people living in the developing world. our media is full of stories about chinese exploitation in the developing world, which also exist, but forgetting that exploitation even slavery used to be our specialty for centuries and the hallmark of the british empire. now, what does this all mean for business studies? it means we have to search for other paradigms other than the existing one if we want to become competitive again. we have to become more interested in what is actually going on in the world, more curious. this reality must be led by business disciplines. some of the more successful university groups in intelligence studies today, like the gretha (le groupe de recherche en économie théorique et appliquée de l’université de bordeaux) at the university of bordeaux, have left the idea of theory building and focus instead on applications and being relevant for industry. as such they have also left much of the article-writing world of academia except as when recording what they have accomplished. the same thinking is well known in the development of new technology. focus is on application. if you have developed something truly new you will try to patent it or apply it. if you publish something valuable in a journal not only will very few read it, but it will also be copied, or stolen. this way of learning by doing is very much the chinese way of doing business, but also of studying business. if society is structured in this way then the experts will be in the practical field, less moved forward by research at the universities. this is already happening in some fields today, as in artificial intelligence (ai). the most respected experts in the field are found in large corporations, like google and facebook. another example is digital marketing. most academics are just running behind, trying to figure out what is happening. a number of social science scholars are reasoning in the same way: to have real impact (not academic impact, measured as a popularity contest among peers of articles and citations in google scholar) they try to go out and change the world. there are many research institutes that think 7 more like this now, particularly in the area of environmental studies, disillusioned by existing social science departments at the more established schools. one example is the iiiee in lund. at the end both developments are important (theory and practice), as we also need to teach new generations of students how to work with intelligence, but it must be based firmly in practice, it must be relevant and it cannot be too narrowly defined. this does not mean we cannot develop theories or focus on causations. i was reading one of the last books by herbert simon the other week, based on some lectures he had given. they reminded me of the last book by schumpeter “history of economic analysis”, published posthumously. both authors tried to explain how their ideas fitted with the evolutionary thinking of charles darwin, an attempt suggested earlier by the german historical school led by wilhelm roscher. a generation after roscher it also found support in the us for a short while, with torstein veblen (before it was picked up again many generations later by kenneth e boulding and others). they realized that a promising path for the social science was to connect to the theories of darwin, but a new superpower demanded a new scientific paradigm. so the attempts halted, except for a few satellites in germany (the international joseph a. schumpeter society) and england (g. m. hodgson). the historical school which was dominating in the 19th century, disappeared, basically i think because fellow economists stopped reading seminal books or even older articles, which are often in german and french. intelligence studies can continue to be relevant by helping organizations become more competitive. it can do this without developing theories. still i think that it can achieve much more by being more rigorous: defining variables, setting up axioms, hypotheses and discussing causations. for my own part, this led to my interest in combining intelligence studies not only with evolutionary theory, but with the disciplines of geopolitics and now geoeconomics. in the early 1990s i started to develop my own ideas of geoeconomics, based on observations of the chinese eclipse and western decline. it was followed by numerous travels and two stays in china, where i started to write the book “geoeconomics”, completed at stanford in 2012. this was done independently of luttwak who i read first much later, and before lorot. geoeconomics helps me understand intelligence studies on a macro level. in 2017 i published an article in jisib called “why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies”. the historical reasoning in the article basically comes from the same book. at the end of his wonderful book “history of management thought” witzel lines up present and future directions of management thinking. he talks first about what can be expected as asia surpasses the western world economically and he draws lines as to present directions of thinking: sustainability research, but also the information turn, starting with thinkers like toffler, who is also well known in the literature of intelligence studies. it is in this direction of the information turn that intelligence studies in business must be understood and placed, not as the primary venue, at least not at the present. that place has been occupied by the management of information systems (mis) literature with a handful of journals, but as an alternative approach, a niche built around another tradition of management: the organization as an information gathering organism. another established direction in management has focused on decision making. intelligence studies looks as the process that leads up to decisions as decisions can only be as good as the information at hand (ignored by the marginalists, as they typically assume full information) and the (bounded rational) mind that is used to process it. intelligence studies as a discipline today has two main directions, how to work with the process of information gathering (1) and how to set up an organization to fulfill that aim (2). the initial answers to both are the same, much like successful state and military intelligence organizations. the problem is that military organizations and businesses are different, so a direct application is not possible, just like a direct adaptation of geopolitics is not possible. the size and goals of the organizations are different, technology is different, but also in terms of the legal and ethical framework the two forms of intelligence operate within. this is what warrants two distinct and different disciplines. 8 today state intelligence services work less with economic questions but as the success of state capitalism spreads this is bound to change. already today state and military intelligence is learning from the private sector, less vice versa. looking back at more than three decades of studies in intelligence studies (with cir, jcim and jisib) we now have a “discipline” – formally in the sense that there is a catalog and archive for a new body of information produced by a scientific community. we also have a number of regular conferences dedicated to different forms of intelligence studies in business. some of the larger of these conferences are dominated by practitioners, which i rather see as a healthy sign (but i realize that my thinking here is contrary to that of most colleagues). it is a challenge for this small group of scholars to convince the world that the problems studied under the umbrella of intelligence studies in business (a term coined by sheila wright and arik johnson at the ici conference in bad nauheim in 2010) are worth undertaking. when work piles up like now before christmas, i like to think that stevan dedijer, one of the founders of intelligence studies (social intelligence, he called it), would have been pleased if he had lived today and saw how his ideas have evolved and multiplied. what is more fitting then, than to start with the largest bibliometric analysis that has been done on the field of intelligence studies authored by lópez-roble et al. it shows what areas of is are most popular, who the contributors have been and what their contributions have been. the paper by ojinagar is also an analysis of scientific contributions to the field of intelligence studies in business, but is narrower. it analyses 72 papers published in mexico between 2000 and 2015 on competitive intelligence. the paper by garcia-garcia and rodríguez presents another form of bibliometrics, called scientometrics. it’s an example of how scientometrics can be used to show the most influential authors and inter-institutional collaborations in a specific industry, namely additive manufacturing for hand orthoses. the paper by svarre and gaardboe is an analysis of business intelligence tasks, use and users in a workplace setting. the contribution by ottonicar et al. investigates how information literacy and competitive intelligence are connected in business management and information science fields. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. we hope to see as many as possible at the ici conference in luxembourg on may 5-7, 2019. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2018 jisib, halmstad university. all rights reserved. 14 competitive intelligence research: an investigation of trends in the literature a.s.a. du toit department of information science, university of pretoria, south africa e-mail: adeline.dutoit@up.ac.za received july 1, accepted september 5 2015 abstract: this article looked at competitive intelligence research reported from 1994 to 2014 in the abi/inform database to determine the development of competitive intelligence as subject field. this development can be attributed to several factors. content analysis was used to establish research patterns and the author based the analysis on the extant literature and on the 338 articles that were gathered from the abi/inform database. only peer-reviewed articles were analysed. the most popular term used in the literature is competitive intelligence, followed by business intelligence and marketing intelligence. the journals in which the articles appeared are scattered and few journals have published more than ten competitive intelligence articles. few authors have published more than five articles. keywords: academic subject field, competitive intelligence, research trends available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 2 (2015) 14-21 https://ojs.hh.se/ 15 introduction competitive intelligence is not a new business activity but it is a relatively new academic study field (de pelsmacker, muller, viviers, saayman, cuyvers & jagers 2005, 607). the definition of competitive intelligence is a complicated phenomenon. similar to many new study fields where coalescence around the domain and scope has not occurred, there are numerous definitions of competitive intelligence but no universal definition (pellissier & nenzhelele 2013). according to pellissier & nenzhelele (2013) a possible universal definition of competitive intelligence is: “a process or practice that produces and disseminates actionable intelligence by planning, ethically and legally collecting, processing and analysing information from and about the internal and external or competitive environment in order to help decision-makers in decision-making and to provide a competitive advantage to the enterprise.” with regard to the concept competitive intelligence, “it would seem that there is no commonly accepted term for referring to internal and external intelligence required for business decision-making. market (or marketing) intelligence, competitive intelligence, business intelligence and other terms are all used at various times to describe more or less the same concept” (venter & tustin 2009, 89). competitive intelligence is an interdisciplinary subject field (walker 1994, 271) and according to gabriel and adiele (2012, 27) competitive intelligence is also studied in business management, marketing management, knowledge management and strategic management. solberg-søilen (2010, 201) regards competitive intelligence as a subset of integrated marketing communications and viviers, saayman, muller and calof (2002, 27) say that competitive intelligence is a marketing discipline. according to calof and viviers (2001, 62) competitive intelligence is a subset of knowledge management. there is little known about the extent of competitive intelligence research and competitive intelligence as an academic study field. this article will look at the competitive intelligence peerreviewed articles reported from 1994 to 2014 in the abi/inform database. the research question, which is the major focus of this article, is: to what extent has competitive intelligence as an academic subject field developed over the past 20 years as reported in the abi/inform database? the rationale of the article is to provide a lens of the development of competitive intelligence as an academic study field over the past 20 years. insights would contribute to a generally under-researched body of competitive intelligence knowledge. the rationale of the article is to provide a lens of competitive intelligence research during a period of 20 years through which to appreciate the prevalence of competitive intelligence in economic and management sciences as it is reflected in the abi/inform database. contextualising competitive intelligence as subject field the field of intelligence originated 500 b.c and competitive intelligence originated from military intelligence (adidam, banerjee & shukla 2012, 243). according to powell and bradford (2000, 184) intelligence dates back more than 5 000 years and fourie (1999) regards porter’s work on strategic management and competitiveness as the main contributor to the development of competitive intelligence as an academic subject field. before 1980, competitive intelligence literature focused mainly on intelligence gathering for decision making and competitive intelligence as a formal function was only institutionalised as a formal function in the usa in the 1970s and 1980s (begg & du toit 2007). during the 1990s competitive intelligence grew fast but less attention was given to competitive analysis (du toit & muller 2005, 321). fleisher (2000, 14) states that the “ci boom of the last decade was driven by the increasingly widespread recognition that good information has a direct impact on the bottom line.” during the 1990s research was done 16 that present the watershed between strategic management and competitive intelligence. competitive intelligence is favoured at the expense of strategic management as a subject field and has evolved over the years as a result of the need for enterprises to scan the complex external environment. according to prescott (1999, 41) the research emphasis is nowadays on the strategic implications of competitive intelligence. as discussed in the previous paragraphs, competitive intelligence has traditionally been associated with strategic management and knowledge management (calof & viviers 2001, 62) but is nowadays a relatively new academic study field. competitive intelligence is regarded as the crux of strategic management at an enterprise and enterprises that excel have competitive intelligence as a formal function in their enterprises. the key issues with regard to competitive intelligence research today are the development of intelligence infrastructures for multinational enterprises and the use of social network analysis for intelligence purposes. competitive intelligence is a process comprising the following activities (viviers, saayman & muller 2005, 578-580) – known as the competitive intelligence cycle:  planning the collection of information according to key intelligence needs.  collection of information from a variety of sources.  using analytical tools to analyse the information.  packaging of information and communicating it to management. some sceptics (for example weiss 2011) argue that since the late 1990’s only a handful of worthwhile competitive intelligence books have been published. despite its growing popularity dissenting views still linger today. weiss (2011) argues that the potential contribution of competitive intelligence is often oversold. the other criticisms of competitive intelligence are as follows:  it is difficult to quantify the direct effect of competitive intelligence in an enterprise (kahaner 1996, 230), since measuring the benefits of competitive intelligence is more qualitative than quantitative (industry canada 2006, 25).  the effect that competitive intelligence has on an organisation is indirect (kahaner 1996, 230). according to prescott (1999, 39), the academic literature of strategic management did not have any impact on the development of competitive intelligence as subject field. the unprecedented growth of competitive intelligence in the last twenty years may be attributed to several factors such as:  the complexity of the external environment (hitt, ireland & hoskinsson 2000, 208).  recognition that information has an impact on the success of enterprises (fleisher 2000, 14).  the increase in the pace of business (kahaner 1996, 28).  the increase on the availability of information due to the development of information technology (kahaner 1996, 29).  an increase in global competition (fleisher & blenkhorn 2001, 25).  an increase in the aggressiveness of competition (kahaner 1996, 31).  recognition that competitive intelligence is an essential ingredient of effective management (shaker & gembicki 1999, 18).  the need for a competitive strategy (west 2001, 28). competitive intelligence research has grown in prominence in the last twenty years suggesting that competitive intelligence is a separate function in an 17 enterprise and a separate subject field (adidam, gojre & kejriwal 2009, 669; calof & skinner 1999, 20; fleisher & bensoussan 2007; kὒhn 2012). competitive intelligence has value to all the business activities of an enterprise and the major attraction of competitive intelligence is that it provides actionable foresight regarding competitive dynamics (prescott 1999, 42). since competitive intelligence is an interdisciplinary subject field, competitive intelligence professionals usually have a variety of educational backgrounds and many do have postgraduate degrees (sewdass & du toit 2014, 187). when these professionals complete a masters or doctoral degree, they usually publish an article on the research conducted and valuable competitive intelligence literature can be found in the relevant dissertations and theses. content analysis of competitive intelligence articles published in the abi/inform database 1995-2014 to answer the research question, the author examined peer-reviewed competitive intelligence articles in the database abi/inform published between 1995 and 2014 and considered the following terms: business intelligence, competitive intelligence, competitor intelligence, marketing intelligence, strategic intelligence and technological intelligence. these terms were published in the title or abstract or subject fields of abi/inform. pendlebury (2010) recommends that when determining the research impact of a subject field, at least five years of research published in publications, should be analysed. content analysis of the articles was used to establish research patterns of the subject field competitive intelligence (harrison & reilly 2011, 10). only peer-reviewed journals were analysed, and not monographs and other vehicles of scholarly communication, since it is agreed that scientific journals publish a significant portion of scientific knowledge in a subject field (bryman 2006, 115). according to creswell and garrett (2008, 323) peerreviewed articles are one of the indicators to measure the extent of growth in a subject field. the term competitive intelligence yielded 11444 references, but the majority of these items were news items and not peer-reviewed articles. a total number of 338 peer-reviewed articles were retrieved. with regard to the term business intelligence, it should be noted that only the articles focusing on the gathering of external information were included. table 1 lists the terms and the number of articles retrieved for the period. concept number of articles competitive intelligence 255 business intelligence 44 marketing intelligence 27 strategic intelligence 5 technological intelligence 4 competitor intelligence 3 total number of articles 338 table 1: articles retrieved from abi/inform for the period 1995-2014 using selected terms according to table 1 the most popular term used in the literature is indeed competitive intelligence, followed by business intelligence and marketing intelligence. the terms competitor intelligence and technological intelligence are not much used in the literature. this indicates competitor intelligence’s fall from usage in the favour of competitive intelligence. the research findings showed that the majority of the published articles (72%) used a descriptive research methodology, followed by case studies (9%). this correlates with the statement by saayman, pienaar, de pelsmacker, viviers, cuyvers, muller and jegers (2008, 384) that competitive intelligence articles are mainly descriptive in nature and that few empirical surveys were published. according to knupfer and mclellan (1996, 1198), descriptive research describes a particular issue or phenomenon and usually answered the what if question. 18 the 338 articles were published in 122 journals which indicated the interdisciplinary nature of the subject field. to emphasized this fact, the journals in which the articles appeared are scattered and are as diverse as global cosmetic industry, internal auditor, journal of legal studies education, journal of manufacturing technology management, journal of medical marketing, journal of social, political, and economic studies, journal of workplace learning, logistics information management, medical marketing and media, mergers and acquisitions, pharmaceutical executive, security management, supply chain management review, team performance management and tqm magazine. table 2 lists the journals containing five or more articles retrieved using all of the six related terms mentioned earlier: journal of intelligence studies in business 38 marketing intelligence & planning 13 south african journal of information management 10 european journal of marketing 7 aslib proceedings 5 interdisciplinary journal of contemporary research in business 5 searcher 5 table 2: journals with five or more competitive intelligence and related articles retrieved from abi/inform for 1995-2014 according to table 2, a very small number of journals (only three) published a high percentage of competitive intelligence articles and only two journals (journal of intelligence studies in business and marketing intelligence & planning) focused exclusively on the publication of intelligence articles. competitive intelligence literature is this very much scattered and published in dozens of journals. competitive intelligence practitioners are very busy and do not write about what they do. the most prolific writers are academics teaching competitive intelligence at institutions of higher education such as j.l. calof, j.e. prescott, a.s.a du toit, s. wright and w. viviers (see table 3). this confirms solberg søilen’s (2014, 62) statement that most users of jisib are academics and researchers. of the 338 articles published, 130 were written by single authors. most of the authors only published one article on competitive intelligence. as indicated in table 3, more than 90% of the authors wrote fewer than five articles. author number of articles calof, j.l. 20 prescott, j.e. 17 du toit, a.s.a. 16 wright, s. 13 solberg søilen, k 11 viviers, w. 11 fleisher, c.s. 10 dou, h. 9 muller, m-l. 9 martin, s. 9 wheaton, k. 8 mcgonagle, j.j. 8 gilad, b. 6 herring, j.p. 6 saayman, a. 6 sewdass, n. 5 pellissier, r. 5 table 3: authors with five or more competitive intelligence articles as retrieved from abi/inform for the period 1995-2014 an analysis of the authorship showed that 43.7% of the most prolific authors were from the united states, 37.5% were from south africa, 12.5% were from canada and 6.3% from france. the impact of research and a peer-reviewed article is often measured by the number of citations it received. google scholar citations were therefore used to determine the impact of the authors mentioned in table 3 on the development of competitive intelligence as subject field. unfortunately the number of citations of the peerreviewed articles of the following authors could not be determined: j.l. calof, w. viviers, m.l. muller, s. martin, k. wheaton, j.j. mcgonagle, b. gilad, j.p. herring, a. saayman and r. pellissier since they do not use google scholar citations. table 4 gives the number of citations of articles by eight authors. 19 table 4 also includes the h-index, which is an indicator of the impact of the publications of an author. author number of citations h-index j.e. prescott 6784 32 s. martin 4599 29 c.s. fleisher 2047 22 h. dou 1421 16 a.s.a. du toit 789 12 s. wright 772 13 k. solberg søilen 161 6 n. sewdass 25 3 table 4: number of citations of peer-reviewed articles according to table 4, the authors with the most impact on the development of competitive intelligence as subject field are j.e. prescott, s. martin and c.s. fleisher. median is the value above and below around which half of all observations fall. it is a measure of the central location, and it is based on the whole distribution of a variable and not affected by extreme values (diamantopoulose & schlegelmich 2000, 95). according to table 5, the median number of pages per article for the terms strategic intelligence, competitor intelligence, technological intelligence, marketing intelligence and business intelligence are much higher than for competitive intelligence. academics are the authors who write longer articles. terms median number of pages per article strategic intelligence 16 competitor intelligence 15 technological intelligence 12 marketing intelligence 8 business intelligence 7 competitive intelligence 5 table 5: median number of pages for articles retrieved from abi/inform for 1995-2014 conclusion this article reviewed competitive intelligence peerreviewed articles published in the abi/inform database from 1995 to 2014 to determine the extent competitive intelligence has developed as an academic subject field. the domain of competitive intelligence is broad and competitive intelligence is an interdisciplinary subject field. the articles published are mainly descriptive in nature, followed by case studies and few empirical studies were published. most of the competitive intelligence articles are published by individual competitive intelligence professionals. few authors have published more than five articles and few journals have published more than ten competitive intelligence articles. content analysis was used to establish research patterns and the author based her analysis on the extant literature and on the 338 articles that were gathered. content analysis is not without pitfalls and the research could have benefited from a triangulation of research methods. for example, interviews with the 17 authors who have published more than five articles might have provided insights that have been obscured by content analysis. the interviews might have revealed a deeper understanding of trends in competitive intelligence research. this limitation of the research is an opportunity for further research. competitive intelligence as subject field deals with relativistic, complex and dynamic social constructs that influence a variety of contexts. more empirical surveys published in peer-reviewed journals provide the possibility to best understand and make assumptions about the complex problems of competitive intelligence as subject field. this will enable competitive intelligence researchers to address all the facets of the complex problems they investigate and will provide a potential for theory 20 building since existing theories may not sufficiently provide a framework to understand, explain and predict the new developments in a unique context. references adidam, p.t., gajre, s. & kejriwal, s. 2009. crosscultural competitive intelligence strategies. marketing intelligence & planning 27(5): 666680. adidan, p.t., banerjee, m. & shukla, p. 2012. competitive intelligence and firm’s performance in emerging markets: an exploratory study in india. journal of business & industrial marketing 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aware online magazine. available http://www.quora.com [accessed 17 august 2014]. west, c. 2001. competitive intelligence. new york: palgrave. http://dx.doi.org/10.4102/sajim.v15i2.559 http://www.quora.com/ 35 foundations of competitive intelligence system to form business coalitions olivier mamawi lara / icd 12, rue alexandre parodi, 75010 paris, france omamavi@gmail.com received june 3, revised form 10 september, accepted 22 september 2012 abstract: this study shows how a business can identify the networks allowing to form coalitions to obtain french procurement contracts. to this end, we have represented, by a graph, the 2008 co-branding system. we have detected, in this graph, 1360 strategic networks of which the organization reveals, on the one hand, identical characteristics within business networks, and on the other hand, the role of the dominant parties as to access to industrial labor. from these results, we propose a network cartography allowing us to consider new applications for competitive intelligence. keywords: coalitions, competitive intelligence, procurement contracts, cartography, network analysis. 1. introduction french state procurement contracts, regional authorities and public corporation contracts add up to over 80 billion euros per year. to ease the way for small and medium-sized companies, the reform of the french state procurement code, initiated in january 2006 and applicable since january 2008, encourages responses to invitation to tender through co-transaction. co-transacting is the process by which tendering companies can ally with a group of companies, to tender a collective offer when they cannot, on their own, assume the necessary competences and resources. effectively, co-transacting means forming coalitions, that is to say, “temporary alliances, which are devised, if not negotiated, amongst those who participate” (lemieux, 1998). but organizing a coalition, to share or to distribute resources to respond to the needs of a project, is not easy for companies with sometimes different interests; so, how can a company analyze its (complex) environment to form a coalition and obtain markets? we begin with the following assumptions: the network is a business structure, and the coalition is a specific structure of the network. we present as the main hypothesis that a coalition is formed according to the structure of relations. in consequence, we consider that a company must be able to interpret its strategic environment as to find good partners, and to understand how the structure of interactions determines the formation of the coalition. available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 35-41 mailto:omamavi@gmail.com https://ojs.hh.se/ 36 the management science literature has shown a lot of interest in network alliances. but, studies on the networks, up to now, have mostly looked into the reasons linked to their formation than an understanding of the inter-organizational relations that they imply. the developments surrounding control (piloting) of the networks have been, for the most part, treated as annexes to more general problematic, essentially economic, sociological and strategic (gulati & nohria, 2000). the aim of this communication is to suggest a new perspective concerning non-cooperative projects (yi & shin, 2000), mainly reached through operational research. the issue today is to go beyond the limits of game theory, to aim for an actors theory (massé et al., 2000).to this aim, we wish to suggest the basis of a competitive intelligence system which will permit a reticular perspective of the strategy, keeping in account the complex environment (that's to say interactive and dynamic). we will attempt, in a first stage, to present the theoretical basis of emerging networks within the markets. then, we will explain the method used to encapsulate and study numerous alliance relationships. finally, we will discuss the results obtained through a cartography that enables to localize partners of strategic networks. 2. contributions of economic sociology interorganizational relationships can be considered as “a coordinated system of heterogeneous parties, developing transactions founded on a cooperational relationship, as to collectively pursue a shared aim” (voisin et al., 2004). this system is the result of a process within which the partners bond to exact a mutual benefit. that is to say, a network of parties which is subjected to business circles, and forced to define a balance with its environment. as defined by assens (assens, 2003), the concept of a network puts forward the inter-connection of parties able to participate in exchanges. the link between the parties gives the nature of the exchanges, their periodicity, their strength, their density. the parties hold positions that are apt to evolve, but that testify to a role or a function held in face of the other parties. to understand the frame of a network, many authors (calon, 1989), (cohendet & diani, 2003), prefer the study of relationships between members, rather than a focus on the nature of the parties themselves. they thus judge an approach to networking as a form of transitional organization, of a hybrid tendency, between the market and the hierarchy (williamson, 1985). which is why granovetter (granovetter, 1985) considers that the functioning of a market depends on business conditions. he thus shares, with other protagonists of economic sociology (white, 1981; baker, 1984), the conviction that economic action is a social action, led by various motivations: sociability, recognition, social status and power. to prove the integration of economic actions within business relation systems granovetter (granovetter, 1985) suggests the concept of “embeddedness”. he makes a point of proving that business relations and institutions allow a market to function. a relation is then distinguished by its content (the exchange of a resource), its direction and its strength (level of exchange). by the same perspective, interorganizational relationships can be considered as a means to control environment uncertainty accessing complementary resources. the rating of a company becomes clear when examining the relations network into which it is encompassed. this “strategic network” (gulati & nohria, 2000) relates to all the links held with partners, whether clients, suppliers, competitors or subcontractors. as such, preference goes to working with a particular partner, depending on the level of interactions, sufficient to obtain an optimal transaction, through optimal human links rather than economic ones (voisin et al., 2004). parties using “strong links” (granovetter, 1985) imply frequent contacts, a supply of reciprocal services, and this justifies a sharing of resources. with this approach, the social relationship helps regulate opportunistic behavior, ensures data sharing, and facilitates collective solutions to problems. uzzi (1996) has shown that a relationship based on trust can enhance company advantages (shared risk, ability to react to markets changes, organizational apprenticeship), that purely commercial relationships cannot offer. and as explained by gulati and singh (gulati & singh, 1998), the economic parties tend to exchange, in priority, with known parties, to diminish uncertainty linked to transactions. when a party knowingly mobilizes its network to follow a given strategy, trust becomes a resource of the network, that allows to save on the transaction costs (williamson, 1985), to share resources (richardson, 1972), to reduce measures of control or incitement (gérard, 2000), to avoid asymmetrical data amongst partners (akerlof, 1970), to contain opportunistic attitudes (olson, 1971). as such, one of the main aims of studies on networks was to put to light the cohesion within members as a means to access, share or control resources. beyond opportunistic explanations, linked notably to proximity (geographical or social), two main principles can explain the formation of links and interactions (lin et al., 2001). when parties have the same level of resources and that they are moved by recognition, exchange or protection of their 37 business status, we speak of homophile interactions. in this case, the aim of links is to maintain a level of resources. when, on the contrary, the hierarchical levels are different, and the actions are motivated by the need to obtain better or supplementary resources, this becomes heterophile interactions. in a more general way, parties interact with other parties because they seek backing or safety which allows them to control their turbulent environment, and find a certain stability. this search for control gives rise to regularities (relationships) which form the basis of business networks. the structure of these regularities can be identified. it's the principal of structural equivalence (white, 2001). as reminded by grosseti and godard (2007), two entities are structurally equivalent, within a network, if they occupy the same place or the same position, that is to say, if they have the same trade relations (or relatively similar relations) with given parties. the notion of structural equivalence thus allows to return to the classic notion of a role (or of position), but from a purely structural point of view, through a network analysis, without conjecturing on the weight of these roles. 3. analysis social network analysis considers society as a system of business parties linked by relationships. it is an adapted method to understand and formalize complex phenomenon calling for an interactive system of relations. as such, this method allows to describe, and reconstruct, a network, in a simplified way by a graph. the graph represents the interactions between objects related by links. the development of a quantitative method, originally issuing from sociometry and completed by the help of the theory of graphs, allows today to put forward a set of properties which form a changeable topology. for network analysis (borgatti et al., 2009), three main dimensions (table 1) can be used. the first aims to identify the networks and to describe the manner in which the structures of these networks can burden the members. the connectivity is an indicator which allows to define the limit of the network in a chart. there is a network if there is always a link between two summits of the whole. a network is thus a related component of a graph. the second dimension enables to identify the position, more or less dominant, of a party in the network. it can be assessed through centrality as defined by freeman (1979). the degree of centrality shows the popularity of a party within the network, that is to say, the number of direct connections of one company with the others. the centrality of proximity identifies the companies closest to the sources of power and influence, that is to say, swiftly reached by the other members of the network. the third dimension aims to define the cohesion of homogeneous groups within the network, to analyze structural similarities of the network. 2 parties are thus structurally equivalent if they have identical relationships with the other parties of the network (white, 1981). partitioning techniques allow to detect groups of parties of structural equivalence (navarro & cazabet, 2011). 4. methodology to analyze business networks, we have chosen to study the responses, through co-transacting, to invitation to tender in french public markets. our study is based on the analysis of coalition relationships within company groups. let's be reminded that invitation to tender procedures find themselves in a system aiming to enhance the transparency of deals within the two categories of contributors. the contractors, meaning with the power to adjudicate, can be: the state (ministries), territorial collectivities (administrative districts, departments, regions), public establishments linked to the state and to collectivities, public establishments outside of a business and/or commercial character (universities, schools, certain museums, etc.). the companies making an offer are “submitters”. data used for this study issues from the attribution notices from of the french official journals (boamp). the french official journals publishes the transactions attributed by a french public guarantor, for market sums above €4.000 before tax. from transactions made in 2008, we have selected, with key words, the transactions held only by groups of companies. table 2 details the census of the observed businesses. it shows the number of parties that we identified within the groups. 38 obtaining this data goes through a multi-stage process: extraction, cleaning, filtering, formatting, dedoubling and indexing. the nature of the data used to analyze the groups of companies is held by three variables. the first is allotted to the identification of the parties (business reasons). the second is ascribed to the type of beneficiaries of the transactions (company groups). the third variable concerns the cooperative relation which links the parties within a group. we have considered that there is a cooperative relationship with two companies when they obtain a market within the bounds of co-transaction (a belonging to a group of companies). 5. results we have organized the relational data in the form of a list of adjacency. the list sets out, for each company, all the companies close to it. then, we used the software graphviz (www.graphviz.org is a series of open source tools created by the research labs of at&t, which allow to represent and analyze graphs) to obtain a complete graph of the cooperation relations within the french public market in 2008. the graph highlights numerous sub-graphs (related components) within which there exists a link between any two clusters. these sub-graphs are strategic networks. the graph is composed of 1360 strategic networks having between 2 and 2233 clusters. figure 1 represents the repartition of strategic networks according to their size. the visualization of the complete graph shows company aggregates which correspond to a concentration of links over a limited amount of companies. figure 1: network distribution according to size to understand the manner by which the strategic networks are constituted, we have isolated them. an in-depth study of the largest strategic network allows to produce a number of indicators on the structure of relations:  global density of the graph is low (0,0004). it reports the number of existing links and the the number of possible links;  local density, or clustering coefficient, is high (0,47). it corresponds to the probability of two close members of a same party being linked;  the average distance between two companies is 6,45. this distance corresponds to the length of relationship links between random members of the network. to evaluate the position of parties within the largest related component, we have measured degree centrality. the distribution of degrees (figure 2), that is to say the number of connections a company has in the network, is heterogeneous. the majority of companies have a low degree, and only few companies have a strong degree. put more clearly, we are close to the zipf-paretto law by which 20% of companies attract and generate 80% of network links. these companies are shown up statistically, but also visually in the graph. figure 2: distribution of degrees within the network 6. discussion the analysis of the largest strategic network in french public markets reveals non-trivial characteristics common to other business networks, such as: acknowledgment networks (two individuals are related if they know each other), physical contact networks (two individuals are related if they have been in physical contact), collaboration networks (two individuals are related if they have worked together), exchange networks (two entities are related if they have exchanged for example an email). as such, the great business networks all possess a low global density, a strong local density, shortcuts to the summits, a http://www.graphviz.org/ 39 heterogeneity of degrees and a low average degree. these characteristics are generally attributed to graphs of a large field (strogatz, 2001), in reference to the “small world” in the experience of travers and milgram (travers & milgram, 1969). these characteristics thus compose a organizational model of inter-organizational networks. furthermore, the distribution of degrees within the network highlights the existence of zones more densely connected than others. these zones correspond to groups of companies more strongly connected to each other than to others. they correspond to an entity of companies with common points and between which the links are naturally stronger. from a more general point of view, the complete graph of the co-joining of companies to a group of companies shows us a number of indicators to describe the phenomena of strategic networks within the public markets. but, to profit from these indicators, we need to determine, on an ongoing basis, the position occupied by each company, to understand its role and importance, or which are the affinities allowing a company to acquire or keep a central position in the network. this purpose renders the use of cartography essential. the cartography stems from the graph of each company with its alliance relationships. the chart represents the strategic space within which influences are played out, and the topology allows to classify the companies according to their relationship proprieties. cartography then becomes a reticular lay-out, representing business interactions in the public markets. this lay-out is a space in which the parties communicate information and interact with each other. in fino, the main asset of cartography is its ability to analyze, on an ongoing basis, transactions and relationships within the public markets. this network analysis allows to:  represent the companies and their relationships,  navigate through the company networks,  identify the position of each company on the market,  measure the strength of the links (affinities) amongst the companies,  determine the role and the status of each company. from this network cartography, we can recognize and act on the strategic environment of a company, and use it as tool of competitive intelligence. in effect, competitive intelligence can be considered as a process with the aim of reducing the part of uncertainty in the taking of any strategic decision (revellic, 1998). so, to be intelligent is the ability to find a solution in a complex environment (massé et al., 2006). this corresponds to the capacity of absorption (zahra & george, 2002) of information to a strategic end, that is to say to its acquisition, its assimilation, its processing and its development. 7. conclusion and future research this study, carried out through data issued by the french official journals (boamp), is an analysis of french public markets throughout 2008. thus, from 54.181 transactions carried out between the contractors and the submitting companies, we were able to observe 4.203 transactions undertaken by coalition companies. the growth of these transactions, with relational information, allowed us to set up a structural analysis. from this, we constitute a data basis on interorganizational relationships. the main contribution of this study is to offer a framework of strategic network analysis within public markets. we set up a cartography giving a graphic representation of alliance networks. it eases their visualization and reveals non-trivial characteristics common to other business networks. but the aim of this study is to propose the basis of an competitive intelligence system. for competitive intelligence can be considered as a process aiming to reduce the uncertainty factor in the taking of any strategic decision (moinet, 2011). the aim, then, would be to provide companies a system of new links references, to help them form coalitions within public markets. to devise an competitive intelligence system, we need to keep in account that networks are where business interactions are made and undone. they can evolve, but also disappear. so we must keep on with this study. to this end, our perspective is to follow up, in a dynamic way, the evolutions and movements of network alliances within public markets over a period of several years. the longitudinal study will try to put forth the emergence and the evolution of strategic networks within public markets. the analysis will be based on the way in which businesses link themselves up and would use the preferential attachment concept described by barabasi and albert (1999). then, the approach that we are considering, the building a system of recommended links would be the following: through a longitudinal study over several years, we would be able to predict new emerging links, which will connect the companies already present in the networks, but which had never been linked previously. supervised training 40 techniques (benchettara et al., 2011) could, then, be applied to build a prediction pattern of new links within the networks to help businesses form winning coalitions. making the decision to form a coalition within public markets means constructing a particular structure of links within a complex system of relations. building a coalition can be considered as a plan of strategic decisions, in which the parties (the companies) can group to obtain earnings (transactions) through their choices (temporary alliances) and keep within the rules (implicit or explicit) which frame or curb their their performances. the earnings depend upon the decisions of parties exterior to the plan, and of which the distribution does not respond to a known probabilist law (uncertain environment). this decision will be defined by the taking into 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reconceptualization, and extension.” academy of management review 27 (2): 185–203. 1. article jisib 2012 version publiée 32 multiversion document warehouse: an approach to multidimensional analysis kaïs khrouf*, jamel feki*, chantal soulé-dupuy** * mir@cl laboratory university of sfax tunisia, ** irit university of toulouse i – france received 15 december 2010; received in revised form 2 march 2012; accepted 27 april 2012 abstract: document warehouses allow the storage of selected and filtered heterogeneous documents, as well as their exploitation through multidimensional analyses techniques. however, the content of documents is dynamic and changes across time. in practice, decisional analysts may be interested with various versions of documents. thus, the document warehouse should store and manage these versions. this paper presents an extended generic model for document warehouses allowing the management of the multiversion documents. in addition, it interests with multidimensional analysis on documents versions. keywords: document warehouse, multiversion documents, multidimensional analyses 1. introduction nowadays, internet allows an exponential evolution of data volumes stored and exchanged among organizations. these evolutions raise new problems: how to deal with changes undergone by documents? what are these changes and how to detect them? for instance, a user revisiting a document might want to be informed of the document changes since his last visit. in order to maintain various versions of the same warehoused document, we need the concept of document warehouse. the author of (khrouf & soulé-dupuy, 2004) defined the document warehouse as a source of information that is subject-oriented, filtered, integrated, archived (versions), and organized for a process of retrieval, interrogation or analysis. according to this definition, documents integrated in the warehouse could be historized (i.e., retain their evolution over time through different versions). in order to reach this objective, we propose an extension for the document warehouse meta-model defined in (khrouf, feki and soulédupuy, 2011). this extension is expected to manage content changes (i.e., when the document content is modified) and structural changes (i.e., when the document structure changes) that can undergo one document or class of documents. the extended meta-model allows applying techniques of multidimensional analyses on multiversion documents. we distinguish two types of analysis: i) multiversion analysis, i.e., analysis covering all versions for the same document, and ii) recent-version analysis; i.e., analysis relying on the last version of document(s). available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 32-40 33 this paper deals with the problematic of multiversion document warehouse; it is organized as follows. in section 2 we outline some works devoted to the management of multiversion documents. in section 3, we propose an extended meta-model for document warehouse and, in sections 4 to 6 we detail our approach of multidimensional analyses on multiversion documents integrated in the warehouse. finally, we give an overview of our software prototype baptized docware (document warehouse). 2. related works for the management of multiversion documents, several theoretical works have been proposed in the literature; furthermore, software prototypes have emerged. nicolle, alvarez & amghar (2001) consider that the document is a set of independent fragments (parts). they distinguish two types of versions: a document version and a fragment version. in fact, the modification of certain document fragments creates new versions of fragments, and therefore a new version of the whole document. xydiff (cobéna abiteboul & marian, 2002) is a component of xylème (abiteboul, cluet, ferran & rousset, 2002) to manage different versions of a document. every modified item is represented as an xml file, stored in a data warehouse and indexed. these files are used thereafter to reconstruct previous versions of documents. xydiff uses the tree structure of xml documents in order to detect movements and changes taking place on a document. x-diff (wang, dewitt & cai, 2003) is an algorithm for integrating the characteristics of xml structures with standard techniques of tree comparison in order to calculate the differences between two versions of an xml document. the main feature of this algorithm is that xml documents are modeled by unordered tree structures, unlike the work of xydiff. rusu, rahayu & taniar (2006) propose an approach for extracting rules from the changes of version of dynamic xml documents. specifically, the authors propose an algorithm that studies the conduct of versions of xml documents in time and thus determines learning rules to predict document changes in the future. in our work, we are interested not only in the management of document versions (track and detect changes of the document evolution through time), but also for managing the versions of the collections of documents (set of documents gathered in the same class). in addition, we develop a multidimensional analysis approach for these multiversion documents. 3. meta-model for document warehouses 3.1 meta-model description the document warehouse should store pertinent documents in order to apply the multidimensional analyse on these documents; in addition, it should be able to manage the heterogeneity and support the evolution of structures and contents. to do so, we propose the meta-model of figure 1. figure 1: meta-model for multiversion document warehouses specific structures (c) 1..* 1..* associate 1 1..* 1..* 1 1..* genelt namege cardge versgenelt datevge versspeelt datevse information content genatt namega speattc namesa valuesa include s_include define 0..* 0..* generic structures (b) documents (a) 0..* 0..* s_compose1 compose 0..1 contain {ordre} {order} {order} itsgenstr 1..* documents namedoc content (d) {order} 1 ontologies (e) 1..* 1 1 ontologies nameont concept namecpt belong 0..* s_concept assign0..* 0..1 1..* 1 genstr namegs versgenstr datevgs versdoc datevdoc 1..* itsdoc 1 1..* itsversgenstr 34 this metadata includes the following components: •a set of documents (figure 1.a) to be integrated in the document warehouse and their different versions (figure 1.a). •the hierarchical structure of documents. it is made up of two types of structures: i. the generic structure (figure 1.b): it is a common structure for a document set. it is composed of a set of versions each of which is defined by a set of versions of generic elements which can be composed of other versions of generic elements. each of these elements can also be described by generic attributes for example book-id. ii. the specific structure (figure 1.c): it is associated to a single document and has to be compliant/identical to one among the existing versions of generic structures. this structure is defined by a set of versions of specific elements that can include specific attributes. •the content (figure 1.d) is the textual element of the specific structure. •the semantic layer (figure 1.e) is defined using domain ontologies. in our context, ontology is composed of a set of concepts hierarchically organized where each leave concept is described by a set of keywords. 3.2 example figure 2 depicts a simple instantiation example for our meta-model of figure 1. in this example, we manage three versions of the same document doc1: •doc1 is initially compliant to version1 of the generic structure article composed of title and content. •after changes made on the content element, doc1 belongs now to the new version2 of article. •after renaming the content element to section composed of two paragraphs (i.e., dimension and fact), the new version of doc1 is becoming conform to version3 of the generic structure article. figure 2: an instantiation example for the meta-model in figure 1. <article> <title>dw</title> <content> dss … </content> </article> doc1 version1 <article> <title>dw</title> <content> olap … </content> </article> doc1 version2 v1 article v1 title v1 content doc1 v2v1 v2 article v2 content dw dss… olap… <article> <title>dw</title> <section> <p> dimension… </p> <p> fact… </p> </section> </article> doc1 version3 v3 v3 article v1 section v1 p v1 p dimension… fact… discovery knowledge data mining olap design kw11 ... kw22 kw23 ... kw12 ... data warehouse kw11 ... 35 3.3 meta-model advantages the meta-model we proposed has the following advantages: •grouping heterogeneous documents having identical or similar structures into classes. this relies on an algorithm for comparing labeled tree structures (ben messaoud, feki, khrouf & zurfluh, 2011) •storing various versions of documents due to evolutions. •adding up of semantics to the documents by linking the textual content to the concepts of domain-ontologies (ben meftah, khrouf, feki, ben kraiem & soulé-dupuy, 2011). •applying multidimensional techniques on documentary information. this feature will be detailed in section four. 3.4 meta-model implementation as shown in figure 1, the meta-model is designed using the unified modeling language (uml) object-oriented modeling. the meta-model implementation is carried out in an object relational dbms (oracle 10g). to ensure this translation, we have used the following transformation rules: •classes are transformed into tables. •for one-to-many relationships implementation, we have two alternatives: use one mono-valuated link or one multi-valued link in the opposite direction. we opted for the mono-valuated link as they facilitate the generation phase of views necessary for the multidimensional analyses. example 1 •we implement many-to-many relationships using multi-valuated links, specifically by using a list of references as nested tables. example 2 •for inheritance, we opted for mono-valued links from subclasses to super-classes in order to separate the two structures, generic and specific. figure 3: the navigational diagram of the proposed meta-model in figure 1 versdoc versgenstr id_doc datedoc itsvgs id_vgs datevgs 319 04/02/2012 17 01/02/2012 716 05/04/2012 24 05/04/2012 1426 14/05/2012 versgenstr versgenelt id_vgs datevgs itsvge id_vge datevgs 17 01/02/2012 67 01/02/2012 68 01/02/2012 24 05/04/2012 85 05/04/2012 inheritge itsgenstr specific structures (c) associate genelt id_ge namege cardge versgenelt id_vge datevge versspeelt id_vse datevse information id_cont content genatt id_ga namega speattc id_sa namesa valuesa include s_include generic structures (b) documents (a) s_compose compose contain documents id_doc namedoc content (d) ontologies (e) ontologies id_ont nameont concept id_cpt namecpt belong s_concept assign genstr id_gs namegs versgenstr id_vgs datevgs versdoc id_vdoc datevdoc itsdoc itsversgenstr inheritega inheritevge define 36 3.5 meta-model instantiation the integration of a document into the warehouse is accomplished through the three following steps: i. extraction of the specific structure for the document by using a parser; it includes the document tags and its hierarchical structure. ii. comparison of the specific structure of the document with the generic structures stored in the warehouse. this step is accomplished through an algorithm which calculates a similarity degree to compare labeled tree structures (ben messaoud, feki, khrouf & zurfluh, 2011). iii. insertion of the document content, information and list of keywords into the warehouse while linking the textual information to one or more concepts that also are characterized by keywords. we use the information retrieval techniques to perform this step (reference). 4. multidimensional analyses the document warehouse is intended to allow decision-making. to do so, we adopt the multidimensional model (kimball & ross, 2002) that considers an analyzed subject as a point within a space having several dimensions. this model relies on the concepts of fact and dimension. the fact represents the subject to be analyzed as the number of articles and, the dimensions represent the context of recording the fact such as author, publication year and conference. dimensions are made up of attributes organized, from the finest to the greatest granularity, into hierarchies. figure 3 describes our proposed multidimensional process to analyze textual information stored in the document warehouse. figure 4: multidimensional analysis process in following section, we detail the first two phases of this process. 5. phase 1: construction of the document mart schema let us remember that a generic structure gathers a set of documents having identical or similar structures. the decision makers can focus on a generic structure to perform his/her analyses. the first step consists in (1) selecting the analysis context through the choice of the generic structure on which analyses will be applied, and then (2) selecting the type of analysis: analysis covering all versions or relying only on the last version of documents. during step two, the decision-maker selects the multidimensional schema components, one fact and a set of related dimensions: •a fact represents a subject of analysis, composed of a set of attributes describing the business activity. these attributes are called measures or indicators and have numeric values. as an example, let us consider the fact publication that has the measure number of published articles. •the dimensions represent the analysis axes of measures. this means that the measures of an activity are observed according to these different dimensions. for instance, measures of the publication fact can be analyzed according to the several dimensions as author, year, and concept. in addition, the decision-maker indicates the order of dimensions and the aggregation function (count, sum, max, min and avg) to be applied to the fact measures. in the third step, the decision-maker can select specific values or introduce predicates in order to filter data for analysis. we distinguish two types of data filtering: •dimension filtering through which the user can select values on a dimension. •fact filtering where the user restricts the values of the fact measures using the comparison operators (<, >, <>, <=, >=, =). example: let us analyze the number of publications addressing the data warehouse concept by author and by year. construction of mart schema warehouse multidimensional schema document mart multidimensional table automatic generation of mart visualization multidimensional table 37 figure 5: affectation of analysis components once all these document mart schema-components are defined, the next phase generates the document mart. in our approach, this generation is automatically performed. 6. phase 2: automatic generation of document mart the decision-maker task is now completed and the automatic generation produces a document mart instantiated from the warehouse. to simplify this generation, we decompose it into two complementary steps namely view generation for each analysis component, element or concept, and joining and grouping generated views. 6.1 views generation for analysis component the first step is to recover the identifiers of the versions of documents belonging to the same generic structure and concerned by the analysis. •multiversion analysis select id_vdoc from versdoc vd whre vd.itsversgenstr.itsgenstr.sags.namegs = 'namegs'; •recent version analysis select vd.itsdoc.id_doc, max(datevdoc) from versdoc vd group by vd.itsdoc.id_doc; secondly, we recuperate trough a sub-query three attributes: (1) the identifier of each document. (2) the identifier of the common ancestor of analysis components. (3) the concerned information. these sub-queries are merged by the sql union operator to obtain a single view. the sub-query the system generates is the following. select 'id_vdoc', (1) i.associate.s_compose.s_compose....id_vse, (2) i.content (3) from information i (4) where i.associate in (select nt.adrvse from the (select vd.contain from versdoc vd where id_doc= 'id_doc')nt);(5) --if the dimension is a generic element and i.associate.inheritvge.inheritege.namege= 'namege' (6) --if the dimension is a concept and i.contain.namecpt='namecpt' (7) where: (1) document identifier (2) identifiers of specific elements those inherit from the first common ancestor of all analysis elements. (3) content of the specific element. (4) meta-model table name. (5) selection of the specific elements belonging to the document id_doc. (6) selected name of the generic element (when a dimension is based on a generic element). (7) name of the concept on which a dimension is based. note that the fact view is generated in the same way like dimensions; the s_compose denotes the link between a specific element and its father conference name year language thematics thematic dates submission notification registration conf committee program member papers paper title authors abstract authorfact (count) dimension 2 information system database cube data warehouse olap dimension 1 dimension 3 38 specific element so then the occurrences of s_compose equal the number of levels between a chosen element and its ancestor. as an example, for the year dimension (cf. figure 5) and the document 314 the system generates the following script. select '314', i.associate.s_compose.id_vse, i.content from information i where i.associate in (select nt.adrvse from the (select vd.contain from versdoc vd where id_doc= '314')nt); and i.associate.inheritvge.inheritege.namege= 'year' the ancestor element of the analysis components (abstract, author, year, title) is conference. there is one level between year and conference. that’s why s_compose is 1. for the analysis component data warehouse concept (cf. figure 5), the system generates the following script for the same document id 314. select '314', i.associate.s_compose.s_compose.s_compose.id_ se, i.content from information i where i.associate in (select nt.adrvse from the (select vd.contain from versdoc vd where id_doc= '314')nt); and i.contain.namecpt='datawarehouse' the number of levels between abstract and conference (ancestor element of the analysis components) is 3. thus the occurrences of s_compose equal 3. 6.2 joining and grouping generated views after generating the view for the fact and its dimension views, we follow by linking these views on their two first attributes, thus we generate a new view called joint. for our running example, it is the following. create view joint (datawarehouse, year, author, title) as select datawarehouse, year, author, title from datawarehouse d1, year d2, author d3, title f where d1.doc = d2.doc and d2.doc = d3.doc and d3.doc = f.doc and d1.anc = d2.anc and d2.anc = d3.anc and d3.anc = f.anc; to generate the final view that describes the document mart we group by all dimensions and apply the count function. create view result (datawarehouse, year, author, nb) as select datawarehouse, year, author, count(title) from join group by datawarehouse, year, author; figure 6 displays the result, obtained with the generated view, in a multidimensional table. figure 6: multidimensional table 7. docware prototype: experimentation to validate our proposals we developed the software prototype docware (document warehouse) for the integration and the analysis of textual data. specifically, docware provides the two following main features: first it determines the generic and specific structures of documents and then inserts these documents automatically into the document warehouse, and secondly assists the administrator (or even skilled decision-makers) during the construction of the document mart. in the remainder we illustrate some functionalities of docware through the following example. suppose we want to count the number of scientific papers dealing with the data warehouse concept, by author and publication year. •context accessing the document warehouse content we find that the documents describing the papers are grouped into the generic structure conference. it contains all necessary elements to perform the analysis (abstract, year and author). nb 2007 1 1 2008 * 2009 2 … … concept data warehouse publication foulen dupont 39 •approach we follow the three steps of our approach. i. choice of analysis context: we start by defining the generic structure for the document mart to be constructed. thus, the system displays. among the list of stored structures in the warehouse, we choose the generic structure conference that will be visualized by a tree (figure 7). ii. selection of analysis components: we specify the role (dimension or fact) of elements to build the mart by using contextual menus. chosen elements are automatically highlighted by using different shapes and colors for dimensions (read) and facts (yellow). in our example, we assign the data warehouse concept to the generic element abstract as the first dimension. then, we select the generic elements year and author as the second and third dimensions. finally, the measure is the count of titles. to assign a concept to a generic element, docware displays the list of all existing ontologies in the warehouse; this enables us to choose the appropriate ontology (cf. figure 8). iii. filtering: as we want to analyze the count of papers for the authors of this paper, we apply a filter on the third dimension. the system displays all author values; among them we select the three following names: kaïs khrouf, jamel feki and chantal soulédupuy. •result to visualize the result, docware creates views according the approach described in section 6 and displays the result multidimensional table (cf. figure 9). figure 7: affectation of a fact and dimensions figure 8: affectation of concept for the generic element abstract 40 figure 9: the result multidimensional table 8. conclusion the document warehouse allows flexible manipulation of heterogeneous collections of documents based on their structures and contents. in this paper, we extended the document warehouse meta-model toward a metamodel that supports multiversion document warehouse. this is for integrating a new feature: the management and analysis of multiple versions of documents. as documents evolution may concern their structure and/or content, we addressed the storage of versions compliant to a same document structure, as well as versions compliant to a multiple document structures. decision makers could be interested with the document evolutions, or even ignore them. therefore, we suggested two types of analysis on documents namely: i) multiversion analysis; i.e., covering all versions for a same document; and ii) recent-version analysis; i.e., analysis relying only on the last version of documents. in our proposed approach, each document version is compliant to a version of specific structure. furthermore, various versions of the same document are able to be compliant to several versions of generic structures. as an immediate perspective, we aim to extend the process of multidimensional analysis by integrating personalization criteria and metadata; this could be done by the user himself or by an assisted process. in addition, semantic aspects during the analysis process are interesting; they can help decision makers to get better analytics. acknowledgement we would like to kindly thank dr mohamed mbarki and ms maha azabou (master degree student) for their contribution to the implementation of the docware system prototype. references abiteboul s., cluet s., ferran g., rousset m.c. (2002). the xyleme project, computer networks, 39(3): 225-238, 2002. ben meftah s., khrouf k., feki j., ben kraiem m., soulé-dupuy c. (2012). document warehouse: integration of semantic structures, international conference on information systems ans intelligence economic, djerba, tunisia. ben messaoud i., feki j., khrouf k., zurfluh g. (2011). unification of xml document structures for document warehouse (docw), international conference on enterprise information systems, p. 85-94, beijing, china. cobéna g., abiteboul s. & marian a. (2002). detecting changes in xml documents. in international conference on data engineering (icde’2002), p. 41-52, san jose, california, usa. kimball r. & ross m. (2002). the data warehouse toolkit (2 edition). new york: john wiley & sons. khrouf k. & soulé-dupuy c. (2004). a textual warehouse approach: a web data repository, (p. 101-124). hershey: idea group publishing. khrouf k., feki j., soulé-dupuy c. (2011). an approach of multidimensional analysis of document. international conference on information systems ans intelligence economic, marrakech, morocco. nicolle c., alvarez a., amghar y. (2001). managing versions and links for structured legacy documents, international symposium on information systems and engineering (ise’2001), june 25-28, las vegas, nevada, usa. rusu l.i., rahayu j.w., taniar d. (2006). mining changes from versions of dynamic xml documents, p. 312, workshop on knowledge discovery in xml documents (kdxd), p. 3-12, singapore. wang y., dewitt d.j., cai j.y. (2003). x-diff: an effective change detection algorithm for xml documents, international conference on data engineering (icde’03), p. 519-530, bangalore, india. vol6no1paper5 rodriguez to cite this article: rodríguez salvador, m. and hernández de menéndez, a.m. (2016) major advances in ophthalmology: emergence of bio-additive manufacturing. journal of intelligence studies in business. vol 6, no 1. pages 59-65. article url: https://ojs.hh.se/index.php/jisib/article/view/143 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to 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https://ojs.hh.se/index.php/jisib/index major advances in ophthalmology: emergence of bio-additive manufacturing marisela rodríguez salvadora and ana marcela hernández de menéndezb tecnológico de monterrey, escuela de ingeniería y ciencias, ave. eugenio garza sada 2501, monterrey, n.l., méxico, 64849; amarisrod@itesm.mx; bmarcelahernandez@itesm.mx journal of intelligence studies in business please scroll down for article major advances in ophthalmology: emergence of bioadditive manufacturing marisela rodríguez salvador* and ana marcela hernández de menéndez tecnológico de monterrey, escuela de ingeniería y ciencias, ave. eugenio garza sada 2501, monterrey, n.l., méxico, 64849 *corresponding author: marisrod@itesm.mx received 3 january 2016; accepted 5 may 2016 abstract important efforts to discover new ways to combat illnesses are being carried out worldwide. in this sense, bio-additive manufacturing is an innovative technology that will revolutionize the health industry, as it provides the possibility to develop three-dimensional bio devices, such as body tissues and even organs. this research explores the most novel inventions of bio-additive manufacturing in ophthalmology. the main aim is to support the decision making of the research community and the organizations involved in this industry. the major advances, organizations, research focuses and main countries involved in the ophthalmology field were identified. to accomplish this, a scientometric patent analysis was carried out using advanced data mining software and consultations with experts. insights show a global research trend toward the development of lenses, followed by prosthesis and implants. bio-additive manufacturing is now in a nascent s-curve phase; however, important advances are being carried out. keywords 3d bioprinting, 3d printing, additive manufacturing, bio-additive manufacturing, biomedical devices, bioprinting, health, ophthalmic devices, ophthalmology, sientometrics, patent analysis 1. introduction additive manufacturing, also known as 3d printing and rapid prototyping, is an innovative technology that enables the development of products in an additive way by fusing or depositing materials in layers to produce a three-dimensional physical object (delgado, ciurana, and rodríguez 2012). the first technique was developed by charles hull in the early 1980s (schubert, van langeveld, and donoso 2014). since then, the industry has grown, and as a consequence, the number of patents has increased (rodríguez et al. 2014). high value products can be developed with this technology, including artwork, automotive parts, architectural models, dental bridges, jewellery and ductwork for mobile hospitals. versatility is one of the core advantages that 3d printing offers (conner et al. 2014). in addition, it allows for customized designs (euromonitor 2013) and product manufacturing with complex geometries and superior quality (campbell et al. 2011). a wide range of sectors could benefit from this technology, particularly the health industry, which presently needs to develop more innovative processes to face global changes in sustainability. worldwide markets demand high quality services and products at affordable prices (kivisaari et al. 2013). bioadditive manufacturing applications are growing rapidly and are expected to revolutionize the entire industry (schubert, van langeveld, and donoso 2014) with tools that facilitate education, surgical planning and organ transplantation research (huang and zhang 2014). journal of intelligence studies in business vol. 6, no. 1 (2016) pp. 59-65 open access: freely available at: https://ojs.hh.se/ 60 the purpose of this research was to identify the main organizations, their research focus, the major advances and the main countries involved in bio-additive manufacturing applied to ophthalmology. for this aim, a scientometric patent analysis was developed. the insights obtained could be useful to key players in the healthcare industry, particularly those who focus on researching emerging technologies to enhance innovative applications in ophthalmology. this paper is organized as follows. first, a review of additive manufacturing applied to health care is presented. second, current applications of this technology in the ophthalmology field are explored. third, an overview of the scientometric patent analysis is provided. fourth, the methodology applied is explained. lastly, the results are analyzed, and the conclusions are presented. 2. literature review 2.1 additive manufacturing: applications in the health care industry additive manufacturing has been used for decades, mainly in the manufacturing industry to produce prototypes (schubert, van langeveld, and donoso 2014). a wider adoption of this innovative technology is expected in the next two to five years due to its rapid diffusion into other industries. currently, its application has been extended to accessories, assembly parts and medical devices, including prosthesis (wohlers associates 2013), eye glasses and implants (schubert, van langeveld, and donoso 2014). as an example of its applications in health care, this technology is used to produce customized dental braces. the dental impression is converted into an stereolithography (stl) file, and then the braces are printed to fit the patient’s anatomy (conner et al. 2014). 3d printing offers valuable solutions for bone implant production. novel materials, such as cobalt–chromium– molybdenum alloy, can be used with this technology, allowing for the integration of a prosthetic component with a surrounding bone, which increases surgery success (stenlund et al. 2015). bio-additive manufacturing will play a determinant role in the health sector, considering the growing interest in developing breakthrough products that could change people’s lives, resulting in its global use (basiliere and shanler 2015). the use of bio-additive manufacturing in the health industry began with the production of medical devices that could repair, replace or control body functions. currently, it also includes the development of pre-surgery planning tools, surgical cutting templates (burton and shanler 2014) and custom-made products, providing patients and doctors with significant benefits that range from reduced time invested in surgery, to expedited patient recovery, to a higher likelihood of successful interventions. additive manufacturing also provides the possibility of printing tissue and organs directly, and it has enabled researchers to develop heart valves and cartilage tissue, among other body components. as the technology advances, the probability of developing functional tissues and organs using additive manufacturing will increase. in 20 years, it is expected that this technology will also offer the possibility of developing organs, such as eyes, hearts, livers and kidneys (ventola 2014). 2.2 bio-additive manufacturing in ophthalmology the potential uses of bio-additive manufacturing in ophthalmology are promising. complex three-dimensional models for ophthalmologists’ training are expected to be developed in the near future, enhancing the learning experience. moreover, advanced models of a patient’s eye anatomy could be reproduced and as a result, surgeons would be able to practice before an intervention, increasing precision and success (huang and zhang 2014). although more research is needed, there are significant advances in this area. along these lines, a 3d hollow eye model was fabricated almost 10 years ago using a rapid prototyping machine in which the purpose was to test a novel cleaner for healing complications in retinal diseases treatments. the inner walls of the model were coated with 5% bovine serum albumin to mimic the surface properties of the human retina (chan et al. 2015). important research has also been carried out for developing ophthalmological surgical instruments. for example, an ophthalmic speculum and a customized spatula have been developed using bio-additive manufacturing technology. they are currently undergoing prototype testing and a computer aided design (cad) development stage, respectively (lupeanu et al. 2014). by means of bio-additive manufacturing, the development of a printed cornea is a real 61 possibility. for example, a research group from massey university and auckland university have discovered how to print cornea replacements using collagen (mechatronics and robotics research group of massey university 2015). this development is in the proof of concept stage. although the use of bio-additive manufacturing in ophthalmology is still limited, there is a significant potential for the development of ocular tissues, such as conjunctiva, sclera and corneas. also, the printing of artificial lenses, glaucoma valves and a variety of medical implants developed in customized processes will be a reality in the future (huang and zhang 2014). moreover, the use of additive manufacturing in the development of flexible optical lenses for smartphones has been reported as well (sung et al. 2015). with additional research, this progress allows for the possibility of producing high-quality ophthalmic lenses for human use. ophthalmology is expected to be an important industry for future developments and innovations in bio-additive manufacturing (huang and zhang 2014). 2.3 scientometric patent analysis important studies have applied quantitative methods of analysis to evaluate scientific and technological literature production in the health domain. they have shown how research trends could improve the management and establishment of new strategies. one example is the investigation developed by zhang et al. (2013), who analyzed research papers on health management with the purpose of identifying the current status of collaborative activities and research topics in the field. their main objective was to develop insights for policy makers to allocate health research funds in a more precise manner; however, when analyzing technologies, patents emerge as an important source for developing valuable insights, in addition to scientific production. patents are highly valuable mechanisms for protecting innovations. they provide important competitive advantages, such as the invention right of for twenty years (weenen et al. 2013). in addition, patents are considered good indicators of the technological innovation process (hidalgo-nuchera, iglesias-pradas, and hernández-garcía 2009; rodríguez and tello 2012 utilization). in fact, they are frequently seen as a level of r&d activities and are widely used to determine research trends as well as development profiles (tsuji 2012). moreover, 90% of all available technological information can be found in patent publications (blackman 1995). they represent an accessible, reliable, updated and standardized source of information (de souza antunes et al. 2012). most importantly, they provide a way to envisage technology trajectories and to identify ongoing developments of organizations (companies, government agencies, centers, universities, etc.) (rodríguez et al. 2014). patents are used frequently as an indicator of technology research; its statistical analysis offers valuable insights (huang and yang 2013), as is the case for scientometrics applications, which involves the statistical analysis of technological literature. since the 1980s, extensive literature regarding patent analysis has been produced, causing a large growth in the early 2000s (ranaei et al. 2014). however, for additive manufacturing technology, there is still scarce patent analysis research. previous studies (rodríguez et al. 2014; uk intellectual property office patent informatics team 2013; gridlogics technologies 2014; tsuji 2014) have focused on determining patent activity from a general perspective rather than in regards to a specific sector or application. in this research, a scientometric patent analysis on additive manufacturing applied in the ophthalmology field was developed. 3. method a scientometric patent analysis was developed during this study. the research began with a broad analysis of the field and included the application of patseer software and consultation with experts. patseer is a global patent database and research platform with integrated analytic tools covering more than 92 million records from the main authorities worldwide (sinha and pandurangi 2015). patents were retrieved from 19 patent authorities. the time period covered in this research depended on the authority coverage, which ranged from 1782 to 2015 (april 29). the “title” and “abstract” fields as well as the following queries were considered: (3d print* or additive manufactur* or bioprint* or rapid prototyp* or rapid manufactur*) and (eye* or ophthalm*). table 1 research focuses and recent inventions of organizations, ordered by family patents. family patent refers to the same patent application or the publication of a single invention protected by different authorities by a common owner. family patent no. patent publication number application date invention description organization research focus: lenses 1 wo2015014381a1 (single patent) july 31, 2013 a method for ophthalmic lens using additive manufacturing. it includes constituting voxels of one or more compositions, wherein manufacturing a threedimensional at least one of the compositions comprises one or more pre-polymers or polymers. essilor international sa (france) 2 wo2015014380a1 (single patent) july 31, 2013 a method using additive manufacturing technologies and processes to manufacture a three-dimensional ophthalmic lens with a high management level of the homogeneity during the construction. essilor international sa (france) 3 fr3006622a1 family patent: wo2014195654a1 june 7, 2013 a process for manufacturing an ophthalmic lens having at least one optical function. it comprises the step of additively manufacturing an intermediate optical element. essilor international sa (france) 4 fr3006623a1 family patent: wo2014195653a1 june 7, 2013 a process for manufacturing an ophthalmic lens having at least one optical function characterized by comprising a step of additively manufacturing the ophthalmic lens. essilor international sa (france) 5 fr3008196a1 (single patent) july 8, 2013 a method for manufacturing an ophthalmic lens having at least one optical function, comprising the step of providing a starting optical system of the lens with a basic optical function and the step of additively manufacturing an additional optical element of the lens. essilor international sa (france) 6 ca2884801a1 family patent: wo2014049284a1 sept 26, 2013 a method for manufacturing an ophthalmic lens comprising a marking step for producing permanent technical marks. it comprises a step of additive manufacturing of a body and first and second surfaces. essilor international sa (france) 7 fr2985214b1 family patent: wo2013098511a1 dec 29, 2011 a template for an ophthalmic lens produced by additive rapid prototyping. essilor international sa (france) 8 cn102854639a (single patent) sept 21, 2012 a manufacturing process of photosensitive resin eyeglasses. with the adoption of the manufacturing process, optometry prescription data can be directly input into rapid prototyping equipment in a factory or eyeglass store. jiangsu wanxin optical co. ltd. (china) research focus: prosthesis 9 cn104091506a (single patent) july 24, 2014 the invention discloses a novel three-dimensional simulation eye. according to the novel threedimensional simulation eye, the 3d printing technology is adopted. liu qinghuai (individual) (china) 10 gb2504665a family patent: gb201211903d0 july 4, 2012 a method of manufacturing an artificial eye is presented. a digital image of an iris may be acquired and transferred to a substrate either by 3d printing or a transfer material, such as a dye sublimation film. manchester metropolitan university (uk) 11 gb2487055a (single patent) jan 5, 2011 a method of manufacturing an artificial eye is presented. in one embodiment, the image of the iris is cad modelled, and the substrate may be formed as an inherent part of the transfer step by a 3d printer using silica powder and then bound using cyanoacrylate. fripp design ltd. (uk) research focus: implants 12 de102012011311a1 (single patent) june 10, 2012 the invention relates to an intraocular lens that has a front side at which light occurs and a back side at which the light emerges. the lens is manufactured by an injection molding process, rapid prototyping or laser sintering. becker hartwig (individual) (germany) 4. results and discussion additive manufacturing applications in ophthalmology are in a nascent stage; only 33 patents were initially identified. a data cleaning process known as standardization (randall et al. 2013) was conducted manually to remove irrelevant information and to homogenize organizations’ names. after this process, a total of 17 patents were analyzed. this information was organized and categorized, resulting in 12 family patents (the same patent application or the publication of a single invention protected by different authorities by a common owner), which are shown in table 1. the results obtained show that the main research focus of bio 3d printing in ophthalmology is on the development of ophthalmic lenses. essilor international sa has 7 families in this area. for example, this company patented the process development of ophthalmic lenses and its intermediate or additional elements. incremental innovations of root patents have been developed through the application of additive manufacturing technology. additionally, jiangsu wanxin optical co. ltd. has patented an invention for producing photosensitive resin eyeglasses. prosthesis advances emerge as the second main research focus, which include 3 families. liu qinghuai (individual), manchester metropolitan university and fripp design ltd. have patented the development of artificial eyes. the third research focus is on implants. becker hartwig (individual) patented the creation of an intraocular lens. figure 1 shows that the top country in patenting these innovations is france (fr: 5 families), followed by the united kingdom (gb: 2 families), china (cn: 2 families) and germany (de: 1 family). in addition, 2 families were first filed to be protected in all european union countries at the same time (ep: 2 families). the identification and analysis of the inventions presented show the first efforts devoted to the application of bio-additive manufacturing in the field of ophthalmology. industry and academy are attempting to identify superior solutions to manage eye illnesses. this technology is in a nascent stage; however, the results show promising advances. bio-additive manufacturing provides the possibility to develop breakthrough innovations to improve patients’ conditions. 5. conclusions valuable insights were obtained through the scientometric patent analysis developed. the application of bio-additive manufacturing in the field of ophthalmology is still in its infancy. the majority of inventions found correspond to products developed to be used outside the human body, which represents the lowest risk for patients. this fact could be related to the novelty of the technology. figure 1 top countries for the development of ophthalmic inventions, determined by family patents. 64 the findings of this study show that the main research focus is on the development of lenses due primarily to the invention activity of essilor international sa. the second focus is related to the development of prosthesis, such as artificial eyes. in this sense, bio 3d additive manufacturing technology is mainly used to simplify the manufacturing processes and to create additional realism in the devices. only one invention belongs to the research focus group of implants, and this corresponds to the development of an intraocular lens. regarding the top country of protection, france occupies the leader position, particularly as a consequence of the patent activity of one company (essilor international sa). the results of this research offer valuable knowledge on emerging technologies and breakthrough innovations in ophthalmology. acknowledgements this research was supported by tecnologico de monterrey through centro de innovación en diseño y tecnología and its research group in advanced manufacturing. 6. references basiliere, p., and shanler, m. 2015. “hype cycle for 3d printing , 2014.” gartner, july 21. http://www.gartner.com/technology/home.jsp blackman, m. 1995. “provision of patent information: a national patent office perspective” 17 (2): 115–23. burton j, and shanler, m. 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"additive manufacturing and 3d printing state of the industry. annual worldwide progress report." wohlers associates. https://wohlersassociates.com/state-of-theindustry-reports.html vol6no3paper1 singh to cite this article: singh, s.k. (2016) geospatial analysis of census data for targeting new businesses using geoeconomics. journal of intelligence studies in business. 6 (3) 5-12. article url: https://ojs.hh.se/index.php/jisib/article/view/175 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index geospatial analysis of census data for targeting new businesses using geoeconomics sushant k. singha avirtusapolaris corporation, santa clara, california, usa; sushantorama@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: geospatial analysis of census data for targeting new businesses using geoeconomics business intelligence through patinformatics: a study of energy efficient data centres using patent data nishad deshpande, shabib ahmed and pp. 13-26 alok khode cross-cultural strategic intelligence solutions for leveraging open innovation opportunities journal of intelligence studies in business v ol 6 , n o 3 , 2 0 1 6 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 6, no. 3 2016 alexandru capatina, gianita bleoju pp. 27-38 and kiyohiro yamazaki business intelligence evaluation model in enterprise systems using fuzzy promethee mansoureh maadi, mohammad javidnia pp. 39-50 and malihe khatami sushant k. singh pp. 5-12 economic and industrial espionage at the start of the 21st century – status quaestionis klaus solberg søilen pp. 51-64 geospatial analysis of census data for targeting new businesses using geoeconomics sushant k. singha avirtusapolaris corporation, santa clara, california, usa *corresponding author: sushantorama@gmail.com received 10 october 2016; accepted 25 november 2016 abstract geoeconomics plays a vital role in encouraging goods and services on new marketplaces. selecting a “sweet-spot” for new businesses is one of the biggest challenges for new entrepreneurs, enterprises, and investors, especially in the restaurant industry. this paper aims to present a novel geospatial methodological approach for new businesses using census data to answer an important business question: where i should start my new asian cuisine restaurant? state and zip code tabulation area (zcta) level data on race and income, downloaded from the us census website, were applied for the analysis. arcgis software was used as a geospatial analytics tool for hotspot analysis and for producing maps. based on the state level standard deviation map, california was found to have the second-highest relative asian population as gauged by the standard deviation (std. dev.) from the mean (1.5-2.5 std. dev.), after hawaii (>2.5 std. dev.), and followed by new jersey, new york, nevada, and washington. the state of california was selected for further investigation. seventeen of 58 counties were found to be asian community hotspots in california. a majority (48%, 854 of 1763) of the zcta were found to be asian community hotspots in these zip codes in this state, and this was statistically significant. only 9% (163 of 1763) of the zcta were not statistically significant asian community hotspots, while 43% of the zcta were found to be statistically significant coldspots of asian communities in california. among the 17 hotspot counties of asian communities, 14 were also derived as hotspots of mean income. the road layer map revealed that these zctas are well connected to major roads in the state. new entrepreneurs, enterprises, and investors, those who are willing to open and or invest in new restaurants, but are not sure about the location, could target hotspot zctas in these counties for asian cuisine. integrating arcgis with census data for producing maps of statistically significant potential business locations could be used as an important decision-making tool for opening new businesses. keywords analytics, arcgis, asian, business, california, census, geospatial, restaurants, zcta 1. introduction geoeconomics is described as a theoretical and an applied science, and a methodical trend in socioeconomic geography, and can be applied in temporal, spatial, and political economic systems encouraging goods and services in new marketplaces (alayev 1983, anokhin and lachininskii 2015). it is also considered to be a multidisciplinary science investigating economic activities and is defined as “the study of spatial, cultural, and strategic aspects of resources, with the aim of gaining a sustainable competitive advantage” (søilen 2012). since geoeconomics lies on a trifold of scientific domains, including sociology, geography, and economics, each component plays a vital role in promoting new economic activities at local and global levels (renner journal of intelligence studies in business vol. 6, no. 3 (2016) pp. 5-12 open access: freely available at: https://ojs.hh.se/ 6 1942, lachininskii 2013, anokhin and lachininskii 2015). therefore, the geoeconomic space, which is a complex network transborder system, is vital in promoting new business activities (gay 2012, søilen 2012, anokhin and lachininskii 2015). furthermore, the local economic groups may strongly influence the regional economic performance (porter 2003). besides, the economic, legal, political, infrastructure, ecological, technical, cultural, and social factors are vital macroenvironments that help in business decisionmaking processes (søilen 2012). selecting a “sweet-spot” for new businesses is one of the biggest challenges for new entrepreneurs, enterprises, and investors. in this study, a “sweet-spot” is defined as a geographic location where the likelihood of maximizing the benefits is the highest for a new business, considering the local environments. the location information plays a vital role in the establishment of new industries as it impacts the economic growth of the firms as well as the socioeconomic, environmental, and political status of the establishment area (bhat et al. 2014, demiriz and ekizoğlu 2015, mishra et al. 2015). the locational information could help in retail site selection (karadeniz 2009), preventing retail banking fraud (demiriz and ekizoğlu 2015), financing commercial real estate acquisitions by real estate investment trusts (conklin et al. 2016), fast-food industry (austin et al. 2005) and much more. moreover, the location could also impact the business-level innovation (jordan 2015). the impact of taxes, subsidies and incentives, environmental regulations, quality of life and amenities, labor costs and availability, technical infrastructure, transportation, and accessibility have been reported as the most important factors in the assessment of finding potential locations for new businesses (kimelberg and williams 2013, bhat et al. 2014). however, the socioeconomics and demographics of the potential customers are largely ignored in most of the studies. this could adversely impact a newly established business or firm. for example, in the restaurant industry, the theme, food quality, ambiance, aesthetics, the service, and economic shifts play a vital role in the success and the failure of the business (murillo 2010, kimelberg and williams 2013). nevertheless, selecting the wrong customer neighborhood, poor accessibility, and a less dense population in the surroundings may unfavorably impact the new establishments (murillo 2010). according to location theory, firms or enterprises tend to assess where and why economic activities happen so that they can maximize benefits (north 1955, kimelberg and williams 2013, dubé et al. 2016). in this process, in most cases, non-spatial data, which are outcomes of small or large surveys, have been applied assessing the potential locations for establishing a new business (kimelberg and williams 2013). these surveys are very expensive and have inherent reliability challenges. therefore, targeting a location for a new business based on the analysis of the survey data with a small sample size could be a big concern for entrepreneurs, investors, and enterprises. the united states (us) census captures socioeconomics, demographics, and business information of the us population that could be used in business decision-making. however, this non-spatial data still lacks a geographical/spatial context. spatial data have the advantage of showing patterns on maps and letting the users connect the dots, taking neighborhood geographies into consideration. historically, presenting facts and figures on a map have played a vital role in both the political and the economic contexts (søilen 2012). geospatial analytics have emerged as an important method for the spatial and temporal analysis of data in various domains for informed decision-making (prato et al. 1995, boulos et al. 2011, rey et al. 2015, singh 2015, singh and vedwan 2015, supak et al. 2015, singh et al. 2016). however, in business, it is still in the rudimentary stages. the reason could be the lack of vision for integrating geospatial tools, such as arc geographical information system (arcgis), in business decision-making. similarly, the census data has been always available for public and private use, though it has not been integrated and/or used in business decision-making. the main goal of this paper is to attempt to bridge the above-mentioned gaps and integrate us census data with arcgis to help new businesses answer an important business question: where i should start my new asian cuisine restaurant? there could be several business questions similar to this. the state of california in the usa has been the center of economic growth with maximum wages and opportunities (porter 2003). because of the high rate of diverse immigration, the state became a hotspot for ethnic cuisine specially restaurants (porter 2003, capps 2007). the restaurant industry is 7 one of the fastest growing industries, and small to large business entities could be impacted if a poor site is chosen to start a business. the small business entities may not have enough resources to evaluate site selection. therefore, the current approach, described in this paper, could be a cost-effective and more efficient way of selecting a site for new businesses within the restaurant industry. however, the approach could be adapted for any other industries. 2. materials and methods the state and the zip code level population data for asian immigrants and household mean income in the zip code areas were used. state and zip code tabulation area (zcta) shapefiles were applied to perform geospatial analyses and to create maps. 2.1 data collection 2.1.1 state and zcta level asian population data the state level race data was downloaded from the american community survey (acs). a detailed description of the acs and the data is found in the 2016 us census (us-census 2016). the acs offers a total of nine different combinations of races at zcta level. for the current study, only hd01_vd05 (i.e. asian alone) was selected. a detailed description on the zcta can be found at the us census site (us-census 2016). in brief, the “zctas are generalized areal representations of the united states postal service (usps) zip code service areas,” however, the “usps zip codes are not areal features but a collection of mail delivery routes” (us-census 2016). 2.1.2 zcta level income data the zcta level mean income data was downloaded from the acs. the acs offers a total of 27 different combinations of mean income at zcta level. for the current study, only hc02_est_vc02 (i.e. estimated mean income in dollars by all households) was selected (us-census 2016). 2.1.3 state and zcta shapefiles state and zcta shapefiles were downloaded from the us census website (us-census 2014, 2015, 2016). these shapefiles were used to produce maps for geospatial analysis. 2.2 data integration to arcgis, analysis, and mapping the state and the zcta data were joined to the shapefiles within the arcgis environment using geoid as a join key (esri 2012). arcgis is a mapping software, developed by figure 1 a standard deviation map of the asian population in the united states. 8 the environmental systems research institute (esri), that offers several geospatial analytical tools (esri 2014). for all mapping and geospatial analyses, arcgis version 10.3.1 was used (esri 2014). 2.2.1 standard deviation mapping there are seven standard classification methods (manual, defined, equal, geometrical interval, quantile, natural breaks, and standard deviation) available in arcgis to spatially display numerical data on a map (esri 2012, 2014, 2016). the state level asian population data, used in this study, is available in absolute numbers and in percentage. the standard deviation classification method was applied to produce a classification map of asian populations at the state level. in this method, arcmap derives the mean and standard deviation and produce maps displaying which feature polygons deviate (positively and negatively) from the mean (esri 2014, 2015). based on the positive deviation and the highest standard deviation values, california was selected for further analysis. 2.2.2 hotspot analysis the hotspot analysis is one of the spatial statistical analysis tools in arcmap that was applied for mapping spatial statistically significant clusters of high values (hotspots) and low values (coldspots) (esri 2014, 2016). the output feature class is in the form of a shapefile with a giz-score, gip-value, and gi_bin. the giz-score and gip-value measure the statistical significance and the gi_bin represents the confidence intervals at 90, 95, and 99% (esri 2014, 2016). 3. results and discussion 3.1 state level distribution of asian population in the us the analysis revealed that the highest relative percentage (38%) of people identifying as asian live in hawaii, followed by 13% in california, 8.6% in ney jersey, 7.6% in new york, 7.4% in nevada, and 7.3% in washington. although hawaii has the highest relative asian population, california was used for this case study because of the availability of other relevant data and the interest of new entrepreneurs, enterprises, and investors in california (figure 1). later, the focus for further investigation was california and all the zctas in the state. 3.2 zcta level distribution of asian populations in the us the zcta is the smallest census unit and may offer more specific information on the figure 2 hotspot and coldspot map of asian communities in the zip code tabulation areas of california, united states. 9 socioeconomics, demographics, and businesses of those who live within the zcta boundaries. the hotspot analysis of asian communities clearly indicated two hotspots in california (figure 2). there are 1763 zctas in california. the zcta level hotspot analysis of the asian population revealed that a majority (48%, 854 of 1763) of the zctas were found to be statistically significant asian community hotspots (figure 2). only 9% (163 of 1763) of the zctas were not statistically significant hotspots of asian communities, while 43% of the zctas were found to be statistically significant coldspots of asian communities in california (figure 2). this further explains that 854 zctas are densely populated with asian communities and could be potential locations for opening new asian cuisine restaurants. california has 58 counties (figure 2), of which 17 counties are hotspots of asian communities. contra costa, los angeles, marin, orange, san francisco, san mateo, santa clara, and santa cruz counties were found to be hotspots of asian communities. however, merced, monterey, riverside, san bemardino, san diego, san joaquin, solano, stanislaus, and ventura counties were partially categorized as hotspots of asian communities in california (figure 2). 3.3 zcta level distribution of mean income in california, us the mean income in california zctas ranges between $9,471 and $413,643. furthermore, the hotspot analysis of zcta level mean income revealed that a majority (51% 894 of 1763) of the zctas were found to be hotspots of mean income, and this was statistically significant (figure 3) in the state. thirty-nine percent (746 of 1763) of the zctas were found to be statistically significant coldspots relative to the mean income, while 10% (170 of 1763) of the zctas were statistically not significant hotspots relative to the mean income in the california. the hotspots of mean income cover a total of 20 counties (figure 3). marin, san francisco, san mateo, santa clara, santa cruz, napa, solano, contra costa, ventura, los angeles, and orange counties were found to be hotspots of mean income in the zctas in the state. on the other hand, the areas of sonoma, monterey, lake, yolo, san joaquin, stanislaus, santa barbara, riverside, and san diego were partially indicated as hotspots of mean income in the zctas in the state. the common figure 3 hotspot and coldspot map of mean income in the zip code tabulation area of california, united states. 10 counties with the hotspots of asian communities and mean income were derived (table 1). table 1 hotspot counties and the coverage of asian population and mean income in california, united states. *nhs = not a hotspot. sl. no asian population hotspots coverage of the county asian mean income 1 contra costa county entire entire 2 los angeles county entire entire 3 marin county entire entire 4 merced county partial nhs* 5 monterey county partial partial 6 orange county entire entire 7 riverside county partial partial 8 san bemardino county partial nhs* 9 san diego county partial partial 10 san francisco county entire entire 11 san joaquin county partial partial 12 san mateo county entire entire 13 santa clara county entire entire 14 santa cruz county entire entire 15 solano county partial entire 16 stanislaus county partial nhs* 17 ventura county partial entire out of 17 counties with hotspots of asian communities (figure 2), 14 counties were either fully or partially identified as the hotspots of mean income (table 1, figure 2 and 3) in california. only three hotspot counties with asian communities, including merced, san bemardino, and stanislaus were not hotspots of mean income (table 1). therefore, the above 14 counties could be targeted for new business establishments of asian cuisine restaurants (table 1). 3.4 hotspot zctas with roads, availability in california, us as discussed in the introduction, the accessibility to the facilities plays an important role in the success of a newly established business. therefore, the hotspot map of the asian population was overlaid with a road layer to see whether the hotspot zctas are close enough to roads and accessibility is not a constraint (figure 4). both of the hotspots were found to have a good network of roads (figure 4). consequently, the 14 listed counties (table 1) meet three major criteria for opening an asian cuisine restaurant in california: high asian population, higher mean income, and greater road network. 4. conclusions geoeconomics can be examined at the lowest, low, middle, upper, and top geographical levels (anokhin and lachininskii 2015). in this study, the lowest geographic unit, the zcta, was used to show how social, economic, and geographic components could potentially impact new businesses. additionally, arcgis offers several tools for geospatial analysis and could be used as decision-making tool for informed business management within geoeconomics. moreover, census data offer various significant insights for the establishments of new businesses as well as for the existing businesses. integrating arcgis with census data could help businesses accomplish their goals, starting from locating new sites to predicting their business growth. the socioeconomic and demographic data are freely available at the zcta level. these could be applied for informed business decisionmaking through geospatial analytics using arcgis. in this study, only race, mean income, and road network data were used for the analysis. however, the us census offers several other important attributes such as gender, age, occupation, and household, housing, and business data, and much more. these attributes could be applied in the selection of new business sites and/or for other business needs. the current geospatial approach described in this paper is a costeffective, easy, and efficient way of selecting 11 new business sites and could be used by small as well as large business entities within and outside the restaurant industry. acknowledgements this 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"geography: zip code tabulation areas (zctas)." retrieved september 03, 2016, 2016, from https://www.census.gov/geo/reference/zctas.ht ml. the competitive intelligence process, an answer to the problem-oriented mechanisms of the knowledge creation : speech analysis as a strategy methodological appropriated 97 competitive intelligence and knowledge creation outward insights from an empirical survey mourad oubrich allal al fassi avenue, madinat al irfane rabat-institutesmorocco oubrich@inpt.ac.ma received 20 august 2011; received in revised form 23 august 2011; accepted 31 december 2011 abstract: the 21st century is characterized by many transformations which have had an impact on the growth of companies, such as aggressive competition, layoff plans, terrorist attacks and rising oil prices. it is of importance for a company to develop a protection against future impediments. this can be done by creating knowledge through a competitive intelligence process, which is the main focus of this article. with different theories about knowledge creation and competitive intelligence at hand, a qualitative empirical study was developed. the article presents how a company’s strategic intent, mission and strategic objectives can act as a guide for the competitive intelligence process, in order to gain the information necessary to find opportunities and eliminate threats. keywords: competitive intelligence, knowledge creation, knowledge management available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 97-106 mailto:oubrich@inpt.ac.ma https://ojs.hh.se/ 98 1. introduction 1.1 creating competitiveness the list given in the abstract is not exhaustive of the events that disrupt the international economic order and affect the growth of countries and companies. if we are able to draw conclusions from observing the environment, perform relevant actions involved in discontinuities and give them a useful meaning, it should be be possible to anticipate events, at least in theory. in order to forecast future developments it is necessary to identify the process that shapes knowledge creation in a company. the question so far is how we can help companies look forward to the future to protect themselves against threats and exploit opportunities. this question forces us to look beyond the competitiveness of a company and ask how they can sustain themselves over time. a development of a competitive intelligence process that boosts knowledge creation and innovation is a straightforward manner to ensure competitiveness. this article focuses on the knowledge creation part. it shows how the creation of new knowledge can be done in a competitive intelligence process. 1.2 problem definition this study pursues two main issues: 1) the determination of the different mechanisms able to create knowledge and 2) how these mechanisms can develop new knowledge. to that end, the article will shed light on the difference between information and knowledge, as pointed out above. this clarification allows us to understand in depth how a competitive intelligence process creates new knowledge. 2. materials 2.1 research context beginning in the mid-1980s, michael e. porter formed the basis of strategic thinking in business. according to porter (1990) competitive strategy is about being different. it means deliberately choosing a different set of activities to deliver a unique mix of value. moreover, the essence of strategy is choosing to perform activities differently than rivals do (porter, 1990). in the beginning of the 90s, his approach was criticized. the first critique was addressed by hamel and prahalad (1989). hamel (1996) explained that strategy should be stretched, not fit; competition should shape industry futures rather than merely positions within existing industries and resources should be leveraged rather than allocated. indeed, since then the research in competitive strategy has integrated the hamel and prahalad’s (1989) approach such as barney (1991). in his article he argued that sustained competitive advantage derives from the resources and capabilities a firm controls; that is valuable, rare, imperfectly imitable, and not substitutable. however, the diffusion of the resource-based view in strategic management and related disciplines has been both dramatic and controversial and has involved considerable theoretical developments and empirical testing (barney, wright & ketchen, 2001). the issue regarding how competitive intelligence drives knowledge creation is becoming a major concern for many organizations. research that has been undertaken around knowledge creation and the competitive intelligence process is somewhat rare (du toit, 2003). in this research, we are going to suggest a way to help organizations to set up an efficient competitive intelligence process that allow them to create new knowledge. to do so, it is necessary to understand both competitive intelligence and knowledge creation. 2.2 theoretical objectives there tends to be confusion between the concepts competitive intelligence and knowledge management. definition 1. knowledge management is the capturing, filing and categorization of the information. definition 2. competitive intelligence is the focusing, analyzing and “actioning” of data (du toit, 2003). without knowledge management it is not possible to create competitive intelligence, as competitive intelligence requires access to information. however, without competitive intelligence, knowledge management becomes a fruitless exercise of filing and categorizing information (calof, 2001). the authors give their definition of the competitive intelligence concept. they believe competitive intelligence has the following characteristics: 1. it is an art of collecting, processing and storing information to be made available to people at all levels of the firm to help shape its future and protect it against current competitive threats 2. it should be legal and respect codes of ethics 3. it involves a transfer of knowledge from the environment to the organization within established rules (rouach and santi, 2001). in this way, the intelligence cycle consists of four, by now well-known, stages that are essential to the process of decision-making: planning, collecting, 99 analyzing and disseminating value-added information. to exploit information needs to be upto-date with market changes. it demands the learning of methods and strategies that supports the use of information for decision-making. to be successful in this environment, the actors need to acquire new combinations of skills. in particular, they need to learn skills that allow them to find, manage and share information and knowledge (du toit, 2003). according to levet (2001), the transformation of information to knowledge implies the mobilization of capacities to interpret and to give sense by learning. achard and bernat (1998) points out that a manager has a role in enriching data throughout the information cycle to transform information into exploitable intelligence, which can be used by decision-makers. in doing so, the organizations need to create a shared space for individual and collective knowledge creation – both physically and mentally. figure 1: the information cycle 2.3 empirical objectives in the absence of a conceptual framework for competitive intelligence, it is appropriate to use a qualitative research strategy. our research adopted a qualitative methodology due to the need for rich data that can facilitate the generation of theoretical categories. furthermore, a qualitative method is appropriate in new topic areas to develop a deeper understanding of the phenomenon and to aid theory development (eisenhardt, 1989). in doing so, the study began by interviewing 20 directors engaged in competitive intelligence (60% are competitive intelligence directors). the empirical study started in october 2003 and was wound up by march 2004. 3. theoretical framework 3.1 competitive intelligence there are many definitions of competitive intelligence. the society of competitive intelligence professionals defines the term as: the process of ethically collecting, analyzing and disseminating accurate, relevant, specific, timely, foresighted and actionable intelligence regarding the implications of the business environment, competitors and the organization itself. according to calof (2001), competitive intelligence is defined as: an actionable recommendation arisen from a systematic process, involving planning, gathering, analyzing and disseminating information on the external environment, for opportunities or developments that have the potential to affect a company or a country’s competitive situation. despite the positive impact and growth of competitive intelligence, there exists a variety of associated ethical issues that are still unresolved. first we notice that competitive intelligence is different from industrial espionage. for example, (rittenburg et al. 2006) go further and propose a theoretical framework that outlines various factors that impact ethical decision-making in competitor intelligence gathering situations. they highlight that ethical decision-making for competitive intelligence gathering can be proactively managed. crane (2005) point out that industrial espionage or spying is both unethical and illegal. there is sometimes a fine line between the legitimate tactics of competitive intelligence gathering and the illegitimate practice of industrial espionage. at the end competitive intelligence is conducted in order to gain more knowledge about things to come so that today’s decisions can be based more solidly on available expertise than before. prescott (1999) outlines a decision-oriented approach to design a competitive intelligence program. 3.2 knowledge creation knowledge creation is often like a moot question for any organization that operates in a competitive environment. some researchers recognize the importance of knowledge for the competitive advantage of the firms. but, despite a great deal of discussion about knowledge creation, relatively little empirical evidence is available. to describe knowledge creation, this paragraph adopts the nonaka and takeuchi’s (1994) model. this model outlines two fundamental elements of organizational knowledge creation theory: epistemology and knowledge conversion. nonaka and takeuchi (1994) highlight that one dimension of the knowledge creation process can be drawn from a distinction between two types of knowledge, identified by polanyi (1966): tacit and explicit. 100 figure 2: the seci model this process, put together with the four basic seci epistemological processes, shapes the well-known knowledge-spiral of the company. nonaka and konno (1998) define the concept of “ba” – a susceptible environment for knowledge creation in terms of networks, teams, and open organizational designs. furthermore, nonaka and takeuchi (1995) describe the cognitive approach to knowledge creation as schemata – mental models and beliefs. it can be described as a perception which reflects our image of reality and our vision of the future. they consider this form of knowledge creation to be achieved through metaphors, pictures and experiences. 3.3 competitive intelligence process the competitive intelligence process is portrayed in figure 1 as a continuous process, which is improved through feedback. moreover, a distinction can be made between information and knowledge through this process. the notions of information and knowledge are often used in a different manner in the literature, including by those of authors who treat learning from an “informational perspective”. the necessity to distinguish between information and knowledge is important for the pursuit of this research. if admitted that information contributes to the improvement of the knowledge, as claimed by the authors of the informational approach of the organizational learning, such as argyris (1976); argyris (1993); cohen and levinthal (1990); huber (1991); nonaka (1994), these two notions cannot be considered conceptually as equivalent. knowledge drifts implies a certain transformation of information. according to huber (1991), information designates a structured togetherness of data transporting a sense (or signal) whereas knowledge is a product generated by the treatment (interpretation) of information. for information that can be acquired, knowledge must be developed. for argyris (1993), information constitutes an input necessary to the initiation and to the formalization of learning. the author defines information as being a flux of messages (or of signals) and knowledge like a belief verified concerning the human action that is founded on a flux of information. he uses this definition as formulated by nonaka (1994); that all knowledge is founded on a basis, more or less complex, of information. a version of nonaka and takeuchi’s (1995) definition of information will be used in this paper: a structured togetherness of data providing some indications of the nature or the evolution of a fact, of a given phenomenon, and the notion of knowledge as being a true and justified belief. our research could not exclude reflections around this distinction between information and knowledge. levet (2001) considers that the strategic dimension of competitive intelligence process resides in the triptych; appropriation (of information) – interpretation (of information) – action. the appropriation is about the knowledge of an enterprise and the interpretation consists of clearing the sense of the strategy. finally the action is founded on knowledge. therefore the role of competitive intelligence is to create knowledge from information. furthermore, competitive intelligence creates knowledge in terms of insights and understanding, known as tacit knowledge in users’ heads. the outcome of competitive intelligence is decisions that improve and optimize business decisions (du toit 2003). 4. theoretical results from a theoretical framework standpoint, organizational learning is a central mechanism in knowledge creation theory. the appropriate way to organize for effective knowledge creation would be to combine various types of organizational learning according to the strategic needs of an organization. regarding organizational learning, the reflection was here based on argyris and schôn’s (1978) work. the authors defined organizational learning as a process that implies the detection and the correction of an error. they distinguished two types of organizational learning (simple and double loop). the learning in simple loop is a compartmental process of adaptation and response or correction of error in the schema map or established organizational routines (learning by improvement of the basis of possessed knowledge). whereas the learning in double loop is a cognitive process that, according to 101 ingham (1994), implies a heuristic imaginative critique. it can be modifications in the diagrams of knowledge and answers or the production of new diagrams. in light of the discussions and theory presented above, this process can then quite easily be represented (argyris & schôn, 1978). figure 3: theory of action recent discussion on organizational learning and knowledge creation has emphasized the role of sharing common strategic intent and collective representation in knowledge generation. these new concepts and their relationships with organizational learning is explained below: 1. organizational learning as change in collective representations: argyris and schôn (1978) propose the basic foundation of the theory of action. from this theory we see how actors build their representation from information. to do that, the actors constantly refer to a collective framework or cognitive schema to act. in this sense, a competitive intelligence process can be seen as a place where the actors try to make up new representation regarding competitors, customers, and clients. the actors in this process interact in order to refine, to complete their representations; to test them and to evolve. in the same tentative explanation of organizational learning as knowledge creation mechanism, cyert and march (1963) note that learning comes from a prompt or continual gap between a level of aspiration associated with an objective and the real level of performance. 2. organizational learning as a result of a situational gap provoked by a strategic intent change: charue (1992) specifies that there is organizational learning when the members of the organization construct actionable knowledge in relation to the organization’s strategic intent. according to campbell and yeung (1991) and lipton (1996), strategic intent is the answer to the question: why does the company exist? company number position title industry interview method 1 director, competitive intelligence energy site 2 director, communication and marketing industrial chemicals site 3 director, human resource management utility site 4 director, competitive intelligence industrial products site 5 director, competitive intelligence energy site 6 director, strategy utility site 7 director, marketing services site 8 director, competitive intelligence automotive site 9 director, competitive intelligence it services site 10 director, competitive intelligence chemical industry site 11 director, knowledge management it services site 12 director, competitive intelligence services site 13 director, competitive intelligence energy site 14 director, knowledge management telecom site 15 director, competitive intelligence energy site 16 director, competitive intelligence semiconductor site 17 director, competitive intelligence transportation site 18 director, competitive intelligence electronics site 19 director, knowledge management utility site 20 senior director, strategic planning electronics site table 1: companies studied 102 ∑ speech % speech number of significant word number of word per speech % word/speech ci director 12 60 334 42151 0,64 others director 8 40 193 24372 0,36 ∑ 20 100 527 66523 1 table 2: summary of data collected 5. empirical study in this paper, a novel approach for competitive intelligence process is developed from conceptual and empirical study. the study aims to give more insight to mangers who wants to set up a competitive intelligence process to create knowledge necessary for making better decision. it is presented empirically how competitive intelligence is crucial for any company or organization which operates in a competitive environment. 5.1 general premises in the proposed model, information is considered the main input to the competitive intelligence process. on one hand, organizational learning is the center of this process and leads to knowledge creation. this knowledge is derived from two main sub mechanisms – strategic intent and collective representation. on the other hand, this model is oriented towards the creation of new products and services that are valuable, rare and imperfectly imitable. as a result, the following hypotheses can summarize the links that exists between competitive intelligence and knowledge management: hypothesis 1. competitive intelligence is the process that allows a company to create new knowledge regarding their competitors, customers, clients, suppliers and technologies. hypothesis 2. technological, competitive and environmental knowledge are created by a competitive intelligence process, as actors learn from the external and the internal environment. hypothesis 3. organizational learning happens when strategic intent is renewable through a competitive intelligence process. hypothesis 4. organizational learning happens, when collective representation is changed through a competitive intelligence process. in order to test the above hypothesis, the different variables are translated into measurements. table 3 shows the different measurements related to the variable’s model. variable measurement (1) direction and vision what are we looking for? what can we expect to happen in the future? are we sure that we have the sufficient information about our environment? (2) information gathering press, books, database, forum, convention informal networks (supplier, customers, competitors, subcontractor, etc.), who gathers the information? (3) information analysis internal and external experts meetings of analysis tools data processing (spss, data mining) (4) information disseminating meetings reports intranet e-mails phone calls (5) knowledge creation to tacit to explicit socialization externalization from tacit knowledge maps groupware knowledge portals workflow knowledge-based systems knowledge portals internalization combination from explicit innovation support tools intranet electronic document management business intelligence knowledge portals errors the system of roles is inefficient the rules for working are not clear the interface of the expertise domains is fuzzy bad use of the tools and techniques 103 (6) organizational learning corrections change of the structure change of the culture modification to the rules improvement in the management (7) collective representation change in the representations regarding external environment (threats / opportunities) change in the representations regarding internal environment (strengths / weaknesses). belief change (8) strategic intent renewal strategic plan renewal strategic objectives engagement of the actors table 3: measurement 5.3 analyzing data the number of data analysis tools in management is numerous. in our study, speech analysis was done. analysis of speech requires that certain questions should be asked with regard to the research question. to obtain answers to questions, speech must then be translated as far as possible into a measurable quantity. table 2 presents the most common occurrences detected by tropes software in 20 speeches. based on statistics generated by the tropes software, a contingency table was built. it is composed of 20 rows that represent the company and five columns that represent a variable. this table was used for quantitative analysis. in doing so, two techniques were used: the spearman rank correlation and factorial correspondence analysis. ci kc ol si rep  c1 21 15 18 15 11 80 c2 4 10 13 19 7 53 c3 5 13 41 21 16 96 c4 19 9 18 29 11 86 c5 23 20 4 20 10 77 c6 12 26 30 20 14 102 c7 12 20 9 14 9 64 c8 32 39 19 26 16 132 c9 20 19 12 18 8 77 c10 26 53 10 24 22 135 c11 11 47 16 47 19 140 c12 8 35 5 14 17 79 c13 12 27 9 12 8 68 c14 9 20 16 8 15 68 c15 50 43 16 33 18 160 c16 26 36 26 17 14 119 c17 27 45 17 6 16 111 c18 10 29 13 21 23 96 c19 7 18 7 12 3 47 c20 14 21 20 23 11 89 total 348 545 319 399 268 1879 table 4: contingency table speech / variable (20 speech) legend: ci = competitive intelligence kc = knowledge creation ol = organizational learning si = strategic intent rep = representation c number = company number the spearman rank correlation coefficient was used to discover the strength of a link between two variables. the research looks at the strength of the link between ci and kc, ol and kc, si and ol, rep and ol. when written in mathematical notation the spearman rank formula looks like this, where: d = the difference between the ranks of corresponding values of x and y n = the number of pairs of values. the use of a non-parametric test was justified by the small size of the sample (20 speeches). the test was carried out by using statview. spearman's rank correlation provides a distribution free test of independence between two variables. to do this, 104 spearman rank correlation provides two parameters : r = spearman's rank correlation coefficient. p = thresholds of significance (10%). table 5 show a strong relationship between ci and kc. by this result, the first hypothesis is confirmed. ci-kc ol-kc si-ol rep-ol r 0,493 -0,024 0,325 0,246 p 0,031 0,915 0,156 0,283 result correlated not correlated not correlated not correlated table 5: spearman's rank correlation coefficient (whole sample) 5.4 empirical results the result of the study showed a significant relationship between ci and kc. however, other relationships had no claim. the full analysis cannot focus only on spearman’s rank correlation. other authors have identified several limitations to this method, especially when the sample size is small (<30). to complete the test, our study used factorial correspondence analysis to measure a manager’s perception to different variables in the theoretical model. as mentioned, the contingency table drawn from lexical statistics and generated by tropes was used for the analysis. spss gave us the following result: company number factor 1 factor 2 c1 ,560 c2 ,132 c3 c4 ,198 c5 ,330 ,880 c6 ,441 c7 ,935 ,341 c8 ,731 ,678 c9 ,401 ,802 c10 ,902 ,331 c11 ,729 c12 ,917 c13 ,979 ,234 c14 ,615 c15 ,363 ,953 c16 ,683 ,246 c17 ,715 ,282 c18 ,756 c19 ,908 ,136 c20 ,472 table 6: correspondence analysis for factorial analysis note: high correlation (>,50) medium correlation (between ,25 et ,50) low correlation (<, 25). observe that factorial analysis of correspondences can only be based on the 19th speech. it says that the competitive intelligence director strongly contributed to the explanation of the factorial axis 2 (>50). smes did not participate in the factorial axis 2. a functional distinction was identified between smes and larger companies regarding the relationship between ci-kc, ol-kc, si-lo, repol. three homogeneous block profile speeches could be identified, that contribute to the construction of the factor 1: (c7, c10, c12, c13, c19), (c8, c11, c18), (c14, c16). two blocks of speech profiles involved in the formation of the factor 2 were detected: (c5, c9), (c1, c8). this classification is significant because it contributes to finding the speeches that give more information regarding the variable model. for example, g1 explains the kc, while as g2 is interested in ci and the rep, and g3 gives more information about is. variable profile variable speech side side + variable profile variable speech 0,999 0,979 0,935 g1 0,917 0,908 0,902 kc c13 c7 c12 c19 c10 105 0,756 0,731 0,729 0,715 g2 0,705 0,683 0,615 0,520 c18 c8 c11 c17 rep c16 c14 ci c4 c1 c3 ol -0,386 g4 -0,191 -0,181 -2,39 e -02 0,472 0,441 0,401 g3 0,363 0,379 0,330 0,132 c20 c6 c9 c15 si c5 c2 table 7: variable profile and variable speech note: g = group of companies with similar perception 8. conclusions the model is based on a competitive intelligence process and the theory of action developed by argyris and schôn (1978). according to havenga and botha (2003) the entire process should be guided by the company’s strategy. the company’s strategic intent, mission and strategic objectives should act as a constant guide for the competitive intelligence process. this paper describes a novel approach for competitive intelligence. it explains in theory how competitive intelligence can add value to companies by creating new knowledge. the views of several writers are assembled to describe the process, although they have different emphases. fuld (2000) believes that competitive intelligence should build on and around the culture of the organisation. our research claims that competitive intelligence allows companies to create new knowledge, if they can learn to align their competitive intelligence process with strategic intent and with collective representation. it means that companies should know how to use their competitive intelligence strategically to find new opportunities and minimize risks. acknowledgements the author feels a debt of gratitude to all directors for their openness, helpfulness and their insightful comments regarding this work. may their spirit continue to enlighten their lives and those of others. references achard, p, bernat, j.-p. 1998. l’intelligence économique: mode d’emploi. adbs editions. argyris, c, schôn, d. 1978. organizational learning: a theory of action perspective. adison wesley. barney, j, 1991. firm resources and sustained competitive advantage, journal of management, n°17. barney, j.b, wright, m, ketchen, d.j. 2001. the resource-based view of the firm: ten years after 1991. journal of management 27 (6). calof, j. 2001. competitive intelligence and the small firm—requirements and barriers. 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(eds). 1997. la connaissance créatrice. la dynamique de l’entreprise apprenante. de boeck université, bruxelles. oubrich, m. 2005. la création des connaissances dans un processus d’intelligence économique, phd dissertation, aix marseille university, france. polanyi, m. 1966. the tacit dimension. garden city, ny: doubleday porter, m.e. 1990. the competitive advantage of nations. new york, the free press. prescott, j.e. 1999. the evolution of competitive intelligence: designing a process for action, apmp spring. available online at url: http://www.apmp.org/fv-154.aspx rouach, d, santi, p. 2001. competitive intelligence adds value: five intelligence attitudes, european management journal vol. 19, no. 5, october. rittenburg, et al. 2006. an ethical decision-making framework for competitor intelligence gathering, journal of business ethics, vol 70. available online at url: http://www.springerlink.com/content/e3582656 18678457/ http://www.apmp.org/fv-154.aspx http://www.springerlink.com/content/e358265618678457/ http://www.springerlink.com/content/e358265618678457/ 15 balancing knowledge management and competitive intelligence, initial insights scott erickson 1 and helen rothberg 2 1 ithaca college, ithaca, usa gerickson@ithaca.edu 2 marist college, poughkeepsie, usa hnrothberg@aol.com received 20 may, revised form 11 september, accepted 25 september 2012 abstract: this paper reports on a large-scale study of how industries balance knowledge development with knowledge protection. in particular, we look at specific industries and the competitive imperatives to increase knowledge assets (or not) and to conduct competitive intelligence activities (or not). this analysis is based on our previously established spf framework, though we have developed new measures and a new database that more reliably establish industry conditions. the paper explains the different results seen in different industries by examining four markedly different spf environments. based on these different environments, we can begin to explore some of the possible explanations for the differences (characteristics of relevant knowledge, value chain insights, life cycle stage, etc.). keywords: competitive intelligence, intellectual capital, knowledge management, strategy, spf framework 1. background the intersection of knowledge management (km) and competitive intelligence (ci) is an area ripe for exploration. in the past few years, we have firmly established that different conditions exist concerning the need or wisdom to aggressively pursue knowledge management and the growth of a firm’s intellectual capital (ic), especially when different conditions exist concerning the need to protect knowledge assets from competitive incursion. we developed a framework for examining these different conditions some years ago and have attached data to the framework in a piecemeal manner in more recent work. we have even more recently constructed a new, full data set classifying firms by the imperative of knowledge management development in their industry (standard ic levels of the industry, presumably what is necessary to compete) and by the level of competitive intelligence activity in their industry (representing the competitive threat to their ic). with this database, we are able to classify firms according to these conditions, providing guidance to managers about appropriate levels of investment in km development and protection. more to the point of this paper, we are also able to analyze the database in more detail, with the aim of uncovering the specific variables that might give even more insight into when a firm should pursue aggressive knowledge development (or not) and when it should pursue ci activities or counterintelligence (or not). these results can be classified into four broad categories, the spf available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 15-22 mailto:gerickson@ithaca.edu mailto:hnrothberg@aol.com https://ojs.hh.se/ 16 framework, we have developed (rothberg & erickson 2005). these categories are based on relative high/low values of required ic and relative high/low threats due to ci activity. a full overview of the database will be available soon (erickson & rothberg 2012). in this paper, we present some instructive examples of firms and industries illustrating the key combinations of circumstances that can be instructive to both scholars and practitioners. 2. literature review our full database is founded on the idea that knowledge assets can confer competitive advantage, but the nature and value of that competitive advantage can vary by circumstances. this conceptual basis is strongly established in the literature, albeit in diverse disciplines. knowledge management (km) and intellectual capital (ic) are related concepts concerning the store of knowledge assets within an organization. ic is the stock concept, referring to the amount of knowledge in the organization, something beyond simple data or information (zack 1999b; zander & kogut 1995). km refers to attempts to better manage these knowledge assets, distributing them, growing them, or otherwise better identifying and applying them. interest exists in these fields because more and more scholars and practitioners are seeing them as potential sources of competitive advantage. while the view of knowledge as a competitive weapon has been with us for a long time (schumpeter 1934), it has grown in sophistication and detail in the past couple of decades. penrose (1959) had discussed the value of an organization’s knowledge stock. nelson & winter (1982) extended the thought with the concept of knowledge flows leading to knowledge growth and superior performance. better management of intangibles or organizational knowledge, then, would be a path to competitive advantage (winter 1987). this view fits in well with the resource-based view of the firm, with knowledge as the key organizational resource. from that perspective, knowledge becomes a unique, defensible competitive differentiator (decarolis & deeds 1999, grant 1996, gupta & govindarajan 2000a, zack 1999a). as a result, the aspects of measuring and managing knowledge drew interest. once again, the distinction between stocks and flows (dierickx & cool 1989) was important, with the idea that the identified stocks could be managed more strategically, adding to the flow of knowledge to the organization (teece 1998). techniques such as the balanced scorecard (kaplan & norton 1992) helped to measure the knowledge assets more precisely while methods to better manage them also developed apace (davenport & prusak 1997, edvinsson & malone 1997, stewart 1997). to better understand the nature of the these knowledge assets, researchers also worked on classifications, with the idea that different types of assets may have different impacts and may need to be managed differently. within the field, the categories of human capital, structural capital, and relational capital (bontis 1999, edvinsson & sullivan 1997) became standard. human capital is about job-related knowledge, structural capital about persistent organizational knowledge assets such as corporate culture or organizational form, and relational capital about knowledge concerning external parties (customers, partners, regulators, etc.). competitive capital, knowledge about competitors, is also discussed in some variations (rothberg & erickson 2002). a second, but equally important distinction between knowledge assets related to explicitness. tacit knowledge was described as more personal, harder to explain, codify, or transmit while explicit knowledge is codifiable and sharable (polanyi 1967). which of these a piece of knowledge is and will become is critical to how it is managed (nonaka & takeuchi 1995). explicit knowledge lends itself to information technology applications while tacit knowledge typically involves more personal tools such as communities of practice (boisot 1995, choi & lee 2003, schulz & jobe 2001). based on this foundation, the fields of km and ic have largely focused on in-depth empirical analyses of specific firms or small groups of firms. these have included studies of best practices (davenport, delong & beers 1998, gupta & govindarajan 2000b, hansen, nohria & tierney 1999, zack 1999b) or bottom-up measurements of knowledge assets, including individual components such as human capital (mouritsen, larsen, & bukh 2002). conditional factors and their impact on km have also been explored (kogut & zander 1992, nahapiet & ghoshal 1998, zander & kogut 1995). what this all amounts to is a fairly good understanding of km at the firm level, including how it might benefit an organization competitively, how to measure knowledge assets, and how to most effectively pursue knowledge growth. in our mind, this state of affairs leaves two big holes. initially, there is an implicit assumption that more knowledge is always better, or at least always worth the cost to obtain or grow it. given the scholarship 17 suggesting that there are variety of different types of knowledge assets and an even wider variety of variables affecting how they are developed, one could make the case that there are probably some more circumstance-based choices to be made on how to pursue km. this idea could be taken even further when we bring in the complicating factor of competitive intelligence (ci) activity (asis 1999, gilad & herring 1996). the presence of ci makes overdevelopment of km not only of questionable impact but potentially even dangerous, as spreading the knowledge too far can leave it vulnerable to a competitor’s ci operation. there is a case to be made that the degree to which to develop knowledge assets is a strategic choice, depending on competitive conditions (rothberg & erickson 2005). consequently, firms may be well-advised to develop a more strategic approach, assessing whether and how far to develop and distribute knowledge assets. but, how can we make that choice? surprisingly, little empirical work has been done that might shed light on this question. as noted earlier, there have been some firm-specific studies on the impact of km installations or how individual pieces of ic impact performance. but beyond some interesting case studies (mcevily & chakravarthy 2002), whether more and better km actually makes a difference in financial performance is one of the great unanswered questions of the discipline. and the obvious related question is whether the impact of km will vary by circumstances, given differences in an industry or in a specific firm. 3. strategy and knowledge assets this paper reports on the preliminary results of a major study to address this question. financial data on thousands of firms was collected and analyzed, specifically looking at a variation of tobin’s q (tobin & brainard 1977) to assess the level of knowledge assets in companies. in this case, we used market capitalization to assets (rather than replacement cost of assets) to get a sense of the value of intangible assets in each organization. these data were paired with data from a proprietary benchmarking study from ci consulting firm fuld & company. the fuld & company data indicated the level of ci activity in individual firms and, by extension, within specific industries. the level and frequency of ci operations in each industry provide a sense of the aggressiveness of ci in those industries. based on these data, we were able to organize industries into broad classifications regarding the necessity of aggressive knowledge development in order to compete (high-knowledge industries) vs. the necessity to protect knowledge (highcompetitive intelligence industries) (erickson & rothberg 2012). one might expect that these classifications would match up, with knowledge valued highly by both originator and competitor (or not). we have not found this to be the case. the conceptual foundations of other potential combinations (high knowledge development, low competitive intelligence and vice versa) were established some years ago (rothberg & erickson 2005) and have been fleshed out over time, including in this new study. in the original work, we termed this the spf framework, with the following characteristics defining the four basic categories. in this short paper, we don’t have the space to fully flesh out the conceptual details or all the reasoning behind them, but the basic structure breaks down as:  spf 45: high knowledge development priority, high competitive intelligence activity. knowledge is highly valued by both the originator and its competitors.  spf 30: low knowledge development priority, high competitive intelligence activity. knowledge development is difficult or unimportant for the originator but of considerable interest to its competitors.  spf 15: high knowledge development priority, low competitive intelligence activity. knowledge is highly valued by the originator but of little interest to competitors.  spf 5: low knowledge development priority, low competitive intelligence activity. knowledge has little value to either originator or its competitors. these pose very different circumstances for managing knowledge, and decision-makers would be well-advised to make note of their environment and develop and/or protect accordingly. to help us better understand these different scenarios and also to help practitioners with understanding what contributes to a firm/industry finding itself in its particular set of circumstances, we looked at what characteristics are common to industries in the same group and which are different across groups. these results are described more widely elsewhere (erickson & rothberg 2012). here, we look at illustrative industries from each group. with a concrete example in place, it’s easier to see how and why the industry finds itself classified the way it is, as well as what 18 characteristics might be typical of industries and firms that are in its group, as opposed to others. the results are interesting in terms of providing insights into the different circumstances that face km practitioners as we look to provide them with a more strategic approach to shepherding knowledge assets. 4. results as noted, the spf framework broadly categorizes industries and firms by the knowledge development and competitive intelligence variables noted above. the groups’ categories include:  spf 45 (high km, high ci)  spf 30 (low km, high ci)  spf 15 (high km, low ci)  spf5 (low km, low ci) table 1 presents illustrative industries falling into each group, along with descriptive metrics concerning knowledge development and competitive intelligence activities. substantial differences are clear across the categories, and we’ll further develop these and other characteristics of each group in the following discussion. table 1: spf categorization and characteristics spf 45 (high km/high ci) is represented by sic 2835/6 diagnostic and biological products, including firms such as genzyme and amgen. according to the measures we applied, this group has a high level of knowledge assets, with a cap/asset ratio of 2.41, well above the average of 1.02 for the entire data set. this characteristic is confirmed by the cap/book value ratio of 4.37, which is similarly high above the universal average of 2.68. these types of firms have valuable intangible assets that make them worth much more than the value of their physical assets, so knowledge is important in this industry and presumably critical to being competitive. given the high relatively level of physical assets ($8 billion per firm, on average, as represented in the table), the high ratio value is especially indicative of the importance of knowledge assets. even from a sizable tangible asset base, the ratio of intangible assets is quite high. the industry also has a high level of competitive intelligence activity, with 6 different firms in our database reporting some level of ci operation, with the majority possessing a fairly advanced capability. firms competing in this industry face quite a number of seasoned ci groups arrayed against them, all interested in acquiring other firms’ knowledge assets. other features of this group that we notice here and in our wider database are complex operations, a wide variety of types of knowledge, multiple value chain activities requiring a high level of knowledge, and early maturity in the life cycle with evidence of continued innovation. while the wider database includes both manufacturing and service operations for both business-to-consumer (b2c) and business-to-business (b2b) purposes, what all have in common are complex operational processes, as is the case with this industry. biological products, in particular have a very tricky, complicated operation with lots of variables affecting the success and the quality of the output. most of the products and processes are regulated and so require processes to be described and approved by the food & drug administration. companies work to perfect their processes before filing the version they will then be required to follow. knowledge here, although complex, is not specific and can often be employed elsewhere by the originating firm (or by an acquiring ci operation). 19 explicit and tacit knowledge are both visible here. while some innovation and production processes may become explicit, there are also softer knowledge assets such as customer relationships (with retailers, insurers, and doctors), regulatory relationships (with the fda), and treatmentspecific competencies. similarly, and as the previous list suggests, there are a variety of types of knowledge asset, including human, structural, and relational. the examples also illustrate how the knowledge assets are distributed throughout the value chain, from operations to distribution to marketing and sales, interacting at several points with support activities, particularly technology development, infrastructure, and human resources. and while all the firms in our database are of a certain size (annual sales over $1 billion) and so almost certainly in the maturity stage of the life cycle, firms in this industry seem to be clearly at an early stage, as growth is still possible, especially in specific treatment categories. innovation is also extremely important, with extensive investment in r&d and new product development. spf 30 (low km, high ci), on the other hand, has a similar level of aggressive ci activity but a far lower km score. in this case, we use the example of sic 6311 life insurance. here, the ci activity is similar to what we saw in the previous case, with seven different firms reporting ci operations and almost all of those at an advanced level. ci is aggressive and notable. the knowledge score, on the other hand, is much lower. here, the main cap/asset ratio we used to construct and analyze the database is only 0.11 (again versus a universal average of 1.02). the cap/book ratio is 1.12, also well below the database average of 2.68. given the unique circumstances of this industry, that latter value is particularly important here, as financial services companies typically have a tremendous amount of financial assets, a fact that would tend to depress the ratio as that large value would be in the denominator when looking at cap/asset. but if we use cap/book, the biasing factor is less extreme. most of these financial assets will be borrowed, and so with cap/book (book corresponds to assets less liabilities), that comes into play and essentially tamps down that high level of assets with borrowed assets cancelling out much of the total assets. so the fact that both measures agree that this industry has low knowledge assets is important. knowledge is less critical to success in this industry and so aggressive knowledge development is a questionable strategy. as would be expected, this group has enormous assets compared to others, but, again, these are usually financial assets rather than physical. in line with that, more industries in spf 30 are services than in spf 45, and what manufacturing we see in spf 30 is usually less complex. knowledge is often explicit, with occasional tacit insights (which may be important but hard to engineer or copy), complex, but specific to particular purposes (though not necessarily specific to the originating firm). intellectual capital of all types is present but at lower levels, and knowledge is apparent all along the value chain, but is not as ubiquitous—rather than appearing in many places for a single firm, it is here and there, in a more spotty manner. insurance companies, for example, do create new products or approaches, but they are usually incrementally different, not dramatic innovations. specific competencies in areas like marketing/sales, underwriting, claims processing, or other areas make differences for firms, but only at the margins. much of what these firms do is similar. those differences at the margins, however, the tacit insights that drive new approaches, are exactly what attract the interest of competitors. difficult for the originating firm to invent, but often rapidly copied once introduced. as would be expected, this industry is considerably more mature than what we saw with the diagnostic/biological group. products are more commoditized, market shares more stable, and innovation more measured. there is little new under the sun, but what there is tends to be taken up quickly by competitors. spf 15 (high km, low ci) is back to a high value placed on knowledge assets but now with minimal or non-existent competitive intelligence activity. the example industry here is sic 4731 freight transport. the cap/asset ratio is 2.29 (far above the 1.02 average) and cap/book ratio is 4.28 (above 2.68). physical assets are often at lower levels. competitive intelligence activity is low. in the freight industry, there is no evidence of any ci, as none was reported by any firms in that classification. knowledge is valuable but competitors seem to have little interest in aggressively pursuing it. part of that may be because the valuable knowledge is right out in the open and takes no effort to procure from a competitor. but our evidence suggests other things going on as well, such as some other complication that may make it difficult for a competitor to use the knowledge in the same way. what we see in this category are industries with complex operations, including manufacturing, natural resources, or services such as retail. knowledge is often explicit though once again with tacit insights, complex, and specific to the originating firm. all types of intellectual capital are present, human, structural, and relational. along the value chain, valuable knowledge can be found 20 almost anywhere but is really concentrated in processes and logistics. industries are well into the maturity stage of the life cycle, to the degree that many of these industries, consolidation has driven competition down to a couple of large firms surrounded by a variety of smaller niche players. when the dominant firms do uncover new knowledge insights, others may have trouble copying them because of a lack of similar scale, lack of an installed base, or other blockers such as strong brands or distribution agreements. with freight transport, we have extremely complex processes involved in scheduling equipment, logistics, and moving freight from point a to point b. providers have established relationships with customers, regulators, facilities operators (e.g. ports, distribution centers), and others that are both difficult to break into and difficult to duplicate. providers also tend to specialize in particular products or geographical areas. companies find ways to develop new knowledge and improve, but that knowledge is often specific to their circumstances and so of little interest to competitors, even if out in the open. spf 5 (low km, low ci) includes industries where knowledge appears to have little value for either originators or their competitors. sic 263 paperboard is the illustrative industry here. this industry has a cap/asset ratio of only 0.28 (versus the overall 1.02 average) and cap/book ratio of 1.48 (2.68 overall average). assets are a little heavy, as each of these manufacturers likely owns forests full of raw materials, but are near the full dataset average and not nearly as potentially biasing as those of financial services firms. there is no reported ci activity in this industry. industries in spf 5 are heavily skewed toward services, especially distribution and transmission. knowledge is highly explicit but often not proprietary, so an established base of knowledge is shared throughout these industries. complexity is limited and knowledge is not particularly specific. intellectual capital types vary but there is little of importance except perhaps structural capital (which, again, is universally known). knowledge in these industries is present in the value chain primarily in processes and logistics. industries are in late maturity, with established processes and competitors filling established roles. there is little new or innovative and very little valuable proprietary knowledge. paperboard manufacturers are in a late maturity industry. the technology behind making cardboard packaging materials is well-known and present throughout the industry. any new innovations, such as incorporating more recycled content into some products, is easily copied by competitors with minimal effort. there’s just very little new in this industry, very little of value to be discovered (apparently), and very little to pursue from competitors, as reflected in the data. 5. conclusions this paper reports on a small piece of a larger study looking at the conditions under which firms develop and protect knowledge assets. based on the idea that knowledge management is a more strategic activity than is commonly recognized, the larger product looks to classify industries and firms according to industry practices and data reflecting the importance of knowledge assets when compared to competitive intelligence threats. based on the larger data set, we reported on four examples that illustrate the usefulness of the approach in several ways. initially, just the basic data used to identify these industries shows the considerable differences between industries putting a high value on knowledge (ratios of 2.41 and 2.29 according to our metric) and those with lower values (0.11 and 0.28). these are, on the face, clearly different situations for managing knowledge. similarly, there are industries with aggressive competitive intelligence activity (numerous firms with highlevel operations), posing a threat to proprietary knowledge assets, and others with no apparent ci. again, these are clearly quite different circumstances. with this framework, we use this opportunity to try to describe more specifically what the tendencies are in each of the selected classifications of knowledge competition. by looking at asset levels, types of industries (manufacturing or service), types and characteristics of knowledge, critical value chain activities, and life cycle stage, we can start to get a read on circumstances and appropriate managerial responses. with a better understanding of all these facets, we can offer more guidance to practitioners on when and how to aggressively pursue knowledge assets as well as when and how to protect the same. acknowledgements: the authors appreciatively acknowledge fuld & company for providing some of the data used in this study. references american society for industrial security (asis)/pricewaterhousecoopers. 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(2018) id en tifyin g an d d escribin g su b-pro cesses in t he strate gic in te lli gen ce process by qualitative content analysis in an inductive way. journal of intelligence studies in business. 8 (1) 16-24. article url: https://ojs.hh.se/index.php/jisib/article/view/283 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index identifying and describing sub-processes in the s t r a t e g i c i n t e l li g e n c e p r o c e s s b y qu a l i t a t i ve c o n t e n t a n a l y si s i n a n i n d u c t i ve wa y ahmad abbaspoura*, amir hussein amirkhania, ali asghar pour ezzatb and mohammad javad hozoria adepartment of management, payame noor university, tehran, iran; bfaculty of management, university of tehran, iran; *aabbaspuor@yahoo.com journal of intelligence studies in business please scroll down for article identifying and describing sub-processes in the strategic intelligence process by qualitative content analysis in an inductive way ahmad abbaspoura*, amir hussein amirkhania, ali asghar pour ezzatb and mohammad javad hozoria adepartment of management, payame noor university, tehran, iran; bfaculty of management, university of tehran, iran corresponding author (*): aabbaspuor@yahoo.com accepted 9 march 2018 abstract the purpose of this study was to identify and describe the sub-processes of the strategic intelligence process in organizational level analysis. data were collected by searching the major academic and practitioner books, theses and journals in the ebsco, google scholar and irandoc databases in persian and english. nine thousand pages of text data were examined using content analysis. fourteen main sub-processes were identified to describe the strategic intelligence process: (1) identification of strategic environments and prioritizing them, (2) determination of organizational information needs and prioritizing them, (3) determination of monitoring period for each section of strategic environment and organization key information needs (kin), (4) determination of information sources and assessment of information capturing, (5) external information scanning, (6) internal information extracting, (7) setting criteria for gathered information assessment, (8) information filtering, categorizing and abstracting, (9) information analysis, (10) interpretation and sense making (intelligence generation), (11) determination of intelligence users and intelligence distribution media, (12) intelligence distribution, (13) feedback from recipients, revision and adjustment, intelligence storage, and (14) intelligence use. the results provided useful insight for strategic intelligence process implementation in organizations and its effectiveness evaluation. the innovative aspect of this study is its response to a lack studies about strategic intelligence process modelling. keywords competitive intelligence, strategic intelligence, process, content analysis, inductive way 1. introduction the notion of strategy is multi-dimensional and multifaceted and includes many meaning (leonard and mintzberg 1996). in this way, strategic intelligence (si) has many definitions too. cohen (2009, 31) states she can account "for at least 25 different expressions in english publications" for the notion of si, by studying books and articles published since 1967. this difference of views has led to some instability of terminology and lack of consensus in the si body of knowledge. mcdowell (2009) reported some difficulty for analysts and practitioners who want do research in si. many authors have written in this regard, acknowledging the disagreement about si process and procedures in many organizations (kruger 2010, marchand and hykes 2007, brouard 2007, xu and kaye 2007, liebowitz, 2006). here, we want to analysis relevant texts about si processes to: 1) find a journal of intelligence studies in business vol. 8, no. 1 (2018) pp. 16-24 open access: freely available at: https://ojs.hh.se/ 17 basic consensus among authors about essential activities that are causing strategic intelligence. 2) identify executive requirements that impose strategic intelligence on organizations and 3) identify the sub-processes of strategic intelligence. 2. theoretical framework intelligence is a comprehensive word, and many types of intelligence known in organizations are under the umbrella of this term. according to liebowitz (2006): artificial intelligence (ai), business intelligence (bi), and competitive intelligence (ci), are different forms of intelligence at the organizational level of analysis. liebowitz (2006, 14) has suggested a framework of intelligence to integrate many kinds of intelligence in organizations. figure 1 indicates liebowitz’s (2006, 14) comprehensive model and shows the inclusion of different types of organizational levels of intelligence. according to liebowitz (2006, 13): "the inner layer refers to ai. this is the field of developing intelligent systems to support or, in some cases, replace the decision maker". although the benefits of ai techniques can be gained, in liebowitz’s (2006) opinion, this does not necessarily mean that other intelligence layers must use ai techniques. he admits that because of the model's comprehensiveness, he introduced artificial intelligence into the model. the next layer in the intelligence framework refers to knowledge management (km). according to bali et al. (2009, 7) km is defined as: "comprised a set of tools, techniques, tactics and technologies aimed at maximizing an organization's intangible assets through the extraction of relevant data, pertinent information and germane knowledge, to facilitate superior decisionmaking so that an organization attains and maintains sustainable competitive advantage". jennex (2009, 4) define km as: “the practice of selectively applying knowledge from previous experiences of decision-making to current and future decision-making activities with the express purpose of improving the organization's effectiveness". km refers to how the organization's knowledge can be used for innovation, essential knowledge retention, loyalty creation, and employees’ productivity improvement. for gaining, organizing and sharing knowledge, ai techniques can be used. business intelligence (bi) has been placed in the next layer of figure 1. the knowledge management and business intelligence (kmbi 2005) workshop defined bi as an: “active model-based, and prospective approach to discover and explain hidden, decision relevant aspects in large amounts of business data to better inform business decision processes”. turban et al. (2007, 24) define bi as “an umbrella term that combines architecture, tools, databases, analytical tools, applications, and methodologies” that “give business managers and analysts the ability to conduct appropriate analysis” on historical and current business data. how to effectively manage the organization's internal information, to improve organizational performance and to align implementation and strategy, are the key issues of bi. liebowitz (2006, 14), has introduced competitive intelligence (ci) in the fourth layer of figure 1. bi focuses on the internal and often quantitative data of the organization; however, ci focuses on data outside the organization, often qualitative in nature. these data refer to the competitive aspect of the external environment of an organization (liebowitz 2006, britt 2006, mcgonagle and vella 2002). the society of km bi ai ci si figure 1 framework of intelligentsia (liebowitz 2006,14). 18 competitive intelligence professionals (scip 2007) has defined ci as: “a systematic and ethical program for gathering, analyzing, and managing external information that can affect a company’s plans, decisions, and operations”. ci is information, which is gathered from the market, then analyzed to provide recommendations and solutions to decisionmakers; all of these are done in a legal and ethical way (miller 2000). ci means creating a systematic plan capturing organizational external information and knowledge, as well as analyzing and managing this information and knowledge, to improve the organizational decision-making capacity (jones 2009, calof and wright, 2008, liebowitz 2006). the last layer in liebowitz’s (2006, 14) framework of intelligence is strategic intelligence (si), which includes all types of intelligences in organization. si helps the organization make the best strategic decisions. the top managers of an organization have to anticipate the future of the organization to gain competitive advantage. to do this, they must have intelligence about the trend and direction of the changes that occur in the following areas: resources, customer expectations, emerging technologies that affect business and customers’ behavior, political and social change, incentive and restrictive laws (marchand and hykes 2007). according to cohen (2009) there is no common, consensual definition of si. each author, according to her/his research background, has defined si. for this reason, in table 1, different definitions and perspectives of si are presented. considering the definitions given in table 1, there is no general consensus among scholars involved in the si phenomenon; and the body of knowledge about this phenomenon is fragmented. so, using the methodological suggestion of elo and kyngäs (2008), a qualitative content analysis method was used to address the aims of this paper. 3. methodology in terms of qualitative versus quantitative methodologies, we use a qualitative methodology to identify and describe si subprocesses. from the ontological point of view, the qualitative methodology is placed in a holistic-inductive paradigm (sarantakos 2004). a qualitative methodology is used when there is some concern about understanding a phenomenon, and the goal is not to measure the relationship between variables. content analysis as a research method is a systematic and objective means of describing and quantifying phenomena (krippendorff 1980, downe-wamboldt 1992, sandelowski 1995). it is also known as a method of analyzing documents (elo and kyngäs 2008). table 1 different definitions of si at the organizational level of analysis. author definition tham and kim (2002, 2) strategic intelligence can be identified as what a company needs to know of its business environment to enable it to gain insight into its present processes, anticipate and manage change for the future, design appropriate strategies that will create business value for customers, and improve profitability in current and new markets global intelligence alliance (2004, 5) a systematic and continuous process of producing needed intelligence of strategic value in an actionable form to facilitate long-term decision making. liebowitz (2006, 22) si is the aggregation of the other types of intelligentsia to provide value-added information and knowledge toward making organizational strategic decisions. marchand and hykes (2007,1) strategic intelligence is about having the right information in the hands of the right people at the right time so that those people are able to make informed business decisions about the future of the business. brouard (2007, 122) strategic intelligence could be defined as the output of the informational process by which an organization stays attuned to its environment in order to make decisions and then act in pursuit of its objectives. mcdowell (2009, 24) the specific objective for strategic intelligence is to provide accurate, long-range intelligence to enable effective high-level planning and management of law enforcement resources to meet the overall perceived threat. cohen (2009, 49) si is a formalized process of research, collection, information processing and distribution of knowledge useful to strategic management. 19 content analysis is (elo and kyngäs 2008, 109): "a method that be used in an inductive or deductive way. which of these is used is determined by the purpose of the study. if there is not enough former knowledge about the phenomenon or if this knowledge is fragmented, the inductive approach is recommended". in an inductive way, concepts and classifications are extracted from the data. the qualitative content analysis in the inductive method has three main steps: preparation, organizing and reporting (elo and kyngäs 2008). these steps are shown in figure 2. 3.1 trustworthiness there is a lot of struggle between authors about the appropriate terms for evaluating the validity of qualitative research. many terms such as rigor, validity, reliability and trustworthiness were developed for this purpose (koch and harrington 1998). the most widely used criteria for evaluating qualitative content analysis are those developed by lincoln and guba (1985). they used the term "trustworthiness". the aim of trustworthiness in a qualitative inquiry is to support the argument that the research’s findings are "worth paying attention to" (elo et al. 2014, 2). lincoln and guba (1985) have suggest five options for assessing the trustworthiness of qualitative research. these are credibility, dependability, conformability, transferability, and authenticity. elo et al. (2014, 3) proposed a checklist for researchers attempting to improve the trustworthiness of a content analysis study. in this paper, we use their proposed checklist and the points to be reported according to their checklist (elo et al. 2014), according to the following headings. 3.2 data collection method material for this study included all published texts and literature in persian and english about strategic intelligence. we used a twostage strategy for selecting material. first, we searched the major academic and practitioner journals and books in the ebsco, google scholar and irandoc databases using the keywords "strategic intelligence" in persian and english for the period from 1967 to the present (march 2017). this time frame was selected because it corresponds to the period during which si appeared in the management field (cohen 2009). second, we checked the reference lists of the articles and books obtained through the initial search to uncover additional studies. in total, a little more than nine thousand text data sheets were collected for review. 3.3 sampling strategy in qualitative research, the sampling strategy is selected based on the methodology and subject and there is no requirement for generalizability of the results (higginbottom 2004). the most commonly used method in content analysis studies is purposive sampling (kyngäs et al. 2011). in this research, purposive sampling was also used. two criteria were used to select appropriate samples: (1) texts should be in the business or organization context; and (2) examine si at preparation phase selecting the unit of analysis making sense of the data and whole organizing phase open coding coding sheets grouping categorization abstraction reporting the analyzing process and the results model, conceptual system, conceptual map or categories figure 2 figure 2 preparation, organizing and resulting phases in the content analysis process by the inductive approach. (elo and kyngäs 2008, 110). 20 the organizational level of analysis. it has been suggested that the saturation of data may indicate the optimal sample size (guthrie et al. 2004, sandelowski 1995a). by definition, saturated data ensure replication in categories, which in turn verifies and ensures comprehension and completeness (morse et al. 2002). the saturation law in this study was "three new texts do not add new code to the study" and "all extracted code can be included in previous categories". 3.4 selecting the unit of analysis in this research, we selected the sentence as unit of analysis. because the meanings we want to extract are infinitive phrases; so the sentence size seems to be appropriate. 3.5 categorization and abstraction after each text was coded, codes were shifted to the codebook. then the codes were reexamined and grouped. groups that had overlapping meanings built the abstract categories of the research. this process continued until saturation of categories was reached. co-researchers checked the categories to ensure no overlap between categories and concepts, and then overlapping categories and concepts were integrated. in the next step, several experts in si were asked to examine the conceptual similarity between categories and concepts. in this way, fourteen abstract categories were identified as si subprocesses. 3.6 interpretation for avoidance of excessive interpretation, only clear and unambiguous sentences were selected for open coding, and hidden concepts in the texts were ignored. according to elo et al. (2014) co-researchers checked out all analyzing process steps. 3.7 representativeness face validities were used to improve the trustworthiness of the research findings. some experts were asked to evaluate research findings, and their assessment was that the results are realistic. 4. findings fourteen main categories (sub-processes) were established to describe the si process: identification of strategic environments and prioritizing them, determination of organizational information needs and prioritizing them, determination of a monitoring period for each section of strategic environment and organization key information needs (kin), determine information sources and assess information capturing ways, external information scanning, internal information extracting, setting criteria for gathered information assessment, information filtering, categorizing and abstracting, information analysis, interpretation and sense making (intelligence generation), determination of intelligence users and intelligence distribution media, intelligence distribution, feedback from recipients, revision and adjustment, intelligence storage, and intelligence use. 4.1 identification of strategic environment and prioritizing them in the opinion of most of the contributors, the identification of important areas of the environment is one of the main activities in the si process. "dividing the environment into sectors to monitor is the first solution proposed" (cohen 2009, 144). "in a limited resource context or in a desire for efficiency and optimization, prioritization of sections and axes of surveillance seems vital to ensure the effectiveness of surveillance practiced" (cohen 2009, 148). therefore, in order to achieve the expected outcomes of a si system, the strategic areas of the organization's environment should be identified and prioritized. 4.2 determination of organizational information needs and prioritizing them some contributors identify the beginning of the si process by ascertaining the organization's needs and problems. according to mcdowell (2009), si is an organizational level of analysis issue and deals with issues and problems which are identified in the structure, goals or nature of organizations so one of the important steps in the si process is to recognize the organization's problems. "as the first stage of the intelligence cycle, the strategic intelligence system is concerned with the establishing of parameters for what information is 21 required, what priorities should be established, and what indicators should be monitored" (kruger 2010,110). 4.3 determination of monitoring period for each section of strategic environment and organization key information needs (kin) nowadays, constant changes are one of the main characters of the organizational environment. for this reason, some authors, considering the perceived uncertainty of different parts of the environment, embedded the determination of monitoring period for each section of strategic environment and organization key information needs as essential activities in the si process (kruger 2010, cohen 2009, montgomery and weinberg 1998). 4.4 determination of information sources and assess information capturing ways information overflow convinced some authors that planning for identifying relevant, reliable, valid, and up to date resources makes the process of si more effective and prevents overflow of information and its related costs. according to cohen (2009, 157): "to ensure the effectiveness of information collection and to avoid wasting corporate resources, which are by definition limited, it is necessary to select information sources and the most valuable information". 4.5 external information scanning and internal information extracting almost in all of the texts which were analyzed, information gathering activity was identified as the most important phase of the si process. according to marchand and hykes (2007, 5) the collecting phase, which "focuses on ways of gathering information that are relevant and potentially meaningful" one of the steps that makes the si process effective. but the origin of the gathered information led to some disagreement among authors. on the one hand, some authors (for example, kruger 2010, cohen 2009, marchand and hykes 2007) believed that the internal environment of an organization's information gathering system and external environment of the organization's information gathering are the same; on the other hand, there are authors (xu and kaye 2007, montgomery and weinberg 1998) who believed that these two areas have different information gathering approaches. 4.6 setting criteria for gathered information assessment most authors agree on the evaluation of the information gathered. however, some have recommended setting criteria for the evaluation of information: "in other words, volume, diversity and quality of information sources, and the existence of control to verify value seem vital for the effectiveness of surveillance" (cohen 2009, 159). while others only assess the validity and reliability of information: "[analysis of gathered information] simply cannot occur until and unless the collected information has been brought together in appropriate sets and then considered for its reliability, relevance, and believability value" (mcdowell 2009, 195). 4.7 information filtering, categorizing and abstracting in recent years, most authors have emphasized categorizing and abstracting refined information. they believe in the benefits that these activities bring. these activities save time and money for the organization and provide a more effective analysis of the data. some even believe that this activity should be done according to user preferences and feedback (ong et al. 2007). 4.8 information analysis compared to the research and collection phase, there is not much said in the literature about the other phases of the si process, in particular the information processing phase, which is central to the activity of si (cohen 2009). the difference between the authors in this phase is their attitude to the method of analysis. cohen (2009) has focused more on the introduction of analytical techniques and their application for information processing, however mcdowell (2009) has suggested instructions for preparing data, for methods of selecting an analysis tool, and auxiliary resources for information processing. 22 nonetheless, the goal of the authors was to turn data into information. that is, the output of this stage should be a meaningful and believable piece of information. "analysis creates information by linking data together and identifying patterns and trends" (brouard 2007, 124). 4.9 interpretation and sense making (intelligence generation) some authors who have written in the field of si believe that information analysis is not enough to generate intelligence. in the opinion of this group of experts, the interpretation of the analyzed information creates intelligence and advice for action. but there is no consensus on how to interpret information and generate intelligence. in daft and weick’s (1984) point of view: "interpretation pertains to process by which managers translate data into knowledge and understanding about the environment. this process will vary according to the means for equivocality reduction and the assembly rules that govern information processing behavior among managers" (291). 4.10 determination of intelligence users and intelligence distribution media almost all contributors have confirmed that the si user's identification and determination of si finding distribution media are activities in the si process context. "the first problem is to distribute the information to the right recipients, i.e. those interested by it and liable to use it." (cohen 2009, 179). "the distribution of the products of surveillance activity be by written, oral, electronic channels, etc. numerous and varied. some studies list the most widely used methods of information distribution" (ibid 180-81). 4.11 intelligence distribution in many references about the process of si, considering the distribution of intelligence is a key part of the process (kruger 2010; mcdowell 2009; brouard 2007; ong et al. 2007; xu and kaye 2007; montgomery and weinberg 1998). according to cohen (2009, 179): "the role of distribution in [si] surveillance effectiveness is therefore obvious: information which is collected, processed, stored but not distributed is not used, which reduces [si] surveillance effectiveness to zero." 4.12 feedback from recipients, revision and adjustment, intelligence storage the recipient’s feedback on transmitted information is recommended by many authors. it is the best way to improve the quality of information. they recommend the implementation of a feedback contract encouraging users to issue feedback on each item of information transmitted (cohen 2009; brockhoff 1992; prescott and smith 1989). 4.13 intelligence use most authors agree on identifying a separate phase in the si process as the intelligence use stage. mcdowell (2009) has called this phase "recommendations". daft and weick (1984) named this stage "strategy formulation and decision making". 5. discussion and conclusion strategic intelligence in the organizational level of analysis is an abstract phenomenon that exists only in the minds of organization members where it appears as cognitive maps of a socially constructed reality. it enacts inter-subjectively in nature. those who coined this term’s intention was to respond to the information needs of decision makers at the strategic level of the organization (seitovirta 2011, liebowitz 2006, miller 1996). to make an inter-subjective meaning, share an opinion and understand this phenomenon, si components and steps describing it seem essential. a process that develops an organizational strategic intelligence consists of fourteen sub-processes. the way each of these sub-processes is implemented depends on the organization's age and size, and perceived complexity of the organization's environment by top managers (daft and weick 1984). one of the weaknesses of the qualitative content analysis method is that it does not provide tools for modeling or prioritizing classes and concepts created (elo and kyngäs 2008). for this reason, the sub-processes identified in this research do not have the order or priority. the process modeling of these sub-processes needs further research. 23 si in the organizational level of analysis is a term which is used to describe some intelligence activities. these activities are meaningful in the context of strategic planning and strategic management (marin 2015). si is about creating a shared common understanding of the internal and external environment in an organization member's minds. whenever these shared understandings are created in the organization it can be assured that appropriate strategies are selected; which are appropriate to the circumstances and the nature of the organization (pirttimäki 2007). for an organization to have an si attribute, it must do the following activities in some ways: (1) identification of strategic environments, (2) determination of organizational information needs, (3) determination of monitoring periods, (4) determination of information capturing ways, (5) external information scanning, (6) internal information extracting, (7) setting criteria for gathered information assessment, (8) information filtering, categorizing and abstracting, (9) information analysis, (10) interpretation and sense making (intelligence generation), (11) determination of intelligence users and intelligence distribution media, (12) intelligence distribution, (13) feedback from recipients, revision and adjustment, intelligence storage, (14) intelligence use. 6. references bali, r.k. and wickramasinghe, n. and lehaney, b. 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(ed). managing strategic intelligence. pp. 36-53. hershey, pa: information science reference. microsoft word content accessibility and semantic networks processed on foreign natural language analysis.docx content accessibility and semantic networks processed on foreign natural language analysis bernard dousset, anass elhaddadi, josiane mothe * * institut de recherche en informatique de toulouse, irit umr 5505 université de toulouse, université paul sabatier 118, route de narbonne, f-31062 toulouse cedex 9 (france) dousset@irit.fr haddadi@irit.fr mothe@irit.fr received 1 june 2011; received in revised form 1 august 2011; accepted 15 december 2011 abstract: in this paper we present a methodology that makes it possible to mine a document collection from a domain without knowing the language in which the documents are written. we describe in detail a method, tools and results that can be used within a digital library context for science watch and competitive intelligence. we consider a collection associated with the aquaculture domain written in chinese and extracted from a digital library. based on the original coding (unicode) of the data and the tag marking the structure of the documents, we extract key elements (authors, phrases, etc.) from within the domain and analyse them. the results are displayed in the form of graphs and networks. we extract people networks and semantic networks before examining their evolution over a period of several years. the principles developed in this paper can be applied to any language. keyword: text mining, graph, semantic network, social network, weak signals, competitive intelligence. 1. introduction accessing information generally implies that the user understands the language that a document is written in. to counter the problem of reading documents in a language with which the user is not familiar, online translators can be of assistance. indeed such translations are available, for example, from google or systran. however, reading an entire document translated using a machine is not entirely satisfactory: some sentences can be difficult to understand, particularly when the original document is written using long sentences or a language which is rich some tasks involve reading many documents, particularly in relation to decision tasks or scientific monitoring. in this paper we consider a related problem, the analysis of a large collection of documents extracted from a digital library where the documents focus on a particular domain. in specific terms, the problem we tackle is the analysis of available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 5-18 6 semantic and people networks from documents written in a foreign language, that the user does not understand. these networks are first created by considering the entire set in a homogeneous form; then we suggest a method to analyse partitioned sets the information is broken down according to the period of time in which it occurs and several periods are fused together so that development of people networking activities can be easily observed. in order to analyse these documents and extract these networks, when the language used in the documents cannot be understood, we set forth a method based on the extraction of n-grams. in the case of chinese, for example, the analysis is based on n-grams of ideograms that correspond to key elements from within the domain (authors, journals, keywords, etc.). more specifically, we take advantage of the structure of some resources to extract key elements such as phrases taken from editors’ keywords and we build dictionaries. these dictionaries are used to analyse free text, either directly or by cross referencing reliable elements with other extracted elements using statistically-based automatic methods. to illustrate our method, we describe the analysis of a document set extracted from the scientific digital library in the chinese scientific journals database (cqvip). we also give some clues on how to manage other resources in a similar fashion, such as the al jazeera information site in arabic and an on-line korean collection, ekoreanstudies.com. this paper is set out as follows: we first present some related work in section 2, then we present the method for chinese. section 3 presents the raw data and the pre-processing before analysis can take place. the analysis is presented in section 4. section 5 presents other examples with arabic and korean. section 6 concludes the article. 2. related work many articles take into account the problem of document access when documents are written in a language that the user is not familiar with or does not use as a primary language. in cross-lingual retrieval for example, users query information corresponding t o their information needs using their own language and the system retrieves documents written in a foreign language (peters 2009). many approaches are employed to resolve this problem. query translation is one of them (he, wang, oard and nossal 2003) (lu, xu and shlomo 2008). reading documents which are not written in a language the user is familiar with is a major issue. li, cao and li (2003) present an english reading-assistance system that suggests translations of words and phrases based on mining techniques. gaolin, hao and fumihito (2006) show a method to predict possible english meanings according to each component of a chinese term. the second aspect we study in this paper refers to the automatic extraction of people and semantic networks based on the mining of scientific publications. analysing scientific publications to discover trends and understand the structure of a scientific field and the evolution of scientific communities or topics has been widely explored in literature, in particular, but not exclusively, in scientometrics (leydesdorff 1995). different types of analysis can be undertaken. in information science, citation and co-citation analysis have been studied in the past as a mean of monitoring scientific activities (white and mccain 1998) (white 2003). citation analysis is used to identify core groups of publications, authors and journals. conversely, co-citation analysis is used to detect networks of authors or to map topics and authors or journals (white 2003) (zitt and bassecoulard 1994). groupings other than authors can be used for the purposes of correlation analysis. mining scientific publications such as keywords, journals, etc. are presented in mothe and dkaki (1998). digital libraries usually deliver results in the form of lists of related elements (lists of related publications or authors) even though it has been shown that graphical interfaces play an important role in displaying the results of analysis to users (chen 2002) (geroimenko and chen 2002). in this context, graphs or networks are powerful methods of visualisation, mainly because linking concepts or elements together is a common mining technique. another reason is that a network is easy to understand, even by a naïve user. in mothe, chrisment, dkaki, dousset and karouach (2006) scientific publications are mined in order to highlight groups of authors and their geographic relationships. this paper extends on an earlier work by dousset (2009). this new version aims at spreading the results for an international reach. 3. chinese as a case study 3.1 raw data we considered the scientific digital library (dl) http://www.cqvip.com. the dl brings together a large number of chinese scientific publications (figure 1). a search engine is available on the main page of the site to retrieve documents in response to a query in chinese (figure 2). since queries can be just a few words, it is easy to write a query in chinese corresponding to the field of interest by simply taking any dictionary or translator. for example, “aquaculture” in french corresponds to “aquiculture” in english and “ ” in chinese. next we can click on the relevant button to obtain the first references (some of the fields are hidden). several options are then possible: gather the references as visualized by copypasting to an editor such as ms word, download all the fields, or ask an engine to download everything. for example, we managed to select 3,000 references in the aquiculture field from 2004-2007. since the information is coded in unicode format (in the form “&#12345;”) it is possible to extract n-grams or sequences of ideograms that correspond either to keywords or to actors in the field (newspapers, conferences, organizations, laboratories and authors). free text (title and summary) can also be used in order to detect new sequences of terms that may be unknown to domain experts. 7 3.2 re-encoding the data there are several goals for this phase: to eliminate text formatting and corresponding tags (html in our case) which do not bring any content, but which correspond to 90% of the file size to rebuild text strings which are split because of formatting to tag the texts again using ascii tags (in our case we use tags in a similar way to many digital libraries: ti for title, au for authors, etc.). such tags may exist in the original version. in this case they are translated from chinese to english. some tags are not visible on the internet browser, but occur in the texts; these should be kept to add new tags to the text by analysing the initial html tags to retain the information which is coded in latin characters or arabic numerals such as dates, numbers or western names (authors, technical formulas or elements). this re-encoding is based on a parser and some re-writing rules as illustrated in figure 3. 8 figure 1: cqvip.com interface the search engine is at the top of the figure. figure 2: cqvip.com interface – the results are displayed. figure 3: re-encoding cqvip data google translation followed up by information figure 4: a bibliographical reference that has been re-coded (tags in ascii and content in chinese unicode) and the corresponding metadata. 9 figure 4 illustrates the results. tags are written in ascii whereas text (content) is in unicode. for example, in the c2617138 reference from figure 4, the publication title, first author of the publication, the journal in which it has been published, and the publication date constitute the beginning of the document. these information elements are tagged using the following field tags: ti:, au:, jn:, dp. when analysing the document visually, we can see that it consists of 3 authors (3 chinese ideograms = 3 codes), only one organization, 8 keywords (here each keyword is composed of 2 to 5 ideograms), the journal and one date (2006). we see thereafter that the title and the abstract are analysed using a specific semantic process in order to detect repeated n-grams of ideograms that in fact do not correspond to any of the keywords. this adheres to a terminology that is not included in the initially provided indexes. metadata (at the bottom of figure 4) describe the new format of references: complete name for each field and its abbreviation, exact identifier of the field in the reference (ex: ti: for the field title). true means that this field will be used in the analysis, separators used to cut out text (character string, “\n” for carriage return, etc.). figure 5: google translation 3.3 translation problems authors’ names to understand unicode (and hence chinese), we list dictionaries that gather the correspondences between the names of authors in chinese and their translation into phonetics (pinyin) using the translator from google. but in so doing, two difficulties arise: google fails when translating some of the names and in this case keeps the unicode (see 7th author figure 5) several authors with different codes can be translated to give the same name. the ambiguity has to be corrected before any analysis takes place in order to avoid analysis mistakes. in this case there is a failure in the translation process. we chose to keep the codes, but where there was ambiguity we added a code that helped to differentiate the names (e.g. li1, li-2 and li-3 refer to different translations that led to li). keywords another translation problem can arise in relation to technical terminology (keywords, additional indexing, full text) because automatic translators struggle when the terms do not appear in their dictionaries (terms that are too technical or too recent), the context or the sentences are too complex or there is some ambiguity. most of the time this uncertainty is resolved during the analysis itself: term clusters, for example, help to understand a term because they occur with some terms that have been correctly translated. the problem is very similar for keywords associated with a particular publication. indeed, some keywords, which are different in unicode, are translated similarly by translation engines. this phenomenon is fortunately rather rare and hence does not fully compromise the interpretation of the analysis. of course, at the final stage, the views of an expert in the language are welcome. figure 6 presents the first phrases of the synonym dictionary based on the keyword field of the documents; it gives the correspondence between chinese terms in unicode and their google translation in english. the number of occurrences of the terms is then calculated for english, thus the occurrences of a term may correspond to the sum of the occurrences of different chinese terms. in the example of figure 6, the most frequent term is “aquaculture”; it combines the occurrences of several chinese forms. even if the fusion is less problematic than in the case of homonyms found in particular authors, there is a risk here of losing some of the differences between the terms. 10 figure 6: unicode and corresponding phrase translation and synonyms (left side), phrase occurrences (right side), extracted from keywords. figure 7: extract from the journal dictionary. other problems for journal names there are no real problems. however, for the names of organizations the problem is that several forms can exist in different documents. this is mainly due to the way addresses are written. we therefore constructed a dictionary that brings together the different versions of the name of any given organization. 4. analysing aquaculture in china 4.1 social networks as explained in the previous section, to begin with, authors’ names are translated into english; then we resolve the problem of english homonyms where chinese names have been translated. next we create a cross referencing table that cross references the authors’ names; in this cross referencing table we consider authors that have written at least two publications. indeed those who have published only one publication are not of any help when trying to extract relationships between authors. figure 8 presents the topology of the main teams. we can immediately see that there is very little co-authoring in the chinese scientific publications we analysed. a second observation is that the teams are generally directed by a main author who has control of 2, 3 or 4 distinct sub-teams. notice that in the figure some names are not translated, whereas others are translated word by word and mean something in english. this has no impact on the results of the analysis. • &#21476;&#32676;&#32418; ancient group of red • &#37329;&#24425;&#26447; apricot jincai • &#21556;&#26089;&#20445; as early as paul wu • &#23391;&#21644;&#24179; bangladesh peace • &#34013;&#27491;&#21319; blue is up 11 • &#21830;&#24503;&#31456; business ethics chapter • &#21830;&#19975;&#25104; business wancheng • &#34081;&#31168;&#20029; cai beautiful • &#34081;&#24314;&#22564;cai embankment • &#38472;&#22269;&#20820;chan kwok-rabbit • &#31456;&#31179;&#34382; chapter autumn tiger • &#38472;&#26435;&#20891; chen the right to military • &#37011;&#27491;&#33829; deng zhenglai business • &#30224;&#33673;&#33805; die in a prison liping • &#21035;&#25991;&#32676; do not text-qun • &#33891;&#22312;&#26480; dong in the kit • … 4.2 semantic networks in the same way it is meaningful to cross reference the keywords suggested in the documents and thus to extract a map of the terminology chosen by the editors or authors of the publication via the keyword field. of course, using the keyword field does not help much to extract weak signals or novel signals because usually the keywords are more common terms. conversely, strong signals and domain diversity are elements that we can extract. figure 9 displays the terms, which are circled in figure 10, belonging to one of the extracted term clusters. this figure displays the entire semantic network extracted from the analysed data. 4.3 analysing evolution evolution can be analysed and visualized in many ways. in the next sub-sections we first analyse evolution by taking into account the correlation that exists between journal names and dates. then we consider the evolution of social networks or relationships between authors over time. 4.4 correlation between time and journal names in this section we analyse the profile of how the journals in which authors published during the four years of the study, namely 2004 to 2007, evolve. correspondence analysis (mardia, kent and bibby 1979) (loubier and dousset 2007) applied to the cross referencing table in which the two dimensions are journals and dates (jn x dp) allows us to visualize the various profiles on a regular tetrahedron (one dimension for each year) presented three dimensionally in figure 11. in figure 11, top left corner, the sub-figure shows the years only and their corresponding direction with regard to the factorial axes. the same projection is applied to the journals in the rest of the figure, for example, in the top right corner the journals are those associated with 2007, meaning that they are associated with 2007 only, i.e. they are probably new journals or journals that have been recently integrated into cqvip. on the edge of the tetrahedron the journals appear in the data collection over a 2 year period (for example 2006 and 2007 are on the edge of the right hand side of figure 12). journals that appear over a 3 year period lie on one face of the tetrahedron. finally, those appearing over a 4 year period are displayed inside the tetrahedron and converge towards the year in which they appear most frequently. 4.5 evolution of author relationships a second method consists in using a three dimensional cross referencing table where two dimensions represent the authors (thus co-authoring is represented) and the third dimension corresponds to time. we can then visualize the evolution of the author network on a graph. this graph is developed in roux (2009). time is distributed chronologically on a circle like the hours on a clock. the nodes corresponding to authors are attracted by these artificial nodes and are positioned towards the centre of the graph if they occur within the four time periods. on the contrary, the author nodes tend to be positioned in the direction of the corresponding reference when the author appears only once. they tend to be in a central position if the author appears in several consecutive periods. figure 12 displays this network. at the bottom left corner, for example, the authors associated with 2006 are the only ones to appear. this space-time analogy is similar to the correspondence analysis presented in figure 11, to which graph drawing techniques can be added. we obtain a graph which shows the main teams (as in figure 8) with their respective evolutions. the colour histogram attached to each node indicates its quantitative evolution; the end time period is represented in green whereas the one that indicates the beginning is represented in red. the position with respect to its collaborative nodes indicates the time of the author’s involvement with the team. the node bonds specify with whom and how long the collaboration lasted. figure 12 brings together the evolution of the main chinese teams in the field of aquaculture. some specific collaboration continues whereas others can be seen as emergent. moreover there are collaborations that either finish for a period of time or stop altogether. it is easy to locate the leaders of the author groups; indeed the size of each histogram is proportional to the appearances of the author in the collection. it is also easy to extract the authors that appear in the end year only (green) or in the beginning year (red). finally figure 12 also shows the main authors who are responsible for the connections between teams, for example, when considering the team represented at the top of figure 12, the only leader who still publishes in the last period is chen changfu. he used to collaborate frequently with meng chang-ming until 2006. he headed two separate teams of collaborative authors in 2004, worked with shen ke ray in 2005 and with one team consisting of 2 authors in 2006. in contrast, the three teams on the left side of figure 12 have many emergent authors and long-standing leaders. other teams disappeared; the four on the right hand side in 2006. this analysis can be completed using a correspondence analysis based on the same three-dimensional cross referencing tables. this analysis shows the trajectories of the authors when they collaborate with other authors. in the data we analysed, no such mobility could be extracted. 12 figure 8: social network analysis extraction of the main teams by authorship. figure 9: terms belonging to one of the extracted term clusters. feed additives, nutrition, spirulina, nutritional value, immunity, garlicin, bait, toxic substances, photosynthetic bacteria, photosynthesis, nitrobacteria, water purification, feed utilization, bacilius, probiotic, industry self-regulation, mechanism, kind, water quality, etc. 13 figure 10: semantic network based on the keywords from cqvip. figure 11: visualising the results of a correspondence analysis on the first axes – journals x dates cross reference table. 14 4.6 semantic analysis of free text we use the dictionary of keywords we built and of which we present an extract in figure 6, including a stop-word list and a dictionary of synonyms (terms that are known to have similar meaning), to analyse the free text. free text from the title and the abstract field of the documents is first reduced to chunks of text using punctuation. the n-grams of ideograms corresponding to the known keywords (from the keyword field) are then extracted from the text and completed by new n-grams of ideograms extracted automatically according to their frequency. these new phrases of ideograms, that can include existing keywords, are translated into english in order to try to understand their meaning. if the translation we obtain using an automatic translator is meaningful with regard to the context but corresponds to a new term, then it is vital to have access to an expert in order to understand the context for this term and to confirm that it is an important term for the domain. these terms can correspond to important terms that are missing in the keyword field. alternatively, we can analyze whether these new n-grams form clusters or not. this can be carried out by analyzing their co-occurrences in the document set. in this findings is to cross reference the new term with the other extracted elements (authors, organizations, keywords, journals and dates) and consider those that are related. this will be explained in the next section. using this approach and without knowledge of a language it is thus possible to detect implicit information that occurs in the corpus and which is inaccessible from a simple reading. the detection of the weak signals is in fact much in demand by decision makers because it corresponds to the need to detect innovation in order to make the right decisions (new avenues to explore, new products to use, etc.). figure 13 presents a list of detected terms (new n-grams of ideograms) and an emergent semantic cluster. 4.7 detecting weak signals to detect weak signals, we first extract the keywords and the known terms from the title and abstract. then we detect the new sequences that exceed a number of occurrences. afterwards we cross reference these new n-grams with time and we keep only those that occur frequently during the end time period ( here 2007). finally these terms are crossreferenced (co-occurrence) and we sort the subsequent matrix to obtain diagonal blocks. each block represents an emergent concept identified by a new terminology which does not exist figure 12: networking and evolution of the main teams (co-authoring). 15 in the keyword field and which only occurs in some documents. weak signals can then be validated by cross referencing them with all the other fields and in particular the keywords. in figure 14, part a) we represent the cross referencing matrix; each plot indicates a non-nil value for the cross referencing. along the diagonal of the matrix, a certain number of clusters consist of new terms and correspond to a semantic group. each cluster is extracted in a square sub matrix and can be visualized in the form of a semantic graph (figure 14 b.). this information should then be submitted to an expert in the field for verification. &#20859;&#27542;&#22616; breeding pond &#20859;&#27542;&#21487;&#25345;&#32493;&#21457; &#23637; sustainable development of aquaculture &#20859;&#27542;&#25345;&#32493;&#20581;&#24247; sustained and healthy development of &#20859;&#27542;&#27827;&#34809; breeding crab &#20859;&#27542;&#33337; culture vessel &#20859;&#27542;&#33391;&#31181; breeding improved varieties &#20859;&#27542;&#22823;&#33777;&#40070; cultured turbot &#20859;&#27542;&#20892;&#25143; aquaculture farmers &#20859;&#27542;&#30149;&#21407;&#20307; breeding of pathogens &#20859;&#27542;&#24037;&#20316;&#24231;&#35848; work culture forum &#20859;&#27542;&#24687; farming income &#20859;&#27542;&#39640;&#20135;&#39640;&#25928; breeding high yield and high &#20859;&#27542;&#32463;&#27982;&#25928;&#30410; economic benefits of aquaculture &#20859;&#27542;&#32599;&#38750;&#40060; tilapia culture &#20859;&#27542;&#34691;&#34809; breeding crabs &#22823;&#27700;&#20135;&#20859;&#27542;&#25143; large aquaculture households &#27700;&#20135;&#21697;&#28040;&#36153; consumption of aquatic products &#27700;&#20135;&#21697;&#20986;&#21475; the export of aquatic products figure 13: new terms extracted from free text that do not occur in the keyword field. 16 figure 10: analysis of newly detected terms and their clusters 17 5. further analysis: arabic in this section we briefly present two other examples of resources on which an analysis can be carried out using the method we presented in the previous sections for chinese. unicode utf-8 can be extracted from the html source code. with regard to the first example, al jazeera, the originality is able to analyse the reactions of the blog users (see figure11) and with regard to the korean library we chose to analyse, we can see that the scale of the characters devoted to this language is different, but that the principle of analysis remains the same (see figure 12). no matter what the collection and the data are, the challenge is to detect tagging that enables us to extract elements of information and hence build the cross referencing tables (actors, semantics, dates, etc.). dictionaries of keywords and expressions are also very useful in the treatment of free text and in the detection of innovation therein. figure 11: aljazeera.net (document brief and associated blog) ideogram of a korean term and the corresponding utf-8 code figure 12: korean from www.ekoreanstudies.com 18 6. conclusion the cqvip library on which we carried out this analysis represents an example of the multiple sources that can be analysed using the method we present throughout this paper. any language can be treated in the same way. however, some issues have to be resolved in order to make this process fully usable and some additional work has to be undertaken: building dictionaries (terms, etc.) and translating them into english (and/or into another language) treating the named entities (for authors, organizations or journals): an automatic translation is sufficient, but there remain many ambiguities that have to be dealt with (importance of accents, pronunciation, context) the translated terms obtained by translating new detected terms or phrases with statistics will not be part of traditional dictionaries, either because they are too new or because other forms will be referenced. checking the validity is an issue if no expert is available to validate manually. in future work it will thus be necessary to contemplate collaboration between different domain experts in: text and data mining -natural language processing (semantics, morphosyntaxic, ontologies, etc.) languages (chinese, korean, japanese, arab, etc.), 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(2016) early warning: the role of market on entrepreneurial alertness. journal of intelligence studies in business. 6 (2) 34-42. article url: https://ojs.hh.se/index.php/jisib/article/view/158 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index early warning: the role of market on entrepreneurial alertness bahare ghasemia and aligholi rowshana auniversity of sistan & baluchestan, department of management and economics, zahedan, iran; bahare_ghasemi1989@yahoo.com and salirowshan@yahoo.com journal of intelligence studies in business please scroll down for article early warning: the role of market on entrepreneurial alertness bahare ghasemia* and aligholi rowshana* a university of sistan & baluchestan, department of management and economics, zahedan, iran *corresponding authors: bahare_ghasemi1989@yahoo.com and salirowshan@yahoo.com received february 2016; accepted september 2016 abstract given the growth and role of entrepreneurship today, it is becoming increasingly important to understand how new entrepreneurial opportunities get developed. discussions of the emergence of new entrepreneurial opportunities often include “eureka” moments, but our understanding of how new opportunities get brought forward is limited. we attribute the difference to a loosely defined quality that kirzner called “entrepreneurial alertness”. other market actors do not have the responsibility to create innovative market opportunities although they do have an obligation to consider such opportunities once they are available in the marketplace. consequently, understanding the opportunity identification process represents one of the core intellectual questions for the domain of entrepreneurship. so question of this paper is how are market environments represented and interpreted in the mind of the entrepreneur such that opportunity identification occurs? and what factors impress on it? to achieve this goal we distribute questionnaires between 115 m.a. students from economics and management college of university of sistan & baluchestan for the years 2012 and 2013. analysis was done by correlation test. results showed that there is significant relationship between market disequilibrium, accuracy vs. timeliness, schema complexity, counterfactual thinking, frame-breaking and sensitivity to profit potential and student’s entrepreneurial alertness; but the relationship between ignorance of new resource and excessive optimism or pessimism about resource and student’s entrepreneurial alertness was not significant. keywords counterfactual thinking, early warning, entrepreneurial alertness, framebreaking, market disequilibrium, sensitivity to profit potential 1. introduction entrepreneurship research is dominated by the fundamental questions of why it is that only some people see new business opportunities and only some people take actions to exploit the opportunities they do see (shane and venkataraman, 2000; venkataraman, 1997). as pointed out by https://core.ac.uk/download/pdf/6836212.pdf “empirical observation suggests that individual people can differ widely in their ability to see new business opportunities within a given situation. some see nothing but constraint and status quo, while others see attractive new opportunities lurking everywhere. the social and economic impact of these differences is enormous, as the economic actions taken by entrepreneurs can have wideranging effects on the provision of valued products and services, on the creation and smooth operation of new markets, and on regional socio-economic development”. journal of intelligence studies in business vol. 6, no. 2 (2016) pp. 34-42 open access: freely available at: https://ojs.hh.se/ 35 once spotted, the opportunity may be recognized as essentially complete in itself or requiring additional development and creative acts by the entrepreneur to become an opportunity worth exploiting. much recent research has been devoted to better understand the diverse range of opportunity types and the corresponding entrepreneurial actions (e.g., eckhardt and shane, 2003; sarasvathy et al., 2005). but these are ex post distinctions that only arise once the entrepreneur has already perceived or enacted the initial market need or underutilized resources, recognized a fit between market need and underemployed resources, and created a new fit (ardichvili et al., 2003). in a reciew by gaglio & katz the authors explain: “shaver and scott (1991) pose the salient psychological questions: how are market environments represented and interpreted in the mind of the entrepreneur such that opportunity identification occurs? do these representations and interpretations differ from those of other market actors? if so, in what ways? “kirzner (1979) asserts that the mental representations and interpretations of entrepreneurs do indeed differ because they are driven by entrepreneurial alertness, a distinctive set of perceptual and cognitive processing skills that direct the opportunity identification process”. the key question of this paper is how market place represents and interprets in the mind of entrepreneur and what factors impress on it? 2. literature review 2.1 entrepreneurial alertness alertness has been central in the context of the recently developing area of “opportunity” in entrepreneurship research. some of this research argues that either opportunities are discovered or they are created (short et al., 2010). another approach parcels it into the three areas of opportunity recognition, opportunity discovery, and opportunity creation (sarasvathy et al., 2003). research on entrepreneurial alertness was initially developed by kirzner (1973, 1979), who characterized individuals who were more alert as having an “antenna” that permits recognition of gaps with limited clues. according to kirzner, entrepreneurial alertness refers to “the ability to notice without search opportunities that have hitherto been overlooked” (kirzner, 1979, p. 48), “a motivated propensity of man to formulate an image of the future” (kirzner, 1985, p.56), “an attitude of receptiveness to available, but hitherto overlooked, opportunities” (kirzner, 1997, p.72), or “a sense of what might be ‘around the corner’, i.e., the sense to notice that which has hitherto not been suspected of existing at all” (kirzner, 2008, p.12). building on kirzner's work, kaish and gilad (1991) saw alert individuals as having a “unique preparedness” in consistently scanning the environment ready to discover opportunities. later kirzner argued that alertness includes creative and imaginative action and may “impact the type of transactions that will be entered into future market periods” (1999, p.10). these various definitions, while intuitively illustrative, lack an explicit theoretical underpinning. clearly, though, entrepreneurial alertness is presented as conceptually distinct from the subsequent development of the opportunity, and from the activities undertaken to subsequently exploit the opportunity. and, while entrepreneurial alertness may work in conjunction with explicit environmental information search behaviors, it is more generally a state of mind that is open to opportunities at all times (busenitz, 1996, p.43). an entrepreneur must be highly sensitive to the key characteristics of schemas, so that he can quickly and accurately activate schemas in an ambiguous scenario to notice the emergence of opportunities. the alertness is reflected by the efforts spent to gather information, or the abstraction from such information of clues indicating commercial opportunities. it is also a kind of “sharp evaluation” that enables entrepreneurs to capture the flash of insight when facing opportunities to perceive the potential opportunities quickly. baron (2006) makes the case that this alertness to new opportunities is based on pattern recognition. he argues that what makes an entrepreneur alert is some cognitive capacity to support the recognition that one situation is similar to another in a meaningful way, that at some abstract level the two situations both resemble some common template or cognitive framework. from this recognition of a common pattern, the entrepreneur can make reasonable predictions of the future and can use these to plan new business moves. but baron's argument leaves open the questions of what these frameworks are and how they are developed and used. 36 entrepreneurial alertness is not solely the domain of the equilibrium-seeking arbitrageur entrepreneur ascribed to kirzner, but applies equally to the equilibrium-destroying creativedestruction entrepreneur of schumpeter (1942). both types of entrepreneur need to be alert to opportunities, whether in the conditions of the present or in the conditions of the hypothesized future (kirzner, 2008). 2.2 market 2.2.1 recognizing events of disequilibrium what would an alertness schema contain and how would it work if it were to lead to a more accurate or superior assessment of a market situation? kirzner (1979, 1985) posits that the alert individual is especially sensitive to signals of market disequilibrium, which can occur at the macroeconomic and microeconomic levels. macroeconomic disequilibrium is the most common form at the moment and in kirzner’s theory, the less considered form. in this situation, market disequilibrium arises from disruptive changes brought about because of new technology, knowledge, demographics, or social values that, as drucker (1985) observed, force industries to reinvent themselves through radical innovation. therefore, it seems logical to expect an alertness schema to include mental models of these kinds of changes and specifically extensive representations of the kinds of signals or cues that would indicate not just the presence of these disruptions but more importantly, to their potential presence. indeed, it is probable that an alertness schema directs attention and focus to search for anomalies, the unexpected or anything remotely new or different. non-alert individuals are not necessarily oblivious to major disruptions in the marketplace. when anyone encounters something different or unexpected that is signaled in a clear, unambiguous, strong and persistent way, he or she will attempt to accommodate the new information (fiske, 1993). weick (1995) notes that these kinds of disruptions trigger extensive “sensemaking” efforts within organizations; research suggests that the context or framework used for sensemaking may lead non-alert actors away from the conclusion that an entirely new assessment is needed. while disruptive macroeconomic market changes are forceful and generally more easy to discern, they are only one source of market disequilibrium. the other source is microeconomic – a less dramatic form but one that has the advantage of being ever present because it is inherent in the marketplace. ongoing microeconomic market disequilibrium arises from the everyday mistakes market actors make in their investment, production, and distribution decisions and actions. these mistakes create pockets of disequilibrium, which become evident as underpriced products, unused capacity, unmet needs, and so on. in more popular terms, these pockets represent market niches, the favored spawning ground of new business opportunities. once again, the key question is what would an alertness schema contain such that it facilitates the anticipation or detection of these mundane pockets of disequilibrium? it is entirely possible that alert entrepreneurs simply recognize the fact that misapprehension and bad judgment occur and they try to capitalize on it. we predict: h1: there is a significant relationship between recognizing events of disequilibrium and student’s entrepreneurial alertness. 2.2.2 changing schema vs. information schema theory assumes that people engage in a kind of pattern matching between environmental stimuli and the information stored in the activated schema (fiske and taylor, 1991; mitchell and beach, 1990). if the pattern match is good enough, attention turns to action and developing a response. if the pattern match is not good enough – that is, when the individual detects something unusual or unexpected, then additional cognitive processing is required. when actors are motivated to be accurate, they usually try to integrate the new information within their existing schema by creating new subcategories or new causal links that increase the differentiation and complexity of their schema (fiske and taylor, 1991; sherman et al., 1989). if the actor places a higher value on quick action or if he or she feels it is socially desirable to adhere to a schema, then the actor will either discount the new information or engage in elaborate reinterpretations that maintain the structure and dynamics of the existing schema (fiske, 1993; kiesler and sproull, 1982). given the nature of this cognitive dynamic, the theory of alertness would predict: 37 h2: there is a significant relationship between changing schema vs. information and student’s entrepreneurial alertness. 2.2.3 cognitive error control the failure to recognize and integrate information regarding market disequilibrium are not the only kinds of cognitive mistakes non-alert actors can make. kirzner (1985) identified several other assessment mistakes non alert individuals may make: (a) failure to recognize that assumptions were never or no longer are appropriate; (b) ignorance of new resource availability; (c) excessive optimism or pessimism about resource availability; (d) excessive optimism or pessimism regarding probable results of actions or decisions. the common thread in all these mistakes appears to be inaccuracy. the chain of inaccurate processing may begin with the non-alert individual simply following the human tendency to uncritically accept and use information only in its original form (the “concreteness principle,” slovic, 1972) or to unquestioningly accept the initial frame of reference (the “framing effect,” kahneman and tversky, 1986). if alert individuals are not making these kinds of cognitive processing mistakes, then it seems logical to conclude than an alertness schema includes a dynamic that induces skepticism about information perceived and that questions, if not challenges, the initial frame of reference. in fact, gunderson (1990) maintains that veridical perception simply means a willingness to challenge assumptions and perceptions, much like a good scientist. this leads to hypothesis 3: h3: there is a significant relationship between ignorance of new resource and excessive optimism or pessimism about resource and student’s entrepreneurial alertness. 2.2.4 accuracy vs. timeliness kirzner examines at considerable length the theoretical proposition that alert individuals have veridical (accurate) perception and interpretation. for example, the four forms of inaccuracy discussed above represent one type of threat to veridical perception. therefore, it would seem logical to conclude that accuracy is a major component of an alertness schema, perhaps even the driving force of the schema. from a psychological perspective, the issue of accuracy is somewhat problematic because accuracy can also be considered part of an individual’s motivation that triggers the activation of a particular schema. a central tenet of cognitive psychology is that people employ information processing tactics that best facilitate their goals (fiske, 1993; showers and cantor, 1985) and that one of the first decisions people must make, implicitly or explicitly, in any information processing episode is whether their goal is to be completely accurate or to act quickly. this stark choice minimizes a crucial and distinctive element of opportunity identification, that is its time limitedness. pockets of microeconomic disequilibrium can quickly change, be filled, or become exhausted. the window of opportunity when viewing macroeconomic changes is also limited and shrinks substantially as other actors see the opportunity and visibly exploit it. thus there is a need to balance perceptual accuracy with time-to-action or timeliness. even managers embedded in a corporate context recognize the time-limitedness of opportunities. weick (1979) argues that managers need to process information in ways that are just good enough to determine the course of action. he suggests that most managers stop their sensemaking activities when they have found the first plausible explanation or framework regardless of its accuracy (weick, 1995). isenberg’s (1986) detailed analysis of managerial decisionmaking appears to confirm weick’s supposition that managers feel more pressure to act than to be absolutely accurate in their analysis. in other words, what is proposed and observed in managerial decision-making is a simple application of march and simon’s (1958) satisficing concept where enough analysis is done to satisfy personal and peer expectations of adequate consideration and therefore, adequate accuracy. this leads to hypothesis 4: h4: there is a significant relationship between accuracy vs. timeliness and student’s entrepreneurial alertness. 2.2.5 schema complexity as noted earlier, an observable difference between experts and novices or between creative and non-creative individuals is the degree of schema elaboration, content complexity, and cross linkages with other schema. research into expert performance suggests that, beyond a certain level of preparation (which will vary by domain), experience and education do not inevitably lead to more elaborate and complex schema (bonner and pennington, 1991; camerer and johnson, 38 1991). what does lead to the increase in complexity necessary to achieve expert status are increasingly complex and hence veridical or realistic mental representations of causal patterns and interacting factors. the availability of these complex patterns as a single unit of information is the mechanism that produces comparatively more accurate, albeit very fast opportunity identification and problem solving in experts than in the novices (chase and simon, 1973; chi et al., 1982). therefore, we predict: h5: there is a significant relationship between schema complexity and student’s entrepreneurial alertness. 2.2.6 schema change – counterfactual thinking counterfactual thinking (e.g., what if; if only, etc.) is a fairly normal response to unexpected events (roese and olsen, 1995). however, we would expect alert and non-alert people to use counterfactual thinking in different ways. nonalert individuals most likely use the typical strategy for dealing with the unexpected which is to mentally undo the unusual circumstance that caused the unexpected outcome. mentally undoing the unusual highlights its abnormal quality but also shifts focus back to the usual, that is, towards normalcy. this kind of counterfactual thinking may be one of the cognitive mechanisms for discounting. on the other hand, if alert individuals increase the complexity of their schema and change their schema to accommodate novel events, we would expect alert individuals to mentally maintain the unusual circumstance and use counterfactual thinking to undo other elements in the causal sequence as he or she imagines how the unusual information will affect other elements or other schema. furthermore, it is possible that alert individuals undo several causal links, which would lead them to break the existing means-end framework. therefore, we would predict: h6: there is a significant relationship between schema change – counterfactual thinking and student’s entrepreneurial alertness. 2.2.7 schema change – framebreaking the alert individual’s extraordinary abilities in discernment that lead to a conclusion about changing times and events, while necessary, do not inevitably lead to the identification or creation of entrepreneurial opportunities. opportunity identification at this level (that is, breakthrough or innovative) depends on the alert individual using his or her insights about disequilibrium to recognize when it becomes necessary to radically reconfigure his or her understanding of the industry, or society, or the marketplace, or more probably, all three. kirzner (1985) refers to this as breaking the existing means-ends framework. he considers this step to represent the heart and soul of entrepreneurial alertness and to be the strongest point of difference between entrepreneurs and other market actors. nonentrepreneurial decision-makers focus on how to work effectively within the existing framework; that is, they attempt to make good decisions about how to allocate their scarce resources in order to maximize return. the belief that breaking the existing mean-ends framework is a necessary step for genuine innovation can also be found throughout the creativity empirical literature (amabile, 1983; csikszentmihalyi, 1996). given the central importance of framebreaking to the theory of entrepreneurial alertness, we would predict that alert individuals would be more likely to break the existing means-ends framework and indeed, there is some preliminary evidence that this is a crucial step in the identification of entrepreneurial opportunities (gaglio, 1997). h7: there is a significant relationship between schema change – frame-breaking and student’s entrepreneurial alertness. 2.2.8 sensitivity to profit potential finally, there is one more perceptual and cognitive component to an alertness schema based on kirzner’s theory of entrepreneurial alertness: the individual’s sensitivity to profit potential. this sensitivity can be reflected in the schema in at least two ways. first, the individual may direct his or her attention to find under-priced products, services, processes, and so on. secondly, the individual may include the question “how can i make money at this” as part of the assessment process itself. this situation is analogous to the differentiation in the innovation literature between invention and innovation. invention may involve the identification of a new idea or opportunity but it only becomes an innovation when the invention or idea is translated into a form that demonstrates its economic potential (kirzner, 1979; schumpeter, 1971; timmons, 1999). kaish and gilad (1991) tried to test this proposition in 39 their early study of alertness and found quite the contrary: founding entrepreneurs appeared to be more sensitive to downside risk while corporate managers were more attracted to the market potential. however, the data collection method used in their study (survey of past behaviors) relies on retrospection; this technique confounds the processes of opportunity identification and opportunity evaluation so, in fact, the question of sensitivity to profit potential still requires a definitive empirical test. it is entirely possible that alert individuals are more sensitive to commercial value of ideas and are able to quickly identify or create entrepreneurial opportunities but as they move on to implementation, they become more sensitive to the downside risks as it becomes more apparent that their careers are on the line with each new venture launch (ronen, 1983). mindful that theory development requires making important analytical distinctions such as that between opportunity identification and evaluation, we predict that at the identification state, alert individuals will be more sensitive to the commercial value or profit potential of facts and ideas. h8: there is a significant relationship between sensitivity to profit potential and student’s entrepreneurial alertness. 3. research method 3.1 sample and procedures the sample was composed of 115 m.a. students from the university of sistan & baluchestan for the years 2012 and 2013. to measure student’s attitudes towards these factors we use a questionnaire that contains four items in demographic information and 43 items in likert’s methods from 1 (very low) to 5 (very much). to ensure validity of the scale content, the components of the attitude area were determined. then, the researcher formulated for each section of the scale. these items were classified and arranged according to the content of each section of the attitude scale. before putting the scale in its final form, the researcher validated the scale by submitting it to a panel of experts in the area of research. the experts were requested to evaluate the items of the scale, and to suggest any changes they considered appropriate in terms of the objectives of the scale, item formulation, and their suitability to the level of the students. to estimate the reliability of the scale, the cronbach alpha test was used, being one of the most appropriate methods to measure the reliability of attitudinal scales. the result was 0.72, which is considered a high value for reliability. the analyses were conducted using spss 22. 3.2 analysis and results table 1 shows demographic information of these samples. table 1 demographic data of samples. type result gender male female 40.9 59.1 age 20-30 30-40 95.7 4.3 field management economic accounting entrepreneurship 43.5 20 13 23.5 year of entrance 2012 2013 37.4 62.6 3.3 hypothesis testing table 2 represents mean, variance accounted and the pearson's correlations among all variables. all tests done on a level under 1% (p<0.01). results show that alertness is significantly correlated with recognizing events of disequilibrium, changing schema vs. information, cognitive error control, accuracy vs. timeliness, schema complexity, schema change – counterfactual thinking, schema change – frame-breaking and sensitivity to profit potential. table 2 means, standard deviations and correlation among variables. variable mean s.d. pearson correlation sig. market disequilibrium 3.76 .91 .309 .001 ignorance of new resource 2.76 1.08 .016 .867 excessive optimism or pessimism about resource 2.88 1.09 .086 .381 accuracy vs. timeliness 3.95 .73 .412 .000 schema complexity 4.17 .75 .245 .008 counterfactual thinking 3.87 .93 .306 .001 frame-breaking 3.58 .99 .338 .000 sensitivity to profit potential 3.98 .84 .245 .006 according to the data collected and based on assessments, six factors which have the most 40 significant effect on the entrepreneurial alertness summarized in figure 1. 4. results and discussion hypothesis 1 predicts that recognizing events of disequilibrium is significantly related to student’s entrepreneurial alertness. as expected, the effect of recognizing events of disequilibrium on student’s entrepreneurial alertness was positive and significant (r=.309, p<0.01). the results corroborate the kirzner (1979, 1985) study that the alert individual is especially sensitive to signals of market disequilibrium, which can occur at the macroeconomic and microeconomic levels. hypothesis 2 indicates that changing schema vs. information is significantly related to student’s entrepreneurial alertness. as expected, the effect of changing schema vs. information on student’s entrepreneurial alertness was positive and significant (r=.412, p<0.01). fiske (1993), kiesler and sproull (1982) assert that if the actor places a higher value on quick action or if he or she feels it is socially desirable to adhere to a schema, then the actor will either discount the new information or engage in elaborate reinterpretations that maintain the structure and dynamics of the existing schema. hypothesis 3 predicts that ignorance of new resource and excessive optimism or pessimism about resource is significantly related to student’s entrepreneurial alertness. as expected, the effect of ignorance of new resource and excessive optimism or pessimism about resource on student’s entrepreneurial alertness was not positive and significant (r=.016, p<0.01; r= .086, p<0.01). the results corroborate kirzner (1985) study that identified several other assessment mistakes non alert individuals may make: (a) failure to recognize that assumptions were never or no longer are appropriate; (b) ignorance of new resource availability; (c) excessive optimism or pessimism about resource availability; (d) excessive optimism or pessimism regarding probable results of actions or decisions. hypothesis 4 predicts that accuracy vs. timeliness is significantly related to student’s entrepreneurial alertness. as expected, the effect of accuracy vs. timeliness on student’s entrepreneurial alertness was positive and significant (r=.412, p<0.01). a central tenet of cognitive psychology is that people employ information processing tactics that best facilitate their goals (fiske, 1993; showers and cantor, 1985) and that one of the first decisions people must make, implicitly or explicitly, in any information processing episode is whether their goal is to be completely accurate or to act quickly. hypothesis 5 predicts that schema complexity is significantly related to student’s entrepreneurial alertness. as expected, the effect of schema complexity on student’s entrepreneurial alertness was positive and significant (r=.245, p<0.01). the results corroborate chase and simon (1973) and chi et al. (1982) study that the availability of these complex patterns as a single unit of information is the mechanism that produces comparatively more figure 1 the role of market on entrepreneurial alertness 41 accurate, albeit very fast opportunity identification and problem solving in experts than in the novices. hypothesis 6 predicts that schema change – counterfactual thinking is significantly related to student’s entrepreneurial alertness. as expected, the effect of schema change – counterfactual thinking on student’s entrepreneurial alertness was positive and significant (r=.306, p<0.01). hypothesis 7 predicts that schema change – frame-breaking is significantly related to student’s entrepreneurial alertness. as expected, the effect of schema change – framebreaking on student’s entrepreneurial alertness was positive and significant (r=.338, p<0.01). kirzner (1985) and gaglio (1997) predicted that alert individuals would be more likely to break the existing means-ends framework and indeed, there is some preliminary evidence that this is a crucial step in the identification of entrepreneurial opportunities. hypothesis 8 predicts that sensitivity to profit potential is significantly related to student’s entrepreneurial alertness. as expected, the effect of sensitivity to profit potential on student’s entrepreneurial alertness was positive and significant (r=.245, p<0.01). kaish and gilad (1991) tried to test this proposition in their early study of alertness found that entrepreneurs appeared to be more sensitive to downside risk while corporate managers were more attracted to the market potential. as noted earlier, in the question of paper, anyone claiming an interest in the opportunity identification process among entrepreneurs would have to address the essential issues of how market environments are represented in the minds of entrepreneurs and whether these representations differed from those of other market actors in any substantial way. this article has detailed a conceptual model and research agenda designed to answer these questions based on a comprehensive and cognitive approach to the theory of entrepreneurial alertness. logic and expediency dictate that compelling answers to the first and last issues should be formed before pursuing the remaining questions. furthermore, the issue of motivation for both alert and non-alert actors will require more consideration than time and space permit here. it is our hope that this article prompts a fruitful line of research and debate that will lead to improvements in theories about alertness, opportunity identification, and entrepreneurship. ultimately results showed that there is significant relationship between market disequilibrium, accuracy vs. timeliness, schema complexity, counterfactual thinking, frame-breaking and sensitivity to profit potential and student’s entrepreneurial alertness; but the relationship between ignorance of new resource and excessive optimism or pessimism about resource and student’s entrepreneurial alertness was not significant. 5. references ardichvili, a., cardozo, r., ray, s., 2003. a theory of entrepreneurial opportunity identification and development. journal of business venturing, 18 (1), 105–123. bonner, s. e. and n. pennington, n., 1991 cognitive processes and knowledge as determinants of auditor expertise, journal of accounting literature, 10, 1–50. camerer, d. f. and e. j. johnson, 1991, the processperformance paradox in expert judgment: how can the experts know so much and predict so badly? 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(2018) exploratory study of competitive intelligence in mexico. journal of intelligence studies in business. 8 (3) 22-31. article url: https://ojs.hh.se/index.php/jisib/article/view/326 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index exploratory study of competitive intelligence in mexico eduardo rafael poblano ojinagaa* atecnológico nacional de méxico/instituto tecnológico de la laguna, mexico; *pooe_65@hotmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: mapping the structure and evolution of jisib: a biblipmetric analysis of articles published in the journal of intelligence studies in business between 2011 and 2017 exploratory study of competitive analysis in mexico eduardo rafael poblano ojinaga pp. 22-31 competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses journal of intelligence studies in business v ol 8 , n o 3 , 2 0 1 8 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 8, no. 3 2018 leonardo a. garcia-garcia pp. 32-44 and marisela rodríguez characterizing business intelligence tasks, use and users in the workplace. leonardo a. garcia-garcia pp. 45-54 and marisela rodríguez josé ricardo lópez-robles, jose ramón pp. 9-21 otegi-olaso, rubén arcos, nadia karina gamboa-rosales, and hamurabi gamboa-rosales a competitive intelligence model based on information literacy: organizational competitiveness in the context of the 4th industrial revolution selma leticia capinzaiki ottonicar, pp. 55-65 marta lígia pomim valentim, and elaine mosconi exploratory study of competitive intelligence in mexico eduardo rafael poblano ojinagaa* a tecnológico nacional de méxico/instituto tecnológico de la laguna, mexico corresponding author (*): pooe_65@hotmail.com received 13 november 2018 accepted 24 december 2018 abstract in order to increase their competitiveness, companies need information for problem analysis, to develop strategies and for decisions making. one way to achieve this is through methodologies, among which competitive intelligence stands out. for pellissier & nenzhelele (2013) competitive intelligence is a process or practice that produces and disseminates actionable intelligence by planning, ethically and legally collecting, processing and analyzing information from and about the internal and external or competitive environment in order to help decision-makers in decision-making and to provide a competitive advantage to the enterprise. because of its importance this paper presents an investigation using a meta-analysis methodology of 72 papers published between 2000 and 2015 of applications of competitive intelligence in méxico. in recent years the practice of competitive intelligence has been increasing in méxico, though its use is not yet widespread. this is why it is important to disseminate and promote the growth of competitive intelligence theory. keywords ci practices in méxico, competitive intelligence, meta-analysis 1. introduction companies need useful information to develop strategies, make decisions and implement them through the organization in order to increase their competitiveness and market share. competitive intelligence (ci) is a designed methodology that stands out to improve decision making. for prescott & miller (2002) ci is any intelligence function that provides a competitive advantage. ci has become an important part of north american business due to the need for companies to keep abreast of technological changes, reduce associated risks, and invest in the acquisition of advanced technology (calof & smith, 2010). however, in mexico, its use is only beginning and there is an opportunity to determine where and how it is being applied. to identify the critical factors in mexican ci practices, a systematic review (sr) of literature was carried out using a meta-analysis (ma) (moher et al., 2009). for basu (2017), ma is essentially a systematic review, but the analysis also pools the results of the studies and provides conclusions. glass (1976) proposed ma as a method of analysis of disorganized knowledge for its integration and organization. it is a process based on statistical methods, or the statistical analysis of a knowledge body searching for valid synthesis. ma uses statistical techniques to integrate the results of the included studies. even though the methodologies developed for ma have been carried out mainly in the social, medical and psychological areas, some recent ma applications have been in the mexican manufacturing industries such as demand and kanban flow (valles et al., 2006); manufacturing (collins, 2007); cellular manufacturing (noriega et al., 2010); and project management (garcía, 2016). in mexico the majority of the theoretical and empirical publications on ci theory are focused journal of intelligence studies in business vol. 8, no. 3 (2018) pp. 22-31 open access: freely available at: https://ojs.hh.se/ 23 on describing the implementing process of ci. publications also cover different approaches where ci can be applied successfully. however, most of these articles do not identify or mention the contributors in which the success of ci practices reside. therefore, it is necessary to carry out a review of the published literature to thoroughly analyze each paper and identify critical factors in the success practices of ci in méxico. the present article carrys out a ma in order to identify the main contributors that impact or influence the success of the application and implementation of ci in méxico. 1.1 description of the problem in mexico, the majority of theoretical and empirical publications on ci theory are focused on describing the implementing process of ci. publications also cover different approaches where ci can be applied successfully. however, most of these articles do not identify or mention the contributors in which the success of ci practices reside. therefore, it is necessary to carry out a review of the published literature, thoroughly analyzing each paper/article and identifying critical factors in the success of ci practices in méxico. 2. literature review ci is defined as any processable intelligence that can provide a competitive advantage (porter and millar,1985). it is a systematic, goal-oriented, ethical and timely effort to compile, synthesize and analyze information of the external environments, such as competition and markets (fleisher, 2009). it also is considered a process of legally and ethically gathering and analyzing information about competitors and the industries in which they operate (scip, 2016). ideally, the use of such information in decision making process aims to adjust activities to improve performance (wright et al., 2009). corporate intelligence, business intelligence, market intelligence, and other similar terms are often used interchangeably, and more often than not, any difference between them is one of semantics more than substance (scip, 2016). the ci process consists of the following steps: monitoring business environment (external data, information and knowledge), gathering, analyzing, filtering and disseminating intelligence that will support decision making process in order to increase competitiveness and improve position of organization (nasri,2012). the cycle of intelligence provides a frame of reference for the management of ci research projects, in such way that projects can be continuously developed, systematically and adhoc (tena & comai, 2001). it is a fundamental basis of the strategic decision-making process (dishman & calof, 2008). in the literature, coincidence is identified in relation to the following processes of the competitive intelligence cycle (miller, 2001; rodriguez, 2005; bose, 2008; dishman and calof, 2008): planning and direction, collection of information, analysis of information, dissemination and feedback. the first phase (planning), focuses on the identification of the needs to gather the relevant information (second phase); then, in the third phase the information collected must be evaluated, determine its usefulness and objectivity, and with this information generate intelligence (third phase) and subsequently, communicate it appropriately to the interested table 1 description of three themes 24 parties (dissemination). the fourth phase requires adequate policies and procedures so that the ci can make a positive contribution to the organization. the importance of the ci cycle lies in its understanding of the stages and support for its application in organizations. in order to identify papers on ci practice in mexico, a search for publications from 2000 to 2015 was carried out. they were identified through the bivir database integrator (of the autonomous university of juarez-uacj), which has 30 databases (including annual review, ebsco, elsevier, emerald, sciencedirect, and wiley), and then perform a debugging of the papers found based on reading the introduction, summary and conclusions. after the phases of identification and selection of the sr, 43 articles out of 72 were considered. to facilitate the review, the articles were grouped into three types: 1) applications in industry, services and the environment; 2) applications in academia and 3) articles of disclosure / dissemination; as presented in table 1. 2.1. narrative summary of the literature by generic themes 2.1.1 applications in the industry, services and environment alcántar (2001) describes the development of the practice of ci in the oil industry in mexico; lozano (2003) proposes a pragmatic view about the advantages and disadvantages of patent analysis; huerta et al. (2003) identify basic design elements to create a ci unit; rodríguez (2003), presents a patent analysis of an advanced materials case; lechuga et al. (2007) apply cti in the search of information about several seawater desalination processes; esquivel et al. (2008) propose to perform information extraction tasks from corporate news published on the web to provide intelligence; saad (2009) uses ci to determine technological trends in biotechnologyphytoremediation; chávez et al. (2010) make use of ci in hotels and restaurants; vera (2011) proposes an intelligence strategy for mexican wine companies to increase their competitiveness; lópez & alcántara (2011) describe the implementation of a system of competitive and technological intelligence (cti) to sustain strategic decisions in wastewater treatment; rodríguez & tello (2012) present a methodology that integrates patent analysis in a study of cti applied in a plastics industrial sector. millán (n.a) identify the most used practices related to ci of export companies in sinaloa; rodríguez & salinas (2012) apply ci to investigate and identify drivers that support the decision making of a plastics company; rodríguez-borbón et al. (2013) present the design of a ci model for horticulturalists in southern sonora; montiel et al. (2014) use ci in the bond industry in mexico; rodríguez et al. (2014a) apply patent analysis as part of a cti methodology on open die forging, also develop a patent analysis on additive manufacturing (rodríguez at al., 2014b); ahumada & perusquia (2016) propose a set of factors for the development of the capacity to manage the knowledge applied for the expansion of business intelligence. regarding to the integration of ci with other approaches, some papers are about a qfd deployment of the quality function application (rodríguezsalvador et al., 2006), kansei engineering in the design of stoves (rodríguez and moreno, 2011), blue ocean strategy (rodríguez and bautista, 2011), and applications of total quality management with ci (rodríguez et al., 2007). 2.1.2 applications in academia rodríguez & gaitán (2002) propose a holistic model for teaching cti, integrating collaborative learning; the learning of cti for future strategic improvements (rodríguez & mora, 2000) and to improve the identification of opportunities (rodríguez et al.; fuentes et al.) present a methodology that incorporates cti with methodologies of design and product development for a learning environment of an engineering laboratory; gutierrez et al., analyze the degree of acceptance of high school students in the business intelligence and development program as a proposal for competitiveness in universities. for research and development centers, lopez & alcántara (2010) present the first results of a methodology proposed to implement a cti system; and lópez-martínez (2011) proposes the application of ci and data mining for the identification of patterns that reveal the structure of scientific research and applied research, as well as their concordance in the surroundings of a country; luna & solleiro (2007) explain intellectual property 25 management in centers of mexican research: the case of the institute mexican oil. 2.1.3 disclosure / dissemination articles rodríguez & valdez (2003) present a review centered on the importance of the cti systems for the detection of innovation opportunities and threats; mier (2003) emphasizes the importance of ci as a factor to build a technological tradition in organizations; rincón-a & ortiz (2005) present an overview on the analysis in technological intelligence; güemes and güemes & rodríguez (2007) clarify the situation of the innovation structure used by mexican companies and their relationship with ci practices; bertacchini et al. (2007) present a case studies in mexico & in gafsa university from territorial intelligence to ci & sustainable system; solliero et al. (2009) identify the state of the art and trends of the cti through the analysis of the literature; gonzález (2011) describes the link between two tools of technology management: the cti and the management of knowledge to achieve business competitiveness through technological innovations; gonzález (2012) proposes an electronic cluster for the competitive development of small & medium companies based on ci actions. vizcarra et al. (2012) offer information that highlights the usefulness of ci by analyzing concepts that describe the application of this development and entrepreurship; cantú et al., (2011) deepen the analysis of previous work concerning the building of national system of cti and suggest a theoretical systemic framework to constitute it; and sánchez-lópez (2012) presents the implementation of a ci and technological surveillance portal; perezvillarreal & valdez-zepeda (2014, 2015) propose a system based on ci as a fundamental factor to increase chances of electoral success in political campaigns. 3. methodology the flow of information of the phases (identification, screening, eligibility and included) of a sr/ma proposed by prisma statement (mohoer et al., 2009) is shown in figure 1. the eight steps of the ma methodology (noriega et al., 2010) were applied to generate statistical support and to obtain a high grade of confidence about the papers for the study. the steps of the ma methodology are described as follows: figure 1 four phases flow diagram of the meta-analysis. 26 1. problem definition. in this step the problem must be clearly and precisely defined. in this case, it was defined as the determination of ci factors that can be obtained in successful ci practices. 2. identification of the information sources and the studies to be analyzed. once the boundaries of the meta-analysis are determined, then, all the studies that fit within those bounds are to be determined. the purpose of this step is to list the sources of the literature. in this research the total number of studies considered was 72, among them are research papers and conference proceedings. 3. information discrimination. in this step, the information is classified according to the degree of scientific strictness, credibility and confidence. for this purpose, a set of inclusion and exclusion criteria is developed and it is applied to all the documents, excluding the papers that do not fulfill the criteria. this is one of two quality filters. in this step, it was reduced from 72 to 43 papers. 4. publications database. the purpose of this step is to generate a papers database with the aim of facilitating the management, localization and treatment of the information gathered. 5. evaluation of articles. the purpose of paper evaluation is to determine, based on the stated criteria, whether or not an article should be included in the ma. at this stage, a questionnaire of 13 items (adapted from garcía, 2016) was applied to all the table 2 data for all papers used in the meta-analysis. 27 documents. each document is judged and assigned a grade according to a likert scale from 1= not important to 4= most important. in this step, it was reduced from 43 to 18 papers. 6. classification and coding of information. in this process, the extraction of data from each study is based on a coding sheet that specifies what data to extract and a key that interprets the various aspects conducted. the coded information is summarized to identify moderating variables, to be used to group studies for conducting ma. 7. statistical analysis. in this step, the aim is to apply the statistical methods to the studies that were selected for inclusion in the ma. the selection of the appropriate ones depends on the specifications of the comparisons to be made. for this research, the statistical treatment began with the normality test applied to the final results, an anderson darling test was applied (for sample size, n<30). if the data shows a normal behavior, a difference in means test is to be used in the next step. the differences in means test was done to determine the relative contributions of the factors and to establish the most important factors. minitab was used for statistical analyses. 8. generation of conclusion. this is the last step of this methodology, which consists of interpretation of the results obtained and generates the conclusion for the defined problem. a ma result is simply evidence that may be used in the attempt to integrate results from multiple studies. also, the assumptions necessary for the ma should be evaluated for the adequacy of the study. 4. results in this section, the results obtained from the ma of ci practices literature are presented. the total number of studies considered was 72, including research and conference proceedings. in the identification phase, it was reduced to 62 papers. later, a first quality filter (screening phase) excluded 19 records, and then each document was judged and assigned a rating according to a likert scale (second quality filter). in this step, the records were reduced from 43 to 18 items (eligibility phase). table 2 shows the author, year and title of each paper. the next step was the determination of the success factors that are critical for ci practices (table 3). for this step the frequency of each factor was summarized. a total of nine critical factors (cf) were found in the documents reviewed. the cfs in order of decreasing importance are: analysis of information; decision making, opportunities and threats; information search and extraction, dissemination of information; generation of information/intelligence. once the total frequency was tallied, a normality test was required. the results are table 3 success factors identified figure 2 normality test for the nine success factors identified figure 3 analysis of means for the success factors identified. 28 shown in figure 2. the approximate p-value = 0.012, and the significance was above 0.01, so it is safe to assume that the data is normally distributed and it is adequate to perform a parametric test. the next step was the application of a poisson analysis of means (anom). the test determined that 3 of the 9 factors can be considered critical (with the exception of factor 7 having sufficient evidence). these were number 2 (information analysis); 8 (decision making), and 7 (identification of opportunities and threats), shown in figure 3. 5. final remarks this research shows, as a first approximation, the critical success factors (csf) identified for the practice of ci in mexico. this research takes over the interest of identifying the variables of competitive intelligence (güemes & rodríguez, 2007), and intends to present a new perspective for ci professionals and researchers in mexico. the findings show that at least 18 articles out of the 43 mentioned csf in different cases or approaches. therefore, research to find the most important csf in the practice of ci is a contribution to the field. regarding the application of ma in engineering areas, as well as the adaptation of ma procedures to the ci framework of research practices, this can be considered successful. in mexico, the main practice of ci is a variation with a strong emphasis on science and technology and its impact on research and development activities (dou & massari (2001) quoted by dou and manullang (2004)). in this study the term cti is understood as a type of ci. results supports the claim that in mexico ci is an emerging practice. although it is taking place in both the public and private sectors, it still has a long way to go in policies to improve its development, as well as in infrastructure and the creation of entities to support this activity (rodríguez, 2005). as shown in this review, some mexican companies conduct ci practices to anticipate future changes, innovations with a high impact on the market, and to enter new market niches and develop new products. the main limitation of the study is the sample size (43). although we consider several issues that may allow for the validity of this study, hunter and schmidt (2000) say that for sample sizes in the range of 25 to 1600, the type i error for random effects is 5% for fixed effects with homogeneous cases. however, this search was exhaustive. both ma and ci are relatively new theories in mexican academia and industry. close to 95 % of méxico´s businesses have less than 16 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(2019) how managers stay informed about the surrounding world. journal of intelligence studies in business. 9 (1) 28-35. article url: https://ojs.hh.se/index.php/jisib/article/view/370 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index how managers stay informed about the surrounding world klaus solberg søilena* adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *klasol@hh.se journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: exploring new ways to utilise the market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power enhancing competitive response to market challenges with a strategic intelligence maturity model gianita bleoju and alexandru capatina pp. 17-27 how managers stay informed about the surrounding world journal of intelligence studies in business v o l 9 , n o 1 , 2 0 1 9 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 9, no. 1 2019 klaus solberg søilena pp. 28-35 kalle petteri nuortimo and pp. 5-16 janne härkönen how managers stay informed about the surrounding world klaus solberg søilena* adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se received 3 march 2019 accepted 20 may 2019 abstract in this paper we look at how managers and knowledge workers stay informed about the events in the outside world that affect their organizations. data was collected using a survey of 308 subjects from around the world. a model for how managers stay informed is presented. we introduce the idea of the proprietary cloud. the findings have implications for managers who want to compare their own sources of information and improve routines for information gathering. keywords business intelligence, intelligence studies, knowledge management, the proprietary cloud, workplace learning 1. introduction how do managers stay informed about the outside world on issues and events that affect their business? this is one of the basic questions not only in intelligence studies in business, but in management and business in general. it’s a question that should be revisited at certain intervals as sources of information change, especially with new technologies and services. research on what managers read is scarce, which is surprising. instead academics tend to focus on more general questions of knowledge management (km), as shown in the theory chapter below. non-academic literature sources tend to focus on what famous people read (or say they read/perception) or on what those who sell management literature and literature in general say managers should read. another part of the literature on what to read takes the form of self-help, which shows how to cope with information overload and suggests how to handle stress. this can be quite banal. holmes (2018): “if all else fails, take a small break”. popular sources also focus on the problems with the information industry online and the fact that we are exchanging information for our privacy. for example, news organizations subject readers to third-party tracking (libert and pickard, 2015). this topic has been revitalized with the cambridge analytica scandal and the introduction of gdpr. griswold and nisen (2014) describe what successful business leaders read: warren buffet tells cnbc he reads the wall street journal, the financial times, the new york times, usa today, the omaha world-herald, and the american banker, and that is only in the morning. bill gates reads the wall street journal, the new york times, and the economist cover-to-cover, according to an interview with fox business. the danish programmer david heinemeier hansson reads reddit, hacker news, engadget, the economist, boing boing, and twitter. jeffrey immelt, the ceo of ge reads the wall street journal “from the center section out". afterwards he goes to the financial times and scans the ftindex and the second section: “i'll read the new york times business page and journal of intelligence studies in business vol. 9, no. 1 (2019) pp. 28-35 open access: freely available at: https://ojs.hh.se/ 29 throw the rest away”. charlie munger is devoted to the economist. nate silver, the fivethirtyeight editor-in-chief, starts with twitter, memeorandum, and real clear politics. later in the day he reads blogs like the atlantic, marginal revolution, and andrew sullivan (griswold and nisen, 2014). elon musk sticks out in his answer: “i read books” (gautam, 2018). many famous leaders and managers say they do their reading very early in the morning. they also exercise in the morning and do a lot of work then, which makes one wonder when they go to bed or if these answers can always be trusted. according to a paper by mckinsey & company (2017), leaders of some of the world’s biggest organizations are all reading a series of three to six books at the time, fiction and nonfiction, with everything from yuval noah harari, to leonardo da vinci and j. m. keynes. newspapers ask a similar question: what people have on the bedside table. it would be embarrassing to say that there was nothing there or that the books were just lying there half-forgotten. what is missing from these sources is what managers in general read for their organizations to stay competitive, as we cannot assume that they follow the example of the persons mentioned above. there is, in other words, a research gap in how the welleducated, or the knowledge workers, keep informed about the world. this is an important question as it to a large extent has a direct effect on our actions, thus on the way companies are run. we would like to know where the managers get their information from and how they try to adapt to changes in the business environment. such answers would also show what they do not read, which may be equally revealing. 2. method the population for this study is defined as any professional knowledge worker. a knowledge worker is an employee whose main capital is knowledge or who can be said to “think for a living”. a professional here simply means someone who is employed. thus, a more complete title for this paper could have been “how knowledge workers stay informed about the outside world”, but for clarity and simplicity we chose the shorter version: what managers read. a sample size of 1050 subjects were selected on linkedin by personal invitation. a pre-test was run for a general invitation but this resulted in few responses. respondents were widely spread across the western world, with about 1/3 of answers from africa, asia and south america. 326 complete answers were collected, where about half could be defined as “managers” and the other half as “knowledge workers”, but with a substantial overlap. a manager is a person who controls a staff of employees. we should have added this as a control question. no questions were removed from the survey after an initial pre-test which included some 25 respondents. about 20% of the complete answers were taken out because they were not precise enough, giving answers like [i read] “good competitive intelligence”. at the end, 308 complete answers were used in the analysis. answers of the same kind were omitted from table 1, but the number of similar answers was counted. the research strategy is a survey. the purpose of the research is exploratory, concentrating on three research questions: rq1: how do you as a manager stay informed about what goes on in the outside world that affects your company? rq2: what kind of newspapers, reports and tv/video do you access to stay informed about what is happening that affects your company? rq3: in what other ways do you stay informed about what is happening in the outside world that affects your company? the reasoning behind the choice of questions were as follows: questions should be exhaustive, repeating questions in detail (q2), asking for deeper answers (q3). the coding process: the data presented in the table went through a process in three stages: 1. clarifying and condensing meaning, 2. classifying key terms/notions and groups based on answers given, 3. placing the data in the appropriate group, and 4. counting occurrences of answers and weighing these with meaning in other answers in the same category (q1) and with other categories (q2 and q3). the raw data are available upon request. the extent of researcher interference has been minimal. the author’s own opinions and experience as relates to the rqs is kept out of the analysis throughout the paper. the study setting is non-contrived, meaning the people were interviewed in their normal environment, in front of their personal computer, tablets or 30 phones. the unit of analysis is individuals. the data collection method is surveys using the service surveymonkey and the analysis is qualitative. the time horizon for the research can therefore be said to be longitudinal. 3. theory when searching in scientific databases on the question of how managers stay informed we found few, specialized and diverse answers. suggestions of how to stay informed varied from participating in public policy discussion (ellis, 2002) to tweeting (turner, 2016). searches on phrases such as “what people read” or “how people stay informed” gave very different results in web of science and scopus, such as an article about what people read in france “between 1920 and 1950” (chesneaux, 1996) or a quick survey done in a french cinema magazine (ciment, 2008), related to cinema viewers only. the single largest amount of articles found refered to how to read the bible, or are specialized contributions like “letters in interwar new zealand”, or “the boer war and the invention of masculine middlebrow literary culture”. there was nothing substantial related to management or business. i realized this may also be symptomatic for the complicated way in which we have learned to write titles and frame problems as we avoid simple titles and subjects, even when they are good questions. instead the social sciences often try to resemble the way that problems and specializations are framed and developed in natural sciences, with over-complicated titles and concepts which make finding the information more difficult. these issues put aside, the general question of what to read has traditionally been studied under workplace learning and knowledge management, but there is hardly any area are of study in the social sciences that does not touch on the topic in one way or another. there is a substantial literature on news consumption. schrøder, k. c. (2019) summarizes key findings in an online paper thus: people find those stories most relevant that affect their personal lives, which they can share with friends and on social media, which are amusing or weird. at the same time, we do want to stay informed on all levels, also internationally. it follows that we are not very good at achieving what we set out to do as rational beings, which is confirmed by much of the neural sciences during the past decade. we want good news, but often end up with entertainment because it is tempting and easily accessible. the shared notion that news is everywhere is making us believe that we are well-informed or that it’s enough to read headlines. news avoidance is also a real issue discussed in this literature as news is seen as negative and we do not want too much negativity in our lives. other studies are focused on certain industries or sectors. kay (2001) looks at how professionals in the hospitality industry read. she found that a significant number of lodging professionals tend to read hospitality industry and general business publications instead of academic research journals, but that academic journals were rated higher by managers regarding usefulness as a source for information on research, employee management, marketing, hospitality industry, and general business, as well as professional and personal development. other papers and papers in general are less optimistic about the value of scientific articles. the link to business intelligence is made, for example, by schroeder (2015): “the widespread availability and accessibility of information via the internet and other sources means that employees at all levels and areas of an organization are often able to directly retrieve and use data in their day-to-day work. new forms of data and analysis are rapidly emerging, particularly from the web 3.0 technologies generating massive amounts of unstructured data that firms need to understand and utilize in pursuit of their business goals. these developments are resulting in a more data-conscious and datadriven business environment overall. firms need to ensure that their employees are equipped with the right skills and expertise to exploit the opportunities offered by this while also managing the risks, such as misinterpretation or inconsistencies in data use.” schroeder (2015) concludes that workers need the right skills and expertise to identify, interpret and apply relevant data and knowledge, and the organization must provide an overall environment that is supportive of and promotes data-driven activity. a manager looking for practical advice may wonder what the specific skills are, but this has not been a focus in the scientific literature. liebowitz (2016), on strategic intelligence: 31 “if we make this assumption, then knowledge is at the root of this equation and thus, the ability to leverage knowledge electively internally and externally should be a core competency for the organization. all this points to the area of “knowledge management” for competitive advantage.” liebowitz, j. (2016) explain the difference between ci and km as follows: “with business intelligence, the use of analytics (davenport and harris, 2007) and advanced information technologies often applied to assist the decision maker. competitive intelligence (ci) deals with establishing a program for collecting, analyzing, and managing external intelligence (such as competitors, environmental scans, etc.) to improve organizational decision-making. knowledge management (km), as we discussed in the last chapter, looks at leveraging knowledge both internally and externally, but typically has an inward focus on maximizing human capital and other intellectual assets in the organization. together, the synergies among these three areas (bi, ci, and km) can result in what the author calls “strategic intelligence” (si).” mckenzie, et al. (2012) suggest that the best way to make employees inspired to learn about the world is by reducing hierarchies. this frees people to use their knowledge more responsively; geographical dispersion gives better access to specialist expertise wherever it exists. in the book “understanding the knowledgeable organisation: nurturing knowledge competence” mckenzie and van winkelen (2004) make similar observations. the notion of tacit knowledge was introduced by nonaka (2007). tacit knowledge consists partly of technical skills – the kind of informal, hard-to-pin-down skills captured in the term “know-how.” a master craftsman after years of experience develops a wealth of expertise “at his fingertips”: “these activities define the “knowledgecreating” company, whose sole business is continuous innovation. deeply ingrained in the traditions of western management, from frederick taylor to herbert simon, is a view of the organization as a machine for “information processing.” there is another way to think about knowledge and its role in business organizations. it is found most commonly at highly successful japanese competitors like honda, canon, matsushita, nec, sharp, and kao. “the centerpiece of the japanese approach is the recognition that creating new knowledge is not simply a matter of “processing” objective information. rather, it depends on tapping the tacit and often highly subjective insights, intuitions, and hunches of individual employees and making those insights available for testing and use by the company as a whole.” the idea that a company is not a machine, but a living organism, leads to the evolutionary approach. it’s not an accident that this comes from a japanese scholar. the evolutionary approach was well-developed in germany and japan and interest prolonged also after wwii. the narrative is often the same. social life on our planet is consistently changing. managers and professional must adapt to these changes to stay competitive. adapting to these changes first of all means getting new knowledge and skills. new knowledge and learning come predominantly through education and reading. what managers chose to read has a direct effect on how well the organizations that they are set to lead are able to compete in the market. the question then becomes what to read. the answer will to a large extent depend on the industry that we are in. cultural factors also play a role. the evolutionary approach is also supported in mckenzie, et al. (2012): “tension is essential to a healthy system: it triggers adaptation.” from the theory review it must be concluded that the question of what mangers should read has not been the object of scientific investigation, and thus represent a gap in the research. existing theory will be used to compare empirical findings and to conduct an analysis. 4. data and analysis the answer data from the three main questions from 308 subjects was exported into ms excel. comments about sources could be classified into general sources, humint related sources, specific sources, internet-based sources and tv and radio sources, as in table 1. when reading the different classes of data, we see that the separation between tv and internet is not that clear, even though it still make sense to keep this classification. nor is there a clear distinction between physical 32 papers and the internet as different sources, including radio, are digitalized and available over the internet. a subscription to, for example, the economist can give access to the physical journal and the web-based journal, as part of the same subscription. from the data we can draw a number of immediate conclusions: • no one said they read books • new media companies are dominating as providers of competitive information: google, youtube, linkedin, facebook, twitter • people watch tv news first of all, to the extent that the content is available on youtube • trade shows are a major source of information • radio is not a significant source of information anymore, with the exception of in places like the african continent and to a certain extent in france • humint is still considered highly relevant for information gathering, on all levels and across organizations. this includes “coworkers and colleagues”, but also gossip and “friends in the media”. • many managers say they get their best information through emails, from google and the act of googling. this makes google llc the single most important source for competitive intelligence. • a number of reports are widely popular, for example from oecd, imf, and the world bank, but those are also distributed by the major consulting companies. • most managers read a combination of their local and/or national news and international news. • the most popular sources offline are the economist, wsj, and ny times. there is a strong notion that “open source is mostly noise”. this implies that managers are willing to pay for good information because searching in open source is often found to be a waste of time. it may also mean that managers feel they are not able to search effectively in open source. table 1 sources of knowledge for managers and knowledge workers. general sources magazines, tech magazines, professional newsletters, financial column in newspaper, business report, online newspaper feeds, social media feed, regular gazettes, blogs, vlogs, scientific papers, regulatory bodies, significant movement or activities in the market, consultancy services and media monitoring services, internal financial data, operational activities, technological advancements, annual reports, events and congresses, focus on credibility of information, previously acquired, subscribing to specialists on macro-economics, reports from business consultancies from big 5, continuously update internet crawl targeting, corporate news of relevance that feeds into a news dissemination intranet system, press releases of companies, scientific community, industry whitepapers, internet forums, gossip humint engaging suppliers, channel partners, competitors. keep a keen eye on sectors, events and people, journalists covering the sector, rely on communication department, peers in other regions, personal network and relationships with top officials, media friends, discussing topics with co-workers and partners, competitor analysis, competitor’s employees, a friend circle with successful people, informal meetings with experts, events organized by embassies or trade associations, coworkers and colleagues specific sources economic times, financial times (ft), khaleej times, gulf news, (brazilian) national industry confederation reports, ghanaian times, daily guide, business and financial times and the dispatch, the economist, autonews, automobilwoche, manager magazine, focus, handelsblatt, il sole 24 ore, business insider, forbes, bbc, in sweden: dn, svd, di, hbr, nrc, handelsblad, le monde, le figaro, mit review, verge, techcrunch, mckinsey q, bcg, bain, deloitte, wef, goldman sachs, the guardian, el païs, ubs, exane, barclays, times higher education, qs world ranking, guardian league table, fortune internetbased linkedin, youtube, gmail alerts, google search, emails, thinkerview, diane, orbis, kompass, tedx, reuters, specialized tech content (gartner, idc), cb insights, infodesk, swedish tax organizations information, wikipedia, crunchbase, mapegy, clarivate, foresight, resumé, journalisten, dagens media, medievärlden, digiday mediaguardian, nieman lab, reddit, google news tvradio cnn, sky news, cnbc, bloomberg, gtv (ghana), france info, aljazeera, euronews, france culture, joy newstv (ghana) 33 humint plays a large role as a source of information, but no one mentions travelling by itself as a source of learning about the world, which is something westerns used to value highly (søilen, 2016). today it seems to be more asian which are “roughing it”, while western youth prefers “to party” and have fun. this may be symptomatic for the decline of the west, as julius caesar surely would have noted if he had lived today [he warned his own youth against the rise of the germans in the book the gallic wars]. from the answers, the managers’ information gathering can be divided into three parts or distinct activities: listening, reading and watching. these correspond to our most important senses for information gathering, hearing and seeing. based on these conclusions and on the existing theory presented above, a model was constructed to make sense of the different components, as shown in figure 1. in figure 1, the larger square box represents all the information available. inside that box most information is open source and most of this is considered ‘noise’, or at best nice-to-know information. the opposite of open source (which is free) is proprietary. proprietary information comes in many categories, as part of what we read, what we hear (as in consultancy), in what we watch and as part of the entertainment we consume. at the same time there are parts of the same four categories that are also open source. the smaller box is the proprietary cloud. i’s called a cloud because it is hanging over the available information we search for, often in the form of barriers, or information behind paywalls. what we read, see and listen to are the groups of categories where we actively seek to gain new information. these groups are placed in a funnel in the model, where the amount of information retained diminishes with time. what comes out of the funnel is the information that we use which is only a small part of all the information we take in from the beginning (to of funnel). the reason is that we forget parts of what we read even in the shorter term (memory loss) and that the situations we are confronted with in business life only demand that we use a very small part of what we read. thus, what comes out of the funnel is a function of memory retention and the use we have of information that was acquired. the information age means that information is in abundance, but this is a mixed blessing as most information is “useless, trivial and distracting”. thus ‘noise’ is a major problem in the process. the challenge with noise is not to put any of it in the funnel, meaning that we must disregard it from the very beginning once it has been identified. we can use ai and machine learning to help us sort out the noise, much like in spam filters figure 1 the manager’s model for staying informed. 34 so far, the model presented could make an ideal model in an ideal world, but theory suggests there are other components to be added. one part is that we mix intelligence with entertainment as we search. we are continuously being drawn to other tempting sorts of information that are distracting and stealing our time, but which at the same time we seek. humans are not machines. we do not spend all of our working time even gathering and analyzing intelligence. instead we have a need to take pauses, perform other tasks (out of necessity and to avoid monotonies), and we want to be entertained. entertainment has never been more accessible than now with the internet (not only cat and dog movies). thus, these three parts may be seen as a necessary part of the information gathering process for it to work, and must be included in our model to make it more realistic. a major question is how good the sources that are identified above in the survey are for the purpose of monitoring the world. this brings us to the second major question which is what alternative sources of information there are that are missed by the respondents in the survey. those included are overall mainstream. we see that those missing are non-western. a more detailed answer is that major external sources are missing like the tv stations cgtv (pro china) and rt (pro russia), often labeled as propaganda channels by westerners. then there are narrower western channels like democracy now! (tv) and the economic blogs zero hedge and naked capitalism. there are numerous university professors in business and economics who blog regularly, like michael hudson, steve keen and richard wolff, none of whom tend to appear on mainstream lists of economic bloggers. even main stream bloggers like robert reich, stephen stieglitz and paul krugman are missing from the survey. institutional blogs are also missing like imf, the mises institute and council on foreign relations, just to mention a few. another problem altogether is that many respondents say they use twitter, but we do not know who they are following which makes a whole world of difference. from the major papers we miss china daily and asahi news (japan). otherwise there are numerous newspapers in japan and pakistan with large circulation but their impact is more local. then there are the major magazines missing like der spiegel, newsweek, time magazine, foreign affairs, harpers, new statesman, the spectator, and focus (german). for france: l’express, le point, l’obs and jeune afrique. in italy: l’espresso and panorama. wikileaks was another major source of information missing even though many probably read or see the stories coming from there but printed in other media outlets. 5. conclusion, implications and future research there are two main conclusions to be drawn from the data. the first is what is in the data, which is what managers and professionals say they read. the other is what is implicit in the data that is what is missing, what respondents do not read. we see that managers mainly read mainstream and western sources. that is not a major problem for the companies as long as valuable information comes from these sources, which is not given. it is a risk that these sources present the same world view, especially as the western world is losing economic influence to asia and china in particular. western managers have a knowledge deficit when it comes to their major competitors and to asian cultures which can be seen through what they read, but more so, what they do not read. it’s noteworthy to see that managers do not read more books and scientific articles. radio is probably better than the attention it gets from managers as a source of valuable information. we also see that few respondents read news agencies directly except for reuters. they do not read smaller, narrower publications except for special trade magazines or for specific industries. the survey also suggests that managers and professionals read more heuristically, not necessarily what gives the most valuable information, and they do not read in an organized fashion. the competitive company is an intelligence driven organization. this is more true today than ever before in history. still it can be argued that managers and knowledge workers in general are not handling the question of what to read professionally. instead much is ad-hoc and based on habit. others know that they have to get good information to know what is happening in the world, but fail to access it. learning is not only a question of what the individual reads, but of spreading the message around repeatedly through frequent dialogue and communication. on this point, managers report that they do quite well. 35 6. future studies this and other studies focus primarily on what people say they read. more studies are needed on what managers actually read, what they recall from reading and what they actually use to make decision. there is another question almost equally important and that is how to read, from what platforms. this raises another question which is when to read what. as we have seen from popular sources, managers say they read early in the morning, but they also prefer to eat and exercising during this time and the morning is only so long. it would be interesting to know how much time we are using on each of the different categories of sources. we are changing back and forth between sources much more than before. this leads to news as a series of distractions which is deteriorating our concentration in general. the consequences of this on our understanding of what we read will have to be studies, but preferably then by psychologists and neuroscientists. 7. references chesneaux, j. (1996). popular literature-what the people read from 1920 to 1950. quinzaine litteraire, (698), 32-33. ciment, m. (2008). survey (survey of what people read). positif, (563), 108-111. davenport, t. h., harris, j. g., jones, g. l., lemon, k. n., norton, d., & mccallister, m. b. (2007). the dark side of customer analytics. harvard business review, 85(5), 37. ellis, b. (2002). stay informed: participate in public policy discussion. acm siggraph computer graphics, 36(2), 13-22. gautam, s. /2018, june 22). what the top, successful managers are reading…and you should too! [blog post]. retrieved from https://medium.com/flock-chat/what-topsuccessful-managers-are-readingba47e40bd99e (accessed 2019-06-04) griswold, a. nisen, m. (2014). what 16 successful people read in the morning. business insider, jan. 24, 2014. accessed 2019-06-03 holmes, l. (2018). how to stay updated on the news without losing your mind. huffington post. 2018-01-12. accessed 2019-06-03 libert, t., & pickard, v. (2015). think you’re reading the news for free? new research shows you’re likely paying with your privacy. the conversation, 6. accessed 2019-06-03 liebowitz, j. (2016). beyond knowledge management: what every leader should know. auerbach publications. kay, c. (2001). what do managers read? a survey of journals and periodicals used by lodging managers in the hospitality industry. journal of hospitality & tourism education, 13(3-4), 76-86. mckinsey&company (2017, july). what ceos are reading in 2017. [white paper]. retrieved 2019-06-04, from https://www.mckinsey.com/~/media/mckinsey /featured%20insights/leadership/what%20c eos%20are%20reading%20in%202017%20pa rt%20i/what-ceos-are-reading-in-2017part-1.ashx mckenzie, j., van winkelen, c., & aitken, p. (2012, september). developing effective change leadership to build the knowledgeable organisation: a paradoxical foundation. in european conference on knowledge management (p. 726). academic conferences international limited. mckenzie, j., & van winkelen, c. (2004). understanding the knowledgeable organization: nurturing knowledge competence. cengage learning emea. nonaka, i. (2007). the knowledge-creating company. harvard business review press. schroeder, h. m. (2015). knowledge, learning and development for success in the new business environment: an art and science approach. development and learning in organizations: an international journal, 29(5), 10-12. schrøder, k.c. (2019). what do news readers really want to read about? how relevance works for news audiences. digital news publications. accessed 2019-06-03 søilen, k.s. (2016). a research agenda for intelligence studies in business. journal of intelligence studies in business, 6(1). turner, p.l. (2016). stay connected and informed: start tweeting. bulletin of the american college of surgeons, 101(6), 25-26. vol6no1paper3 fourati-jamoussi and niamba to cite this article: fourati-jamoussi, f. and niamba, c.n. (2016) an evaluation of business intelligence tools: a cluster analysis of users’ perceptions. journal of intelligence studies in business. vol 6, no 1. pages 37-47. article url: https://ojs.hh.se/index.php/jisib/article/view/141 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index an evaluation of business intelligence tools: a cluster analysis of users’ perceptions fatma fourati-jamoussia and claude narcisse niambab institut polytechnique lasalle beauvais-esitpa, 19 rue pierre waguet, bp 30313f-60026 beauvais cedex, france; afatma.fourati@lasalle-beauvais.fr; bnarcisse.niamba@lasalle-beauvais.fr journal of intelligence studies in business please scroll down for article an evaluation of business intelligence tools: a cluster analysis of users’ perceptions fatma fourati-jamoussi* and claude narcisse niamba institut polytechnique lasalle beauvais-esitpa, 19 rue pierre waguet, bp 30313f-60026 beauvais cedex, france *corresponding author: fatma.fourati@lasalle-beauvais.fr received 11 february 2016; accepted 18 march 2016 abstract the purpose of this paper is to discuss and evaluate the use of business intelligence (bi) tools by professionals and students to help designers of these tools get the most efficiency out of a monitoring process. this paper explores the business and competitive intelligence literature. bi is considered to be a new area in information systems, so literature research was conducted in the area of management information systems (mis) with two evaluation models: task-technology fit and technology acceptance to evaluate bi tools. a questionnaire was sent to users of business intelligence tools addressed to french companies in different trades and engineering students and the most pertinent replies were examined. the responses were analyzed using the statistical software spad. results showed a typology from the various profiles of users of this technology using the method of classification. we note different perceptions between professional and student users (the clients). although this study remains focused on individual perspective, it requires more examination of the organizational impact of the use of bi tools. the identification of the different user profiles was done by using a cluster analysis. for the designers of bi tools these results highlight the importance of user perception, suggesting designers take into account the perception of all user types. as these tools develop, more and more companies will be looking for skills for monitoring and management of strategic information. keywords business intelligence, cluster analysis, tam model, ttf model, user perception 1. introduction in recent years, the emergence of information technology and knowledge has improved the completeness of data collecting in order to ensure a better ability to classify information and knowledge through the use of artificial intelligence. business intelligence (bi) now has better tools able to identify the interests of users and facilitate the analysis and dissemination of information and knowledge. bi is considered to be a separate and scientific discipline dominated by engineers and programmers (solberg soilen, 2015). adamala and cidrin (2011) attempted to analyze what the factors are that influence bi. sabanovic and solberg soilen (2012) defined bi as: “an analytic application, […], that enables a wide range of users to access, analyze and act on integrated information in the context of the business processes and tasks that they manage in a given domain…” these authors showed that there is a positive correlation between company size and usage of bi systems. they used and developed a purchase and employment layer (pet) model of bi implementation to identify companies’ understandings, expectations and needs in terms of bi systems. nyblom et al. (2012) journal of intelligence studies in business vol. 6, no. 1 (2016) pp. 37-47 open access: freely available at: https://ojs.hh.se/ 38 proposed a model for evaluating the performance of bi software systems by using five criteria: efficiency, user friendliness, satisfaction, price and adaptability. their results showed that the choice of system used is related to the individuals’ experience. amara et al. (2012) developed and tested a solberg søilen amara vriens (ssav) model for the evaluation of bi software to facilitate the user’s selection tool. by generating more relevant information, these tools seem likely to influence the process of decision making in the company. despite this important role of business intelligence, little research has addressed the interaction between the monitoring tools and their users. this article addresses the issue of the identification of business intelligence tools and the evaluation of professional and student perception by putting this technology in the business intelligence process. the management of information and knowledge poses three major challenges related to three basic needs: the analysis of structured and unstructured data, the measurement of the user perception on monitoring tools and the identification of user categories. from these three challenges, our approach seeks to answer two key research questions: 1. how can we make the choice between different monitoring tools to collect, to process and to disseminate information? 2. what are the characteristics of the use of monitoring tools? in the second section, we define the concepts of "competitive intelligence", "business intelligence", "strategic intelligence" and "bi or monitoring tools". in the third section, we propose the approach of our study and the research method. in the fourth section, we present our results on the monitoring tools developed within the higher education institution and the companies surveyed and classification of users of this technology in their perception. conclusions are drawn in the sixth section. 2. conceptual background historically, a business company is listening to its changing environment (customers, suppliers, competitors, government and web) to identify indicators that have an influence on its present and future activity. over time, some companies have integrated this process into their organization by seeking information about their environments. this process has become an autonomous research field. aguilar (1967) pioneered research on strategic intelligence and he defined this concept as the gathering of external information on events and trends of the environment. he showed support for the identification and understanding of the threats and opportunities of strategic processes. thus, during the last fifty years, researchers have in turn spoken of organizational intelligence (wilenski, 1967; choo, 1998), business intelligence (gilad and gilad, 1988) and intelligence of business (lesca and chokron, 2000) before the more recent appearance of the "competitive intelligence" and "business intelligence" concepts. competitive intelligence is regarded as a specialized branch of business intelligence. solberg soilen (2015) proposed the classification of intelligence studies to help us to place different forms of intelligence and to show how they related to each other. the first concept aims to collect and analyze data on specific and generic competitive environments, while the second focuses on the current competitors and can analyze areas such as potential acquisitions-mergers and evaluate specific country risks (lesca and caron fasan, 2006). in the case of competitive intelligence, herring (1998) defines this process as a number of separate activities; it is a continuous cycle which includes the following levels: level 1: human collaboration • planning and management: working with decision makers to discover and identify their needs in an intelligent way. level 2: content sharing • data collection: conducted in a legal and ethical manner (using general search agents, meta-search engines, personalized web crawlers). • data analysis: data interpretation and compilation of relevant data (text mining, platforms of monitoring). • dissemination of information: presentation to decision makers of what was analyzed (kahaner, 1998; ruach & santi, 2001). 39 • return: effectively taking into account the response of decision makers and their needs presented intelligently and continuously. level 3: platforms standby and software • the technological infrastructure for automating tasks. these tools increase the exhaustivity of the collection to ensure a better ability to rank and prioritize information (processing and analysis). the purpose of these applications is to provide everyone with the information enabling them to manage their business and thus achieve their objectives and optimize performance. besides the organizational revolution induced by the implementation of these tools, business intelligence has a considerable impact on the technological infrastructure of the company. first, the success of business intelligence is based on the ability to compile and analyze all available information. the volume of data to be processed can be considerable. for example, billions of lines published every day on supermarket receipts are valuable masses of information, but so are big data extracted and processed from operational systems. one specificity of business intelligence tools is their remoteness and independence from operational systems. these are tools that affect the strategic level of the organization. this separation is to avoid penalizing operational systems asking them to ensure heavy processing (sorting, extraction, computing). it also helps protect operational data by authorizing a posteriori analysis. it is therefore necessary to extract information from massive operational systems to inject into specific tools for "data warehousing" into multidimensional databases. the frequency of these extractions should be adapted to the analytical (daily, weekly, monthly) needs. finally, these extractions should allow the creation of a series of historical periods that can be shorter or longer as needed. these volumes should be protected not only because of their size but because of the sensitivity and confidentiality of any information they contain. since the end of 1990s, business intelligence has evolved in its definition according to the phases covered (lesca 2001; ruach and santi, 2001) and according to the tasks assigned. anticipative and collective strategic intelligence (vas-ic, or veille anticipative stratégiqueintelligence collective; lesca h, 2003) is the collective and proactive tool by which members of the organization perceive, process, choose and use relevant information about their external environment and the changes that occur therein. the use of vas-ic aims to help and create business opportunities, to innovate, to adapt to the changing environment, to increase responsiveness at the right time to avoid strategic surprises and to reduce risks and uncertainty. its main feature is to help the building of a proactive vision for decisions in the short, medium or long term. the objective is to act quickly at the right time and the lowest cost. the business intelligence process was to find, interpret and transform relevant information useful to the action of decisionmakers (blanco, 1998). ten researchers have contributed to the definition of strategic intelligence (including thietart, 1981; morin, 1985; marmuse, 1992; walls et al 1992; lesca, 2000,2001,2003). whatever the terminology used, all these notions express the fact that the strategic intelligence process is a voluntary process by which the company tracks, assimilates and disseminates information from the external environment for its use for action. it is also a process in which actors interact on a voluntary basis, according to objective, with information systems. thus, we move from process of information to its use and from use to the action. theoretically, monitoring tools are used and integrated into the business intelligence process. for a long time, business intelligence was confined in the upper echelons of business leaders. providing dashboards to some officials, the business intelligence tools were used to control and manage. democratization of these tools will facilitate common dissemination of information traditionally limited to the leaders to all levels of the company, making business intelligence an ideal tool for performance management (sakys and butleris, 2011; adamala and cidrin, 2011). the articles published in the journal of intelligence studies in business since 2011 focus on developing and testing models to evaluate bi systems and software. following these studies, new problems have emerged including differentiating bi vendors (solberg soilen and hasslinger, 2012) and classifying bi software based on their functionalities and performance (amara et al. 2012; nyblom et al. 2012; abzaltynova and williams, 2013). 40 3. methodology 3.1 data collection the study concentrated on a certain number of variables stemming from the literature in information systems, which join the problem of the evaluation of the bi tools used within the framework of the process of strategic intelligence. a questionnaire was built and tested by two specialists in the field of the conception of bi tools (lesca and caron-fasan, 2006; grublješič and jaklič, 2014). through this study, we tried to show the use of the watch tools and their applications. the survey was built with the aim of operationalizing the variables of the theoretical model as well as profiling the users who answer this survey. it was designed and diffused to 200 professionals. only 78 responses were usable for clustering of user’s monitoring tools (these respondents were from six sectors: 1) consulting/engineering; 2) commercial enterprises; 3) it; 4) electric and electronics; 5) financial enterprise; and 6) industry). this survey was also diffused by mail to 80 engineering students at lasalle beauvais institute (sector 7) of which 56 responded. 3.2 logic of the study to evaluate and compare the user profiles, the selected criteria were taken from the theoretical fusion of two models: technology / task fit (goodhue and thompson, 1995) and the technology acceptance (davis, 1989; venkatesh et al., 2003) as part of the literature on the evaluation of information systems: variable i: the dimension “task characteristics” was explained by: a. complexity of the task b. interdependence between the tasks variable ii: the dimension “technology characteristics” was measured by: a. bi tools used b. functionalities of bi tools: were the capacities of the system to help individuals or group determined by the type of system used (benbasat and nault, 1990; wierenga and van bruggen, 2000). the tasks presented in the questionnaire were: search information, store, process and extract a large quantity of information, resolve the semantic and syntactic problems. variable iii: the dimension “task/technology fit” aims to evaluate the user perception towards the used system. it is defined by the degree of correspondence between the functional needs relative to the task and the technical features offered by the information technology. it was explained by five criteria: a. data quality: measured the correspondence between needs and the available data, it also measured the exactness of these available data by using bi tools and the quality of data at a level of detail suitable for the tasks. b. localization of data: measured the ease of determining the availability and the exact sense of data (the existence in due course and under the deliberate size of public information). c. authorization of access: measured the accessibility of data (ease of connection and ease of extraction of public information). d. data compatibility: between the various sources of data. e. relevance of the system: making sure that bi tools did not raise unexpected problems or difficulty of use. variable iv: the dimension “intensity of bi tool use” was explained by: the intensity or frequency of use: it was a subjective appreciation of the increase or the decrease of the degree of use. the intensity depended on the integration of the bi system (grublješič and jaklič, 2014) and on the strategy adopted by the company. variable v: the dimension of the acceptance of bi technology: inspired by the “technology acceptance model” of davis (1989), this dimension was explained by: a. ease of use of the bi tools (davis, 1989): measured the degree of faith of a user in the effort to supply in order to use the system. to measure the ease of use, we referred to the measuring instrument of davis (1989) which consists of six items, 41 proven valid and reliable by doll and torkzadeh (1998). b. perceived utility of the bi tools: this element was not directly measurable. this notion came from microeconomic analysis: it was the measure of the use value of hardware or software for a user. it measured at the same time the impact of bi tools on productivity and quality. the perceived utility was defined by the degree of improvement of the performances expected from the use of the system (davis, 1989). c. satisfaction of the bi tools user: this was the degree of continuity of use by the individual. it was a positive faith of the individual perception which showed the value of bi tools. this variable was considered as a dimension of success of bi tools (sedden, 1997). it could influence the intention, but it was also a consequence of the use (delone and mclean, 2003) of the utility and the ease of use perceived. d. intention of bi tool’s use: the manager can accept a system but decides when he uses it or plans to use it in the process of decisionmaking. the intention of a user to use a system adopted by the organization as well as its satisfaction by this use depended on the utility and on the ease of use perceived from the system. 4. results and discussion descriptive statistics have been used in order to show population characteristics. we have used spss.19 to treat data. in total, 60.4% of respondents were male and 39.6% were female. furthermore, 17.2% of respondents were 23 years or less, 30.6% were between the ages of 23-26 years, 24.6% were between the ages of 27-35 years and 27.6% were 36 years or older. finally, our sample of users was composed of 58.2% students and 41.8% professionals (table 1). according to table 2, about 36% of respondents used general tools such as search engines and other free tools (such as google search, google alert and netvibes), while 45% used specialized tools like databases of patents or sector studies (such as espacenet, patenscope and xerfi), and a final 19.4% used platforms to monitor the competitive environment and social networks (such as cognos, business objects, sas, sindup and digimind). around 29% of respondents didn’t frequently use monitoring tools, 44.8% used them sometimes or often and 26.1% always used them. table 1 demographic profile of respondents (n = 134). char = characteristic. char. descriptor distribution (percentage) gender male 60.4 female 39.6 age < 23 years 17.2 23-26 years 30.6 27-35 years 24.6 > 36 years 27.6 occupation student 58.2 employed 41.8 table 2 tool usage and characteristics. char = characteristic. char. descriptor distribution (percentage) tool general tools 35.8 specialized tools 44.8 platforms 19.4 frequency of use never 8.2 rarely 20.9 sometimes 15.7 often 29.1 always 26.1 4.1 result 1: link between technology and tasks (appendix a. cluster analysis 1) a cluster analysis was applied to the data using the spad software. the aim was to classify the respondents in groups in order to know their characteristics. three main groups were identified: the first group contained 52 persons, the second one 35 persons and the third one 47 persons. the first group was composed of the persons who agreed with the fact that it is easy to find the location of data using key words. they also agreed with the link between the tasks and the work. according to the quality of the data, these people agreed that the data were up to date and facilitated their job. they disagreed 42 with the fact that they can’t obtain the data useful for their job. the technological tool (sindup) was very useful for their job and no problems were encountered with its use. these people were mostly from the sector of consulting and engineering (sector number1). the second group was composed of the persons who agreed with the fact that they were involved in tasks which deal with problems. they found it difficult to deal with the data sources. moreover, it was difficult to have the authorization to get the data, which were not always updated. for these people, it was not easy to find the location of the data through key words. in the third group, people also found that it was difficult to have the authorization to get the data but they didn’t agree that the tasks in which they were involved dealt with problems, particularly with data sources. these people were students of lasalle beauvais (sector number 7) 4.2 result 2: individual perception of tools (appendix b. cluster analysis 2) in this second phase of the analysis, two distinct groups: the first was composed of individuals from the it sector while those of the second group were mostly students. individuals in group 1, 83 in number, were satisfied or very satisfied with the sindup tool (information gathering, user interface, information processing) and more generally of monitoring tools. the functions of tools were generally well received (research and information extraction, processing and storage). individuals in group 2, numbering 51, were instead indifferent or even disagreed with the usefulness of monitoring tools including the sindup tool. they had a poorer perception of their duties and were unhappy. this was explained by the fact that this group of students used a new intelligence platform for the first time. user satisfaction was gained through experience and frequency of use. 5. conclusion the business intelligence process was to find, interpret and transform relevant information useful to the action of decision-makers. we presented the bi software systems that were studied by many authors that emphasized a different set of factors divided into three perspectives: organization, process and technology. we focused our article on the technology perspective and the evaluation of bi tools by proposing a cluster analysis of users’ perception and a classification of these tools used (general, specialized tools and platforms). technology-task fit and technology adoption models have been applicable to specific information systems, we adapted these models to bi tools, and this is a main theoretical finding. regarding the managerial implication, the first technology-task fit model showed three groups in those who used business intelligence tools, ranging from source identification to the dissemination of information. based on the innovation adoption model (rogers, 2003), we can see that the profile of the first group of users can be part of an advanced monitoring unit. the second and third groups of users were latecomers in adopting this technology. finding the monitoring tools not flexible, this implies the dissatisfaction with the quality of service offered by this technology may be due to limited use. two opposite groups were identified in the second technology adoption model, the first group is aware of the perceived usefulness of these monitoring tools and the second is not satisfied as completely as the first users of a platform (sindup) as part of a monitoring project. the difficulty lies in the appropriation of this tool by students and its adaptation to the selected bi project. regarding the users’ perceptions towards the bi tools, we suggested more attention from bi software vendors that should be integrated in their differentiation strategy with many key success factors. finally, we conclude that a bi tool implementation in a company is accompanied by organizational changes, which are sometimes cultural, where the financial impact (price) wasn’t negligible. this would explain, in part, why this technology is 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size = 52) characteristic variables average in the class overall average standard deviation in the class general standard deviation test statistic’s value p-value ct2 5,404 4,619 1,114 1,578 4,566 0,000 ld1 4,731 4,007 1,456 1,591 4,176 0,000 qd3 5,019 4,433 1,263 1,341 4,017 0,000 ld2 4,750 4,194 1,207 1,352 3,776 0,000 ct4 5,673 5,142 1,051 1,311 3,722 0,000 ct3 5,423 4,910 1,276 1,453 3,240 0,001 ct1 5,038 4,493 1,427 1,554 3,227 0,001 qd2 5,154 4,701 1,406 1,506 2,758 0,003 qd4 3,462 4,007 1,365 1,427 -3,513 0,000 cs3 4,096 4,672 1,348 1,455 -3,633 0,000 qd1 2,769 3,440 1,325 1,586 -3,886 0,000 po1 3,500 4,201 1,563 1,629 -3,955 0,000 po2 2,923 3,866 1,439 1,549 -5,588 0,000 ad1 2,000 3,187 1,109 1,754 -6,212 0,000 ad2 2,327 3,590 1,383 1,821 -6,367 0,000 legend of variables : ct : characteristics of task ld: localization of data qd: quality of data cs : compatibility of data sources po : relevance of system ad : accessibility of data 45 class 2/3 (weight = 35.00; size = 35) characteristic variables average in the class overall average standard deviation in the class general standard deviation test statistic’s value p-value cs3 5,914 4,672 0,732 1,455 5,858 0,000 cs2 5,800 4,672 1,141 1,530 5,058 0,000 ad2 4,886 3,590 1,526 1,821 4,880 0,000 ad1 4,229 3,187 1,692 1,754 4,073 0,000 qd4 4,829 4,007 1,424 1,427 3,945 0,000 po1 5,086 4,201 1,273 1,629 3,722 0,000 po2 4,686 3,866 1,190 1,549 3,630 0,000 cs1 5,114 4,269 1,545 1,631 3,556 0,000 qd1 4,200 3,440 1,653 1,586 3,285 0,001 ct2 5,286 4,619 1,161 1,578 2,896 0,002 ct1 5,143 4,493 1,150 1,554 2,870 0,002 ct3 5,486 4,910 1,180 1,453 2,715 0,003 ct4 5,543 5,142 1,024 1,311 2,098 0,018 ld1 3,486 4,007 1,680 1,591 -2,249 0,012 qd2 4,114 4,701 1,563 1,506 -2,673 0,004 ld2 3,457 4,194 1,273 1,352 -3,737 0,000 class 3/3 (weight = 47.00; size = 47) characteristic variables average in the class overall average standard deviation in the class general standard deviation test statistic’s value p-value ad1 3,723 3,187 1,620 1,754 2,594 0,005 po2 4,298 3,866 1,351 1,549 2,365 0,009 ad2 4,021 3,590 1,550 1,821 2,009 0,022 ld1 3,596 4,007 1,347 1,591 -2,194 0,014 qd3 4,064 4,433 1,060 1,341 -2,333 0,010 cs1 3,702 4,269 1,398 1,631 -2,945 0,002 cs2 3,957 4,672 1,254 1,530 -3,958 0,000 ct4 4,255 5,142 1,296 1,311 -5,732 0,000 ct3 3,915 4,910 1,285 1,453 -5,808 0,000 ct1 3,404 4,493 1,347 1,554 -5,937 0,000 ct2 3,255 4,619 1,360 1,578 -7,328 0,000 46 7.2 appendix b. individual perception of tools characterization by continuous variables of partition classes. class 1/2 (weight = 83.00; size = 83) characteristic variables average in the class overall average standard deviation in the class general standard deviation test statistic’s value p-value sat3 5,265 4,567 0,958 1,330 7,722 0,000 eou6 5,301 4,590 0,954 1,383 7,569 0,000 up5 5,578 4,851 1,066 1,453 7,366 0,000 up1 5,747 5,045 0,890 1,424 7,255 0,000 sat5 5,566 4,955 0,839 1,286 6,989 0,000 up2 5,843 5,201 0,975 1,359 6,948 0,000 up6 5,855 5,164 1,054 1,467 6,932 0,000 up3 5,602 4,918 1,075 1,461 6,892 0,000 up4 5,639 5,022 1,025 1,368 6,624 0,000 sat1 5,482 4,836 1,123 1,452 6,548 0,000 eou5 5,229 4,627 1,112 1,359 6,520 0,000 eou2 4,988 4,381 1,047 1,381 6,470 0,000 eou3 5,518 4,948 0,923 1,301 6,452 0,000 eou4 5,651 5,090 0,911 1,318 6,261 0,000 sat2 5,060 4,493 1,206 1,342 6,222 0,000 sat4 5,699 5,149 1,179 1,438 5,623 0,000 eou1 5,458 4,978 1,112 1,390 5,083 0,000 fonc3 5,313 4,910 1,119 1,296 4,574 0,000 fonc2 5,651 5,216 1,265 1,498 4,264 0,000 fonc1 4,807 4,410 1,954 1,921 3,039 0,001 legend of variables : eou : ease of use fonc : functionalities of bi tools up : perceived utility sat : satisfaction of bi tools 47 class 2/2 (weight = 51.00; size = 51) characteristic variables average in the class overall average standard deviation in the class general standard deviation test statistic’s value p-value fonc1 3,765 4,410 1,676 1,921 -3,039 0,001 fonc2 4,510 5,216 1,576 1,498 -4,264 0,000 fonc3 4,255 4,910 1,296 1,296 -4,574 0,000 eou1 4,196 4,978 1,442 1,390 -5,083 0,000 sat4 4,255 5,149 1,370 1,438 -5,623 0,000 sat2 3,569 4,493 0,995 1,342 -6,222 0,000 eou4 4,176 5,090 1,368 1,318 -6,261 0,000 eou3 4,020 4,948 1,291 1,301 -6,452 0,000 eou2 3,392 4,381 1,285 1,381 -6,470 0,000 eou5 3,647 4,627 1,135 1,359 -6,519 0,000 sat1 3,784 4,836 1,303 1,452 -6,548 0,000 up4 4,020 5,022 1,260 1,368 -6,624 0,000 up3 3,804 4,918 1,314 1,461 -6,892 0,000 up6 4,039 5,164 1,343 1,467 -6,932 0,000 up2 4,157 5,201 1,243 1,359 -6,948 0,000 sat5 3,961 4,955 1,267 1,286 -6,989 0,000 up1 3,902 5,045 1,390 1,424 -7,255 0,000 up5 3,667 4,851 1,199 1,453 -7,365 0,000 eou6 3,431 4,590 1,176 1,383 -7,569 0,000 sat3 3,431 4,567 1,034 1,330 -7,722 0,000 vol8no3paper4svarre and gaardboe to cite this article: svarre, t and gaardboe, r. (2018) characterizing business intelligence tasks, use and users in the workplace. journal of intelligence studies in business. 8 (3) 45-54. article url: https://ojs.hh.se/index.php/jisib/article/view/328 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index characterizing business intelligence tasks, use and users in the workplace tanja svarrea* and rikke gaardboea aaalborg universitet, denmark; *tanjasj@hum.aau.dk journal of intelligence studies in business please scroll down for article characterizing business intelligence tasks, use and users in the workplace tanja svarrea* and rikke gaardboea a aalborg universitet, denmark corresponding author (*): tanjasj@hum.aau.dk received 14 june 2018 accepted 27 december 2018 abstract this paper investigates business intelligence (bi) tasks, use and users in a workplace setting. the study reports on a mixed methods study of users in three different types of organisations employing bi. 1052 respondents answered a survey and 15 individual and 3 group interviews were conducted to elaborate on the survey results. the study finds that the majority of public bi users are employees, and fewer managers and students, that are handling a variety of tasks. although they can experience challenges learning and using the bi system, they are still satisfied with it from different perspectives. keywords business intelligence, information system use, workplace studies 1. introduction in 2017, gartner performed a worldwide survey of it spending among 2500 chief information officers (cios). business intelligence (bi) was one of the top technology priorities they identified (“gartner survey of more than 2,500 cios charts the rise of the digital ecosystem,” n.d.). one of the reasons for this focus on bi can be attributed to the increasing importance of bi systems. bi can be defined as "a broad category of technologies, applications, and processes for gathering, storing, accessing, and analysing data to help its users make better decisions" (wixom & watson, 2010, p. 13). in recent years, bi technologies have received considerable attention from both industry and the public sector (chen et al. 2012). bi is an interesting technology because several studies have shown that there is a relationship between computerdriven decisions and organisational performance (brynjolfsson, hitt, & kim, 2011). however, achieving bi success depends on both organization and staff characteristics (worley et al. 2005; salmasi et al. 2016). salmasi et al. (2016) previously conducted a study of organisational level competences in achieving success with bi. however, garcía and pinzón (2017) found that amongst others, the human perspective along with learning and skills are highly important to success. therefore, we will focus on the individual perspective and focus on the users in this paper. at the same time as the development of government processes, organisations and technologies are expected to change government employees' tasks. before the emergence of e-government, governments’ information technology and data management tasks were largely related to employment (see kraemer & dedrick, 1997). today, changes in work tasks are an expected consequence of governments’ digitising efforts. in particular, e-government is expected to affect the composition of public employees' tasks (dörfler, 2003; snellen, 2002). jürgensen (2012) documented employees' expectations within the framework of administrative grants and found that specific, routine tasks had fallen from employees’ daily tasks while the proportion of challenging applications had journal of intelligence studies in business vol. 8, no. 3 (2018) pp. 45-54 open access: freely available at: https://ojs.hh.se/ 46 risen. others note similar findings regarding tax department employees. the present paper is concerned with characterising the tasks users solve with bi. thus, to achieve success with bi at the user level, there is a relationship between task characteristics and success (petter et al. 2013). furthermore, we examine bi systems’ ability to underpin the tasks their users solve with bi in a danish e-government setting. the use of bi in e-government has spread worldwide in the latest decade. by improving access to bi among employees, governments are aiming to improve their decision-making processes, resource use, increase quality of the services delivered or even reduce costs. the paper is structured as follows: in the following section, we review existing studies of task characteristics and present the theoretical framework for the data collection process. the next section is a presentation of the research methods applied in the study: a survey questionnaire, 12 semi-structured interviews and three group interviews. the subsequent section presents our findings with regard to the research question. the paper concludes with closing remarks and suggestions for further research. 2. theoretical background 2.1 the concept of a task a task is what individuals engage in to keep their work or life continuing (li & belkin, 2008), and the concept of ‘tasks’ is important in human–computer interaction. a task (whether workor leisure-related) may trigger information-oriented activities (byström katriina & hansen preben, 2005). on this basis, the task becomes a central element of any user’s context, as it arises from an incident external to the user that first triggers an information need, followed by a searching activity (ingwersen & järvelin, 2005). being external to the user, the task, as such, will be easier to observe and measure, from a research perspective, if compared to information needs that are inherent to the user. tasks have been analysed in human– computer interactions from many different perspectives. historically, the focus on tasks went from a technical (ergonomic) perspective, to a conceptual (information processing) perspective and then to work-process (contextual) models (crystal & ellington, 2004). different approaches can be followed to gain insight into tasks in specific contexts. hierarchical task analysis breaks generic tasks into smaller sub tasks with related sub goals. (stanton, 2006). the purpose is to become able to map goals, and sub goals in particular, with technologies or information systems to ensure successful solutions for the users’ tasks. a different way of perceiving tasks is to model them according to li and belkin’s (li & belkin, 2008) taxonomy of task characteristics. departing from a literature review, the taxonomy defines tasks on the basis of generic facets and common attributes, thus representing a top-down perspective on the task concept. the different approaches to understanding and operationalising tasks emphasises the importance of the concept in human–computer interaction. we have not identified any papers to date within the bi systems field that have attempted to identify and characterise the specific tasks users carry out. the purpose of the current paper is to address this gap in the research in a public organisation context. 2.2 delone & mclean: the is success model delone and mclean’s is success model (delone & mclean, 1992) is used to frame the study. the model represents a framework for understanding influential factors on information systems’ success. the identified variables in the model include system quality, information quality, use, user satisfaction, individual impact and organisational impact. we use the model to frame the quantitative data collection below, as it represents a consolidated theoretical model (eg. iivari, 2005), providing both an organisational and system-based perspective on the notion of tasks. 3. research design and method in this study, we used a multiphase ‘mixed methods’ research design. the research design consists of two main phases, namely a questionnaire and interviews. the mixed methods approach represents a form of triangulation; the quantitative approach provides a broader view, while the qualitative approach provides greater depth. together, the approaches yield results from which more accurate inferences can be made (seddon et al. 1999). 3.1 quantitative method we chose a questionnaire to research users' perceptions of different task characteristics. 47 data were collected via an online survey available for a specific period during the spring of 2017. all respondents were bi end-users who had access rights to their organisation’s bi system. the users accessed the bi web client through a browser, meaning that bi can be implemented across an entire organisation without having to install software on each machine. all bi users from three public organisations were invited to complete the survey. the three organisations were a municipality using business objects, a public healthcare organisation (among 12 hospitals) using tableau and a university using qlikview. initially, we conducted a pilot study before distributing the survey to all invitees. the survey was based on a literature review, and three researchers in the field evaluated the questions. afterwards, bi users with differing levels of bi experience evaluated the questionnaire using a think-aloud test (nielsen, 1994). minor refinements were made based on these results. the final part of the pilot study called for testing the survey on 24 bi users. after evaluating those results, the questionnaire was distributed by email to 4901 invitees. participants accessed the questionnaire via a personal invitation email with a unique link to the online survey. each respondent received an adapted questionnaire depending on whether he or she had previously used or never used the bi in question. participation in the survey was voluntary, and two reminders were sent. in total, 1741 people completed the survey, resulting in a response rate of 35.52%. among these, 1052 were used for the statistical analysis, as 689 respondents indicated that they did not use bi. all data were analysed in spss version 24.0. 3.2 qualitative method the next step in our research design was interviewing bi users. in addition to the questionnaire, we used interviews for three reasons: qualitative data can explain the complexity of the users’ tasks identified in the survey, data from interviews helps us to grasp the users’ contexts and interviews make it possible to check for potential additional elements of bi systems’ successes or failures (driscoll et al. 2007). we conducted 15 interviews as part of the qualitative study, and three group interviews with a total of seven participants were arranged for the three organisations. the results from the survey were presented to the groups, and the participants in the group interviews commented on the survey results. afterwards, we formulated a semi-structured interview. the semi-structured interviews had an average length of 45 minutes. all interviews were transcribed and analysed in nvivo version 11.0. we used a deductive method to categorise the different tasks’ descriptions. the different categories were adapted from earlier work. we will use the interviews to exemplify quantitative findings in the analysis. 4. results the results of the study are presented in three sections: end users’ characteristics, task characteristics and the users’ assessments of bi success. 4.1 end user characteristics in the survey, the respondents were asked about their gender, age (table 1), education, organisational role and experience. table 1 respondents' ages. age n % 20–29 years 66 4 30–39 years 225 22 40–49 years 345 33 50–59 years 325 31 60–69 years 91 9 total 1052 100 table 2 organizational roles. role n % employees 758 72 managers 223 22 students 65 6 missing 6 0 total 1052 100 most of the respondents were women (73%). as shown in table 1, the majority of respondents were 40–49 years old. their educational levels varied; most commonly, the respondents either held a master’s degree (35%) or a vocational degree (30%) (see figure 1). the respondents’ organisational roles were distributed among employees (72%), managers 48 (21%) and students (6%) (see table 2). for the sake of comparison, negash & gray (2008) found that bi is mainly used by managers and highly educated employees. finally, we can characterise the respondents in terms of their bi experience. the distribution appears in figure 2. the question asked the respondents to assess their bi experience on a scale from 1 to 5, where 1 is ‘little experience’ and 5 is ‘great experience’. more than three-fourths (76%) of the respondents rated their bi experience at 3 or below, indicating that they were not highly experienced users. here, it should be noted that two of the three organisations under investigation had used bi for a number of years, while one implemented bi about two years ago (in 2016). this difference of time spent with bi may explain some of the differences in experience assessments among the organisations. in related studies, technology experience has been found to be a critical factor for system success (dishaw & strong, 2003; marshall et al. 2000; thompson et al. 1994). corresponding explanations were found in the interviews. one interview participant explained: “…the more experience you get with the system, the more you think: ‘well, this is fine and really easy to understand’. but then when you get out and have to explain it – for instance at meetings in our controller group, if i have prepared something and ask ‘what do you think about this?’, then they are like, ‘we don’t understand that’, and i think, ‘well, that is easy to understand’. but you easily get into an understanding of what you think is easy to understandable” (2017). apart from confirming the importance of experience, the quote above also illustrates the difference between system users (users interacting with the system) and information users (employees using the information from bi). 4.2 characteristics of bi tasks we identified bi tasks from several different dimensions in the study. at an overall level, the respondents were asked what bi was primarily used for. the distribution of their answers is shown in figure 3. more than half (56%) reported their main use is for data extraction, 29.8% point to reporting and the last 14.2% mentioned ad-hoc analysis as their most frequent use of the system. the respondents were also asked what specific bi functionalities they use. the results appear in figure 4. as shown, the most-used function by far was data filtering, followed by compiling data in a table and visualisation. less common functionalities included drilling down, layout formatting, calculations (e.g., numeration) and merging (e.g., linking data together from different sources). figure 1 respondents’ educational levels. 0 50 100 150 200 250 300 350 1 2 3 4 5 figure 2 respondents’ assessments of their bi experience 14% 56% 30% ad hoc-analysis data extraction reporting figure 3 what is bi primarily used for? 49 figure 4 functionalities used in bi figure 5 the amount of work tasks in which bi is used figure 5 presents the share of tasks that bi represents among the total tasks handled by the respondents. as is evident from the figure, the majority use bi less than half of the time, or not at all. thus, bi use represents a minor part of the total number of tasks respondents handled. however, based on interview data, it appears that, despite these minor use patterns, users still consider bi to be an important tool in their everyday work practice. all statements in the survey were rated on a 5-point scale, with 1 being highly disagree and 5 being highly agree. as shown in table 3, the mean response rating is above 3, indicating that the respondents more or less agree with the statement. the statement with the lowest rating addresses the amount of data in the system and the relation with the respondents’ tasks. in the interviews, more participants claimed that they think the amount of data is appropriate. one comment may explain some of the lower rating of the statement. the participant states: “as regards the report module, i can create the things i would like to, but it is less appropriate in terms of publication and dissemination. it comes in short in terms of saying ’we would like to continue here, but we can’t with this tool, so we need new technology to move on’” (2017). table 3 univariate statistics on ‘task compatibility’ reply min max mean sd this information is useful for my work 1 5 3.86 0.974 this information is complete for my needs 1 5 3.28 0.976 this information is sufficiently up-to-date for my work 1 5 3.46 1.04 this information is relevant to our work 1 5 3.45 0.943 table 4 univariate statistics on ‘task significance’ statement min max mean sd the tasks i complete in bi are an important part of my tasks. 1 5 3.44 1.180 i make decisions on the basis of the tasks i complete in bi. 1 5 3.32 1.284 my tasks completed in bi are important to other employees in the organisation. 1 5 3.50 1.176 other people make decisions based on the tasks i complete in bi. 1 5 3.45 1.234 my tasks in bi are important for collaborators outside the organisation. 1 5 2.28 1.273 error! reference source not found. shows the distribution of responses as regards ‘task significance’. in all statements, except for the last one, the mean value is between 3 and 4. in general, the respondents consider their bi tasks to be important, and they or others make decisions on these tasks. the respondents do not consider the tasks to be important for collaboration outside of their organisation, so the bi is instead used as an internal tool. the following quotes from the interviews illustrate the significance of bi tasks: “the tasks are pivotal, because we need to touch upon the economy so much. we need to file reports very, very much” (2018). “i think it is quite important, at least in relation to many of the requests we get. we get a lot of requests that are used politically, or […] 773 434 308 181 170 126 100 57 0 100 200 300 400 500 600 700 800 900 fi lte r d ata me rg e d ata in a… vi su ali za tio n dr illdo wn no t u sin g t he … fo rm att ing la yo ut ma ke ca lcu lat ion s me rg e d ata fr om … 16% 70% 7%6%1% none below half part of the tasks half part of the tasks above half part of the tasks all tasks 50 so, if we didn’t have the option […]. usually, it is with a very short time frame, where a politician asks, ‘we need this for our…’ or it can be on the same day that you are in a meeting and they go, ‘we need this…’ and that would then be within an hour” (2017). the quotes illustrate why bi is important to the users. one thing is that they need to file reports within their organisations. the other is that several users receive requests from others regarding facts that are being drawn from the bi system. table 5 univariate statistics on ‘task interdependence’. statement min max mean sd if i do not complete my tasks in bi, one or more employees in the organisation cannot complete their tasks. 1 5 2.49 1.346 in bi, i can only do tasks if one or more employees have completed another task first. 1 5 2.61 1.378 i am independent of other employees to prepare tasks in bi. 1 5 2.94 1.339 task interdependence reflects the users’ dependencies in relation to the system; this can be in terms of a user’s dependence on something, or another’s dependence on the user. these assessments are presented in table 5. here, we can see that, across all three organisations, the users do not depend on anything to use bi themselves. it is assumed that the bi system is available, updated and so on. further, the respondents disagree that their tasks depend on colleagues’ completion of other tasks first. although the ratings for task interdependence are low, the interviews revealed dependencies, typically in the participants’ ability to deliver information to other employees, such as managers. to illustrate: “well, the closest managers” (2017). “the department management, and then our doctors. they are the ones using me for this” (2017). “that would typically be our political committees or the management of our administration” (2017). a partial explanation for the dependencies reported of the respondents may be found in this quote from the interviews: “everyone can go in and get data. it is just not everyone [who] know[s] how to use it. the benefit of asking me is that i know data better than most people, and by that i also know how to use data and how to do this. that’s how it works” (2017). in sum, one of the barriers to employees’ access to the bi system is a lack of knowledge of the underlying data models. the respondents were also asked about the difficulty of the tasks solved by the bi system. the assessments appear in error! reference source not found.. table 6 univariate statistics on ‘task difficulty’. statement min max mean sd bi makes it possible to complete complicated tasks. 1 5 3.12 0.984 the tasks i complete in bi require specialised knowledge. 1 5 3.05 1.127 the tasks i solve in bi are ones i have never faced before. 1 5 2.55 1.207 the assessments of the two first statements in table 6 signal a neutral attitude. the latter statement, concerning the novelty of the tasks, demonstrates that the users, to some extent, consider bi tasks to be routine. despite their ratings of the statements, the interviews reveal nuances of task difficulty. thus, the interviews demonstrate examples of both routine and more complex tasks. to illustrate routine tasks, consider: “well, if i have to do a monthly follow-up, then i need to define and follow up on every cost centre and see the transactions, if they are okay. that is like a routine task” (2017). “that is when i make a list of the patients we had for the last five years with a specific diagnosis. super easy task, because the template was developed for that purpose. some bi people have been thinking big thoughts, and there are very good headings for what you should go and look for in the system, so it is just a matter of going in and typing your filters” (2017). 51 however, the interviews also reveal examples of more complex tasks. for instance: “we had some where we should combine the kind of medicine they got, which is a standard extract in bi, with how long they were hospitalised. so, they should have had both a certain kind of medicine and be hospitalised for more than five days, for instance” (2017). here, the complexity consists of combining different data types. another kind of complexity is when the underlying data models are complex. for example: “yes, you need to know your data and which… you could believe that you have the right data and then there is really something you didn’t take into account. i think i have tried that quite often, at least in the first couple of years i was working with this. that you think that you had everything under consideration and then there is some kind of twist of it” (2017). the last cluster of statements, regarding the users’ tasks, concerns the specificity of these tasks. the assessments appear in table 7. the respondents’ assessments are average when rating to what extent the tasks are defined before they start solving them. there is a general agreement that the tasks can be solved in different ways. again, the table indicates some extent of the routine tasks in the low rating of the repeatability of the tasks in the last statement. table 7 univariate statistics on ‘task specificity’. statement min max mean sd my tasks are always defined before i complete them in bi. 1 5 3.03 1.061 the tasks i complete in bi can be done in more than one way. 1 5 3.29 0.935 normally, i do not complete the same kinds of tasks in bi. 1 5 2.03 1.117 4.3 users’ assessments of bi success in addition to the respondents’ background characteristics and the characteristics of their bi tasks, the survey also considered system and information quality as independent variables that influence the success of the bi system. the assessments of system quality appear in table 8. in that table, all statements have mean ratings below 3, meaning that the users find the system difficult to learn, use and understand. the challenges are expressed in the interviews: “it requires quite a lot to learn how to use bi” (2017). “i would say that, about using the front end part of it, if you haven’t used it a lot, then it can be quite difficult to find out how to present it” (2017). table 8 univariate statistics on ‘system quality’ statement min max mean sd bi is easy to learn. 1 5 2.62 1.098 bi is easy to use. 1 5 2.74 1.094 the information in bi is easy to understand. 1 5 2.89 1.009 when the users have difficulties using the bi system, they report two strategies for the appropriation of the technology (dourish, 2003). one is asking a colleague for help, which is considered an example of the employee aiming to adopt the technology. the other exemplifies adaptation. here, the users import the data into excel: “at times, i import it into excel. i might as well admit it: i love excel, including the graphical part. i like working with that” (2017). table 9 univariate statistics on ‘information quality’. statement min max mean sd data are displayed in a consistent format in bi. 1 5 3.11 0.948 the data in bi have high validity. 1 5 3.20 0.955 other employees in the organisation also think the data in bi have a high degree of validity. 1 5 3.04 0.871 information quality is another aspect that influences the users’ assessment of bi success. three statements are included in the construct. the assessments appear in table 9. overall, the users have a neutral assessment of the three statements with a mean slightly above 3. 52 thus, the users believe the consistency of the data to be reasonable. the data validity is rated slightly higher, while the users’ impressions of other employees’ impressions receive the lowest, but also most neutral, assessment. regarding users’ satisfaction with the bi system (see table 10), they do not think that the system’s functions and capabilities are as expected (rated at a mean of 2.82). however, they would still recommend the system to colleagues (rated at a mean of 3.21). the overall rating of satisfaction has a mean of 3.07. table 10 univariate statistics on ‘user satisfaction’. statement min max mean sd bi has all the functions and capabilities i expect it to have. 1 5 2.82 1.067 if a colleague asked, i would recommend bi. 1 5 3.21 1.161 overall, how satisfied are you with bi? 1 5 3.07 1.014 the interviews revealed some of the issues the users experience with the system. in some cases, the users prefer to report in excel. for instance: “it is not like it is working in the same way as a spread sheet with formulas and the like. it is a little more complicated and heavy to work with” (2017). the users’ individual impact is lower, when asked if they can make reports in bi effectively (mean of 2.98) and quickly (mean of 2.73). completing the reports in bi is rated higher (mean of 3.04), suggesting that, although it may not be effective or fast, the users do finish their reports in the system (see table 11). table 11 univariate statistics on ‘individual impact’. statement min max mean sd i can effectively make my reports using bi. 1 5 2.98 1.105 i can complete my reports quickly using bi. 1 5 2.73 1.240 i can complete my reports using bi. 1 5 3.04 1.111 5. discussion the data analysis has shown that the majority of respondents and active users of bi are employees, and not managers as found in other studies. to most respondents, bi was not playing a dominant role in their work life, which may also explain their assessment of their own experience as being limited. however, the users handle routine tasks and more difficult tasks in the system. the most important task handled in the bi system was data extraction and more specifically filtering data and merging them into tables. the most important use of bi is internally in the organisations. the users do not think it is very easy to learn how to use the system, but they do experience consistency and validity of the data in the system, and they would recommend it to colleagues. the results of the study can be used to indicate how implementation can be approached to take into account the strengths and challenges users experience in using bi as a part of their work practice. the results demonstrate that the users still can experience challenges in using the system, although the system has been implemented for some time in all three case organisations. this paper used delone & mclean (1992) for guiding the data collection. that enables comparison across diverse organisations for a general picture of bi use and users in the public domain. however, if the aim is a more detailed understanding of the bi tasks and related use in subdomains within this domain, more task-oriented theories as presented in the theory section could generate a more detailed understanding of task characteristics and the system use generated on that basis. 6. conclusion this paper has provided a picture of the characteristics of bi users and their tasks carried out by means of a bi system in 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(2005). implementation and optimisation of erp systems: a better integration of processes, roles, knowledge and user competencies. computers in industry, 56(6), 620–638. https://doi.org/10.1016/j.compind.2005.03.006 a discourse analysis methodology based on semantic principles an application to brands, journalists and consumers discourses luc grivel* and olivier bousquet** *index-paragraphe, université de paris 8, 2, rue de la liberte saint denis, france, université de paris 1, (panthéon-sorbonne), paris, france **index-paragraphe, université de paris 8, 2 rue de la liberte saint denis, france harris interactive, paris, france luc.grivel@univ-paris1.fr, olivier.obousquet@gmail.com received 20 july 2011; received in revised form 10 september 2011; accepted 29 december 2011 abstract: this is a r&d paper. it describes an analysis coming from a research project about opinion measurement and monitoring on the internet. this research is realized within "paragraphe" laboratory, in partnership with the market research institute harris interactive (cifre grant beginning july 2010). the purpose of the study was to define crm possibilities. the targets of the study were self-employed workers and very small businesses. the discourses analysis is linked to a qualitative study. it turns around three types of discourses: brands, journalists and clients’ discourses. in the brand discourses analysis we benchmarked brand websites belonging to several businesses. in this first step, we tried to identify the most used words and promises by brands to the target we were studying. for that benchmark, we downloaded "professionals" sections of the websites. clients’ discourses analysis is based on opened answers coming from satisfaction questionnaires. the questions we are studying have been asked after a call to a hot line or after a technician intervention. journalists’ discourses analysis is based on articles, published on information websites specialized in harris interactive's client sector. these websites were chosen because we considered them to be representative of information sources, which the target could consult. keywords: discourse analysis, brand management, market research 1. introduction regarding the deep change in our relation to communication, university paris 8’s paragraphe laboratory and the market research institute harris interactive started a common project in 2010, aiming at developing a methodology to monitor and measure opinions on the internet. to define our research area, we first analyzed various opinion and market research processes (master 1 essay). then available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 76-86 https://ojs.hh.se/ 77 we did discourses analysis with computer tools assistance (master 2 essay) for answering the question: what are the contributions and challenges of a computer assisted semantic analysis, within the analysis of web-coming discourses? this article describes that experiment. the tool that has been chosen for this discourse analysis is tropes. first, we will justify this choice and describe how the tool works, our approach of the mission and then present the results of the study. finally, we will discuss economical, scientific and methodological contributions of an opinion analysis method based on semantic analysis, and identify the technical and methodological limits of this method. 1.1. a semantic experiment in a crm context the experiment takes place as part of a harris interactive mission for a client. the goal of that mission was to improve the brand’s performances in terms of relations with specific clients: very small firms. these ones are particular targets and it can be difficult for a great brand to define the way to communicate with them. the research was aimed to identify the levers that could be pulled to improve the brand’s performances. 2. methodology the research is divided in three phases: a qualitative phase (individual interviews of professionals), a quantitative one (validation and establishment of a decision model based on ideas defined in the first phase) and a phase of discourse analysis. this step is the one which we are focusing on in this article. the qualitative phase is an exploration phase. its goal is to explore every possible dimensions of very small firms’ engagement to a brand, specifically in the brand’s sector. we also needed to understand the expectations of the targets and the way they are satisfied or dissatisfied, and to identify experiences that can make clients leave the brand for another one. the discourses analysis is linked to the qualitative phase. it is about three types of discourses: brand discourses: this analysis is based on a benchmark of twenty websites of brands belonging to varied business sectors. we searched the “professionals” sections of the websites. this discourse analysis enabled us to identify words, expressions and different types of discourses that these brands use when they are communicating to professionals. journalistic discourses: this is based on analysis of articles. these articles are taken from mass specialized website, chosen because they represent the type of sources that are used by the targets. consumer discourses: this analysis is based on answers to open ended questions in satisfaction surveys. the one that we used is a survey that had been sent after a call to a hotline or after an intervention by a technician. 2.1 tool choice a main criterion that led to the choice of the tool is that it should be based on semantic-pragmatic principles. that means that the tool had to allow an analysis, taking into account a specific conception of meaning: the meaning of a discourse can't be understood without a reference to the enunciation context. a second criterion that has been important for the choice is ease of use: it should be as easy as possible since all research executives should be able to use it the third criterion was linked to market research structures. the experiment research was an adhoc research and it was not certain that it would be followed by other similar studies. thus the tool had to be adapted to this specific logic. for instance, a global monitoring solution, that most often implies a yearly subscription or additional software development, was not adapted. following these three fundamental criteria, the chosen tool has been tropes. this software is based on the work of ghiglione (1998), a psychological linguist. inspired by goffman and hintikka, ghiglione (1998) worked on automated content analysis, and more particularly on cognitive and discursive analysis. his idea is that communication issues are defined by the fact that every speaker takes place in a communication system: he never speaks alone. his speech is the expression of a "possible world", that is personal to the speaker, but which is in dispute with other people, who have their own "possible worlds". communication is like a permanent clash between subjectivities, and it has to be based on argumentation. in that context, syntactical operators play a fundamental role; they are weapons used in the fight, the discourses elements that impose the speaker’s personality. they are central elements in ghiglione's theory. thus, this study distinguishes between three types of words: references that "name the objects of the world", verbs that place rn in the proposed universe, and the other categories of words, negatively defined as all words that are neither a reference nor a verb. these words are, among others, adjectives, modalities, connectors, all words that show the speaker through the discourse and adjust the meaning of what is said. therefore, meaning is built by the articulation of these three categories of words, inside phrases, considered as the smallest meaning unity. tropes is 78 based on propositional analysis principles: discourses are cut in propositions (simple phrases), considered as micro-universes concentrating a simple and self-sufficient meaning. the analysis is based on the text cutting in propositions, based on a punctuation and syntax analysis (conjunctions, syntactic links and so on). a proposition is at least made of an “actant” (from french, which acts), an “acted” (that is subjected to the action) and a verb (that makes the action). this minimalistic model can be extended, adding complements. in each proposition, we can find referent nucleus linked by verbs, defined by adjectives and integrated to argumentation thanks to modalities, connectors and pronouns. the software allows a first step of meaning analysis through an organization of the references. this organization is based on an internal dictionary, like a generalist thesaurus of french language. when a text contains a word that is missing in the dictionary, this is individually underlined. this means that the word is not integrated in the following diagram. this thesaurus is the foundation of tropes' work, in what the developers call a "linguistic analyze engine". thus, tropes allows a semantic-pragmatic approach. as well as proposing a generalist thesaurus of french language, it enables the analyst to build his own thesauruses. as every analyzes is inscribed in a specific context, the building of a particular dictionary allows the analyst to give a specific and unique meaning to every word, linked to the context. 2.2. tool configuration in this article, we have developed a specific thesaurus, suitable for the research context. the role of the thesaurus is to enable comparison between the discourses of firms from varied economic sectors, but also to compare the discourses of these firms with the client's. their common point is the relation built between brand and consumer. thus, marketing has developed an angle of analysis for that relation: the marketing mix, or the 4p’s (product, price, place, promotion). we use an adaptation of that tool and we have defined five common entries for all studied discourses:  "material": notions linked to material aspects of the firm offer (infrastructures and terminals)  "relations and services": vocabulary linked to the services offered by the firm, and client relationship  "pricing policy": vocabulary linked to prices, pricing offers, sales and so on  "brand": quotes of brands and sub-brands  "client or professional": shows the consistency of the vocabulary naming the clients, particularly professional clients. the five entries are the base in the analysis of the crm themes quoted by the firms and the clients. these are common to all sectors and they enable comparison. in a context of topic-centered analysis, this choice seems to be problematic. as written by pang and lee (2008) comparing topic-centered analysis to sentiment-centered analysis templates in “traditional information extraction can differ greatly from one domain to another”. this is why each entry’s content was specific to each sector. in thesauruses, words have a unique meaning, linked to the context in which they are used, called pragmatic-semantic. these five entries are themselves switched in several branches. they underline five ways a firm can showcase its offer with five brand profiles (different but not exclusive). the entries are large enough to be operative for all sectors. thus, the five entries are always the same, but the notions that compose them are specific to each sector. this resulted in creating a specific thesaurus for each sector (without changing the five entries). for example, in the telecommunication sector, we classified the notion "internet" in the "material entry” because we considered that it is an infrastructure (and not a service itself). for energy or bank/insurance sectors, “internet” is classified as "relations and services" because it becomes a communication device, a tool linked to client relations. building a thesaurus is quite time consuming. it took two days to build the first thesaurus. the following ones, which are just adaptations of that first one, have been built in half a day each. this work has been made possible by notions extraction. before the discourses analysis, websites have been analyzed with tropes to extract the vocabulary and notions that should be organized. in such a framework, this method appears as the safest to build an efficient thesaurus, which means a thesaurus that is exhaustive but without unnecessary notions and words. geyken (2008) 79 states that if an expression is part of the language, it must appear in the corpus, and conversely the frequency of an expression in the corpus is the image of its frequency in language. the software shows the words in their context, which allows the analyst to define the meaning of words in the specific context of the text, and to classify them correctly. in the end, we notice that the thesaurus, on the contrary to what it may seem, do not only make a lexical analysis. even if that method is focused on the vocabulary used in the text, tropes does not only count occurrences of lexical forms. (by lexical form this article refers to a series of characters between two spaces or punctuation signs). the software has previously created a word based on recognition and categorization of words (nouns, adjectives, verbs and so on) and the fact that the analyst classifies these forms in a thesaurus is a first step in pragmatic-semantic. words included in the thesaurus have a unique meaning, linked to the usage context. therefore the thesaurus appears both as the central tool of computerassisted discourses analysis and as a way to compare the various websites of the benchmark, as well as the element that links the three steps of analysis. 3. data, analyze and implications through tropes, we obtained various analyses quite different from the ones we usually obtain in market research. in this part, we are presenting some possible analysis on different data: documentary data and open-ended questions. 3.1 analyzing secondary data: websites benchmark and journalistic articles analysis the website benchmark and the journalistic articles analysis are two examples of secondary data analysis. when it comes to websites, each one is synthesized in a personal identity card. this is described in figure 2 and it is divided in two parts:  on the left side, basic information about the website: general statistics (number of pages, words, used notions), top ten most used notions (what we call "notions" is actually the "equivalent classes", but translated into a more accessible word here), frequently used pronouns, discourses concentration and the distribution (in percents) of the five entries of the thesaurus.  the right part is dedicated to analysis and commentaries about the website. figure 3 represents the detailed distribution of equivalent classes defined in the thesaurus. it is fundamental to understand brand discourse. it describes the semantic organization of all the vocabulary on the website and that organization is partly determinate by the objectives of the study. in this example, the discourse brand underlines the material dimension of its offer, particularly concerning infrastructures. the discourse brand also insists on relations and services. we notice the importance of the word "solution", which appears as a central word in a client’s relation to that brand. more than half of the brand discourse is contained in the two entries material, relations and services. we also notice that brand quotations are more than one notion out of five, which is more than the pricing policy. this brand seems to be selfcentered, when it comes to highlighting its brand. concerning the client, a firm belonging to a mobile fleet, is not a small firm. in the case we are describing here, another type of secondary data has been studied: journalistic articles. a double approach has been necessary: thematic and semantic. the thematic approach defines the importance of brands in articles (principal or secondary place) and the tonality of the articles. semantic analysis has been more precise and complete than the one on websites. we used tropes' "actant chart". this chart represents relations between words. it is based on syntactic structure of sentences. on the horizontal axe, references are defined as "actant" (acts on the verb), or “acted” (object of the action): the further to the right a notion is, the more passive it is in the text. vertically, this chart represents concentration of relations between notions. the higher a notion is, the wider is its usage context. thus, websites are often less redacted, with lots of non-verbal phrases (at least in commercial websites). the analysis presented in figure 4 describes the central place of telecommunication companies in journalists’ discourses. 80 figure 2: identity card of a brand figure 3: the distribution of equivalent classes defines in the thesaurus 81 figure 4: chart of repartition for actor and acted references figure 5: map of the notion concerning the intervention of a technician on site 82 all companies are quoted in agent position, while the user is more often an object. we notice that the user seldom is a professional, which shows that generalist websites are not adjusted for professionals. "user" and "consumer" are submitted to companies, they have no real choice. they are used in varied contexts, in other words their relation are less concentrated. in general, all notions that matter to the material basis of the offer are on the right side of the chart (passive position), whereas words that refer to price policy and services tend to be in the middle of the chart. we notice that the words "tribunal" and "appeal" take place in an agent position, with weakly concentrated relations: this is explained by articles concerning orange's issues with french justice. relations are concentrated because the contexts are always similar. this analysis has a low interest, particularly because the corpus has not been defined precisely enough. most of the interesting information comes from thematic analysis. this remark shows the pertinence of semantic analysis in that precise case. it also introduces questions regarding corpus definition. 3.2 clients discourses analysis the last step of the study concerned clients’ discourses. the source we used was different: data had been collected in a quantitative questionnaire. this example can be seen as a new way to analyze open-ended questions. we have studied data in a double way. firstly, we used a notions map, based on the actant/acted analysis, and then we used a linguistic analysis (linking lexical and syntactical analysis). the map of notions enables us to analyze the answers in a double way, both thematic and discursive. figure 5 is representing the map of the different notions taken into account, regarding a technician intervention. the chart in figure 5 gives several information types. firstly, we notice that terms which are in an agent position designate the clients’ expectations regarding technical interventions. it also appears that all these notions are in the lower side of the chart: they are used in more concentrated contexts. these expectations are the starting point of most answers: several sentences begin with these words, which are obvious and central for the respondents. notions placed in object position allow us to understand a different type of discourse logic. in the beginning of the questionnaire people seem to have a problem: main notions ("waiting", "time"), are always associated. the perception of technical answers belongs to a more diversified context: there is a variety of issues, answers and perceptions. this is even more obvious concerning the commercial relation (appointment making, contact with a consultant). finally, conclusions of the intervention (thanks or waiting for a continuation) take place in varied contexts. this analysis, completed by syntactical and semantic analysis, allows an understanding of the way respondents are implied in their answer. thus, we notice that adjectives ("competent", "fast", pleasant", "good", "efficient", "professional", "clear" and so on) and verbs ("fix", "solve", answer", "satisfy" and so on) that are used show strong expectations towards technical support, but these expectations are often deceived. this is highlighted by the use of opposition connectors (contrasting judgment: "but", "in spite of", "however") and of intensity and negation modalities (60 percent of modalities). injunction verbs ("must", “improve”, “can”, “have to" and so on) are associated with adjectives and verbs that underline the fact that clients expect a change from a firm that do not satisfy their needs. through the linguistic operators, we can see a personal involvement (showed by modalities, but also by adjectives and connectors) of the clients in their relation with the firm. these linguistic clues also show the clients’ feeling that their dissatisfaction is not taken into account (injunctions to change). thus, the technical relation with the brand seems to be the place of a personal, or even emotional, involvement with clients. that is why technical support is a sensitive part of the client relation. this type of analysis can be a supplement of a more traditional opened-ended questions' coding, that determines generic themes, but does not highlight linguistic stakes. for that matter, semantic analysis can be used for coding. on the one hand, it allows gaining time; on the other hand, it enables building more precise and exhaustive coding patterns (taken the entire corpus into account, not only an extract of verbatim). 4. conclusion and further research the method used in the article has allowed us to analyze the discourses of twenty brands belonging to varied sectors and to compare possibilities of client relations, on a deeper level. finally, it enabled us to better understand our clients’ discourses. clients’ discourses analysis has permitted us to compare brands discourses to the clients’ feelings in their contact experiences with the firm. openended questions have been analyzed on a deeper level, since brands discourses were more appropriate to this type of analysis. on websites, language is generally poor: for example, sentences are often non-verbal, which is a problem for a syntactic analysis or to determine the agents and objects. answers to open-ended questions are different. they look most often like correct sentences, built according to a precise grammar. that is why it is possible to analyze them on a 83 deeper level. therefore, this data has been studied according to a double approach: building a notions map (chart of agents/objects notions) and semantic analysis linking lexical and syntactical aspects. the double approach has given us an understanding of the heart of clients discourses, to analyze the way they are implied in the discourses about (or to) the brand. as well as finding the expectations of the clients we have understood the way these expectations are expressed, and above all the way people handle issues and find resolutions. a graphical approach enabled us to understand the general process of discourses, whereas the analysis of syntactical forms (specific verbs, adjectives, connectors and so on) permitted us to understand how clients are personally implied in their discourses. 4.1 automated semantic contribution to opinion and discourses understanding from a scientific and methodological point of view, automated semantic analysis enables us to gain more detailed and deeper understanding. the previous example concerning open-ended questions, with semantic analysis tools can build coding pattern taking into account all responses, and not only a sample of answers. thus, the coding pattern is more precise because it is based on a more exhaustive view on information. automated semantic allows approaching discourses in a different way than traditional content analysis. this enables it to become enveloped in the message sender. semantic analysis exceeds in a way content analysis and it takes the content of the discourses ("dictum") and its form (how it is said) into account. semantic analysis gives a more complete view on discourses because it takes into account syntactical constructions, modalities and usage of adjectives, as well as all other words that enables discovery of the speaker’s personality and the discourse enunciation context. this highlights the way the speaker is implied in his or her own discourse, in an emotional or argumentative way. it allows placing discourses and speakers in wider groups. barthes (1984) states that: "every speech belongs inevitably to a dialect." (barthes 1984, 439). this means that discourses are never the speech of just one individual: each individual shares a part of its individuality with other people and with other people of its group(s). this is called inter-subjectivity (larsson, 2008). semantic-pragmatic analysis should enable us to reach this discourse inter-subjectivity, which means taking into account the way the speaker keeps to a context, with interactions, and history. this should enable extract specificities of groups, defined before analysis (according to "objective" criteria like gender or age) or defined by analysis (by recognition of regularities and disruptions of discourse). this approach, that places context in the middle of the analysis, is not only linked to the semantic approach. it is a global approach for information and intelligence studies. this can be summarized in floridi’s (2007) “subjectivist interpretation of relevant information”, which implies that information relevance can be understood only when it comes to an exchange. semantic analysis permits a qualitative approach of wider samples. hitherto, qualitative research is limited to questions with relatively small samples. this limit is practical: the qualitative questioning of a large amount of people is costly, in term of fieldworks but also when it comes to analysis and interpretation time. computer tools (particularly in automated semantic analysis) enable us to analyze answers for wider qualitative samples. as a result, we can plan to hit the experience saturation threshold, regarding the moment when all experiences on a subject can be considered. 4.2 technical limits from a technical point of view, the main limit of semantic analysis is the difficulty to adapt it to spontaneous discourses language. for example, an online forum is a discourse place. on a forum dedicated to a firm, the firm’s name is obvious and the participants do not name it often. instead they use the third person ("it" or equivalent). this raises some questions: how can we automatically spot the posts that speak about the firm? we cannot determinate that every "it" refers to the brand. how can we take the speaking moments into account? discussions are defined by interruptions, people speaking when they may not. finally, how can we manage interruptions in debates? speeches are not put together in a logical way, but in a chronological way. it is not always the logic of the debates that determines the apparition order of speeches; it is more often the writing time of the contribution. a contribution do not necessarily make reference to a previous post, it can answer to a question that has been asked a few messages before. in simple sentences, anaphora management is a problem. on a discussion forum, the anaphora referent is not even in the previous clause. in the "style" point of view, authors tend to "write as they speak", they use abbreviations, forget capital letters, punctuation signs and make orthographic, grammatical or syntactical mistakes. it is difficult for software that has been developed on formal language models to analyze informal or incomplete formulations, as we can find on forums like twitter and facebook. this is why it appears essential to include abbreviations in terminological dictionaries. it is not possible to include all incorrect orthographic 84 forms in dictionaries. the introduction of automatic orthographic correctors, or at least of a tool that tries to compare unknown forms to lemmatized form, seems to be a solution. to analyze such texts in natural language, it is necessary to begin by editing the text, which can be time consuming work. in this time consuming aspect, editing the texts can be compared to another step of analysis: corpus constitution. when analyzing great quantities of texts semantically and with computer assistance, we adopt a corpus linguistic logic. in this field, sources determination is essential. the grouping of texts in a corpus is a first semantic approach. when we choose the elements of the corpus, we propose a first step of interpretation, linked to our context. the sources must be coherent, and have a representative dimension. for example, if we chose to analyze a brand image through what is said on forums, it is a first choice. this involves considering if the chosen forums are representative for what is said on forums in general, or even on the internet, not to say that it is representative of what all consumers of the brands think. this interpretation depends on the scope that is adopted. that is why the corpus must be determined, often by an exchange between the analyst and the client. in a context of business, this need can be a limit to introduction of automated semantic since it involve stakeholders spending time on determining the corpus. other technical limits appear when we decide to analyze information coming from the internet. an efficient way to analyze web pages is to investigate and save them in order to analyze them a second time. this can be made difficult by limits linked to websites structure and to the way they are created. on a web page, how can we identify relevant information? heuristics exist and in addition to useful information, a web page often contains a navigation menu, advertisements, hypertext links to others articles, legal information and so on. for example, the navigation menu contains several html links, advertisement in links and pictures, and legal information can be found on all pages. the message is rich in meaning and poor in hyperlinks. automation of websites investigation raises the question of information hierarchy. during the analysis, it is difficult to know the audience of a page and to organize all pages in a hierarchy. thus, we can ask if information on a page that is often visited (for example a home page) has the same value as information placed on a page with few visitors. 4.3 renewal and methodological uncertainties automated semantic introduces challenges in some practices. the first of these challenges regards the gap between qualitative and quantitative fields. this approach can be compared to two types of methodologies. it can be considered as a qualitative methodology since its object is an unformed discourse. automated semantic manages with quantitative processing matter and in order to process language through a computer, it must be transformed into computer data, which means mathematically managed. automated analysis tools for language supply quantitative data; linguistic forms occurrences are represented as statistics, charts, tables and so on, which are quantitative representations. this is true when it comes to opinion mining, in which information is often envisaged as rating inferences, rankings and so on. automated semantic analysis often has a qualitative part; it is possible and necessary, to come back to plain text. this qualitative comeback is a way to set highlighted linguistic forms back in their production context. this return to context is necessary to understand texts. without it, the risk of misinterpretation is high. quantification is not enough. methodologies and tools of automated semantics are double-edge: qualitative material (discourse) is analyzed with a statistics and probabilistic logic, and allows results that are between the two areas. the analyst using such tools has to master the two areas of the methodology. we exceed areas of market research (where we experimented) and of social sciences. this is likely to meet strong reticence (in each of these sectors). the reluctance can be analyzed in two areas. the first one, which is the most obvious, regards the reliability and pertinence of the results. the trust and value of information coming from these types of tools can be questioned. the second reluctance is the fear of being compared with a computer, the fear that human intelligence could be belittled by the use of a computer tool. these two reluctances are linked. it seems necessary to understand that a tool cannot do anything without human intelligence, without human interpretation aptitude. a tool is only assistance for the analyst, who keeps his legitimacy as a decider and controller. to understand the analyst role in a research process using automated semantics, a distinction exposed by rastier (1994) can be used. as authors of this article we have adapted this distinction to our subject. rastier (1994) analyzes understanding systems and distinguishes three steps: analysis, interpretation and understanding. he defines an understanding system as "every system that tries to pass from a syntactical tree to a semantic network and to make inferences inside this network." (rastier 1994, 240). for him, there are three steps in the progression and at each step we can distinguish the role of the computer and of humans. 85 the first step, the syntactical tree, equates to analysis. it can be compared to morphological and syntactical analyses, which are the first parts of automated text analysis. this analysis is entirely done by software, which recognizes words and defines their relations. the second step, semantic network, corresponds to interpretation and is performed by computer and human. the goal is to define a "signification", in the meaning adopted by rastier (1994): "meaning became impoverished of context." (rastier 1994, 240). some software automates this step, like is the case with tropes. this software uses two methods to determinate signification. firstly, it extracts syntactical marks, modalities and so on, which organize the utterance and show interlocutors presence in discourses. it also classifies and organizes notions into a hierarchy based on its french language thesaurus. thus, the software offers significance to each word, defining synonymy, hyperonymy or hyponymy links. for example, terms as "firm", enterprise" or "society" have a similar meaning: they belong to the equivalence class "firm". this signification is abstract and polysemy risks are high because interpretation does not take context into account. the last step, the understanding system, is comprehension. this step is completely mental, which means that it can only be human. it enables us to pass from "signification" to "meaning", to "create inferences inside the semantic network." the analyst uses all the elements extracted by the computer, the analyst makes comparisons and links them, in order to define the final meaning of the text. thus, the building of a personalized thesaurus allows giving each word and each notion a specific meaning, relative to analysis context. the real value-added of the analysis appears at this level. analysis is here fueled by the analyst’s knowledge because analysts’ own external data, external knowledge, memory and critical thoughts permit them to extract useful information from the text. the usage of understanding systems, underline that computer and human intelligence are complementary. software maintains assistance tools for analysts who remain the centre of analysis, since they are able to detect strategic information. the other thing that automated semantic transforms is the way speakers are considered by analysts, particularly in market research. by putting discourses in the middle of interests, it highlights the exchange between the person who questions and the one who answers. in internet discourses, there is an exchange, at least implicit, between a speaker and a receiver. this point of view allows placing people in the group(s) where they belong. in traditional analysis, particularities of targets are highlighted: these targets are defined by objective criteria like age, gender or product consumption. in our new point of view, we consider publics that belong to diverse social groups, have a history, and live in a specific context. we put the knowledge of the discourse sender in the middle of our questions, which implies other questions, particularly in relation with the collection of consumer discourses on the internet. we often ignore people who are speaking on the web and who they could represent. it could be interesting to question the identity of those internet users, and the criteria that should be chosen to define this identity. should these criteria be the same as in "real" life, or should they be different ones? being an internet user speaking on websites, is it not the beginning of an identity? this question about validity of an analysis concerning people we know nothing about can be seen as a limit of that method. setting up an automated semantic analysis solution is costly. that must not be ignored. this is an investment of research and development. buying a tool, taking time to discover software and train employees is an investment and setting up an automated semantic analysis solution is at least a middle-term investment. this can be complicated in a sector such as market research since visibility often does not go above a few months. these remarks added to previously quoted technical limits, also underline that the tool choice may not have been as relevant as previously thought. today, powerful solutions exist, which manage efficient technical limits. for future analysis, it would be efficient to develop a partnership with a firm that develops software. in that case, market research institute could concentrate on its core work, on its value-added; analysis; and entrust software firms with technical issues. regarding these limits, automated semantic for opinion analysis must stay a complementary methodology, which can help existing methodologies. it assists these methodologies in two ways. first, it allows a faster and easier processing for specific steps (open-ended questions, qualitative numerations and so on). it also permits a new point of view on problems processed, in addition to traditional content analysis methodologies. references barthes r. 1984. le bruissement de la langue. essais critiques iv, seuil, points essais, 439 p. beaudoin j. 2005. l’opinion, c’est combien? pour une économie de l’opinion, village mondial, 237 p. bourdieu p. 1984. « l’opinion publique n’existe pas », in questions de sociologie, les editions de minuit, reprise, pp. 222 235 cardie c. 1997. “empirical methods in information extraction”, ai magazine, vol 18, 86 condamines, a. 2007. « l’interprétation sémantique de corpus : le cas de la structuration de terminologies », in revue française de linguistique appliquée, xii-1, juin, pp. 39 52 demaziere, d. (ed). 2006. analyses textuelles en sociologie – logiciels, méthodes, usages, pur, méthodes, 219 p. floridi, l. 2007. a subjectivist interpretation of relevant information », in pichler, a. and hrachovec, h., wittgenstein and the philosophy of information, proceedings of the 30. ludwig wittgenstein symposium, vol. 1 fuchs, c. (ed). 1993. linguistique et traitement automatique des langues, hachette-classiques, hu linguistique, 303 p. geyken, a. 2008. « quelques problèmes observés dans l’élaboration de dictionnaires à partir de corpus », in langages, 171, septembre ghiglione, r. (ed). 1998. l’analyse automatique des contenus, dunod, psycho sup, 168 p. jenny, j. 2004. « quali / quanti – distinction artificielle, fallacieuse et stérile ! », 1er congrès de l’afs, groupe rtf 20, session n°4, 25 février, consultable à l’adresse http://testconso.typepad.com/files/jenny-quantiquali.pdf (le 8 novembre 2010) larsson, b. 2008. « le sens commun ou la sémantique comme science de l’intersubjectivité humaine », in langages, 170, juin, pp. 28 40 marc, x, tchernia, j. (ed). 2007. etudier l’opinion, pug, 260 p. martin, r. 2001. sémantique et automate, puf, ecritures électroniques, 190 p. pang, b. and lee, l. 2008. opinion mining and sentiment analysis, foundations and trends in information retrieval, 2 (1-2), rastier f., cavazza m., abeille a. 1994. sémantique pour l’analyse. de la linguistique à l’informatique, masson, 240 p. tamba i. 2005. la sémantique, puf, que saisje?, 128 p. vol8no1paper4_barnea to cite this article: barnea, a. (2018) israeli start-ups – especially in cyber security: can a new model enhance their survival rate? journal of intelligence studies in business. 8 (1) 37-45. article url: https://ojs.hh.se/index.php/jisib/article/view/285 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index israeli start-ups – especially in cyber security: can a n e w mo d e l e n h a n c e t h e i r s u r vi va l r a t e ? avner barneaa* anetanya academic college, netanya, israel; *avnerpro@netvision.net.il journal of intelligence studies in business please scroll down for article israeli start-ups – especially in cyber security: can a new model enhance their survival rate? avner barneaa* a netanya academic college, netanya, israel corresponding author (*): avnerpro@netvision.net.il accepted 21 march 2018 abstract start-up companies are the fastest growing business in israel. however, half of them do not last through their fourth year. this paper looks into the issue of the power of israeli start-ups to survive and to become successful companies. the challenge is to seek new directions, which will help this sector to change this disappointing course. the start-up sector has a significant contribution to the strength of the israeli economy which leans on its intellectual resources. based on my continuing consulting in implementing competitive intelligence to local israeli start-ups and further research that i have done by following closely the added value of developing capabilities, which enable better understanding of the external environment, i have found that one of the main causes of the high percentage of failures of israeli start-ups is the difficulties in comprehending the competitive landscape, which has a significant contribution to making them less competitive. by using a new model, the competitive review model, which considers the special attributes of start-ups, especially in cyber security, this kind of small company can be better prepared for intense competition. this is in addition to the lean start-up model, which is not executed in this segment in israel and faces serious resistance based mainly on opposition to unfamiliar input. based on combining the new competitive review model with existing analytical models, a few local start-ups' executives have already matured by awareness about the value of sensing the external environment, which have the potential to change the course of at least some of the israeli start-ups and increase the success rate for this sector. keywords adaptability, competition, competitive review model, competitive intelligence, four corners model, israel, lean start-up, strategic planning, start-ups 1. introduction the growth of the israeli economy is dependent much on its export, mainly high-technology industries and the ability to develop new technologies and applications that would be attractive in the global markets (central bureau of statistics, 2014). many firms are aware that one of the keys to success is intimate knowledge of the global markets (bulley, baku and allan, 2014) by ongoing monitoring of the changes and it is not enough to offer advanced technological solutions (prescott, 1999) and to prevent business failures as a result of intelligence downfalls in business (tsitoura & stephens, 2012). many corporations already understand that competitive intelligence (blenkhorn, & fleisher, 2005) can be of great help in reaching a competitive advantage and sustaining it (global intelligence alliance, 2009, 2011). it is evident that companies with poor information about competitive landscapes were stuck being reactive (le bon, 2014). the use of competitive intelligence can be referred to also as journal of intelligence studies in business vol. 8, no. 1 (2018) pp. 37-45 open access: freely available at: https://ojs.hh.se/ 38 integrated intelligence capabilities, which occur in many larger corporations (bulger, 2016) and more professionals in corporations are using intelligence for their daily missions (mcgonagle and misner-elias, 2016). it looks as though corporations that have ci practices do not use half of the information they collect for various reasons (gilad and fuld, 2016). the challenge is to adjust between the needs of executives and how their corporations collect and process intelligence. there are also those who believe (hoppe, 2015) that in most organizations, intelligence is constructed informally. i do not share this view. large and medium-size israeli companies are moving forward slowly and recent studies conducted indicate this direction (barnea, 2006, barnea, 2009). it seems that competitive intelligence as a discipline in israel that is underdeveloped (barnea, 2016) and it is focused more on fulfilling the immediate needs of the corporate decision-makers rather than on working closely with marketing and strategic planning. in a study titled "why start-up companies failed to adopt competitive intelligence" (barnea, 2006) the key conclusion was that the absence of competitive intelligence awareness was one of the main reasons why israeli start-up companies failed in the global markets during the 1990s. the author has offered different ways to change the situation; one of the primary suggestions was to appoint a senior executive to take care of this issue, as monitoring the international markets was a critical factor for such companies. the author has recommended also to the investment ventures to encourage these ideas and to act to implement them. most of these lessons have never been fulfilled. another study that has looked at ci in israel, mainly from the aspects of using expert tools (barnea, 2009), has revealed that "local firms were not prepared to invest in new ci tools that would enable ci professionals to perform better. as a result, most ci professionals have to continue using generic tools such as office (microsoft), which offers unsatisfactory solutions to their ci program needs". and also that "the high level ci solutions have not reached its potential target market due to a lack of support by senior executives." in 2015, research on the use of open source intelligence (osint) by israeli firms (markovich, 2015) showed that there is intense use of these sources, but the added value to the corporate decision-making process was little. it overlooked the entire picture of ci in the israeli business scene. 2. methodology throughout my consulting in ci among israeli start-ups, i have noticed that their sense of the competitive landscape is very low. the next step was to hold discussions with executives in these start-ups regarding the reasons behind this phenomenon and also watch the start-ups' business performance, mainly in their rate of success to their efforts to penetrate into the markets after their products were completed. as a result, i have proposed the competitive review model with support from other tools as will be described later. after the implementation of the new model in these start-ups, i interviewed the relevant executives in these start-ups to receive feedback. so far, based on a small number of start-ups, it looks as if the decision-making process has been improved and makes these new business entities more competitive. i plan to expand this model to more israeli start-ups and hope that in two years there will be more information regarding the added value of this model. in building the methodology for this model, i used the grounded theory (glazer & strauss, 1967), which guides the scholar on matters of data collection and details rigorous procedures for data analysis. it is based on a systematic watch of certain activities and based upon these views, to build a theory which will improve the quality of these acts. 2.1 limits of the research this research is based on a few start-ups that have agreed to implement the model which will be presented later. it is obviously a limitation, but it looks that in the coming year, more startups will participate and this will enable further analysis to reach a better understanding of how much this new model is really helping startups to become more competitive. 2.2 the startup industry in israel over the last 15 years, israel has built a strong reputation as one of the leading countries in the segment of startups. dan senor and saul singer's book "start-up nation: the story of israel's economic miracle" (senor and singer, 2009), has been translated into more than 30 languages, has strengthened the success story of israela state that produces more start-up companies than large, peaceful, and stable 39 nations such as japan, china, india, korea, canada, and the united kingdom. the success of israel's high-tech sector has attracted attention from larger corporations and each year around 1015 israeli startups are acquired by global corporations for billions of dollars in total. a substantial number of foreign investors are investing directly in israel's technology market through foreign venture capital funds (vcs), corporate vcs or as individuals ("angels"), as a result of the tremendous success of the growing israeli technology market. contrary to the public perception, the israeli start-up success report 1999-2014 (ivc, 2016) uncovers that about 47% of israeli start-ups stop operating (3985 start-ups out of 8489) within 3.5 years on average since their foundation. we do not see an intense theoretical effort dedicated to change that direction from the business studies point of view. in the last three years, israel has seen a very significant growth in the segment of new start-ups in cyber security. it looks as if these start-ups are facing the same illness as regular start-ups – lack of profound understanding of the competitive landscape, both competitors and customers. perhaps adaptive start-up companies that are capable of change fast have better chances to last. in 2016, the israeli start-ups industry raised an all-time high of $4.8 billion, up to 11% from the $4.4 billion raised in 2015 (solomon, 2017). the year 2015 was the most successful for israeli high-tech capital raising activity – 708 deals accounted for an exceptional investment of $4.43 billion. the amount reflected a 30 percent increase from the previous record in 2014, when 690 deals attracted $3.42 billion. the average deal peaked with $6.3 million in 2015, compared with the previous year's $5 million average and a $4 million average deal in the past 10 years (ivc and kmpg, 2016). however, a closer look at the start-up industry in israel shows that the picture is not so pink. although the israeli start-up industry is very attractive for investors, the israeli startup success report 1999-2014 (ivc, 2016) shows that about 46% of the israeli start-ups stop operating within 3.5 years on average since their foundation and 41% of venturebacked start-ups are shut down or are sold at a loss. another study published in israel shows similar rates of failure: the number of start-up companies which were terminated is high and in recent years (2005-2014), there are about 300 (on average) a year when about 700 new start-up companies have been initiated (orpaz, 2017). following the length of life of start-ups operating in israel in 2005-2014 clarifies that there was no change from 10 years ago and 46% of companies lasted between 1 3 years, while 76% of these companies did not last more than six years (orpaz, 2017). similar findings have been reported already regarding the dot com era in israel (barnea, 2006). the amount of money lost in these failures in israel is huge, reaching approximately $ 1 billion a year. it is relevant to mention that the tendency in israel is often to hold companies alive as long as possible, relative to the u.s. or europe and thus to give them more time to bleed. it is a component of the israeli business culture not to give up, and to try again, but it succeeds only in some cases. shutting off failed start-ups is usually hidden and is not reported through the business media, while great success stories like selling waze, the world's largest communitybased traffic and navigation application, to google for $ 1 billion, was in the israeli headlines for a long period. another recent great success is selling the israeli mobileye, operating in development of vision technology for advanced driver assistance systems (adas) and autonomous driving, to intel for $15 billion. the difficulties of start-ups survival are known also in other countries: shekhar ghosh, a senior lecturer at harvard business school wrote, "three out of four start-ups venture capital-backed start-ups do not return capital to investors" (blank, 2013). the figures in the us are quite similarabout 60% of start-ups survived until the third year, and less than 35% matured and survived the sixth year (barnea, 2014). other sources of information indicate that 90% of start-ups fail (patel, 2015). 2.3 lessons from start-up companies according to cb insights research (griffith, 2014), which follows worldwide tech markets, including start-ups, the main reason for failures of start-ups was a low demand for their products: almost 50% of start-ups did not survive for that reason. the second reason for failures was ending of the funds, and the third reason for closing the doors was losing the battle against competitors. however, it would be more refined to put together reasons 1 and 3, as they are interconnected, enable one to see that almost 60% of start-ups have lost the 40 battle to survive for poor understanding of the essence of markets and competitors. looking at many start-up companies worldwide for a long-time shows the following (blank, 2013): 1. usually successful start-ups grow differently than ordinary companies, and they are quickly adjusting themselves to changes and to inputs from customers until they reach to their targets (if they get there!). 2. only seldom, business plans survived as is after the first feedback from customers. 3. most business plans of start-ups are not practical and preparing them in the conventional way can be a waste of time. 4. too often, start-ups lack the knowledge and the experience acquired from monitoring competitors and the marketplace, so they are incline to repeat similar mistakes or ignore important lessons. contrary to existing companies, which are busy implementing business plans, successful start-ups tend to look for the right business plans. this great difference has an incredible impact on their chances to succeed (blank, 2013). blank proposed (blank, 2013), that startups will fulfill the approach of "lean start-up" that is taught in more than 30 business schools in universities in the us. the "lean start-up" methodology is based upon three principles: 1. entrepreneurs have to drop a conventional business plan and offer a set of assumptions or wild guesses that can clarify how start-ups can bring value to customers. 2. to test their assumptions, start-ups have to go out to the field and to ask customers and potential partners about the new product, including characteristics, pricing, distribution and strategies how to reach to customers and based on this information to update their assumptions regarding the new product. 3. further, "lean startup" has to cut the length of the product development cycle by adjusting fast to the information gathered. through this process it will enable creating a product that stands in the most advanced requirements. this new model by blank assumes that contrary to start-ups that launched in the dot com era, working in "silent motion" to avoid potential competitors learning about their plans and to find they are not relevant to the customers eventually led to their collapse. as blank proposes, it is desirable to act differently to increase success rates by exposing beta products at an early stage. feedback gathered from customers and sometimes from competitors, is more significant than secrecy and therefore, delivers better results. lowering failure rates of startups have major economic implications. as a result of the fierce competition in many industries, countless jobs are lost and successful start-ups have a great potential to increase the employment rates and so to compensate for the jobs that are lost in existing industries. so far, israeli start-ups are not aware of the "lean start-up" approach. one of the weaknesses of the "lean start up" model is that it does not include the fundamental need to systematically monitor the external environment, especially competitors, and to learn continuously about potential threats and opportunities. largescale enterprises and leading business schools in north america, europe and parts of asia recognize that competitive intelligence has increasingly come of age as it steadily expands “into mainstream business practices" (hawley & marden, 2006). it happens also in israeli business schools. there is a need within the start-up industry to adopt the competitive intelligence discipline and to implement it suitably with its specific needs. 2.4 the challenge of cyber security start-ups in israel in the last three years, israel has seen a very significant growth in the segment of new startups in cyber security in israel. two years ago there were around 200 israeli cyber start-ups, and we are seeing now around 450. this is very fast growth, especially as the support by the governmental funds is quite minimal. we already see first indicators that in 2017, launching new israeli start-ups in cyber seem 41 to be slowing. most of the funds for these ventures as well as most start-ups in israel are coming from outside israel. in the last year, we are facing also a huge increase in chinese interest funding and acquiring new israeli technologies. the israeli cyber security start-ups’ solutions are covering almost every relevant business segment including automotive, health, infrastructure, information systems, mobile applications, and enterprises. cyber security expenses will keep on growing across all industries. stricter regulation is brought in, while the threats and the concerns are increasing. according to the grant thornton report, (grant thornton, 2015) the leading accountancy and advisory organization, cyberattacks cost global business about $315 billion over the past 12 months. a doubt has been raised regarding the future of these start-ups in cyber (orpaz, 2017). is it possible to forecast who will survive and who will disappear? it is already known that the rate of israeli start-ups that do not survive is quite high – around 50% after their fourth year. it is not known yet how the figures will look within the cyber segment of start-ups, as most of them are quite new. looking into the start-up industry in israel uncovered that about 90% of these start-ups do not monitor systematically the external business landscape. it appears that start-ups in cyber in israel are focused more on the quality and the innovation of the products they offer to their clients. considerably less effort is put into the analytical issues such as what exactly their competitors are offering or intend to offer, what the clients are looking for and analyzing the gaps between "our" solutions vs. the competitors, possibly by applying the methodology of gap analysis (businessdictionary, 2017). israeli outsourcing information suppliers are providing their start-up clients with intelligence on their competitors. they are pretending to give insights; however, these information specialists are unable to give added value and quality intelligence as this needs intimate knowledge of each segment in such a level that only those who are doing this internally on a daily basis, can really deliver. the conclusion is that especially in the start-up industry, outsourcing inputs are incapable of providing proper intelligence and are caught in information rather than in intelligence. the second point is that while considering the small size of most of the start-ups, they need to build up their own capability of intelligence and understand the competitive arena with adaption to their special characteristics. unfortunately, an effort to build a small dedicated intelligence internal capability too often comes across with internal opposition claiming that the resources for such a move are limited. 3. competitive review model: the theory a new model, the competitive review model, has been introduced lately in israel, in order to challenge and support start-ups to become more competitive, that probably increase their survival success rate. so far, this model which i have developed and tested in the last year was implemented in a few start-ups in israel. it is still in its first stage of implementation. it was also presented a few months ago in the quarterly meeting of the israeli ci forum (fimat) and received a warm welcome. 3.1 basic assumptions 1. start-ups are in critical need for dynamic monitoring of the competitive environment. doing this must be an internal business procedure supported by the senior management. 2. each start-up needs to designate a "ci care taker" (a partial job). the goal of this function is to make sure that the firm will be aware of external changes and new directions in its specific segment and to evaluate their possible impact on the firm. 3. intelligence reports have to be prepared internally (osint, supported by outsourcing gathering) implementing the rule of sharing of information internally to avoid unnecessary silos. the outcome is completive review reports. 3.2 competitive review model: the process 3.2.1 aim to present the senior management of the start-up with periodic assessments of the competitive environment to help decisionmakers to better understand threats and opportunities and to consider formulating these insights into business strategy. 3.2.2 when assessments will be presented each quarter. an annual intelligence report will be presented towards at the end of the year. the annual 42 report will outline the current year and will present also trends and potential moves for the next year. only occurring of highly significant events will need an immediate special report. 3.2.3 the outline of the competitive review intelligence report the outline of the concise competitive review report is as following: a. executive summary – what are the major changes in the last period that may effect "our" performance and business plan? b. analysis of the competitive environment – description of important changes that occurred during the period reviewed: notable successes and failures of competitors, new players, new technologies, important changes in regulation, significant mergers and acquisitions in your segment, vital innovation moves and major market trends and clients' expectations. c. analysis of key players: related to key competitors and strategic suppliers separately: key movements, current status of products / capabilities and plans for the future. this stage can be supported by competitive analysis template which divides the analysis into four categories: company highlights, market information, product information and swot information. d. summary and conclusions how “our” start-up stands relative to the competitors / strategic customers and against the trends in the competition environment. it will include also defining what the opportunities are for “us”. 3.2.4 competitive review model: further recommendations based on the experience acquired already in israel, there are further recommendations. a. with regard to the examination of each key competitor and its future strategic moves, it is highly recommended to strengthen the analytical capability by using porter's four corners model (porter, 1980; gilead, 2009) as a complementary tool, which will provide with remarkable insights the future moves and the strategy of key competitors. b. it is also suggested that competitive review intelligence reports are shared with the senior executives of the start-up and with key investors and further used as an agenda for strategic discussions. c. start-ups have also to implement rules for gathering information at exhibitions and professional conferences attended by their employees (calof and fox, 2003). unfortunately, when this is not done systematically it causes losses of meaningful insights. figure 1 four corners model. 43 the competitive review model, actually forced start-ups which use it to review systematically the competitive landscape. its outcome is important not only to executives but also to the investors to be able to understand better the capabilities of start-ups to compete successfully and to be more knowledgeable in their discussions with the senior executive of "their" startups. 3.3 adaptability and start-ups: adjusting organizational culture throughout the process of developing and executing the competitive review model i have noticed that the success of this model depends not only on its own merits but also on the ability of these companies to change. a major challenge of implementing this model in start-ups is also to learn how best to adopt new plans and to establish decisions that may improve their potential to succeed. the meaning is that they need to act on signals of change from the external environment and to be able to move forward rapidly. to do so, start-ups have to behave as "adaptive companies" (reeves and deimler, 2011) in order to gain competitive advantage. adaptability as a new competitive capability in response to uncertainty (garcia-salmones and yin, 2014) can be also a result of experimenting with customers in the early stage as already mentioned by blank (blank, 2013). adaptability is the organization´s capacity to change internally in response to external conditions (denison and mishra, 1995) which can change the classical strategic thinking, and force start-ups to operate as "adaptive companies" while they create more fluid structures, which can make the decision-making process faster and better. 4. conclusions unfortunately, a high number of israeli start-ups will not survive, and many of them will disappear within the first three to four years after their establishment as happens also in the start-up industry in other nations. regarding the cyber start-ups, it is fairly reasonable to foresee a process of fast consolidation, which has already begun. contrary to what most founders and vc officials think and expect, i believe that those who will survive will be those who have the best understanding of the markets and the competition i.e. identify early indicators of opportunities and threats, and not those who just have better products. so, start-ups have to be superior "adaptive companies" and move fast to improve their dynamic monitoring and especially their intelligence of the markets and the competitive arena to support building a winning strategy. thinking more about the future and the next move by competitors supported by systematic use of the competitive review model is essential. in two years, it will be possible to look at the success rates of start-ups that have implemented the new competitive review model and to compare it with those who continue with their "traditional" direction. 5. a short case study the managing director of the israeli start-up (hola, http://hola.org/), ofer vilenski, has admitted recently (vilenski, 2017) that: "for four years, since 2013, we have developed a technology that will connect users to accelerate the internet. however, when we went out with the product on the market, we discovered that it did not interest anyone. as a result, the start-up has created an organizational culture of quick attempts that focus on a particular direction only if two conditions were met: the basic assumptions of the product can be examined within two weeks and there is business potential in a direction that justifies the experiment. otherwise, you have to kill the idea or change the focus. the start-up raised about $30 million, but most of the money was spent without any real progress." following this experience, the company started teaching its employees that it is okay to fail and to move on. vilenski emphasized that: "most people are not used to changing direction at 90 degrees. it took a long time to convince them that an approach of rapid change is the way to achieve success, that they have to move quickly to change direction, to adapt to what is happening on the ground, and not to treat the ego." today hola's employees prefer to find out why a certain product will not work, instead of getting stuck after three years of working on a 44 product that is not required. vilenski is confident that: "you cannot tell if something is good or bad, and you have to know how to accept it (even outside the world of work). therefore, a management culture must be developed to ensure that product development is a rapid evolutionary process." the hola start-up reported (2017) a significant milestone: 117 million installations have so far been recorded for the company's product. the company's main product is a vpn service that allows you to bypass geographic or government restrictions for surfing the internet. the success story of the hola start-up can be summarized by the following key success factors: ability to become an adoptive company, receiving early feedback from the customers about the new product, and to develop greater awareness of the activity by the competitors to observe how it is possible to 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"we invested four years in a product that did not interest anyone", themarker (in hebrew), may 30, at http://www.themarker.com/technation/startu p/1.4137788 opinion section 79 evaluating the impact and value of competitive intelligence from the users perspective the case of the national research council’s technical intelligence unit jonathan calof 1 1 telfer, canada email: calof@telfer.uottawa.ca received december 20, accepted december 25 2014 abstract: understanding and being able to measure and prove the impact and value of intelligence is of significant importance. the objective of this study was to develop an evaluation instrument that the users of intelligence could fill in that could be used to assess both the impact and value of the intelligence they received. starting with an evaluation instrument based on lists of benefits identified in the competitive intelligence literature, measures of these benefits and client satisfaction/service quality metrics, the study researchers interviewed clients of one large government competitive technical intelligence organization asking them to articulate the benefits they obtained from the intelligence they received and methods for evaluating these benefits. all users of intelligence identified benefits they had received from the intelligence received. additional benefits beyond those that are in the current literature were identified by those interviewed. in terms of measurement of these benefits, intelligence users (the clients) understood why hard financial type measures for example roi or dollar impact on performance was important (especially in their organization) they felt that assessing these for the intelligence they received would be difficult but that softer, more subjective measurement such as extent to which the user agrees that the intelligence provided the intended benefit could be used. additional perceptual based indicators of service quality and customer satisfaction measures were also suggested by intelligence clients. based on available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 2 (2014) 79-90 mailto:calof@telfer.uottawa.ca https://ojs.hh.se/ opinion section 80 the results of the literature review and interviews, an intelligence evaluation instrument was developed that asks the clients to assess the extent to which they have realized one or more of 27 impacts identified in this study as well as assessing 10 elements of service quality. keywords: evaluating intelligence, intelligence impact, cti, technical intelligence, cti impact, case study 1.0 introduction the need to understand the impact of intelligence evaluating the impact and value of competitive intelligence has been identified as an important intelligence research issue for many years (blenkhorn and fleisher 2007; global intelligence alliance 2004; herring, 2007; davison, 2001; kilmetz and bridge 1999; lonnqvist and pirttimaki 2006; viva business intelligence 2000). fehringer et al. (1996) wrote that “the ability to measure and demonstrate the value of ci has consistently been among the top items on many practitioners wish lists and previous surveys have reflected their desire to be able to demonstrate ci’s contribution to their organization” (fehringer et al. 1996, 99). kahaner (1997) warned ci professionals on “the need of showing the added-value of their services to ensure the commitment of top management to support” and almost 20 years later it still remains an important issue as highlighted by global intelligence alliance“ mi professionals have been struggling to answer questions related to the expected value and impact of the mi investment for just about as long as the profession has existed “ (gia 2014, 4). given this stream of literature and the weaknesses identified, the objective of the study and the article is to develop an instrument that can be used to measure the impact and value of intelligence for its users. 2.0 measuring and proving the impact of intelligence – literature review given the importance of showing the impact of intelligence, it is not surprising that many ci practitioners and researchers have proposed (but not tested) frameworks and approaches for doing so. herring (1996) was among the first authors who tried to identify relevant criteria for ci measurement. he proposed four types of metrics: revenue increase, cost avoidance, and cost and time savings. the concept behind this approach was that the best way to evaluate impact was to identify what impacts intelligence were supposed to bring to those that tasked the intelligence function (the end users/clients) and then find out if these impacts arose. the key contribution of the herring paper was the identification of the core benefits that intelligence could bring to its users – increase in the company’s revenues, avoiding costly mistakes, saving time and identifying cost savings. for the development of the instrument for this study, therefore, the literature review and instrument must identify the specific benefits that are supposed to arise from the intelligence produced and develop a way of measuring it. ten years later, fehringer et al. (2006) expanded this list of impacts and identified 7 values or impacts of ci financial goals met, new products or services developed, new or increased revenue, cost savings or avoidance, time savings, profit increases, and actions taken. similar to the herring approach this related to the direct impact that the intelligence was to lead to, the reason it had been requested. fehringer et al. (2006) also defined another measurement category they called assessing ci effectiveness which had six factors (return on investment, competitive intelligence productivity or output, customer satisfaction, decisions made or supported, new products or services, strategies enhanced). this latter category contained both direct impacts (decisions made or supported, new products or services, strategies enhanced) which in a sense results in 10 direct impacts and an indirect measurement of the benefit of the intelligence – customer satisfaction. this measure has its roots in the service marketing literature which posits that a subjective measure (customer satisfaction) is a good proxy for the quality of the service provided. if the customer was not satisfied with the service received (in this case the intelligence) then it would not have much impact (anderson et al., 2008; patterson et al. 1996; wirtz and lee 2003). finally, the study also provided direct hard measures in terms of roi and productivity. opinion section 81 the fehringer et al. study (2006) made three very important contributions to the development of the intelligence impact instrument. 1. it added additional direct impact factors which intelligence products were designed to create. 2. it added a measurement concept of implying benefit based on satisfaction with the service/product itself, a soft measure. 3. it suggested a direct impact measure such as roi and productivity. hard and quantifiable numbers. this concept of using a mix of hard (quantifiable) measures and soft (subjective) measures is not unusual in the ci evaluation literature. for example, in 1998 simon proposed an evaluation framework that included 21 hard measures and 29 soft measures. these are provided in table 1. a similar approach was taken by mcgonagle and vella (2002 – see table 2). as the impact literature developed, additional direct impact factors and measurements were proposed. for example in 2014, global intelligence alliance, in writing about evaluating intelligence listed 3 broad indicators with several factors that could be measured underlying each. decision making related indicators: decision-makers’ perception of the availability of information when it’s needed; mi’s involvement and contribution to different types of business decisions in the company; financial indicators : calculated financial worth of caseor project-specific mi efforts; cost savings through coordinated purchases of information and the elimination of redundancies; demonstrated time savings through systematically organized market monitoring ; and, indicators of a qualitative nature : the status of the company’s mi program as measured against the gia world class mi roadmap; the number of active users of the company’s mi software tool and/or participants in internal events that mi organizes; the size of the internal network of people that are involved in mi activities on a regular basis; the number of requests to the mi team; the number of deliverables (regular and ad hoc) that the mi team produces; the development of the internal nps score of the mi program; number of new business ideas generated as a result of mi efforts). there have been many other studies that have looked at evaluating intelligence impact that provided valuable input for the development of a research instrument. davidson (2001) proposed a formula to calculate the return on ci investment (rocii) for individual projects. he proposed that ci outputs (or the effects of ci plus decision maker satisfaction) less the monetary value of ci inputs (or costs associated with) are divided by ci inputs to derive the rocii. this measure of impact combined both hard numbers (the monetary impact of ci) with subjective or soft measures (decision maker satisfaction. pirttimäki et al. (2006) conducted a case study of a finnish company they examined how intelligence activities were measured. they identified four categories of measurement: financial (e.g. inputs and outputs ratios), process (e.g. inputs and outputs), learning and growth (e.g. organizational learning, decision making) and customer (e.g. usage of intelligence, satisfaction, resources/time). in all, they identified five objects of measurement and specific indicators for each: intelligence output (number of fulfilled assignments), intelligence input (working hours, total costs of information sources, total costs of using services), satisfaction of information users (surveys, feedback), intelligence usage (intelligence portal usage, number of intelligence requests) and intelligence costs (billing, and reports). table 1. hard and soft measures of ci success (simon, 1998) hard measures soft measures costs – ci contribution to the bottom line (input) 1. cost of doing the research 2. cost benefit of ci research 3. financial gain from ideas quantitative measures (output) customer usability 1. work habits 2. user friendly reports 3. participation on teams 4. contributions to teams 5. communication skills 6. contact follow-ups opinion section 82 1. clients serviced 2. projects completed 3. suggestions submitted 4. suggestions implemented 5. projects assisted 6. number of bi/ci staff 7. staff productivity 8. participants in the ci process (direct and indirect) quality measures 1. intelligence product measures 2. accuracy of information (validity and reliability) 3. immediate usability of results (no rework) time measures 1. ability to produce timely info. 2. efficiency 3. time saved by ci 4. on-time delivery ci practitioner performance measures 1. effective use of resources (resourceful and creative) 2. knowledge of ci methods 3. resourcefulness 7. customer satisfaction ratings 8. understanding acceptance and alliance measures 1. work climate 2. number of requests for service 3. number of repeated requests for service 4. requests for participation in team meetings 5. referrals from customers 6. further integration of ci projects unit and personnel effectiveness measures 1. feeling/attitude 2. solicitation for services 3. attitude changes – clients taking you in to confidence or consulting with you 4. customer loyalty rating 5. perception of ci contributions 6. relationship building (sharing of personal information) 7. problem solver perception personnel development/advancement rewards 1. job effectiveness 2. attendance at ci orientation and training programs (participant or teaching) 3. promotion 4. pay increases 5. work accomplishment acknowledgments ci practitioner performance measures initiative 1. implementation of new ideas 2. degree of supervision required 3. ability to set goals and objectives total: 21 criteria total: 29 criteria table 2. ci measurement according to mcgonagle and vella (2002) assignments and projects 1. meeting objectives 2. number completed 3. number completed on time 4. number requested 5. number requested—increase by end users 6. number of follow-up assignments 7. number of projects assisted 8. number of suggestions submitted budget 1. comparative cost savings—compared with cost of outsider 2. comparative cost savings—compared with cost of untrained 3. meeting project and function budget constraints efficiency 1. accuracy of analysis 2. data quality opinion section 83 3. first time results (no reworking) 4. meeting project time line 5. time for research versus time for response end users 1. creating compelling reasons to use ci 2. effectiveness of implementation of findings 3. meeting needs 4. number of referrals 5. number served feedback 1. [feedback]—written 2. [feedback]—oral financial 1. cost avoidance 2. cost savings 3. [financial] goals met 4. linking ci to specific investments 5. linking ci to investments enhancement 6. linking ci to specific savings from unneeded investments 7. revenue enhancement 8. value creation internal relationships 1. building strong with end-users 2. formulating relevant strategy and tactics 3. quality of relationship with end-users 4. quality of participation on cross-functional teams new products and services 1. number developed due to use of ci 2. cost savings/avoidance in development from use of ci performance 1. growth profitable for the unit or firm 2. impact on strategic direction of unit or firm 3. market share gains for unit or firm report and presentations 1. number 2. number of follow-ups 3. production of actionable ci sales effectiveness customer satisfaction 1. linking to specific customer wins 2. number of customers retained 3. number of leads generated 4. repeat business 5. improvement in win-loss ratio surveys 1. [surveys]—written 2. [surveys]—oral time 1. gained by ci input 2. projects delivered on time 3. saved by input to summarize, in examining the literature around evaluating intelligence impacts four concepts are identified that impacted this studies evaluation instrument: opinion section 84 the concept of an intelligence having a direct impact on an action or decision: the literature has identified many of these direct impacts starting with herrings (led to revenue increase, led to cost avoidance, led to cost and time savings). in measuring the impact and value of intelligence any instrument designed would need to recognize the actual objective of the intelligence provided. the concept of measurement of impact and value using hard indicators: most studies reviewed for this paper proposed or identified efficiency and effectiveness measures such as return on investment in the specific project (or unit), amount of revenue arising from the intelligence report and so forth. the concept of measurement of impact and value using soft or perceptual based measure: decision makers perception of availability of information when it was needed, extent to which they agree that a value was received were found in many studies as well as other soft and perceptual measures. the concept of implied impact based on client satisfaction with the service: questions such as to what extent where you satisfied with the service?, would you recommend it to someone else? despite all these concepts and several papers that propose evaluation frameworks and measures, few have tested these measures within an organization. it is this gap as well as the weaknesses identified in the 2014 in the global intelligence paper and other articles reviewed that this study sought to address. 3.0 methodology 3.1 case study design given the areas of importance and weakness in the ci performance evaluation literature described in 2.0, the objective of the study was to develop an instrument that could be used to measure the benefit’s clients received from the intelligence they received and the value of these benefits. in developing the study methodology access was needed to an organization that had conducted a significant number of intelligence studies and had a broad client base. the higher the number of intelligence products (unit of analysis) the larger the base to draw upon to get client feedback on how the intelligence benefited them and how this benefit could be measured. the author was given access to the competitive intelligence unit of the national research council (canadian government organization), to their intelligence personnel, past intelligence products and clients. the organization refers to the unit as competitive technical intelligence unit as the unit is producing intelligence within a technical environment. note that performance being an issue of importance has also been extensively written about in the competitive technical intelligence (cti) literature as well (rosenkrans, 1998; norling et al. 2000; dollatabady et al. 2011). however, the training the staff received and the projects themselves cover far more than just technical intelligence techniques. in reviewing the intelligence products produced by the unit, the researchers noted that the nrc’s cti unit produced a broad range of intelligence assessments and products. studies took anywhere from a day to produce (simple patent scans, market analysis or literature reviews) to multiple months in the case of scenarios and expert panels used for policy development. clients for the cti were very broad including canadian companies, departmental technical officers making investment recommendations (whether the government should provide funding to the venture), research recommendations for government scientists, policy advice and so forth. the following approach was used to develop the instrument for measuring the benefits of intelligence to the end user (client) and their satisfaction with the intelligence. a document was developed (which would be shown to intelligence clients) that identified the benefits of intelligence found in the literature review. the document then had suggestions from the literature regarding how to measure these benefits, providing the participant with both soft and hard measures and finally the document contained a listing of the quality of service/customer satisfaction measures seen in the intelligence literature. a sample of the organizations cti clients was drawn (sampling methodology is mentioned in the next section), who would be interviewed for their opinions on benefits they received from intelligence and how these benefits could be measured. the research team did not want to be seen as biasing the study towards a priori benefits identified in the literature review but wanted to ensure that as comprehensive a list of benefits and measures from the perspective of the user could be developed. as such, rather than present opinion section 85 the document with all the benefits identified in the intelligence literature and measures all of those interviewed were asked to list the benefits that they could recall from the cti project they had commissioned/received. after describing all benefits, the clients were then shown the intelligence reports that they had received from the nrc’s cti unit and asked if they could recollect any other benefits. after the respondents had exhausted their recollection of benefits, the researchers then showed the respondent the intelligence benefits portion of the document (appended with any new impacts that the respondent had stated in the interview) and asked again to look at the list and to also indicate the extent to which any of the benefits had been received. the interview would then end with a discussion on how each of the benefits on the list could be accurately measured and the quality of service/customer satisfaction measures. after each interview, the study document was modified with the addition of benefits previously not included in the document and the addition of other measures based on interview results. any additions to the document were based on two researchers independent review of interview notes. in other words, additions arose only if both researchers reached the same conclusions based on the interview notes. to develop the final survey instrument, those benefits receiving at least one mention in the interviews would be included in the final evaluation instrument and those items which respondents did not list as benefits was removed. in some cases some of the items removed not only did not get a single “vote” but were frequently mentioned as benefits which those interviewed did not feel were an appropriately important benefits of intelligence. while the intelligence literature has identified many direct and indirect benefits of intelligence, in assessing impact and value from the user (clients) perspective, the researchers felt that it was important that the benefits measured be those of importance to the clients themselves. 3.2 sample frame in all, clients representing over 50% of the organizations intelligence projects were interviewed for this research. to identify who to interview a two-step process was followed. in the first step which offices to focus on was identified and in the second step selection of clients to interview. the organization has intelligence offices across canada. some of these are small offices (one or two intelligence staff) and some are large offices. five offices were chosen for the study. the offices chosen represented those that produced the highest volume of cti reports and had been involved in producing cti the longest. given that the intent of this study was to develop a comprehensive instrument for measurement of benefits it was felt that offices with higher experience levels and greater number of projects would be appropriate. second, within each office, the researchers sought to identify the clients that they wanted to interview for the study. similar to the office selection, experience was used as a basis for the selection of the clients selected for interviews. clients were chosen based on two factors: volume of cti products requested: how many products were requested? who were the most frequent users of cti? scope of cti products requested: the organization has three levels of cti products, information reports, cti brief/insight and cti assessment. the intent was to interview clients who had requested most if not all of these products. as an example of this selection methodology, one of the offices (call it office 1) was selected as it was one of the oldest offices as of the time of the interviews with one of the largest number of cti projects completed. the office had 21 clients (people that had requested intelligence reports). in reviewing the type and number of projects ordered by these 21 clients, it was noted that five clients accounted for over half the projects in general and almost all the analysis reports. accordingly, interviews were scheduled with all 5 clients who collectively represented 60% of all projects done in this office. sampling in this manner resulted in similar project coverage rates. for office #2, 71% of their projects were covered in the interviews, 77% in office #3 and 100% in office 4. 4.0 results and discussion based on the methodology described in section 3, 27 decision impact items and 10 service items were included in the final evaluation questionnaire (appendix a). based on interviews with the clients, only perceptual measures were used in the final evaluation questionnaire and in particular, a likert evaluation scale of perceptual impact was found to be the best method for measuring impact. opinion section 86 impact factors: support for many of the impact factors cited in literature reviews arose in the interviews and in fact, all clients interviewed articulated that they had received significant benefits from the cti products and process. saving time, saving money, making better recommendations, quicker recommendations, etc., all respondents were easily ably to identify benefits from the intelligence they had received. |additional impacts were cited that the researchers did not note in the current literature. service quality/client satisfaction: in all interviews, respondents talked about service quality elements when they talked about the benefits. while the initial study design was to have this brought up by the researcher in the interview when discussing measurement, in all cases the interviewees themselves (the clients) talked about their experience with the intelligence staff before being asked about it . service quality and satisfaction were evident in statements such as professionalism of the cti officer, how pleasant they were to deal with, their (the clients) desire to use the service again and how they were recommending cti services to others. these are all measures that have been examined in the management consulting literature as ways to evaluate the professionalism and effectiveness of consultants and consulting units (see the earlier literature review). these statements provided confirmation on the earlier framework that recommended evaluating the intelligence impacts using service quality and client satisfaction metrics. measurements, soft versus hard. clients interviewed stated that use of hard measures such as return on investment, impact on decision, etc. would be difficult, if not impossible to do. the participants felt that the only measures that should be used would be a perceptual measure (subjective questions) about whether they felt they had received the benefit. although all interview participants told stories about the benefits they received and were insistent that these benefits had been received, when asked if they could quantify the benefit the answer was consistently no. respondents were aware that harder measures such as return on investment, cost/benefits were critical for their organization but cautioned against it for competitive intelligence. however while they could not quantify the benefit they could provide an indication as to the extent to which they had received the benefit using a likert scale of 1 (strongly disagree) to 5 (strongly agree). when asked why harder measures could not be used, respondents answers fell into five broad categories: complexity of the clients decisions making process. while the cti report was clearly used to help make the decision/policy, their decision making was more complex than reading the cti report and implementing the report recommendations. no respondent was prepared to say how much of the decision was influenced by the report, only that it was an important element in making decisions and developing policies. here is one example of this difficulty. in one of the intelligence projects, the client stated that the cti they received was used to provide an investment recommendation (whether the government should provide funding to the canadian company that had requested technology funding assistance). the client of the intelligence product (the government officer making the recommendation) talked about how their final decision was based on many factors including the cti report which provided the market assessment, a technical report provided by technical advisor which assessed the underlying technology, and a business analyst report discussing the strength of the organization that would receive the investment. the cti report contributed but so did the other reports as well as the officers own experience. additional value added by the clients to the intelligence: this is a slight extension of the complexity of decision making process. several respondents stated very strongly that in the end they made the decisions/recommendations based on discussing it with others, doing additional research, etc. call this client value added activities with the intelligence. complexity of factors beside the intelligence responsible for success and impact: this was mentioned more when the type of intelligence received was designed to help develop new products/services, reduce costs, make sales, almost dealing with growth. in implementing the intelligence recommendations for example designing policy, strategy, r&d programs there are a lot of other factors that need to line up for success to occur. thus, directly linking the cti report in a quantifiable way to the success of the technology investment would not be possible. further, in trying to quantify costs saved, opinion section 87 program benefits arising from the decision itself, or policy benefits (when the cti report clearly impacted the decision), participants pointed out that policy impacts were too complex to be assessed in this way. in one case program impacts were mediated by government elections wherein the recommended policy was scrapped by a subsequent government. in this case the intelligence had no impact due to change of organization. in another case, the intelligence was not fully implemented – the client decided to adopt some of the intelligence reports recommendations but not all. temporal orientation of the intelligence: while some intelligence was designed to impact decisions that would get results in a short time frame (under a year) other intelligence projects had a longer time frame. one for example was an intelligence report done for seed research for which whether the benefit is received (market share and sales) will not be known for 40 years. therefore to link the intelligence with the subsequent research success or commercial success in this case would require waiting 40 years. organizational politics: many respondents indicated that politically in their organization it would be unwise to credit too much of a decisions success to anything besides their own skills/expertise. talk of complexity in measurement of benefits was evident in most interviews with those interviewed providing specific examples to the researchers and challenging them to develop a method that would involve hard measures on direct benefits. for example, one of the clients provided a cti example and challenged the researcher on how it would be evaluated from a financial/roi perspective. the cti developed was a market study which told the officer that a government investment in a technology was sound but that the company was focusing on the wrong market. the report identified other markets. the client then discussed this cti report with the intended recipient of the government technology investment funds. the investment was approved as the cti report proved that the technology was sound and the technology was built as per the objectives of the cti. however, the cti provided to the company caused them to change their marketing approach. the client challenged the research to identify how the roi of the cti would be calculated. was it the value to me (the client) of a good decision or was it the value to the company that was provided with the money? is the roi on this one the money saved by not going to the wrong market? money gained by going into the correct one? value of not investing in the wrong company? another client challenged the researcher on what could be best termed an indirect cti report benefit. the client had commissioned a cti report to assist with policy development. while the cti did land up being used as the basis for policy development (verbatim elements of the cti report were included in the policy), the government client stated that elements of the cti report were integrated in a speech the officer made to an industry association and an interview conducted with a national news network. the information was then used by many companies in the industry. again, the client was clear on the benefits he received from the cti report but stated that there were additional benefits beyond that intended by the report. in a corporate environment this would be similar to intelligence reports being shared by different divisions or people within the same division and impacting their decisions – whose roi would you measure? clients were indicating that the value of cti was greater than just impact on the policy or decision and while they could subjectively state that they got high value from the intelligence product, they could not quantify it. to conclude this section, based on an extensive literature review and a multi-step methodology that involved extensive interviews with cti users, a cti impact evaluation instrument was developed. this instrument identified specific benefits of intelligences and then measures the extent of the benefit were received by asking the client to assess the extent to which the benefit was realized using a five point likert scale. as well, consistent with the consulting and management services literature client satisfaction and other service quality measures were put into the evaluation instrument which was also measured based on client perceptions. this instrument can be used after the cti project has been done to assess the benefits to the client of the intelligence received. 5.0 conclusions the intelligence literature notes the importance of proving value and impact of intelligence on the intended user of the intelligence. this study opinion section 88 sought to develop an instrument that could be used to measure this impact. consistent with consulting and intelligence literature, it was found that client perceptions of benefit needs to be used as a primary method of evaluation. client’s themselves indicated that it would be difficult to use non perception based methods of evaluation. 5.1 study limitations and areas for future research the results of this study are based on intelligence as conducted in one organization and may not be generalizable to other organizations. in fact, as the unit is a technical intelligence unit, it is uncertain whether the evaluation instrument developed out of the study could be used in a non-technical intelligence organization. generalizability is further restricted as the list of benefits were driven by the users of intelligence in this organization and perhaps other intelligence organizations have a different focus. while most of the benefits identified in this study are consistent with past research, nevertheless there appears to be organizational nuances to intelligence benefits that may need to be looked at in future studies. further, even though the literature used in the development of the initial evaluation instrument was global, the evaluation instrument may not be generalizable outside of canada or even outside this one organization. accordingly, future studies should attempt to test the instrument developed here. another area for future study is instrument reliability and validity testing. the instrument should be tested on a broader group with appropriate statistical tests of reliability and validity. without factor analysis and cronbach’s alpha it is not possible to state definitively that the instrument is both reliable and valid. while face validity has been established by use of client testing and fit with the existing literature, nevertheless statistical testing is required before the evaluation instrument should be considered acceptable for use. 5.2 implications for cti practitioners, policy and other stakeholders notwithstanding the limitation noted above, the results of this study have significant implications for cti practitioners as well as policy and other stakeholders. cti can be assessed without having to wait for the final impacts of the cti recommendations to arise. for all involved in cti, it is clear from the results of this study that user perceptual measures should be used. asking clients to assess on a likert scale for example the extent to which the cti provided saved them time in making the decision or helped them gain funds (research funds) is a good way to evaluate cti impact. not only is this consistent with the literature but based on the client interviews may be the only method they are prepared to accept. it is undeniable that the evaluation of cti is a complex task owing to the complexity of both the cti process and the ensuing client decision making/policy development process. nevertheless, this study has demonstrated that evaluation can be done, albeit using perceptual measures. 6.0 acknowledgements funding for this research was provided by the national research council of canada. the author acknowledges the research support provided by france bouthillier, mcgill university on this research project. her research skills and insight helped in the development of the study and associated instruments. the author further thanks the reviewers for this paper. the comments provided served to improve and focus the paper. 7.0 references anderson, shannon, lisa klein pearo, and sally k widener. 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(2003). an examination of the quality and contextspecific applicability of commonly used customer satisfaction measures. journal of service research 5, 4,345-355. opinion section 90 appendix a final cti questionnaire please note the extent of the benefit using the following scale: 1 2 3 4 5 strongly disagree strongly agree item: benefit to you benefits impact on savings 1. it helped to save time 2. it helped to save money 3. it helped to save resources impact on gains 4. it helped me to gain more money 5. it helped me to gain more staff impact on decision making/recommendation 6. i made my recommendation more rapidly (timeliness) 7. i made a better recommendation (appropriateness) 8. my recommendation was validated (reassurance) 9. it helped to reduce bias(es) in decision making/recommendation 10. it helped to reduce the possibility of errors in my recommendation 11. it helped to pursue opportunities 12. it helped to develop partnerships/collaboration 13. it helped to develop better strategies impact on knowledge (cognitive dimension) 14. i became aware of important issues that i was not aware of before 15. i could go further in my thinking 16. it gave me information that i was able to use in future projects 17. it broadened my knowledge 18. it had given me the information required to improve my proposal/project 19. it had given me the information i needed to provide my client with good advice 20. it helped me to identify new markets 21. it helped me to identify new ideas impact on perception (affective dimension) 22. it made me more confident on my recommendation 23. it helped to reduce perceived uncertainty 24. it has enabled me to do my job better 25. it helped to reduce risk 26. i could act differently impact on service towards clients 27. it has helped improve service to my clients appreciation of service quality 1. the reports were easy to read/ consult 2. staff showed good knowledge of my area/industry 3. staff understood my problem/issue 4. staff was flexible in adapting themselves to my requests 5. staff paid attention to my needs 6. cti reports were reliable 7. cti reports were accurate 8. i felt that my needs were dealt with in a timely manner 9. i will recommend the unit to others 42 strategic foresight: determining patent trends in additive manufacturing marisela rodríguez salvador *, paola cruz zamudio * , andrés santiago avila carrasco*, elías olivares benítez ** , beatriz arellano bautista ** * tecnológico de monterrey, campus monterrey, méxico marisrod@itesm.mx, paopcz4@gmail.com, andresavilca@hotmail.com ** universidad popular autónoma del estado de puebla, méxico elias.olivares@upaep.mx, beatriz.arellano@upaep.edu.mx in memory of jonas rundquist, halmstad university received november 5, accepted december 26 2014 abstract: additive manufacturing is an emerging technology that brings several opportunities to the manufacturing industry. therefore, research in this arena on current and future developments is required to make strategic decisions. under this context, the goal of this research is to develop a patent analysis on additive manufacturing. keyword-patent analysis is performed to identify the most important organizations, countries, inventors, and technology areas through international patent classifications (ipcs) of the additive manufacturing industry. results show that there is an increase on additive manufacturing research, particularly in 2013 and 2014. the main areas of research are focused on shaping of plastics and after-treatment of shaped products and working metallic powder and manufacture articles from this material. moreover, the analysis indicates that leading countries on additive manufacturing research are united states, great britain and available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 3 (2014) 42-62 mailto:elias.olivares@upaep.mx mailto:beatriz.arellano@upaep.edu.mx https://ojs.hh.se/ 43 switzerland. additionally, top three companies on this area are: stratasys inc. (usa), united technologies corp. (usa) and alstom technology ltd (switzerland). its recent research inventions were identified in this study. the main contribution of this research is to offer a template for analysis in other industries, but it also brings valuable insights to decision makers interested in recent patent efforts developed for the advancement of additive manufacturing. keywords: strategic foresight, foresight, patent analysis, additive manufacturing 1.0 introduction manufacturing is an important sector for the worldwide economy. in 2009, this sector employed 31 million persons in the european union, generated eur 5,812 billion of turnover and eur 1,400 billion of value added (european factories of the future research association, 2013). with such economic impact, it is mandatory that entities involved in this sector keep abreast of the competitive environment including technological advances to support strategic decisions on research & development + innovation (r&d+i). due to current movements in market forces it is expected that not far away from 2020 manufacturers will be confronted by strong challenges for developing more customized products with better performance and less cost. to accomplish this, organizations involved should be more innovative and creative. a proper identification and use of relevant knowledge in decision making acquires a key role to gain new competitive advantages (youtie et al., 2007). a promising technology that has emerged recently is additive manufacturing (am). am produces products layer by layer, contrary to the traditional way of subtracting material from larger pieces. with am, assembly lines and supply chains may be decreased or removed for many products. products can be printed on demand and thus, inventories may be reduced. furthermore, carbon emissions to the environment may be decreased. finally, more customized products can be developed as production is brought closer to the consumer (campbell et al., 2011). am is a new technology that brings several opportunities to the manufacturing industry so research to identify technical advances, and key players is required. as literature has showed since many years ago patent analysis represents a key tool to determine and analyze industry trends. it provides a way to envisage technology trajectories and to identify on-going developments of organizations (companies, government agencies, centers, universities, etc.) so it is an important tool to support strategic planning in terms of r&d as well as innovation (hsieh, 2013). in this research, a patent analysis is developed to determine trends in am. main countries, organizations, inventors and technology areas through international patent classifications (ipcs) were identified as well as the last inventions of top players. the purpose of this study is to offer valuable knowledge to decision makers interested in knowing patent activity including technological advances and key players of am. more important, the results of the procedures can be incorporated for a broader strategic foresight analysis. strategic foresight comprises the activities and processes that assist decision makers in the task of defining the company's future course of action (vecchiato, 2012). strategic foresight provides business executives and government policy makers with interesting methods to envision the future. it also helps them to understand the implications of alternative technological or societal paths (rohrbeck and schwarz, 2013). the paper is organized as follows. sections 2, 3 and 4 provide a literature review of foresight, am technology and patent analysis 44 respectively. a description of the methodology followed is detailed in section 5. section 6 presents the main findings of the research and section 7 presents conclusions. 2.0 foresight in organizations foresight is a set of systematic attempts to look at the long-term future of science, technology, economy and society, in order to identify emerging issues that are likely to generate the higher social and economic benefit (balbi, 2001). moreover, popper (2008a) defines foresight as a process which involves intense iterative periods of open reflection, networking, consultation and discussion, leading to a joint refining of future visions and a common ownership of strategies. the first multinational company that formally employed a foresight tool may have been royal shell. this oil organization was able to identify and anticipate the scene of the oil crisis that took place in 1973 (ortega, 2004). since the 80’s the studies related to foresight have been strongly increased (da costa et al., 2003). roadmapping is one of the most common techniques of foresight (ortega, 2004). this tool is applied to predict a possible future and results obtained allow delineating or changing strategies (da costa et al., 2003). since long time ago there is a growing interest in developing roadmap analysis particularly in the departments of r&d of hightech companies (willyard and mcclee, 1987). due to a growing intensive competition, organizations have the challenge of adapting them to a fast and changing environment based on a new era of knowledge (marsh, mcallum and dominique, 2002). the authors argue that organizations need to change their traditional planning methods and be able to anticipate competitive environment movements. nowadays, companies should not plan under a unique vision centered on the present. they should conceive strategies and contingency plans based on possible future scenarios (ortega, 2004). under this perspective, foresight emerges as an important methodology. according to popper (2008 a,b) foresight analysis typically includes five steps: 1) pre-foresight, 2) recruitment, 3) generation, 4) action, and 5) renewal. during the pre-foresight step, the goal and activities of the foresight analysis are established. a literature review, scanning, bibliometric or patent analysis from academics or research institutes should be performed to identify the project goals. the recruitment step consists on organizing key actors and resources. in the generation step knowledge is obtained through exploration, analysis and anticipation of possible future scenarios and new policies and decisions are produced. action stage comprises the implementation of results previously determined. finally, renewal phase includes evaluation and changes. popper (2008 b) classifies foresight methods as qualitative (e.g. brainstorming, environmental scanning, expert panels and swot analysis), quantitative (e.g. bibliometrics, modeling/simulation, trend exploration/megatrends), semi-quantitative (e.g. cross-impact/structural analysis, delphi, stakeholder mapping and technology roadmapping) and other methods (e.g. benchmarking and patent analysis). during this research a patent analysis is developed. the aim is to obtain valuable knowledge that could support organizations' decisions in terms of their r&d+i activities. lin et al. (2013), consider that foresight has evolved from being an explorative and tactical tool to become a strategic planning tool. this is not an instrument used to forecast or predict, instead, it is used to define alternative futures and create paths for potential developments. there is a difference between foresight and strategic foresight concepts. while the first one has been used to describe an inherent human activity, i.e. the act of looking forward daily by individuals throughout society; the second one determines future research activities of organizations (rohrbeck and schwarz, 2013). in this paper, the term strategic foresight is applied considering that this research aims to support 45 organizations that are interested on planning for the future. strategic foresight analysis provides decision makers new ways to delineate future that could affect competitive position of the organization. 2.1 strategic foresight and competitive intelligence foresight and competitive intelligence (ci) disciplines have similar goals. both practices systematically monitor the organization environment to provide valuable insights about possible future events (lin et al., 2013). as sarpong et al. (2013) establish that ci is one of the practices that organizations have to define the future; other techniques are: scenario planning, counterfactual analysis, peripheral visioning and scenario thinking. calof and smith (2010) deepen this relation. they consider that competitive technical intelligence (cti) and strategic technological foresight (stf) are fields with similar objectives and techniques. while the authors define cti as a practice that provides business sensitive information on external scientific or technological treats, opportunities or developments that have the potential to affect a company’s competitive position. stf according to them is a collaborative tool that draws upon the talents of many individuals (not only from the technology domain) and is an important source for technical and business intelligence. cti and stf have strong similarities and complementarities. both practices guide r&d+i process, use similar techniques for examining and understanding the environment and both are designed to support key decisions. 3.0 additive manufacturing (am) the origins of additive manufacturing (am) can be traced back to the end of the 80’s. in 1987 the first commercialization of a stereolithography (3d printing machine) was performed. since then, the industry has grown in an accelerated pace and as a consequence the number of patents has strongly increased. this industry has a strong interest on developing new technologies (beer, 2013) to compete more efficiently. additive manufacturing comprises a group of emerging technologies that produce objects through the addition of materials layer by layer (campbell et al., 2011). these technologies are: binder jetting, directed energy deposition, material extrusion, material jetting, powder bed fusion, sheet lamination and vat photopolymerization (basiliere and shandler, 2014). 3d printing is a concept commonly used in the industry when referring to am (beer, 2013). three main advantages arise when using am in manufacturing processes. first, the possibility of building complex objects. a diversity of industries are benefited (manufacturing, health, education, etc.). second, am does not require assemblage of parts. both production time and costs decrease. finally, am reduces waste and offer the opportunity to use recycled materials (campbell et al., 2011). the general process of am starts with the creation of a 3d model. for this task computer-aided design (cad) tool or the scan of an existing object is applied, information generated is sent to a specialized equipment that produces the 3d object through the addition layer by layer of material (campbell et al., 2011). nowadays, am is used to produce a variety of products from automobile and aircraft components, custom orthodontics and hearing aids (campbell et al., 2011), surgical or medical models, to architectural models and teaching aids (beer, 2013). particularly use of am has a strong interest from the manufacturing industry. this technique could be used to produce a final or intermediate product. additionally, it could be used to print tools, dies and molds needed for production. adoption of this technology accelerate commercialization of products, push production to the customer and give other advantages to compete in a more innovative way (basiliere and shandler, 2014). for this reason, manufacturers of several 46 industrialized economies are increasingly using am technologies. a recent study was developed to reveal how 504 us manufacturers from the georgia state (usa) with 10 or more employees, deploy information, execute quality management and perform production technologies (youtie et al., 2014). the results showed that 70% of respondents use at least one advanced technology like additive manufacturing. 3.1 the future of additive manufacturing the future of am is promising. during the next decade, it is expected that this technology will have a predominant role in different industries. in particular, two applications are gaining interest among the current and potential users of am (campbell et al., 2011). the first one is centered on metal components. through am engineers are now able to develop components using titanium and steel alloys. the second one is the desktopscale 3d printers. the cost of these products is decreasing. in the future, more persons will be able to adopt this technology. furthermore, advances in metals, development of new design tools, expiration of related patents and other related changes are expected to come, as consequence new business will emerge (beer, 2013). basiliere and shandler (2014) consider that, within two to five years, it is expected a higher adoption of 3d printing technologies in organizations. the authors also estimate that 3d printing of medical devices such as prosthetics and implants will increase. basiliere (2014) estimates that from 2014 to 2018, the total number of 3d printer units shipped per year will grow to 2,319,494 worldwide. this represents a cagr (compound annual growth) rate of 106.6%. the author considers that by 2018 the sales of these technologies will exceed us$ 13.4 billion. such forecast is based on the fact that consumers and organizations will rapidly adopt 3d printers for home and corporative use. the european factories of the future research association (2013) reports that in 2030, factories will be green and sustainable. to achieve this goal, efforts should focus on reduce energy consumption, close loops for products or production and scarce resources; finally, sustainability in terms of materials and production processes will be required. all the above efforts can be achieved through the use of am technologies. 4.0 patent analysis patents are the most accessible and reliable sources of information for assess of a technology (hsieh, 2013). they are considered one of the most valuable output indicators of the technological innovation process (hidalgo et al. 2009), (rodríguez and tello, 2012). moreover, from all the available technological information, 90% can be found in patent publications (blackman, 1995). the strategic planning of an organization can be improved if technology is evaluated through patent analysis. there are several patent classification systems: the international patent classification (ipc), the united states patent classification system (uspcs) and the cooperative patent classification (cpc). this research focuses its analysis on the ipc. the world intellectual property organization (2015) defines ipc as a “hierarchical system of language independent symbols for the classification of patents and utility models according to the different areas of technology to which they pertain”. ipc divides patents into classes, sub-classes, groups and subgroups. 4.1 keyword-based analysis keyword-based patent analysis represents an important tool used to determine technology trends, discover technological opportunities and predict new technological advances. this tool is based on patent keyword frequencies and cooccurrences between them (choi et al. 2012). it provides decision makers with valuable 47 knowledge to compare the strategic positioning of an industry or organization in different countries. analysts can determine who the leaders are in different technological areas or which of these areas are emerging. similarly, researchers can analyze the profiles of inventors/organizations to identify density of technological domains through their corresponding classifications. besides, hidden relations between organizations can be determined (trappey et al. 2011). a patent map uses patent information to create specific graphs and charts that provide simple and intuitive ways to address complex technical information (zha and chen, 2010). for this purpose, patent information, such as assignees, inventors, countries and ipcs is considered. 5.0 methodology to develop this research, matheo patent software was utilized. this is a french software that collects, analyzes and deploys patent information. it offers solutions for decision making, analysis of strategic information and technology scanning. matheo patent retrieves information from uspto and espacenet databases. while in the first case it is possible to retrieve whether issued patents or applications; in espacenet there is not such distinction, analysis through the software comprises both types into the same research. its results provide with an accurate perception of the latest advances in any given research topic. this software allows searching patents through keywords contained on title, abstract, inventor, applicant, patent number and classification codes. (matheo patent, 2015). the results of this research were obtained in three steps. these are explained below. 5.1 planning during this phase, the goals and scope of the project were established. the goal of this research was to develop a patent analysis on am as a first step to conduct a further strategic foresight analysis. main countries, organizations, inventors and technology areas through international patent classifications (ipcs) were identified. this research is focused on am patents issued and submitted between 2011 and january 28th, 2015. matheo software, the tool applied on this research, extracts information from patent families; hence some results may have a period of years longer than the one previously defined. data was retrieved through espacenet database. its search engine offers free access to more than 90 million patent documents worldwide and contains information about inventions and technical developments from 1836 to present (espacenet, 2015). 5.2 selection and gathering of information a search was performed using the exact phrase "additive manufacturing" in “title and abstract”. when using the general terms additive manufacturing, relevance of the information gathered could be not adequate. in fact it was tested and more than one hundred thousand patents were obtained where a high rate of patents didn’t correspond to the field of the study. 48 figure 1. patents per year. data from espacenet using matheo patent. 5.3 data cleaning this task consisted on combining similar terms and removing repeated information from “applicants”, “inventors” and “country” fields on the patents obtained. 6.0 results and discussion 6.1 patent density a total of 735 patents, 336 family patents and 629 inventors were obtained on am between 2011 and january 28th, 2015. in figure 1, the number of patents per year is presented. as it can be seen, there is a significant increase in patent publications on am, particularly from 2013 (209 patents) to 2014 when they increased to almost the double (420 patents). regarding family patents, 129 families were detected in 2013 while in 2014 this amount raised to 247 family patents. figure 2 shows results according to family patents during the period defined of 2011jan 28 2015; it is important to notice that families can be repeated and a patent could have a family before this period, so as it can be seen in the next figure results of patent families comprises 2008 to 2015 counting 434 in total. 49 figure 2. family patents per year. data from espacenet using matheo patent. in the next section a patent density and main focus of research is presented. 6.2 patent activity and main trends 6.2.1 top ipc four digits code top 3 ipc four digit codes are shown in figure 3. it can be seen that am research efforts are focusing on ipcs: b29c, b22f, and b23k. according to wipo (2015) they corresponds to:  b29c: shaping or joining of plastics; shaping of substances in a plastic state, in general; after-treatment of the shaped products, e.g. repairing.  b22f: working metallic powder; manufacture of articles from metallic powder; making metallic powder.  b23k: soldering without fusion or unsoldering; soldering; coating or plated for soldering; cutting by localized heating, e.g. flame cutting, work by lasers. 6.2.2 top applicants and inventors countries from the applicant country point of view a strong patent activity was detected primarily from usa (360 patents), followed by great britain (137 patents) and switzerland (59 patents). these results are shown in figure 4. regarding inventor country, the highest patent activity was from usa (369 patents), followed by great britain (139 patents) and germany (51 patents). results are shown in figure 5. figure 3. top 3 ipc four digit codes. data from espacenet using matheo patent. 50 figure 4. patents per applicant country. data from espacenet using matheo patent. results show a similar trend for usa and great britain. however, the rest of the countries have a different behavior. figure 5. patent per inventor country. data from espacenet using matheo patent. 51 6.2.3 top organizations organizations with the highest number of patents (issued and submitted) were identified coming from: usa and switzerland as figure 6 shows. top 3 organizations in descending order are the followings: figure 6. top organizations. data from espacenet using matheo patent.  stratasys inc. (usa): 87 patents  united technologies corp. (usa): 41 patents  alstom technology ltd (switzerland): 29 patents organizations with the highest number of family patents were also identified. results are shown in figure 7. the top 3 organizations in descending order are the followings:  stratasys inc. (usa): 36 family patents.  united technologies corp. (usa): 29 family patents.  renishaw plc (great britain): 21 family patents. when both indicators: global patents (issued and submitted) and family patents are considered, there are similarities in only the first two positions. stratasys inc from usa leads the patent application activity with 87 patents and 36 family patents, followed by united technologies corp from usa with 41 patents and 29 family patents. but the third position is different, alstom technology from switzerland has the third position considering their 29 patents and renishaw from great britain has the third position taking into account their 21 family patents. in the following sections a more detailed analysis of the top companies will be developed considering number of patents issued and submitted. 52 figure 7. top organizations by family patents. data from espacenet using matheo patent 6.2.3.1 stratasys inc. (usa) considering that stratasys inc. from usa is the patent leader in am field, this research proceeds to know more about its patent activity during last years. based on the same period previously established, figure 8 shows their patent activity from 2011 to 2014 (they did not have results for 2015 when this study was concluded). it is important to remark the growing effort of this company on the advancement of this technology, particularly during 2014 when its patent efforts were of almost 50% more with respect to 2013. figure 8. stratasys inc. patents per year. data from espacenet using matheo patent 53 figure 9. stratasys inc. main ipcs four digit codes. data from espacenet using matheo patent top ipcs (four digits) from stratasys inc. were also identified. the main results are shown in figure 9. this company focuses its research on ipc code b29c. as mentioned before, this ipc comprises shaping or joining of plastics; shaping of substances in a plastic state and after-treatment of the shaped products. while the rest of the codes corresponds according to wipo (2015) to:  b65h: handling thin or filamentary material, e.g. sheets, webs, cables.  b05d: processes for applying liquids or other fluent materials to surfaces, in general  g03g: apparatus for electrographic processes using a charge pattern.  b32b: layered products, products builtup of strata of flat or non-flat, cellular or honeycomb. figure 10.united technologies corp. patents per year. data from espacenet using matheo patent. 6.2.3.2 united technologies corp. (usa) after stratasys inc., united technologies corp. is the organization with the highest number of 54 patents according to the figure 10. it is important to notice that, in 2014, the company increased its patent rate in an unexpected rate. top ipcs from united technologies corp were also identified. results are shown in figure 11. the company is focusing mainly in research related to ipc code b22f (working metallic powder, manufacture of articles from metallic powder and making metallic powder) followed by code f01d (non-positive displacement machines or engines, e.g. steam turbines). while the rest of the ipc are as follows:  f02c: gas-turbine plants; air intakes for jet-propulsion plants; controlling fuel supply in air-breathing jet-propulsion plants.  b23k: soldering or unsoldering; welding; cladding or plating by soldering or welding; cutting by applying heat locally, flame cutting; working by laser beam.  b29c: shaping or joining of plastics; shaping of substances in a plastic state, in general; after-treatment of the shaped products, e.g. repairing. figure 11. united technologies corp main ipcs four digits. data from espacenet using matheo patent. 55 figure 12. alstom technology ltd patents per year. data from espacenet using matheo patent. 6.2.3.3 alstom technology ltd (switzerland) alstom technology ltd is the third organization with the highest number of patents. as the previous cases, this company presents a big jump from 2013 to 2014 according to figure 12, in the rest of the years analyzed they do not have patents. top ipcs of this company were also identified. results are shown in figure 13. as can be seen, the focus of the company´s research is related to ipc code b22f, similarly to united technologies corp, this code is associated to working metallic powder, manufacture of articles from metallic powder and making metallic powder. figure 13. alstom technology ltd main ipcs four digits. data from espacenet using matheo patent 6.2.4. recent patents of top organizations in this section, top three companies and their most recent patents are presented. 56 6.2.4.1 stratasys inc. the three most recent patents of stratasys inc. are shown in table 1. patent number us2014358273a1 consists on a method for printing a three-dimensional part with an additive manufacturing system. it comprises the generation and printing a planarizing part having a substantially-planar top surface relative to a build plane, and a bottom surface that substantially mirrors a topography of a platen surface, and printing the three-dimensional part over the substantially-planar top surface of the printed planarizing part. patent number us2014265040a1 consist on an additive manufacturing system that retains a print head for printing a three-dimensional part in a layer-by-layer manner using an additive manufacturing technique, where the retained print head is configured to receive a consumable material, melt the consumable material, and extrude the molten material. the system also includes a velocimetry assembly configured to determine flow rates of the molten material, and a controller assembly configured to manage the extrusion of the molten material from the print head, and to receive signals from the velocimetry assembly relating to the determined flow rates. patent number us2014252684a1 consist on a method for printing a three-dimensional part with an additive manufacturing system, the method including printing layers of the three-dimensional part and of a support structure for the threedimensional part from multiple print heads or deposition lines, and switching the print heads or deposition line between stand-by modes and operating modes in-between the printing of the layers of the three-dimensional part and the support structure. the method also includes performing a purge operation for each print head or deposition line switched to the operating mode, where the purge operation includes printing a layer of at least one purge tower from the print head or deposition line switched to the operating mode. patent number tittle publication date us2014358273a1 platen planarizing process for additive manufacturing system 12/04/2014 us2014265040a1 additive manufacturing system and method for printing three-dimensional parts using velocimetry 09/18/2014 us2014252684a1 additive manufacturing method for printing three-dimensional parts with purge towers 09/11/2014 table 1. stratasys inc. recent patents. 6.2.4.2 united technologies corp. the three most recent patents of united technologies corp. are shown in table 2. patent number wo2014210338a1 consists on an additive manufacturing method which segments a computer aided design (cad) file of a component along a build interface to define at least a first component segment and a second component segment each of the first component segment and the second component segment sized to fit within an additive manufacturing build chamber; manufacturing additively the first 57 component segment and the second component segment within the build chamber; and bonding the first component segment and the second component segment to form the component. in patent number wo2014193505a1 a machine for fabricating a fiber-reinforced component by additive manufacturing is disclosed. the machine may have a surface, a matrix feed configured to deposit a plurality of matrix layers on the surface, and a fiber feed configured to deposit a fiber layer on at least one of the plurality of matrix layers. the deposition of the plurality of matrix layers and the fiber layer may be controlled by a computer. patent number wo2014179679a1 presents a method for operating an additive manufacturing apparatus; the method comprises directing a first energy beam along a surface contour vector in a build plane. a second energy beam is directed along a plurality of substantially parallel hatch vectors disposed in the build plane inward of the surface contour vector. a sum of the surface contour vector and the plurality of hatch vectors define a processed powder region in the build plane. a third energy beam is directed along an offset contour vector in the build plane. the offset contour vector includes a plurality of unprocessed powder regions in the build plane between the surface contour vector and the plurality of hatch vectors. patent number tittle publication date wo2014210338a1 additive manufacturing system and method of manufacture 12/31/2014 wo2014193505a1 continuous fiber-reinforced component fabrication 12/04/2014 wo2014179679a1 method of eliminating sub-surface porosity 11/06/2014 table 2. united technologies corp. recent patents 6.2.4.3 alstom technology ltd the three most recent patents of alstom technology ltd are shown in table 3. patent number ep2772329a1 refers to a method for manufacturing a hybrid component comprising the steps of a) manufacturing a preform as a first part of the hybrid component, then b) successively building up on that preform a second part of the component from a metallic powder material by means of an additive manufacturing process by scanning with an energy beam, thereby establishing a controlled grain orientation in primary and in secondary direction of at least a part of the second part of the component, d) wherein the controlled secondary grain orientation is realized by applying a specific scanning pattern of the energy beam, which is aligned to the cross section profile of said component or to the local load conditions for said component. previous patent is also published as patent number us2014242400a1 (the second patent on the table 1) as well as us2014242400a1, kr20140109814a, jp2014 169500a, cn104014799a, ca2843450a1. patent number us2014154088a1 refers to a method for manufacturing a three-dimensional metallic article/component entirely or partly. the method includes a) successively building up said article/component from a metallic base material by means of an additive manufacturing process by scanning with an energy beam, thereby b) establishing a controlled grain orientation in primary and in secondary direction of the article/component, c) wherein the secondary grain 58 orientation is realized by applying a specific scanning pattern of the energy beam, which is aligned to the cross section profile of said article/component, or with characteristic load conditions of the article/component. patent number tittle publication date ep2772329a1 method for producing a hybrid component 09/03/2014 us2014242400a1 method for manufacturing a hybrid component 08/28/2014 us2014154088a1 method for manufacturing a metallic component by additive laser manufacturing 06/05/2014 table 3. alstom technology ltd recent patents as it can be seen from the previous information, stratasys inc. (top 1) is patenting methods for developing three dimensional objects with additive manufacturing systems. specific components (e.g. heads, velocimetry) for manufacturing processes are invented. these components are incorporated to improve the quality of the resulting objects. moreover, united technologies (top 2) is focusing its research efforts on equipment for printing 3d objects. the company has patented a method for operating a 3d printing device and a machine for fabricating fiberreinforced objects. finally, alstom technology (top 3) is patenting methods for developing hybrid components with metallic powder materials. 6.2.5 top inventors top inventors on am were also identified. as shown in figure 14, swanson williams j. from usa is the inventor with the highest number of patents (in total 32). secondly, etter thomas from switzerland (28), and thirdly scott simon peter from great britain (26). regarding family patents, the top 3 inventors in descending order are: swanson william j. from usa (17) who presents the highest technology diversification in terms of patent families, renishaw plc from great britain (15) and mannella dominic f. from usa (11). these results are shown in figure 15. 59 figure 14. top 3 inventors per patents. data from espacenet using matheo patent. figure 15. top 3 inventors per family patents. data from espacenet using matheo patent. 6.3 technology mapping relationship between top patent organizations and top ipc four digits are presented on figure 16. top organizations are focusing its research efforts on subjects related to ipc codes b29c and b22f, shaping of plastics and after-treatment of shaped products and working metallic powder and manufacture articles from this material. stratasys inc. is the organization that has the highest number of family patents related to ipc code b29c (31 family patents). moreover, united technologies corp. is the firm that has the highest number of family patents related to ipc code b22f (16 family patents). 60 figure 16. top organizations vs. top ipc four digit codes. data from espacenet using matheo patent. 7.0 conclusions for the development of this research a patent analysis tool was applied to identify key players and trends in the am industry. main countries, organizations, inventors and technology areas through international patent classifications (ipcs) were identified as well as the last inventions of firms with the highest patent activity. a total of 735 patents, 336 family patents and 629 inventors were analyzed in a period of time comprising 2011 to january 28th, 2015. results indicate that research on am has had a significant increase in the last years, particularly in 2013 and 2014. the trend is similar when considering family patents, a significant increased could be observed for both years. the main areas of research are focused on shaping of plastics and after-treatment of shaped products and working metallic powder and manufacture articles from this material. methods for soldering are also considered in research efforts. from the applicant and inventor country points of view a strong patent activity was detected primarily from usa followed by great britain. an analysis of the top patent companies and their recent research efforts was performed. top three companies are stratasys inc. (usa), united technologies corp. (usa) and alstom technology ltd (switzerland). the first company is patenting methods for developing three dimensional objects with am systems. the second one is focused on the development of equipment for printing 3d objects. the third one is patenting methods for developing hybrid components with metallic powder materials. a technology map was also developed to identify the most important research lines of the top organizations. insights obtained show that they are devoting efforts on shaping plastics and on aftertreatment of shaped products, as well as working metallic powder and manufacturing articles from this material. results obtained aim to offer valuable knowledge to decision makers interested in knowing the technological advances and key players of am. moreover the findings serve as model for how to perform similar analysis. 7.1 limitations and future research 61 this research on additive manufacturing represents a first approach for developing a broader analysis on strategic foresight. a patent analysis was developed considering the exact phrase: additive manufacturing. a complimentary analysis should be developed adding terms such as 3d printing or rapid prototyping. additionally, it is important to extend information collection from primary and secondary resources. expert participation from industry and academy is fundamental. inclusion of scientific literacy and industry reports is also needed. a future research can also develop technological trends analysis. 7.2 acknowledgment we would like to thank marcela hernández, research assistant of the competitive and technological intelligence area of tecnológico de monterrey, campus mty for her valuable support during the development of the final version of this paper. we also thank the anonymous referees for their valuable comments. 8.0 references balbi, e. 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(2010). study on early warning of competitive technical intelligence based on the patent map. journal of computers, 5(2), 274–281. http://www.oei.es/salactsi/prospectiva2.pdf http://www.oei.es/salactsi/prospectiva2.pdf http://works.bepress.com/jan_youtie/54 vol9no1paper1 to cite this article: nuortimo, k.p. & härkönen, j. (2019) exploring new ways to utilise the market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power. journal of intelligence studies in business. 9 (1) 5-16. article url: https://ojs.hh.se/index.php/jisib/article/view/368 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index exploring new ways to utilise the market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power kalle petteri nuortimoa*, janne härkönena auniversity of oulu, finland; industrial engineering and management *kale.nuortimo@shi-g.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: exploring new ways to utilise the market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power enhancing competitive response to market challenges with a strategic intelligence maturity model gianita bleoju and alexandru capatina pp. 17-27 how managers stay informed about the surrounding world journal of intelligence studies in business v o l 9 , n o 1 , 2 0 1 9 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 9, no. 1 2019 klaus solberg søilena pp. 28-35 kalle petteri nuortimo and pp. 5-16 janne härkönen exploring new ways to utilise the market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power kalle petteri nuortimoa*, janne härkönena aindustrial engineering and management, university of oulu, finland corresponding author (*): kale.nuortimo@shi-g.com received 12 december 2018 accepted 2 april 2019 abstract the challenge in today’s corporations is that even though the technology portfolio of a company plays a crucial role in delivering revenue—falling as a topic mainly under the area of technology management—technology may have a negative image due to observed risks or failing the sustainability criteria. it may influence the company’s image and brand image, possibly also influencing decisions at corporate level. the monitoring of technology sentiments is therefore emphasized, benefiting from the advanced methods for business environment scanning, namely market and competitor intelligence functions. this paper utilizes a new big data based method, mostly utilized in market(mi)/competitor intelligence(ci) functions of the company, opinion mining, to analyse the global media sentiment of nuclear power and projects deploying the technology. with this approach, it is easier to understand the linkage to corporate images of companies deploying the technology and also related corporate decisions, mainly done in the areas of technology market deployment, marketing and strategic planning. the results indicate how the media sentiment towards nuclear power has been mostly negative globally, particularly in social media. in addition, results from similar analyses from a single company’s images for the companies currently deploying the technology are seemingly less negative, indicating the influence of company’s communication and branding activities. this paper has implications showing that a technology’s media sentiment can influence a company’s brand image, marketing communications and the need for actions when technology is deployed. in conclusion, there seems to be a need for better co-operation between different corporate functions, namely technology management, mi, marketing and strategic planning, in order to indicate technology image impacts and also counteract firestorms from social media. keywords company media analysis, editorial media, learning machine, market intelligence, media-analysis, nuclear power, opinion mining, social media, web intelligence 1. introduction new applications based on web intelligence, digitalization and social media analytics are currently being studied in different research branches. competitive and technological intelligence (cti) tools are used in companies and research organizations to get the best efficiency out of a market monitoring process, and when these tools develop, more and more companies will be looking for monitoring and management of strategic information (fouratijamoussi, f et al., 2018). in recent years, social media has increased in importance for social networking and content sharing, and services such as twitter can be used for various analyses. for example to forecast box-office revenues for movies, based on sentiment and quantity, it can now outperform purely marketjournal of intelligence studies in business vol. 9, no. 1 (2019) pp. 5-16 open access: freely available at: https://ojs.hh.se/ 6 based predictors (asur, s. & huberman, b, 2010). in a study by søilen et al., 2017, twitter was seen as a source of analysis, what information is being tweeted and not tweeted, thus professional users are aware that tweets are being manipulated by communication departments. twitter has also been considered as a source for detecting disruptive events (alsaedi et al., 2017). furthermore, many companies utilize social media data for analyses, such as likes, comments, and sentiment by using lexicon-based classification to categorize the sentiment of users’ comments (yulianto, m. et al., 2018), like it was in this study. for a company-wide view, individuals and organisations are now adopting public opinions presented across the media to their corporate decision making (liu et al., 2012). by adopting these faster than before, almost in real time, feedback from media sentiment to a change of a company’s product can influence decisionmaking processes of the company. media activities generated by consumers that are neither paid or induced by brand owners are seen to have a potentially game-changing impact on communication and brand building (corstjens, m. & umblijs, a. 2012). what if the large quantity of negative information about a company’s product would flow suddenly by word of mouth (wom) from social media (some)? in reaction to any questionable statement or activity, social media users can create large waves of outrage rapidly, and these online firestorms pose new challenges also for marketing communications (pfeffer et al, 2014). social media monitoring can be efficiently dealt with via a company’s market intelligence (mi) function. to highlight case-specific features of this paper, when nuclear power generation technologies are concerned in the combat against climate change, nuclear power can be considered to be one possible mitigation strategy, due to the extremely low carbon dioxide emissions during the energy resource’s life-cycle (dones et al., 2003). if carbon emissions are reduced also in developing economies, alternative energy sources in the form of green technologies should be deployed as substitutes for coal and petroleum (ganda, 2018). the public perception of nuclear power is however an essential factor influencing whether the technology is used for producing electricity (goodfellow et al., 2011). by relying on nuclear power, a country could be virtually independent from foreign energy sources, and thus gain energy supply security. for example, should fossil fuel reserves become insufficient, other cheap energy sources would be needed to fill the gap (roth et al., 2009). hence, the supporters of nuclear power currently apply two main arguments, firstly nuclear power can secure the fulfilment of our energy demands, and secondly, it is co2 neutral, and would therefore be an effective mitigation strategy against climate change (bang, 2010). nuclear energy falls short on sustainability criteria and its public acceptance can be an issue (verbruggen, 2008). nuclear technologies, despite their enhanced safety, reduced costs and minimised waste, still include the burden of the weapons proliferation, safety, waste handling and high costs. furthermore, concerns have not been reduced due to the recent fukushima accident (karakosta et al., 2013). several countries are currently facing the question of whether or not to rebuild their nuclear power stations in the next few decades, while policy makers are consulting the public regarding its opinion of nuclear power (visschers et al., 2011). based on literature, the technology itself seems to have a negative image, which is an issue to solve for companies developing nuclear projects. there is an increasing need for studies to better understand the dynamics of the media sentiment, including also some, which can be used for analysing public attitudes with the help of opinion mining, based on artificial learning machine media monitoring systems, by a company’s mi function. compared to traditional news media, which can shape public opinion regarding an issue by emphasising some elements of the broader controversy over others (shah, watts, domke & fan, 2002), some presents more direct opinions, often including emotional content (stieglitz and dang-xuan, 2013). this study analyses the global media sentiment of nuclear power from both editorial and social media by using the madaptive tool for media monitoring, thus comparing the differences at company level. this research aims to fill the gap related to technology sentiment impact at a strategic level of the company with related research method development, namely based on big data utilization with computational linguistics and machine learning, to discover the sentiments from large data sets. 2. literature review the general public is a stakeholder, although this can be overlooked in stakeholder 7 management (mitchell et al., 1997). although nuclear power and renewable power are considered to be the main existing technology options for near zero emission power production, their main difference is sustainability and acceptability. renewable power is considered to be sustainable, nuclear is not, and the public acceptance of nuclear power is also rather low (verbruggen., 2008). there are indications that people’s acceptance of nuclear power may be influenced by the available alternatives, and previous nuclear accidents have increased the public’s opposition towards nuclear power (siegrist et al., 2013). when comparing people’s perception of nuclear power to climate change, it shows that if people are presented with the benefit of nuclear power to mitigate climate change and are asked to choose between nuclear power stations or climate change, cautious preference or ‘‘reluctant acceptance’’ to nuclear power stations and related waste may arise over the consequences of climate change (pidgeon et al., 2008). however, the increase in adoption of renewable power systems can be considered as a decreasing factor for this when providing alternatives. there have been studies examining the willingness to take actions against or in favor of nuclear power stations, with logical implication that the perception of nuclear risks seems to reduce the public’s acceptance or their preference for nuclear power (tanaka, 2004). this has also increased people’s willingness for opposition (de groot and steg, 2010), whereas more perceived benefits increased the acceptance of nuclear power (tanaka, 2004). the recent fukushima daiichi nuclear power plant accident in japan on march 11, 2011 influenced the acceptance of nuclear power globally (siegrist et al., 2013). research about the chernobyl accident in the eighties shows that such accidents may influence the formation of more negative attitudes towards nuclear power (eiser et al., 1990; verplanken, 1989). for example, in germany, attempts to locate a permanent nuclear waste repository and ‘‘the resistance of the german people towards nuclear weapons and atomic energy’’ provoked an aggressive anti-nuclear movement. the movement’s influence particularly heightened after the chernobyl accident, especially in southern germany and bavaria which were affected by the fallout (sovacool et al., 2012). the more recent fukushima accident also had a clearly negative impact on the acceptance of nuclear power, however the mean change was considered moderate and was strongly influenced by participants’ pre-fukushima attitudes (siegrist et al., 2013). in general, media reporting about nuclear accidents does not increase knowledge and understanding of radiation risks, but rather increases negative feelings and risk perception (perko et al., 2012). according to keller et al. (2012), particularly affective images seem to affect people’s acceptance of nuclear power. therefore, people who earlier may have opposed the replacement of nuclear power plants may change their opinion when associating nuclear power with images such as radioactivity, nuclear accidents, risks and negative consequences for health and the environment, or even nuclear war (siegrist et al., 2013). there are studies showing that those people who trust authoritative institutions such as the government are usually more supportive for nuclear technologies. it is shown that renewable technologies may not be as liked as nuclear technologies are disliked (sovacool, et al., 2012). the concepts of risk and dread can be more often expressed reasonably by people who are opposing the replacement of nuclear power plants than by those who are in favour (siegrist et al., 2013). different content analysis methods can be considered to study a technology image, such as media framing (teräväinen et al., 2011). however, these were not applied in this study. previously, media frames were used together with cluster analysis and automated sentiment classification by bursher et al, 2015. also, few studies compare people’s acceptance of nuclear power to that of other energy sources (ansolabehere and konisky, 2009). from this, it seems that people who supported the replacement of nuclear power often associated nuclear power plants with neutral and positive concepts such as energy, and to a smaller extent, with necessity (siegrist et al., 2013). furthermore, many discursive strategies can be considered when communicating nuclear power technologies, such as necessitation, naturalisation, scientification and rationalisation (teräväinen et al., 2011). this study introduces a new method for both editorial and some analysis: an opinion mining approach based on a machine leaning mediaanalysis to provide a wider view. 8 3. research methods the research methodology in this paper is based on a literature study accompanied by opinion mining based on media sentiment analysis including a vast number of editorial and social media sources, with a lexicon-based approach. thus, the basic research principles have been formerly used in different fields of studies, for example in competitor and market intelligence studies. in this study, however, the application of framing and cluster analysis was considered to be non-applicable, in addition to statistical methods. this is due to a comparison of editorial content with some, and to the fact that media frame comparability between two different types of communication is challenging. furthermore, it was also challenging to find suitable statistical method for data-series analysis. the main reasons for choosing this method was applicability to large global datasets, both from editorial content and some, fast data processing and reduced risk of bias caused by human perceptions and interpretations (matthes & kohring, 2008). the data for this study is taken for one year, included in the period was a major international climate conference, paris cop21. the users of the social web have a new role as data providers, as it seems to provide an excellent platform for analysing public attitudes (penalver-martinez et al., 2014). by adopting this type of approach and a particular tool, the amount of analysed datapoints is drastically increased compared to questionnaires and interviews, or traditional media-analyses. despite the ipr-protected algorithm, which is not visible, the method is not entirely a black box, it is rather a grey box. for this reason, software was tested in a master’s thesis (nuortimo, 2015) comparing it to traditional media analysis methods and the logic of how the sentiment is calculated is known, as sentiment is mathematically calculated as a sum from local document sentiments. futher, software is learned by humans for better accuracy. in computational linguistics, due to the complexity of the algorithms, they are usually evaluated on the basis of testing and comparison, as was done by chen, 2018. the data was analyzed to obtain a clear view of nuclear power technology sentiment and to discuss further implications to companies. hence, the research setting in this article is the media-sentiment analysis, where media sentiment is analysed to discover possible implications to public acceptance. as a result, we attempt to clarify the link to technology market deployment and corporate decisions. this method is based on commercial software in order to discover the sentiment relating to nuclear power, similar to the method applied by burscher et al, 2015. opinion mining is a research field, which consists of natural language processing, computational linguistics and text analysis technologies, in order to get various informational and added-value elements from users’ opinions (penalver-martinez et al., 2014). the approach used in this paper, where an algorithm calculates the global document sentiment based on the quantity of local sentiments, seems to be a valid approach despite known errors (app. 20% of classifications). furthermore, human analysis of text information is subject to considerable biases, such as emphasising the importance of opinions matching with their own preferences (liu et al., 2012). in this paper, the media sentiment of nuclear power both in editorial and some is studied. the m-adaptive software is used, which includes 3 million some platforms and 100,000 news outlets. the sentiment is analysed as a combination of computational linguistics and human aided machine learning (m-brain). the method is a more quantitative type of analysis compared to traditional qualitative methods such as surveys. in the software, the keywords “nuclear power” were used as input. the analysis was made over one year 2.7.2015-2.7-2016, and included a total of 41,591 data points from both editorial publications (14,482) and some sources (27,109). the study can be replicated by typing the same search words into the m-adaptive software. the sentiment expressions in the text are recognised and then classified automatically by type:positive, negative, neutral, mixed or unknown. m-brain has made some internal tests, which indicate app. 80 % accuracy in sentiment classification. the error occurs in case of any given individual document, due to inherent ambiguity in natural language. it is also known that humans do not agree 100% in similar cases. as a limitation, the system does not recognise humour or sarcasm. however, in large data sets, the overall model matches human judgement on the same data qualitatively. 9 4. media sentiment of nuclear power technology in the machine-based analysis, the large amount of data points gained from media hits provides a good basis for analysing the media sentiment, especially in terms of regular people on some. in figure 1, the sentiments towards nuclear power are described both from editorial publications, and some. the results indicate that nuclear power is linked to negative hits both in editorial publications (8,976) and some (11,458). there were 3,737 positive hits in the editorial content and 5,183 in some, which is fairly low compared to the total hits. the neutral hits accounted for 726 in the editorial content and 9,899 in some. mixed hits accounted for 1,043 hits in the editorial content and 569 hits in some. this seems to indicate that the press has adopted a negative tone towards nuclear power during the time period in question. figure 2 describes the 62% of negative hits in editorial content. only 26% of hits in editorial publications were positive, indicating a relatively low technology acceptance among journalists, and also an absence of the journalistic type of discussion and rhetoric which would include multiple views. the amount of mixed (7%) and neutral (5%) hits is quite small. figure 3 describes the public sentiment towards nuclear power in some as negative (42%). this was somewhat different compared to editorial publications, with a slightly less negative share. figure 3 indicates that public sentiment toward nuclear power in some is also more neutral (37%) with a 32% difference compared to editorial publications. this can be seen as an indication that the press has adopted more negative discourse than individuals on some. figure 4 indicates that twitter provided the most some data, with almost eighteen thousand hits. these were mostly neutral (9,231) or negative (5,425), with fewer positive (3,185) and mixed (44) hits. this can be observed as a negative data concentration. blogs had 4,288 negative hits, 1,253 positive, 411 mixed and 226 neutral. in comparison with tumblr (238), google plus (1,345), facebook (471) youtube (404), vkontakte (45), instagram (109) and forums (434), twitter (17,885) was the most influential some source. figure 5 shows that media sentiment has followed roughly new nuclear building in the selected countries. finland is building the olkiluoto 3 unit and also the hanhikivi plant by fennovoima (subject to building permits), and the country clearly has less negative sentiments both in editorial content and in some. japan, after the fukushima accident, experienced more negative attitudes. france, china and russia are all major countries with nuclear capacities. they fall in the middle of the spectrum. britain, now with hinkley point considerations, interestingly has a more negative tone compared to germany, which has a significant nuclear decommissioning program and large renewables capacity. it may be an indication that the supply security issue might rise in importance. india has the largest difference between opinions from editorial content and some, where sentiment in some is interestingly 23% less negative. figure 6 illustrates the effect of the global paris cop climate negotiations on the nuclear power media image in editorial publications figure 1 sentiment analysis of nuclear power in some vs. editorial publication. figure 2 sentiment analysis of nuclear power in editorial publications. figure 3 sentiment about nuclear power in social media. 10 and in some. the preliminary conclusion that can be drawn from this entails that nuclear power technology is not seen as a solution that is considered for addressing climate change, and thus media-attention towards nuclear power technologies is mostly negative. from the general data analysis it is visible that public sentiment towards nuclear power in both some and editorial publications was mostly negative, similar to the results of the literature review. however, when moving from a global level to country level, there exists some variations in media sentiment, depending on each country’s political situation and also new nuclear building in the country. two countries with ongoing nuclear developments, namely finland and uk, were selected. on a country level, finland clearly had the lowest negative editorial media sentiment of the selected countries, and also the second lowest percentage in some after germany. this figure 4 deviation of social media sentiment analysed by media type. 46% 27% 17% 40% 58% 63% 73% 39% 66% 17% 20% 43% 50% 40% 57% 50% 60% 0% 10% 20% 30% 40% 50% 60% 70% 80% china germany finland france great britain india japan russia usa media sentiment in selected countries editorial % negative some % negative figure 5 media sentiment on nuclear power in selected countries. 11 indicates a more positive tone towards nuclear power in finland. project media sentiment over a half year (1.12.2016-25.5.2017) was observed in the case of two projects, namely fennovoima in finland and hinkley point c in the uk, both of which are in early construction phases of development. figure 7 illustrates the sentiments towards fennovoima, a project company established to build a hanhikivi nuclear reactor in finland. from figure 8 it is visible that fennovoima has attracted mostly neutral and also positive attention both in editorial content and in some. this indicates the general positive attitude in finland, visible in the country analysis, and may indicate also the presence of pr-activities by the company. when looking more closely to the media source in the case of fennovoima it can be observed that the mostly positive editorial media attention has had some response from twitter, which is more negative, possibly indicating the presence of local opposition groups. compared to the editorial media, which is clearly more positive, this indicates figure 7 media emphasis on nuclear power during the global paris cop climate negotiations. figure 6 media sentiment towards fennovoima. figure 8 media sentiment towards fennovoima/by source. 12 that some channels can be used as means for communicating local opposition in the case of large onshore projects. the media attention for the hinkley point c project in the uk (figure 9) seems to follow the general consensus of the country with its more negative attitude. however opinion towards nuclear power is still mainly positive in the editorial media, but mostly negative in some with app. ten times less hits than in editorial media. figure 9 describes the sentiment towards hinkley point c according to editorial media and some, with an clear indication that the editorial media emphasized both positive and negative communication. the general sentiment is positive. however, the percentage of negative sentiments is slightly higher in some (figure 10). when summarizing the media sentiment of nuclear power (figure 11), it can be observed that although globally the sentiment in the editorial media (62%) and in some (42%) is negative, there are differences on a country level. for example, countries with less negative sentiments compared to the global average, such as finland and the uk, also have active nuclear projects in the country, and those projects also have a less negative media image than nuclear power does on the country level. there is slightly higher percentage share of negative some sentiment for a single project. however, on a project level, the media attention is less negative both in the editorial media and in some than at the global and country level, possibly indicating that with positive project investment decision, there is supporting communication from the project company. for these countries with nuclear figure 9 media sentiment in hinkley point c. figure 9 the comparison of nuclear power negative sentiments at global, country and project levels. figure 10 media sentiment towards hinkley point c, editorial/some. 13 capacity, it is not comparable to country sentiment. figure 11 shows that globally the sentiment about nuclear power in the editorial media (62%) and in some(42%) is clearly negative, there exist differences on country and project level. finland and the uk have less negative sentiments compared to the global average, and nuclear projects also have a less negative media image than nuclear power on the country level. thus there is slightly larger percentage share of negative some sentiment for single projects (finland/fennovoima (2%) and uk/hinkley point c (7%)). on a nuclear project level, the attention is less negative both in editorial media and in some than at the global and country level. 5. discussion the global media-analysis was conducted by utilising a key-word based search and madaptive media monitoring software. the analysis was made over one year, 2.7.2015-2.72016, and included a total of 41,591 data points from both editorial publications (14,482) and social media sources (27,109). media sentiment of nuclear power was neutral and negative in editorial content and in some, where some sources included more neutral attitudes. active discussions concerning nuclear power have taken place for example on twitter, with almost eighteen thousand mostly neutral and negative hits, emphasising the importance of short communication via social media. the analysis points out that the general publics’ opinion can be an important factor for technology acceptance and a company’s brand image. good examples of this correlation include finland’s positive attitudes and new building projects, and japan’s negative media sentiment as a response to the recent nuclear accident and nuclear decommissioning program. when considering the effect of relevant international events such as the paris cop 21, the media attention is increased during the event. in this case the attitude shift towards nuclear power was mostly negative. the main benefits of the results lie in figuring out global trends and technology development directions by using a larger data set than previous studies, and fast analysis of possible changes influencing decisions on a corporate level. the role of some is continuously increasing and it presents a challenge for technology developers and corporate strategists. it seems that a negative link between media sentiment of technology to technology market deployment exists in the case of nuclear power, needing actions on the company and project levels, such as communication, branding and pr. the main contribution of this study lies in incorporating a method of competitor/market intelligence functions to study the media sentiment of nuclear power, therefore bringing a new angle to corporate decisions. this is a new type of approach compared to earlier questionnaire, or interview-based studies with moderate datasets of hundreds of data points that are used in most similar studies, e.g heras-saizarbitoria et al., (2011). this method has positives and negatives when compared to qualitative studies. however, in the future this type of method could be used as a basis for both longitudinal data-series analyses, and also for some firestorm detection. the ability of the software does set some limitations on the extent of possible time periods to be analysed, yet still allows for 62% 17% 10% 58% 32% 42% 20% 12% 50% 39% 0% 10% 20% 30% 40% 50% 60% 70% global finland fennovoima great britain hinkley point c nuclear power media sentiment comparison editorial % negative some % negative figure 11 the comparison of nuclear power negative sentiments at global, country and project levels. 14 analysis of extensive data sets. the sentiment analysis indicates that large emotional bursts relate to some firestorms, thus sentiment is calculated and the number of negative bursts is clearly visible in the data-series trend analysis. this study agrees with stieglitz and dang-xua’s (2013) view, that emotionally charged social media messages are repeated more often and quickly than neutral ones. this view could be used as a basis for an automated social media firestorm detector, in which the application would give signals if there are signs of large negative sentiment rising in some together with escalation in speed estimates and a corporate action plan. managers can benefit from the possibility of analysing global attitudes and their changes, for example for their companies or projects, highlighting the needs for public engagement and the urgency of some participation. in this study, there are the following limitations: 1) the results are dependent on the keywords used. 2) content analysis methods, such as framing and cluster analysis, were not applied. 3) statistical methods were not applied. although statistical techniques are applied by communication scholars in order to identify news frames, it is not possible to do this in a conceptually valid manner (carragee & roefs, 2004). this also brings challenge for further research. 4) no detailed content analysis was possible due to a very large dataset, leaving the classification errors depending mostly on accuracy provided by the software supplier. 6. conclusions this study shows how a company’s mi function can be utilized in defining product technology sentiment, which in the case of nuclear power technology has a neutral and negative public sentiment. this is further emphasised during large national climate congresses such as the paris cop21. companies deploying nuclear power projects suffer from a negative media sentiment, which is clearly visible via social media. this is in contrast to renewable power technologies (nuortimo, 2018). factors that favour nuclear power market deployment include its availability and co2-emissions. the media-analysis indicates that on a global level sentiment towards nuclear power is negative, but in the case of individual projects there is a more positive sentiment, probably due to the project company’s communications and branding efforts. some especially has a role in influencing nuclear power technology’s media sentiment, which can be considered when planning marketing and pr for a single company. thus, when facing negative sentiment towards the company’s main technology, there seems to be constant need for a positive brand messaging. this paper also indicates the need for cooperation between a company’s mi function and marketing, in order to detect and counteract possible firestorms arising from some. the link from technology’s media sentiment at the corporate level exists in the case of nuclear power, with implications to managerial decisions. how can a company monitor media efficiently and distribute this information between different functions? what is the result, does the general public like the technology, and if not, what can be done with this information? a company could divest the technology or increase pr-activities, among other actions. the implications for company strategy also include the emphasis on product portfolio management and co-operation between different functions, including mi, technology management and marketing/pr. this view includes taking advantage of digitalization to refine the product portfolio of the company and better link to the mi function, thus the company’s product strategy is refined to better account for changes in the external market environment, and to highlight the need for supporting pr, communications and public engagement activities. our main finding is that the technology related sentiment of a company’s products may impact corporations on a strategic level, and media monitoring systems from a company’s market intelligence function based on big data utilization with computational linquistics and machine learning can be utilized to detect this. further research for deeper data-analysis could have interesting results. company-wide implications and co-operation between functions, such as strategic planning, market intelligence, communications and marketing, could be an extensive area for further research. finally, algorithms cannot entirely replace human intelligence yet, however, they do provide significant advantages in quantity and objectivity to aid in various tasks. 15 7. references alsaedi, n., burnap, p., & rana, o. 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(2017) insight through open intelligence. journal of intelligence studies in business. 7 (3) 62-73. article url: https://ojs.hh.se/index.php/jisib/article/view/245 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index opinion insight through open intelligence jonathan calofa,b, greg richardsa and paul santillic atelfer school of management university of ottawa, canada; bnorth-west university, south africa; chewlett packard enterprise; calof@telfer.uottawa.ca journal of intelligence studies in business please scroll down for article opinion integration of business intelligence with corporate strategic management jonathan calofa,b,*, greg richardsa and paul santillic atelfer school of management university of ottawa, canada; bnorth-west university, south africa; chewlett packard enterprise corresponding author: calof@telfer.uottawa.ca received 10 october 2017; accepted 27 october 2017 abstract the traditional model of competitive intelligence and its operationalization in most organizations appears to be inadequate to address the intelligence challenges arising from the speed of change in the environment, increasing data complexity, and growth of international activities. to address this challenge, this article borrows concepts from open innovation, applying them to all ci activities. we are suggesting going beyond the traditional model of an in-house ci unit with activities largely conducted by the units personnel and moving towards a cross pollination approach whereby others in the firm contribute to all ci activities including, for example, the selection of key intelligence topics and being involved in analysis and eventually towards a full open intelligence model in which key stakeholders and external experts also assist the organization in all aspects of competitive intelligence activity. in proposing a more open approach for intelligence, the authors recognize the concern that ci professionals will have regarding sharing intelligence and intelligence activities outside the ci unit and outside the organization. however, as pointed out in this article, organizations around the world have been moving quickly towards an open innovation model generally concluding that the benefits associated with opening up all elements of the innovation process, including r&d, outweigh the risks of intellectual property loss. keywords analytics, big data, competitive intelligence, open innovation 1. introduction with over 60 years of combined experience in competitive intelligence practice, research, consulting, teaching and writing (and areas related to intelligence) the authors of this article propose a reconceptualization of competitive intelligence. weaknesses in the current definition and practice of competitive intelligence lead us to broaden out those involved in helping organizations’ intelligence programs by incorporating several concepts from open innovation. we propose the integration of principles from analytics as well. we are calling this new intelligence concept “open intelligence”. we feel that the current practice of competitive intelligence does not address challenges arising from the speed of change, the growth of international activities (not just selling internationally but sourcing) and increasing data complexity, but that by incorporating ideas from open innovation and analytics that these challenges can be met by tomorrow’s competitive intelligence practitioners. journal of intelligence studies in business vol. 7, no. 3 (2017) pp. 62-73 open access: freely available at: https://ojs.hh.se/ 63 2. objective of the article the journal of intelligence studies in business has served for several years as the primary outlet for the exchange of intelligence ideas. the journal has had articles that attempt to define competitive intelligence. for example, du toit (2015) looked at academic scholarship in ci from 1994 to 2014, looking for a common definition and parameters for the field. soilen (2016) through a survey of ci experts and an examination of articles in scopus that contained the words competitive intelligence, attempted to develop a definition of ci and establish and a research agenda for the field. while these and other authors of papers in the journal have tried to define competitive intelligence, others have proposed the need to extend the domain of competitive intelligence. nienaber and sewdass (2016) proposed to expand the domain of ci to include workforce related competitive intelligence. vriens and soilen (2014) proposed extending the domain of ci to include disruptive intelligence. the idea of adding like this to the domain of intelligence generally represents an acceptance of the definition of competitive intelligence, but an expansion of its role or, put another way, a broadening of the key intelligence topics, to use jan herring’s terminology. still others have sought to broaden the domain of intelligence, pushing into or absorbing other similar or related areas. for example, rostami (2014) wrote about integrating knowledge management with business intelligence. calof, richards and smith (2015) suggested extending foresight to include both foresight and analytics and, in fact, many articles in the journal of intelligence studies in business have focused on business intelligence, for example alnoukari and hanano (2017) and gauzelin and bentz (2017). in short, the journal of intelligence studies in business has served not only as one of the primary journals for publishing scholarship about ci (soilen 2016) but it is also a journal that has sought to define competitive intelligence including what it is, its scope and research agenda. in fact, the journal, in defining its publication topics, notes that it “publishes articles on topics including marketing intelligence, marketing intelligence, strategic intelligence, business intelligence, competitive intelligence, collective intelligence and scientific and technical intelligence”. with this article, the authors seek to add to this theme within the journal. we propose a reconceptualization of competitive intelligence with the incorporation of concepts from open innovation and contributions from analytics. we write this article to the ci community and in doing so invite feedback from those who read it. a version of this article has been published in competitive intelligence magazine (summer 2017) but this is geared more towards an academic audience. it is our collective view that how we look at and practice competitive intelligence has to change in light of several changes in the environment that will be described in this article. we draw upon many concepts in open innovation as we seek to push the boundaries of competitive intelligence and expand the role played by both those within organizations and outside of it in driving the organizations’ intelligence initiatives. we seek to be part of a growing dialog within the pages of the journal of intelligence studies in business about how competitive intelligence should evolve in the future, and invite those who read this article to lets us know what they think. 3. the challenge while there have been many changes in the business environment that competitive intelligence has had to address, there are three that the authors of this article seek to highlight, that we feel are amongst the most important changes and also those for which we feel traditional views of intelligence have had difficulty addressing, at least according to our experiences and discussions we have had with leading practitioners and researchers in competitive intelligence: 1. speed of change, 2. increasing data complexity 3. growth of international activities (not just selling internationally but sourcing) these challenges are explained in greater detail in this section. 3.1 speed of change in 2011, harvard business school professor and noted management thinker john kotter wrote: “anyone in the business world – even casual observers of it – knows that it’s currently experiencing a rapid rate of change. new companies spring up seemingly overnight. products and services that were revolutionary two years ago are rendered obsolete if they don’t adapt to market 64 changes fast enough. the rate of change in the world today is going up. it's going up fast, and it's affecting organizations in a huge way. the evidence of this can be seen almost everywhere—life-cycle of products, number of patents filed in the us patent office, amount of cell phone activity across national boundaries—on and on and on. and what's particularly important is that it's not just going up. it's increasingly going up not just in a linear slant, but almost exponentially.” what does this mean for competitive intelligence? many intelligence projects will need to be done on a frequent, almost daily basis to reflect the rate of change in these areas. looking for both the emergence of threats and opportunities needs to be done in time so that managers can act in a timely manner, but the rate of change is also greatly compressing the amount of time available to gather, analyze and make sense of the information. 3.2 increasing data complexity at the scip conference in atlanta (may 2017), a dominant theme among many of the keynotes was increasing data complexity and the need to develop approaches to deal with and in fact take advantage of big data. steven hughes opened the conference with a talk “big data is our future” and day two had major general neeraj bali present a case study from the indian army in which big data figured prominently. among the numbers quoted in the presentations: 31.25 million messages sent every minute, 30 billion pieces of shared content on facebook every month, 2.77 million videos viewed every minute, google users perform 40,000 searches per second, more than 196,000 databases published annually by the u.s government, and by 2019 one million minutes of video will be uploaded every second. it would take five million years to watch all the videos posted each month. the internet of things (iot) with increased machine to machine communications, data gathering sensors, and more, was also mentioned as both an opportunity and challenge for competitive intelligence. social media, twitter, and blogs also generate data that can be used in intelligence programs. it’s not that the traditional primary sources from interviews are not important for intelligence, but the growth and availability of these online videos, discussions, and materials does provide great opportunities on the collection side of intelligence. the problem, however, is coming up with a way to cope with all this data. ibm, in their big data and analytics hub, wrote about the four vs of big data (ibm, 2017) which we are collectively terming “data complexity”: 1. volume or scale of data. for example, most companies in the us have 100 terabytes of data stored, six billion people have cell phones; 2. velocity/analysis of streaming data. for example, 1 terabyte of trade information captured by the new york stock exchange each day, 18.9 billion network connections – 2.5 per each person on earth; 3. variety or different forms of data. for example, 400 million tweets sent per day, 4 billion hours of video watched on youtube each month, 30 billion pieces of content shared on facebook each month; 4. veracity or uncertainty of data: notably, 1 in 3 business leaders don’t trust the data they use to make decisions, poor data quality is estimated to cost the us economy alone $3.1 trillion per year. 3.3 growth of international for many organizations, tomorrow or even today’s competitor can come from outside their country. customers may also come from countries from outside the organization’s country. technology and other changes can come from anywhere in the world. managing in this environment requires the development of intelligence programs that gather information from many different countries, knowing what the best sources of information are in foreign environments and in some cases dealing with the fact that the best information for their intelligence program may not be in english. the challenge for ci is how to integrate the opportunity provided by this volume of data along with our more traditional information sources while addressing the problems related to data volume, variety, velocity, veracity and internationalisation. the combination of the rate of change, international factors and the big data challenge means that ci teams will need to come up with a way to increase the frequency of their intelligence project updates while integrating a broader array of data. doing this 65 in the traditional one or two-person intelligence team is going to be difficult. the following lays out how we are proposing to add to the concepts of competitive intelligence to address these challenges. it is a reconceptualization of the phases of intelligence and the addition of concepts from open innovation to intelligence. 4. new ideas within the wheel of intelligence traditional ci approaches revolve around some version of the wheel of intelligence approaches we have seen on leading organizations’ use terms, such as: 1. issue identification 2. plan generation 3. data acquisition 4. data analysis 5. recommendation there are many variations of this approach based on corporate management structure and decision-making authority, size of the organization, and the type of issue to be resolved. but these five steps are really the crux of any “generic” ci effort in an organization. the du toit (2015) article explores these ideas in great detail and serves as a useful review of the ci literature. the problem with this traditional approach is that the time for all of this to happen can exceed weeks or months before actionable insight can be developed. the sequential nature of the wheel of intelligence has been challenged in many past studies, but it is clear that in fast changing environments time can be a challenge for doing all these steps. add to that the time for the organization to actually act on the insight and we are talking additional months added to the overall ci lifecycle. given the time frames involved, the impact of the 4 vs associated with big data can make this traditional approach grossly inadequate and subsequently useless. business disruptors and industry changes occur in the blink of an eye and through the globalization of the digitized world we live in, can affect regions and potentially world economics in a fraction of the time it took only 10 years ago. data and insights that are months out of sync with reality cannot provide a competitive advantage to any organization, rather, an approach must be developed that takes into consideration the volume of information, the sources, the ability to manage the content, and the organizational flexibility to not only adapt, but to flawlessly execute on a regular basis, will be needed. there are several strategies that can be employed to help navigate the challenges stemming from this environment during this important data collection and analysis phase. 4.1 data generation first, in terms of data generation, the sources and volume of data overall are exploding. as mentioned earlier, this growth is expected to continue at an exponential rate. there is essentially no such thing as a suitable environment for “batch” processing – anything not done as close to real time as possible will become useless. so, it is critical to know that the longer from the time the data is generated to analysis, the more misleading and outdated the data becomes – and all downstream activities of analytics, processing, insights and execution eventually snowball into an extremely high-risk business strategy. that is not to say that one should just hang up the proverbial ci hat and chalk this environment as a no-win scenario. rather, there are techniques available for moving closer to the “real-time” environment that will provide valuable insights and ultimately a competitive advantage for organisations. there are many techniques (albeit some more advanced than others) that have shown great promise in a) getting better data, b) getting it quickly, and c) expanding the breadth of data collection to include more value-rich content. these techniques include: 1. concurrent analyses methodologies – simultaneously collecting, analyzing and sharing the data with stakeholders in a reiterative parallel process, rather than serially collecting and vetting the data with stakeholders, which can take magnitudes longer in time and resources 2. organizational efficiencies – built-in hierarchical structures that encourage quick data sharing and communication without long lag times to decision making and execution 3. real-time data collection methods – ability to harvest content from thousands of sources to effectively pull valuable “golden nuggets” from the vast amount of overall data. 66 4.2 tools for data generation and analysis secondly, the use of specific data-management tools becomes a necessity in this data-rich environment. public domain search engines fall woefully short in providing the content in a format that is user-friendly, and throwing lowcost physical resources at the problem only leads to more confusion and frustration in coordination and results in a reduction in speed to insights. knowledge management tools or related automation mechanisms are crucial in order to navigate the volume of data coming from the web. this includes not only public domain source content, but social media, customer feedback, and paid sources. the key determinant in the appropriateness of the result will often depend on the robustness of the input content. identifying and managing the resources that provide data into the automation tools is a critical area of development. letting the tool do the “heavylifting” of analytics with source content that routinely numbers in the thousands or tens of thousands or more of sources and will ultimately provide a much better outcome over time. from a practitioner’s perspective, the value of the tool cannot be overstated. it has allowed organizations to be far more efficient and, overall, more effective in improving the analytics and arriving at actionable insights far faster than without the tool. an example of such a tool is one by which a comprehensive database repository can capture data and categorize it into several areas: 1. content repository – funneling hundreds or thousands of data sources into a central location 2. content search – performing boolean, phrase, truncation or other searching mechanisms 3. communication / sharing – ability to cross-functionally share this information readily 4. knowledge visualization – transforming the data analysis into a useable, easily understood visualization for fast deciphering and application 5. actionable insights decisions – arriving at the quickest time possible, the actionable insights to make organizational decisions 4.3 analysis / taxonomy first off, it is important to know what is meant by “taxonomy” – this is the ability to categorize content in the classifications best suited to achieve the intelligence initiative. think about the objective – if it is about a product launch or about how a competitor is performing, there is a set of criteria that needs to be established that acts as a catalyst to achieving the objective. what initial segments of the industry? geographical areas? specific products or general applications? how defined do you want to get into the details of what you are trying to determine? therefore, the ability to analyze this data with the desired taxonomy is important, but one is not looking for a simple listing of relevant sources for a business need. rather, the key output element is to appropriately analyze the data that allows the user to identify and derive key content that can be immediately adjusted to include in the insights for recommendations. many tools have dashboards that are customizable for the user’s preferences and can be adjusted based on the parameters that the user requires. this is something used extensively by many successful organizations and is key to being able to get the data in the right format so that it is easily ported to a recommendations output. additionally, people-engagement is key here – ensuring that the content driven from the automation is relevant, timely, and actionable. you still have to utilize individual perspectives to make sure the dashboard outputs are in line with the company objectives and requirements for the need being investigated. 4.4 organizationstructure and culture it’s not just the process of competitive intelligence that needs to be modified in light of the new environment, but the organization itself will need to be looked at. there are two elements of this, one is the structure itself in that if the information is to be acted on quickly then mechanisms need to be in place to get intelligence into the hands of decision makers quickly. the idea, for example, of the pinnacle of ci being that it is included in the weekly or monthly senior management meetings needs to give way to real time, possibly daily intelligence updates. there is also the cultural element of organization. far too many times senior management will be aware of the 67 content of the intelligence, but will either chose not to act upon it (due to internal feelings outside of the data results), or simply ignore it as a “nice to know” sort of factoid. obviously, both are potential catastrophic behaviors that will only improve the competitor’s chances of getting an advantage in the marketplace, especially given the speed of change mentioned earlier. therefore, company structures have to be shallow and decision making has to be quick. “analysis-paralysis” has to be avoided at all costs. this can only be achieved where you have a “sponsor” at the executive levels of the organization who values the ci contributing efforts and can therefore prioritize and include the results in the strategic direction of the company. 5. opening up the intelligence process: open intelligence with the above ideas implemented in organizations, it becomes more likely that organizations will have the ability to handle the four vs of data and the corresponding international and speed components of insight generation. however, there are concerns that with most intelligence units being one or two people, it will be difficult for the user to actually cope with frequent intelligence projects integrating massive amounts of data, dealing with fast changing environment and incorporating international elements into the model. not only will it be difficult as will be pointed out in the next part of this article, but it might even be undesirable. perhaps a better approach will be to open up the intelligence process. in the next section, we look at a very popular topic – open innovation, the opening up of organizations’ innovation activities including research and development to people outside the organization – even competitors – and applying the concepts of open innovation to competitive intelligence. 6. open innovation our notion of open intelligence is based on open innovation concepts which were pioneered by henry chesbrough. in 2003, chesbrough wrote “open innovation is fundamentally about operating in a world of abundant knowledge, where not all the smart people work for you so you’d better go find them, connect to them, and build upon what they can do”. he went on to explain that: “open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology. open innovation combines internal and external ideas into architectures and systems whose requirements are defined by a business model”. up to this time, innovation was seen as an exclusively internal organization function: r&d inside the organization came up with the ideas and then the organization determined (again internally) which ones to pursue to development and commercialization. open innovation implies opening up the entire innovation process to “smart people” outside the organization. elaine watson in 2012 wrote about coca cola’s open innovation program. coca cola’s chief procurement officer, ron lewis, summed up open innovation and its importance to coca cola when he said: “…our goal is to be the best at innovation in the industry and the way we’re doing that is via an open network. and there is a good chance that the source of such innovation may well come from outside coke’s r&d department. we want to be the best at connecting the dots.” finding ideas outside the organization and connecting the dots are certainly the objectives in open innovation and definitely areas where ci has a role to play. in a 2008 harvard business review article by huston and sakkab on procter & gamble’s (p&g) open innovation initiative, it was noted that as of the 2006, 35% of their new products had elements of open innovation with 45% of the initiatives in the product development portfolio having elements that were discovered externally, with a goal for 50% of innovation to come from outside the company. p&g even established a policy of licensing new products/technology to competitors if p&g had not commercialized it within three years of development. in opening up the innovation process, open innovation researchers do note that part of this opening up is also to parts of the organization that traditionally had not been consulted/included in innovation efforts. for example, volkswagen, in looking at car engine design, allowed individuals from outside the engine group to bring ideas forward and 68 become involved in the selection of which ideas would go forward into design. hansen and birkinshaw linked open innovation to each element of the innovation value chain. in their harvard business review article “the innovation value chain,” they looked at key questions to ask and performance indicators to identify how “open” the innovation process was (table 1). the typical company has virtually all idea generation done in-house. to open up the r&d process to other “bright” people, they talk about crosspollination with other units across the organization providing input to r&d, and external input from people outside the organization who contribute to the r&d idea generation process. we have seen examples of this in many industries. we mentioned earlier about volkswagen opening up engine r&d to people outside the r&d department. bed, bath and beyond, in working with “edison nation,” put a call out for inventors from around the world to provide ideas that could result in new products sold in bed, bath and beyond. this goes beyond idea generation to using an open approach for both idea generation and conversion with bed, bath and beyond doing the diffusion. after 14 years of research and writing on open innovation (14 years after chesbrough introduced the topic) there have been enough case studies and papers written that it is safe to say that there are examples of each element of the innovation value chain, idea generation, conversion and diffusion being done through open innovation. 7. from open innovation to open intelligence innovation was opened up because despite the risks (e.g. loss of intellectual property) the benefits associated with allowing people external to the r&d unit both inside and outside the company to assist with all aspects of the innovation process were too great. organizations have found that with the speed of change and the need for faster and better innovation, it was beneficial to allow other people to have a role in generating ideas, evaluating them and even helping with commercialization. given the complexity and volume around data and intelligence, it is clear that similar to open innovation, it is time to for ci to consider opening up all phases of the intelligence process to deal with similar challenges: the need for quicker intelligence, the need to cope with frequent environmental change, and the need to deal with the complexity posed by big data. the following discussion explores how this would work by going through some of the elements of the traditional intelligence wheel. in looking at open intelligence, some of the language of open innovation from hansen and birkinshaw can be related to ci: • in-house: this will refer to the traditional model of intelligence where most aspects of the intelligence process are done within the ci unit; • crosspollination: this will refer to supplementing the in-house ci unit with input from others and other units table 1 hansen and birkinshaw innovation value chain. 69 of the organization to assist in all aspects of intelligence development; • external: this will refer to supplementing both in-house and crosspollination with people outside the organization such as key customers, suppliers, experts, and other stakeholders to assist with intelligence development. 8. intelligence planning there are many aspects of intelligence planning that could be discussed that could benefit from open intelligence but for the purposes of a basic exploration of the concept we will look at one: intelligence topic generation. intelligence topics are traditionally developed by the person responsible for intelligence based either on their understanding of management needs or through direct consultation with management. we call this the traditional in-house approach to topic development. in ci, we talk about it in terms of “what is keeping the ceo up at night”, “what key decisions are being made”. crosspollination (opening up the process to units outside intelligence) would involve allowing others in the organization to contribute to the intelligence topic generation process. personnel in r&d, for example, understand the technical environment well and might have some interesting perspectives on what topics need to be investigated. those in maintenance or service may have ideas based on the complaints and problems that customers are having. taking an external perspective (fully open), imagine if customers, suppliers, and other stakeholders—possibly even including competitors—provide input on the intelligence topic selection process. nan bulger, in a 2015 article, wrote about integrated intelligence and said that the purpose of intelligence is to “help your customers’ compete in the market and help your customers make money”. if the purpose is to make customers more competitive (a business to business objective – b2b) or simply to satisfy customers (both b2b and more traditional consumer markets), then would it not make sense to ask them what topics are most relevant to them? or perhaps show customers suggested intelligence topics and ask them which one would result in intelligence that would help them better position themselves with their customers? it’s not just idea generation of topics that could be done in an open intelligence approach, topic selection could also be done this way. we can envision a delphi approach where people from outside the ci function rank the intelligence topics, thereby helping the intelligence team determine which ones are more relevant to other units of the organization and to key stakeholders. 9. collection open intelligence applied to collection is something that on the surface ci already does very well. the profession understands the importance of gathering information from broad sources both within and outside the organization. they get the need for diverse sources of information but there are a few aspects of collection that we want to bring up in the context of open intelligence. to what extent is information being entered into the intelligence system from other units of the organization (cross-pollination)? from outside the organization (external)? this is not about where information comes from but who is providing it. in an open intelligence environment, information is being directly entered into the system by stakeholders and by people in other parts of the organization. open intelligence also requires that ci practitioners extend collection sources to recognize data variety – to what extent (where relevant) is online video, social media, and so forth being integrated into intelligence efforts? how is the internet of things figuring into collection plans? imagine what could happen if organizations addressed variety, velocity and volume. this no doubt will require the use of technology but given rates of change and increased data (and data complexity) this will be needed. one thing to consider is that, in the big data world, 80% of what is available is unstructured or semistructured (text, images, and sound). therefore, some form of unstructured data technology will become important. 10. analysis the traditional view of analysis has the person responsible for intelligence applying any one of several dozen formal analytical techniques to information that has been gathered. this is a straightforward and logical process that fits with the in-house view of intelligence. we have added to this in the earlier section in mentioning some online/technological analytical tools but it’s still conceptually about the ci unit engaging in the analysis and then sending the results with recommendations off to the decision makers. a few things that we 70 have seen over the past several years have caused us to question whether this should be changed to incorporate the open intelligence approach. the first was a presentation by johan van zyl, ceo of toyota europe nv/south africa on the toyota south africa intelligence system. during the presentation, he talked about how the client for the intelligence joins with the intelligence team during the analysis phase. this provides the intelligence team with client insights and perspectives on the data. we have also seen various foresight initiatives where experts from around the world were invited to provide analytical input either as part of expert panels or in delphi approaches to help organizations make sense of complex environments. volkswagen provides a very interesting open innovation example in this respect. they set up a virtual exchange where participants from throughout the company received play money that they could “bet” on what they thought were the better ideas. whichever idea attracted the most “virtual money” on the exchange was the one selected. there are two aspects then to think about in applying an open intelligence approach to analysis. the first is who do you open the analysis process up to (i.e., who is invited in)? and the second is the kind of analytical techniques you use to integrate broader involvement. an in-house approach (like in open innovation – so call this closed) involves only having the intelligence unit doing the analysis. cross-pollination would involve allowing others inside the organization to participate in the analysis process and external would require inviting in outside experts, stakeholders and others. for cross-pollination and external initiatives, traditional analytical techniques would be combined with techniques such as delphi and expert group approaches. the foresight field has a lot of techniques that should be used that integrate broad groups in the analysis function. a final aspect of analysis that ties in with the concept of rapidity of change is the frequency of analysis. as mentioned in the collection section, organizations will need to refresh and reanalyze their data on a frequent basis. automated analytical approaches (software and other online tools) will become more important in addressing the need for more frequent data refresh rates, broader data types, and the need for more frequent analysis. 11. communication traditionally, intelligence is given to the client after being developed by the intelligence unit. there are variations in this approach with some suggesting providing the analysis but not the recommendations (the true intelligence) to other managers in the organization and in some cases making the non-sensitive information gathered for intelligence available more broadly throughout the organization. but, generally, it’s about targeted intelligence being developed and given its sensitivity being provided to those with the authority and requirement to receive it “a need to know basis only”. the open innovation groups have discussed at great length the sensitivity and concerns with sharing intellectual property more broadly than just in-house (in the r&d unit) but have generally concluded that despite the risk the potential benefits are big. similarly, for intelligence, there will have to be discussions around how broadly intelligence should be communicated. under the crosspollination approach, intelligence results could be shared with others in the organization (besides the client) but perhaps only those who have appropriate security clearance levels. under an external approach (full open intelligence) the intelligence would be shared with trusted stakeholders outside the organization. this certainly is done within the government intelligence environment (within the five eyes community for example – australia, canada, new zealand, the united kingdom and the united states) and it might make sense to share intelligence findings with key customers or suppliers to get their perspective on the intelligence. again, this fits with the integrated intelligence concept but more importantly provides an additional level of validation on intelligence results and helps provide unique perspectives on it as well. 12. ideas from analytics and it to enhance this new approach to a certain extent, the analytics field has proposed it-related solutions to address some of the problems described in this article. it systems enable organizations to expand geographies, shift time zones, and build linkages among people (e.g., collaborative groupware) that enable the rapid transfer of knowledge across boundaries (dodgson et al., 2006). while an it system enables co-creation through information flows, the data are only useful to the extent that managers can 71 generate insights that help their businesses. in a co-creation environment, different stakeholders might interpret the same data in different ways. analytic tools, such as machine learning, can help to enable consistent interpretation of data across the co-creation ecosystem the use of analytics in innovation however, is not well-understood (george & lin, 2017) and we are certainly proposing an innovative approach to competitive intelligence. nevertheless, many companies are starting to learn how best to leverage the power of these advanced technologies in generating and in implementing new ideas. george & lin (2017) provide a framework for considering the different ways in which analytics could be integrated into innovation. the aspect most relevant to open intelligence is the role of analytics as a driver of organizational transformation. as such, analytics could influence both product and process innovation by capturing and translating data more effectively to better inform transformation decisions. in terms of open innovation, its defining feature (relative to closed innovation) is the gathering and processing of data from external stakeholders. he and wang (2016) argue that social media can be used for improving interaction with a wide variety of these stakeholders. in addition, it can be employed in co-creation efforts during product development. in an analysis of it strategies and open innovation, cui et al. (2015) suggest that outbound, inbound and coupled processes involved in open innovation can be leveraged in different ways through it. whereas inbound and outbound innovation tend to involve oneway flows of information, coupled processes embrace the co-creation concept in which partners and other stakeholders are involved throughout the innovation initiative. in summary, companies can enhance the chance of open intelligence success by expanding the breadth and depth of information processing (ciu et al, 2015). information technologies can help to enable breadth in that these systems can gather and process information from a wide variety of sources. analytics, however, can help with depth, leading to insights that might not have been previously considered. 13. conclusions speed of change, needing to address international dimensions of business and information and increasing complexity of data (volume, variety, velocity and veracity) will require a rethink and possibly reconceptualization of how we develop intelligence. open intelligence, our concept which is inspired by the popular and growing field of open innovation, provides an approach for addressing this challenge. however, it will require that the competitive intelligence function opens up to others inside the organization (cross-pollination) and at the most open, from others outside the organization (the external approach). table 2 provides examples of this within planning, analysis and communication. this may make some intelligence practitioners nervous due to the potential for the intelligence to be seen by some that they do not wish to see it, but this is no worse than the potential loss of intellectual property that can arise in open innovation. yet, many of the world’s largest companies have adopted aggressive open innovation targets and established open innovation programs. it is only by harnessing the information from broader networks (open intelligence), involving a broader array of experts in analysing information (open intelligence) and sharing the intelligence with appropriate stakeholders (open intelligence) that organizations will be able to deal with the speed of change and increasing complexity of data described in this article. even planning (including intelligence topic selection) can benefit from an open intelligence approach. future competitive intelligence scholarship should look at the open intelligence concept. ci researchers should look for examples in which intelligence was developed using external networks. in this article, we have provided a few examples of where open intelligence concepts were observed (e.g., toyota south africa) but more examples should be sought out. the concept of open intelligence appears to address the challenges we have described in this article but further development and testing of the concepts is required. to paraphrase henry chesbrough, the ci unit does not have all the smart people in the world working for it, but it could. the idea in open intelligence is to get the “best minds” working for the organization’s ci program as a means for addressing today’s challenges but also to maximize the ability to identify and take advantage of opportunities. table 2 open intelligence – examples within the wheel of intelligence. traditional model – in house (ci unit) cross pollination – across the firm external planning: where the topics come from senior management driven: “what’s keeping them up at night” ci practitioner driven: “we know what’s needed” other parts bring forward and help to select the intelligence topics – they know what key issues are from their unit’s perspective key stakeholders have a unique perspective on the environment. what’s important to them? what do they need to be competitive? analysis: techniques and methods our unit knows how to make sense of the information. craig fleisher and babette bensoussan have shown us the techniques. we still need craig and babette but let’s have others from the organization help us make sense of the information. we will need group analysis approaches exchanges, delphi who are our five eyes for intelligence? let’s harness the power and insight from key customers, suppliers, other allies, experts etc. we will need group analysis approaches such as exchanges and delphi communication the intelligence is provided to the client – need to know basis the intelligence is shared with those in the organization that could provide perspective on it and are cleared to see it. the intelligence is shared with key people outside the organization that can provide perspective and we trust to see it 14. references alnoukari, m and hanano a. 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[online] foodnavigator-usa.com. available at: http://www.foodnavigatorusa.com/manufacturers/coca-cola-onthinking-like-a-start-up-open-innovation-andavoiding-kodak-moments [accessed 28 sep. 2017]. 40 the definition of competitive intelligence needs through a synthesis model vincent grèzes 1 1 university of applied sciences and arts of western switzerland, switzerland email: vincent.grezes@hevs.ch received march 12, accepted april 5 2015 abstract: based on an exhaustive literature review, this paper presents an overview of the evolution of different methods useful for defining competitive intelligence needs, where the information helps the firm to justify its strategic decisions, the analysis of the early warning topics and the elements of the competitors' environment and the actors influencing the organization or its value system, and their categorization. these findings are part of a doctoral study aiming at identifying the usefulness of data coming from open intelligence. the researcher presents, on one hand, a categorization of competitive intelligence needs, and on the other hand, a synthesis model that assists managers in defining competitive intelligence needs. it also aims to show how to foster innovation. keywords: competitive intelligence, needs definition, decision support, innovation 1. introduction competitive intelligence (ci) is about information gathering and use, looking for opportunities and threats; driven by the expression of the managers’ needs and expectations, focused on finding the information «believed to be wanted», which they «would like to have» (nicholas, d., 2000). according to larivet, s. (2009), the oldest definition of competitive intelligence (ci) is found in a publication of hans peter luhn, in 1958, where he refers to the use of information gathered through a communication system, emphasizing the «intelligence» character of the process because of its «ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal» (luhn, h.p., 1958, 314). nowadays, choo, c. (1999) classifies the various information gathering activities based on four complementary definitions: available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 1 (2015) 40-56 mailto:vincent.grezes@hevs.ch https://ojs.hh.se/ 41 competitor intelligence, defined by porter, m.e. (1982), as the activity aiming at developing «a profile of the nature and success of the likely strategy changes each competitor might make, each competitor’s probable response to the range of feasible strategic moves other firms could initiate and each competitor’s probable reaction to the array of industry changes and broader environmental shifts that might occur»; competitive intelligence, proposed by the strategic and competitive intelligence professionals (scip) as the «process of monitoring the competitive environment»; business intelligence, described by gilad and tamar (1988), as the « activity of monitoring the environment external to the firm for information that is relevant for the decisionmaking process in the company»; environmental scanning, outlined by choo, c. (1999) as follows: «environmental scanning is the acquisition and use of information about events, trends and relationships in an organization’s external environment, the knowledge of which would assist management in planning the organization’s future course of action», and «environmental scanning casts an even wider net and analyzes information about every sector of the external environment that can help management to plan for the organization's future. scanning covers not only competitors, suppliers and customers, but also includes technology, economic conditions, political and regulatory environment, and social and demographic trends». according to prescott (1999, 45-46), who refers to a 1997 study by the american productivity and quality center, ci efforts mainly focus on (1) early warnings, with the aim of identifying «the opportunities and threats in the competitive landscape», (2) «strategic decision making», (3) «tactical decision making», (4) «competitive monitoring and assessment», and (5) «assistance with the strategic planning process of the organization». therefore a central question concerns the choice of the focus, and «the types of intelligence that are most critical, both currently and in the future ». competitive intelligence concerns amongst others the identification of opportunities and threats, and then is at the starting step of a creativity and innovation process (debois et al., 2011, 44). hence, we can identify two phases during which environmental scanning takes place, namely during the project development phase, and during the conduct of the project. the need for environmental scanning is indeed recognized «at the business model elaboration stage, environmental scanning provides a precognition of the environment of the project necessary to the elaboration of strong and competitive business models (osterwalder and pigneur (2010, 14). when the business model is confronted to the market, the involvement of scanning takes on another dimension: it is the insurance of the business model’s continuity by its redesign according to the environmental changes (lequeux and saadoun, 2008)» (grèzes et al., 2012). the monitoring process, or intelligence cycle, can take different forms depending on the different authors. the environment scanning activity is based on a formalized process, which is iterative and adaptable and is called «intelligence cycle», «information cycle» or «monitoring cycle». the aim of this process is to manage the quality of the procedure by systematizing it, and to adapt it to each situation. the successive steps of this process are described by the french agency for standardization (afnor, 1998) as follows: 1) to identify and map the users of information; 2) to assess information needs; 3) to identify and evaluate sources of information; 4) to provide access to information for each user; 5) to convert the raw information into useful knowledge; 6) to capitalize knowledge. in his commented presentation of the standardization document afnor x 50-185, sutter, e. (2005, §8.2) states that «the analysis of the collected information should identify threats and opportunities for the business’ activities or market changes» (free translation). although critically discussed, this process illustrates the logic of the sequence of the environmental scanning process. even if it is, for some authors (bulinge, f., 2006), not directly transferable to the organization, this model has the advantage of providing a tool for rapid and effective understanding. a process that is able to detect the opportunities for a sustainable business model is proposed by bonazzi and grèzes (2013). this process follows the steps shown in fig. 1, and can be adapted to the general monitoring process in the following manner: (1) employees answer a series of questions concerning to the ci needs of the organization; (2) managers confirm the relevance of the questions by checking their accordance with strategic priorities; 42 (3) employees or the associated system collect the variables in open databases, perform data analysis, gather trends, and present them to the managers; (4) managers and experts gather information about trends and design new scenarios based on the detection of opportunities or threats; (5) new scenarios are tested. fig. 1: weak signal detection process, source: bonazzi and grèzes (2013) in order to define the ci needs, several methods are regrouped and compared by vuori (2006), such as questionnaires, interviews, observations, critical success factors (csfs), which are defined as «the few key areas of activity in which favorable results are absolutely necessary for a particular manager to reach his goals» (bullen, c. v., rockart, j. f., 1981), and key intelligence topics (kits), which allow the manager to focus on the strategic actions and decision of the firm, the early warning topics (competitor’s initiatives, technologic and governemental issues), and the key competitors profiles (competitors, customers, suppliers, potential partners) (herring, j. p., 1999). vuori’s findings show that questionnaires, interviews and observations are mainly affected by the skills of the researcher, wheras csfs and kits, structured to elicit critical and specific information needs, are more affected by the manager’s skills. hence, the manager’s skills are crucial in the ci needs definition process. butcher, h. (1998) identified that the major problem concerning the ci needs definition are the ignorance of the information’s availability, and the misunderstanding of its obtaining and use. moreover madinier, h. (2007) and belin et al. (2008) show that environmental scanning processes encounter implementation problems due to a lack of managers’ ability to define objectives and strategies, in order to elicit scanning axes. regarding the managers’ attitudes towards the definition of ci needs, herring (1999) recognized three types: (1) the reticent manager who has some problems expressing his needs, (2) the one who wants to know everything, but who is not able to describe his needs and believes that he will recognize the pertinent information, (3) «the manager who asks the business intelligence unit what he needs to know». regarding the needs, marti, y. v. (1996) considers three categories: (1) «information that is wanted but that is not really needed», (2) «information that lacks and that is recognized to be needed», and (3) «information that is needed but not known to be needed, nor wanted, nor asked for». this distinction is important in that it allows to distinguish between the «wanted information» as «nice-to-know» information, and the required information. one of the main problems concerning the ci process in a firm is that managers do not know what to ask their ci manager, because they sometimes seem to ignore the vectors of opportunity, threats and innovation. hence it is of utmost importance to look for methods that help managers to know about it. therefore our research question is the following: how to support the managers in the definition of their competitive intelligence needs? it is the aim of our research to propose a model that supports managers in defining their ci needs. the remainder of this article is organized as follows: the second section exposes the methodology used; after the state of the art, results are analyzed in the fourth section; a discussion on limits and further research concludes this paper. 2. methodology this research consists of a literature review and analysis based on scientific and professional literature in the fields of competitive intelligence 43 and strategic management, related to the definition of the ci needs. we synthesized the results from the literature review and produced a ci needs design model, based on a typology of the ci needs, that facilitates the identification of their types. on this basis we also deduct a ci alert matrix, or strategic matrix, which allows to link information from the outside to the inside of the firm and in order to identify opportunities and threats for an organization. the typology allows one to describe the potential collectable knowledge in a given geographical area and provides an analysis of the factors that determine the structure of production of that knowledge (doty et al., 1994). the approach we adopted to infer the theory from the analysis of the data is called «grounded theory» (strauss and corbin, 1994). 3. state of the art there are only a few studies in the existent literature that concern our research question, amongst them are müller (2004), vuori (2006) and herring (1999, 2006) which propose a method to elicit the ci needs based on questionnaires, or on a comparison of several methods. in order to enlarge our analysis of the literature on ci needs, we searched and consulted the following references in the field of competitive intelligence and strategic management: porter, m. e. (1982, 1986), ghoshal and westney (1990), bloch, a. (1999), herring, j. p. (1999), prescott, j. e. (1999), bieger, t. 2002, besson and laloum (2003), conseil régional de lorraine (2003) fleischer and bensoussan (2003), müller, m.-l. (2004), vibert, c. (2004), fleischer and bensoussan (2008), abels and klein (2008), icomtec (2010), and scip (2013). finally, the state of the art confirms the need of our research question. 4. analysis, typology and model creation the research steps were threefold: (a) analysis of the evolution of different methods useful to define ci needs based on competitive intelligence and strategic management literature, (b) analysis of the ci needs and typology, and (c) creation of a model which is a synthesis of the existing models and which serves as a support for managers to define their ci needs. a) evolution of different methods useful to define the ci needs the literature offers several approaches in order to define the ci needs of an organization. they can be defined as the categories of information, or themes, on which the company or organization must focus its environmental monitoring efforts. in the early 1980s, porter emphasized the need to establish, within the company, a competitor intelligence system. according to him «the competitive analysis aims at revealing the nature and the degree of success of strategic changes that, in all likelihood, each competitor could undertake, and the possible reactions of other firms, and their likely responses to all the industrial changes and, broader, to all the transformations in the environment that may arise» (porter, m. e. 1982, 52 – free translation). following these developments, martinet and ribault (1989) systematized the ci needs based on the model of the 5 forces of porter, me (1979, 1982), including customers, suppliers, substitute products or services, new entrants, as well as intraindustry competition (public authorities are not mentioned in the first model of porter). 44 fig. 2: the ci needs source: martinet and ribault (1989), based on the 5 forces of porter, m.e. (1979) the model proposed by martinet and ribault (1989), followed by bloch, a. (1999), has the advantage to offer a simplified view on external issues in terms of external pressure forces related to the organization. according to fleischer and bensoussan (2003, 60), this approach allows to identify opportunities and threats in the industry, by studying its participants and its characteristics. fleischer and bensoussan (2003) propose the following model by developing porter’s (1982) model of the 5 forces of porter: fig. 3: standard process of sector analysis. source: fleischer and bensoussan (2003, 67) the authors, referring to m. porter, propose to collect information on each element of the competitive environment successively: competitors, suppliers, potential entrants, substitutes, customers, consumers. bloch, a. (1999) recalls the principles proposed by porter, me (1982), which advocates, achieving a monitoring on the competitors’ value chain, in addition to the ci needs model including the 5 forces approach as presented by martinet and ribault (1989) first, then by fleischer and bensoussan (2003). 45 fig. 4: michael porter’s value chain. source: bloch, a. (1999, 21) according to porter, me (1986) the advantage of this approach based on the value chain model, is its ability to simplify the main activities (internal and external logistics, production, marketing and sales, service), and the support activities (infrastructure, human resources, technological developments, supplies) for a company or organization. this approach also allows to analyze the companies’ functioning, by employing a competitive intelligence approach, and additionally to analyze the microeconomic environment of the company. the most recent developments in modeling the business components have taken the form of business models designs. this approach, formalized by the business model canvas proposed by osterwalder and pigneur (2010) is complementary in terms of mapping and simplifying a complex reality. indeed, the authors define a business model as describing « the rationale of how an organization creates, delivers, and captures value. » the proposed framework therefore aims at helping to « describe and analyze the economic model [a] company [a] competitor or any other organization. » based on the results of a doctoral research (osterwalder, a. 2004) and tested with many companies, this framework is composed by 9 interrelated blocks: the value proposition, key activities, key resources, key partnerships, distribution channels, customer relationships, customer segments, cost structure and revenue streams 46 fig. 5: the business model canvas source: strategyzer.com based on osterwalder and pigneur (2010) moreover, and according to seddon and lewis (2003), the design of one or several business models takes part of the strategy of the organisation as an abstract tool that can be multiplied according to the different value propositions of the firm (fig. 6). fig. 6: the relationship between « business model » and « strategy » source: seddon and lewis (2003) assuming this position, synergies can be found between the business model design and the environmental scanning in order to benefit from their complementarities, as 47 much in the definition phase of the strategy of the company as during its activities. one major limitation of these approaches which aim at defining ci needs relies on the fact that they only take into account the internal factors of the company and those of its direct microeconomic environment. hence, they should be complemented with the observation of the elements emerging from the company's macro-economic environment. according to andrews, k. (1971, 59-60), «the determination of a suitable strategy for a company begins in identifying the opportunities and risks in its environment». the author states that «the environmental influences relevant to strategic decision operate in a company’s industry, the total business community, its city, its country, and the world. they are technological, economic, social, and political [...] ». in addition, andrews emphasizes the continuous nature of the monitoring, without which it «become[s] inappropriate or even obsolete». the synthesis of the microeconomic and the macroeconomic approaches has been achieved by combining the 5 forces of porter’s approach and the analysis of the environment as initiated by andrews, k. (1971). this particular model is formalized by the analysis of the 9 sector strengths proposed by fleischer and bensoussan (2008) (fig. 7). fig. 71: the 9 sector strengths. source: fleischer and bensoussan (2008) the model proposed by fleischer and bensoussan (2008) has the advantage of linking internal and microeconomic ci needs with the environment of the firm, based on a logical evolution of the model of porter, me (1979), supplemented with elements from the pestel analysis. this approach has a holistic and schematic nature, which can address part of the theoretical ci needs of the business. moreover, this model allows to consider all the elements required in the analysis of the environment proposed by the french ministry of economy, industry and employment (2009) in his guide of best practice in competitive intelligence, as well as osterwalder and pigneur (2010), which present a systematic approach to the analysis of the environment in order to support leaders in their strategic thinking. however, porter, me (1986) states that «to gain and maintain a competitive advantage, we must not only understand the value chain of the firm, but also how the company fits into the overall value system». (free translation). this value system is shown below (fig. 8). this position is also shared by andrews, k. (1971), for whom the observation of the evolution of the corporate sector and crosssector developments having an indirect link with the structure is necessary. 48 fig. 8: the value system. source: porter, m.e. (1986, 51) this system can be schematized, as in the example of porter, me (1986), by a series of activities that add new value to the same good or service. hence, this is called a chain for industrial activities. this broader flow of activities is the clustering of different value chains of suppliers and customers in an economic relationship. for example, the construction industry includes activities such as material extraction and processing, transport, several building activities, promotion, sales and management. thus, the observation of the structural changes (diversification and integration of activities) of the analyzed sectors composing the value system is likely to provide information about the potential development of the other sectors of the chain, and the chain as a whole. other value system approaches are presented, particularly in the field of tourism industry, where different types of tourist services are divided into sectors connected by a functional link through geographic and temporal elements. (leiper, n., 1979) (fig. 9) fig. 9: tourism services chain. source: adapted from bieger, t. 2002 the various activities in the chain have no direct commercial relation as in the model of porter, me (1986); however, according to leiper, n. (1979) and bieger, t. (2002), this succession of services can deliver the value expected by the tourist in a tourist destination. a change in the structure of the various activities of the value system is therefore also likely to affect other system activities. b) types of ci needs and categorization the definitions of the identified types of ci needs are summarized below. these types of ci needs cover the various strategic information needs aiming at providing the company a pertinent knowledge about the opportunities and the threats from its environment. the ci needs are distinguished according to the level of connection 49 with the organization: (a) microeconomic level ci needs, (b) macroeconomic level ci needs. 1) ci needs at the microeconomic level the ci needs at the microeconomic level concern the elements which are directly related to the organization. these are the competitive ci needs (1), the marketing ci needs (2), the partnerships ci needs, (3) the substitutes and new entrants ci needs (4), and technologic ci needs (5). these types of ci needs are particularly relevant for risk management and benchmarking, as well as in the conquest of new markets and skills acquisition. according to aguilar, m. (1992), based on a study conducted by the french government on 845 sme, information about competitors (71%) was the third largest ci need after the technology sector (75%) and the markets (82%). this study confirms the results of aguilar, fj (1967, cited by andrews, k., 1971), which stated that the information about the market, including competitive field information, dominates other categories of information search (including technological). more recently, digimind’s study (2012) revealed that 89.6% of the respondents announced that the competitive ci need is one of the key areas of business intelligence, while two thirds agree that the acquisition of talent is a less prominent concern. it should be noted that some authors include, in the competitive ci needs, all activities involving the observation of customers and suppliers (besson and laloum, 2003, rouach, d. 2005). indeed, relations with suppliers of the company, as well as with its customers, are represented by a chain of contractual relations. however, we have chosen to distinguish these different interests by basing us on the type of relationship, such as participation in the company's business (partners) or end consumers (marketing), rather than on the legal artifact used. a) ci needs about competitors competitor ci needs means the monitoring of the economic agents using simultaneously the same resources (natural, human, intellectual, etc.) and acting simultaneously on the same market. this type of intelligence focuses on all direct or indirect competitors of a project, company or organization (bourcier-desjardins et al., 1990). bloch, a. (1999) states, that this monitoring should cover the entire competitors’ value chain. these information requirements are intended to identify the advantages and disadvantages of competitors (osterwalder and pigneur, 2010) i.e. the observation of competitors' business model as a whole: competitors‘ value proposition (pricing strategies, quality, services), markets, distribution channels and key activities, key resources, physical, intellectual, human and financial resources (osterwalder and pigneur, 2010, besson and laloum, 2003), technological partnerships and their cost structure (marcon and moinet, 2011, besson and laloum, 2003). some authors emphasize that this monitoring should focus on the management choices (besson and possin, 1996, porter, me, 1982 calori and atamer, 1988) which should allow to highlight the competitors’ strategies, and thus to have a vision of the market’s direction. b) ci needs about marketing marketing ci needs focus on the observation of the opportunities and threats that may have an impact on the promotion and distribution channels, the targeted places, and the pricing strategy (besson and laloum, 2003, rouach, d. 2005). some authors insist particularly on the importance of data from the market (jakobiak, 1992), as well as customers’ follow-up, new prospects’ detection, and image among customers (marcon and moinet, 2011). according to the business model of the organization, elements relating to customer relationships and distribution channels, as well as customer segments and revenue streams, might be relevant. quantitative methods (business intelligence, investigation, etc.) and qualitative customer analysis (focus group, survey, etc.), will be advantageously coupled with sociological approach, in order to assess the acceptance of products and distribution channels by the public. risk management associated with current partners, with marketing related activity, is analyzed in terms of partnership ci needs. in the marketing field, it is important for the organization to detect trends in distribution, commercial methods, expression of new needs (marcon and moinet, 2011) and new pricing strategies. c) ci needs about partnership the partners are strategically important due to their involvement in the production of the company's value proposition, this way providing a key activity or a complementary key resource to the company. partners can also participate in the delivery of the product or service to customers, or in maintaining relationships with customers. therefore, the partnership ci needs particularly focus on suppliers, business partners, and contractors or distributors of the organization (besson and possin, 1996, bourcier-desjardins, et al., 1990, besson and laloum. 2003, rouach, d. 2005, marcon and moinet, 2011). according to 50 osterwalder and pigneur (2010) the four types of partnerships are: strategic alliances between noncompetitors, strategic partnerships among competitors, joint ventures to develop new activities, and buyer-supplier relationships. for its part, wanner, r. (2011) distinguishes partnerships depending on their purpose as pre-production, on an alliance related to a specific demand, on distribution or on marketing. the partnership ci needs have two facets. the first is based on the management of risks in relationships with existing partners (a), the second is to identify opportunities and threats related to the emergence of actors or alerts in the field of current business partners (b). a) the partnership ci needs are particularly related to limiting risks associated with agencies’ relations and information asymmetries between the partners. the bigger the value added by the partner is, the more its potential failure is likely to have important consequences for the organization. this monitoring focuses first of all on the review of the capacity of partners to fulfill their obligations to ensure their non-failure (besson and possin, 1996, besson and laloum, 2003). consequently, the ci needs also focus on actors and partners’ strategic positions and moves. for example, the vertical integration of a partner in order to strengthen his market power, or the strategic alliances with some competitors, could limit access to resources or customers (osterwalder and pigneur, 2010, porter, me, 1982, calori and atamer, 1988). b) the partnership ci needs focus also on monitoring and identifying new potential partners to optimize the processes, looking for costs reduction through the acquisition of new resources and activities, or to expand or gain a customer segment. (marcon and moinet, 2011, wanner, r. 2011) d) ci needs about new entrants and substitutes ci needs concerning potential entrants and substitutes could have potential effects at different levels of the organization. observation of new entrants and substitutes must cover the identification of actors in the different areas which are partners, marketing, technological developments and competition (porter, me, 1982, rouach, d., 2005 osterwalder and pigneur, 2010). different authors insist on substitute’s detection (rouach, d., 2005) and potential new entrants (marcon and moinet, 2011). according to porter, m. e. (1982), ci needs concerning substitutes and potential entrants are on the boundary of competitive and technological intelligence. the ci needs concerning potential entrants and substitutes focus on the identification of actors acting simultaneously on the same customer markets, offering the same products or services, meeting the same needs, or acting with the same resources as the organization. this ci needs seek to identify potential threats that arise from the emergence of new competitors or new replacement offers. the identification of new players could have an impact on the product or service, markets, distribution channels, customer relations, or on the pricing strategy. it also focuses on the opportunities associated with the implementation of new collaborations for the resources management and the achievement of key activities, as well as threats to current collaborations. it may include the identification of good practices among peers, and consider benchmarking. e) ci needs about technology technology ci needs are a special type of ci needs that has many facets: it concentrates on developments in the near and distant technological environment of the company (bourcier-desjardins et al., 1990). in terms of close technological environment, it refers to the changes in technological fields related to key activities, key resources, and the company's value proposition, but also in its distribution activities and customers’ relationship. according to rouach (2005), technology ci needs cover fundamental and applied research activities, processes and machining processes, as well as patents and standards (besson and possin, 1996). this field deals with monitoring of brands, seminars and expert publications on innovation in the sector of activity (besson and laloum, 2003). it is also necessary to focus on all relevant scientific information (scientific articles and books), technological data, research programs and development projects (jokobiak, f. 1992 marcon and moinet, 2011). 2) ci needs at the macroeconomic level the ci needs at the macroeconomic level concern the indirect environment: technology (1), policy (2), law (3), economy (4) and social issues (5). this field is of particular interest to the public service and its definition of policies and strategies, concerning the development of tools and organizational and working methods in the 51 government and the administration, in order to increase the economic performance of a nation, of a state. a) ci needs about technology according to andrews, k. (1971, 60), technological developments are the elements of the environment of the organization that may have the fastest deployment, and are likely to have the largest impact on the creation or limitation of opportunities. indirect technological environment of the company refers to the detection of technological developments which lead to a change in the general environment of the company, in his value system. referring to the work of bright, jr (1963), andrews, k. (1971, 61) identified seven major areas where progress is apparent. these are (1) the increase in transport capacity, opening new horizons in reducing costs or necessary transportation time, (2) increasing energy efficiency, changing the intensities and amounts of available energy, (3) increasing the capacity to expand and control life and associated services, such as life extension of perishable goods, control of growth of biological materials, etc. (4 ) increasing capacity to alter the characteristics of materials, providing new properties or new materials, (5) the extension of human sensory, (6) the growth of physical activities’ mechanization, in terms of production, distribution, communication and control, even for industries such as mineral extraction, (7) the growing mechanization of intellectual processes such as problem solving, processing information and process’ extension by the use of machines. b) ci needs about politics the ci needs concerning politics refer to the government stability, which is likely to affect the security and public tranquility, the fiscal policy of the country of residence or activity and the social protection measures, corruption, risk of theft by states or parallel organizations (hassid, o. 2005), legislation on intellectual property and protection of private and confidential information, measures of attracting foreign expertise and the rules of foreign trade in force in the relevant state, conditioning border flows of goods and services. (rouach, d., 2005) (andrews, k. 1971 marcon and moinet, 2011) the objective of those ci needs is to anticipate any changes in the political, legal, economic and social environment, which may influence the activity of the organization. indeed, changes in political conditions are likely to have an impact at all levels of the business model of the organization, on one or more activities of the component, and on its value system. it is related to the observation of the discussions and debates which are likely to have an effect, related to the creation of legislative rules, economic or social framing, of the activity. it is therefore an upstream monitoring, sometimes legal, sometimes economic, and sometimes social. it includes monitoring of proposed laws, parliamentary debates, and employer proposals. these elements are upstream because they do not yet constitute positive law. c) ci needs about law ci needs concerning law issues focus on the legal environment of the organization, allowing it to exert in accordance with the laws that govern its business. its purpose is also to anticipate any legislative changes that could affect the activity, including the regional and the european level e.g. that are crucial for all sectors (besson and laloum, 2003). this type of ci needs includes all legal and normative acts that affect the business, such as new legislation, laws and decrees, and the case law which has links with the organization’s activity or with an activity in the value system of the organization (besson and possin, 1996, rouach, d. 2005). it also focuses on the evolution of labor law and collective agreements governing the sector's activities, and the value system in the country or in countries where the activity is carried out, as well as subcontractors. by observing the rules governing social movements in the industry will include information on how the employees could make claims (besson and possin, 1996). d) ci needs concerning economic issues ci needs related to economics concerns information about economic and sector specific issues (rouach, d., 2005, jakobiak, f., 1992). it focuses on the observation of key players in the value system, prices and trends in the raw materials’ prices and resources of the organization, as well as the level of infrastructures such as transport, education, access to suppliers and consumers in a market. some authors include the general perception of the market, the unemployment rate and the country risk studies for countries in which the organization is active (besson and possin, 1996). andrews, k. (1971, 64) specifies that this type of ci needs must also take into account national and international trends, including the extension of the industrial revolution phenomenon to less developed countries, which are sensitive to quick changes in living standards. the author also stresses the importance of the economic policies of different states, especially in the field of customs barriers. at a more basic level, it concerns the following of the reappraisal of minimum income. 52 e) ci needs concerning social issues the ci needs concerning social issues include different factors: demographic trends in the relevant regions, changes in cultural and societal modes, as well as those related to consumer trends. social factors are indeed likely to affect directly the organization's human resources and consumer segments (rouach, d. 2005). the effects of social factors can be felt at every step of the organization's value chain likely to involve human resources, both at the organization’s level as well as at that of partners and other entities in its value system. the monitoring of sociological and environmental changes includes film critics, studies and press articles on consumer tastes, articles on fashion, leisure, and gastronomy (besson and possin, 1996), expenditure patterns (housing, health, leisure), habitat (urban, etc.) (osterwalder and pigneur, 2010). it also includes the impact of the activity on the environment, and the management of natural and technological risks, which is, according to besson and laloum (2003), more relevant in an industrial context. andrews, k. (1971) outlines five major trends in social change: (1) work mode changes and leisure, (2) minority groups looking for the recall of old grievances or for inequality, (3) change of values moving from self-interest to the good for society, (4) consideration of the environment at the expense of efficiency, (5) growing interest in education. c) a synthesized model that supports managers to define their ci needs in order to synthesize those different and complementary approaches on a microeconomic respectively a macroeconomic level, we designed the following model (fig. 10). we also take into account different sectors and industries. fig.10: model of definition of ci needs. source: author contribution the advantage of this model is to bring together internal and external elements of the organization: its business model and its value chain, microeconomic forces that can exert pressure on its business, able to support an analysis of its industry and its value system, as well as macroeconomic factors derived from the approach of andrews, k. (1971). moreover, such as andrews, k. (1971), clerc, p. (1995; cited by carayon, b., 2003), and fleischer and bensoussan (2003) recommend, monitoring activities should identify opportunities and threats by scanning the current and the potential external factors as well as the opportunities and threats related to internal components. hence, the specificity of the ci needs lies in a dual approach combining monitoring threats or risks related to the existing, and detection of opportunities and threats related to the discovery of new elements likely to influence the company or the organization. to represent this dual position of the ci needs, we designed the following matrix in order to estimate the impact of each ci need. (fig. 21) 53 fig. 11: alert matrix, or strategic matrix of ci needs. source: author contribution this matrix can be used to connect each element of the model of definition of ci needs (fig. 10), including all internal and external elements of the company or organization. with this approach, managers have the ability to estimate the impact of information related to external elements, resulting from the use of different types of ci needs, on the internal elements of the business. this strategic matrix of ci needs supports strategic thinking within the business intelligence processes in the company or organization, attributes quality to the information (opportunity or threat) and analyzes it in terms of current or potential impacts on the business model of the company or organization. to detect weak signals depending on ci needs, the following matrix (fig. 12) allows eliciting key issues, to point out the relevant topics. fig. 12: alert matrix, or strategic matrix of ci needs (extended version). source: author contribution external elements of the strategic matrix of ci needs are numbered according to the amount of identified relevant elements. this matrix is complementary to the model of definition of the ci needs (fig. 10), in order to deepen the thinking on ci needs. the use of the model of definition of the ci needs is illustrated in the following figures (fig.13-18), as a support for the presentation of the different types of ci needs. opportunité menace facteur actuel facteur potentiel axe de veille détail des éléments à surveiller o p p o rt u n it é m e n a c e o p p o rt u n it é m e n a c e o p p o rt u n it é m e n a c e o p p o rt u n it é m e n a c e fact eur act uel fact eur pot ent iel fact eur act uel fact eur pot ent iel fact eur act uel fact eur pot ent iel partenaire 1 autres facteurs externes… proposition de valeur ressources clés autres éléments internes… matrice d'alerte stratégique de veille entreprise de référence 1 concurrent 1 54 fig. 33: ci needs about competitors fig. 44: ci needs about marketing fig. 55: ci needs about partnerships fig. 16: ci needs about new entrants and substitutes fig. 17: ci needs about technology fig.18: macroeconomic ci needs fig. 13-18: source (author’s contribution) 5. conclusion based on our literature review and analysis of proposed methods able to define the ci needs, we categorized the ci needs, identified several types of ci needs at the microeconomic and at the macroeconomic levels, and synthesized a model able to support managers in the definition of their ci needs. we postulate that this approach could accompany and help managers in the definition of their ci needs. furthermore it can help them to identify opportunities and threats, as well as to foster creativity and innovation. as we were not able to test this model with a sufficient panel of managers during our current research, this will be part of our further researches. it would also be very interesting to test it with several types of organizations. 6. references abels, e. g., klein, d. p. 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(2016) competitive intelligence: a case study on qoros automotive manufacturing. journal of intelligence studies in business. 6 (2) 52-65. article url: https://ojs.hh.se/index.php/jisib/article/view/160 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive intelligence: a case study on qoros automotive manufacturing hamed ahmadiniaa and muhaimin karima aåbo akademi university, school of business and economics, turku,finland; hamed.ahmadinia@abo.fi and m.karim@abo.fi journal of intelligence studies in business please scroll down for article competitive intelligence: a case study on qoros automotive manufacturing hamed ahmadiniaa* and muhaimin karima* aåbo akademi university, school of business and economics, turku, finland *corresponding authors: hamed.ahmadinia@abo.fi and m.karim@abo.fi received 7 june 2015; accepted 8 july 2016 abstract in this paper, qoros automotive manufacturing company, which is aiming at expanding their market in europe, will be analyzed. in this case, the challenges that the aforementioned company has faced will be explained and some recommendations regarding marketing, strategy, production methods and other related issues based on competitive intelligence models like swot, porter's five forces analysis, adl matrix, and other related theories will be provided. keywords qoros automotive, competitive intelligence, market analysis 1. introduction qoros auto co., ltd. established in 2007 as a chinese automotive manufacturing company headquartered in shanghai, china. the company design and produce different cars, which specialize in international quality, design, safety, and other remarkable connected services. the company aims at hiring the most talented personnel either in the field of engineering or business to gain competitive advantages in terms of having the most creative and talented people in their production and marketing teams. (bloomberg, 2015) they are trying to offer the best products for the current markets by having such a creative team. the company has two main offices in germany and china, with their operational hub in shanghai. the company has several international partners such as bosch, microsoft, harman, and neusoftalpine. the main idea behind this is that the company is trying to have world-leading technology and use the best service companies to keep their competitive advantages in a close 1 http://www.qorosauto.com/en/company and long-term partnership with their key collaborative partners. these partnerships play a vital role for the company to be a creative, innovative and internationally recognized car factory that provides the highest quality cars and services for their customers1. in order to have a better analysis of the case, we provide more information related to the company structure in the following parts of this report. 2. brand the company sold their cars under four main brand names: chery, karry, rely, and riich2. the company embedded in their brand a changed driver progressive production method by which they try to drive the changes within an upward and progressive trend in the car industry. in the company, they share values such as that the technology that they are using in their production process must make life simpler and better for their customers. they are trying to implement the aforementioned spirit to be the first premium chinese car brand that provides the highest 2 "chery's "outstanding 4+1" pattern exhibits the "chinese power"". chery inc. 2010-04-23. journal of intelligence studies in business vol. 6, no. 2 (2016) pp. 52-65 open access: freely available at: https://ojs.hh.se/ 53 possible quality cars to make their customers feel that they are “living in a modern metropolitan lifestyle with a customer experience that goes beyond driving”3. 3. products the main products of the company could be categorized into small box-shaped passenger vans, passenger cars, and high-performance four-wheel drive cars built on a truck chassis. these cars sell under either the chery or karry brands (xing, 2002). the most significant progress in these cars, compared with other chic cars, is that the qoros 3 sedan has become the first chinese-developed car with a five-star safety rating by euro ncap, which plays a role as a key competitive advantage for the company4. moreover, the company is considered to be the largest chinese passenger car exporter and the tenth-largest chinese car manufacture, since 2003 and 2012, respectively (the global times, 2012). the assembly of the cars and their component manufacturing facilities are mainly in china and approximately fifteen other countries all around the world. moreover, the main company location has two local r & d research centers and the company allocate about 7% of their total income to the process of product development (dyer, 2006). as a significant development in their products, the company also designed and developed some hybrid and electric vehicles5. 4. technology the company uses state of the art technology introduced by microsoft to offer new stylish, safe, international quality standard cars to the global market. the company, with this collaborative production, introduced a new idea into the car manufacturing industry: the “connected car”. this term refers to using internet technology via various means such as mobile phones and tablet, so that the user has the opportunity to access different driving services6. apart from this technology they also offer a new electronic bike, known as “ebiqe”. it is an electric bike that offers several electronic facilities and applications to its 3 http://www.qorosauto.com/en/aboutqoros/brand 4 http://www.caradvice.com.au/253375/qoros-3sedan-first-five-star-euro-ncap-rated-chinesedeveloped-car/ 5 "china's fuel subsidy costs the world". reuters. 2008-06-04. rider. these facilities are available via a permanent 3g internet connection and a five inch touchscreen monitor7. the main idea behind these bikes is more than having an electronic engine; the new concept mainly targets new technologies to offer a modern navigation system and to be ready to ride in any off-road situations as well8. 5. price and sales the company considers several developments in expanding their markets in various parts of europe, to cope with the company vision and long term target of the company to be recognized as a successful brand in the car manufacturing industry. in this case, the executive director of sales, marketing and product strategy at qoros automotive co mentioned that “the value is not a matter of price, but mostly the combination of product and services in line with customer requirements” (pietro, 2014). he also argued that this value is estimated by the level of satisfaction that the company’s cars will offer to the buyers. for example, the price of their cars ranges from 22,470 to 28,900 usd for the qoros 3 city suv, and 19,000 to 27,000 usd for the qoros 3 hatch9. 6. fuel recently, most car manufacturing companies are trying to offer new cars with alternative fuel powered engines. in this case, we consider them to fall into seven engine groups: diesel, gasoline, bi-fuel-cng, bi-fuel – lpg, hybrid – gasoline, battery electric vehicles (bev) – owned batter, and bev – leased battery (valeri, and danielis, 2015). qoros auto co., like other car manufacturers, offer cars with petroleum fuel engines; however, they recently allocated considerable fund to their r & d department to develop modern hybrid and fullelectric cars. in this case a new technology called the “start-stop system or stop-start system” is used in the recent products of the company to reduce fuel consumption and emissions from gas as a new step toward the expanding process of green marketing in the company. therefore, the car automatically 6 http://blogs.microsoft.com/businessmatters/2015/03/04/automakers-innovate-connectedcars-withmicrosofts-tech/ 7 https://www.electricbike.com/qoros-ebiqe/ 8 http://www.qorosauto.com/en/newscenter/news/ article41 9 http://www.carnewschina.com/tag/qoros/ 54 shuts down and restarts the internal combustion engine, and the amount of time the engine needs to spend ready will be decreased and consequently less fuel will be consumed in general10. 7. marketing the company has different marketing strategies in different parts of the world. on one hand, the executive director of sales, marketing and product strategy at the company expressed that for european markets they promote the qoros 3 sedan, hatchback, cross and now also the suburban utility vehicle and the station wagon. furthermore, the company has a gradual marketing plans to introduce the euro 6 tgdi and diesel engines onto the market. on the other hand, the company has a special marketing plan for china. in this case, they are targeting the starting development in metropolitan areas by having special partnerships with recognized expert dealers. through this collaboration the company can provide technical support and it platforms for the management of the information from both technical and customer points of view (montagna, 2014). 8. strategy the recent marketing strategy of the company announced at the 2015 geneva international motor show indicated that “the company has a plan to export some selected models to central europe and the middle east within 12-18 months” (gedalyahu, 2015). furthermore, the company representative argued that they are going to expand their markets through a stepby-step plan. however, their current target is to expand their market thorough their sales network in china. not to be left behind, the chief executive of the company mentioned that another significant change in the long-term strategy of the company is hiring more chinese staff as local employees rather than having many costly international expert personnel who are working as catalysts to market the company’s cars (murphy, 2015). 9. after sales the company has three main after-sales support methods for their customers, as follows: 10 "chery wins three awards including "influential ev manufacturer of the year"". chery inc. 2011-12-31. archived from the original on 2 april 2012. 1. one touch system as an innovative sales services for the customers, by which they can be in touch with the car service department of the company, register for an appointment with a chosen company service center, and have all the relevant information about the car’s current situation on-screen. this system has several merits, such as time saving for servicing the car with less effort from the customer, which brings a new service experience to them. 2. the product is covered by a 36 month or 100,000 km warranty for all terms. 3. finally, the company implemented special facilities to support their customers, such as “roadside assistance,” which is available via a special phone number, 24 hours per day year-round11. 10. sustainable business model the company has an especially environmentally and user friendly business model for its productions. the main idea of the company is not only to produce a brand new car for the market, but the company also aims at producing a different one. for this, the company implemented a new approach, which should be more user-friendly for the drivers and should bring a better driving experience to them. therefore, the company developed a new digital eco-system business model for their value chain. the business model has the following benefits to the customers: 1. provides interactive information in the car without any stress for the driver. 2. expresses any relevant information to the driver through universal gestures for all critical actions that don't require looking t the screen. 3. easy access to any of the key areas in the software such as navigation and entertainment. 4. simple and contextual information (villanti, 2013). in this part of the report we discuss the european automotive market, its size, key players and current trends. it is undoubtedly 11 http://www.qorosauto.com/en/aftersalesservice/overview 55 important for qoros management to analyze the european automotive market before planning to penetrate it. this analysis will help the company to understand the industry size, key players, opportunities and the current trends in product design and customer preferences. having a proper analysis of the industry and the pocket market of slovakia will help them understand their own position. the management can then assess their strengths, weaknesses, opportunities and threats. a proper analysis of the industry and selfassessment has a better chance of producing a more appropriate business plan. 11. the european automobile market the european automobile market is the largest automobile manufacturing market in the world. the european union is the largest automobile market with an annual passenger car registration of approximately 13 million per year by its manufacturers; close to one quarter of all cars in the world are manufactured in europe. it is needless to say that the industry also experiences fierce competition in terms of sales volume, market share and profitability. the major companies also compete in terms of design, technology, co2 emissions and safety. in order to analyze this industry from qoros’s perspective we will focus on the passenger car segment and exclude commercial vehicles. the objective of this phase of the report is to have a clear understanding how promising or otherwise the market is for qoros. the european automobile industry is large and sophisticated. they boast about their cleanliness, safety and speed. the turnover generated by the automotive sector represents 6.9% of eu gdp. hence it has ripple effects throughout the economy, supporting a vast supply chain and generating an array of business services. automobile manufacturers operate some 290 vehicle assembly and production plants in 25 countries across europe. in total, 16% of worldwide passenger car registration is done in europe. however, there exists a big challenge in this particular region. unlike the us market, there has been a decline in the sales figures for a prolonged period of time. russia experienced a sales drop of 25% and the whole of the region is emerging 12 http://www.strategyand.pwc.com/perspectives/ 2015-auto-trends 13 http://drmsriram.blogspot.com/2015/02/businessspecial-2015-auto-industry.html fitfully from a six-year sales period with noticeable deterioration in performance and quality. however, on the contrary, some business analysts argue that the european automobile market still holds the potential for 6% annual growth in the passenger car segment (campestrini, & mock, 2011). however, it is evident that the market and the consumers are changing. three powerful forces driving the change are shifts in consumer demand, expanded regulatory requirement for safety and fuel economy, and expansion of the availability of data and information12. 12. shifts in consumer demand the consumers have recently shifted from being extremely loyal to the brands and have started considering them to be a transportation machine; so they are looking for more comfort, safety and sophistication in a competitive price. this might not directly affect the sales but it has an effect on the consumers’ willingness to pay. this basically indicates that the customers have become more demanding. customers are becoming more “value for money” centric, where they want additional value for the additional expenses13. 13. expanded regulatory requirements regulators are mandating the most safetyrelated facilities. for example, features in the cars, such as backup cameras are recognized as standard equipment on new models, adding further to costs. globally, the regulatory bodies have started being more concerned and are giving substantial importance to the safety and security of citizens. as a result, they are also implementing stricter road and traffic laws and they require the vehicle manufacturers to comply by producing vehicles that have technology and designs that provide enough safety. moreover, they are concentrating on co2 emissions and imposing laws that force car manufacturers to produce more environmental friendly vehicles14. 14. increasing availability of data and information availability of information is creating a big change in consumer behavior. these days, 14 http://www.chinapartsfactory.com/2015-autoindustry-trends/ 56 consumers are exposed to all sorts of information about the car, its brand, price, specifications, discounts, quality and performance. all of these factors relate to the automotive value chain and are interested in collecting more customer and car data, but uncertainty about how to use it is still considered to be a matter of doubt. these driving forces are creating an impact on the entire automobile industry. in order to manage them and satisfy both the customers and other stakeholders, it is imperative to understand how these forces are affecting the other variables of the industry (campestrini, mock 2011). 15. increased electronics and software content in the past few decades the cost of software and electronics was only 20% of the entire cost while now it has risen to 35%. now 90% of the innovations and new features are contributed by the electronic systems and new software. infotainment supplies an opportunity for oems and suppliers to differentiate their products. the latest consumer reports survey showed that infotainment equipment was the most difficult to deal with feature in 2014 for vehicles, making a proposal for a powerful upside for companies that can arrange superior systems15. the increasing popularity of infotainment and telematics is forcing the traditional oem and suppliers to change their business thinking and become more innovative and comply with the products and services of the industry’s key players. recently, developments in software are considered to be as important as hardware innovations, and global competition also emphasises nontraditional factors. ever more vital software content has also accelerated the pace of change in products and features. whereas the time frame for new vehicle launches is typically three to four years, the cycle for new software iterations, often driven by interactivity with mobile devices, is measured in months (campestrini, mock 2011). 16. product-mix changes to cope with regulatory needs regulations and laws are becoming stricter and more concerned about the environment. as a result, the governments and other regulatory bodies are creating pressure on the car 15 http://www.chinapartsfactory.com/2015-autoindustry-trends/ manufacturers to comply more with sustainability issues. in order to create a greener environment and to reduce co2 emissions, the governments are encouraging companies to manufacture hybrid and environment friendly cars. for instance, cafe standards in the united states that will go into effect in 2016 are planned to add as much as us$1,000 to the production cost of a vehicle, according to the national automobile dealers association. however, the challenge is that only a few of the automobile buyers are willing to pay more for environmentally friendly choices. thus the cost pressure is falling heavily on the omes. this, however, paves a path towards innovation. in order to make the car more fuel efficient, the companies are reducing the weight of the cars. this is dramatically evidenced by ford’s decision to allocate a considerable amount of steel with aluminum to the 2015 version of its f-150 pickup truck. 17. new developed platforms and platform modularization the pressure of consumer preferences has made car manufacturers become more responsive and flexible. in order to reduce cost and to cater to the want of segmented vehicles, the omes are adding a number of models at the same time, reducing the number of vehicle architectures and thus improving product commonality. volkswagen, gm and many other companies are increasing their number of platforms. it might initially increase the cost but the additional expense is outweighed by savings from the sharing of common components between cars and platforms, and increased volume. 18. the changing face of retail along with the core product and technologies, the sales channels are also changing. customers want a smooth purchase experience including financing, insurance and all other formalities. while most of them are interested in taking a test drive some are looking for an instant purchase from the internet. although it is an emerging sales channels, the dealers prefer a sale through a test drive. accommodating these shifting attitudes about buying a car will require equal changes to 57 dealers’ processes, including investment in new technology16. apart from these forces responsible for the above mentioned changes, some additional historic data trends might also be important for qoros in order to design strategy. in this phase we discuss the current trends in the industry and major concerns such as passenger car industry size, price, market share and major players, annual sales volume and sales trends, co2 footprint and technologies. 19. number of vehicles: after a major decline in sales in 2009, registration of passenger cars steadied in 2012 and 2013 to 12 million, which is still 20% below the volume before the economic crisis. before this crisis, the average volume hovered around 15.5 million annually. for some countries like spain and russian, the dent was even higher; 50% for spain and 25% for russia. the historic data says the market is more concentrated in a handful of countries. in total 75% of the total new car registration is taking place in germany, france, uk, italy and spain and 50% of the market is captured by the top seven brands. germany holds the title of market leader, having 25% of the total new car registration volume (campestrini, & mock, 2011). 20. fuel consumption and co2 emissions under the new eu regulations, 95% of the new vehicle fleet must comply with the 95 g/km target by 2020 (campestrini, mock 2011). 2013 was the first year in which the target of co2 emissions from passenger cars dropped to 130 g/km. from 2021, the manufacturers’ average will be monitored. in percentage term, all manufacturers are given a target of reducing co2 emission by 27% from 2015 to 2021 (campestrini, & mock, 2011). 21. technologies eu or europe is yet to gain maturity in the environmentally friendly hybrid car segment. there are significant differences among the member countries; belgium, france, and spain have diesel take-up rates of around 65%, while in the netherlands the rate is much lower, 29%. surprisingly, 53% of cars newly registered in 2013 were powered by diesel, which is quite different from the us, chinese 16 http://www.strategyand.pwc.com/perspectives/ 2015-auto-trends and japanese markets, which are dominated by gasoline powered cars. on the other hand, hybrid car registration is experiencing growth and reached a level of 1.4% in 2013. however, it is still relatively low compared to the netherlands (5.7 %) and france (2.6 %). if we look into the hybrid shares, brand wise, onefifth of all new toyota vehicles sold in the eu were hybrid-electric. plug-in hybrid (phev) and battery-electric vehicles (bev) make up about 0.4 % of vehicle registration in the eu, with notable differences among the member states. in the netherlands, a stunning 4.1 % of all new sales were phevs in 2013, and another 1.4% were bevs (campestrini, mock 2011). the underlying reason for this shift in manufacturing is directly correlated with the government imposed co2 based vehicle taxation scheme where vehicle that emit less than 50 g/km of co2 receive tax rebates. phevs and bevs accounted for 5.8 % of all new car sales in norway in 2013. and in 2014, that market share further increased to 14.6% during the first half of the year (icct, 2014d). this makes norway the world’s leading market for electric vehicles (in terms of market share, not absolute number of vehicles). underlying reasons are, again, fiscal incentives provided by the norwegian government. however, it is worth mentioning that the europe market has experienced a sharp increase in gasoline direct injection (gdi) to obtain greater efficiency and lower co2 emissions. by 2013, the share is assumed to reach 30%. the top brand of hybrid cars is toyota prius. (campestrini, & mock, 2011). ninety percent of the vehicles in eu-28 are passenger cars and largely dominated by germany, france and uk, holding 60% of all registrations of new cars. germany holds the largest market share with 25%. after a dent in sales due to a government imposed scrappage scheme, the country has remained stable at around 3 million vehicles per year. for the first time in years, vehicle sales in spain increased again in 2013. the european market is very diverse in terms of brands, with the most registered brand, vw, commanding only 13% of the market. the top-five companies dominate about 65% of the market. the vw golf remains the most popular car model in europe. it accounted for about 3.8% of all new vehicle sales in the eu in 2013. the biggest segment 58 of the market is the small and lower medium segment, comprising almost 65% of the entire industry while luxury cars are only 10% of the total. a steady hike, however, is being observed in suv and off road cars since 2009. after the crisis in 2009 where most of the brands either declined or stagnated, bmw and audi continue to have a positive upward trend. (campestrini, & mock, 2011). 22. price sales taxes in the eu are between 18% and 27%. in addition to the general tax, some member states have also introduced a special sales or registration tax for new cars. the price figures from 2001 to 2013 show that there has been a steady growth in price. the luxury brands, audi, bmw and mercedes-benz, are the most expensive brands followed by vw and ford. a positive picture is observed in the hybrid electric segment, where greener vehicles are in a declining price trend (campestrini, & mock, 2011). 23. market in slovakia slovakia is a small country in europe born in 1993. it joined the eu in 2004 and the euro area in 2009. from 2001 to 2008, the economic growth of slovakia was among the highest in the eu, heavily fueled by foreign direct investments especially in the automotive and electronic sectors. the country has cheap skilled labor with low taxes and liberal labor laws along with a favorable geographical location. the qoros management has decided to first launch their product in slovakia as a stepping stone to penetrate the european automotive market. hence, learning about the slovakian automotive market is as important as learning about the european automotive market. the slovakian market started to grow more drastically when it welcomed new plants, and production grew to over one million units. the market comprises 70% of passenger cars. the downfall in the economy has maintained the market decreased of 4.7% from 2012. skoda is the market leading brand with 19.9% market shares, followed by volkswagen at 9.7%. apart from that, the market has new entrants such as hyundai and kia, who have already managed market shares of 8.1% and 7.5% respectively17. 17 http://focus2move.com/slovakia-car-industry-2014outlook/ not only is the automotive industry growing but so is the entire economy of slovakia. the main driving forces are rebound investment and an expansion in private consumption supported by improved labor market conditions. from the end of the 1st quarter of 2015, the automotive industry in slovakia started to grow, with 11% growth from 2012. if qoros can successfully penetrate the eu market and create a strong foothold there highly depends on five major forces. how the market is behaving, how the major players are performing, how the consumers are behaving, how the regulations are changing and how qoros complies with these forces. it is of paramount importance for the qoros management to analyze the industry, its target market and its competitors to design a well thought out strategy. every activity qoros management undergoes should be backed by a well-designed strategy that address the current trends and market demands and has a solution to those18. in the following phase we will discuss is how qoros can use competitive intelligence methods and techniques to respond to the dynamic market and plan their next attempts19. 24. market in the uk another big part of the europe market is the united kingdome (uk) automotive market. of all uk suppliers, more than 70% manufacture their products in the uk. at present, about 80% of all component types required for vehicle assembly operations can be procured from uk suppliers. the uk automotive supply chain typically generates £4.8bn of added value annually. there are around 2,350 uk companies that regard themselves as ‘automotive’ suppliers, employing around 82,000 people (2009 data). (smmt, 2012). it is estimated that every job in the uk vehicle assembly supports 7.5 elsewhere in the economy. uk-based oems are actively committed to increasing local sourcing practices to support new model programs and facility expansion. the uk boasts a production of 1.6 million cars and more than 2.5 million engines yearly. 1.58 million vehicles and 2.5 million engines were produced in the uk last year, and of these, 81% of the total vehicles and 62% of engines were exported. uk automotive is an important part of the uk economy and 18 http://focus2move.com/slovakia-car-marketoutlook-at-july-2012-skoda-wins-in-a-flat-market/ 19 http://focus2move.com/slovakia-light-vehicle-sales/ 59 normally generates more than £55 billion in annual turnover, along with £12 billion in net value-added to the economy. the automotive industry is the uk’s largest sector in terms of exports by value. it generated £27 billion of revenue for the uk in 2011. on average, the sector exports to over 100 markets worldwide and accounts for around 11% of total uk exports yearly20. average new car co2 emissions fell to a new low of 133.1g/km in 2012, and have fallen by over 20% in the last 10 years. uk automotive is at the forefront of the low carbon agenda, investing in r&d and new technologies that will deliver ever cleaner, safer and more fuelefficient cars. the automotive industry is subject to numerous national, eu and global laws and regulations, including those relating to vehicle safety and environmental issues such as emissions levels, fuel economy and manufacturing practices. 25. key environmental legislation there are several recent environmental policies that are now impacting the automotive industry including: in 2009, legislation was passed that committed european car manufacturers to cut fleet average co2 emissions from new cars to 130g/km by 2015 and 95g/km by 2020. from november 1, 2011 all new types of approved vehicles were required to have electronic stability control fitted as standard and from november 1, 2014 all newly-registered vehicles must also comply. the highest selling car in the uk is nissan followed by land rover. the most popular model is ford fiesta. uk car manufacturing peaked in 1972 at 1.92 million units, and 2003 saw the highest car output in recent years, totaling 1.65 million units. although car manufacturing levels have not yet matched pre-recession levels, full year 2012 figures verify that uk car manufacturing reached its highest since 2008 and broke all-time export records21. the volume of cars export to other countries exceeded 1.2 million units, up 8% on 2011. the highest registrations of new cars are observed in west midland followed by scotland. the supermini and lower medium segments are the biggest segments, comprising 60% put together. the mini segment is led by hyundai i10 followed by volkswagen. the supermini segment is led by ford fiesta followed by 20 http://www.cordantrecruitment.com/cordantfocus/driving-the-automotive-industry volkswagen polo. the lower medium segment is led by ford focus. overall, there has been an increment in the usage of cars in the uk market. compared to 2011, 2012 experienced 0.4% more traffic on the roads on average with a maximum spike of 0.9% in the south-west region. a recent study showed 12.6% of co2 emission is caused by cars in the uk. addressing that a concern in 2011, uk vehicle manufacturers reduced energy consumption per vehicle produced by 14%. in addition to producing ever more efficient powertrains, manufacturers have designed various innovations to help drivers save fuel and lower co2 emissions. stop-start technologies automatically cut the engine when a vehicle is stationary. the engine is restarted by releasing the brake or depressing the clutch. tire pressure monitoring systems measure the pressure of each of the tires and will give a warning through the dashboard display if they become underinflated. gear shift indicators show the driver the optimum time to change gear (up and down) while driving. low rolling resistance tyres are designed to improve the fuel efficiency of a vehicle by minimizing the energy wasted when the tyre rolls down the road. the new industry tire labeling scheme indicates fuel efficiency using a rating scale from a(most efficient) to g (least efficient). the difference between an a rating and a g rating could be a reduction in fuel consumption of up to 7.5 % (smmt, 2013). 26. qoros automobileimplementing competitive intelligence model to assess: strengths, weaknesses, opportunities and threats (swot) founded in 2007, qoros automobile, the chinese car manufacturing company, has decided to penetrate and gain a foothold in the european automobile industry. it is worth mentioning that several attempts to penetrate the european market were made by different chinese car manufacturers in the past few years. however, most of them did not succeed. learning from the past, the qoros management has crafted its strategy well considering all the probable pros and cons. in this phase of the report we will make a swot analysis in order to understand the current position of the company and how it can plan to 21 http://blogs.matchtech.com/engineering/ automotive/beginners-guide-uk-automotive-industry/ 60 overcome its threats and weaknesses and capitalize its on its opportunities and strengths. this competitive intelligence method will help the company to narrow down its plans and implement appropriate business activities where necessary. 26.1 threat qoros, being a chinese brand, will experience heavy competition from the other key players in the industry. brands like volkswagen, bmw and mercedes benz have been operating in the european market from the beginning. this means the company needs to compete with the world’s greatest car manufacturers in their own market. this means the company needs to focus on product differentiation and out of the box marketing and communication plans. at the moment, the timing is not the most appropriate. the european market is experiencing a slight decline, while the chinese market is also stagnant. this might create a liquidity crisis for the company. another threat is that, making radical innovations in gasoline powered engines is not easy. this implies that the company should also concentrate on hybrid or green powered cars. 26.2 opportunity starting business in slovakia on a test basis was a smart move. this country can be quite a big market. with 324 cars for every 1000 citizens, the market has yet to grow and qoros can take the opportunity. however, it will have to face skoda, which happens to be the top choice there. the company has initiated an activation plan of describing the cars to its customers over a cup of coffee. this has somewhat positive feedback. the conversion rate of qoros is 6% to 8% while the industry average is not more than 5%. there is a market for a social car. the new customers require comfort, sophistication and digital connectivity. the qoros cars have a digital ecosystem that allows the car to connect with the owner's mobile devices via an app and features a touchscreen "infotainment" system. 26.3 strength qoros has a state of the art manufacturing facility with the capacity of making 350,000 cars. they have strong experience in this market as a player in the largest automobile market: china. they also have a sophisticated design center in munich and engineering facilities in austria. the hatchback introduced has twice the power of vw golf, the most popular brand in the eu. the sedan has a competitive price, considering the power and the features. the price is around 20k, while a car with that power usually prices around 27k. apart from that, they designed unique connectivity with an eight-inch touch screen and a cloud connected platform that enables customers to access social networks and book service appointments. qoros has integrated leading talent around the world across all engineering, commercial business functions and at all levels of management. the management team has been crowned by various automobile business experts and veterans working for long periods in organizations such as volkswagen, bmw and mercedes benz. the company has already achieved a 5 star score in the euro ncap safety testing in 2013, which marks the first time for any chinese brand to gain this ranking. they have also received the red dot design honor award. this means the cars and the brand are in the process of gaining more acceptability and credibility for their end users. unlike other chinese companies, qoros is a venture between israel’s richest man and the state owned chinese automaker cherry automobile. it has advanced and modular architecture to enable the rapid development of a full range of new models and variants and to allow for the adoption of hybrid technologies. it is supported by major global suppliers including magna steyr, trw, continental, bosch, valeo, microsoft and icon mobile. 26.4 weaknesses qoros could not make online purchases easy. it is rather complex and not user friendly. this is due to too much emphasis on engineering, and less effort in business and brand building. this refers to the fact that the company made less effort in marketing and communications. the biggest weakness that qoros will face in the european market is the deeply rooted social stigma against a “chinese brand”. this reflects the lack of trust and confidence in the brand, and thus the core product itself. after a detailed analysis of the company, its desired market and its assessment, we will now 61 discuss how we can use competitive intelligence and its various methodologies to create a dynamic strategy for qoros. in this part of the report we will discuss a few competitive intelligence techniques that the management of qoros could use to analyze the industry structure and competitiveness, customer intelligence, growth path analysis and competitive strategy exploration. 27. industry structure and competitiveness 27.1 adl matrix this analysis helps one understand how an industry’s maturity and competitive position affect strategy. it compares two axes: industry maturity (ranging from embryonic, growing, mature, to aging) and competitive position (from dominant to weak). from the discussion of the european automotive market and slovakian automotive market we can conclude that while the eu market has reached maturity, slovakia is still in the growth stage. on the other hand, with the swot analysis, we can state that in this particular situation qoros is in a favorable position in slovakia but in a tenable position in the eu market. there are a number of challenges due to the social stigma against a chinese brand but it has got an outstanding product portfolio with a five star rating and a very positive conversion rate. according to the adl matrix, the management will have to consider the european market and the slovakian market separately. slovakia is a growing market (324 vehicle for every 1000 citizens) and qoros has a favorable position, the management will have to concentrate on an attempt to improve its position and push for a market share. in order to improve its position in the market, the management will have to craft outstanding marketing and communication strategy. the aim of these activities will mostly include attempts to reduce the social stigma against chinese brands and highlight the five star rating to increase credibility and trust. they would have to remember that qoros will be facing skoda, which has been the favorite brand for a long time with an enviable market share. in order to acquire a market share, it is important to have some similarities and some points of differences with skoda. the parameters could be price, design or more infotainment and electronic features. going for hybrid cars in this market might not be the smartest step at the moment. although there is an opportunity, the market may get price sensitive when it comes to hybrid vehicles. on the other hand, the eu market, being a mature one and qoros being in a tenable position, the management must act a bit less aggressive. the company must gradually build its brand image, slowly and steadily. the best choice at the beginning might be to create a comparatively smaller niche and build the trust of that group. this would disseminate positive word of mouth, which would complement the international ranking scores they are awarded. repeated communication about credibility and quality can help build up the trust of the end users, which might mitigate the negative social stigma. 27.2 porter's five forces analysis: we also analyzed the case via porter’s five forces as a conceptual framework, which will examine the level of competition within the industry. in the following part of this essay, the position of the company compared to its competitors via porter's five forces theory is analyzed: 1. buyer power: as statistics show, for example, in china the company could sell only 7,000 models while the total number of sold cars in the same year exceeded 19 million units (fusheng, 2015); it is strongly suggested to the company to allocate considerable funds to increase their production rate per year. therefore, they will be able to draw more customers to their products. however, the company must keep the price of production as low as possible, compared to other manufactures in the luxury car market to have the competitive advantages as to the highest cost for buyers to switch from their products to those of the others providers. moreover, eventually the company will be able to increase the number of cars sold per year. in this case, the company will be able to cope with the market demands in terms of their state of the art cars. 2. supplier power: the main car manufactures operating in the european market that provide competition are volkswagen, bmw and mercedes benz. in this case, the company needs to provide specific cars 62 with state of the art facilities to cope with the market demands in this really competitive market (lanza, 2014). also, it is suggested to the company to allocate considerable finds to expand its public advertising and special plans for marketing its products. not to be left behind, as a chinese firm the company should focus on both the quality and cost of production to gain and keep its position in the market as a brand new international car manufacturer. in this case, the company can achieve a competitive advantage over these main suppliers by focusing their strength and control over businesses through high tech cars as well as the lowest cost of production. finally, the cost of switching from one car manufacturer to another one for the customers will be really competitive for the company. 3. industrial rivalry: there is a significant rivalry among the company’s cars and the other car manufactures in terms of price and productivity. for instance, qoros 3 hatchback will compete directly with vw’s golf, while the sedan takes on the german automaker’s jetta (tschampa, 2014). in this case, it is strongly suggested to the company to focus more on expanding their products and state of art facilities in daily operations by hiring the most talented staff. therefore, as the company has many competitors that offer equally attractive products and services, keeping an upward trend in product quality and facilitating the latest technology will bring them more competitive power compared to their competitors. this is because suppliers and buyers will go somewhere else if they don't get a good deal from the company. on the other hand, if none of the other companies can provide the same quality cars as the company is providing, then the company can have enormous strength in the market. 4. threat of substitution: as is mentioned in the “industrial rivalry” section, the company must put more emphasis on their production technology and their products’ state of the art technology, as well as productivity and user friendliness of their cars. in this case, the company can have the merit of making it hard for their customers to find an equal substitution for their cars in terms of productivity and user friendliness. for instance, it is expected that average fuel economy (cafe) standards will be 54.5 miles per gallon (23.2 kilometers per liter) by 2025. fuel economy is about maximizing the number of miles your vehicle can travel on a gallon of fuel. the cost of fuel has a major impact on fuel economy. consequently, it is really important for the company to work on expanding such technologies in their production line. in this case if they can make the substitution for their cars easily possible, then this will be a big strong point for the company. 5. threat of new entry: by using some local raw materials provided in china (as a country full of natural and human resources needed in car production) the company would make a big challenge for a new entry into the car industry. also, it is really good practice if the company focuses more on the chinese’s market which has a really big market of approximately 1.3 billion consumers, which could impact the biggest manufacturers and retailers in the world. furthermore, china’s huge population would bring a strong competitive advantage for the company against the most dominant players in the outsourcing industry (evans, 2014). 28. customer intelligence 28.1 journey map “customer journey maps allow you to walk in your customers’ shoes by traveling with them as they interact with your company. when based on sound research, they provide an accurate outside-in view, focusing on desired outcomes from the customer’s perspective. you’ll see what customer needs are at each interaction, how well you meet them, and where opportunities for improvement lay. with this understanding, these are 10 points any company contemplating, planning, or already undertaking a customer journey mapping initiative should consider: • “be clear on what you want to accomplish: having a precise strategy. 63 • “know whose journey you are mapping: being more customer centric and using their point of view. • “talk to your people: gather information about customers from the front end employees. • “talk to your customers: clear, transparent and frequent interaction with customers and potential customers. • “must-haves: the most important matter in this process; understanding what the need of the customer is. what are the “must have” attributes they are looking for? • “nice-to-haves: this part discusses the wants of the customers. how they think and feel and what are the features they consider to be “nice to have” and are willing to pay for. • “the importance of design: this is a customer analysis tool to gather information and turn it into intelligence. so designing this entire process to be simple and easy to understand is very important. this will ensure more qualitative data, which can be very vital in product designing. • “socialize and share: this study needs to be communicated throughout the organization with a pivotal aim. first, all employees must have a clear idea about the target customers and what they want and need. second, it will keep all the employees on the same page when giving the customers any service. this helps an organization to be more customer centric and responsive. • “take action: this is not a customer entertainment tool. so after proper analysis, actions should be taken in order to fill the gaps and implement improvements where necessary. • “avoid analysis paralysis: too much analysis not only wastes time but can also dilute the aim of the study and can shift the focus. the aim of this too is to find out what’s most important to them–bringing the data (and your customers) “to life” as they pursue their 22 http://www.mcorpcx.com/customer-journeymapping-10-tips-for-beginners/ goals. hence it will have to be quick and simple yet effective”22 the reason this competitive intelligence method will be instrumental for the qoros management is that, as a new entrant in the market, it is imperative for them to understand the core customers’ needs and wants. without a thorough knowledge of customer preferences, this company can never achieve its goals. 29. competitive strategy exploration 29.1 innovation ambition matrix the innovation matrix in competitive intelligence is often called an ansoff matrix23. this model helps an organization to understand where to compete and how to compete. this model consists of three innovation horizons and three levels of ambition. in this matrix, when the organization is operating in an existing market with its existing products the strategies can be a line extension or optimization of the existing products. this strategy can be useful for qoros while maintaining business in china. china is the largest automotive market and qoros can concentrate more on optimizing its existing brands/products by introducing new series of its existing models of the hatch back and the sedan. they might also consider revitalizing the market of the electronic bike they manufacture. the second horizon consist of an adjacent market with existing business. this is qoros in slovakia. since it is a new market and there are opportunities to grow, the management will have to consider expanding with their existing brands. here more focus is needed in marketing and communication in order to create awareness and buzz. however, qoros’s long term plan is to enter the european automotive market, which is a new one for the organization. this market has strong players, hence there will be entry barriers. in order to overcome these hurdles, the company will have to develop breakthroughs. the management will have to consider that this market is not necessarily price sensitive, so low pricing might not help and will rather damage the brand image. in this case they will have to add features to their 23 http://www.strategyhub.net/2012/05/ framework-of-week-81-innovation.html 64 products, which will be unique and at the same time they will have to be competitive in price. along with this, proper communication about the brand, its safety and its features should be continuously communicated through proper channels. 30. conclusion from the overall discussion we can observe qoros is planning to penetrate the biggest automotive region in the world that has fierce competition amongst famous brands like volkswagen, bmw, ford and mercedes benz. the market overall is huge, hence it still has the opportunity to grow (6% annually) in the passenger car segment. it is not price sensitive but it has a very demanding customer pool. moreover, the regulatory bodies are concerned about sustainability and instructing the omes to manufacture more environmentally friendly automobiles with lower weight, higher mileage and lower co2 emissions. on the other hand, qoros, being a chinese brand, will have to penetrate the market while facing the challenge of a negative social stigma. moreover, the structure of the uk automotive market is completely similar to the european automotive market. therefore, the company can use the same strategy for the european car market. not to be left behind, the consumer base might be totally different from the uk market and that might be considered to be a powerful factor in changing its marketing and communicational strategy of the company. the customer engagement plans need to be changed accordingly. therefore, the company’s management team might keep the penetration strategy unchanged, but customer engagement and communication will have to be tailored. in this case, managing the social stigma against chinese brands might be even higher, as this is mainly due to the fact that people from the uk tends to have a strong preference for products made in their country or region and are less open to brands from other countries. in order to enter this market and have a strong foothold, the company needs to develop a precise and sustainable business plan. they have shown sensibility by starting with a smaller market where opportunity exists. this will help them create a niche and create awareness. qoros management should analyze both the eu and the slovakian markets very carefully. learning from slovakia will help it to be more effective and smart in the eu market. the company should also analyze the end consumer and should add features to its products that will give them a new experience. the idea of the café was brilliant and can have a positive outcome since vehicles are high involvement products. so, along with improvements in technology and design, the company should also engage different regulatory authorities to test their quality and safety levels. later these testimonies will be instrumental for building trust in the consumer’s mind. regular communication of the brand would mitigate the bad reputation of a “chinese brand”. these strategies might not get them an immediate piece of the market share but they can create a niche market and qoros can then capitalize on that. 31. references "geely aims to become china's largest auto exporter". the global times. april 9, 2012. retrieved july 19, 2012 campestrini, m. & mock, p. 2011, "european vehicle market statistics", international council on clean transportation. evans, michael, 2014. “manufacturing in china can give your business the competitive advantage”, forbes, 2/07/2014: http://www.forbes.com/sites/ptc/2014/02/05/on -shoring-canbring-competitive-advantagefor-manufacturers/. fusheng, li, 2015. ”qoros seeks new strategy amid poor performance”, china daily, 201504-27 07:58:23: http://www.chinadaily.com.cn/cndy/2015 04/27/content_20547586.htm gedalyahu, ben, 2015, “qoros changes marketing strategy: idan offer’s joint car venture plans exports "to central europe and the middle east.”, globes, 04/03/2015, 17:29. 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(2018) business intelligence through patent filings: an analysis of ip management strategies of ict companies. journal of intelligence studies in business. 8 (2) 62-76. article url: https://ojs.hh.se/index.php/jisib/article/view/310 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index business intelligence through patent filings: an analysis of ip management strategies of ict companies shabib-ahmed shaikha,b and tarun kumar singhalc,* asymbiosis international university (siu), lavale, mulshi taluka, pune, maharashtra, india; bcsir-urdip, pune, maharashtra, india; cit management, symbiosis centre for management studies, noida, up, india; *tarun.singhal@sitm.ac.in journal of intelligence studies in business please scroll down for article business intelligence through patent filings: an analysis of ip management strategies of ict companies shabib-ahmed shaikha,b and tarun kumar singhalc* a symbiosis international university (siu), lavale, mulshi taluka, pune, maharashtra, india b csir-urdip, pune, maharashtra, india c it management, symbiosis centre for management studies, noida, up, india corresponding author (*): tarun.singhal@sitm.ac.in received 29 august 2017 accepted 21 august 2018 abstract business intelligence enables enterprises to make effective and good quality business decisions. in the knowledge economy, patents are seen as strategic assets for companies as they provide a competitive advantage and at the same time ensure the freedom to operate and form the basis for new alliances. publication or disclosure of intellectual property (ip) strategy based on patent filings is rarely available in the public domain. because of this, the only way to understand ip strategy is to look at patent filings, analyze them and, based on the trends, deduce strategy. this paper tries to uncover ip strategies of five us and indian it companies by analyzing their patent filings. gathering business intelligence via means of patent analytics can be used to understand the strategies used by companies in advocating their patent portfolio and aligning their business needs with patenting activities. this study reveals that the indian companies are far behind in protecting their ips, although they are now on course correction and have started aggressively protecting their inventions. it is also observed that the rival companies in the study are not directly competing with each other in the same technological domain. different patent filing strategies are used by firms to gain a competitive advantage. companies make use of disclosure as strategy or try to cover many aspects of a technology in a single patent, thereby signaling their dominance in a technological area and at the same time as they add information. keywords business intelligence, competitive intelligence, intellectual property, ipr, ip strategy, patent analytics, software patents 1. introduction business intelligence helps enterprise users make effective and high quality business decisions. it includes multiple applications, tools and technologies for information gathering, accessing, and analyzing involving all factors that affects a business (rajan, 2009). howard dressner, an analyst at the gartner group, first coined the term business intelligence in the early 1990s. business intelligence has become the art of sifting through large amounts of data, extracting pertinent information, and turning that information into knowledge upon which timely actions can be taken. all successful enterprises have made use of business intelligence for their business (chaudhuri, 2011). as per ranjan (2009), business intelligence reveals: •the position of the firm relative to its competitors journal of intelligence studies in business vol. 8, no. 2 (2018) pp. 62-76 open access: freely available at: https://ojs.hh.se/ 63 •changes in customer behavior and spending patterns •the capabilities of the firm •market conditions, future trends, demographic and economic information •the social, regulatory, and political environment •what the other firms in the market are doing business intelligence as a strategic framework is becoming increasingly important in strategic management and in supporting business strategies (alnoukari and hananao 2017). alignment between business and business intelligence strategies can be a powerful enabler of business strategy, including new business models that bring about organizational transformation (watson & wixom, 2007). business intelligence using tacit knowledge can lead to intellectual capital including patents (sveiby, 1997 ; herschel & jones, 2005). the it industry has grown rapidly since the 1960s, starting in the usa and has slowly become global (cameron et al., 2006). information and communication technology (ict) innovations are usually incremental, fast changing and having a short lifecycle (shaikh & londhe, 2016). firms investing in this continuously evolving technology expect quick returns for their investments by means of some protection. intellectual property rights (ipr) are the rights given to persons over the creations of their intellect. the framework of ipr offers a wide range of protections such as patents, trademarks, copyright, design registrations, trade secrets, anti-competitive practices in contractual licenses, protection of new plant varieties and data protection. a patent offers the strongest protection within the framework of ipr. it is a form of intellectual property granted by the government in order to secure legal protection for inventions by means of exclusive rights for a limited period in exchange for the public disclosure of an invention. patents are also important for trade and industry worldwide as they attract foreign investment and rapid technology transfer (oecd, 2004). patents also promote innovation by disclosing an invention in the public domain (moser, 2005; walaski, 2004). patenting decisions are seen as important strategic considerations since gaining maximum value from a patent depends on the individual firm’s ability to enforce the patent (arrow, 1962 ; dornelles, 2016). patents are a major source of information and when properly processed and analyzed, can yield a wealth of information on competitors’ activities, r&d trends, emerging fields, and collaborations. taking into account the filing practices (for example, broad or specific applications, filing routes, and territorial protection sought) associated with specific companies or domains, the analysis of patent portfolios can give a reasonably accurate idea of the volume of the activity in specific research areas, reveal underlying trends, detect emerging or hidden information or deviations from expected patterns, and more. patent analysis can also yield a wealth of information related to research activity, collaborations, location of research work, key inventors and licensing (grandjean et.al., 2005). strategic ip management can be offensive or defensive resulting in the formulation and execution of strategies related to technological ip, including issues such as how to acquire, create, govern, exploit and extract value from patents. patents can also be used to understand technology and competitor intelligence (holgersson 2012; krig & sandra, 2017). patenting usually has strong business corelations (pargaonkar, 2016). in the present study, patent filing data of selected ict companies are used as a source of information for competitive/business intelligence to highlight the intellectual property (ip) management strategies of ict companies. patent landscape and the accompanying ip competitive intelligence involves understanding and anticipating the competitive environment within which a company operates. more specifically, ip competitive intelligence highlights emerging ip risks, provides patent portfolio benchmarking, monitors competitor technology development efforts, and predicts commercialization of technology (pargaonkar, 2016). the main objective of ip competitive intelligence is to create value for competitive advantage. ip competitive intelligence improves decision quality and enables ip strategies by defining the relative competitive position. ip strategy becomes important when firms differentiate themselves using technology. in such cases, ip competitive intelligence analysis plays an important role for defining, creating and sustaining a winning ip strategy. ip competitive intelligence enables value creation and strengthens multiple 64 aspects of an effective ip strategy (pargaonkar, 2016). considering the above, there is a need to understand the various motives of firms to patent. 2. literature review various studies have been carried out in the field of competitive intelligence, business intelligence, their advantages to business in taking timely decisions, as well as the use of patent data for carrying out business intelligence for competitive advantage. hughes (2017) reports that due to the high volume and speed of scientific research, it is impossible to collect, update and analyze the variables that impact the evolution of technologies as disruptive innovations need knowledge from adjacent technologies as well. hughes (2017) proposes a model featuring expanded search depth, breadth and speed along with inputs from internal and external experts for identifying emerging technologies by coupling big data analytics machine learning with technology sequence analysis. on the other hand, gauzelin and bentz (2017) report on how small and medium-sized enterprises (smes) perceive and make use of business intelligence in decision making and highlight that business intelligence systems are perceived as a solution to various unforeseen disruptive events that hit the businesses unexpectedly. they report that assessing the success of business intelligence is not easy as they cover the entire organizations and their benefits are long term. smes lack business intelligence implementation due to a lack of financial and expertise capacity to implement it. however, small businesses deal with increasing volumes of data, hence making the appropriate choice of the best business intelligence in line with their strategy will allow them to have a competitive advantage. collecting and analyzing data on business intelligence from smes, gauzelin and bentz (2017) report that business intelligence and its use have a far-reaching impact on the operation of smes. søilen (2017), highlights the importance of competitive intelligence and market intelligence through a case study of two swedish mncs and reports that companies would succeed only if the competitive intelligence model, along with the specialist’s role, are properly defined in bringing out and reporting facts instead of pleasing their seniors. søilen (2017) also highlights that the expectations from the analysts is predicting the future, which at times is difficult. the analysts often also end up performing different tasks aside from analysis. with the increase in data and its low cost, competitive intelligence is largely defined by how well companies can draw conclusions from it, as the outcome is mainly dependent on the quality of data available and, at times of crisis, the demand for intelligence is the greatest. business intelligence can be viewed as a broader tool that includes knowledge management, enterprise resource planning, decision support systems and data mining (gangadharan and swamy, 2004). business intelligence is also referred to as competitive intelligence, market intelligence, customer intelligence, competitor intelligence, strategic intelligence or technical intelligence (lönnqvist and pirttimäki, 2006; deshpande et.al, 2016). scholars have define business intelligence as the process of collecting large amounts of heterogeneous data from multiple sources, analyzing that data using advanced analytical tools and methods, and quickly presenting a high-level set of reports to multiple users that condense the essence of that data into the basis of business actions, enabling management to make efficient and effective strategic business decisions that can help organizations to survive and thrive in the global economy (stackowiak et al., 2007; zeng et al., 2006; ranjan, 2009). the main challenge in any business intelligence solution is in its intelligence ability (alnoukari and hananao, 2017). business intelligence or competitive intelligence is considered to be an interdisciplinary field (walker, 1994). studies have suggested that competitive intelligence is associated with strategic management as well as knowledge management (gabriel and adiele, 2012; calof and viviers 2001) and intelligence has evolved as a discipline over time (hoppe, 2015). knowledge management can be perceived as an integral component of business intelligence (herschel & jones, 2005). it is usually defined in reference to collaboration, content management, organizational behavioral science, and technologies. knowledge management is a systematic process of finding, selecting, organizing, distilling and presenting information in a way that improves an employee’s comprehension in a specific area of interest (herschel & jones, 2005). it can be seen as consistent with resource-based theories of the firm, such as building and competing in a capability that could be quite difficult for 65 others to imitate practically. knowledge management was seen to be central to product and process innovation and improvement, to executive decision-making, and to organizational adaptation and renewal (earl, 2001). specific knowledge management activities help focus the organization on acquiring, storing and utilizing knowledge for such things as problem solving, dynamic learning, strategic planning and decision making. alnoukari and hananao (2017) report that the integration of business intelligence and corporate strategic management has a direct impact on modern and flexible organizations, which leads to a gain of competitive advantages as well as easier adatation to changing scenarios and corporate strategies. the core advantage of any competitive intelligence system is to extract the knowledge needed about competitors’ opportunities and threats (alnoukari and hananao, 2017). competitive intelligence ensures a firm’s competitiveness in the marketplace through a greater understanding of competitors and the overall competitive environment (solomon, 2004). competitive intelligence and market intelligence can also be built on competitors and influencers from exhibits and tradeshows (solberg-søilen, 2010). intellectual property assets are becoming increasingly important drivers of competitive advantage. this has forced organizations to effectively and efficiently mine their ip for business intelligence. studies suggest that patent data is also a valuable source of competitive intelligence from which to derive a strategic advantage (rouach and santi, 2001; dou et al., 2005; grandjean et al., 2005; shih et al., 2010; deshpande et.al, 2016). stern (2005) highlights that for creating competitive advantage, management must focus on exploiting ip during a product’s lifecycle, which would encompass resource management and ip strategy. ip protection is a strategy that helps in formulating new strategies for protection of innovations and sustainable development. patent data, its legal status and litigation data can be used for business intelligence purposes such as ip portfolio valuation, patent valuation, identification of competitors and their r&d efforts, assessment of active researchers in a particular field, assessment of patent quality, research quality, market trends, discover human capital, and to anticipate product launches (sagacious research, 2017). patent analysis enables firms to make more informed decisions about their ip strategy and create value for their business (great dome associates, 2018). analysis of patent data accelerates innovation, saving time and money (cubicibuc, 2017). a patent portfolio can be analyzed by carrying out patent landscaping (tekic, 2014). intellectual property landscaping is a strategic tool providing valuable business intelligence to ensure maximum understanding of the potential opportunities and competitive threats (hee.org, 2018). patent landscaping provides insights which guide business strategies that include cost optimization, enforcement, licensing, r&d and mergers and acquisitions. patent landscaping supports business strategies that help in the development of a quality patent portfolio, which in turn generates revenue and mitigates risk (ip.com, 2017). ip strategy as a subset of the business strategy requires analysis of a firm’s own inventive capabilities along with the ip landscape (barrett,2005). a patent landscape can give a new perspective on a market by illustrating the players, their technologies and their filing history and behaviors over time. a comprehensive landscape informs companies about the strength of their ip and how it compares to other companies operating in the same market. looking at ip in a broad perspective and applying business intelligence provides decision makers with actionable insights and a clear view of potential outcomes for various strategies (clearviewip, 2017). business intelligence is a systematic way of gathering data, analyzing and utilizing the same while making decisions in expanding, launching a new product, while carrying out mergers and acquisitions or for implementation of corporate strategies. business intelligence from intellectual property rights helps organizations to follow a proactive approach (siddhast.com). it provides information that will allow organizations to predict the behavior of their competitors, suppliers, customers, technologies, acquisitions, markets, products and services, and the general business environment with a degree of certainty (vedder et al., 1999; jourdan et al., 2008) stern (2005) reports that managing ip as a strategic driver helps businesses become market leaders, align their business strategy with product ip strategy and protect their technology via means of maintaining a product monopoly. this provides a competitive 66 advantage, thereby encouraging and defining measures for ip evolution and exploitation. wang (2011) highlights how patent intelligence can be used to make an intellectual property strategy. citing various researchers, wang (2011) reports that patent data can be used in core areas of technology management. jürgensa and solanab (2016) provide insights on the use of patent information for technology watch activities, classifying patent indicators for performance, technology, patent value and collaboration indicators. they report that to gain insights and competitive advantage in a specific technical domain, patent intelligence is used, which is also referred to as technology watch, technology intelligence or technology monitoring. this is a subdomain of competitive intelligence, a methodology for gathering analyzing and managing external information that can affect the organizations plans, decisions and operations. citing various researchers jürgensa and solanab (2016), report that competitive intelligence through patent data allows one to measure current technical competitiveness and forecast technological trends in specific sectors. highlighting a case study of the nanotechnology industry in spain, jürgensa and solanab (2016) report that statistical analysis of patent information and its visualization is a powerful and successful way to gain insights into a technology that can be further used to monitor and evaluate technology activities. patents encourage and promote innovation by the disclosure of a technology in the public domain (moser, 2005; walaski, 2004). patents also promote technology transfers and cross licensing. it is reported that countries that support stronger patent protection laws are much preferred destinations for foreign investments, new innovations and technology advancements (goswami & yadav, 2010; mcgowan et al., 2007). patenting does not always lead to a monopoly in pricing as it helps recover the r&d investment cost (spinello, 2007) and hence the ip law allows the developer to profit from their creation (mcgowan, stephens & gruber 2007). increased incentives for patents have pushed firms towards “patent thickets” (cockburn and macgarvie, 2011). patent thickets constitute a potentially imposing obstacle and do not allow freedom to operate for other businesses (clarkson & dekorte, 2006). patent flooding and thickets have been used as anticompetitive tools to lock out competitors, especially in fast moving technological markets (weatherall et al., 2013). the higher number of patent applications by firms also increases transactional costs and thereby opens the doors for strategic collaboration for patent pooling and cross-licensing so that the negative effects of patent thickets can be reduced (zekos, 2006; cockburn & macgarvie, 2011). patent laws have been interpreted over time to provide protection to the desired licensee. even unwilling infringements by means of ignorance are not an excuse to avoid prosecution (biles & mann, 1992). patent trolls have made an impact on business and innovation in the ict sector. trolls are becoming professional patent exploiters that have high quality technological patents (pohlmann & opitz, 2013). the trolls’ blackmailing tactics can have adverse effects on the whole industry, which in turn may slow down innovation processes (pohlmann & opitz, 2013). bessen & hunt (2007) have warned that strategic patenting by non-r&d firms may pressurize firms to engage in a patent “arms race.” however, useche (2015) reports that a high number of patents reduces the risk of failure and acquisition, while quality increases their attractiveness as an acquisition target. patents may give a firm an upper hand and a competitively advantageous position, thereby adversely affecting the competitor firms’ market values (chung et. al, 2016). large companies see iprs as incentives to compete in ipr portfolios and patents as strategic assets to protect from competition, give design freedom, offer complementary protection and form a basis for new alliances. at the same time, smes see iprs as restrictions and market barriers and they need to build their own ipr portfolio to make themselves more credible players in the market (välimäki, 2001). one strategy followed by successful chinese multinationals was to skip filling in the domestic market and go directly to developed countries by collaborating with the world’s major companies, pointing out that high application does not result in profit (nakai & tanaka, 2010). companies strongly involved in collaborating with customers that are experienced using patents are more inclined to use patents (blind, 2007). among the many strategies used by companies, technology disclosures can be a rational offensive strategy to make its presence felt in a particular technological domain (baker & mezzetti 2005). this helps to make the patent office aware of its availability of 67 potential prior art. this is done intentionally to create prior art that might stop rivals from patenting and making it more difficult to patent, hence extending the patent race through disclosure. disclosing the intermediate results in a multi-stage patent context signals a firms’ commitment to a research project, which may induce the rival to exit the competition or provide its followers ground to work ahead on the technology, depending on the knowledge spill over (gill 2008). this at times leads to future acquisition or collaboration with its followers and at the same time prevents its competitors from working in the same domain. open source software (oss) is attracting increasing commercial interest among firms as they take royalties over patented technologies of products and services sold as top-ups for oss products (fosfuri et al., 2008; wen et. al., 2015). firms with software patents highjack an oss project and direct its development in a particularly favorable direction by threatening or exercising enforcement rights. fosfuri et al. (2008) also states that patenting by firms that support oss can also be for defensive purposes, thereby supporting their defensive strategies. firms with large stocks of software patents or with large stocks of hardware trademarks are more likely to release oss products (fosfuri et al., 2008). red hat is making a profit from the sales, service and support of linux even though linux is open source (mcgowan et al., 2007). it is seen that red hat has patent filings to protect its commercial interests (shaikh & londhe, 2016). firms patent not only to prevent imitation, but also to obtain bargaining power and improve their corporate image, to freely operate in the market, to extract value of their patents through licensing and royalties, to collaborate with technology leaders and to seek a competitive advantage. to strengthen a firm’s technological leadership and to protect its innovation, patents serve as influential instruments of corporate strategy and have become an important source of competitive advantage (grindley & teece, 1997; sullivan, 2001; holgersson, 2012). studies have pointed out the need for integrating and aligning patent strategy with a firm’s business and technology strategy to generate valuable returns (alexy et al., 2009; granstrand, 2000; smith & hansen, 2002; reitzig, 2004; davoudi et.al., 2018; lynskey 2009; holgersson & grandstrand, 2017). the software market was born in the us and it still acts as a trendsetter for software patenting by opening its doors to software and business method patents (cameron et al., 2006). other countries are following the us to protect the interest of their researchers, as the failure to protect might affect a company’s ability to operate freely at the basic level in the global market (clarkson & dekorte, 2006), which in turn would threaten their own existence (dedrick & kraemer, 1993; jyoti et al., 2010). the best way to survive is to study and learn from the patenting strategies followed by the market leaders who are successfully protecting their inventions via means of patenting. since no publication or public disclosure about ip strategies is available, the only way to understand such ip strategies is to look at the patent filings, analyze them and based on the trends, deduce their strategy. these insights thus obtained may help the it industry to customize its strategy with respect to patent acquisition. 3. methodology the study covers patent data published from 2005 to 2014 from five indian and five us ict companies. the list of these companies is given in table 1. the derwent innovation database (https://clarivate.com/products/derwentinnovation/) was used to retrieve the relevant patent data for the study. the text mining and visualization tool vantage point (www.thevantagepoint.com) was used to clean, normalize and analyze the patent data. as the data retrieved was huge, it was also imported into a relational database for further filtering. the search strategy consisted of assignee names of the ten firms. as the study was to find the technological trends and strategies, the patents searched were based on the application year (trippe, 2015). the exemplary search strategy was: cmp=("company names") and (ad>=(20050101) and ad<=(20143112)) as patents are territorial in nature, the same invention may be duplicated by way of multiple fillings in different countries, which can be referred to as patent families. to reduce this form of duplication, one representative of each family was retained to obtain the data set highlighted in table 1. the bibliographic details of patents such as the title, abstract, claim, priority date, assignee name, inventor name, inpadoc family 68 members, and citations have been used for the analysis. table 1 companies with patent data sets and patent families. company patent data set patent families international business machines corp. 87,086 24,206 samsung electronics co. ltd. 168,170 26,885 microsoft corp. 118,860 19,274 google inc. 57,589 8,931 qualcomm inc. 179,640 13,899 tata consultancy services ltd 1,803 414 infosys ltd 644 273 wipro ltd 799 375 hcl technologies ltd 316 205 mahindra it & business services 523 263 4. analysis and visualization 4.1 patenting trends for us and indian it companies the overall patenting activity for these us and indian it companies between 2005 and 2014 can be seen in figure 1 and figure 2, respectively. the figures highlight that the patenting activity of the us companies is higher than their indian counterparts, which lag in protection of software innovations. the us companies applied for about 93,000 patents, while the indian companies applied for less than 2% of that quantity, with about 1500 patent applications in the same time period. it is observed that the patent applications of google and qualcomm have gradually increased in the study period, while that of microsoft decreased. samsung leads the application rate for almost 5 years, with more than 3,000 patents each year. on the other hand, indian companies such as tcs, hcl and wipro aggressively started patenting their activities only in 2010, 2011 and 2012, respectively. infosys and mahindra made their 69 presence felt throughout the decade under consideration. after comparing the indian and the us firms it can be said that the indian companies entered late into the patenting foray. 4.2 origin of inventions for us and indian it companies the origin of an invention can be found by using patent data (trippe, 2015). the priority filing country in the patent document is considered to be an indicator for the origin of a particular invention, as companies usually prefer to first file for a patent in the same country in which the technology is invented. figure 3 illustrates the priority country filing trends for the indian and us it companies. during the study, it was observed that the majority of the patents (67%) claim the us as the priority country. however, a closer look revealed that the indian companies have india as their origin of invention. a further analysis of the top filers from india reveals wipro has its patent origins in at least 9 countries while tcs has its origin of invention in 4 countries, infosys and hcl in 3, and mahindra had its origin of inventions in 2 countries. the study of major us filers reveals that samsung leads the way by priority filing around 78% of its patents first in korea followed by 18% in the us. samsung and qualcomm have priority filings in at least 12 countries and 78% of qualcomm’s, and 86% of microsoft’s, inventions originated from the us. microsoft has filings for origin of inventions from 13 countries. ibm has a spread across 14 countries and has about 88% of its inventions’ priority filings in the usa. around 5% of ibm’s inventions originate in europe. the reason that the us-based companies have many countries as their origins of invention can be attributed to their global presence in the form of technology and r&d centers in multiple countries, along with their collaboration in research. however, this is not the case of the indian companies, as they operate in selected markets other than india such as the usa and europe only. wipro is the only indian company with priority filings for inventions from at least 9 countries. it is also interesting to note that wipro has around 16% of its patents in the usa and 3% of patents originating in singapore. 4.3 patent legal status for us and indian it companies patents’ legal statuses are an important component of patent information. they show whether a patent is dead or alive. they can also throw light on the various strategies used by the patenting firms, such as which technology is still protected and where, or whether it will soon become freely available in the public domain (wipo-a). alive patents are the ones that are valid and can be enforced. the dead patents are the ones whose applications are either withdrawn, rejected or the granted patent has expired, lapsed or been revoked for various reasons such as non-payment of maintenance fees. there is also a third category in the legal status known as “indeterminate,” where patents are assumed to be applications undergoing examination, the examination is pending or whose status is not known. table 2 highlights the legal status of patents in percentage for the 10 companies studied. it is interesting to note that infosys has around 92% of its patents live and enforceable. inversely, about 30% of ibm’s patents are unenforceable due to withdrawal of the application, rejection, lapse or revocation. this may be seen as an offensive tactic by ibm to make data public via means of disclosure to 70 force firms out of competition and at the same time save costs incurred on prosecution or maintenance of patents. it might also be due to the technology in ibm’s patents becoming absolute. even then a figure of 30% is quite high. table 2 patent legality status in percentage. company name living patents dead patents indt. ibm 67 30 3 samsung 85 9 6 microsoft 81 9 10 qualcomm 74 10 16 google 82 6 12 tcs 77 3 20 hcl 9 0 91 mahindra 26 0 74 infosys 92 2 6 wipro 41 0 59 4.4 technological trends of us and indian it companies. the international patent classification (ipc) is used in a patent document to classify the patent according to the technical fields it claims. an analysis into the top ipc-4 digit for the 10 companies studied revealed that 7 companies (ibm, microsoft, google, hcl, infosys, tcs and wipro) lead with maximum patenting in g06f which indicates “electrical digital data processing” (table 3). around 62% of microsoft’s patents were in the ipc-4 digit class g06f, while ibm has around 55% of its patents in g06f and about half of google’s patents were in g06f ipc-4 digits. samsung lead with the majority of their patents in h01l, with 17% of its total filings in the class indicating “semiconductor devices” while qualcomm has about 34% of its patent filings in h04w, indicating “wireless communication networks” and mahindra with 9% in b60r, or “vehicles”. table 3 count of patents for top ipc-4 digits of each companies. ipc-4 digit g06f h01l h04w b60r google 4456 ibm 13192 samsung 4519 microsoft 11889 qualcomm 4750 hcl 91 tcs 184 infosys 187 wipro 188 mahindra 24 table 4 count of patents for the top 3 ipcs of each company. ipc google ibm samsung microsoft qualcomm hcl tcs infosys wipro mahindra g06f001730 1510 2138 2900 9 61 37 g06f001516 685 1544 1675 27 g06f000700 481 g06f000944 1540 1548 43 h04w000400 924 912 h01l002100 504 g09g000500 437 h04l002906 520 h04l000100 508 g06q001000 9 g06f000944 7 27 g06f001700 14 g06q001000 13 g06f001730 12 g06q001006 29 b60r002100 4 b05b001500 3 b60k002000 3 71 table 5 claim count in patent applications. claim count google ibm samsung microsoft qualcomm hcl tcs infosys wipro mahindra 0-10 833 48 7341 6890 1347 200 169 31 308 258 11-20 4539 15349 13533 11448 2844 27 234 128 90 9 21-30 3026 4144 4599 689 3717 12 20 90 74 0 30-50 757 415 1289 214 4179 6 6 25 8 0 51-75 107 16 117 28 1374 0 2 1 1 0 76-100 27 4 11 4 336 0 0 0 0 0 >100 11 0 2 1 103 0 0 0 0 0 table 6 illustration of counts for family size, claim count, citations, number of inventors and assignee count. *rounded off to the nearest whole digit. ib m s am su n g m ic ro so ft q u al co m m g oo gl e t c s h c l m ah in d ra in fo sy s w ip ro average family country* 4 6 6 13 6 4 1 2 2 2 average claim count* 17 16 15 33 21 14 19 6 21 20 maximum claim count 99 126 113 208 119 59 50 18 56 54 minimum claim count 1 1 1 1 1 1 3 1 1 5 maximum assignee count 62 23 19 21 16 13 6 5 11 9 average assignee count* 3 2 2 2 2 2 1 1 3 1 maximum backward reference 571 598 1248 1509 2007 37 15 26 148 51 minimum backward reference 1 1 1 1 1 1 1 2 1 1 average backward reference* 23 16 27 29 26 6 5 10 12 9 maximum forward reference 112 151 189 85 206 32 6 50 101 28 minimum forward reference 1 1 1 1 1 1 1 1 1 1 average forward reference* 4 5 9 4 9 3 2 19 5 5 maximum inventor count 61 21 60 20 29 12 10 8 10 8 average inventor count* 4 3 4 3 3 3 3 3 3 2 a further analysis of the ipcs taking into consideration the full ipc revealed that all these companies are working in different domains with a minimum domain mapping with each other. this is highlighted in table 4 for the top 3 patenting technologies of each company based on the ipc. google has around 17% of its technologies patented in g06f001730 (“information retrieval”), while microsoft and ibm map the same technology with around 15% and 9% of their total patents, respectively. qualcomm and samsung work in the same domain of h04w000400 (“services specially adapted for wireless communication networks”) with about 7% and 3% of their total patent filings in this domain. even though microsoft leads in g06f001730 (“information retrieval”), a closer look of its filings reveals that it has decreased its applications in information retrieval for the last 10 years. at the same time, google has increased its activity in this field. 4.5 claims filed by us and indian it companies claims play an important role in patent document. the patent description reveals how to make and use the invention, while the claims define the scope of legal protection and provide boundaries of the patent owner’s exclusive rights. hence, patent assertion for novelty depends on its claims (merges & nelson, 1990). thus the number of claims of a patent document determines the depth and breadth of the technology for which protection is sought. 72 table 5 shows the claim counts for each of the companies in this study. usually, patent claims are in the range of 1-10, as claims above 10 incur additional filing charges. however, as seen above, less than 20% of the patents have claim counts of less than 10. around 53% of the patents have claim counts between 11 and 20. all of the us-based companies have the maximum patent applications with claims in the range of 11-30. one important thing to note is that the us-based companies also have about 3% of their patents with more than 50 claims in a patent document. at the same time, qualcomm has more than 13% of its patents with more than 50 claims each. google has 11 patents with claim counts of over 100, qualcomm has 103 (about 1%) patents with claim counts of over 100. this is much higher than the average patent claim counts. google can be seen in table 5 with a patent having 119 claims, whereas qualcomm had a patent (application number ep2559309a1) with 208 claims. it can also be seen that qualcomm leads with the highest average claim count in patents with more than 33 and google following it with an average of about 21 claims per patent document. indian companies infosys, wipro and hcl have an average of around 20 claims per patent document. 4.6 analysis based on patent family size, claims count, number of citations, number of inventors and assignees for indian and us it companies as highlighted in table 6, the average family size of a patent is 4.7, while all the indian companies are below this average count, us companies, baring ibm, have an average family size per patent higher than 6. qualcomm has the highest average family, around 13 per patent. base on this, it can be derived that qualcomm tries to enforce its inventions in most countries simultaneously. however, ibm, which has much higher patent families than qualcomm, has an average family size of around 4. this is the lowest for the us-based companies. if correlated with the origin of inventions, ibm has the maximum presence, in 13 countries, from where its technology has emerged. hence it can be deduced that ibm’s strategy is to enforce particular technologies in specific countries only and not in many countries, as in the case of qualcomm. a patent application contains references to other patent documents in its description (wipo-b). these references can be forward or backward references. while the backward citations refer to the publicly available technological documents to form prior-art, the forward citations highlight all other patents and refer to the new patent application (wipoc). these citations, when analyzed, give insights into the evaluation of a particular technology (breitzman, 2010). table 6 shows that all of the us based companies have an average backward citation above 20, except for samsung which has an average citation above 16. with respect to the indian companies, the average backward citation is less than 10. the us-based companies had at least one patent with a maximum backward citation of more than 500. google had a patent with 2007 citations, whereas qualcomm and microsoft have patent publication with maximum backward citations of 1509 and 1248, respectively. the forward citations are also useful from a competitive or business intelligence perspective to identify players working in a similar area or technology to the new patent application. monitoring the forward citations of a new patent application allows a user to identify new competitors entering a similar field of technology, potential infringers and possibly, potential licensing opportunities (minesoft). google and microsoft have the highest average forward citations for patents, with an average of about 9 forward references per patent, while hcl had the minimum with 2. thus it can be inferred that patents of google and microsoft are used by other players to advance their technologies. google has a patent with the maximum of 206 forward citations, while microsoft has 189 forward cited patents for its publication. infosys tops the list on the indian side with 101 forward references in its patent publication number us7787887b2. the number of inventors per patent is summarized in table 6. it can be seen that for all of the companies the average inventor count per patent is around 3. even then, ibm and microsoft have patents with inventor counts of more than 60, and they are the only two companies with an average inventor count around 3.5. 5. conclusion business intelligence in general and competitive intelligence in particular has been traditionally used for inputs related to sales, marketing and finance. however, the use of 73 patents as strategic business tools has opened a new horizon for the use of patent analytics in gaining inputs based on business intelligence and competitive intelligence. patent analytics based on competitive intelligence can be used for understanding the strategies used by companies in advocating their patent portfolio and aligning their business with patenting activities. it can be seen from the study that the ict companies in the study are not directly competing with each other in the same technological domain, except for g06f001730 (information retrieval). indian companies are far behind in protecting their ip, although they are now on course correction and have started aggressively protecting their inventions. it is observed that the patent filing strategy of qualcomm differs from its competitor ibm because qualcomm is filing patents in all major countries while ibm has it presence felt only in specific countries, which can be seen from average patent family countries count. claims in the patent document highlight the technological depth and breadth of patent applications, and qualcomm seeks protection to maximum claims, thereby revealing its strategy of covering many aspects of a technology within a single patent application. based on forward and backward citations, it appears that microsoft and google possess high quality patents. it is apparent that ibm uses disclosure strategies, as 30% of ibms patents are dead, resulting in the technology coming into the public domain. this may be a tactic to force competitors out of their activities. contrary to ibm’s tactics, samsung has 85% of its patents enforced, while rentaining the highest number of patent families, proving it to be a serious player in protecting its intellectual property. business and competitive intelligence, when use to study ip competitive analysis, can 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(2006, october). techniques, process, and enterprise solutions of business intelligence. in systems, man and cybernetics, 2006. smc'06. ieee international conference on (vol. 6, pp. 4722-4726). ieee. page 4 editors note vol 9 no 1 editor’s note vol 9, no 1 (2019) developing new models for intelligence studies the aim of any social science to develop theories and/or models to better understand the business reality. we are happy to see that a majority of contributions this time do exactly that. the first article by nuortimo is entitled “exploring new ways to utilise market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power”. it is an in-depth case study about the monitoring of technology sentiment based on business environment scanning. results show how media sentiment towards nuclear power has been mostly negative, particularly in social media. however, results from similar analyses of the image for the companies currently deploying these technology are less negative, suggesting the importance of companies’ communication and branding activities. the paper shows how technology’s media sentiment can influence a company’s brand image and marketing communications. it concludes that there is a need for better co-operation between different corporate functions, namely technology management, mi, and marketing and strategic planning. the second paper, by bleoju and capatina, entitled “enhancing competitive response to market challenges with a strategic intelligence maturity model” shows a way to gain robustness in confronting unexpected events in real markets by adopting a wider unstructured learning perspective with the help of maturity assessment tools. this helps to pool strategic intelligence skills. the theoretical contribution is called the strategic intelligence capability maturity model. the article by solberg söilen is entitled “how managers stay informed about the surrounding world”. it’s a survey of managers and knowledge workers to find out exactly what sources of information they gather to help their organization stay competitive. conclusions from the data are drawn and a model presented that brings together previous theory with new empirical findings. the first issue of 2019 was delayed primarily due to the journal’s involvement as co-sponsor of the ici conference in luxembourg in may. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. we hope to see as many as possible at the ici conference in bad nauheim in may, 2020. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2019 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 9, no 1 (2019) p. 4 open access: freely available at: https://ojs.hh.se/ vol8no2paper1kalle to cite this article: nuortimo, k. (2018) measuring public acceptance with opinion mining: the case of the energy industry with long-term coal r&d investment projects. journal of intelligence studies in business. 8 (2) 6-22. article url: https://ojs.hh.se/index.php/jisib/article/view/307 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index measuring public acceptance with opinion mining: the case of the energy industry with long-term coal r&d investment projects kalle nuortimoa* asumitomo shi fw energia oy, p.o.box 201, fin-78201, varkaus, finland; *kalle.nuortimo@shi-g.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: measuring public acceptance with opinion mining: the case of the energy industry with long-term coal r&d investment projects social business intelligence: review and research directions helena gioti, stavros t. ponis pp. 23-42 and nikolaos panayiotou investigating the competitive intelligence practices of peruvian fresh grapes exporters journal of intelligence studies in business v o l 8 , n o 2 , 2 0 1 8 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 8, no. 2 2018 christophe bisson, maria mercedes pp. 43-61 and tang tong an analysis of ip management strategies of ict companies based on patent filings shabib-ahmed shaikh pp. 62-71 and tarun kumar singhal kalle nuortimo pp. 6-22 business intelligence for social media interaction in the travel industry in indonesia michael yulianto, abba suganda girsang pp. 72-79 and reinert yosua rumagit measuring public acceptance with opinion mining: the case of the energy industry with long-term coal r&d investment projects kalle nuortimoa* a sumitomo shi fw energia oy, p.o.box 201, fin-78201, varkaus, finland corresponding author (*): kalle.nuortimo@shi-g.com received 18 june 2018 accepted 21 august 2018 abstract new web 2.0-based technologies have emerged in the field of competitor/market intelligence. this paper discusses the factors influencing long-term product development, namely coal combustion long-term r&d/carbon capture and storage (ccs) technology, and presents a new method application for studying it via opinion mining. the technology market deployment has been challenged by public acceptance. the media images/opinions of coal power and ccs are studied through the opinion mining approach with a global machine learning based media analysis using m-adaptive software. this is a big data-based learning machine media sentiment analysis focusing on both editorial and social media, including both structured data from payable sources and unstructured data from social media. if the public acceptance is ignored, it can at its worst cause delayed or abandoned market deployment of long-term energy production technologies, accompanied by techno-economic issues. the results are threefold: firstly, it is suggested that this type of methodology can be applied to this type of research problem. secondly, from the case study, it is apparent that ccs is unknown also based on this type of approach. finally, poor media exposure may have influenced technology market deployment in the case of ccs. this paper is the extended version of a paper from the ici 2018 international conference on competitive & market intelligence, june 5-8 bad neuheim, germany. keywords carbon capture and storage, ccs, greenhouse gas control, market deployment, opinion mining, public acceptance, web-intelligence 1. introduction: emerging webintelligence applications for competitor and market intelligence the aim of competitive intelligence (ci) is to analyse and exploit information about a company’s competitors and sectors of activity to determine its competitive strategy and to develop new knowledge about its competitors in an increasingly complex and fast-moving economy to maintain levels of innovation and thus gain a competitive advantage (amarouche et al. 2015). the most popular term used in the literature is competitive intelligence, followed by business intelligence (bi) and market intelligence (mi) (dutoit 2015). the lack of sufficient and reliable information sources about competitors can restrict the capability of ci (xu et al. 2010). traditionally, information about competitors has mainly been obtained from press releases, analyst reports, and trade journals, and recently also from competitors' websites and journal of intelligence studies in business vol. 8, no. 2 (2018) pp. 6-22 open access: freely available at: https://ojs.hh.se/ 7 news sites. unfortunately, such information is mostly generated by the company that produces the product; therefore the amount of information is limited and its objectivity is questionable (xu, et al. 2010). competitive intelligence is favoured at the expense of strategic management as a field and has evolved over the years as a result of the need for enterprises to scan the complex external environment (dutoit 2015). competitive intelligence provides the company with a clearer picture of its competitive environment, while the increasingly frequent use of information and communication technologies (ict), including online shopping sites, blogs, social network sites, and forums, provides incentives for companies to promote their advantages over their competitors (amarouche et al. 2015). due to the emergence of web 2.0, including social media, ci now has a potentially wide field for developing new applications. the large numbers of customer-generated product reviews often contain information about competitors and have become an interesting source of competitive and market intelligence to mine (xu, et al. 2010). finding the weakness of products from customer feedback can help manufacturers improve their product quality and competitive strength. in recent years, more and more people have begun expressing their opinions about products online, and both the feedback of manufacturers’ own products and their competitors’ products could be easily collected (chang et al. 2012). several applications have been developed for next generation ci/mi. the opportunities associated with data and analysis in different organizations have helped generate significant interest in business intelligence and analysis (bi&a). bi&a is often described as the techniques, technologies, systems, practices, methodologies, and applications for analysing critical business data to help an enterprise better understand its business and market, and to make timely business decisions (chen et al. 2012). opinion mining in product ci was discussed by amarouche et al. (2015). a system to efficiently analyse patent data, a patent trend change mining (ptcm) approach that can identify changes in patent trends without the need for specialist knowledge, has been proposed by shih et al. (2010). market intelligence from microblogs, which have become great sources of consumer opinions, has been developed in the form of compact numeric summarization of opinions by li et al. (2013), from which the proposed mechanism can effectively discover market intelligence (mi) to support decision-makers. in 2012, chang et al. introduced weakness finder, which helps manufacturers find their product weakness by using aspect-based sentiment analysis on chinese reviews. in computational linguistics, irony is one of the more challenging topics in sentiment classification, and tools to detect irony were described by reyes and rosso in research focusing on identifying key components for the task of irony detection (2012). this paper describes an opinion mining approach to discover the public acceptance of carbon capture and storage (ccs) technology, in order to highlight influences on long-term r&d strategy. compared to media images of solar and biomass power (nuortimo 2017a&b), differences exist, and can be used to highlight the link and differences between existing theoretical base. 2. case carbon capture and storage (css) the need to reduce atmospheric co2 has resulted in several global agreements (e.g. kyoto protocol, 1997; paris agreement, 2015), all affecting environmental legislation, technology strategies, and decision-making of individual companies. the large-scale adoption of ccs in combination with increased energy efficiency is seen as one option to halt co2 emissions in the short run (wennersten et al. 2015). power plants with ccs in addition to large shares of low carbon generators such as renewables would be required to meet the global targets (brouwer et al. 2015). carbon capture and storage facilities coupled with energy efficient power plants would provide a strategy to permit the continued use of fossil fuels whilst reducing co2 emissions. the ccs process includes three stages of capture and compression of co2 from power stations, transport of co2, and storage away from the atmosphere for hundreds to thousands of years (hammond et al. 2011). however, regardless of the potential, the technology deployment has not been realised due to lack of economic incentives, regulations, and public acceptance (nuortimo 2012). technologies have been connected with societal controversies in the past; for example, nuclear power and gene technologies have been surrounded by dispute, potentially causing public rejection. past rejection of technologies by the public emphasises the urgency to 8 understand the psychological features of societal acceptance of technologies (gupta et al. 2012). public acceptance of technologies such as ccs is crucial for successful introduction into the society (huijts et al. 2012). in this study, the media image of ccs, especially in social media (some), was studied to find possible implications for public acceptance of ccs technology. this was done by reviewing the relevant ccs discussions and studying the media image of ccs from 2014 to 2016. the main research question is formulated as: what is the media image of ccs and its possible implications for public acceptance, and, furthermore, how does this relate to coal combustion technologies in general? this paper is organised as follows. first the literature is analysed in terms of the important aspects of ci/mi tools and developments, case ccs and related public acceptance and market deployment, and subsequently with application of the new method, opinion mining with machine-based media analysis. a possible link from media image to product market deployment is suggested in the discussion section. then follows the methodology section, including explaining the learning machinebased media analysis that was used to demonstrate the importance of visibility for technology acceptance. finally, discussion, conclusions, and policy implications are presented. this methodology is rather new and experimental, but its main contribution is highlighting the paradigm shift from humanmade media analysis to machine-made analysis with a multidisciplinary approach, and describe its possibilities in technology intelligence, especially in weak-signal detection related to long term r&d strategy decisions. 2.1 public acceptance of ccs the viability of ccs, or any other technology, is influenced by economic, regulatory, and technical aspects, but also by public acceptance. public acceptance of ccs is seen to depend on people’s sense of trust in stakeholders and not solely on the properties of the technology itself. (terwel et al. 2011). the size of the project and local history as well as trust in stakeholders may influence local public acceptance of ccs (dütschke 2011). trust in organisations also affects people’s perceptions of the magnitude of risk and the benefits as well, impacting their acceptance of ccs (terwel et al. 2009). similar logic has been presented, for example, for public acceptance of gene technology (siegrist 2000) and also for nuclear waste where overwhelming political opposition has been fueled by the public’s perception of risks (slovic et al. 1991). education about ccs can also affect public acceptance by highlighting qualities of the technology that the public finds acceptable and thereby reducing fundamental opposition (itaoka et al. 2004). public acceptance of different ccs elements— namely plant type, transport, and storage—may, however, be different, as wallquist et al. (2012) indicate. pipelines, for example, may result in lower acceptance, whereas storage location can have the least influence (although environmental legislation practically prohibits land storage in europe), and plant type some influence. itaoka et al. (2009) indicate that different factors, including risks, effectiveness, responsibilities, and fuel use, have varying impacts on ccs acceptance. lay attitudes toward ccs are also seen as relevant, and the lack of public acceptance is seen to potentially reduce the viability of ccs severely (terwel et al. 2009). in fact, people’s acceptance is seen as critical for the widespread deployment of any low-carbon technologies to become viable options for reducing co2 emissions (fleishman et al. 2010). the way ccs might contribute to reducing the impact of global warming is unclear, even to those who believe they have a good understanding (de best-waldhober et al. 2009). this is interesting, as many studies indicate that awareness of the necessity of preventing global warming can be crucial to the acceptance of ccs (itaoka et al. 2009; tokushige et al. 2007) past examples exist for lack of public acceptance being a major hindrance for developing new energy infrastructure costeffectively, affecting many technologies, including nuclear (grove-white et al. 2006), ccs (bradbury et al. 2009), wind farms (firestone and kempton 2007), gene technology (siegrist 2000), nanotechnology (siegrist et al. 2007a), and many others. public acceptance in these cases is typically affected by fears of radiation (kim et al. 2013), co2 being released from the ground and causing suffocation (wallquist et al. 2009), potential noise or threat to animals (wolsink 2007), and unknown consequences (zechendorf, 1994; siegrist et al. 2017b). public acceptance is somewhat an unknown factor in developing public policy for ccs technology (itaoka et al. 2004). only educating 9 in order to increase public awareness of need for mitigating co2 emission would not directly increase the acceptability of ccs (itaoka et al. 2004), but information may increase support for some aspects of the technology, such as storage options. on the other hand, information on ccs may in some cases result in stronger opposition (palmgren et al. 2004), particularly against geological storage under the ocean. it is noteworthy that public acceptance depends on information sourced from different actors, especially people’s influence on each other, emphasizing trust (huijts et al. 2007). international examples may also be required to enhance confidence and trust in ccs, as public acceptance is seen as a requirement for market deployment (de coninck et al. 2009). in fact, high public acceptance is seen as one of the critical factors for widespread deployment of various ccs projects (zhang and huising 2017). public acceptance is seen as one of the important obstacles for ccs implementation, along with a lack of policy framework, costs, and international regulatory framework, a factor that is seen to potentially have the biggest effect on commercial success (gough 2008). in some ways, however, public acceptance is viewed among other uncertainties surrounding ccs (lohwasser and madlener 2012). benefit and risk perceptions are seen to influence on the progress of the technology (wallquist et al. 2010). wüstenhagen et al. (2007) describes three types of public acceptance to highlight different aspects of market deployment, namely sociopolitical acceptance, market acceptance and community acceptance. bell et al. (2007) note how public acceptance can have multiple dimensions by indicating that the acceptance of generic technology might be very different from that of local projects. regardless of general acceptance of ccs, ‘not in my backyard’ (nimby) attitudes can appear when facilities are proposed close to one’s own communities, yet attitudes about ccs are based on concepts and perceptions, not on actual past events, making the possibilities of comparing nimby attitudes to other energy industry developments somewhat limited (krause et al. 2014). although there are many co2 storage sites available, the possibility of co2 leaking from the storage area has affected public opinion towards the technology. wallquist et al. (2011) found the nimby attitudes to exist towards both co2 pipelines and storage sites. such attitudes persist regardless of techno-economic aspects favouring the large technology market deployment of near-zero co2 power production in the medium term (10-20 years). due to public fears, ccs market deployment in the form of building a commercial-size demonstration plant (for example oxyfuel technology) has been delayed (santos 2015). the situation has been seen to have strong linkages to public acceptance and as well as to political decision-making. ccs technologies have been increasingly communicated during their development, starting from the early 2000s (ashworth et al. 2009). the topic has also attracted, to a lesser extent, attention on social media. due to the fact that ccs technology is still under development, its commercialisation is dependent on public opinion and on related media communication. market deployment includes the actions towards managing organisational resources in the marketplace (slotegraaf et al. 2003), and deployment is the next step after the r&d activities in the product cycle (midttun and gautesen 2007). various factors (political, technological, financial, etc.) can promote market deployment. ccs market deployment necessitates achieving effective emission reduction incentives alongside public-private funding for r&d (gielen et al. 2014). from the technological perspective, the energy mix and ambitious co2 reduction targets impact market deployment, whereas should coal be part of the energy mix, ccs is seen as the only technological solution worth deploying (folke et al. 2011). investment costs and co2 allowance prices strongly influence the market deployment of coal-fired ccs power plants (lohwasser and madlener 2012). money is an important factor in the market deployment of new energy industry solutions that necessitate private finance (mathews et al. 2010). market deployment of new technologies such as ccs requires significant investments and entails some technological risks to demonstrate their viability (burnham et al. 2013). attracting the attention of government and industrial sectors is important for ccs market deployment since incentives, financial support, the regulatory system, and venture capital require widespread participation of government and businesses (dapeng and weiwei 2009). complementary policies and 10 incentives are seen to impact market deployment (grubler and riahi 2010). systemic policy strategy is necessary for market deployment to overcome any technology barriers and manage the risks (åhman et al. 2013). different types of policies are potentially needed for supporting lowcarbon technologies along with the technology maturity to support the level of market deployment (iea 2010). because it comprises the measures that aim at promoting energy technologies from early research to market deployment, an energy technology policy is needed (ruester et al. 2014). initiatives such as the strategic energy technology plan, the technology pillar of the eu's energy and climate policy adopted by the european union in 2008, are the first steps toward establishing an energy technology policy for europe. this type of initiative may eventually result in market deployment of key low-carbon technologies at the european level (fütterer et al. 2014). market deployment is potentially hindered by the commonly understood fact that it typically takes some thirty years for a new technology to materialise and to build the necessary expertise, capacity, and knowledge (kramer and haigh 2009). further, those r&d efforts that focus on technologies with modest potential for mitigating climate change result in market deployment initiatives for technologies to remain fragmented (grubler and riahi 2010). in the case of ccs, the time is now critical for the potential market deployment (maddali et al. 2015). market deployment takes its time as the extensive number of wells required for global scale deployment of ccs limits the possibilities of deploying ccs on a wide scale in a rapid manner (maddali et al. 2015). public opinion and attitudes are reflected in political decision making, impacting policies, regulations, and even finance. hence, the realities of ccs market deployment can be affected by the public accepting the technology. 2.2 research methodology this study is a first attempt to study media image, public acceptance, and product market deployment by first studying the literature and then comparing the results to findings from empirical analysis through opinion mining with learning machine-based media analysis of a vast number of editorial and social media sources. therefore, this work is not directly related to one specific field of study; supporting literature is gathered from ci/mi and technology intelligence methods, as well as from corporate decision-making, and is used to describe a possible link from some users to possible effects in company management. the basic research principles have been used in different fields, but are now applied to a single case; in the same way, public acceptance studies have been carried out on other topics using media analysis but with much smaller data sets. bursher et al. (2015) applied a similar approach with editorial content media framing and sentiment analysis by software. in this study the application of media framing, cluster analysis and statistical methods were considered to be non-applicable. this is due to the comparison of editorial content with social media and to the fact that media frame comparability between two different types of communication is challenging with a large amount of data. hence, the learning machinebased media analysis is applied in this study to demonstrate the importance of visibility, whether it would be a driver for technology acceptance, namely public acceptance and product market deployment, or not. the main reasons for choosing the opinion mining approach along with the learning machine-based media analysis method was its applicability to large global data sets (both from editorial content and some), fast data processing, and reduced risk of bias caused by human perceptions and interpretations (matthes & kohring 2008). the analysis period and data for this study covers one year, including a major international climate conference, the paris cop21. much narrower sentiment analyses have previously been carried out in the field of marketing, yet this study applies the existing elements in a new way. the users of the social web now have a new role as data providers, which seems to provide an excellent platform for analysing public attitudes (penalver-martinez et al. 2014). by adopting a media analysis approach and a particular tool, the quantity of media sources to be analysed is drastically increased compared to questionnaires and interviews or traditional media analyses. merely relying on qualitative methods such as research interviews would entail challenges, compared to a global media coverage study. for example, responses can be difficult to code and answers may vary by participant, while respondents can provide socially acceptable responses, telling what is considered acceptable, to the researcher (sovacool et al. 2012). the analysis 11 in this study was conducted to clarify the social acceptance status of ccs technology in order to investigate the possible connection to recent challenges in technology market deployment. the analysis findings were synthesised to obtain a clear view of the effect of media image, resulting social acceptance on ccs technology development, and related market deployment. hence, the research setting in this article is media analysis, where media sentiment is analysed to discover possible implications for public acceptance, political decision-making, and technology market deployment. the methodology used in this study can be considered a fairly new method in media research, especially in a comparison of global editorial media and global social media. in the past, some attempts have been made to create an automated tool for analysing nuclear power acceptance (reis et al. 2011), but media sentiment has not been clarified to this extent. this study relies on commercial software to mine the opinions relating to ccs, a similar method to that applied by bursher et al. (2015). opinion mining can be seen as a highly active research field consisting of natural language processing, computational linguistics, and text analysis technologies with an aim to get various added-value and informational elements from user opinions (penalvermartinez et al. 2014). the analysis was conducted to clarify the ccs technology’s media image. also, the potential effects on social acceptance of technology and its commercialisation were highlighted by comparing literature to data analysis. hence, the research setting used in this article is media analysis for one case, which is then compared to different, similar analyses (nuortimo 2017 a&b) m-adaptive software is used as the main tool in the learning machine-based analysis of global editorial and social media (some) sources. in this study, the m-adaptive sources cover 3 million social media platforms globally and 100,000 news outlets in 71 languages in 236 regions (m-brain 2015). sentiment analysis was carried out based on a combination of linguistic knowledge and human-aided machine learning, which means that the software suggested classifications to researchers who then provided feedback on correctness. by repeating this process a number of times the system learned to improve its classification of content into sentiment categories (m-brain 2015). in practice, the sentiment-coding expressions in the text were first recognised and classified automatically. the software matched all relevant ccs-related documents after which the sentiment-focused types were assessed, while the overall compound judgement displayed four options: positive, negative, neutral, and mixed. data analysis was conducted from 4 december 2014–28 february 2016, by searching ‘carbon capture storage’ and ‘ccs’, which included a total of 4496 data points (3380 editorial/1116 some). according to m-brain’s internal tests, 80 percent of the sentiments are correct on average for a given document when using the m-adaptive software. hence, it is possible that the system may make a mistake with any given individual document, due to inherent ambiguity in natural language. further, it is widely known that humans do not agree 100 percent in similar tests either, due to some individuals not being capable of identifying humour or sarcasm. as is the case for any artificial system, humour, sarcasm and irony are beyond the system's abilities to understand. however, catching the trends in the data becomes more accurate as the number of analysed documents increases, meaning that with large volumes, the overall model qualitatively matches human judgement on the same data. 3. results of machine-aided media analysis of ccs technology the large number of data points enabled the analysis of media sentiment towards ccs. figure 1 depicts overall sentiments towards ccs in both editorial publications and social media. the number of hits for ccs (4496) was low compared, for example, to wind power during figure 1 sentiment analysis of social media and editorial publications. 12 the same period (76,819), indicating relatively low visibility of ccs in the media. the results show that ccs resulted in positive hits mostly in editorial publications but also in social media. nevertheless, a larger proportion of negative hits in social media indicate lower levels of public technology acceptance. additionally, the number of some hits is smaller compared to editorial hits, which also indicates less exposure to the general public. further analysis shows that 33% of hits in the editorial publications were negative and 47% positive, indicating relative technology acceptance among scientists, experts, and journalists. the number of mixed and neutral hits is relatively small, which seems to indicate a consensus towards ccs (figure 2). attitudes in social media appeared somewhat different compared to editorial publications. figure 3 indicates that public sentiment toward ccs in social media is also mostly positive (45%) with only a minor 2% difference compared to editorial publications. the amount of negative hits was 3% higher than in editorial publications, indicating a bit more negative attitude. in mixed hits the difference was 6-11%, which can be seen as an indication of stricter view expression in social media. however, the 4% more neutral hits seem to indicate that some groups have not yet firmly fixed their attitudes, which can be considered an indication of a need to increase communication efforts in some. figure 4 illustrates the social media sentiment of ccs across different media. dividing the social media sentiment by media type reveals that blog writing has attracted most of the social media attention with over six hundred hits, of which the largest share is positive towards ccs. also facebook has been active with over 250, mostly negative, hits. due to a more visible number of negative hits, the social media effect can be considered quite large when public opinion towards technology is formed. in figure 5, media sentiment in selected countries is presented. in germany, france, and finland, the sentiment was more positive than in china or australia, emphasising the need for further communication efforts. relevant international events may also influence the appearance of pertinent writings in the media and media sentiment at the time. for example, during the paris cop negotiations from 30 november to 12 december 2015, a total of 279 hits appeared in the media. the media attention towards ccs was figure 2 sentiment analysis of editorial publications. figure 3 the media sentiment of ccs in social media. figure 4 social media sentiment of ccs across different media. figure 5 negative sentiment percentage in selected countries. 13 approximately doubled during these two weeks compared to an average of 300 hits a month (figure 6) (calculated as monthly average over 15 months). aside from the visibility of ccs being relatively low, it was evident that the editorial hits during the meeting were more negative than usual with 47% negative hits for ccs, while the same for some was only 34%. the normal 15-month averages were 33% and 36%, respectively. the percentages of positive hits during the paris cop negotiations were 44% and 49%, respectively, while the 15 month averages were 47% and 45%. 4. discussion this paper describes the media image of ccs technology, with possible implications especially from some for public acceptance and product market deployment, by synthesising a possible literature-based connection and demonstrating the role of visibility of ccs technology via advanced media analysis. when comparing the literature and empirical findings, the following can be observed. ccs has smaller media exposure with a more positive image. according to some communications theories, large media exposure can have some effect, whether positive or negative; small exposure maybe doesn’t affect at all, and small attention is transferred to be negative—if something is unknown, it has more associated risks. here, this is visible via the number of hits through various media-channels, especially in the editorial/some ratio. when comparing ccs to the case of biomass, ccs also has a positive image with a small number of hits, making the impact smaller. in the case of ccs, one of the main findings is that it is rather unknown, which is the worst case, because people can be afraid of what they don’t know. this is evident both from literature as well as from our analysis, therefore partly validating the method used. in the case of ccs, both communication and corporate stakeholder literature prove beneficial for explaining the phenomenon. for example, traditional stakeholder salience theory does not fully take into account general public attitudes, which can influence corporate decisions both directly and indirectly. in the case of ccs, it is evident that: 1) literature states that ccs is unknown (wallquist et al. 2011), which is empirically true due to low numbers of media hits. 2) pr-communication theory implies that if technology is unknown, it can have poor acceptance (mccorkindale et al. 2013). this is evident via the opposition to end storage in different countries and single projects. also, empirical country by country analysis indicates a high percentage of negative hits in countries with no deployment, such as australia, and also a high percentage of negative hits in some, such as in finland. 3) communication has been intraand interspecialistic (ashworth et al. 2009). this follows the funnel model by bucci et al. (2008). this is empirically visible via the low number of hits, indicating the urgency to increase communication activities to the general public already in the beginning of the product development cycle. 4) poor media image can possibly have an effect on technology market deployment in the case of ccs. this can be deducted from points 1–3. 5) means to measure media image have previously been challenging to apply to large global data sets. this study incorporates a new method, opinion mining approach including machine learning, which is tested and found applicable for fast large dataset sentiment analysis. the total media sentiment relating to ccs was found to be generally positive based on the analysis due to a relatively large number of positive editorial hits, among the rather low media visibility. in the social media, the sentiment seemed to be a bit more negative. for example, facebook appeared as a platform with active discussions concerning ccs with over 250, mostly negative, hits. the appearance of ccs in various platforms used by the public highlights the role of social media in shaping opinions. the sentiment also varies by country, as, for example, germany and france had positive attitudes, whereas australia had a negative media sentiment, with no deployment of the technology possibly twined with the sentiment. the sentiment can also vary among the type of figure 6 media hits during paris cop 30.11-12.12.2015. 14 media, as, for example, in finland, the editorial content was seen to be more positive than in the social media. the general attitude towards the technology may differ from the local as for example in germany, it seems that nimby is large, regardless of positive general attitudes in both editorial and some content, and as projects have been cancelled due to challenges in finding end-storage sites. such matters are not directly visible in media analysis and therefore this is a limitation of the utilised methodology. the analysis, however, indicates that general public opinion can be an important factor for public acceptance, and derived from that aspect, also for political decision making. hence, from the perspective of market deployment, it seems that the more editorial and some content ccs can obtain the better, to counteract the status of being unknown, whereas all possible scientific, technical, marketing and pr communication efforts are important for ccs market deployment, especially those targeted to the general public. the media sentiment toward a technology can be affected temporarily by relevant international events, such as the global climate negotiations, paris cop 21, during which the media sentiment seems to be influenced in one way or another. in this case the effect towards ccs by the editorial publications was mostly negative. although the needs of co2 reduction and the related agreements are of a global nature, technology commercialisation is influenced by regional politics and legislation. it is to be noted that local nimby attitudes are not necessarily clearly visible by using the approach in this study. any discrepancies between media sentiment and the actual project implementation seem to be a clear indication of stronger nimby attitudes. it would seem that one of the main benefits of the study lies in discovering global trends and technology development directions with a larger data set than previous studies, and also trying to establish new methodology for bigdata-based media research. also, this study highlights effectively the differences in channels of communication that may affect public acceptance and perhaps political decision making. the role of some is continuously increasing and presents a challenge for technology developers. it seems that at some level, a speculative negative link from public acceptance, economics, and policies to technology market deployment might exist in the case of ccs. another contribution of this study lies in incorporating a method formerly utilised mainly for marketing purposes to study media image and, furthermore, trying to find correlations to public acceptance of ccs, therefore bringing a new angle to related media and social acceptance issues. this is a new approach compared to questionnaireor interview-based studies with moderate data sets of some hundreds of data points that are used in similar studies (e.g. herassaizarbitoria et al. 2011). when compared to regular qualitative studies, the method has its positives and negatives, but it can be considered an approach that might provide a basis for longitudinal data-series analysis in the future. as highlighted by sovacool (2013), quantitative tools can make it difficult to indicate nuances and variance, and they also seldom look for acceptance. however, by utilising this method and comparing editorial content and some, some indication of acceptance appears to have been gained. hence, it is straightforward that this type of approach would be best, if supplemented with qualitative methods, such as questionnaires. the software sets some limitations, although it still allows the analysis of extensive data sets. the important local media sentiments, such as the nimby syndrome (wolsink 2000), have not been analysed. in accordance with the results by herassaizarbitoria, et al. (2011), it would seem to be a call for research combining qualitative and quantitative study on the public acceptance issue of ccs technologies. the type of approach involving vast data might be most useful to sight larger trends and could be complimented by qualitative methods, such as questionnaires and interviews. also further text analysis methods could be applied, such as framing and discourse analysis, but as in this case, the comparability of two large data sets can be challenging. this is due to different types of communication in some, such as hate speech. the changes that take place in the mass media coverage and framing can also affect public acceptance (heras-saizarbitoria, et al. 2011). however, this is not so visible when using this type of approach. also, these types of issues are often emotionally charged, potentially influencing the appearance of the issue, particularly in social media. according to stieglitz and dang-xua (2013), emotionally 15 charged social media messages tend to be repeated more often and more quickly compared to neutral ones. hence, there is a possibility that media sentiment is influenced by these types of factors. the managerial implications of this study are related to mi/ci method utilization, and also public acceptance research method development issues. this study highlights the fact that in traditional stakeholder theories, a some participant is not considered so much as a salient stakeholder. however, when combining some users into larger groups, there are possible implications at the corporate level in cases needing both proper political decisions and regulatory environment and policies, as well as long-time r&d activities with also perceived technical and hse risks. this study tries to find applications of a new method for power plant investment-related media analysis, a learning machine-based sentiment analysis that utilises a very large global data set. managers working with relevant issues can potentially benefit from the results or the potential of the methodology. the method is applicable to analysing global attitudes, and also their changes, for example, during the time of relevant international events. furthermore, managers planning power projects or long-term r&d development projects may benefit from understanding the needs for public engagement, and the urgency of social media participation. figure 7 describes a possible chain from ccs mediaimage to product market deployment. this chain starts from public image, which influences people’s perceptions of technology. in addition to traditional news media, which can shape public opinion regarding any issue by emphasising certain elements of the broader controversy over others (shah et al. 2002), social media (some) presents more direct opinions, often including emotional content (stieglitz and dang-xua 2013). the application of social media is seen to support market intelligence and product development (berendsen et al. 2015). media framing in editorial content has the potential to influence public acceptance as attention is focused and placed on a field of meaning (herassaizarbitoria, et al. 2011). following this reasoning, in pr-communication literature, the rule of effects describes the chain from media exposure via attention, comprehension, motivation, and behavioural trial to sustained behavioural change (mccorkindale et al. 2013). according to the rule of effects, in the rule of halves describing the effect is halved in each step, leaving the percentage from media exposure to sustained behavioural change to 0.78 %, emphasising the need for extensive media exposure. for ccs, one main challenge when the public perception is considered is that in most countries, the public is rather unfamiliar with the technology (wallquist et al. 2011). this also seems to indicate that communication activities so far have been mostly intraand interspecialistic, following the funnel model by bucci et al. (2008), which states that more popular communication is usually done in the commercialisation stage of the product development. media image influences public acceptance, and furthermore, public opposition can influence ccs projects directly in the form of local action groups, and indirectly via making the political climate unfavourable for ccs (wallquist et al. 2011). recent years have witnessed proliferation of studies on public perceptions of ccs, accompanied by the efforts to translate such knowledge into toolkits for public engagement and communication. at the same time, both literature and toolkits have paid little attention to the organisational dynamics and views of project implementers with regard to public engagement (breukers et figure 7 possible chain from media image to product market deployment/case ccs. 16 al. 2015). allowing for improved understanding of the global capacity and applicability of ccs is seen to potentially strengthen the global trust, awareness, and public confidence in ccs technology (de coninck et al. 2009). for nuclear waste, it was observed that long-term, stable contacts with the local politicians and population are important, but also, as can be seen from the finnish decision by parliament, a good contact with the national politicians is necessary. however, there is not necessarily a link between national public acceptance (or lack of it) and political decisions. national decisions, however, require a local acceptance (le bars, y., et al.). a us-based study found that individually, both ccs and biomass are perceived generally as beneficial for energy development by the news media, though they are not often mentioned in combination, as feldpauschparker et al. (2015) emphasise their value for climate change mitigation and as an alternative to fossil fuels. earlier examples of failed technology commercialisation have indicated that social acceptance is a decisive factor for technologies, including ccs, while the early adoption of the general public may be essential for technology acceptance (ashworth et al. 2009). as a final step from public acceptability to managerial decision-making and technology deployment, a stakeholder salience model (mitchell et al. 1997) can be considered. the stakeholder salience model introduces three key attributes for stakeholder classification: power, legitimacy, and urgency. the question is: how can one evaluate the groups communicating via some? how can one measure someone’s power, legitimacy, or urgency when posting opinions in various discussion forums or on twitter? considering development and technology deployment of a single company, these groups have seemingly no power, legitimacy, or urgency and could therefore be considered traditionally to be nonstakeholders in the decision making and would be perceived as having no salience by the firm's managers. however, reflecting on figure 7, in the case of ccs product market deployment, one pathway for this is suggested. furthermore, figure 8 is synthesised, suggesting that earlier stakeholder adoption would benefit from ccs market deployment. the findings from media study support this hypothesis via implicating negative attitudes toward the technology, especially in some, and low levels of hits in general, implying unknown technology. the figure illustrates how ccstechnology development would have potentially benefited from the earlier stakeholder adaptation. furthermore, due to lack of public acceptance, second generation ccs-technology, development is under risk. some of the managerial implications of this paper are also related to the r&d decisionmaking process and the social media influence. this study indicates that investments in ccs technology may not be favourable due to uncertainties in public acceptance. it was clearly visible that the amount of media attention was not large enough to fully support product commercialisation. the utilised artificial learning machine-based analysis tool may prove beneficial when evaluating social acceptance issues affecting long-term r&d investments. hence, as a practical implication, this study emphasises the need for more versatile analysis of factors affecting long-term r&d investments with strong public involvement both directly and via political decision-making. the limitations of this study include the analysed media sentiment being limited to those classifications possible with the used keywords and also to the english language. using other keywords, or not including some topics, might provide slightly different results. in addition, framing, cluster analysis, and statistical methods were found difficult to apply as the comparability between editorial content and some could have been lost. in addition, although statistical techniques are widely used among communications scholars to identify news frames, they are criticised for not being able to do so in a conceptually valid manner (carragee & roefs 2004). this also brings a challenge to further research. figure 8 stakeholder adoption in ccs product development. 17 the utilised method may entail some uncertainties that require further studies. results correlate to literature, so that based on the analysis, ccs is unknown and also has more positive sentiment. also, the methods that were used for ccs product life-cycle estimation are not based on calculated figures and are only directional. in addition to addressing the limitations of this study, relevant future research could relate to developing the machine/artificial intelligencebased methods further. 5. conclusions and policy implications new ai, computational linguistics and machine learning methods can be utilized for weak signal detection in ci/mi and strategic planning functions of a company. public acceptance appears as a clearly essential part of the energy market products’ market deployment, an issue that should be addressed during the early stages of a product life-cycle. the overall visibility of a technology is important, while if public acceptance is ignored, it can cause delayed or abandoned market deployment of long-term energy production technologies, accompanied by techno-economic issues. this paper has twofold implications. firstly, it studies ccs media image with a new type of method, public acceptance, and product market deployment based on literature. secondly, it highlights the importance of visibility and studies possibilities for closing the gap between the rhetoric and technical progress inherent to ccs, which is critically important to global climate mitigation efforts. developing strong international cooperation to demonstrate ccs with global coordination, transparency, costsharing, and communication as guiding principles would facilitate efficient and costeffective collaborative global learning about ccs. founded on the learning machine-based media analysis, it appears that the popular type of communication might have been beneficial to start to a larger extent during the early stages of ccs product development. as a policy implication, the media image of technologies, possibly affecting larger audience groups’ public acceptance, can be studied by means of learning machine-based analysis. this type of analysis indicates the majority of attitudes in both editorial publication and social media. learning machine-based analysis provides a fast way for policy makers to get information on the general public sentiment. the media image of ccs was found to be mainly positive—however, small and unknown, implying a need to push towards regulations to provide some common ground to commercialise ccs technologies. however, the visibility of ccs is currently lacking. policies favouring ccs could 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(1994). what the public thinks about biotechnology. bio/technology, 12: 870–875. issn: 2001-015x v o l 4 , n o 3 ( 2 0 1 4 ) c o n t e n t s marisela rodríguez salvador, paola cruz zamudio, andrés santiago avila carrasco, elías olivares benítez, beatriz arellano bautista strategic foresight: determining patent trends in additive manufacturing pp. 42-62 dirk vriens, klaus solberg søilen disruptive intelligence how to gather information to deal with disruptive innovations pp. 63-78 o p i n i o n s e c t i o n jonathan calof evaluating the impact and value of competitive intelligence from the users perspective the case of the national research council’s technical intelligence unit pp. 79-90 avner barnea competitive intelligence in the defense industry: a perspective from israel – a case study analysis pp. 91-111 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: prof. dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2014 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india associate professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain associate professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, hedin intelligence & strategy consultancy, sweden javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/22') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/23') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/24') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/9') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/10') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/12') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, december 26 2014 e d i t o r i a l n o t e v o l 4 , n o 3 ( 2 0 1 4 ) jisib continues to publish case studies. in addition we also publish in this issue patents analyses. patent analyses can be read both as examples of how to perform such analyses, but may also find interest within specific industries. professor henri dou, who is a founding father of this journal, was one of the pioneers in this area, also with the development of patent analyses software. we have also included a conceptual and theoretical paper. all of the contributions in this issue show that scientific work does not have to be limited to more narrowly defined empirical studies. the paper by salavdor et al. is dedicated to associate professor jonas rundquist, a colleague at halmstad university and at the same time a great admirer of the spanish speaking americas, who passed away in december 2014. he will be greatly missed. . the first paper by salador et al. is also a patent analysis, but this time for the additive manufacturing industry. unlike the first paper this one identifies a number of trends through a keyword patent analysis. “the main areas of research are focused on shaping of plastics and after-treatment of shaped products and working metallic powder and manufacture articles from this material”. the leading countries on additive manufacturing research are united states, great britain and switzerland. the second article by vriens and solberg søilen is an attempt to show the implication of disruptive innovation on intelligence studies. it is a theoretical paper. through a broad discussion of disruptive innovation theory the authors arrive at what they coin”disruptive intelligence”. in addition they describe ‘biases’ which may impair the production of ‘disruptive intelligence’. the third article is a case study written by calof. it is about how the national research council’s technical intelligence unit work with intelligence. the study shows that intelligence users understood and could appreciate a combination of hard and soft intelligence type measures. a survey in the form of an intelligence evaluation instrument was developed to gather data for the paper. the last article by avner is a case study about ci in the israeli defense industry. it confirms previous assumption that the industry in general and especially in israel is using ci intensively to support the decision making process. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen editor-in-chief halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 opinion section 70 revisiting sun tzu in the information overload age for applied intelligence education: stop answering, find good questions jean-maurice bruneau 1 , pascal frion 2 1 telecom business school, france, 2 jules verne institute for prospective & innovative projects, france email: jean-maurice.bruneau@telecom-em.eu pascal.frion@acrie.fr received february 9, accepted may 20 2015 abstract: sun tzu's 'art of war' is an illustration of the chinese strategic mode of thinking. today, faced with information overload it is unclear if the model of ''foreknowledge'' is as relevant as it once was. the method we used in this paper is action research to compare an occidental approach and an asian approach. the results obtained are applied suggestions to intelligence education. the contribution is to show how to step away from the epistemic of the information-centric approach to shift to a more multi-centric approach. we identified anchors such as strategic and critical questioning, identifying source people we do not yet know, and uncertainty-acceptance and bounded rationality. the implications are numerous. we are not so much dependent on the information available as associated with big data and software. our suggestions can be used in small and mediumsized organizations and do not necessitate resources associated with large organizations. keywords: applied intelligence education, sun tzu, competitive intelligence, strategic questioning, information. available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 1 (2015) 70-89 mailto:jean-maurice.bruneau@telecom-em.eu mailto:pascal.frion@acrie.fr https://ojs.hh.se/ opinion section 71 introduction the 'art of war' i was written by the chinese general sun tzu centuries ago and continues to be a standard text for the study of intelligence education. the concept of 'foreknowledge' in particular 'observe your environment and you will win your battles' has been used as a cornerstone for discourses and practices in intelligence for business, law enforcement and national security. in this context, we are faced with a gap between our capacity and our intention. baumard (2012) noticed that 'the art of being right overtook that of reflection' (p. 175). we want to notice, we want to observe the environment to win 'battles' but the representation of the environment is much richer today in terms of information ii and the battles are more diverse than ever before. 'noticing noticing' (neugarten, 2008) in small organizations allows the identification of postures and beliefs, different from the traditional discourse that is usually associated with large organizations. our resources to observe the environment have improved over time, but our increasing information needs in today's complex environments continue to push capabilities to the limit. until in the past, our challenge is not lack of information, but an information explosion. so the question is: in the information overload age, how can we adjust our thinking to better inform ourselves iii and our leaders? how can sun tzu's art of war enlighten us today? considering information overload, can we use sun tzu's art of war today in the same manner we have done in the past? the focus of this article is 'how to think and how to inform oneself' differently', in a position of information asymmetry iv , for intelligence matters in small organizations v during other periods than in 'peace' vi . how shall we think and inform ourselves professionally when we suffer from information overload and from missing information? in france, since the 90's, occidental competitive intelligence discourses have not succeeded in influencing small companies. there were epistemological misleadings (frion, 2012). how can we use the chinese strategic thinking mode derived from suntzu's work vii , to produce an operational system when we want to think or to inform ourselves, in an occidental environment, when a company experiences information asymmetry? sun tzu's work has been considered an art and has not been modelized with clear success. should we try and modelize it? our aim is to help occidental leaders to question themselves and to choose between two approaches, and by doing so, offer a modern contribution to applied intelligence education. our challenge is determining when should we use the occidental approach based on modelization and when should we use the asian approach based on the potential of the situation? the authors are also trying to understand similarities and differences in order to identify the transferable skills across the intelligence fields. sun tzu was an army general and his book was written with direct military purposes. we try and use sun tzu's legacy for competitive intelligence in particular for small organizations experiencing information asymmetry. this article is directly dedicated to intelligence education for business, but can be adapted for the police and for the military. our research method is mainly action research with these two approaches, each being put forward by one of the two authors. we will present the major criteria to select the modeling approach and the potential of situation approach, as well as a combination of methods along the continuum between the two. it is difficult to understand the world today; simple situations are rare. it cannot be taken in simple parts: it is complex (morin, 1986). there is a need for a global approach to think and to inform ourselves, as well as a necessity for ad hoc techniques and methods, when established processes are determined to be inappropriate or ineffective. background related work the art of war has been studied, translated and adapted since before the information age. in today's environment, it is important that many major and implicit considerations be identified and made explicit. foreknowledge the scene: sun tzu is leading an army on behalf of a sovereign. he is using a variety of people within and outside his army to collect data. military training teaches to fight, as well as how to observe the environment in order to secure and cease opportunities. he is using simple soldiers, civilians, scouts and spies to maintain situational awareness. many intelligence education works are based on the input-output model. information is sought, gathered and processed. objectivity is key; no preconceived idea can be accepted. in today's environment, technology is a cornerstone in the process. many works deal with information searching on a system, sometimes as a substitute to human intelligence. the human dimension is often ignored, except in a few contributions, such as illustrated by baumard (2012), boutin (2006 & 2007) or bulinge (2009). still, there is an epistemic opacity on how we think and how we opinion section 72 inform ourselves. even in intelligence matters, some people consider that every single bit of information should be considered, gathered, checked and used. consequently, intelligence organizations or team function like a data gathering and data crunching fusion center, rather than as the analysis center they were often intended to be. they target and filter data/information/intelligence. as sun tzu demonstrated, his information requirements were already defined in his orders from his sovereign, therefore, it is not information that comes first but issues-driven orders from a political leader. the way we read sun tzu in the occident is very informationcentered. focusing on information is misinterpreting or over interpreting (eco, 1992) sun tzu's text. spies in chapter xiii of the art of war, sun tzu describes the use of spies. today, conducting competitive intelligence activities for business purposes is legal; however, we always exercise caution not to stray into illegal activities. the value of studying the art of war in this context, is to understand the different aspects of the use of spies, legal and illegal, in order to recognize and prevent these techniques from being used against us. information overload (io) the detrimental impact of information overload on an organization has been neglected or ignored. information overload is defined here as a feeling of too much information during too short a period of time for a project that is too important to be ignored or to do a quick review of the information available. not many works refer to information overload in corporate intelligence, police and national security as an intelligence education literature. io is one symptom of the information asymmetry. size of the organizations the suggestions from the art of war have mainly been prepared for large organizations. sun tzu refers to an army of a hundred thousand men. oriental and occidental modes there has been a lack of knowledge, misreading or disregard for the fact that this text was written in an oriental style and is one illustration of a different strategic thinking mode that was generally unfamiliar to the west. it should not be read as an occidental book, with a beginning and an end. it is more a list of thoughts and experiences, presented in a poetic style. reading mode we agree with other authors who contend that sun tzu' art of war should not be read literally. lévi points out the challenge of translation (2011). for him, one cannot modelize the chinese strategic mode from the art of war with an occidental point of view. how can we take advantage of a book we cannot apply as a model? how can we use speech forms such as metaphors, oxymorons and paradoxes viii in an operational way? jullien (2002) shows that the art of war is the expression of the chinese mode of thinking that is different from the occidental one (with the limit of not suggesting an operating mode to learn to think differently). as for couderc, he provides a deep text analysis (2012). he mentions that the ancient chinese language does not clearly allow us to express an idea. the plasticity of the text, obscurity and ambiguity, made it possible for sun tzu'art of war to live on through centuries. modelling or not modelling ix shall we try and modelize a text that is using so many poetic representations? this text is considered here as not modelizable. so how are we going to suggest operational hints if we can't modelize it? thinking modes major postures in intelligence such as the chinese strategic mode primarily observe the potential of the situation whereas the occidental strategic mode is based on modelizing. in addition to these two modes, we identified other factors that are sometimes taken into account, such as behaviors, beliefs, organizations, methods, theories, tools and techniques based on a variety of modes and conditions such as luck, serendipity, exposition, provocation, totality of information, repeating what has been done before, looking for homogeneous solutions, making waves or no scandal to name a few. a combination of some of them can be useful during a long project whereas during a short activity, beliefs and actions that are not aligned, may create pitfalls. table 1 presents a brief comparison between the occidental and the chinese strategic mode. opinion section 73 table 1: the chinese and occidental strategic modes to apply sun tsu's art of war 'means-end' logic occidental strategic mode 'condition-consequences' logic chinese strategic mode purpose destruction of the enemy (check game) accomplishment and liberty of individuals (realization of 'i') destructuration of the enemy (go game) success of the group / family: harmony between the places of individuals and society (achievement of 'my role') strategy 'confrontation with the opponent' the environment is transformed by the actions of the actors objective: convince encirclement by the reduction of the room for manoeuver of the opponent' actors are transformed by the environment objective: suggest relation to the model general representations of things and time values and beliefs  modelize reality  distinction (separation and complementarity) between theory and practice  impose a shape to the reality materialism, a 'objectivated' world conscience of the subject, of the individual linear time rationality and technological progress  adapt the shape to the real  use of reality prevails over theorization of reality interdependent world, mysticism. conscience of the group, community spirit. immutable circular time pragmatism, moral and spiritual progress opportunities detection the detection of opportunities based on the reference to a model set by force to reality by the will of the actors actors submit to reality. no opportunity outside the process approach description of the world 1. first, definition of the goal, 2. gather the means, 3. look for opportunities and ways. principle of non-contradiction operating mode: reductionism and logical argumentation 1. identification of the potentiality of the situation, 2. anticipation of the consequences by the detection of opportunities 3. outline the actions depending on the conditions of the environment. third included logic operating mode: aphorisms and metaphors, adjustments, in perspective source: jean-maurice bruneau, based on jullien (1996, 2002) opinion section 74 conceptual framework model design sun tzu's art of war is considered valuable and insights are believed to be transferable to business. the models we use we used the works of jullien (2002) and herrigel (1953/2004) in particular to address epistemology in intercultural approaches, in particular between the chinese strategic mode of sun tzu to create knowledge, and a more occidental way with modelization. the main theories we use user-oriented. dervin & nilan (1986) are regularly cited as a change in paradigm from system-oriented research to user-oriented research. frion & frion (2008) mention that the person who is looking for information is an actor or even a director with the intellectual building of the 'staging of information'. we also use small groups sociology rather than focusing on large groups, and the lack of fulfilment theory from gödel. the frameworks we use informational asymmetry: information is not purely and perfectly distributed among the actors. small companies generally have less information and fewer resources than larger ones. systemism: the chinese thinking mode is interested in processes. complexity: we opt out from the epistemological point of view of objectivity and adopt a more complex position, assuming our subjectivity. in particular, we use the work done by morin (1986). we consider 'how to think and how to inform ourselves' and not 'data/information/knowledge management', 'mastering information' or any information-centric approach. indetermination postulate: there is no predefined information and predefined goal. tier-included logic: the person who is watching the environment is part of the environment and influences it. economic warfare: the authors distinguish periods of 'war' and periods of 'peace' for companies. the hypothesis we make information is not always a given. the authors would like to stress that this article refers to intelligence for business, police and national security and not to data/information/knowledge management. intelligence is taken here as a rare occasion. we often don't know what to expect. is it very different from monitoring the web with deterministic keywords and the 'matching process' among large quantities of information available. the company does not know the topic very well to start with. it simply cannot start analyzing the first information available. on the contrary, we need to start by asking questions. by doing so, we try and push away the limits that a neophyte can have. impossible validation. frion & frion (2008) say we cannot validate information, because we would need to validate the validation of the validation in a vicious circle attaining no more than a point of reference. we can just believe in references. the validating process misleads us. they suggest staging or directing the information scene with a list of criteria to select the information subject to acceptance. we decrease some analysis after the information and we increase the questioning prior to the information. responsibility principle authors use the responsibility principle from hans jonas (1979/1985) to question our future. how shall we inform ourselves today and tomorrow? looking at any data available on the web would not be responsible today when we face information overload. not looking would not be responsible either. looking responsibly, ethically, is what we try to achieve. operational versus true authors are researcher-practitioners. they study to practice in a more operational way and are not so interested in a theoretical truth. small companies are not just large ones on a small scale. they have unique ways of thinking and informing themselves due to their limited access to information and resources. we reject the progress paradigm in relation to information gathering: for the authors, the progress paradigm that says 'more information is better' is simplistic and misleading. the authors take into account the human dimension and the operational constraints and consequently consider that more information is not necessarily better. the authors summarized in table 2, the general pros & cons of classical views on modelization and opportunity seizing. opinion section 75 table 2: pros & cons classical views on modelization and opportunity seizing pros cons or to be addressed opportunity seizing thinking rather than informing oneself because thinking is synonymous with analyzing the information available (mainly with or after the information). allow opportunities to be seized. contextual. difficult to teach. adapted for small projects and topics that can be handled by one person or a small group. weak signals. does not need hierarchy to be run as long as the leader welcomes weak signals. 'if one does not know to which port one is sailing no wind is favorable' seneca not so well adapted for large projects when there is a lot of information or a lot of constraints to review. no beginning and no end. risk of over-interpretation of the information available. some negligible information is taken into account. time consuming to process 'all' the data/environment. feeling of not leading the process. work interruptions. incitation to stay in the known known and the known unknown. modelization informing oneself rather than thinking because informing oneself is synonymous with working before or without the information available to start with. not many questions asked, we follow the plan. avoid/limit work interruptions. easy to teach. there is a beginning, there is an end. no need to process 'all' the data/environment, just the one we need. feeling of leading the process. strong signals. fragility of the check list effect. risk of forgetfulness and blindspots. does not allow opportunities out of the model. not contextual. lack of spontaneity. lack of use of luck. incitation to go to the known unknown. the research method our research method was built in a succession of steps. we started by regularly discussing our observations on intelligence education, allowing us to use the appropriate method. our main observations are as follows. what is the art of war? sun tzu's art of war is regularly quoted in a centuries-old context. there has been no real new examination or point of view expressed despite the recent changes of the information age. the chinese strategic mode aims at observing the potential of a situation, by observing the internal and external environment. opinion section 76 sun tzu's art of war cannot be modelized. we should try other ways to make the most of it in the occidental world rather than to make models out of it. information overload and lack of information many people suffer from information overload. at the same time, they also suffer from a lack of information, in particular on strategic issues. today, it is frequent to have a feeling of too much information. how can we apply some precepts from a period prior to the information overload to aid us with the challenges we face today in small organizations? small organizations small businesses generally represent a larger proportion of the actors compared to a much smaller proportion of larger organizations. still, small organizations are often given the same suggestions than larger ones. they are relatively ignored in scientific research compared to large organizations. for instance, students who are leaving their school or their university to join start-ups or to launch new businesses, have been mainly trained to join a large firm. these start-up have less information than the large companies and still they can be very innovative, before many of them are bought by a large firm. some small organizations take advantage of this situation and favorably benefit from information asymmetry. information asymmetry small organizations have developed ways and means to think and to inform themselves differently from larger ones. small companies are used to thinking and informing themselves without or before information. large companies are more used to thinking and informing themselves with and after information. for instance, data bases and big data, are really topics keep large organizations awake at night rather than small ones. small companies are less likely to use consultants than are larger companies. generally, small companies possess less investigative methods and means than larger ones, and have less time to spare for activities outside producing, selling and administrating the company. small organizations experience an information asymmetry that influences the types of intelligence to which they have access and are able to use. types of intelligence when confronted with large amounts of data, like on the web, one can develop one's intelligence by analyzing and connecting it. people consider that you just need to dig into it, targeting and filtering the information, and nuggets will surely be found eventually. connect the dots. when confronted with smaller and even small quantities of data, one can develop a different form of intelligence, specifically by making assumptions, without being sure of receiving the information they think they need. two major types of intelligence should be studied in particular: intelligence with or after information and intelligence without or before information. different types of intelligence will need a specific validation of information. validation of information strictly speaking, information cannot be validated. we cannot validate information, we can just believe in references. the validating process misleads us. we suggest staging or directing the information scene with a list of criteria to identify the information subject to acceptance. by doing so, we increase the questioning prior to information and decrease some analyses after the information. this becomes an intellectual building of the ''staging of information'' (frion & frion, 2008.) of course this can be a risky process. however, if we do not participate in the validation process, we face cognitive biases we could otherwise limit or avoid. cognitive bias toward the 'strategic void' members of large companies can easily suffer from information overload in general and from cognitive biases such as the confirmation bias in particular. according to baumard (2012), the beliefs of larger organizations are no more robust as those of smaller organizations. by the nature of their organization, large companies tend to work with more established norms, standards and guidelines so that they tend to reject high value incongruous information. the nature of large organizations produces some 'strategic void'. large companies do not work with physical perceptions as much as small ones do. physical perception members of small companies are usually more directly impacted by customers and other physical elements from the realities of their markets. they tend to experience more physical perceptions such as a lack of comfort, uncertainty and solitude while doing their job. physical perception seems to be very useful in different ways in the industrial and information age. industrial and information age states of mind the mastering of information is often taken as a reference to achieve or to get close to. mastering opinion section 77 includes various assumptions such as art, control, virtuosity and superiority. the mastering of information is often understood by its control subjacent meaning. the denial of surprises, of incongruous information and of the unknown are relevant signs that the current state of mind is a heritage from the industrial age. what is the information age state of mind? we observe that people try to adapt from the industrial age state of mind to the information age. awkwardly and out of pique, many people seek more data to solve problems. indeed, big data will certainly address some of our current endemic problems as well as amplifying some others that have not been addressed properly. as an example, web searching skills have been rather poor for the last twenty years, creating poor habits and weak beliefs and the authors do not see why they would spontaneously be corrected with big data. the authors have observed the way many members of companies in occident-mainly in franceusually think and inform themselves. after having acknowledged and presented a short list of the salient elements the authors took into consideration, it is time to turn to the method chosen. the method chosen the authors wanted to go over a contemplative approach of observing gaps between a discourse and its effects and to be in a position to propose new ways of improvement. they introduced the chinese strategic mode in their missions and lectures and made empirical observations in small companies when they think and inform themselves. the authors also introduced sun tzu's art of war in missions and training sessions with small companies. the authors used the action research method. bruneau started from the chinese strategic mode and relied heavily on sun tzu's precepts, sometimes with the use of physically feeling the effect of information and situations. he started from the asian side with sun tzu and walked along towards occidental companies. frion started from the old occidental mindset and started to include the asian influence of sun tzu and also walked along towards occidental companies. he worked with more than two hundred very small and small enterprises on commercial aspects, using competitive intelligence, over the period 2009-2014 in a regional program called 'dinamic entreprises' in france. the two approaches used the 'participant observer' method separately and with different populations. sometimes a group was divided in two subgroups, one using the traditional and occidental approach whereas the other group was introduced to some precepts from sun tzu, in order to compare the results. the authors often compared their results over a period between 2010 and 2014. they also worked together in 2014 with a group of students with bruneau as a teacher and frion as a customer over a few months. the authors observed the participants and also themselves. they had distinct approaches and compatible goals. these two approaches are not quantitative approaches. they are described in detailed below. since our work is due to be used in applied intelligence education, the authors are presenting two practical hints to revisit sun tzu's art of war. at the beginning, they seem to be in opposition; still they share some of sun tzu's heritage, objectives, beliefs and results. we will present bruneau's approach first and then frion's, and we will compare them in a table in order to produce a working document and help to assist in applying the appropriate approach to a specific situation. bruneau's approach success story a five-person firm is specialized in soil biological analysis. its clients are mainly farmers. this very small company is competing with multinational firms and international institutes in agronomic research. despite its world class recognized expertise this company does not receive any public or private funding and still, strives to grow. this company is clearly in a situation of information asymmetry. in this context, sun tzu's precepts such as aphorisms and metaphors were used to facilitate the questioning. as an example, ʺthis knowledge cannot be elicited from spirits; it cannot be obtained inductively from experience, nor by any deductive calculationʺ (chapter xiii on the use of spies) suggests raising an incongruous question like 'has my competitor already done the investigation i intend to launch?' the questioning that follows will lead to factual hypotheses such as: is there a powerpoint file on the web that would present the marketing efforts of company x on soil quality control? while hypothesis check is carried out, surprises often emerge. in our case, we found that a competitor had prepared a document presenting the typology of the various tailored offers on the market, prepared. this approach is based on the idea that actors submit to the reality of the environment. the culture of resource management to reach a goal is neglected in favor of reality exploitation. in the absence of many investigation resources, such as consulting, opinion section 78 expensive databases, large sophisticated personal network, this little company only adapts to the shape of reality without being able to make it or to change it. questioning works in a cascade, based on sun tzu's precepts selected at random. this channeling of sun tzu's precepts produces creativity in the questioning. it favors the generation of pertinent questions for which the absence of answer becomes an issue. priority is given to these questions, which are disturbing, paradoxical or incongruous. based on these types of questioning, more possible factual hypotheses are produced. then an invalidation process is organized and provides additional outcomes that could not be imagined with a more classical needs assessment. as an example: a file from a real estate office that is specialized in vineyards from which winegrowers shall soon retire and need a soil analysis before they can sell their property. the goal of this approach is contrary to the one that starts by defining the information needs. indeed, it consists of eliminating the search for answers and avoids some cognitive biases such as the confirmation bias. exploitation of the competitive reality prevails over theorizing. it is more a logic of 'conditionconsequence'. this leads the small firm to canvass for new customers conditioned by the results of the investigation. based on this success story and on collaborative explication process in working together, the two authors have structured some guidelines and a list of insights. action items / steps step 1: explicitly identify the unknown elements of the environment by developing a list of questions for which the absence of an answer becomes an issue. step 2: use sun tzu's precepts as stimuli to improve the questions. for each 'inspired' question, produce four or five factual hypothesis. step 3: sun tzu's precepts are left to chance, with no specific order. questions chain themselves in a series, matching them to factual hypothesis. verification gives some answers and allows more precision to the subsequent questions and hypothesis. step 4: divide questions in two types. one for players and sources possessing knowledge of the field investigated. the other one for the topic of the investigation. step 5: a first exploration is prepared and a dead line is given. identify the players with experience in the field who are available and who could possibly answer the critical questions for this step. step 6: prepare the meetings and get in touch with these players. turn the critical questions into precise hypothesis so that implicit knowledge can emerge from the players. step 7: interview the people from the field and consolidate their answers. this last step makes the potential of the situation emerge without pre-conceived ideas. the specificity of the answers helps to bring out operational elements. lasting questions that remain with no answer can also be very enlightening. example from frion a small company was curious to know if its main competitor would be to for sale in the next couple of years. two people gathered around the president of this company to work on this topic of special interest. frion suggested his methodological information resistance (temporarily) method or mir(t): for a short period of time, the team started by methodologically resisting the compulsion of acquiring information on the potential target. instead, the team identified a strategic question symbolizing the precise goal. this question was prepared during a one hour discussion made of a succession of attempts. originally, the question was: 'is our competitor going to be for sale soon?' the second attempt became: 'what are the three main options for our competitor in the next couple of years?' the third attempt turned to: 'how can our company increase its production capacity and secure its current margins within the next five years with internal or external growth?' the team was glad to have moved from the first question to the second and third question. the first question seemed useless by this time. then the team started strategic questioning and identified a list of ten significant questions in order to approach and to encircle the topic to be addressed. two hours were necessary to identify the items to be considered, to give them precision, and to turn them into questions. the president did not take part in this second step until the list of questions was presented to him. two questions were disregarded: one seemed useless for the president and one was already answered. the president had some information he forgot to give to his team and the strategic questioning step gave him the opportunity to discuss this extra information. one question was added. four questions were discussed and slightly modified to reach a more incisive question. the initial question of the goal was reviewed and modified slightly to include adjustments that emerged during the strategic questioning. opinion section 79 then, for each question, a prototype was elaborated. the first one needed one hour. the following ones took approximately fifteen minutes each on average. a list of missing information was identified, profiles of sources people human sources were modelized. accesses ways, means and tools to contact these people were prepared as scenarios. when the first best approaches were identified the most promising ones the team experienced a moment of excitement with laughter and little shouts that frion calls the 'success syndrome.' after a quick estimation of time and effort that would be necessary for this operation, the team realized that resources and time would be too limited. the initial command was reviewed and modified one more time, with an agreement that this final adaptation of the strategy was still very good and was worth doing. the seeking started and sources people were contacted. good surprises emerged from some interviews and some questions from the strategic questioning list were considered unnecessary at this time. finally, the company decided to launch an internal growth plan over the next few years instead of waiting for the competitor to be potentially for sale. frion's approach since information is not necessarily a good thing in general and in a situation of general information overload in particular, a temporary methodological information refusal -or resistanceis used first (frion, 2012). frion's method suggests a temporary actionable strategic questioning or an agile questioning before information (frion, 2009a). the method is made of three subsequent steps. step 1: the command. the command is discussed and reformulated to reach a second then a third version and not taking the first version for granted. the command is a question, as it is action-oriented rather than a list of intelligence requirements that is more knowledge-oriented. with a question, it is usually easier to understand the point of what we are looking for and when we reach this point. one working principle is that 'a leader doesn't clearly know what he wants to start with.' the reformulation is compulsory. step 2: the strategic questioning. instead of analyzing the existing data, one person or a small group of persons tries to find approximately ten right ways to go about the 'problem'. the leader does not take part in the process at the beginning. it starts with brainstorming to identify concerns, refines and adds precision to these concerns, and ends in finalizing precise questions regarding these concerns. we try and ask questions and identify what we would like to learn-what is missing in order to move on. going from step 1 to step 2 can involve a confirmation bias, however the questions in step two are useful to identify what has not been said so far and what has been believed either consciously or unconsciously. the leader is given this list of ten questions. he usually already knows the answer for one of them, is not interested in two of them, may add another question and modifies three or four or them. if the leader only says the questions are ok, the exercise is doomed to fail: he needs to get involved in the questioning process. the question from step 1 is usually modified with a longer description and more precise wording. after a general picture is developed, we dive into a more analytical approach taking the context into consideration. step 3: the information seeking prototype. for each question of step 2, there is an information seeking prototype. it starts with the identification of the most suitable format to give as an answer to address this question. this format can be a short memo, a table, a pie chart, a picture, a conversation with an expert, a verbatim explanation, among others. in this document we intend to produce to fit our leader's cognitive style, we identify three best missing information that would fill this content. for each piece of missing information, we modelize the profile of a source person. we want source persons and not access. source persons are in the best position to help us reformulating a poorly developed question. for each source person, we produce a scenario or a script to approach this person. how is he or is she going to react to my questions? he or she must not tell me a secret and it must be the person in charge for this matter. sometimes we need to ask a portion of the command to figure out the big question without asking for it directly. it is a framework rather than a strict procedure. the idea is to keep it simple and to develop relations between the leader and the task force. through a succession of three main tasks, we produce loops and reviews at different levels. the command evolves throughout the process and it is 'easy' to adjust to the 'new' formulation of the command because we do not invest a lot of time in processing data. at step a1, a2, a3, the scenario goes to the point of two indicators to be met:  subcontracting: a seeking prototype can be subcontracted to someone from our team without major difficulty. thus, it has to be well presented and explained with details.  success syndrome. a physical syndrome of success must be experienced before the interviews start. no success syndrome, no seeking. in fact this approach provides so much preparation that the participant must feel an easiness to act with or without surprise, a bit like the art of archery (herrigel, 1953) with a zen approach. opinion section 80 figure 1: acrie method various constraints are identified or explicitly asked and this situation will provoke ideas to reach the predefined goal. at each step, there is an ambition to formulate or to identify the best question, the best source person, the best access. this first best technique mobilizes the energy of the game of the 'treasure hunt'. this method is particularly adapted to on-the-spot questions and rather not for monitoring purposes. we try and avoid or limit different mistakes and cognitive biases:  the sticky information to start with;  the confirmation bias when a popular information is repeated;  we avoid the validation fallacy, among others. comparison between bruneau and frion there is a long list of similarities, shared beliefs and similar results and another one with differences. major noticeable similarities both approaches aim at improving, skills, business behaviors, and a sustainable activity. both rely heavily on human behaviors. therefore, they need to be taught during an action-training period over a few weeks: 3 days minimum between 3 to 9 weeks for bruneau, and 5 days between 5 and 8 weeks for frion. the maximum impact of the two approaches is at the beginning, whereas in the classical ci approach a major impact can be seen later. the two approaches can be used with a new topic, with people who do not particularly fear of missing out (fomo). missions like canvassing on export or on unknown markets, economic war, innovation, r&d, start-up launching are particularly adapted. small companies or small team inside of larger ones, will benefit from these two approaches, in particular when they face information asymmetry. both approaches can provoke serendipity. with bruneau's methods it can spring at the beginning and with frion, it usually appears at the end, during interviews. in both cases, the main idea is not to find answers, it is rather to have our fist questions contradicted and improved. answers will eventually join. both approaches save the time that is usually spend with the classical competitive intelligence approach to gather a lot of information prior to analysis and distribution. there is no ongoing and tedious monitoring. no software is necessary; the internet is not necessarily used as a cornerstone. electricity is an option: these two approaches can be realized with a place to gather physically in a quiet environment, with a small team. a combat or a game energy will be expected with both approaches. figure 2 shows that both approaches aimed at improving occidental companies. bruneau starts from the oriental prospective and frion from the occidental one. opinion section 81 figure 2: the oriental and occidental prospective major noticeable differences with bruneau's approach, the profile of the participants is key. some people will subscribe to this approach, in particular if they already have a liking for non-deterministic activities such as: art, horse riding or hunting. with frion's approach, there can be a clear time for ending the task because constraints are helping to design the work to be done. different profiles of persons can jump into this approach. when shall we use these two approaches to think and to inform ourselves of intelligence matters? we identify 4 main situations: 1. we ought to observe the potential of the situation 2. we ought to modelize 3. we ought to use both 4. undetermined to keep it simple, we have written a few words for each choice. this synthesis needs to be read as a comparison and not as an eternal truth. how to choose between the two approaches one and only one of these two approaches can be launched at the same time. they are based on very different assumptions and would inevitably clash if used together without great care. people who are visionary, innovators, pioneers and users leaders with naturally enjoy more bruneau's approach. in particular if they come from complex activities where uncertainty is accepted and when structuring is needed. obligation is more based on means with bruneau's approach and more on result with frion's one. as far as the environment is concerned, with bruneau's approach, people consider that the environment is taken as it is whereas with frion's approach, it can be changed. long term issues will probably benefit more from bruneau's approach. in order to use extensively the potential of frion's approach, the leader must be actively participating three times during the process. people who consider that information overload is so present and so annoying that they believe information is not so much a good thing today as it used to be when we didn't have so much of it, these persons might be happy to try the methodological and temporary information resistance mir(t) from frion, as a starting point. people who want to identify and reformulate theirs needs rather than waiting for the best from the environment, will also probably enjoy frion's approach. objectivists and positivists will happily turn to bruneau, and subjectivists and constructivists will turn to frion. surfers will turn to bruneau, planners will turn to frion. none of these two approaches is rejecting the other point of view, still both of them stress differently on as it can be shown in table 4. table 4: trial and error vs. modelling trial and error modelling bruneau 80% 20% frion 20% 80% each author possesses his own justifications to prefer his own approach and none of them tried and convince the other one. both respect and admire the other's approach and enriched their own in the process of this comparison. when one of these two approaches has been experienced with no great success, the other one is probably a good alternative to revamp the motivation as well as a mean to keep on working on the initial mission with a second chance. some situations are more undetermined and do not particularly call for any of these two approaches. when people want to know 'everything', when a very strict administrative process is running, when internet searching is the only possible way to think or to inform oneself, when there is necessity to use many resources from various places in a large organization, when people are not ready to lose one's grip for a short period of time, then the authors recommend not to put much hope in their approaches. opinion section 82 after having described our method, we will turn to the results of this research. results both authors received various level of enthusiastic welcome from many companies. some members of these companies expressed their disagreement with these new approaches but they represent a small chunk of the population studied. although the appreciation was positive, the authors verified that trained people tend to go back to their good old ways if the 'coach' or their leader does not make sure the new approach carries on as shown. possessed by the information both authors of this article observed that the word 'information' was present in many sentences when discussions were going on the topics of thinking and informing oneself. people think first and foremost with or after 'information'. outside information, there seemed to be no way out. therefore, the authors concluded that many people were possessed by information, that is they cannot imagine thinking or informing themselves without or before information. authors regret that information is only considered as a raw material. sun tzu is putting forward the model of 'foreknowledge' in chapter xiii on spies foreknowledge and not information. sun tzu's approach is more postured-centered and knowledgecentered than information-centered. nowadays, there should not only be information to be taken into account. information should not be the center of our professional universe. with information overload in particular, a complex situation is emerging. there is no unique center, there are several ones: we are facing a hubble revolution. information is an important dimension but thinking and informing ourselves cannot be reduced to the single dimension of information. incongruous strategic information this research confirms the results of jones (1989) and baumard (2012) relative to incongruous strategic information. indeed, in the art of war, speech forms such as oxymorons and metaphors provoke unexpected combinations of words and ideas that proved to be useful to stimulate the thinking process. they can be used as starting points for strategic questioning as well as critical questioning. it is the opposite with the use of databases, big data, and internet web 'key-word matching' techniques, that is looking for similarities. various possibilities can be used to monitor the environment, in particular three of them:  the classical one in competitive intelligence is looking around for information, as much as possible, targeting and filtering it;  looking for the unknown through a strategic questioning;  making assumptions and hypothesis; modelizing the environment. before monitoring the environment, one could consider these alternatives and select the most appropriate one with regards to his situation. distancing both authors influenced their audience to dismiss information available to provoke more strategic questioning, at least for a short period of time. bruneau used physical exercises, feelings, poetry or loosening one's grip. frion used weaning or his (temporary) methodological information resistance. these techniques allowed people to focus on to questions rather than the answers. it seemed to reduce the number and the intensity of cognitive biases such as confirmation bias. as baumard states 'dominant logic channels the observation on signals that reinforce our expectations and remove strategic attention from contradictory signals' (baumard, p. 140). the use of sun tzu's art of war appeared to be a good opportunity to encourage people to think differently, and to get out of the closed and simple system of targeting and filtering data. there is a unique and short period of time during which we can think 'before' and 'without' information on a new topic. once we have the first pieces of information on a new topic one cannot pretend to think without being under the influence of what he has just learned. our current information management is usually more concerned with answers than with questions. good surprise the authors have experienced with success the value of being surprised, feeling insecure during a cognitive process, and to commute between one's comfort zone and a lack of comfort. different frameworks, sometimes opposite ones, are the cornerstones of the reform of the strategic thinking as baumard describes it, as well as putting forward atypical behaviors and impertinence (p. 152). 'what defines the strategic dimension is the capacity to reveal what is surprising, what is disturbing, what does not fit to the existing beliefs' (baumard, p. 153). toxicity of information the authors confirm the potential toxicity of information available (taleb, 2005), based on a relatively poor information-centered approach, with not much prior questioning. thinking differently, opinion section 83 questioning ourselves individually and collectively, and questioning the environment, have the potential to enrich our approaches. recently with the information explosion, information has proved to be potentially useful but the amount of information available makes us shift from the interest of accumulating information towards questioning a situation. when small companies face too much information, it is toxic. when they face deceptive information in tiny quantities it can also be toxic. so, small companies very often were inclined to be intoxicated by information or 'infoxicated'. responsibility and accountability theoretically, information can be a good thing and it has often been stated that we need to inform ourselves. but today this theoretical dimension is overtaken by the applied dimension: small companies destroy more value with information than they produce value with it. this has been witnessed most frequently with the proliferation of emails. only a small number of emails are considered useful and creating value whereas the largest proportion of emails are said to be counter-productive, destroying more value than they may create. it is therefore our responsibility to reconsider some weak messages such as 'we need information to think.' both our approaches showed we need to flee from the 'nice to know approach' with large quantities of information to the 'vital to know' based on what is usually missing and really needed. in the future, we could become accountable for the information we lack and for the information we unnecessarily accumulate with no applied outcomes. profitability is it more profitable to possess large amounts of data? the authors interviewed many people and they did not find any convincing direct or indirect link between information possession and profitability. on the other hand, companies mentioned ever growing costs in acquiring, handling, processing, sharing, memorizing, and cleaning data, with and without information technology. structuring uncertainty the authors revealed the known uncertainty and the unknown one. uncertainty was presented as a valuable period of time to explore the potential of a situation (bruneau) or our needs (frion). with different approaches the authors reached the same conclusion: they helped and structured uncertainty for a beneficial effect. how can small companies benefit from sun tzu's art of war precepts? for whom is it vital? companies that do not have many resource nor competences to access a lot of information, can use some precepts from sun tzu's art of war. here is a short list of these situations: during the strategic move of a competitor on a market, when the company is striving to survive, to make an urgent and important decision, to choose a supplier for a key element, to identify a threat, when a local authority is locked up on its territory for a larger scope issue, when a small organization cannot afford to work with a consultant or with an expert. explication of a list of beliefs: when a simple situation happens, when there is no doubt it is a simple situation, then a simple response can be operated. when a situation is not simple, when no automatic procedure can face the situation, we can have recourse to a principle or to a motto, in order to draw a line of conduct without a long period of potentially useless discussions. here is a short list of them that the authors experience with good results.  'i am not certain and it's ok' (bruneau);  'less data is better than more' (frion);  'information is toxic' (taleb);  a large proportion of the success in intelligence is in identifying what and where to look at (bruneau);  processing large amounts of data/information is frequently tiresome and counterproductive (frion);  'don't use the word 'all' and denounce the spirit of 'totality' as not strategic' (frion);  'stop answering, find good questions' (bruneau). these short sentences do not represent the truth but rather illustrate working principles. when in doubt, they can help getting started. if people do not adopt their own motto, when they face complicated situations, they will revamp some motto from their memory, their education, their habits, and these spontaneous mottos could be inappropriate. working on these mottos is useful introspection, although it is easy to stay in the dark for particularly complex situations. sun tzu's art of war is not compulsory. the authors do not pretend their approach can be used unconditionally. the actual informationcentered approach can still be used. the authors identify the following conditions that call for the traditional target-filter input-output approach:  when information exists as a raw material;  when information is available;  when resources are available;  when key-word standardization is acceptable on mature topics;  when context is not very important (there is almost no context on a query on a system);  when continuity of work is preferred to opinion section 84 'made on the spot' thinking;  when there is a logic of result rather than a more philosophical questioning approach;  when the human dimension is negligible;  when a decision is taken in cold blood with facts and only facts;  when rationality is not bounded, without cognitive biases, without errors of judgment;  when we want to know everything;  when information can be simply transformed into knowledge;  when information is unconditionally a good thing and when the progress paradigm applies.  when we can/should work in silos and mutilate the thinking process, such as in particularly secret discussions. as a shortcut, we could say we can use the traditional competitive intelligence discourse when 'more information is better'. totality of information do we need the totality of information to think or to inform ourselves? does sun tzu observe everything? he definitely observes the global environment and he does not reduce his environment to some specific indicators, avoiding the rest in the meantime. since an interview isn't an option, we can only refer to his text. sun tzu used the word 'all' 28 times in his art of war (giles, 1910). apparently, he is in a state of mind as if he wanted to know everything. how does it compare to other intelligence reports? in france, with the five first official report on competitive intelligence, the number of times we can read the word 'all', that is, 'tous, tout, toute, toutes', is 74% per page. with the art of war translated by lionel giles, the percentage to take is 'per word' and not 'per page' because the case of the words is much larger in the art of war. the percentage of 'all' per word, in sun tzu's art of war is 0,255%. it is very similar to 0,264% per word in the first five french ci official reports. table 3: the use of the word 'all' in the art of war vs. other references in intelligence field competitive intelligence police military sun tzu reports / books / manuals 5 french official reports (harbulot 1990, martre 1994, carayon 2004, mongereau 2006, buquen 2012) practice advice on analysis (asso. of chief police officers and nat. policing improvement agency, uk (2008). field manuel 2-22-3, land force (human intelligence collector operations) the art of war % per page (occurrences over p.) 74% per page (543 over 728p.) 52% per page (76 over 145p.) 119% per page (452 over 384p.) 55% per page (28 over 51p.) % per word 0,26% per word (287 543) 0,19% per word (38 564) 0,29 per word (157 123) 0,25 per word (10 968) it seems obvious that the reference to 'all' doesn't bother the different authors in intelligence reports, books or manuals. working in intelligence would therefore consider gathering all the information. it is sometimes clearly written as such, but not in the art of war. still, we identified that the myth of totality is present in the intelligence documents we studied here. the mean for the different documents in table 3, shows that the word 'all' is 0,24% of the words. with 0,25%, sun tzu is just a little bit above the mean. the authors are aware that the idea of totality in occident is different than the one in asia. in particular, the taoist and buddhist philosophies have not much in common with the occidental mode. in asia, the idea of 'all' could be seen as to lose one's grip, whereas the occidental view would rather mean the control. a last result has been obtained, in the shape of a working document presenting and comparing bruneau's approach and frion's, in order to discover sun tzu's work from two different perspectives, to apply a specific approach according to various situations, for a very similar effect. discussion and implications three levels of discussion and implications will be presented, for science, for companies, and for applied intelligence education. opinion section 85 discussion and implications for science scientifically speaking, this article is adding some knowledge to the intercultural study of occidental and oriental business cultures, to the study of small organizations and to intelligence studies. the two authors have humbly expressed their approaches, their methods, their practices and their beliefs. two authors, two very different ways of thinking and still, one common suggestion to use sun tzu's art of war with strategic questioning. what is most noticeable is their suggestions to use sun tzu's art of war by an occidental audience despite the impossible modelling of the masterpiece studied. in particular, when they release the constraint of the information-centric approach of normal sciencex, other disciplines like psychology, sociology, information science and communication, can be enriched by this research. the two authors humbly contribute to a complex approach, by including as fundamental two dimensions in particular: information overload and a more human oriented approach. research would benefit from more frequent and more robust 'points of view' exposed, explained, and discussed. indeed some fundamental beliefs such as 'is information a good thing' is usually not addressed and it can be difficult to follow a scientific article and its operational suggestions when some fundamental issues are kept in an epistemic opacity. there is a tendency to stick to 'information', working on acquiring it and analyzing it. there are rather new approaches that stress communication and not only 'information' (libaert & moinet, 2013) or data science (big data for instance). we subscribe to a more communicational approach and we also reckon the potential for technical and informational approaches for large organizations. still, our main concern in this article is to work on information asymmetry in small organizations. both authors are willing to consider some conventional and unconventional topics. still they include a temporality in their approach so that these topics are brought to the table within a methodology: bruneau will address this concern with an uncomfortable strategic questioning to start with, whereas frion will start by a methodological information resistance (temporarily.) both authors are crediting innovation and the discontinuity of the information age after the industrial age. when topics are inextricable or orthogonal, the authors suggest the use of another thinking mode, a new angle of vision, a new posture, a paradoxical questioning, to stimulate reflection and to create an appropriate new frame of reference. besides the public good that science can represent, discussions and implications for small companies need to be carried on. discussion and implications for small companies sun tzu was in the military and his books are directly dedicated to prepare, to avoid or to direct a war. he did not write a book on peace keeping. the topic of 'war' can be sensitive in some civilian companies and it can be tricky to use war metaphors to convince civilians, in particular antimilitarists. and yet, some lessons can be adapted and drawn from the military. as an example, during special forces trainings, the idea of 'one bullet to kill' is used rather than the image of a 'hail of bullets' with a machine gun. the image of 'one bullet to kill' in a military context could be adapted by 'one vital question to ask'. the figure 'one' should be understood here as a small number, between one and ten approximately. comfort and lack of comfort there is general trend that emphasizes comfort and that tries to eradicate lack of comfort in companies. however in chaining up questions and hypothesis, one can clarify the nature of uncertainty. along the way, with a learning process, uncertainty can vanish or diminish at least. according to bruneau, looking for a physical lack of comfort is a simple and often useful way to explain the gap between the known and the unknown. from a uncomfortable situation, we don't know what will be learned: we don't know what we don't know. it is radically different than starting from a comfortable situation when we know what we know. according to frion, starting from the comfort of a model also necessitates a level discomfort, in particular during the interviews of source people: indeed there is an additional advantage to just receiving an answer during an interview, and that is when the source person calls our question into question. we learn more from a call into question than from an answer! the value is greater, the advance is more significant, the focus defocuses, and the way of thinking is improved. during targeted interviews we are specifically monitoring indicators of physical reaction with the source persons, because these physical reactions are usually spontaneous and reveal indicators before a sentence is said in reply to the question asked. discussion and implications for applied intelligence education a list of concerns and beliefs has been developed that should be taken into consideration in intelligence for business, police and military. still this article is dedicated to business applications. opinion section 86 the discourse on competitive intelligence over the last twenty years was evaluated as a failure for small companies (frion, 2012). many assumptions in this discourse were evaluated as weak or wrong. therefore the discourse did not reach the 'applied' level and remained at the 'theoretical' level. in particular, the discourse ignored information overload and usually emphasized the need for more information without setting any limit apart from focusing and targeting. the authors condemn the conventional discourse based on these false collective beliefs. the use of sun tzu's art of war precepts can be a good opportunity to refresh our view on competitive intelligence in explicit beliefs and assumptions. the two authors consider that intelligence education needs to give more room to the following fundamental topics in particular: the human and cultural dimensions (individually and collectively), the feeling of information overload, the value of questioning over information in some cases. reviewing the chinese strategic mode in the light of these two topics will also contribute to opening up the barriers that have been excluding topics so far. using sun tzu's precepts in a creative process is a way to access the incongruous nature of strategy. in particular, accepting the third-included approach will improve the vision of contradiction that is excessively considered as a bad thing. looking for contradictions could actually improve our understanding of others' needs and we can better understand the information available as well as the missing information. also we contribute to building and fostering a collaborative and interdependent conscience and way to work with different cultures, accepting that someone can think and inform himself differently without being wrong. limits the main limits to this article are presented in the following list of questioning:  ancient chinese language is elliptical and may be hard to understand;  moving from chinese ideograms to an alphabetical system can be puzzling;  military and business share some common topics and also retain specificities;  ancient thinking mode is used for a modern thinking mode: how can we adapt an old discourse to the evolutions in business, in technology and in sociology for instance;  use of poetic style to contribute to a business style;  diversity of translations;  two languages used: the authors of this article are french and the writing is in english. inevitably, some questions remain unanswered when we try and use sun tzu's art of war in today's business live. the two authors humbly recognize this. this research was realized by two french researcherpractitioners and might need to be tested and evaluated by researchers from other countries to see if the results can be replicated. on initial examinations, the two approaches presented by the two authors seem to be in opposition. with a closer look, bruneau's approach is not only observing the potential of the situation and frion's approach is not only about modelling. each of these two approaches needs some conditions to be used. if these conditions are not met, then, these approaches might not be relevant and even worse they could be misleading and out of the responsibility principle for the future. both of the approaches are counter-intuitive. therefore, they can attract the attention of atypical persons like explorers and early adopters of innovation. people who have an artistic sensibility will tend to join in quicker. followers will have more difficulties in adopting them. clearly there is a barrier of entry related to culture, psychology and competences in particular. agreement and disagreement although the two authors reach a common ground and declare together that questioning is better than information, they diverge on the intensity in the way they include some constraints. in particular, bruneau considers that the 'evaluation of needs' will most certainly start with the evaluation of what we know and that will induce cognitive biases such as the confirmation bias. indeed, frion reckons that when identifying needs, the tendency can be seen to keep the investigation within the scope of what is already known. on the contrary, bruneau argues that the incongruous question can make the reflection start from a new point of view, with no obvious preconceived idea, and new assumptions can emerge. however frion also argues that with the mir(t) approach it is possible to limit or to eradicate this concern. both authors shared a real commitment to their different approaches and neither changed his mind. still both authors learned a great deal on the best conditions in which to apply their own approaches, and their limits, and they gained a better methodology for explaining their own point of view. both authors are willing to present the two approaches to use sun tzu's art of war, including information overload, on top of the classical way to use it, ignoring the information explosion. opinion section 87 there is no such thing as a universal method. there are different methods to apply to different situations, and some are more appropriate to small companies that suffer from information asymmetry. the effectiveness of sun tzu's legacy is inversely proportional to the size of the company. the art of war is less relevant to large companies that rely on the action of planning. interestingly enough, small companies are potentially better suited to use sun tzu's work despite their lack of resources and competences. conclusion and research agenda sun tzu is still a valuable source of inspiration today for applied intelligence education. however, we should not apply the occidental representation of his ''foreknowledge'' model in a straightforward manner, before considering the implications of information overload. sun tzu's approach is more postured-centered and knowledge-centered than information-centered. this article presented two accomplished approaches to applied intelligence education including terms, practical details and returns on the experience required to operate them. these two approaches can contribute to intelligence education, with the following main concerns: ease of use, adding value, inexpensive to run, profitability, responsibility and durability. therefore it can become vital for some small organizations to apply it. this article shows that sun tzu's art of war can be used from different points of view for a common apprenticeship more human oriented to think and to inform oneself differently, with alternation of control and loosening one 's grip. small organizations, experiencing uncertainty, lack of time to practice classical competitive intelligence, and facing information asymmetry, will benefit from either of the two approaches presented above. it is often more operational to raise questions than to look for answers. doing so is also more profitable in terms of time and money. it usually brings more value than crawling the web. the two approaches remain very different. bruneau starts from orient and goes to occident whereas frion start from occident and also goes to occident. still the two approaches are very similar regarding fundamentals. both bruneau and frion are dedicated to applied actions for strategic questioning. in companies experiencing information asymmetry, stop answering questions and find good questions: a big question is often better than big data. both of these two approaches can be beneficial and the authors don't believe one is better than the other, nor that only one is good for any given situation. how shall we choose? there are some objective conditions and there is also the idea of a bet. these two approaches are a bet and this bet is usually subconscious. we would be better off if we could consider these two approaches and see if the one we usually choose is aligned to our usual conditions. when it is not, we know that we can have another approach to try. a bit of both approaches can be a good combination in a time line. in the very short term, a temporarily methodological information resistance should be applied first, even during a short period of time, in order to have once and only once the possibility to think 'before' and 'without' information. in a longer term, observing the potential of the situation should be applied, 'with' and 'after information' in order to avoid blind spots. various situations give us different options in using sun tzu's art of war. we need to consider not only information but also other key intelligence influences such as: time, crisis, aim, and information availability, among other things. we need to consider how we inform ourselves and not only how we manage information. we need to inform ourselves more on how we inform ourselves. whatever the method we use, we need to think more about the way we think. the contribution of the authors is more appropriate for small companies in a position of information asymmetry. still they believe that large companies can also adapt these findings to their benefit. it is not a copernican revolution. a more complex revolution is emerging: a hubble revolution. we tested different approaches with companies. we believe many assumptions also hold for police forces and national security. opinion section 88 bibliography baumard philippe (2012), le vide stratégique, cnrs editions, 250 p. ben israel isaac (1989), philosophy and methodology of intelligence: the logic of estimate process, intelligence and national security, vol. 4, n°4 (october), 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he who is skilled in attack flashes forth from the topmost heights of heaven' (chapter 4.) antithetical terms are put together. example of a metaphor: 'military tactics are like unto water; for water in its natural course runs away from high places and hasten downwards. si on war, the way is to avoid what is strong and to strike at what is weak. water shapes is course according to the nature of the ground over which it flows; the soldier works out his victory in relation to the foe whom he is facing. therefore, just as water retains no constant shape, so in warfare there are no constant conditions (chapter 6.) two realities are put together. example of a chiasmus: 'that general is skillful in attack whose opponent does not know what to defend; and he is skillful in defense whose opponent does not know what to attack' (chapter 6.) the use of two consecutive phrases in which the second is an inverted version of the first. example of a comparison: 'a victorious army opposed to a routed one, is as a pound's weight placed in the scale against a single grain' (chapter 4.) ix modelling is defined here as an attempt to list variables, relations and considerations suitable for imitation x kuhn, p. 5 ''normal science, the activity in which most scientists inevitably spend almost all their time, is predicated on the assumption that the scientific community knows what the world is like.'' 41 analysis of competition in chinese automobile industry based on an opinion and sentiment mining system xie xinzhou * , wang qiang ** , chen anqi ** * competitive intelligence and competitiveness research center of peking university, beijing, china. xzxie@pku.edu.cn ** key laboratory of competitive intelligence and innovation evaluation, beijing academy of science and technology, beijing, china. wq.malmsteen@gmail.com received 10 january 2011; received in revised form 12 march 2011; accepted 11 march 2012 abstract: in this paper a methodology for a mining system is introduced. the architecture of the system is based upon what is called opinion and sentiment mining. the mining system is used to analyze competition in the auto industry. the results show the advantages with each of the two cars used for this study. instead of offering theory this is a hands-on approach to help solve specific problems by describing a complex process. keywords: competitive intelligence, opinion mining, chinese automobile industry 1. introduction internet has become the main source for competitive intelligence (ci). the reason is that internet users express their opinion and attitude towards products and images of enterprises online. this paper presents a concept for how to analyze the competition in the automobile industry. the main focus is based on what is called opinion and sentiment mining. a comparative analysis between two auto brands in china is shown as an example. first the role of opinion and sentiment mining in ci will be introduced. further on we present the methodology for this study as well as key issues of opinion and sentiment mining. finally the architecture of the opinion and sentiment mining system and how to use this system to analyze the competition in the auto industry is discussed. 1.1 the role of opinion and sentiment mining in ci as shown in table 1, internet users increased dramatically with the development of internet over the past years. the number of internet users has available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 41-50 https://ojs.hh.se/ 42 reached close to 2 billion, and is about 30% of the world’s population. the number is higher in developed countries and developed areas. (table 1) table 1. world internet users and population statistics users express their thoughts online, making internet the main information distribution and access channel. this provides new opportunities and challenges for the development of ci as a discipline. it opens up user preferences and topics such as:  how do users evaluate the products?  do users like the products?  which properties of the products make users like or dislike them?  how do internet users perceive the image of the enterprise?  which practices of the enterprises do users like or dislike?  how do users choose between different products?  what properties make users buy the products? opinion and sentiment mining provide views and preferences of internet users for different companies. the users’ comments are important for companies and for product development. take windows vista as an example. vista has been selected by time magazine as one of the 10 biggest tech failures. mr. nash, windows vice president of product, confirmed the hesitation to launch the product, based on early users opinions. it said that the service was not being user-friendly, which again influenced other users in a negative way. users of products are an important information source for ci, and their opinions can provide companies with rich contents, making them an important reference for enterprises. 2. the methodology opinion and sentiment mining goes through five major steps as shown in figure 1: figure 1. framework of opinion and sentiment mining 43 1. determine object analysis in the object analysis stage we answer the following questions:  which competitors should be analyzed?  what are the products, brands and services of the competitors? according to our needs, these aspects are defined as our objects. 2. determine information sources in the stage of determining information sources, an alternative information source list can be created, containing authoritative forums, web stations, and blogs. it can be filtered according to the influence and quality of the information. it can also be filtered and complemented with help from industry experts. 3. evaluation index system configuration the third step is to build an evaluation index system to describe the properties of our objects. for example, the index system may contain engine, computer screen, wheel, seat and so on in an auto industry analysis. the index system creates an alternate property list. a sentiment vocabulary need to be built, which describes the “sentiment” of the properties like good, excellent, terrible and so on. in this step, the participation of industry experts who will help us filter and complement the property list and sentiment vocabulary is necessary. the relationship and weight of properties should be determined, after which a complete index system is constructed. 4. collection and integration of information the properties of index systems are used as the query words to retrieve from the information sources. at the same time, the opinion and sentiment words are extracted. this information will be integrated into the opinion and sentiment database. 5. intelligence analysis the final step is to analyze the data. before the analysis, some provisions need to be done, including error correction and elimination of duplicates. then we need to identify the emotion tendency, which can be positive, neutral or negative. some intelligence analysis methods like association, comparative and trend analysis are used to research the competitive situation further. 3. key issues the introduction above is the framework of the methodology, and in almost every step there are some key issues including:  how to select the more authoritative information sources?  how to obtain and integrate the information which is heterogeneous?  how to build index systems which can describe our objects comprehensively?  choose an opinion and sentiment mining algorithm. (1) selection of authoritative information source in the source selection, methods such as web metrics can be used to evaluate the information source, and inputs from industry experts are essential. (2) acquisition and integration of multiple heterogeneous information sources during the acquisition and integration of multiple heterogeneous information, spam and filter noise should be removed through metadata standards, using segmentation algorithms to process unstructured and semi-structured information. (3) evaluation index system for different ci tasks, the index system is different. this step is a semi-automated process and some work must be done manually. in order to improve efficiency, software to help industry experts build or modify the index system was developed. (4) opinion and sentiment mining algorithms the core part of the opinion and sentiment mining system is the algorithms, which include the corpusbased approach, dictionary-based approach, supervised machine learning methods, image segmentation algorithm and other opinion extraction algorithms. during the development of this system, a dictionary-based algorithm is more suitable for chinese information processing, and the accuracy is about 82%. that is acceptable for a commercial operation. 44 4. architecture of opinion and sentiment figure 2. architecture of opinion and sentiment mining system the opinion and sentiment mining system is developed to gather data about opinions and sentiments related to products and services. the system consists of four parts: data acquisition, data pretreatment, data analysis and user interface, as shown in figure 2.  the function of the data acquisition part is information selection, information extraction and information integration;  the function of the data pretreatment is to eliminate duplication of information, do error correction, emotion tendency judgment and so on;  the main task of the data analysis part is to do association research, comparative research and trend research;  the analysis of the result will be shown through different types of terminals. 5. analysis of competition in the chinese auto industry how to use this system to analyze the competition in china’s auto industry will be illustrated through a case study. in this case, peugeot 307 and ford focus (shown as figure 3), are used as examples. both cars have a high selling rate and the competition between them is fierce. we performed an analysis of the competition of the two cars through analyzing the comments of internet users. 45 figure 3. auto products used in the case study (1) information source the information was mainly collected from auto forums using systems and saved information in databases which provided information about the targeted cars. the information sources are shown in table 2. no url logo 1 http://www.autohome.com.cn/ 2 http://www.xcar.com.cn/ 3 http://www.chetx.com/ 4 http://auto.sina.com.cn/ 5 http://auto.qianlong.com/ 6 http://www.ieche.com/ 7 http://auto.sohu.com/ 8 http://auto.huanqiu.com/ 9 http://www.feelcars.com/ table 2. information source 46 (2) evaluation index system the index system was established containing properties, such as sunroof, abs, air-condition and engine. indicators used in the index system are shown in table 3. sunroof chassis power window ebd side airbags cd support center armrest rearview mirror valve structure external audio interfaces center console air-condition spare wheel gps body side molding sun visor mirror speaker brake pedal front brake fuel consumption transmission headlight seat belt alloy wheels head airbags car phone bluetooth rear outlet cnd electric trunk seat vehicle door abs ba central locking keyless go rear lcd screen single-disc dvd cylinder cover qa quality assurance appearance rke rear suspension tire airbags single-disc cd multi-disc cd cylinders max.hp temperature zone control trim ascd steering wheel cylinder bore eas rear side airbags car tv drive mode drl internal hard disk displacement maximum power compression ratio cylinder stator rear head airbags hud sunshade rear brake auto parking front passenger airbags engine maximum torque windshield wiper stroke sport kit view camera air conditioning maximum speed multi-disc dvd power assisted steering computer screen front suspension head lamp tumbler holder fuel way man-machine interactive system others table 3. indicators used in the index system (3) sentences extracted by the system a data set can be obtained through opinion extraction. take peugeot 307 for example (shown in figure 4), the first line is the sentence about appearance, the second is about other properties that is not described in the remaining part, the third is about air-condition and the fourth is about doors. figure 4. sentences extracted by the system (in chinese) 47 (4) attention comparison figure 5 is the comparison of the attention between our targeted cars. attention is measured by the number of posts about the given car. the red line is the attention of ford focus and the green line is for peugeot 307. in this figure it is shown that users pay more attention to ford focus than to the peugeot 307. figure 5. attention comparison between peugeot 307 and ford focus (5) positive comments after identifying the emotional tendency, we summed up the positive comments through which a trend of the users’ positive comments are shown. the number of positive comments for ford focus is higher than for peugeot 307, which indicates that users prefer the ford focus over peugeot 307. this results may help people who want to buy a family car make their decision. it can also attract the attention of staff from peugeot 307 who should like to change the image of the car. figure 6. positive comments of target cars (6) negative comments figure 7 shows the comparison of the negative comments. in this figure we see that the negative comments about these two cars are similar. after combining the positive and the negative analysis, the conclusion is that the negative comments occupy much larger proportions of the users’ comments of peugeot 307 than for ford focus. 48 figure 7. negative comments of target cars (7) skylight comparison a comparison of the selected properties of the two cars is valuable because it tells us why the users like or dislike the products. the comparison in figure 8 shows that users prefer the skylight of peugeot 307 over the skylight of ford focus. figure 8. skylight comparison between target cars 49 figure 9. overall comparison between target cars (8) overall comparison other properties are compared in a similar way achieving this overall result. we see that compared to peugeot 307, users prefer ford focus, but the appearance and trim of the peugeot 307 is preferred to its rival. peugeot 307 is better on ford focus is better on skylight, fuel consumption, seat, appearance, trim, headlight, door, rke, cruise control system, abs, electronic anti-theft, speaker engine, air-condition, rear suspension, tire table 4. comparison result of peugeot 307 and ford focus (9) comparison result we came to the conclusion that the advantages of ford focus is the car’s power and performance, which is embodied in the engine, air-condition, rear suspension and tire. peugeot 307 on the other hand has an advantage in appearance and design which is embodied in the skylight, fuel consumption, seat and so on. peugeot 307 ford focus increase the pr about appearance and design. let consumers understand the importance of vehicle performance. fix engine deficiencies. strengthen the design of appearance and trim. table 5. recommendation according to opinion and sentiment mining 50 6. outlook further research in this field could include:  use opinion and sentiment mining system to perform other industry analysis, such as for cosmetic industry and health industry and see what are best applied areas.  improve the accuracy of the opinion extraction and sentiment judgment;  embed natural language processing algorithms of other languages, which can make this system analyze the information of several languages at the same time. references a hownet word list for sentiment analysis (beta version). retrieved 2010-04-30. available online at url: http://www.keenage.com/html/c_index.html. agarwal, a. & bhattacharyya, p. (2005). sentiment analysis: a new approach for effective use of linguistic knowledge and exploiting similarities in a set of documents to be classified. proceedings of the international conference on natural language processing (icon). chao, l., jian, s., yi, g., xingjun, x., lei, h. & sheng, l. (2009). etc. chinese chunking with maximum entropy models. proceedings of cips-parseval-2009. fuld & company. intelligence software report 2008-2009. london, united kingdom. fuld & company, inc. 2009. gang, l. & qiangbin, d. (2008). an approach based on words numbers for extracting text from web pages. information science, 26(3). hatzivassiloglou, v. & mckeown, k. r. (1997). predicting the semantic orientation of adjectives. proceedings of the 35th annual meeting of acl. internet world stats. available online at url:http://www.internetworldstats.com/stats.ht m. pang, b. & lee, l. (2008). opinion mining and sentiment analysis. foundations and trends in information retrieval, 2(1-2): 1-135. whitelaw, c., garg, n., & argamon, s. (2005). using appraisal groups for sentiment analysis. proceedings of cikm-05, 14th acm international conference on information and knowledge management, bremen, germany. pp. 625–631. zhao, j., xu, h., huang, x., tan, s., liu, k. & zhang, q. (2008). overview of chinese opinion analysis evaluation 2008. proceedings of the first chinese opinion analysis evaluation (coae 2008). pp. 1-20. page 4 editors note vol 6 no 3 editor’s note vol 6, no 3 (2016) what role does technology play for intelligence studies at the start of the 21st century? all articles published in this issue show the role technology plays for intelligence studies in business. we see how patents can be used for competitive and business intelligence, how datamining and software can be used for geoeconomics, how it may measure the success of open source innovation in different cultures, how business intelligence software can be evaluated using fuzzy promethee and how software and the internet are used for economic and industrial espionage. singh writes on geoeconomics on a micro scale, the question about where a business should be located geographically to be economically viable. the author presents a new geospatial methodological approach using census data. arcgis software is used as a geospatial analytics tool for hotspot analysis and for producing maps. deshpande, ahmed, and khode’s article entitled “business intelligence evaluation model in enterprise systems using fuzzy promethee” presents a new model to evaluate business intelligence for enterprise systems. the article by capatina, bleoju, yamazaki and nistor show how strategic intelligence solutions, once performed in a collaborative culture environment, will lead to the improvement of the partners’ managerial competences and will act as enablers for competitive positioning, proving the added-value of the acquired know-how through open innovation practices. the article by maadi, javidnia and khatami shows how patents can be used as a source of information for competitive/business intelligence to highlight the technological trends in the field of energy efficient cooling of data centers. as such it is a good applied example for how patent analysis can be done in a specific industry. the last article entitled “economic and industrial espionage at the start of the 21st century – status quaestionis” is by solberg søilen. it is an attempt to define where the field of economic and industrial espionage is today, more than ten years after the author wrote a dissertation on the subject. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2016 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 6, no 3 (2016) p. 4 open access: freely available at: https://ojs.hh.se/ vol8no2paper2gioti_etal to cite this article: gioti, h., ponis, s.t. and panayiotou, n. (2018) social business intelligence: review and research directions. journal of intelligence studies in business. 8 (2) 23-42. article url: https://ojs.hh.se/index.php/jisib/article/view/308 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index social business intelligence: review and research directions helena giotia, stavros t. ponisb* and nikolaos panayiotoub ahellenic open university, greece; bschool of mechanical engineering, section of industrial management and operations research, national technical university athens, greece; *staponis@central.ntua.gr journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: measuring public acceptance with opinion mining: the case of the energy industry with long-term coal r&d investment projects social business intelligence: review and research directions helena gioti, stavros t. ponis pp. 23-42 and nikolaos panayiotou investigating the competitive intelligence practices of peruvian fresh grapes exporters journal of intelligence studies in business v o l 8 , n o 2 , 2 0 1 8 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 8, no. 2 2018 christophe bisson, maria mercedes pp. 43-61 and tang tong an analysis of ip management strategies of ict companies based on patent filings shabib-ahmed shaikh pp. 62-71 and tarun kumar singhal kalle nuortimo pp. 6-22 business intelligence for social media interaction in the travel industry in indonesia michael yulianto, abba suganda girsang pp. 72-79 and reinert yosua rumagit social business intelligence: review and research directions helena giotia, stavros t. ponisb* and nikolaos panayiotoub a hellenic open university, greece b school of mechanical engineering, section of industrial management and operations research, national technical university athens, greece corresponding author (*): staponis@central.ntua.gr received 14 june 2018 accepted 20 august 2018 abstract social business intelligence (sbi) is a rather novel discipline, emerged in the academic and business literature as a result of the convergence of two distinct research domains: business intelligence (bi) and social media. traditional bi scientists and practitioners, after an inevitable initial shock, are currently discovering and acknowledge the potential of user generated content (ugd) published in social media as an invaluable and inexhaustible source of information capable of supporting a wide range of business activities. the confluence of these two emerging domains is already producing new added value organizational processes and enhanced business capabilities utilized by companies all over the world to effectively harness social media data and analyze them in order to produce added value information such as customer profiles and demographics, search habits, and social behaviors. currently the sbi domain is largely uncharted, characterized by controversial definitions of terms and concepts, fragmented and isolated research efforts, obstacles created by proprietary data, systems and technologies that are not mature yet. this paper aspires to be one of the few -to our knowledge contemporary efforts to explore the sbi scientific field, clarify definitions and concepts, structure the documented research efforts in the area and finally formulate an agenda of future research based on the identification of current research shortcomings and limitations. keywords βig data, business intelligence, review, social business intelligence, social media 1. introduction in the last decade, business intelligence (bi) has proved, beyond any doubt, that it is a rapidly expanding domain in both research and business terms with the number of bi related scientific publications and organizations embracing bi methodologies, techniques, tools and platforms rapidly increasing year by year. this remarkable growth is directly connected with the abundance of customer/user data as a result of increased bandwidth, technological advancements in information systems and mobile applications and the explosion of user generated content mostly materialized by social media and other web 2.0 platforms. nowadays, social media and bi are converging faster than ever before. the confluence of these two emerging domains is already producing new added value organizational processes and enhanced business capabilities utilized by companies all over the world to effectively harness social media data and analyze them in order to produce added value information such as customer profiles and demographics, search habits, and social behaviors. this point of convergence is exactly the scientific area where this paper sets its focus and research efforts, i.e. social business journal of intelligence studies in business vol. 8, no. 2 (2018) pp. 23-42 open access: freely available at: https://ojs.hh.se/ 24 intelligence (sbi), a very new concept trying to capture this transformation of bi systems in the era of big data and amidst the social media revolution. this paper constitutes the third -to our knowledgeeffort to explore the sbi scientific field, clarify definitions and concepts, structure the documented research efforts in the area and finally formulate an agenda of future research based on the identification of current research shortcomings and limitations. in doing so, this paper follows a structured literature review approach utilizing data from one of the most established academic databases in the world, i.e. elsevier’s scopus, and imposing a ‘search and filter’ process based on a carefully selected set of inclusion and exclusion criteria described in detail in the next section. the collected papers were studied thoroughly with the objective to initially eliminate duplicates and critically exclude papers dealing with sbi superficially, fragmentally or not at all. at the end of the literature scrutiny process, 83 papers were selected for further in-depth, full-text examination with the objective to provide the reader with an overview of the main themes and trends covered by the relevant sbi literature. the review process imposed on the 83 papers included in the final review sample produced several interesting findings regarding the current structure of the domain and the necessary prioritization of the research activities for the future. the remainder of this paper is structured as follows. the next section provides a brief theoretical background of the two domains under study, i.e. bi and social media. it aims to provide the necessary information for understanding the importance of big data for bi and the potential impact and transformative nature that social media have on existing bi research and practice with a special focus on user generated content (ugc) and trends related to specific social media platforms. in section 3, the methodological approach to the review and the results of the selection process are presented, followed by the review of the selected papers and the synthesis and taxonomization of the identified research efforts in section 4. finally, section 5 attempts a critical discussion of the review findings in section 4 and concludes with a proposed sbi domain research taxonomy and a suggested list of priorities and directions for future research. 2. background business intelligence (bi) is an “umbrella” term including a wide range of processes, applications and technologies through which various data sources can be gathered, stored, accessed, and analysed in order to gain meaningful information crucial for decisionmaking (olszak, 2016). the term, although growing in popularity recently, was first introduced more than seven decades ago to describe “an intelligence system utilising dataprocessing machines for auto-abstracting, autoencoding and profiling of action points in an organisation” (luhn, 1958). however, only recently it turned to a prevailing field for academics and practitioners and a leading commercial concern for most business organisations. according to chen et al. (2012), there are several reasons explaining this incremented popularity. on the one hand, there is a great opportunity from the rapid expansion of readily available web data sources and on the other, bi tools are becoming more sophisticated, easier to use and find applications in many business processes. meanwhile, intensive competition and global economic pressures set the success barrier too high, leading companies to a continuous fight for improvement, better quality of service (qos) and more productive operations. chaudhuri et al. (2011) underline the declining cost of data storage and acquisition as an additional reason for the extensive proliferation of bi systems. the same applies to hardware, which is becoming more technologically advanced and less expensive, allowing for more powerful architecture of data warehouses. the implementation of bi provides modern organisations, even smes (ponis et al., 2013), with the ability to achieve timely and quality decision-making, which constitutes a crucial prerequisite to build a stable competitive advantage. upon the effective aggregation of “intelligent” data regarding the internal and external business environment, executives are able to take proactive actions preparing their firms for future economic trends and conditions. according to ranjan (2009), bi is like a “crystal ball” in the hands of managers, revealing the best course of action depending on five major parameters: the company’s position in relation to its rivals; the overall strengths and weaknesses of the company; current and future market demographic and economic trends; social, political and regulatory environment; competitions’ 25 decisions and strategy and finally, customer preferences and purchasing patterns. beyond any shadow of doubt, the business landscape in the era of a fast paced and intensively competitive environment is dominated by the struggle to proactively respond to changes, satisfy the increasingly demanding customer needs and timely decision making on the best courses to action. bi and sophisticated analytics provide contemporary enterprises with the tools, methods and corporate mentality required to survive the hard business arena and maintain profitable relationships with the whole value chain surrounding their activities. the concept of participation, on which web 2.0 is based, has also great economic implications and opens up significant new potentials for enterprises (tziralis et al., 2009). in this very demanding and fiercely competitive environment, businesses have found a powerful ally in the face of social media applications and their fast-paced advancement and prevalence in the business and internet ecosystem. social media are online platforms through which users can communicate, share content and connect with each other. since their first appearance in the early 2000s, social media are constantly increasing in numbers, types and popularity. according to the academic literature, social media constitute a reasonable aftereffect of web 2.0, an argument that is summarised in kaplan and haenlein's (2010) definition: “social media is a group of internet-based applications that build on the ideological and technological foundations of web 2.0, which allows the creation and exchange of user-generated content”. however, what clearly distinguishes social media from other web 2.0 applications is the element of social connectivity on a personal level. within such sites, users pre-select their connections and own privacy control over the content they share (heijnen et al., 2013). when it comes to classification, there is no systematic way in which social media can be categorised. indicatively, diamantopoulou et al. (2010), propose a rational social media segmentation based on their major activity (i.e. communication, collaboration, share, rate and opinions’ expression) and purpose of use (leisure, work/business, democratic engagement). kaplan and haenlein (2010), however, suggest a matrix categorisation consisting of two social media dimensions, namely; self-presentation/ self-disclosure and social presence/media richness. the outburst of social media and their increasing popularity has led to an era of fast and immense internet data generation. consequently, the notion of social media analytics and its utilisation in bi systems has become a dominant trend in the entrepreneurial world, due to its huge potential in added-value applications (fan et al., 2015). in the next sections an attempt to structure the current research domain on the intersection of these two disciplines is made, following a systematic literature review approach. 3. research method according to hart (1998) a literature review is an objective, thorough summary and critical analysis of the relevant available research literature on the topic being studied. a review of prior and relative literature of a scientific area is an essential feature of academic progress and theory development, since it creates a solid foundation for understanding the current research status quo, while at the same time highlights underdeveloped or unexplored areas as candidates for future research. the literature review should contain processed information from all available sources, be unbiased to the highest possible extent, be free from jargon terminology and supported by a well-defined and consistent search and selection strategy (hart, 1998). this review examines literature contributions directly addressing sbi, i.e. the use of social media for bi purposes between 2006 and 2016. expanding the search before 2006 was deemed unproductive since the advent of social media in its current form is connected with the launch of facebook in 2004. previous efforts, like friendster and myspace, are not taken into consideration in this study, since they never managed to establish their social media presence and were either defunct (friendster) or forced to pivot their offerings (myspace). in this paper, we utilize a systematic literature review (slr) approach, which is a trustworthy, rigorous and auditable methodology for evaluating and interpreting all available research relevant to a particular research question, topic, area or phenomenon of interest (keele, 2007). the selection process was straightforward. initially, it was decided that the scopus academic database was adequate in order to provide this study with a representative list of relevant contributions, within the context of this paper. second, the 26 list of keywords was kept to a representative minimum by using the strings: “social business intelligence”, “social media and business intelligence”. the keywords were applied to the title, abstract and keywords sections of scrutinized publications included in the scopus database. the search includes publications in scientific journals, peerreviewed conference proceedings and book chapters. the research focus of our approach led us to the decision to eliminate books and editorial reviews. we decided not to exclude publications in peer-reviewed conference proceedings, since sbi is a rather new and emerging scientific area and will be populated by more than a few first stage publications in the conference dissemination channel. other types of publications such as notes and short surveys, are also excluded from the study. the keyword search described above returned 131 papers published from 2006 to 2016, as shown in table 1 and table 2 below. these initial results show that contributions using sbi as a term are scarce (14) implying that, indeed, sbi is a scientific area in its infancy. the collected papers were studied thoroughly with the objective to eliminate duplicates and then critically exclude the ones dealing with sbi issue superficially, fragmentally or not at all, in the case of the publications included in table 3. contributions that were included in the initial sample fulfilling the keyword string criteria but not directly dealing with the study subject were excluded from the database. finally, a sum of 83 relevant papers was selected for in-depth, full-text examination with the objective to provide the reader with an overview of the main themes and trends covered by the relevant sbi literature. table 1 search results for keyword string ‘social business intelligence’. table 2 search results for keyword string “social media and business intelligence”. year of publication source type 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 journal paper 1 1 2 5 6 8 12 16 conference paper 1 2 5 8 8 11 13 11 book chapter 2 3 1 1 sum = 117 papers 2 3 7 15 17 20 25 28 4. literature review 4.1 descriptive analysis as stated in the previous section, the main body of literature identified comprises 83 papers. while 2006 is the first year of publication where contributions were sought, the first published papers found were from the year 2010, further validating the decision not to extend the study period prior to 2006. the allocation of the publications within the researched period (2006-2016) is presented in figure 1. the allocation of papers in the three source types, i.e. journal papers, papers in conference proceedings and book chapters, is presented in figure 2. it is noted that contrary to what was expected there seems to be an even distribution between journal papers (44.6%) and conference year of publication source type 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 journal paper 1 conference paper 2 1 1 4 2 book chapter 1 2 sum = 14 papers 2 1 2 7 2 27 proceedings (44.6%), with book chapters corresponding to the smallest share (10.8%) of the work published on sbi between 2006 and 2016. a closer look in the data set shows that a significant part of the publications (14 documents or 16.9%) originate from the institute of electrical and electronics engineer (ieee) association (10 conference papers, 3 journal papers and 1 book chapter). this is no surprise, since ieee is a leading organization with a wide scientific area coverage including the technical background and information systems infrastructure necessary for sbi to be facilitated in companies and other organizations. in the same direction, association for computing machinery (acm) leads the item count when it comes to publications in peer reviewed scientific journals, with its cross-discipline journal entitled “acm transactions on management information systems” leading the relative list with four publications. in table 3, the number of papers per journal in the dataset is presented. the journals are presented in four categories depending on their main focus and thematic interest, i.e. information systems in management, information and computer science, social networks and miscellaneous. it is interesting to note the absence of any special issues dedicated to sbi and the scarcity of papers’ appearance in more specific domains, such as social networks and journals. 4.2 thematic analysis sbi, as evidenced from the descriptive statistics in the previous section, is a relatively new area, with the first publications referring explicitly to the term dating back to 2010. for those critically standing before the rapid emergence of the subject, sbi is nothing but the next logical step of bi evolution, providing enhanced collaborative capability in the decision-making process of an organization by adding the analytical capability pertaining to social media. for others, sbi is a bi paradigm revolution, especially when combined with the emergence of big data and the ever increasing variety, volume and velocity with which they arrive in front of business systems’ queues for further processing in order to effectively support decision making. needless to say that this duality of perspectives, coupled with the initial triggering of the term from the it business area, has led to a plurality of terms describing sbi, still serving different business needs or marketing of it products, thus creating confusion and reduced clarity on its definition. on the academic front, dinter & lorenz (2012), who according to our knowledge provide the single academic reference attempting to develop a framework of research in the sbi area, along the same lines as this paper, argue that lack of definition clarity for sbi might lie in the ongoing use of diverse related terms, coming mostly from industry literature freely accessible on the web. zeng et al. (2010) provide one of the few available definitions of the term as a set of tools and techniques that “derive actionable information from social media in context rich application settings, in order to develop corresponding decision-making frameworks and provide architectural designs and solution frameworks for existing and new business applications”. in this paper, the term sbi is explored in literature and used as the term of focus for the following study. in that direction, thematic analysis of available literature in the sbi research field is organized into the four following distinct sections: the use of social media data in bi systems, sbi tools and techniques, bi applications in prevalent social media and finally, industry-specific sbi applications. figure 2 distribution of publications per year across the study period. figure 1 allocation of publications in source types. table 3 number of papers per scientific peer-reviewed journal. journal title # of publications main thematic focus acm transactions on management information systems 4 information systems in management decision support systems 1 journal of enterprise information management 1 journal of the university of pardubice 1 management decision 1 production and operations management 1 technology analysis & strategic management 1 journal of decision systems 1 journal of destination marketing & management 1 international journal of services technology and management 1 intelligent systems in accounting, finance and management 1 procedia manufacturing 1 15 information systems 1 information & computer science international journal of computer technology and applications 1 information systems frontiers 1 frontiers in artificial intelligence and applications 1 ieee computer graphics and applications 1 ieee transactions on knowledge and data engineering 1 international journal of engineering & technology 1 ieee transactions on visualization and computer graphics 1 ksii transactions on internet and information systems 1 knowledge and information systems 1 scandinavian journal of information systems 1 knowledge-based systems 1 mobile networks and applications 1 sensors 1 information visualization 1 journal of computer information systems 1 procedia computer science 1 17 journal of internet social networking & virtual communities 1 social networks international journal of sociotechnology and knowledge development 1 social network analysis and mining 1 3 the decision sciences journal of innovative education 1 miscellaneous the scientific world journal 1 2 4.2.1 the use of social media data in bi systems meredith and o’donnell (2010; 2011) and sathyanarayana et al. (2012) were among the first to detect the value of social networks in bi systems, beyond sales and marketing applications. they developed a framework to classify the social media functions that foster the web 2.0 core concepts of user collaboration and contribution, and used it in order to exploit how it can “create more effective and ‘active’ bi applications”. shroff et al. (2011) introduced 29 the term “enterprise information fusion” to describe an emerging bi need across multiple industries, such as manufacturing, insurance and retail. the term includes the publicly available data, derived from social media, that can potentially be of immense business value for the enterprise ecosystem. on the same account, ruhi (2014) attempted to outline the undeniable value of social media analytics, incorporated in a bi perspective. as he explains, the advantage of social media analytics in the business environment is twofold, as it can help organisations “formulate and implement measurement techniques for deriving insights from social media interactions” and, alongside “evaluate the success of their own social media initiatives”. wongthongtham and abu-salin (2015) emphasise the need of evaluation of traditional bi warehouses, which are more focused on handling structured internal enterprise data, in order to support the tremendous volume of valuable, yet unstructured, social media information, such as customer reviews and brand-related posts. finally, ram et al. (2016) conducted a survey in it consultants and managers in various industry sectors of china, in order to prove the paradigm shift that social media have dictated in business strategies globally. with a semi-structured questionnaire, they managed to identify the critical issues in creating value through big data and social media analytics for bi systems. alongside the prevalence of social media in bi applications, several traditional business terms were redefined in academic literature in order to incorporate the new social trends, i.e. social customer relationship management (scrm), digital marketing (luo et al., 2015), voice of customer (voc) and voice of market (vom). bachmann and kantorova (2016) separate the original concept of crm “based rather on face-to-face and offline communication in the physical environment”, from social crm which is mainly conducted “through social networks and relationships within online communities”. beverungen et al. (2014) argue that the global penetration of social networks constitutes a fertile ground for novel crm strategies (rosemann et al., 2012). after introducing the social crm emerging field of research, the authors propose a framework to exploit facebook data in crm strategies and testify its applicability by building management reports for the retail industry. berlanga et al. (2014, 2016) use advances in opinion mining techniques and sentiment analysis to describe the new opportunities arising in the vom and voc concepts in bi applications. as they explain, organisations can take advantage of the wealth of sentiment data in massive social media (e.g., social networks, product review blogs, forums) to ‘listen’ to their customers’ needs and extract valuable business insights. in the same context, lotfy et al. (2016) propose a framework to integrate customer opinion streams extracted from social media, with preexisting corporate data, so as to constitute an integrated data warehouse. according to them, such a multidimensional data base “can perform advanced analytical tasks and lead to better insights that would not have been possible to gain without this integration”. chan et al. (2015) deliberately examine the challenges faced by contemporary bi systems, associated with user-generated content (ugc) derived from social media communication channels. according to them, the available social data is not fully exploited for three main reasons: its unstructured format, its subjective nature and tremendous volume. on that account, they propose a systematic approach to social media data analysis, which counterbalances the aforementioned challenges and captures the real value of online social content for bi applications. likewise, tayouri (2015) also draws attention to risks associated with social media in the corporate environment, highlighting cyber security issues, such as fraud through social media activities, leakage of sensitive business information and damages to a firm’s reputation. hence, he suggests a consistent cyber security training framework supported by social media site monitoring tools, able to assist companies in building a robust sbi strategy by keeping track of correlated malicious activities and threats. 4.2.2 sbi tools and techniques sbi tools and techniques is a predominant research field in academic literature. data visualization tools; online analytical processing (olap); ugc and natural language processing (nlp) techniques; sentiment and opinion mining in the social media context; and user profiling and personalized marketing tools are some of the core thematic areas associated with contemporary sbi practices. 4.3 visual analytics zimmerman et al. (2015), zimmerman & vatrapu (2015) and sigman et al., (2016) 30 highlight the importance of visual analytics (va) toolkits in assisting the interpretation of the unstructured data derived from social media into meaningful business or educational insights. their research project provides a series of visual dashboards able to comprehensively project the analytics related to a brand and its marketing campaigns outcomes. the technical architecture and the specific characteristics of this set of dashboards is further explained and defined in ‘social newsroom’, a prototype va tool for sbi, which was developed to “provide practitioners with user interfaces that can assist them in interpreting social media data and taking decisive actions” (zimmerman et al., 2015). lu et al. (2014) proposed a va toolkit able to handle “noisy, unstructured data and use it for trend analysis and prediction” in sales forecasting and advertisement analysis. their data visualization tool was successfully applied in twitter users, in order to predict movie revenue and ratings. moreover, pu et al. (2016) focused on the valuable geo-location data available in social media applications by introducing the ‘social check-in fingerprinting (sci-fin)’ tool which offers organisations “the opportunity to capture and analyze users’ spatial and temporal behaviors” through social network check-in data. respectively, wen et al. (2016) suggested an alternative va system, called ‘socialradius’ that can interactively explore spatio-temporal features and check-in activities, in a variety of applications, ranging from bi applications to transportation and information recommendation systems. meanwhile, kucher et al. (2014; 2016) presented a va tool for social media textual data that “can be used to investigate stance phenomena and to refine the so-called stance markers collection” with respect to sentiment and certainty. lastly, wu et al. (2014) introduced ‘opinionflow’ a va system detecting opinion propagation patterns and providing gleaned insights in government and bi applications. 4.4 olap techniques, ugc and nlp tools gallinucci et al. (2013; 2015) defined sbi as the “discipline of combining corporate data with user-generated content (ugc) to let decisionmakers improve their business, based on the trends perceived from the environment”. in order to enable contextual topics extraction and aggregation at different levels, they introduced ‘meta-stars’, a model based on ugc and real-time olap techniques. golfarelli (2014) demonstrated an empirical application of a prototype demo of the model in real-world marketing campaigns, in order to prove its technical robustness and methodology. he furthermore presented the available olap solutions, for ugc analysis, that enable decision-makers analyze their business environment based on trends perceived from social media. lin and goh (2011) proposed a least-square (ls) algorithm to model sales performance and business value derived from social network data, by emphasizing the role of social marketer-generated content in influencing ugc sentiment and attitude. the authors actually suggest that there is a positive relationship between “the richness of information embedded in both user-and marketer-generated content and firm sales performance”. finally, ferrara et al. (2014) provide a classification of the available ugc extraction tools in two main categories, namely the enterprise and social web data extraction (wde) tools, through a structured literature review. in a natural language processing (nlp) context, dey et al. (2011) discuss a series of methodologies that can be followed in order to “obtain competitive intelligence from different types of web resources, including social media, using a wide array of text mining techniques”. as they explain, social media do not only provide valuable competition insights but also constitute an open forum where customers express their opinions about different brands’ offerings. sleem-amer et al. (2012) introduce ‘doxa’, a semantic search engine for the french language, with nlp capabilities and social bi application. centering their work on two separate business cases, the authors explain how ‘doxa’ can be applied to discover “hidden patterns in social media data, using rich linguistic resources”. lastly, bjurstrom and plachkinova (2015) propose a controlled natural language that does not require advanced technical skills and can be directly compiled into executable code, for automated social media data extraction. 4.5 sentiment analysis and opinion mining sentiment analysis and opinion mining techniques are two research areas that attracted the academic interest from the early stages of introduction of social media as a powerful leverage for bi systems. upon the rise of web 2.0 and the increasing popularity of social network sites (sns), castellanos et al. 31 (2011), in collaboration with hp and its bi software solutions, introduced ‘lci’, a prototype sentiment analysis platform able to extract sentiment from textual data in realtime. the platform’s interface consisted of multiple chart and visualization options that dynamically changed as soon as new data was ingested, exploiting state-of-the art sentiment analysis algorithms. a year later, yang and shih (2012) proposed a rule-based sentiment analysis (r-sa) technique “to automatically discover interesting and effective rules capable of extracting product features or opinion sentences for a specific product feature”. that way, they offered a means of effective and realtime analysis of the tremendous volume of data, hidden in social media applications, regarding customer reviews about business offerings. in the same direction, liu and yang (2012) developed a buyer behavior prediction technique, using dynamic social network analysis and behavior pattern mining algorithms on e-commerce purchases and viral marketing applications. qazi et al. (2014) focused on the suggestive type of customer reviews, found on online review forums, by combining machine learning techniques and sentiment analysis. their findings suggested that sentiment analysis “achieves maximum performance when employing additional preprocessing in the form of negation handling and target masking, combined with sentiment lexicons”. later, colombo et al. (2015) compared two novel methodologies for sentiment analysis with cross-industry application, by using secondary unstructured textual data from twitter, yelp and cars.com, while kim and jeong (2015) applied their opinion mining methodology in online reviews about the oldest instant noodle snack in korea. finally, nithya and maheswari (2016) implemented a scoring system technique to identify the most promising features of a product offering, consisted of two rating attributes, namely the ‘sentiment score’ and the ‘feature score’. their technique provides managers with valuable insights regarding future demand, brand promotion and product penetration. 4.6 user profiling and personalized marketing tools sbi tools and techniques for customer-centric marketing applications constitute another popular research field in academic circles. personalized advertising messages, based on intelligent user profiling, is top priority for the contemporary business world, striving to survive in a highly competitive and globalized environment. ranjan et al. (2014), using an association rules mining (arm) algorithm, exploit social media data to locate tie-strength networks and active friends, in order to be used as a basis for targeted and relevant advertising campaigns. yang and chen (2014) introduce a novel profile expansion mechanism which enhances the effectiveness of personalized recommendation systems in social bookmarking sites to assist companies in developing “effective service offerings that are better tailored to their customers’ needs” (gronroos, 2008). in a more targeted approach about accurate profiling of social media users, liu et al. (2014; 2015) develop ‘hydra’, a solution framework to identify linkages across multiple social networks and discover correlations between different user profiles. the authors argue that ‘hydra’ can be a profitable addition to existing bi solutions, as it was successfully implemented in a tenmillion data base and correctly identified real user linkage, across seven dominant social network platforms, outperforming “existing state-of-the art algorithms by at least 20% under different settings”. finally, yang and chang (2015) highlight the knowledge gained from social tagging system (also known as folksonomy) as an invaluable asset for enhancement and upgrade of existing bi applications. on that account they employ delicious, an established social bookmarking service, to construct “a statistical-based thesaurus, which is then applied to support personalized document clustering”. their empirical study indicated that such services improve the overall quality of sbi systems, and promote their efficiency in handling targeted marketing applications. 4.6.1 bi applications in prevalent social media a fairly important percentage of existing academic literature on bi focuses on specific social media use-cases and their potential applicability on corresponding systems. tools and techniques able to extract value added data from popular social network platforms, such as twitter and facebook blogs or websites containing customer review content, are among the most preferable research subjects. 4.7 twitter rui and whinston (2011) argue that twitter hides a huge business potential as a base 32 platform for bi applications, given its valuable structural information and the tremendous volume of data flows that are produced by its users in real-time. within this context, they introduced a twitter-based bi system for revenue forecasting, which was successfully implemented in movie box office revenue prediction, achieving remarkable results. seebach et al. (2012) focused on the corporate reputation management area and how firms can use social media intelligence in order to handle reputation threats timely and effectively. by using sentiment and manual content analysis techniques on twitter, regarding posts about a large american bank, they showed “how social media might impact corporate reputation and what organizations can do to prepare themselves”. lee et al. (2013) used twitter as a real-time event detection system for crisis management and bi applications. their proposed framework is able to detect emerging events from social network streams and “accurately extract ontology entities associated with specific events for decision supporting applications”. o’leary (2015) highlights ‘twitter mining’ as an invaluable asset for the majority of fortune 100 companies. in his paper he reviews some of the most prevailing bi applications of twitter data extraction on a prediction, discovery and informative basis. in the same year, arora et al. (2015) applied sentiment analysis tools in order to investigate whether tweets provide a sufficient ground to gain useful insights on competitive brands, using the smart-phone industry. their results showed that although twitter data is rich regarding costumer sentiments, the exposure of different brands varies significantly making their comparison a rather ambiguous task. in a similar approach, chilhare et al (2016) designed a marketingdriven competition analysis tool to “recognize specific areas in which businesses are leading and lagging”. in their paper, they propose a methodology combining nlp techniques and sentiment benchmarks, in order to analyze and structure multilingual twitter data for competitive fmcg companies into meaningful business insights. sijtsma et al. (2016) introduced ‘tweet-viz’, an interactive tool to assist companies in actionable information extraction from unstructured textual twitter data. in their paper, they prove that twitter can provide bi systems, customer preferences, demographics and location data. completing the twitter bi academic cycle, piccialli and jung (2016) summarize the businessgenerated tweet content in three categories; namely informative, advertising or a hybrid of the two. according to their estimations, the hybrid approach increases customer engagement and promotes ugc activity with brand related content. 4.8 facebook according to scholars, facebook, apart from being the most dominant social network on a global basis, contains such a high volume of ugc data that it could also turn to an alternative customer relationship management (crm) platform, replacing traditional in-house corporate software. bygstad and presthus (2013), conducting a case study on two scandinavian airliners' pages on facebook during the ash crisis in april 2010, showed that crm through the platform proved more effective in terms of dynamic interaction and customer engagement. milolidakis et al. (2014), aiming to provide a generic framework for social media data extraction and transformation into meaningful business insights, used facebook fan pages of three greek communication service providers as their case study. according to their findings, facebook includes data capturing of all the standard bi indicators, and moreover provides additional user sentiment information through artifacts features, such as the “like” button, that can turn to intelligent business statistics through visual excavation tools. 4.9 blogs and micro-blogs banerjee and agarwal (2012) used a natureinspired theory to model collective user behavior from blog-originated data in order to explore its application on bi systems. based on swarm intelligence, “where the goal is to accurately model and predict the future behavior of a large population after observing their interactions during a training phase”, they concluded in promising results about blog value in trend prediction applications. meanwhile, kulkarni et al. (2013) draw attention on the importance of social media brand propagation enablers. on that basis, they study the degree of customer engagement through blog contents and the corresponding analytics for bi systems. obradović et al. (2013), in the context of the ‘social media miner’ project combined textual analysis methods with a blog processing technique to “aggregate blog articles of a specific domain from multiple search services, analyze the social 33 authorities of articles and blogs and monitor the attention they receive over time”, in order to provide a highly automated bi tool. lastly, jingjing et al. (2013), using as a reference the chinese micro-blogging platform ‘sina weibo’, conduct a social influence analysis to discover “information retrieval, recommendations and businesses intelligence opportunities”. according to their findings, their proposed framework can overcome difficulties related to volume and complexity found on microblogging platforms and can find numerous applications in bi systems. 4.10 amazon.com social media, based on principles and technologies deriving from the user-centered web 2.0, constitute by definition an open platform where users can express their sentiments, share their knowledge and build a social environment. within this context, consumers exchange their opinions towards different brands, share their experiences through word-of-mouth (wom) and provide their own reviews. the importance of social activity related to brand offerings and the added-value of publicly available customer reviews has naturally attracted the interest of the business and academic world. zhang and chen (2012) studied the business impact of social media and ugc in sales and marketing, by applying text mining techniques and a set of innovative metrics focusing on customer reviews on two popular e-commerce websites, namely bn.com (barnes&noble) and amazon.com. according to their findings, usergenerated reviews have serious effects on product sales and should be consistently processed by bi systems, through carefully selected measures. similarly, ngo-ye and sinha (2012) argue that customer-generated reviews in e-marketplaces “are playing an increasingly important role in disseminating information, facilitating trust, and promoting commerce”. on that account, they developed an amazon.com based tool to automatically identify the most important reviews and provide meaningful customer feedback. finally, zhang et al. (2013) in an attempt to further explain how wom is affecting product sales, they combined network analysis with textual sentiment mining techniques to build product-comparison networks consisted of customer reviews. their empirical study on amazon.com suggests that it is imperative for firms to understand and manipulate the wom process taking place in social media, in order to survive in the increasingly competitive online landscape. 4.10.1 industry-specific sbi applications the integration of social media analytics in bi systems is a need soon realized both by organisations and academia. sbi tools and techniques are not limited in a specific area but have rather a cross-industry application, a fact that is clearly reflected in the existing literature. heijnen et al. (2013) argue that the potential of social medial data is invaluable for multiple facets of bi systems, yet it is “largely unused by companies, and it remains unclear what data can be useful for which industry sectors”. their findings indicate that key performance indicators typically differ between industry sectors and therefore sbi metrics should accordingly adapt to their corresponding needs. the need to approach the matter from industry-specific perspectives led to a series of academic publications focusing on distinct sectors: education, automotive, pharmaceutical, cosmetics, tourism, fashion, government and politics. 4.11 education moedeen and jeerooburkhan (2016) focus on the higher education sector to explore how “social media strategies can be aligned with business strategies to help universities gain a competitive edge”. using the facebook page of a university as their case study, they argue that higher education organizations pay attention solely to advertising and reputation management aspects, while neglecting other business objectives that could be met through a holistic sbi application. 4.12 government and politics bendler et al. (2014) associate static environmental characteristics with dynamic user-generated content from social media to explain and predict criminal activity in metropolitan areas. by combining traditional statistics, such as zero-inflated poisson regression and geographically weighted regression with social media data, they provide a framework that enhances the accuracy of criminal activity forecasting. meanwhile, chung et al. (2014) developed an approach to pinpoint opinion leaders in social networking sites that could be approached by policy makers to collaborate and “bring about change in the communities and the general public welfare”. in a more generic approach, golfarelli 34 (2014; 2015) studies sbi options in politics. according to him, processing of user-generated content through a robust sbi system could prove invaluable for political entities in order to align their governmental decisions with environmental trends and public opinion. finally, beigi et al. (2016) explore crisis and disaster management through sentiment analysis and social media visual analytics. according to them, individual posts in social media about natural disasters and emergencies can be used as inputs in governmental sbi systems “to improve situational awareness and crisis management (…) while assisting in locating people who are in specific need during emergency situations”. 4.13 automotive abrahams et al. (2012) introduce a decision support technique for vehicle quality management designed to identify and prioritise automotive defects, deriving from reviews in vehicle enthusiasts’ online forums. they suggest that conventional sentiment analysis does not suffice to efficiently detect customer complaints and therefore, bi systems should incorporate advanced text mining algorithms specifically designed for social media applications. baur et al. (2015) also focus on the vehicle industry by exploring chinese auto forums as a new proactive means of market research. according to them, although the increasing popularity of social media offers a fertile ground for novel marketing techniques, there is a number of arising challenges to be confronted, namely the tremendous volume of posts, their unstructured format and the wide range of user languages requiring complex natural language processing techniques. on that basis, they propose ‘marketminer’ a novel framework for “search, integration, and analysis of crosslanguage user-generated content”, specifically designed for the competitive automotive sector. one year later, baur (2016) examines alternative applications for ‘marketminer’ in public administrative bodies and commercial firms. his results indicate that the tool can significantly improve the processing of multisource and multi-language social media generated content and apply to cross-industry sbi systems. 4.14 pharmaceutical according to basset et al. (2012) the social media sphere is a challenging environment for the pharmaceutical industry, as it is associated with a number of ethical and legal issues imposed by governments globally. however, sbi systems can prove valuable to such an antagonistic sector mainly for marketing, customer relationship management and competition monitoring applications. bell and shirzad (2013a; 2013b) propose a social media data extraction model to assist pharmaceutical companies to effectively position themselves in new marketplaces. according to them, social media networks offer a channel of communication for business-to-business environments and can enable companies to connect with all the actors of their value chain (i.e. customers, partners and even competitors) on a real-time, global basis. finally, he et al. (2016) using the three biggest drugstore chains in us as their case-study, suggest a model for competitive strategy formulation by applying quantitative analysis, sentiment analysis and text-mining techniques in social media ugc content. their findings indicate that such tools can prove invaluable if adopted by existing bi systems. 4.15 tourism online social networks, and web 2.0 applications in general, are rapidly becoming a significant marketing channel for the tourist industry which is challenged by new and emerging business models utilizing social media and other crowd sourcing and shared economy applications, such as airbnb. in this new and turbulent environment, social bi can be a source of critical competitive advantage in a very demanding and customer-service intensive industry such as tourism. in that direction, palacios-marqués et al. (2015) study the effect of online social networks on firm performance and explore ways of adding value to established market competences. the authors conduct a large survey in one of the world’s largest tourist destination, spain, with the participation of top managers from 197 fourand five-star hospitality firms. their results show that social bi has a significant positive relationship with firm performance by enhancing market intelligence and knowledge management competences, thus leading to the acquisition of a significant advantage over the competition. remaining in the same geographic territory but penetrating one layer deeper in the social bi area, marine-roig and clave (2015) study the usefulness and applicability of big data analytics for the industry and specifically for a smart city tourist destination, barcelona. the authors 35 study the online image of the city by analyzing more than a hundred thousand travel blogs and online travel reviews by people who have visited the destination in the last decade. by extracting bi through these large volumes of user generated content, the authors provide an efficient decision support tool for industry executives and city officials to develop and evaluate competition, marketing, branding and positioning strategies and policies, which will enhance the city’s image as a smart tourist destination. 4.16 fashion and luxury the fashion and luxury products industry has for many years resisted the adoption of the ecommerce channel, since they associated anything digital with malpractices such as discounting, counterfeiting and brand dilution. this is not the case anymore and currently emblematic brands, such as ferragamo, have entered the e-market arena, which according to a report from mckinsey and altagamma (2015) has reached €14 billion in 2014, a 50% increase from 2013. this change has created the need for managing user-generated content in order to better understand customer profiles, identify preferences and determine trends, with the latter playing a crucial role for product development of companies in the fashion industry. in that direction, petychakis et al. (2016) turn their research focus on a very important aspect of social media analysis, which is the identification of opinion makers within the social media ecosystem, the monitoring of their behavior and the extraction of targeted campaigns utilizing their media presence. the authors present a platform providing marketers and product designers with data analytic services for influencer identification and trend analysis and evaluate it in a single case from the fashion industry. fourati-jamoussi (2015) explores the concept of e-reputation by applying bi practices to analyze the social media presence of four companies from the organic cosmetics industry. the author attempts to compare the reputation of the participating brands by using different monitoring tools, conducts user profiling for each brand and finally proposes recommendations for enhancing marketing strategies. 5. conclusions in this paper 83 papers, which were published in the period from 2006 to 2016 dealing with sbi concept, management, tools and applications, were collected. the review of these papers and the analysis of their content, presented in the previous chapter, produced useful information, in order to synthesize a comprehensive research agenda for sbi including major directions and identified shortcomings that seem to shape the future of research in this area. the core focus of the research, as expected, seems to be the unearthing of the currently unused, to its full potential, value of sbi and put it to good use for the benefit of businesses and organizations around the globe. in that direction, academic literature in the novel research field of sbi is essentially developed around three main pillars of research orientation. the first pillar attempts to provide answers to the question ‘what is sbi and how can it help a business or organization”, putting sbi’s business validation and real-life applications in the epicenter of research, thus given the title ‘business descriptive’. papers in this pillar are attempting to highlight the prevalent acceptance of social media as a source of business value and the parallel expanded usage of bi systems through social media data for multiple operations within companies, in a variety of industry-specific applications. in doing so, they provide mostly definitions, methods, models and frameworks, which support a wide range of corporate activities, spanning but not limited to strategic decisionmaking functions, business processes’ optimization, operational efficiency improvement and revenue management. within this pillar, one can identify two discrete waves of publications that can be organized together based on their focus and objectives. the first identified wave of publications within the business descriptive pillar deals mostly with determining the current status quo of bi in contemporary organizations and provides means of expanding its reach through the exploitation of social media. the first step in this direction is the identification and validation of social media potential and functionalities to act as a consistent bi decision-making support tool through solid argumentation and empirical tools like surveying experts in interested business areas. at the same time, the second wave of publications attempts to deal with sbi by exploring the enhanced capabilities that it gives to traditional bi systems and how these can be rethought and restructured in order to be ready to absorb and process the abundance and large variety of data that social media 36 produce. what is interesting at this point is the determination of sbi usefulness and transformative impact on other established business functions such as marketing and customer relationship management (crm). the introduction of novel marketing and crm strategies such as social crm, vom and voc as a result of information harnessed by sbi practices is explored in depth by many publications and specific algorithmic sbi techniques and tools, e.g. opinion mining, sentiment mining, are mentioned as playing a critical role for business success and competitive advantage. finally, the main barriers/shortcomings identified in this pillar of literature are the following: probably the most important issue identified is that of data security and privacy. there are major concerns for all levels of data usage, i.e. data creators (users), data suppliers (e.g. facebook or telco companies) and businesses in need of the data. what makes the situation even more complicated is the fragmentation of legislation between continents and nations, which make compliance a cumbersome and sensitive task, especially in the case of companies operating at a global level. the second most important issue identified in this pillar of literature is data governance by businesses. in other words, the ability of companies to streamline their processes and systems in order to provide more accurate information, achieve increased visibility and in essence better analytics. there seems to be a consensus that much more is needed to be accomplished in this area. finally, the third prominent issue identified in this pillar is process governance. the huge impact of social media data on current established business processes and its transformative effect on every-day operations, coupled with the need for the use of more advanced analytical systems, creates the need for research on business process management and reevaluation of traditional processes and their efficient transformation. the second pillar attempts to reveal ‘under the hood’ knowledge and answer the question “how does sbi work”. it sets technical implementation in the epicenter of research, thus this pillar is given the title, ‘technical descriptive’. papers in this pillar provide mostly technical information on algorithms, techniques and tools that are used in order for sbi to process social media data and produce meaningful information to be used directly or passed for further processing by traditional bi systems. the prevalent techniques, which seem to dominate the research interest in this pillar are those dealing with three major issues of sbi at the technical level: user profiling, user (customer) voice translation into actionable information and data visualization. the main shortcomings identified in this pillar of literature are the following: there is an increased demand for new ai algorithms for the automation of the user generated content extraction and translation procedure. current algorithmic efforts in research are many. still their validation in actual commercial environments does not commensurate with the materialized research. the need for a switch towards an ai based, data-scientist agnostic sbi process is evident in the literature. user profiling and the underlying targeted marketing and personalized recommender systems are very important issues in the sbi literature especially for companies that are forced to enter the paid advertising arena by increased competition and the need to sustain profitability. although profiling models and algorithms present a rapid increase in numbers and variety of approaches there are still several unexplored areas in profiling that need intensified research and investments. data visualization has seen many advances in the last few years with the emergence of the dashboard logic in data presentation and display. although there is a fair number of social media tools already providing services like data collection, aggregation and analysis into key performance indicators, there is still a deficiency in visualizations, especially when it comes to standards and design principles, thus making the support from data scientists and supplementary systems mandatory. finally, the third trend attempts to answer the question “does sbi work in real life?” real 37 life cases of sbi applications in practice are the focus of research in this pillar, which thus is given the title “case descriptive”. two discrete waves of publications can be identified. the first focuses on industry-specific applications and describes how sbi can provide valuable services for businesses operating in these industries. in doing so, papers in this pillar explore successful applications of sbi in real business cases, highlighting the crossindustrial nature of sbi and its potential impact for a variety of industries and governmental organizations. specifically, they provide focus on the impact of sbi in traditional business models and processes and its operational fit in order to support industryparticular requirements. the second wave of publications includes papers focusing on specific social media use-cases, with twitter and facebook being the platforms most widely used as data providers and application test beds. tools and techniques able to extract value added data from popular social network platforms, blogs or websites containing customer review content, are among the most preferable research subjects. the main shortcomings identified in this pillar of literature are the following: utilizing sbi to support real-life cases is a cumbersome task demanding a holistic approach, including technological and organizational aspects, leading to a complex transition requiring high executive competences supported by a global strategy. this is not the case dealt within the publications studied in this pillar. empirical evidence provided is rather fragmented and cases seem isolated from the business ‘big picture’, while connection with ‘bottom line’ metrics is loose. there is a, to some point justifiable, strong focus of sbi research on social networking giants, like facebook and twitter. still, there is an abundance of social networking sites and other emerging social media business models like snapchat, vine and reddit for example, for which the possibility of more open data extraction and enhanced algorithmic testing could take place, that are currently not sufficiently explored. at this point, a research agenda can be formed including eight discrete research directions, each one dealing with the shortcomings identified in literature and discussed previously in this section. in table 4, a summary of the literature review’s main findings is presented. the three main pillars’ research offerings are shortly described and specific publications are assigned to each one of the pillars in accordance with their number in the reference list at the end of this assignment. the eight research directions comprising the future research agenda for sbi are categorized per pillar and presented in table 4. finally, it has to be noted that adoption of this paper’s findings should take into account the inherent limitations of this study, which are: the big difference between current and published capabilities of academia, especially coupled with the fast pace of the sbi scientific field. the author is certain that several research efforts providing innovative approaches and empirical use table 4 sbi future research directions. title (main research offerings) publications (by ref. number) first pillar business descriptive (definitions, methods, models & frameworks) rd1: data security & privacy rd2: data governance rd3: process governance [116], [201], [19 ], [20 ], [55], [163], [128], [129], [173], [166], [22], [190], [30], [158], [9], [169], [120 ]. second pillar technical descriptive (algorithms, techniques and tools) rd4: improvement / development of new ai algorithms sbi process automation rd5: user profiling rd6: data visualization [210 ], [211], [64], [211], [212], [65], [110], [52], [28], [179], [114], [204], [202], [118], [160], [206], [157], [103[, [113], [112], [205], [96], [101], [39], [25], [156], [139], [199], [103], [176], [92]. third pillar case descriptive (empirical evidence / industry focus & social media focus) rd7: holistic sbi approaches enhanced validation rd8: extend research coverage in social media [135], [71], [167], [1], [12], [138], [11], [210], [171], [16], [17], [107], [27], [102], [80], [209], [91], [142], [131], [18], [37], [63], [122], [140], [13], [14], [8], [145], research directions 38 cases highlighting novel applications of techniques do exist, that are either in development or already finished but yet unpublished. unfortunately, the academic publishing pipeline has a lead time of six to eighteen months in some cases and work in progress papers are relatively low in numbers, thus creating problems to researchers who conduct a literature review. furthermore, significant research on sbi is done by or on behalf of big players in this area, such as social media platforms, big advertising companies and global brands. these studies are based on home-grown methodologies, use proprietary tools and perhaps focal datasets and thus never made public, making the task of the researcher who conducts the review even more difficult. finally, the reader, before adopting the results of this study, has to consider its methodological limitations, related to the selection of the academic library, i.e. elsevier’s scopus, the inclusion of specific source types, i.e. peer reviewed journal papers, conference proceedings and book chapters and finally the selection of the search keywords for conducting the review. 6. references abrahams, a.s., jiao, j., wang, g.a. and fan, w. 2012. vehicle defect discovery from social media. decision support systems, 54(1), 87-97. arora, d., li, k.f. and neville, s.w. 2015. consumers' sentiment analysis of popular phone brands and operating system preference using twitter data: a feasibility study. in: proceedings of advanced information networking and applications (aina) ieee 29th international conference, pp. 680-686. bachmann, p. and kantorová, k. 2016. from customer orientation to social crm. new insights from central europe. scientific papers of the university of pardubice, series d, faculty of economics and administration, 36/2016. banerjee, s. and agarwal, n. 2012. analyzing 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(2016) study on competitive intelligence in israel: 2016 update. journal of intelligence studies in business. 6 (2) 5-16. article url: https://ojs.hh.se/index.php/jisib/article/view/156 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index study on competitive intelligence in israel: 2016 update avner barneaa aschool of business administration, the netanya academic college, israel; avnerpro@netvision.net.il journal of intelligence studies in business please scroll down for article study on competitive intelligence in israel: 2016 update avner barneaa aschool of business administration, the netanya academic college, israel *corresponding author: avnerpro@netvision.net.il received 13 march 2016; accepted 20 august 2016 abstract this paper investigates the state of competitive intelligence among israeli firms in 2014. the methodology used was self completion questionnaires, which were responded to in may and june of 2016. a response rate of 26% was achieved with 39 questionnaires returned of the 69 questionnaires that were sent out to 65 local firms, most of them with an annual turnover of greater than 100 million usd. the results indicated that there were insignificant changes in the use of competitive intelligence in israel in the last 10 years, since a survey conducted in 2006. initially it looked as if the use of competitive intelligence was expanding, but the actual findings shows that the contribution of competitive intelligence to the decision making process was not progressing as it was expected to and there were difficulties in making competitive intelligence an integral part of the decision-making process and having it reach an influential position. the results indicated that the recent global downturn evidently had only a minimal effect on the competitive intelligence scheme and in 75% of the firms there were actually almost no changes in the competitive intelligence programs. clearly, competitive intelligence was primarily a tool used by the larger organizations and most of the firms that responded (60%), were among those who competed in the global markets. i have also attempted to look into the quality attributes of competitive intelligence performance, and it seemed that the low use of analytical tools was an indicator that we cannot ignore. only 33% of the competitive intelligence professionals were using these tools regularly as part of their analysis work and in presenting their findings. keywords business strategy, ci in israel, competitive intelligence, israeli firms 1. introduction business research literature deals extensively with competition between firms, and global competition has made the competition a more dynamic environment (grant 2005, chan kim & mauborgne 2004). business strategy literature deals with the early detection of competitors' intentions and capabilities (fellman & post 2010) and recognition strategies of their objectives, strengths and weaknesses combined with trends in the markets and among consumers. hughes, le bon & rapp (2013) explain that they all are critical components in the success of corporations. a study of 800 firms showed that an important factor in the success of companies is the special expertise of customers' requirements and competitors' moves (nunes & breene, 2011). the importance of monitoring the business environment (external environment) arises with respect to rapid technological developments (grant 2005). it is impossible to win competition strategy (strategic competition) without introducing competitors, warning of threats (henderson, 1981) and analyzing information on the competition environment (fleisher, right & allard 2008; chernev & kotler 2012). the basis for competitive intelligence was the need for environmental scanning of information about activities that happen around firms and have an impact on their journal of intelligence studies in business vol. 6, no. 2 (2016) pp. 5-16 open access: freely available at: https://ojs.hh.se/ 6 performance (aguilar 1967). the increase of environmental uncertainty gradually strengthened the demand for information processing activities within firms (daft & macintosh 1981; culnan 1983). firms' skills to adjust to market conditions largely rely on their competences in processing relevant information, mainly on market conditions. broud (2006) went on to connect competitive intelligence and environmental scanning in the process of building scanning capabilities to affiliate firms' strategy with important changes in the external environment. competitive intelligence (ci) is a process involving the gathering, analyzing and communicating of environmental information to assist strategic decisionmaking (dishman & calof 2007). although there are calls (hoppe 2015) to move away from a narrow perspective of the practice to pursue a broader understanding of intelligence as an organizational discipline, the above definition of ci is widely recognized by most scholars who are doing research on competitive intelligence and related areas like business strategy and information sciences. intelligence as part of strategy, (solberg søilen 2015) mainly marketing as an instrument to increase a firm's competitiveness in its strategic planning process, has been long recognized (montgomery & weinberg 1979) and is also backed strongly by porter (1979, 1980). many scholars have proposed theories about intelligence processes in business. from environmental scanning (aguilar 1967), strategic intelligence (montgomery & weinberg 1979), competitor analysis (ghoshal & westney 1991) and market intelligence (maltz & kohli 1996), day and schoemaker (2006) brought forward the concept of "peripheral vision" which is near to the concept of ci in its broader sense. most works (bulger 2016) look at ci as an essential requirement for better strategic planning and execution. the literature shows evidently that ci is not only about competition but covering the whole business environment. more firms were aware that one of the keys to success was intimate knowledge of the global markets (bulley, baku & allan 2014) by ongoing monitoring of the changes, and it was not enough to offer advanced technological solutions (prescott 1999) and prevent business failures as a result of intelligence downfalls in business (tsitoura & stephens 2012). many corporations already understood that ci (blenkhorn & fleisher 2005) can be of a great help in reaching a competitive advantage and sustaining it (global intelligence alliance 2009, 2011). it is evident that companies with poor information about competitors are stuck being reactive (le bon 2013). contrary to findings by reinmoeller and ansari (2016), ci added value can be assessed mostly by strategic planning and decision making (hambrick 1982; fingold, carlucci & page 2005; grant 2005) although it is not an easy task as the ci discipline is broadly based on qualitative evaluation. the growth of the israeli economy was highly dependent on its exports, mainly hightechnology industries and the ability to develop new technologies and applications that would be attractive in the global markets (central bureau of statistics 2014). the use of ci in israel can be found mostly in large-size companies. it was moving forward slowly, according to recent studies (barnea 2006, 2009). it seems that the discipline of ci in israel is still looking for its position of influence, since it is focused on management practices and fulfilling the immediate needs of the corporation rather than working closely with the strategic planning and the senior decision-makers. it is largely focused on formal intelligence activity through ci units, while there are those who believe (hoppe 2015) that in most organizations intelligence is constructed informally. 2. past studies on competitive intelligence in israel there were a few studies on competitive intelligence in israel conducted in previous years. the first one was conducted in 2003 (barnea 2003) and was published in israel (in hebrew) which was followed by an english version that was also updated (barnea 2004). the next ones were published in 2004 (belkine 2004; shirtz 2004). both studies showed that competitive intelligence in israel was in its early stages, more in the stage of ad hoc approaches, but they identified the move towards established activity. it pointed towards the potential of the progress of competitive intelligence in israel as the needs were obsevered. the next study was published in 2006. it was titled "why start-up companies failed to adopt competitive intelligence" (barnea 2006). the key conclusion was that the absence of competitive intelligence awareness was one of the main reasons why israeli start-up companies failed in the global markets during 7 the 1990s. the author has offered different ways to change the situation: one of the primary ways was to appoint a senior executive to take care of this issue, as monitoring the international markets was a critical factor for such companies. the author has recommended also that the investment ventures that usually heavily support these initiatives encourage these ideas and act to implement them, and by doing so they could save a lot of money and help to make better decisions. the next study was concluded in 2006 (barnea 2006). its focus was on competitive intelligence in large israeli exporters. the key findings were that ci was used by almost 50% of the companies and that ci professionals were succeeding in bringing added value through their activities, mainly tactical insights. the study stated that ad hoc solutions were still common but there was a growing understanding of the need of ci expertise. the findings showed that the use of open source intelligence (osint) was wide while the use of primary sources was limited, mainly due to a lack of awareness of its potential. another important result was that the use of expert tools (i.e. software) was very rare, while the expectations of the developers of such tools were higher, as israel had a strong orientation toward using information technology tools. in 2008 and 2009, two short studies on ci in israel by barnea were published (in hebrew) in two israeli management magazines. the key findings were that ci in israel is moving forward slowly while the main obstacle is the lack of awareness by senior executives who expect to present their intelligence needs and the needs of other units. the conclusion was that without their firm support the creation of durable intelligence capabilities will be difficult. another study that has looked at ci in israel mainly from the aspects of using expert tools (barnea 2009) has revealed that "local firms were not prepared to invest in new ci tools that would enable ci professionals to perform better. as a result, most ci professionals have to continue using generic tools such as office (microsoft), which offers unsatisfactory solutions to their ci program needs". and also that "the high level ci solution has not reached its potential target market due to a lack of support by senior executives who did not see it as critical to move ci forward in their firms". in 2015, research on the use of open source intelligence by israeli firms (markovich 2015) showed that there is an intensive use of these sources, but the added value to the corporate decision-making process was low. it overlooked the entire picture of ci in the israeli business scene. it was therefore challenging to conduct a new study of ci in israeli companies, especially in the time after the global downturn (2008/9). the objective was to compare the results with previous studies, to evaluate the latest findings to see what still has to be done and to try to indicate the directions that ci in israel may have to take in order to strengthen its position. research conducted by the federation of the israeli economic organizations (2011), showed that the global financial crisis almost had limited affect on israeli global corporations. the depression moderated the growth of israeli companies abroad. despite the economic crisis, israeli multinational companies showed impressive economic strength. research objectives: 1. to evaluate the existing use of competitive intelligence within israeli companies, primarily large companies with annual revenues of 100 million usdand above. 2. to compare the findings with previous studies and to recommend what has to be done in the future to support the use of ci. 3. methodology the study was based on a questionnaire of 25 questions that was sent out to 65 israeli companies. the directory of the companies included in this research was based on records of participants in competitive intelligence conferences held in israel in the last five years. the questionnaire was divided into six sections: 1. general questions about each firm, 2. questions about the characteristics of the competition in the relevant industry, 3. how ci is conducted, 4. the value that ci was delivering to the firm, 5. the state of the competition in the recent global downturn 6. recent changes in the mode of ci activity. the data was collected by self-completion questionnaires. they were sent directly to ci 8 managers that have been identified in each company. sixty-nine questionnaires were sent out. thirty-nine completed questionnaires (56%) were received. these questionnaires were analyzed. the high rate of response is related to my personal acquaintances with the responders. the actual meaning was that all companies studied had active ci functions. 4. limitations the limitations of this study were as follows: the results were based only on the self experience of the ci managers rather than on their superiors. it was impossible to know how much these replies represented the view of senior executives in these companies about some of the questions, for example the added value of ci. 5. data analysis the profiles of companies that responded and participated in this study by sector are shown in figures 1-5. figure 1 sectors (industry type) of responding companies. figure 2 annual revenue (2013) by company. a company with annual revenues exceeding 100 million usd (100 m$) is usually considered to be a large corporation in israel. figure 3 number of employees by company. figure 4 primary markets where the companies compete. a few companies operate in both markets: global and local. the questionnaire instructed the respondent to indicate the primary market. figure 5 where ci is done (internally or externally) all ci managers that responded indicated that their ci units were operating in –house, meaning that they were part of the company's structure and located in the company's premises and thus interacted continuously with its people. none of these units was operating externally. obviously, many of these companies were receiving input from external suppliers, mainly information gathered from public domains. in comparison, the "global study on large companies" (global intelligence alliance, 2009) has stated that 71% of the intelligence activities were produced within the company. 9 figure 6 the size of the ci unit: number of employees per unit. the results in figure 6 indicate that the size of the competitive intelligence units in israel were usually small. in 90% of the firms the ci units were two people or less. there were no differences in the size of the units between companies who focused on the local market and those that were competing in the global markets. the hypothesis that israeli companies in the global market needed larger ci units than in the local markets due to the scope of the intelligence tasks was not supported by the results of this survey. as ci units were small, ci was usually fulfilled through a centralize unit. it is possible that israeli companies in the global markets were using outsourcing services by information professionals more intensively than those operating internally, but this was not substantiated in the results of this study. figure 7 the profile of competitive intelligence units: how old is the ci unit in your organization? it was found in this study (figure 7) that 69% of the units are more than four years old while the rate of new ci units in the last three years was only around 30%, meaning that in this period the growth of ci in israel was slowing. these results were contrasted with my initial assumption that ci is growing in israel in the last three years faster than in the years before. figure 8 to whom the ci director reports. the majority of ci directors in israel were reporting to the senior level management, i.e. to vps (figure 8). it seems that ceos preferred not to manage the ci function directly, mainly as a result of a lack of ability to allocate management attentiveness. in most of the firms, ci was part of the marketing or sales units, and their directors were reporting to the vp level. second most common were ci units that operated under the guidance of the vp business development. the vps of strategic planning were getting continual support from ci, but usually were refraining from taking direct control of ci. figure 9 the participation of ci in major decisions. the question here was referring to the rate of participation by ci directors in the regular meetings of the senior management and the results showed that the level of participation on a regular basis was low while the participation on an occasional basis was 30 percent (figure 9). it was not satisfactory but it revealed that the awareness of the importance of the contribution of ci is growing. the following question regarding the level of satisfaction from the contribution of the ci activity added a better perspective on this issue (figure 10). 10 figure 10 to what extent does the ci provides added value to the firm? figure 10 indicates that most of the ci directors were aware of the situation that their units were not graded very highly by their executives. these results also exhibited that the ci managers were aware of the need to improve their performance. although the results came from the ci managers, it was reasonable that they took into account the feedback they received regularly from their "internal customers", mostly the executives. figure 11 the advantages the firm is gaining from ci. the primary advantage of ci (approximately 70%) was placed on the identification of threats (figure 11). this may also be pursuant to the directions they got from their superiors. it was intriguing and annoying to find out the low rate (8%) that ci received in improving the decision making process. it is possible to deduce that the most important advantage was threat identification, while they felt a lesser need to support in the decisionmaking process. figure 12 primary users of ci products. the results of the question shown in figure 12 remained in firm correlation with the results in figure 8. evidently, ci was primarily serving the needs of marketing or sales. as a result of a lack of awareness and resources, the service to other functions was low as ci was incapable of looking simultaneously in other directions, mostly due to a lack of resources. figure 13 the existence of a systematic process of establishing kits. the results show undoubtedly that setting up a systematic process of kits has been executed very well (figure 13). it shows also that the routine of ongoing amendments was working properly. ci directors had intense awareness of the significance of keeping their attention on the real needs of their firms. it remained unclear why 25% of the ci directors were not operating using the same procedure. i tend to believe that this was a lack of awareness, which had an impact on their level of expertise in the ci discipline. in comparison to the global scene, 87% of the companies were systematically collecting and analyzing information. 11 figure 14 the use of information from primary and secondary resources. the results in figure 14 show that using secondary resources was a standing procedure while using primary sources was less frequent. these results correlated with the difficulties of building a primary source network, which could be a result of the lack of capabilities by the ci professionals and/or a result of difficulties in establishing themselves in their firms. figure 15 the use of ci dedicated information technology tools. although israel was positioned high in the development and the use of advanced information technology tools, the rate of ci units that were using these tools was low, only one third of the companies (figure 15). the prospects for the future were not promising. it is relevant to add that there were three local companies that provided excellent ci dedicated tools (barnea 2009). the results in figure 15 did not match the results of "the global study on large companies" (global intelligence alliance, 2009), stating that 64% of the firms utilized technological ci tools and 9% were intending to do so. the difference between the results in this survey and the one by gia is high, especially while israel is considered to be advanced in using new technologies. the findings from the global intelligence alliance survey on market intelligence in global organizations (2011), did not relate to this issue. figure 16 this figure relates to three questions: 1) return on investment (roi) of the ci unit (financially), 2) the contribution of ci to the decision making process, and 3) the contribution of the ci to the understanding of the competitive environment. looking at the question of the roi, (blue bars, figure 16), the results did not supply any hard figures to support the estimation of the roi grades. the replies expressed the perspective of the ci managers and their observations. it looks as if the high grades (4 and 5) that have exceeded 84% of the replies, may be too high, and it would be possible to accept them only if we had substantial data to support them. however, it is possible to say that ci managers believe that the ci units had proven themselves also from a financial perspective. i did not use specific models to measure the roi (faran 2003) and thought that the above results were sufficient. the other two questions (green and red bars in figure 16), reviewed the involvement of the decision makers that were expressing high satisfaction to the ci managers regarding their position and their abilities to contribute to the firmsquestion no. 2: 87% in grades 4,5 and question no. 3: 66% in grades 5, 6. the results to question no. 3 were extremely high – almost all the replies, except one, ranked the contribution as 4, 5, or 6. the results of the global study on large companies (2009) indicated that 98% of companies are utilizing ci while making key decisions. the results of these three questions (figure 16) show the high satisfaction of the ci managers with their contribution to the firms and to the internal process of the decisionmaking. these figures were also in firm correlation with the results in figure 10. comparing them to the results in figure 9 revealed that ci managers were not pleased with the level of their participation in the decision making process, and they seem to believe that they could be more effective. 12 figure 17 the key success factors of ci function. it is clear from figure 17 that the ability of the ci function to fulfill the immediate needs of the management was leading by far. this means that ci was perceived mostly as a tactical tool. ci managers did not think that ci would be more effective if it was pushing for sharing the information it acquired and encouraged different management layers to use it. it could be an indicator that ci managers were not yet fully aware of their role to push for sharing the information horizontally and vertically. another conclusion from the results in figure 17 was that ci managers may not feel that they had the support of the senior management to make ci prosperous. from the point of view of the firm, as long as the ci managers were provided with immediate information, it was good enough. figure 18 the improvement of the culture of sharing of information. although the ci managers did not think that sharing information was one of the ksfs of ci as we saw in figure 17, actually the results of figure 18 showed that while ci was active in the firm, it still had a significant effect on the development of the culture of the sharing of information, as one of the by-products of this activity. figure 19 the use of analytical tools (such as: 5 forces, swot, scenario analysis, benchmarking/gap analysis, financial analysis, profiling). this question referred to the use of one (or more) of the analytical tools that are the most familiar and practical (figure 19). the results were very disappointing as most of the ci managers (67%) admitted that they did not use even one of them on a regular basis. the question which was left unresolved was how they still fulfill their analytical objectives. figure 20 changes in the intensiveness of the competition since the downturn. most of the ci managers (75%), have indicated that they did not spot any changes in the magnitude of the competition in the various fields where they were competing since the economic slowdown (figure 20). however, 23% have felt more competition since the recent economic events. in the "global study on large companies (2009)", 45% of respondents felt strongly that ci activities have increased significantly after the global downturn in their industry. the average increase across all industries is 17%, almost similar to the results acquired in figure 20. 13 figure 21 changes in the demand for intelligence products as a result of the economic slowdown. most of the replies (65%) in figure 21, suggested there were no changes in the character of the needs and products these ci units produced. these results were in correlation with the results of figure 8, which showed no indications of significant changes in the volume of the competition. figure 22 did the ci function change since the global downturn? the results in figure 22 show that the recent global downturn had almost no effect on the size of the ci functions. those ci units that have been downgraded (20%) were affected by the general downsizing of many organizations due to the slowing of the world economy. it seems that ci units did not have to make internal modifications in their modus operandi, while most of them were successful in protecting their staff against dismissals. 6. conclusions as a result of the recession into which the global economy slipped in 2008, budgets have been cut in most corporate functions, with intelligence activities being no exception. yet simultaneous with the thinning resources, the demand for high quality information has stayed intact. we have learnt from the results of this research conducted in israel that ci units are operating mainly inside large companies in almost all the main sectors in the israeli economy. most of the companies (75%) have had ci functions for less than five years. it is evident that ci is growing slowly in israel. according to the results, ci in israel is considered to be mostly a tactical tool to identify immediate threats. around 70% of the responses mentioned this as the prime advantage the companies were gaining from ci. ci directors thought (77%) that they were successfully fulfilling this task. after following ci in israel for several years, i have noticed that ci is not considered to be a meaningful tool for strategic decisions. this may also be a result of the relative weakness of the performance of strategic planning in israel. in the us and europe (kahaner 1997; prescott & miller 2001), intelligence management is a business needs oriented process that transforms data into intelligence allowing companies to make better strategic decisions. it is a key task for the overall company's strategic management focusing on the observation of the external environment. this does not take place in israel. business strategy literature emphasizes the crucial need to monitor the competitive environment to utilize information more effectively (grant 2005, 1997) while competitive intelligence is the major tool used to fulfill this fundamental management challenge (herring 1992). almost 80% of the respondents assessed ci as performing fair or satisfactory and only less than 20% thought that the overall performance was high. this is another indication that ci managers are not aware of the need to improve their contribution to the corporate decision making process. still, around 70% of the ci directors indicated that they were not participating in major decisions, and it is hard to say why the rate of involvement of ci was so low. ci managers had to be bothered as these results were possibly projecting their unsatisfactory performance. the position of the ci unit under the vp of marketing and/or sales, as seen in almost 70% of the firms, did not have any impact towards better performance of the ci as a second tool for better comprehension of the marketplace. the ci function has to become part of the firm’s organizational structure as other units and thus conclude the forums and crossroads in which it officially participates. this research did not enter into ci's roi through a deeper survey, by using different models (rouach & santi 2001). the process of carrying out ci is performing well – 75% of the companies declared they had a systematic process of setting up key intelligence topics, meaning that their gathering efforts are well in place. unfortunately, the use of primary sources, 14 mainly the internal network, was found to be not good enough, and it may be an outcome of a lack of awareness by the ci directors and/or a result of insufficient resources. still, 77% of the ci managers thought that they were playing a major role in expanding the organizational culture of sharing of information internally. thus, it is necessary to improve the collection of information, through a better use of primary sources and the internal networks. this research reveals multiple phases of creating meaningful intelligence within the process. it also discovered that the practice of competitive intelligence, while strong in the area of information collection, was weak from a process and analytical perspective. the research identified an actual problem in the performance of the analysis by the ci function. the use of analytical tools was relatively low but these results did not stop ci managers from mentioning strongly that ci functions were a valued investment and that their contribution to the decision making process and the understanding of the external environment was fairly good. ci directors were not satisfied with of their involvement in major decisions. the low rate of the use of ci dedicated it tools (36%) could not be just a result of a lack of budget, but instead a result of a lack of pressures on the ci managers who may think that they can manage with ordinary tools instead of using advanced ones. there is a need in israel to fulfill advanced tools such as dedicated software for gathering, analysis, and dissemination to improve ci performance. the ci global survey has achieved different results, presenting data that show 64% utilize technological ci tools and 9% intend to do so. and finally, ci managers firmly declared that they noticed only a small amout of growth in their activity since the recent downturn. most of them kept their staff while the profile of their tasks remained intact and the magnitude of the competition had almost no influence on them. the global survey on ci (2009) indicated different results. from this, 45% of the respondents felt strongly that ci activities have increased significantly after downturn in their industry. the average increase across all industries was 17%. and a final note – israel is unique in the sense that many of the executives have been exposed to the benefits of the intelligence discipline in their military service. thus, one could expect that the penetration of competitive intelligence would be faster and its influence on strategic moves in addition to tactical ones would be more visible. however, the results are different. maybe this is a result of an israeli business culture marked by high self-confidence, by strong capabilities of fast adjustments to changes instead of 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"development and evaluation of a framework to explain causes of competitive intelligence failures" information research, 17 (2), paper 521 eg-uk conference paper style guide 59 standards, evaluation, certification and implications for the study of competitive intelligence christian bourret * * university of paris-east marne-la-vallée, france. bourret@univ-mlv.fr received 10 december 2010; received in revised form 19 february 2011; accepted 27april 2012 abstract: the rise of standards, evaluations and certifications are expressions of what may be called the cult of performance and efficiency. standards and assessment are frequently presented as inevitably, improving quality through a project approach. as such they reflect a strong focus on efficiency in a world dominated by the quantitative approach. these standards and evaluations may hinder competitive intelligence goals. building on the interdisciplinarity of information and communication sciences (ics), we propose another qualitative approach to standards and assessment. finally, we considers the challenges represented by standards in the context of globalization of the economy and of trade. keywords: standards, evaluation, certification, competitive intelligence 1. introduction standards have become increasingly important in our society. in 1997, the french sociologist l. thévenot had already spoken of "government by the standards." since then the phenomenon has been largely amplified, with a close link between standards, outsourcing and its control, and evaluation. standards have also become a main issue in the process of globalization. standards are considered as part of modern management, for private companies and for public institutions alike. standards are also as a main issue in globalization, with the role of iso and of the “society of risk” (u. beck) and a key point in risk management. standards also have strong interconnections with competitive intelligence stakes as the analyst sets out to predict future scenarios. this article begins by demonstrating how the rise of standards, evaluation (assessment) and certification are a part of what we shall call the cult of performance and efficiency. then we proceed by proving how standards and evaluation are important to improve service quality through a project approach. standards can lead to an obsession with available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 59-67 mailto:bourret@univ-mlv.fr https://ojs.hh.se/ 60 efficiency in a too exclusively quantitative approach. this ambivalence of standards and evaluation processes can involve contradictions with competitive intelligence goals and methods. based on the interdisciplinary of information and communication sciences (ics), this article proposes another qualitative approach to standards and assessment. the perspective of this article is finally broadened by considering the challenges due to standards in the larger context of globalization. 1.1 standards, assessment, certification or the rise of the cult of performance and efficiency the concept of standards is ancient. in france, this term has a latin origin (norme) and dates back to the year 1160. in the craft sector, guilds imposed a strict respect of the manufacturing processes. the french revolution swept corporations away as vestiges of the “old regime”, with the revolutionaries willing to change both the things that were made and the people. the revolution imposed new standards such as the metric system, a new calendar (“revolutionary”), and a new division of national territory (the departments replacing the provinces). even in metrology aspect (weights and measures), standards have deep social influences. other standards (calendar, administrative districts) constitute the basic framework of daily life in a developed society. today standards frame information exchanges (pdf, excel and so on). all the classifications are not neutral and they imply debatable statistical classifications (for example of social categories 1 ). classifications condition people’s representation and the vision of the future. as such it also affects the study of ci, as it decides how we look and try to analyze future events. the industrial revolution relied on the standardization of production, particularly from the early twentieth century with the scientific organization of work advocated by f. taylor. the accounting techniques, which appeared in venice (italy) in 1494, are also based on standards, to assess the revenue and expenditure of companies, to assess profit (development of capitalism). according to colbert’s view in france in the seventeenth century (development of the administrative or absolute monarchy), the state point of view of standards are for tax purposes: french accounting plans of 1947 and 1982 met these two different goals. standards and assessment (evaluation) are thus an integral part of the management that has 1 classifications are never neutral: documentation and statistical bodies (insee in france) are linked to social categorizations and used to support any form of government, as with apartheid in south africa. gradually emerged, following the pioneering works of the french engineer h. fayol in the early twentieth century. this was also part of the main characteristic of the united states (departments of management for example at harvard university). according to le moënne (2004), the big managerial disruption in the late eighties, corresponding to the spatial and temporal dislocation of companies, is probably the largest movement of managerial standards, most systematic and most radical since the origin of capitalism. it is accentuated by the digital revolution. we must not forget other “revolutions” either: the taylorization and fordisme at the beginning of the 20 th century. boussard (2008) defines "managerial ideology" as based on thee main points: monitoring and controlling an organization (the main justification of management), aiming at enabling organizations to be effective and efficient and finally relying on a rational and methodical approach to problems. the three keywords of management are: control, performance and rationality (boussard 2008, pp. 25-27). the dislocation of companies corresponds to the development of outsourcing, contributing to control and evaluation of results (regarding the goals contracted). the evaluation (assessment) began in the anglo-saxon countries and in private companies. in france, it gradually extended to the public sector (traditionally important in france) with the nmp (new public management / nouveau management public), which gradually developed in the 1980s, succeeding to the ppbs (planning programming budgeting system) and in france rcb (rationalization of budget choices). the main idea of the nmp is to transpose management methods of the private sector to the public sector in order to improve efficiency, relying on the "3 es": economy, effectiveness and efficiency. since 1996 when the social budget of the nation in france became higher than the state budget, parliament members voted for the annual lfss (law of financing social security / loi de financement de la sécurité sociale). later came the logic around goals or outcomes imposed by the lolf (organic law of public finance / loi organique des finances publiques), which gradually after 2003 transformed all management processes in the public sector, including universities (dashboards, indicators) and the focus on ppp (partenariats public privé). as a result our society has progressively become a “society of mistrust”, as trust is a main stake. standards are said to help "build confidence in an era of suspicion." in this perspective, d'almeida (2001) emphasized the role of brands, labels and trade marks of companies and their products. these "work as safeguards to promote the security and sustainability of the exchange, 61 matching supply and demand in selective criteria clearly identified” (d'almeida 2001, p. 242). d'almeida (with men like boutinet, gramaccia) show how the project process, which is seen as increasingly natural in companies (boutinet 2001), leads to a focus on innovations and has almost become an affair of state. the project process is at the heart of the modernization of the state as viewed by rocard’s government in 1989. developed in a competitive market space, the project has also been put at the service of improving the functioning of the state services, seeking to move the system from administration around procedures to administration with responsibility (d'almeida 2006). the project, as a network for innovation, has become a symbol of our post-industrial society. this system has been implemented with notions of performance and efficiency and in relation with quality approaches. this article aims to outline the role of quality approaches. born in japan after 1945, the notion of quality was developed in the industrial field in a process of continuous improvement (kaizen). this gradually became total quality management (tqm), and expanded to the western world in the 1980s. it then expanded to all sectors of organizations, whether private or public, and was backed by statements of procedures and certification corporations (iso, afnor in france) and the development of references as standards of measure. thevenot (1997) points to the evolution towards a "government by the standards" linked to market development, including the construction of the european market in the context of globalization. the rise of normalization corresponds to the competition in the market and is thus an integrated part of capitalism. thevenot (1997) outlines the extension of the standardization area from that of goods, products and services to that of people (standardization of skills). it's a process to standardize objects or acts in order to bring consistency to an efficient industrial operation (taylorization). the challenge is to ensure new surrounding formal contractual relations between individual subjects, with the risk of information dominated by a uniform standard of cognition. the evolution of the notion of standards has met two other major issues in the last sixty years: the development of the welfare state and the development of services (tertiary sector) with the shift to the “taylorization of services”. the welfare state, often interventionist, particularly in france, has gradually evolved to become more of a guide, a motivator and an arbitrator. this in a context of limited resources, deep deficits and higher charges, has implied a tighter cooperation with the private sector. with a social or welfare budget which amount is larger than that of the state’s itself during the last twenty years, the state has been forced to delegate, develop partnerships with the private sector and learn to "manage risk", especially financially. at the same time, western societies have become service societies, since the service sector now counts for nearly 75 percent of the active working population, with a high proportion of "knowledge workers." 1.2 standards and assessment for improving quality according to afnor (french standards association or association française de normalisation), the best way to introduce standards and norms is to recall the definitions of "standard" as proposed in iso/cei 2 . standardization is an "activity of establishing, in front of real or potential problem, provisions for common and repeated use, aimed at obtaining the optimum degree of order in a given context." the document states that "this activity involves, in particular, the formulation, dissemination and implementation of standards." it says that standardization offers significant advantages, including better adaptation of products, processes and services for which they are assigned, for the prevention of trade barriers and facilitating technology cooperation. the same guide outlines that "the standards are based on the consolidated results of science, technology and experience and seek the optimum benefit of the community." we shall retain the ideas of "common and repeated use for obtaining optimum degree of order in a given context and facilitate cooperation". all organizations, private companies or public sector agencies, have developed customer approaches based on standards and benchmarks to ensure the quality of the services offered. the change has largely concerned management devices which have proliferated in all organizations. boussard (2006) conclude that "the management devices between organizational and professional standards” systems of standardization (of quality, security) about integration of information (erp: enterprise resource planning) and assessment (of skills, of financial results), are imperative in the name of the ideal organization, which is rational and efficient because regulated and controlled. according to boussard (2008), these management devices constitute the privileged support of the the "makers of performance". this article comes to a key point: 2 normalisation et activités connexes – vocabulaire général (2004), european standard reference en 45020, in france nf en 45020.using iso definitions (international standards organization), website : http://www.bivi.metrologie.afnor.org/ofm/metrologie/i/i20/i-20-10/4 (visited on september 2010, 25 th ). javascript:bivi_preredirect('nf%20en%2045020'); http://www.bivi.metrologie.afnor.org/ofm/metrologie/i/i-20/i-20-10/4 http://www.bivi.metrologie.afnor.org/ofm/metrologie/i/i-20/i-20-10/4 62 the link between standards, productivity and the evaluation of the performance. the development of a "government by the standards" and by the quantitative techniques of management is inseparable from evaluation. the use of increasingly important sub-contracting (outsourcing) or of a delegation and contracting approach can be defined as an objective or outcome approach and requires an assessment of the results obtained by the contracting party in comparison with the targets written in the original contract. states often try to master huge deficits, particularly in the health sector in france. lievre invites j. plante who defines "assessment as the formation of value judgment on action in the perspective of decision making." plante continues: "the quality of an assessment lies in the degree of integration of the results produced in the representations to come of the sponsors" (lievre 2002, pp. 22-23). in the public sector or quasipublic social protection in france, these notions of standardization and evaluation correspond to the proliferation of different agencies. for example in the healthcare sector, france developed andem (national agency for the development of evaluation in medicine), established in 1990, then in 1997 it became anaes (national agency for assessment and accreditation in health) and finally it became the high authority for health (has) in 2005. then there is the afssaps for sanitary security and health products. in the case of healthcare networks, devices of cooperation between public and private sectors wanting to articulate the activities of the hospital and primary care, it is outlined that: "the assessment of healthcare networks means to appreciate the achievement of qualitative and quantitative goals to measure their impact on the quality of care for patients, the quality of access to care, practices of health professionals and on all the context of these healthcare networks." 3 the risks of drifts from a "government by the standards" are important in this case. the pointillist application of guidebooks and procedures (to take documents literally) can override the main spirit, forgetting the importance of context, as the cult of quantitative approaches overriding more qualitative approaches. quality does not amount to the only application of standards. it constitutes above all a state of mind, a culture modulating behaviour, and a way of being and know how to face situations 4 . 3 circular cnamts (health insurance)/dhos – ministry of health (march 2 th , 2007) about orientations for evolution of healthcare networks in france, p. 2. 4 ecole des enseignants-chercheurs en qualité, cnqp (comité national de la qualité et de la performance) – université de technologie de compiègne (utc), paris, negocia, 27 janvier 2011. quality is not only standards; it is not only order or rule without meaning. it is rule and meaning. the problem is when we have rules without meaning or against meaning. 1.3 the cult of standards or the risk of efficiency obsession in a too exclusive quantitative approach alémanno-parrini and le moënne (2010) have outlined how the issue of evaluation of professional practices has become central in various sectors, including that of home services. alémanno-parrini and moënne (2010) conclude that: "this concept is obviously ambivalent. sometimes value judgment focused on practices, based on estimations of disparities with the specifications or expected results, in the case of projects (with extremely passionate reactions and mass movements of resistance). it can also be understood as a device for improvement or as an overall issue of resource management". this ambivalence is between the possibility of improvement and instrumental control. the rise of "performance devices" refers to the "injunction to professionalism" that "most often come into collision with the ideas that the professionals themselves have about their activity" (boussard, demazière & milburn, 2010). in the healthcare sector and especially in the hospital, schweyer (2010) highlights the tension between costs (administrative and economic point of view about efficiency, corresponding to a will to control expenditure) and values (of the different professions). the central objective of cost containment in the healthcare sector is also based on standards. mintzberg (2001) is particularly vehement in his denunciation of the drifts of a too exclusively quantitative approach, notably in "note on an ugly word: efficiency." 5 for mintzberg (2001) "management, as practiced now, may be causing the problem and do not propose the solution. it can work against our vital interests (...) a management obsessed with the idea of efficiency is a management obsessed with the idea of the quantifiable. the cult of efficiency became the cult of the quantifiable. and here lies the real problem (...) because the economic benefits are more easily quantifiable than the social benefits, efficiency often leads the organization to adopt an economic ideology that can sometimes mean social immorality" (mintzberg 2001, pp. 479-485). critics of mintzberg are met by de gaulejac (2009) when 5 mintzberg h (2001), « remarque sur un bien vilain mot : "efficience"», in le management. voyage au centre des organisations, paris, ed. d’organisation, p. 479 – 485. 63 he denounces the “society sick of management”. de gaulejac (2009) concudes in his preface that "disease of management becomes an epidemic." he stresses the point that "management by project became the model of governance." "the performance is not measured by the quality of service delivered, but only in terms of cost and financial results." de gaulejac (2009), who has been associated with the creation of the university of management in paris dauphine, emphasizes that "our purpose is not to condemn management. management is necessary to optimize the functioning of organizations and administrations. it is not bad in itself. it becomes bad when, with the pretext of reform or rationalization, tools are applied blindly, without concern for human consequences, organizational and social (…) when management is at the service of instrumental rationality, it loses its legitimacy" (de gaulejac 2009, pp. 9 -13). there are examples of drifts, in france, as in the case of companies like france telecom (orange), known for scandals of moral harassment or in the pôle emploi (french organization for unemployment). scepticism has also be directed towards the gap between the display of "quality certification" in ratp (underground company in paris) and at sncf (french railways) stations. the reality perceived by the users is of a sharp deterioration of the service during the last years. this is also the case in call centers (symbols of the “taylorization” of services), where quality guidelines emphasize the speed of response and limitation of waiting times, which is praiseworthy, but these guidelines rarely mention the quality and the added value of the information given to users. in order to stick to quality procedures, these users have become “customers”, even in the public services. in parodying the title of the work of ehrenberg (2000) on the "tiredness of being oneself" about an "individual uncertain, more and more exhausted by the "cult of performance". jeannot (2010) speaks of the "tiredness of being a customer", also in the public sector. jeannot (2010) stresses that these are not "users" who wish to become "customers". it is a "managerial standard", highly debatable, since the so-called customer has no real choice between different service providers. this "king customer" is more "confused", in "probation freedom" or suffering "pressures close to the forced sale" (jeannot 2010, pp. 35-39). the emphasis is strongly on information and communication, but wolton (2009) among others, states that "to inform is not to communicate." that is the question of meaning, especially in the public sector where the notions of "public service" and "public interest" no longer seem to have the same significance. 2. methodology our approach relies on a literature review and mainly on a qualitative method (with emphasis on qualitative and not just in the speeches of leaders and in the titles of laws, but in the reality of daily activity), nevertheless without neglecting the quantitative aspects. a first step is to measure the gap existing between the official speeches of the leaders and the daily reality lived by employees. the question of meaning is critical, as in any approach linked with the "intelligence of complexity", by giving full value to autonomy and responsibility of "knowledge workers" (dortier 2005). the question is also essential in the answers proposed both by mintzberg and by de gaulejac. they outline the imperative to "give meaning to action", changing the point of view from the "employee as a resource" to the valorization of the "individual subject" and so a "more human management of resources" (de gaulejac 2009, pp. 302-310). with the equally critical issue of developing trust (le cardinal): in oneself, in others and in the future, in the people and in sociotechnical devices. beyond standards, it is necessary to bet on the intelligence of the relationship. thus we meet both n. d'almeida (2001), who insists on a "relationship economy" with all the importance of networks and zacklad (2009) with his “economies of conviviality” and his “semiotics of cooperative transactions”. 3. standards and competitive intelligence not always an easy relationship these developments and shifts, which increase the gap between the noisy and incantatory speeches which are "customer focused" and the reality perceived by the so-called customer about the deterioration of delivered services, can contribute to the degradation of the image of companies. thus, the excesses of a "government by the standards" and of performance only considered in quantitative terms ask the question about the difficult relationship between standards and competitive intelligence. according to levet (2001), "competitive intelligence is the ability to understand our environment and to anticipate change (...) it is based on mastering information and on the production of new knowledge" (levet 2001, vii). the intelligence economique mémo, prepared by the french national gendarmerie (2006) distinguishes three families of threats for a company: 1) the damage to image and reputation 2) exposure to economic and financial risks 3) risks of information and know-how. the document, intelligence economique mémo, thus clearly 64 distinguishes between human threats and technological threats. for le bas and picard (2003), if "information is at the heart of any competitive intelligence device (...) it is no longer considered as a scarce resource (...) but what became rare and may be considered as a source of competitive advantage for companies that control this resource, they are the skills needed to use, to interpret, or assimilate information" (le bas & picard 2003, p. 17). in an organization that turns into a "learning organization", workers become "knowledge workers" (dortier, 2005). moral harassment and lack of motivation among employees may constitute a major risk for the company, resulting in risk management at different levels, a major concern for the function of competitive intelligence. holmes (2002) refers to bernstein, for whom, "the boundary between modern times and the past is the mastery of risk" (holmes 2002, p. 2). for bernstein, "risk management is an active process" (holmes 2002, p. 6) concerned with "the relationship between risk and change" (holmes 2002, p. 8). introducing new management methods and methods for assessing performance, standards induce powerful changes in human relations and in the lives of individuals, and all of these consequences are normally not taken into account in ci analysis as analysts try to select the best scenarios. for their part, metayer and hirsch (2007) insist on ethical risks and human needs in the company, referring to maslow's pyramid: need for belonging and of self respect and need for achievement. in this article emphasis has been on risks that the standards applied rigidly, expressed as instrumentalization. the standards used properly can contribute to a positive image of the company by improving the quality perceived by customers. these standards can also improve cooperation between organizations, especially in the context of globalization. it is only in their drifts, also for the project (boutinet) standards and project often being associated that they constitute a risk for companies. 3.1 a different approach to standards and competitive intelligence relationship the author believe that another approach of the relationship between standards, assessment and competitive intelligence is possible, especially based on the concept of “reliance”, important in the interdisciplinary of information and communication sciences (ics). bernard (2006) positions the information and communication sciences at the articulation of four issues: relationship, meaning, knowledge and action. ollivier (2000) points out three issues: meaning, power and identity. the question of meaning is essential. it is at the heart of the specificity of ics, by providing the question of interactions with that of relationship (interactions or relationship) with knowledge and with action (issues of representations) , and with the joint issues of competitive intelligence as an aid to decision making in a strategic perspective. the human dimension is essential. wolton (2009) emphasizes that to "think communication is to think the lack of communication, he speaks of “incommunication”. for wolton "to communicate is less and less about how to transfer, rarely to share, but usually to negotiate and finally to cohabit" (wolton 2009, p. 94). this importance of meaning must be enhanced in relation to the notions of situation and contextualization as expressed by mucchielli (2010) through his approach of "situational semiotic”. mucchielli proposes to analyze situations for an actor from different frameworks or contexts: through identification of actors, positioning of actors, space and temporal contexts, standards, values, quality of relationships. these should be applied to standards in companies, for goods or services, for a wider general use in society (social norms) but also as a method, as for technical requirements to supervise activities, standards established by iso or french afnor. this is the subject of this communication. it is essential for "situational semiotic” to analyze the situation for any actor following these dimensions for reflection. the ics approach tries to answer the central question of the meaning of the activity, recognizing issues that are central in management for a more complex approach. genelot (2001) stresses the importance of "making sense" and "build a culture", by "putting the human being at the heart of the company", "knowing how to recognize and articulate different logics to go back to the source of representations" (genelot 2001, pp. 336 340). 3.2 standards: an example of the globalization only for the benefit of its dominant countries and companies? besides their weight of standards on the evolution of organizations, including those imposed through socio-technical devices such as information systems or management, standards are also a strategic issue for economic globalization. the competition between companies and countries is now global, both in the field of industrial products (cars, computers, machine tools and so on) but also in services (energy, insurance, banking, retail, transport, telecommunications and so on). producers seek to generate margins in one battle at a time, all centered around cost, sales, and 65 the setting of prices as essential in the context of fierce competition. for their part, buyers and regulators seek qualitative benchmarks, for selecting the most competitive, rather than the less expensive suppliers or contractors. in this perspective, as already stressed by d'almeida, the company's image and its reputation (around the concept of brand) can be valuable with all the challenges of e-reputation or reputation by examining information from internet. standards and certifications (as recognized signs of quality) may also help to develop the confidence of buyers and consumers and, therefore, constitute a strategic issue for companies, as part of a competitive intelligence analysis. the definition of standards is presented in basic documents published by the standards’ organizations as the result of a consensus. in this article the author questions the weight of the anglosaxon countries and companies, especially united states of america, particularly in the iso (international organization for standards) which, by progressive or more coercive methods, contribute to impose standards on the rest of the world. these standards correspond to their particular approach and interests, helping to create a competitive advantage for their own businesses. other standard organizations such as afnor in france, integrate and use the standards proposed by iso, more or less willingly. as for patents and industrial property, the standards battle is a major issue for the credibility of the european union and the economic weight of the countries of the old continent in the global marketplace. after the quasi abandonment of the national policy of scientific and technical information in france in the 90’s, hope was placed on the european level. worries have been expressed about the recent draft agreement (in december, 2010) between the european patent organization (epo) and google for the translation of the european patents 6 . the stakes are particularly high in the field of standards, concerning the production of industrial goods or services, but there is also a key issue around accounting standards, as demonstrated by capron (2007). capron (2007) has stressed that in france, accounting is often perceived as a neutral technique (also often perceived as esoteric) that may be required objectively. furthermore, capron (2007) states that it is above all a social convention, historically dated, evolutionary, developed according to the big economic movements, more or less buffeted by conflicting pressures and intended to produce economic and social effects, the most important thing is bringing confidence in trading. 6 la dépêche du gfii (groupement français des industries de l’information) 2010, december 1 st . by focusing only on learning the ways of recording and bookkeeping system, france is in a vulnerable position, not reconsidering the foundations of the accounting systems. this includes the principles that guide accounting choices: any accounting system is a choice of representation of the economic and financial reality among many other possibilities. this instrumental and technical approach impedes being aware of the diversity of accounting systems in the world and across time, and more importantly, to underestimate the importance of valuation methods and valuation of companies. these are crucial to define the value of companies in case of purchase and also for taxation. taxation is dependent on the criteria for evaluating benefits and benefits in term depend on provisions and depreciations. for example anglosaxon accounting systems grant more freedom to the accounting players as shown in the case of enron (2001). as seen afterwards, this perspective of the accounting system must be questioned. it is for the competitive intelligence function to detect its weaknesses in advance. thus questioning the whole system becomes its domain. 4. conclusion and future research standards, certification and evaluation are key areas which influence the future of our world. the field of ci must be aware of the stakes. in this article the author has showed the risk of our existing standards in the form of certification and evaluation, which may lead to an obsession with instrumental and quantitative techniques. examples of this is stressed by mintzberg (2001) and de gaulejac (2009), where the subtitle of the book is "managerial ideology, managerial power and social harassment." we must not deny the interest of management or the standards for the development of confidence, both for consumers and policy makers, to ensure the quality of goods and services, but must also foster comparisons. it is necessary to assess all the issues (not always seen) in the field of standards, both in the overall context of the globalization of trade and markets, but also the risks of abuses in daily activities in enterprises and organizations. the technique or even the idea of progress itself, standards, certification and evaluation, and more widely quality approaches, are at the end ambivalent. they must be seen as tools and not as an end in themselves. in this perspective, the problems of the relationship, meaning, knowledge and action, as presented in an ics (information and communication sciences) approach are essential. this approach values the importance of the investment in the field of standards, certification and assessment by competitive intelligence actors, 66 to restore its relational and human dimensions (not leaving it only to engineers and technicians) both at the strategic, the policy (macro), and day-to-day working (micro) levels. the challenge is to create relationship and meaning to have better choices. in this spirit the author has also wanted to offer some areas for future research linked with challenges in the development of trust, meaning and cooperation in a new qualitative approach around “quality 2.0” or ”sustainable quality”. in what can be called the stereotypical speeches of main world organizations (such as wto: world trade organization), some states and large companies insist on the benefits of free global competition for consumers. many are questioning whether or not these are smokescreens, trying to hide a manipulation. strategic issues such as standards, are they not often ultimately a tool for domination of a few countries and for big multinational companies? more broadly, does not the unbridled pursuit of profit through the obsession of performance and efficiency (stiglitz speaks about “cupidity”) risk to forget the quality, in the best sense of the word, sacrificing for example the healthcare and the environment because it is not profitable? the relationship between 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siponen et al., 2014), iss organizational rules or even guidelines or requirements (ifinedo, 2012; workman et al., 2008). however, numerous surveys and studies have confirmed that managerial support is essential in obtaining adherence of employees to iss (avolio, 2000; johnston & hale, 2009). in addition, employees’ involvement and propensity to act are directly dependent on managers’ concrete actions (dong et al., 2009; forcht & ayers, 2000). to date, little attention has been given to top management’s role. withal, many scholars advocated that iss should be addressed at the top management level (markus, 1983; longeon & archimbaud, 1999; friend & pagliari, 2000; knapp et al., 2006). the mis literature repeatedly shows that managers must not only be aware but also be personally involved. managers' involvement is essential in the implementation, maintenance and success of issrelated actions (johnston & hale, 2009). rockart & crescenzi (1984) declared that managers must recognize that information is a strategic resource and that "senior executives are increasingly feeling the need to become informed, energized, and engaged in information systems" (p.3). top managers must be considered as the starting point for satisfactory iss (robinson & volonino, 2004). according to longeon & archimbaud (1999): "determining and supervising the security policy are top management concerns. nothing valuable can be done without the manager, provided that he knows all the challenges involved." (p. 19). however, some managers are poorly involved or are poorly acting in their company’s iss, leading to potentially disastrous consequences. few studies aimed at understanding ceos' participation and actions in iss (dong, 2008; zwikael, 2008; barlette, 2012). moreover, studies dedicated to factors influencing action, their incidence on iss, and major actions that are incumbent to managers usually focus on medium or large business executives (lee and larsen, 2009; vance et al., 2012). this study investigates iss in french smbs. in 2013, smbs (less than 250 employees) accounted for 99.8% of all enterprises active in the eu28 non financial business sector, representing 66.8% of total employment, including a large part of small (less than 50 employees) and micro‐enterprises (less than 10) (european commission, 2014). iss surveys have revealed that smbs are far behind larger companies in implementing protection because they lack technical (labodi & michelberger, 2010) and financial resources (lee & larsen, 2009). smbs have to face important issues: (1) it is more difficult for smbs to recruit and keep ict or iss specialists (monnoyer, 2003; pritchard, 2010), (2) ongoing risk assessment is often lacking (gupta & hammond, 2005), and (3) many smb managers are not sufficiently aware of iss issues (mitchell et al., 1999) and consider information security to be a ‘large business’ concern (rees, 2010). the unfortunate truth is that smbs are as much – and in some cases more – at risk from security breaches that could threaten their organization (rees, 2010). therefore, smbs and their managers constitute a specific case for iss research. in this study we test protection motivation theory (pmt) on smb ceos and observe what factors explain their intention to engage in protective actions for their firm. this paper is structured as follows: in section two, the literature review will lead to our model and hypotheses development. third section introduces our methodology. we present our results in the fourth section and discuss them in section five. in the last section, we sum up our main results and introduce our next study. 7 2. research background in this section, we will introduce successively protection motivation theory, then our model and hypotheses. 2.1. protection motivation theory (pmt) pmt (rogers, 1983) is one of the most powerful explanatory theories for predicting an individual's intention to engage in protective actions (anderson & agarwal, 2010). pmt can be divided into two major components: threat appraisal and coping appraisal factors. 2.1.1. threat appraisal the perception of threat is defined as the anticipation of a psychological, sociological or physical violation or harm to oneself or others (lazarus, 1991; workman et al., 2008). people perceiving this threat will adjust their behavior according to the amount of risk they are willing to accept. this adjustment is based on the perceived severity of cost and damage associated with the threat and their perceived vulnerability related to the threat. perceived vulnerability is the conditional probability that the threatening event will occur provided that no adaptive behavior is performed or there is no adaptation of an existing behavior (lee & larsen, 2009). the more perceived vulnerability to a security breach the more iss behaviors people will exert (ryan, 2004), the opposite can be also true, e.g. perceived invulnerability can lead to less iss behaviors (bulgurcu et al., 2010; ryan, 2004). perceived severity corresponds to the perception of the severity of the consequences of an iss problem, because iss measures were insufficient or ineffective (ifinedo, 2012; liang & xue, 2010). it includes for example the perceived level of company's loss of activity, loss of data, financial losses and the eventual side effects (e.g. loss of image). this perceived severity will lead people to behave in a more cautious manner if this perception increases, but the reverse effect also exists, e.g. people will be less cautious if the perceived severity diminishes (bulgurcu et al., 2010; herath & rao, 2009). 2.1.2. coping appraisal coping behavior will depend on the control perceived by people on this behavior, their perceived capabilities, and the effort they will expend to accomplish that behavior (bandura, 1977). three components will influence this coping appraisal: response efficacy, self-efficacy and response cost. response efficacy corresponds to the beliefs about the perceived benefits of the behavior exerted by the individual (rogers, 1983). if people perceive the available coping mechanisms as adequate, for example because available security measures are improving (kankanhalli et al., 2003), they are less likely to omit an iss-related behavior. on the contrary, if people have a negative perception of the efficacy of the necessary behavior, because no matter what they do security breaches will go on increasing, they will be more likely to omit this behavior (workman et al., 2008). self-efficacy is defined as "people’s beliefs about their capabilities to produce designated levels of performance that exercise influence over events that affect their lives" (bandura, 1994, p. 81). prior research has demonstrated people are more motivated to cope with or perform it security behaviors as the level of their self-efficacy increases (workman et al., 2008). response cost resembles to the physical and cognitive efforts necessary for the adaptive response (lian & xue, 2010). it can correspond to money or time to invest in the behavior or the security measure, the inconvenience or the difficulty of the behavior itself. this perceived effort is put into balance with the perceived value of the iss-related behavior (workman et al., 2008). 8 2.2. the research model and hypotheses figure 1. the theoretical model threat appraisal: an increase in perceived severity and vulnerability leads to greater intention to behave in a healthier manner. therefore we postulated (see fig. 1):  h1: perceived severity of potential information security threats influences positively and significantly smb ceos’ intention to perform information securityrelated actions.  h2: perceived vulnerability from potential information security threats influences positively and significantly smb ceos’ intention to perform information securityrelated actions. coping appraisal: according to pmt, it consists of self-efficacy, response-efficacy and response cost. response efficacy, in the context of our research, refers to the ceos' belief in whether performing information security-related actions can enhance their company's security and reduce security flaws. we postulated:  h3: response efficacy to potential information security threats influences positively and significantly smb ceos’ intention to perform information securityrelated actions. self-efficacy referred here to ceos' belief in their ability to perform information security-related actions. we believe that self-efficacy to potential information security threats has a positive and significant impact on ceos' intention to perform information security-related actions. we therefore postulated:  h4: self-efficacy to potential information security threats influences positively and significantly smb ceos’ intention to perform information security-related actions. response cost represents any costs (e.g. time, monetary, difficulty, complexity, effort) associated with taking the adaptive coping response. hence, we postulated:  h5: response cost influences negatively smb ceos’ intention to perform information security-related actions. gender has been found to be important in it contexts (venkatesh et al., 2003). therefore we postulated:  h6: male smb ceos have a greater intention to perform information security-related actions than female ceos. age showed significant differences in the involvement of managers and their perception of troubles affecting their company's is (stevens et al., 1978, venkatesh et al., 2003). thus, we posited: behavioral intention perceived severity perceived vulnerability response efficacy gender age self-efficacy response cost size coping appraisal threat appraisal h1 h2 h3 h4 h5 h8h7h6 9  h7: age negatively affects smb ceos' intention to perform information securityrelated actions. lee and larsen (2009) did not identify that the size had any significant influence on the behavioral intention. anyway, we posit that the smaller the size of the company, the more important the role of the ceo in the management of information security. thus, we postulate that a larger firm’s size is negatively related with ceo’s behavioral intention to take or implement i.s. security measures.  h8: company’s size influences negatively smb ceos' intention to perform information security-related actions. 3. methodology 3.1. research design the research model was tested using a field survey. we administrated the questionnaire to smb ceos. each participant received an email explaining the purpose of our study, including a link to our webbased questionnaire. a total of 258 responses were returned between december 2014 and january 2015. after removing incomplete and invalid responses, we obtained 177 usable responses. response rates for information security-related surveys are usually low (kotulic & clark, 2004). in addition, smb ceos are very difficult to contact by email and time is a scarce resource for them (wolcott et al., 2008). the scales used in this study (see appendix a) were taken from previously validated research. the response efficacy and perceived severity scales (eff. r, sev.) had measures adapted from vance et al. (2012). the self-efficacy scale (eff. s) had measures borrowed from lent et al. (2006) and vance et al. (2012). the response cost and perceived vulnerability scales (cost, vuln) had measures borrowed from vance et al. (2012). the behavioral intention scale (int.) used measures adapted form workman et al. (2008) and yoon and kim (2013). all items, except nominal variables, were measured using 7-point likert scales anchored at 1="strongly disagree" and 7="strongly agree". the questions included in our instrument were first pre-tested through face-to-face interviews with smb ceos (n=14). based on ceos' feedback, the readability of the questions was improved. the questionnaire itself was created using qualtrics tool. in the beginning of the questionnaire, an introductory text defined information security and specifying that only ceos of businesses with less than 250 employees were authorized to respond. participation in the study was voluntary and respondents were assured that individual responses would be treated with anonymity and confidentiality. 3.2. measures our purpose was to determine the influence of antecedents on behavioral intention. all the items of the questionnaire are described in appendix a. dependent variable the dependent variable behavioral intention (int.) was calculated through a factorized construct (cronbach’s alpha = 0.904) composed of two items, int1 and int2. independent variables the independent variables were divided into two groups. to measure threat appraisal, we observed perceived vulnerability (vuln.) and perceived severity (sev.). to measure coping appraisal, we used three variables: response efficacy (eff. r.), selfefficacy (eff. s.), response cost (cost.). all items exhibited a reliability score over 0.7, which is considered as satisfying. variable factoriz ed constru ct cronbac h’s alpha items (see appen dix a) threat apprai sal perceived vulnerabil ity vuln 0.857 vuln1, vuln2, vuln3 perceived severity sev 0.770 sev2, sev3 copin g apprai sal response efficacy eff. r 0.795 eff. r1, eff. r2 selfefficacy eff. s 0.899 eff. s1, eff. s2, eff. s3 response cost cost 0.712 cost1, cost2, cost3 table 1: constructs and reliability of measurement items control variables as control variables, we included gender, size and age. we included gender in the form of a dummy variable (male = 0; female = 1). size was measured through a scale according to the european classification of firms: less than ten employees (micro-enterprises = 1), ten up to 49 employees (small enterprises = 2) and 50 up to 250 employees 10 (medium enterprises = 3). age represents the respondent’s age. 3.3. data analysis to test the hypotheses, a multiple regression analysis was performed using the statistical analysis software spss (version 21). in doing so, we performed regressions of the control variables size, age and gender as well as the independent variables, on ceo’s behavioral intention, our model’s dependent variable. the common method bias was controlled by a harman’s single factor test (podsakoff et al., 2003). the most covariance explained by one factor in our data is 17.6 percent; hence cmv bias was not a problem for our data. 4. results as showed in table 2, the main part of the respondents were male (about three quarters). our proportion of 25 percent of female ceos is close to the 29 percent european figure (european union, 2014). sizes of companies were distributed as follows: 58.8 percent micro-enterprises with less than ten employees, 29.4 percent businesses between 10 and 49 employees, and 11.9 percent of medium-sized businesses. our sample shows a slight under representation of the smallest businesses compared to european figures (oecd, 2013), but remains closer than previous studies dedicated to information security in smbs (gupta and hammond, 2004; lee and larsen, 2009). the average age was around 40 years old (see table 3). variable frequency percent (%) gender male 132 74,6% female 45 25,4% size 0-9 104 58,8% 10-49 52 29,4% 50-250 21 11,9% table 2: demographic characteristics of the sample (n=177) table 3 shows the means, standard deviations, and correlations of our variables. variables mean sd 1 2 3 4 5 6 7 8 9 1. size 1,53 ,70 1 2. gender 0,25 ,43 ,190* 1 3. age 39,9 12,08 -,132 -,087 1 4. vuln. -,008 ,99 -,068 -,047 ,196* * 1 5. sev. ,007 ,99 ,002 ,028 ,047 ,000 1 6. eff. r. ,008 ,99 ,230* * -,151* ,260* * ,000 ,000 1 7. eff. s. ,006 ,99 -,157* -,139 -,095 ,000 ,000 ,000 1 8. cost ,004 1 -,089 -,142 -,091 ,000 ,000 ,000 ,000 1 9. int ,007 ,99 -,104 -,162* ,066 ,224* * ,058 ,298* * ,202* * ,199* * 1 n= 177; significance: *** p < 0.001; ** p < 0.01; * p<0.05 table 3: descriptive statistics and correlations 11 table 4 presents the regression results. we integrated the control variables in model 1 to determine their effects. model 1 reports no significant effects: neither the firm size, gender nor cio’s age impact significantly the behavioral intention. in model 2, to test all hypotheses, we included the different independent variables to examine to which degree they determine behavioral intention. the results of the f-test (f = 8.26; p < .001) are significant. hence, we can reject the null hypothesis, concluding that there is strong evidence that the expected values in the groups differ. we also evaluated the reliability by examining the multicollinearity of measures to determine their variance inflation factor (vif). all vif were less than 2, therefore we can say that all indicators have an acceptable reliability. variables model 1 vif model 2 vif step 1: controls size -,069 1.050 ,002 1.131 gender -,136 1.040 ,053 1.087 age ,045 1.022 ,027 1.163 step 2: main effects vuln. ,232*** 1.056 sev. ,056 1.005 eff. r. ,292*** 1.128 eff. s. ,189** 1.057 cost ,187** 1.039 r² ,031 ,222 adjusted r² ,014 ,185 δr² ,031 ,191 f 1,82 8,26*** significance: *** p < 0.001; ** p < 0.01; * p<0.05 table 4: multiple regression analysis: dependent variable = behavioral intention cio’s behavioral intention is significantly influenced by perceived vulnerability, and by coping appraisal (response efficacy, self-efficacy and response cost). as shown in table 4 and as illustrated in figure 2, the total explained variance is 18.5 percent. figure 2. results for the tested hypotheses (***: p < 0.001; **: p < 0.01; *: p<0.05) behavioral intention (r²=0,185) perceived severity perceived vulnerability response efficacy gender age self-efficacy response cost size coping appraisal threat appraisal 0.232*** 0.056 0.292*** 0.189** 0.187** 0.0020.053 0.027 12 perceived vulnerability (β = 0.232; p < .001), response efficacy (β = 0.292; p < .001) and selfefficacy (β = 0.189; p < .01) serve as significant determinants of behavioral intention to implement security measures. these findings support hypotheses h1, h3 and h4. response cost (β = 0.187; p < .01) had an opposite influence contrary to what was expected, thus h5 is not supported. the influence of perceived severity was nonsignificant, thereby h2 is not supported. none of our control variables, gender, age and size showed any significant effect, therefore h6, h7 and h8 are not supported. 5. discussion table 5 shows the previous studies we identified dealing with the protection motivation theory. papers year target company size models tested behavioral intention actual behavior workman et al. 2008 employees large it firm pmt (threat control model) n/a take measures to protect infos (subjective) + logs (objective) herath & rao 2009 employees all sizes pmt, deterrence compliance with orga issp n/a lee & larsen 2009 executives smb (2008) pmt, social influence support, encourage purchase purchases of antimalware soft ifinedo 2012 employees all sizes pmt, tpb compliance with orga issp n/a vance et al. 2012 administrative city govt habit, pmt compliance with orga issp n/a yoon & kim 2013 employees all sizes pmt, tra take measures to protect info n/a siponen et al. 2014 employees all sizes (2006) pmt, tra compliance with orga issp compliance + recommend & assist johnston et al. 2015 employees city govt pmt, deterrence changing password n/a issp: i.s. security policy table 5: previous studies and characteristics if we compare our respondents with all the previous studies in table 5, only lee and larsen’s study was dedicated to executives (yet nearly 60 percent were is-experts) and to smbs (yet less than 500 employees). we posited that for the smallest sizes of businesses, as no cio exists in the company, ceo’s importance is reinforced in the management of information security. our study is clearly different from the previous ones because:  smbs of our sample follow the european definition: “less than 250 employees”, with an average size of 27 employees (vs. 192 employees for lee and larsen’s study);  we focused exclusively on ceos ;  deterrence theory was not used because we contend that it is more relevant to explain employees’ behavior than ceos’ one ;  as ‘behavioral intention’, we used the implementation of is security measures, as ceos take part and/or support the creation and the implementation of security policies whereas compliance can be seen as more passive and more requested from employees. perceived vulnerability had a strong and significant positive influence on iss behavioral intention. this confirms the results of ryan (2004) and bulgurcu et al. (2010) concerning ceos. the more company’s i.s. is perceived as vulnerable, the more ceos tend to develop or apply iss policies and procedures in their companies. response efficacy and self-efficacy had a positive influence on smb ceos’ iss behavioral intention: our study extends the results of kankanhalli et al. (2003), showing that when ceos have a positive perception of the efficacy of their behavior, they intend to be more secure and to implement iss 13 measures. our results are also in line with the results of ifinedo (2012) and lee and larsen (2009) as we confirmed that behavioral intention is mainly influenced by coping appraisal. another interesting result is that if is-experts accounted for nearly 60% of lee and larsen’s study respondents (2009), 40 percent were non is-experts (ceos, cfos and coos 1 ). they could assess strong differences between is experts and non-is experts. as very often ceos are far from being is experts, our results are also consistent with the fact that behavioral intention of non-is experts is more influenced by coping appraisal, while behavioral intention of is experts is more influenced by threat appraisal (lee and larsen, 2009, p. 184). therefore, the fact that perceived severity had a weak and nonsignificant influence in our study is also in line with lee & larsen’s findings. the size of the company was not relevant to explain ceo’s behavioral intention to take or implement security measures: this means that when the ceo is alone or even if a dedicated function exists (cio or other employee who takes in charge information security), the cio’s level of intention to act doesn’t vary significantly. therefore, our study confirms the importance of ceos’ role in smbs’ iss. surprisingly, response cost influenced positively the ceo’s behavioral intention, which is counterintuitive and contradictory to previous studies results. such result means that the more ceos feel costly their behavior in terms of efforts or inconveniences, the more important their behavioral intention. we can suppose that ceos feel that information security is not only important, but also implies vital and compulsory changes in their smbs. response cost could be, in this case, linked with the perception of iss as a strategic issue and with the level of ceos’ commitment in their businesses. studying the link between response cost, ceos’ commitment and the related stakes, would be an interesting avenue for future research. to conclude with this discussion, in our study the strongest effect was exerted by response efficacy, explaining 30 percent of behavioral intention variance. self-efficacy and response cost also proved to have a significant although lower effect. 5.1. limitations although this study’s findings provide meaningful implications, our study has some limitations. 1 chief x officer. x = e for executive, o for operation, f for finance. first, our research used a web-based questionnaire, which may have introduced response bias because people outside the target population may fill out the questionnaire, or people in the target population could submit more than one response: even if we partially addressed this problem by controlling the respondent’s ip address, by eliminating companies’ sizes over 250 employees, some non-ceos could have filled our questionnaire. second, this study only examined positive actions instead of maladaptive actions which may require further investigation. third, we could not assess the effects of certain variables such as industry type or the fact that a company is it-intensive or not (lee and larsen, 2009). to end, this study did not examine actual iss-related behavior. it would be interesting to compare the behaviors of taking or implementing security measures in large companies (workman et al., 2008) with actual behaviors in smbs. 5.2. implications for researchers and practitioners this study confirmed the importance of ceos’ role in smbs’ iss. smb ceos must realize that they sometimes just have to communicate on the importance of information security or set an example (such as shredding confidential documents), and security measures are not systematically expensive or cumbersome. as numerous meetings and seminars are organized for entrepreneurs, trainings or communications during those events could integrate some advice and insist on good practices related to iss. for researchers, we showed that even if it is relevant to study employees’ behaviors to decrease negative behaviors and improve positive behaviors it is of utmost importance to dedicate more research on smb ceos as they constitute a specific and important population, and as it has been proved that their actions influence employees’ behavior and have a strong impact on smbs’ overall security (barlette, 2012). 14 6. conclusion the involvement of ceos in implementing security measures is important for improving the level of information security in smbs. we tested a model based on protection motivation theory (pmt) using data collected from 177 french smb ceos. the results showed that response efficacy had the strongest effect, explaining 30 percent of behavioral intention variance. self-efficacy and response cost also proved to have a positive and significant impact on ceos’ intention to implement information security 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"top management involvement in project management: exclusive support practices for different project scenarios", international journal of managing projects in business, vol. 1, n°3, p. 387-403. 17 appendix a nb: the colors used for the variables are in line with those of our model. variables authors item code adapted from vance et al, 2012 implementing information security policies in our organization keep is security breaches down. effr1 adapted from vance et al, 2012 if i comply with information security policies, is security breaches are scarce. effr2 vance et al. 2012 i can implement information security policies by myself. effs1 vance et al. 2012 implementing information security policies is easy for me. effs2 lent et al. 2006 i have the capability to solve possible problems during the implementation of security measures. effs3 vance et al, 2012 complying with information security policies would require considerable investment of effort other than time. cost1 vance et al, 2012 there are too many overheads associated with complying with information security policies. cost2 vance et al, 2012 complying with information security policies inconveniences my work. cost3 adapted from vance et al, 2012 if i lost my computerized data, there would be serious information security problems for my organization. sev2 adapted from vance et al, 2012 if my computerized data were temporarily not available, serious information security problems would result. sev3 vance et al, 2012 an information security problem could occur if i did not apply security policies. vuln1 vance et al, 2012 i could be subjected to an information security threat, if i did not apply information security policies. vuln2 vance et al, 2012 my organization could be subjected to an information security threat if i did not apply security policies. vuln3 i intend to implement security measures in the next months. int1 i plan to implement security measures in the next months. int2 age venkatesh et al, 2003 age age gender venkatesh et al, 2003 male =0; female =1 gend firm size european union <10 employees =1 ; 10-49 employees =2; 50-250 employees =3 size control variables coping appraisal adapted from workman et al, 2008; yoon and kim, 2013 behavioral intention perceived vulnerability perceived severity threat appraisal response efficacy self-efficacy response cost 22 the impact of crm on qoe : an exploratory study from mobile phone industry in morocco amine aziza 1 , mourad oubrich 2 and klaus solberg søilen 3 1 institut national des postes et télécommunications (inpt), morocco, 2 madinat al irfane rabat-institutes-morocco, 3 halmstad university, sweden e-mail: oubrich@inpt.ac.ma, amineaziza10@gmail.com, klasol@hh.se received august 10, accepted october 10 5 2015 abstract: today’s mobile phone sector is marked by intensified competition and strong market penetration. in this environment, the carriers offer their customers a wide variety of services that are quite similar from one operator to another. these customers are always searching for a quality of experience (qoe). on one hand, operators interact with their customers through crm practices inspired by their marketing strategies and rolled out through their procedures and technological support. on the other hand, the customers expect an extremely high quality of service (qos) and subjectively perceive the utility and usability (qp) of these mobile services. this paradox led us to study the impact of crm on the customer experience (qoe) in the mobile phone industry, in this study with data from morocco. empirical data confirms existing theory, crm determinants for qoe include quality of service, quality of interaction with customer, claims management and customer knowledge. however, we also found that practitioners are aware that organizations should look beyond the relationship to manage the customer experience. to this end we developed a model based on the first four crm determinants and the findings in this study. keywords: crm, qoe, qos, qp, mobile services, business intelligence, erp available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 2 (2015) 22-35 mailto:oubrich@inpt.ac.ma mailto:amineaziza10@gmail.com https://ojs.hh.se/ 23 1. introduction the field of customer relation management (crm) is linked to that of business intelligence (bi) in that crm systems rely on ever greater sets of data and datamining capabilities. interest in crm has begun to grow in the 1990’s (xu and al., 2002). within the sector of information technology management research, crm has become its own niche thanks to its relative newness and growth explosion (lambert, 2010). according to nguyen (2013), dyché (2001), greenberg (2004), osarenkhoe and bennani (2007), crm allows companies to build a lasting relationship with their customers whilst constantly keeping in touch with them. according to ejaz and al. (2013), crm is considered as one of the best approaches to satisfy and retain customers. the results of their studies have shown that crm has a positive impact on customer satisfaction and on customer experience which in turn directly impact customer loyalty. our research goes in the same direction as that of ejaz and al. (2013), but with a different vision. our objective is to explore the determinants of crm and those of the quality of the customer experience in order to study their causal relationship. the customer relationship is a subject of great interest, especially in the domain of service activities/interactions due to the importance of the "supplier-customer" interface to achieve a high quality of the realization of service (qos) (damperat, 2005). in addition, services have now become a priority; they are by nature "moments of truth", which makes them more sensitive to good perceived quality (qp) in the exchange relationship (giordano, 2006). furthermore, the quality of experience (qoe) is a subjective measure of the adequacy of a service which the customer was expecting. in the literature, we found that there is little empirical research on the study and the measurement of the impact of crm on qoe (research gap). it is important to understand the cause and effect relationship between crm practices and (qoe) in order to establish a conceptual framework. we begin by drawing from the literature of those two concepts, theirs definitions, theoretical foundations, models and functions. secondly, we present the research methodology and the results of the exploratory qualitative study of thirteen crm practitioners. in conclusion, we propose a preliminary conceptual model that links crm to qoe. 2. literature review the customer and the service provider are found in the service relationship in two separate logics (averous, 2004). everyone perceives their service delivery according to their perspective and its repository. the customer repository is one of the affects, the subjectivity and the holistic cognition while as the display domain of the service provider can be defined as the technicality, occupation, objectivity and accountability (averous, 2004). the interaction between the two perspectives is not obvious and requires efforts in terms of listening, proximity and anticipation. from this come the sensitivity and complexity of the crm field of study and qoe for both service providers and customers respectively. as crm advances, so does its multidimensional character. we therefore think that to go through the crm practices and determinants, is worthwhile by studying the link to qoe. the mobile phone industry is a major area for crm practices. the question is how does crm impact qoe? 2.1. crm crm is a strategic concept which draws its basis from economic and social exchange theories and relationship marketing (damperat, 2005). the supporters of transactional exchange paradigm as coase (1937) and williamson (1979) study the customer-supplier relationship in its absolute transactional sense. the paradigm of social exchange supported primarily by hakansson (1982), raises the importance of the social relationship that promotes greater transactional exchange. other authors such as marion (2001), parvatiyar and sheth (2001), arndt (1979) bring the notion of relational exchange that takes into account both transactional and social exchange with a concept of relationship sustainability over à long period of time. since 2000, supporters of the new technology approach as plakoyiannaki and tzokas (2002), grabner and moedritsher (2002), chang and young (2007) and coovi (2010) defend the role of technology in crm. crm can be defined as a business strategy oriented towards the customer (park and kim, 2003). this strategy is supported by information and communication technology and aims to facilitate and improve relationships with customers (lamparello, 2000; mckim, 2002). several definitions have been developed by several authors (table n°1); it appears that the crm is seen as both a business strategy and a technological process (dionne, 2001), thus the increasing importance of business intelligence (bi) and datamining. 24 the depth and specificity of different crm definitions can be seen in the form of crm layers. for instance, trepper (2000) propose three categories: operational, analytical and collaborative crm. collaborative crm includes exchange channels with the customer (chen and al., 2006), while the analytical crm enables the analysis of information gathered (zikmund, 2003) and finally the operational crm, which aims to industrialize the company’s daily contacts with its customers through a pre-established process (cast, 2003; pepper and rogers, 2004). according to lambart (2010), crm is the business process that provides the structure and the way for how customer relationships are developed and maintained. specifically, the crm process is divided into several stages combined with practices. these are defined by chen and russell (2007) as a set of actions taken by the company to retain current customers and attract potential ones. these practices include customer segmentation, database marketing, personalization and one-to-one marketing, proactive selling, cross-selling and loyalty program (peelen and al., 2009). while shaw (1999) defines crm as an interactive process for achieving the optimum balance between corporate investment and the satisfaction of customer needs to generate the maximum profit. objectives and crm functions are multiple; it is a way to get superior financial performance (lambert, 2010; boulding and al., 2005; bohling and al., 2006), a differentiator with a competitive advantage (almquist and al., 2002; missi and al., 2002) and a long-lasting contact support for customer loyalty through long-term relationships (nguyen, 2007; greenberg, 2004; osarenkhoe and bennani, 2007). crm also allows the company to customize and improve the quality of customer service (nguyen, 2007) and to share customers knowledge within and between offices (nguyen, 2007) and consequently to achieve profitable growth (greenberg, 2004) and better performance. crm is considered a strategic approach, oriented toward processes (lambert, 2010; payne and frow, 2006; zablah and al., 2005), it’s cross-functional (lambert, 2010; payne and frow, 2006), a mutual value creator for the buyer and the seller (lambert, 2010; boulding and al., 2005; payne and frow, 2006). the analysis of the most important and various crm models that we found in the literature review allowed us to highlight some determinants (table n°2), where it is recognized that strategy, people, technology, and processes are all important factors in crm (chang, 2007). all models which are found in the literature review are predictive, conceptual and integrators of factors which explain crm. our theoretical contribution will be to study the determinants of crm and their relationship with qoe. 2.2. qoe the customer experience is an interdisciplinary concept that has been the subject of research in various fields including economics, psychology and management (qing et al., 2013). the customer experience is considered a new concept that refers to all the emotions and feelings experienced by a customer before, during and after the purchase of a product or service (gentile et al., 2007). it is a source of satisfaction and loyalty influence (lefranc, 2013). pine and gilmore (1999) were the first who studied the concept of the customer experience and they showed that the customer experience can provide be a new area of competition. table n° 1: crm approaches crm as a business strategy parvitiyar and sheth (2001), buttle (2001), thieriez (2002), zablah and al (2005), singh and al (2003), peppers and rogers (2004), peelen and al (2009), allard and guggémos (2005), rogers and dorf (1999), urbanskienė and al (2008), hobby (1999), dalziel and al (2011), osarenkhoe and bennani (2007), lambert (2010). crm as a strategy supported by technology lamparello (2000), mckim (2002), crosby and johnson (2002), dionne (2001), ramaseshan and al (2006), allard and guggémos (2005). crm as a technological process bose (2002), xu (2002), missi and al (2002), payne and frow (2006), khanna (2001), stone and woodcock (2001), frock (2000), ryals and knox (2001), chen and al (2009). 25 to provide an optimal and a positive customer experience is important, seeing as it impacts customer satisfaction and creates an emotional connection with the brand. it therefore enhances customer loyalty (gentile et al., 2007). the quality paradigm is the theoretical basis of the qoe, through disconformity theory based on the measurement of the gap between customer expectations and performance of the product or service (oliver, 1980; churchill and suprenant, 1982). the american school, known as servqual (parasuraman et al., 1985) suggests a conceptualization of perceived quality seen in ten dimensions and refined in five dimensions: reliability, helpfulness, insurance, tangibility and empathy. in comparison the nordic school defended by grönroos (1990) is based on the work of swan and combs (1976) and identify two dimensions of service quality, the technical quality (what the customer receives) and the functional quality (what the customer perceives). theories of psychology have also treated the customer experience including the ergonomic psychology theory in the context of humantechnology interaction that revolves around usefulness, usability and acceptability (dillon and morris, 1996; tricot and al., 2003). other psychosocial theories analyze the subjective component of the customer experience, mainly the theory of reasoned action (tra) (fishbein and ajzen, 1975), the theory of planned behaviour (tpb) (ajzen, 1991) and the interpersonal behavior theory (ibt) (triandis, 1980). for soldani et al., (2006), the term (qoe) refers to the perception of the user on the quality of a particular service. it is expressed in human feelings as "good", "excellent", "poor", etc. soldani et al., (2006) highlight in their researcs, focused on umts networks, the difference between qos and qoe, stating that the quality of service (qos) is inherently a technical concept. it is measured, expressed, and understood in terms of technical features, mechanisms and procedures between the user equipment and the network, which usually makes little sense for the end user. many methods have been proposed to evaluate qoe subjectively and objectively (xin yu et al., 2012). qoe, is a subjective measure of the adequacy of a service compared to customer expectations. it measures the "rendering" of the use of a service and how a user perceives the conviviality of a service, the satisfaction level that comes with a service in terms of conviviality, accessibility, continuity and integrity of the service (soldani et al., 2006). the literature review allowed us to highlight two different approaches of qoe (table n°3): -the qoe as objective and subjective measure of the customer experience. -the qoe as an evaluation of customer perception, the gap between expectations and performance. 26 table n° 2: summary of the determinants according to different crm models determinant model summary model author strategy the customer connections ernest & young model sign in and get closer to customers to make them real partners allard and derringer, (2000) strategy the model of the idic methodology identify, differentiate, interact, customize peppers and rogers, (2004) strategy, process, hr, organization, customer centric. balanced scorecard calculation of the performance: financial perspective, perspectives related to the customer, internal processes to the business, organizational learning kaplan and norton, (1996) customer centric model based on the several stages of customer life cycle initialization or acquisition maturation and rupture dwyer and al., (1987) customer centric, organization and culture, hr, process, technology the crm value chain primary level are centered on customer and support conditions are focused on profitability buttle, (2001) strategy process technology the model of the strategic framework crm the development strategy the information management the value creation process the process of performance evaluation multi-channel integration payne and frow, (2006) organization et hr service and profit chain model there is a link between satisfaction and employee motivation and customer satisfaction heskett and al , (1994) strategy an integration framework of crm implementation strategy analysis formulation and strategy selection implementation of the strategy osarenkhoe and bennani, (2007) process measures framework of crm impact on economic added value impact on sales, cost of goods sold, total expenditures, inventory investment, other current assets, and investment in fixed assets lambert, (2010) strategy culture contexte conceptual framework for overall crm macro factors: internal and external to the company micro factors: marketing activities, customer focus, buying behavior. conceptual framework for overall customer relationship management ramaseshan and al., (2006) technology strategy hr challenges for overall customer relationship management -technology -economy and market -regulatory framework -culture and social ramaseshan and al, (2006) process hr technology crm implementation the successful implementation of a crm requires an integrated and balanced approach of technology, processes and human resources injazz and popovich, (2003) 27 table n° 3: qoe approaches qoe objective and subjective measure (kilkki, 2008), (rehman and al., 2011), (xin and al., 2012), (mitra and al., 2011), (hassenzahl, 2008), (chen and el zarki, 2011). assessment of customer perception gap between expectations and performance (rehman and al., 2011), (fiedler and al., 2010), (chumpitaz and swaen, 2004), (gentile and al., 2007), (lefranc, 2013), (johnston and kong, 2011), (johnson and mathews, 1997). 3. epistemology and research methodology this research aims to explain the relationship between crm practices and the quality of the customer experience (qoe). to sort out this relationship, we position ourselves within a positivist perspective based on the hypotheticodeductive approach. this epistemological position aims to draw a state of the art to build an adequate theoretical framework for this relationship and derive hypotheses that will bring forward a more representative reality (miles and huberman, 1991) through a qualitative study in order to explore the main determinants of crm practices and the most significant factors in the quality of the customer experience. in this paper, we present an exploratory qualitative study in terms of crm practices in the mobile phone industry. the sample consists of about 60% of practitioners among telephony mobile operators, 16% of vital service provider and 24% of ss2i. interviews were carried out according to an interview guide constructed at the base of the determinants of crm identified from the literature review summarized it in table n°2. for data analysis, we collected, recorded and transcribed data by transcriber application. to this end, we mobilized the content analysis method (bardin, 1977). moreover, with the sphinx lexica, we treated and coded all the answers and we analyzed the verbatim by following the method of parsing (syntactic unit) and semantic (andreani and conchon, 2005). following this analysis, we got answer segments that we have grouped around recurring key ideas that revolve around the five factors: strategy, process, organization, personnel and technology. for greater objectivity, we opted for a statistical analysis of key ideas through coding categories (andreani and conchon, 2005), marking out the words forming these categories. with the method of multiple correspondence analyses (mca) 1 , we have five sets of contingencies tables that intersect in multiple matrices, as variables for each practitioner. at the end we treated statistically the contingency tables by xlstat for the study: the rate of inertia 2 which measures the practitioner’s opinions dispersion around the variables (key ideas) from the center of gravity (crm determinant) as two factorial axes. the factorial axes are the most active components of crm determinant and around which the variables and observations disperse. these are the main terms or combinations formed by matching variables to observations and the observations of each variable (absence, presence, recurrence). the variance of the distribution of the practitioner’s notices by qualitative variable associated with the variance of the distribution of variables per practitioner around factorial axes to represent the eigenvalue. 3 the total inertia rate is the sum of the eigenvalues. when the inertia ratio is high, it means that there is a strong dependence between variables and observations, if the total inertia ratio is low, the variables are independent of observations. the cumulative percentage of inertia indicates the level of inertia or dispersion and can explain the categories of profiles alike. in our research we have practitioners who share the same point of view about the correspondence of the crm determinants. 4. results and interpretations the analysis of the crm determinants components by the mca method allowed us to identify for each determinant, the total inertia ratio, the eigenvalues, inertia percentage and percentage of accumulated inertia. 4.1 the crm strategy determinant crm practitioners mostly confirm the existence of a customer-centric crm strategy and perceive crm as a software tool. they argue that the crm goals are: quality of customer service (qos), satisfaction, customer loyalty and profitability of the company. other objectives were mentioned but with less 1 the multiple correspondence analysis (mca) is a statistical method to study at least the association between two variables, observations (crm practitioners) and terms of observational variables (absence, presence, recurrences). 2 inertia ratio is the sum of the projected variances. 3 this is the projected variance of inter-qualitative variables for a variance inter-practitioners. 28 frequency, for example performance, segmentation, complaints management, customer knowledge. the inertia of the key components of crm strategy is 3,923. this is the highest value of the calculated rate. it indicates that there is a high practitioner’s opinions concentration around the crm strategy variable and its perception as an information technology tool. it’s focus is on a customer-oriented approach, segmentation and claims management means, satisfaction etc. this concentration is measured around the gravity center of all crm strategy components with the first three eigenvalues μ = 0.492, μ = 0.376, μ = 0.318. these values are close together and involve a high association between correspondences of practitioners opinion concerning the crm strategy formulated by the variables listed in table n°4. 4.1.1 eigenvalues, inertia percentage and percentage of accumulated inertia: for table n°5 we have: -the first line represents the rank of the factorial axis considered, p = 23 factorial axes, the second line shows the eigenvalues of the matrix associated with each axis, the third line gives the inertia ratio explained by the axes, the last line gives the cumulative inertia ratio (that is to say, explained the subspace formed by the axis and the previous). the first tree values together account for over 30% of the total inertia opinions of practitioners according to the crm strategy determinant (point cloud), so we can therefore consider other significant factorial axes that represent a combination of correspondences (variables strategy and practitioners). we can extend the factorial space to f13 which shows over 77% of the total inertia of the point clouds. 4.2 the crm process determinant the practitioner’s descriptions of the crm process allowed us to deduce a perceptual schema crm process. this scheme focuses on the phase and the quality of interaction with customer, customer data collection stage, qualification of customer data and integration of multi-channel communication with crm. table n°5: the 23 factorial axes . f1 f2 f3 f4 f5 f6 f7 f8 own value 0,492 0,376 0,318 0,280 0,253 0,227 0,198 0,188 inertia (%) 12,542 9,579 8,106 7,142 6,446 5,775 5,055 4,801 %accumulated 12,542 22,121 30,227 37,369 43,815 49,590 54,645 59,446 f9 f10 f11 f12 f13 f14 f15 f16 own value 0,166 0,147 0,144 0,131 0,124 0,113 0,098 0,094 inertia (%) 4,232 3,743 3,674 3,335 3,153 2,874 2,501 2,396 %accumulated 63,679 67,422 71,095 74,43 1 77,584 80,45 8 82,959 85,356 f17 f18 f19 f20 f21 f22 f23 own value 0,090 0,088 0,084 0,081 0,078 0,077 0,077 inertia (%) 2,283 2,252 2,138 2,071 1,979 1,961 1,961 % accumulated 87,638 89,890 92,029 94,100 96,078 98,039 100,000 table n°4: semantic recurrences related to the practitioners crm strategy variable. v a r ia b le s tr a te g y c u st o m e r c e n tr ic s tr a te g y e x is te n c e to o l s a ti sf a c ti o n q o s p ro fi ta b il it y l o y a lt y s e g m e n ta ti o n p e rf o rm a n c e m a n a g e m e n t o f c la im s c u st o m e r k n o w le d g e a c ti v it y r e p o rt in g p ro x im it y a n ti c ip a ti n g c u st o m e r w a ll e t p ro c e ss la u n c h n e w p ro d u c t d a ta c u st o m e r fo c u s b u si n e ss c o m p e ti ti v e a d v a n ta g e p ro d u c ti v it y c o st u m e r c o n q u e st r e c u r r e n c e s 14 11 10 10 9 8 8 5 5 5 5 4 4 4 3 2 2 2 2 2 4 2 1 1 29 the determinant crm process is in the second position with inertia ratio of 2.6. the analysis of crm process asymmetric graphic components and observations shows that there are three different categories of profiles but closely spaced. the majority of practitioners category which recognizes the existence of the crm process confirms its efficiency and describes it as a series of phases: customer interaction stage, customer data collection stage, qualification and treatment of data customers stage, quality interaction with the customer, billing, claims management, through procedures and certifications that enact the script and interaction with the costumer in order to satisfy and offer them the best qos. also there is a class of practitioners who focuses on respect of charters, crm procedures and scripts, the quality of customer interaction and multi-channel integration with communication channels and finally another group who perceive crm process through the interaction with the customer stage, customer data collection stage and the multi-channel integration with the communication channels in the crm. thanks to iso certification standards, charters, scripts and quality procedures, the crm process is considered efficient and cover among other aspects of the company's business, billing and claims management. the efficiency of the different crm processes respectively depends on: targeted training around the crm function and delivery by the team which in most cases is conducted to work in networks, the sensitization and assessment system of crm human resources and their professional skills. the first three eigenvalues are: μ = 0.413, μ = 0.348, μ = 0.316, they are close together which explains that there is a significant association between concepts, listed in table n°6 to explain the crm process. own values, inertia percentage and percentage of accumulated inertia: f1 f2 f3 f4 f5 f6 own value 0,413 0,348 0,316 0,297 0,249 0,196 inertia (%) 15,902 13,387 12,149 11,422 9,571 7,548 % accumulated 15,902 29,289 41,439 52,860 62,432 69,980 f7 f8 f9 f10 f11 f12 own value 0,187 0,155 0,138 0,114 0,099 0,086 inertia (%) 7,211 5,978 5,312 4,370 3,823 3,327 % accumulated 77,191 83,169 88,480 92,850 96,673 100,000 table n°7: the 12 factorial axes 4.2.1 eigenvalues, inertia percentage and percentage of accumulated inertia: for table n°7 we have: the factorial axis rank is p = 12, the first 3 values together account for over 41% of the total inertia practitioners opinions in relation with crm process determinant. we can think about other factor axes that are significant and represent the combination of correspondences (process variable and practitioners). we can extend the factorial space to f5 with more than 62% of the total inertia of the point clouds. 4.3 the crm organization determinant the crm function is considered by a minority of practitioners as a call center job. crm is a project table n°6: semantic recurrences related to crm process according to practitioners. concepts number of occurrences interaction with the customer phase 18 integration multi channels with crm 16 qualification and customer data processing 15 efficiency procedure 11 collecting customer data phase 10 claims management 9 quality of interaction with the customer 8 billing 8 charter, user guide, scripts respect 7 quality of service 5 iso certification, internal procedures 5 satisfaction 3 existence of crm procedures 6 absence of crm procedures 1 30 that is often supported by top management but without a specific function in the organization. in addition, it is located halfway between the marketing function, the business function, the customer service function and sometimes the information system direction (isd). the determinant of the crm organization gives us an idea about the crm position inside the service provider’s organization. its inertia ratio is 2.286 and it comes third after the crm process determinant. we found that there are three positions categories with average dispersion. there is a category of practitioners where the crm is positioned at the top management level and largely deviates from the two other categories. the second category positions crm into the sales function level with an average concentration of observations around this variable. the third category consists of practitioners who share their opinions around a crm organizational position that integrates the marketing function, is direction, management services and customers, n-1 levels of top management and the sales office. the first three eigenvalues are μ = 0.413, μ = 0.315, μ = 0.281, they are less close together which explains that there is a less significant association between the variables representing crm organization listed in table n° 8. own values, inertia percentage and percentage of accumulated inertia: 4.3.1 eigenvalues, inertia percentage and percentage of accumulated inertia: table n°9: the 12 factorial axes we considered twelve factorial axis p = 12, the first tree values together account for over 44% of the total inertia practitioners opinions related to the crm organization determinant. also we can take into account other factorial axes. we can extend the factorial space to f5 with more than 62% of the total inertia of the point cloud. 4.4 the crm technology determinant the technological component of crm comes in the fourth position with 1,81 as total inertia ratio. there are several categories of profiles relatively dispersed according to their crm expectations but concentrated into two categories. the first category of practitioners use the software crm (integrated crm software in the erp, crm-sql, vocalcom, nobelsystem, software grc, efbi platform, microsoft dynamic crm, sap crm, saleforces, zoho, sugarcrm) and other software managements such as elag and business management software. they are interested in reports generated by the crm and indicators that these reports occur. while the second category consists of a minority of practitioners who are aware of the importance of the crm software and dashboards they generate, they don’t use it in their own activities because they are involved as ss2i; in other words as, assistant project manager in crm solutions integration. these results reflect the overall vision of a recent study published by the gartner institute for the year 2014 "magic quadrant for business intelligence and analytics," especially for the point of operational and decision-making ability of crm that are raised f1 f2 f3 f4 f5 f6 own value 0,41 3 0,31 5 0,28 1 0,22 5 0,20 4 0,17 9 inertia (%) 18,0 77 13,7 76 12,2 89 9,85 7 8,91 4 7,84 8 %accumul ated 18,0 77 31,8 53 44,1 43 54,0 00 62,9 14 70,7 62 f7 f8 f9 f10 f11 f12 own value 0,149 0,133 0,124 0,094 0,087 0,081 inertia (%) 6,526 5,817 5,404 4,132 3,801 3,560 % accumulated 77,288 83,105 88,508 92,640 96,440 100,000 table n° 8: semantic recurrences according to the crm organization concept number of occurrences top management 9 business function 8 existence of responsible unit 7 management services and clients 6 marketing function 5 customer relationship centre 4 level n-1 3 is direction 3 marketing officer 3 networks team 3 claims management centre 2 sales management 2 31 in this report. the report also highlights that "historical leaders of the crm market: oracle, microsoft, ibm and sap are this year the big losers” with a speed loss on the clear quadrant. the first three eigenvalues of crm technology determinant are μ = 0.360, μ = 0.234, μ = 0.193. they are less close which explains that there is less and less of an important combination between concepts that represent the crm technology that we list in table n°10. table n° 10: semantic recurrences on crm technology according to practitioners concept number of occurrences specific software 9 other software 6 dashboard 2 performance report 5 accessibility and flexibility 8 excellent experience, satisfaction and customer knowledge 7 managements indicators 6 performance indicators 6 sales report 4 marketing campaign report 4 periodic reports 4 independence 4 profitability 4 performance 4 predictors 3 reliability 3 management report 2 sale force automating 3 zoning report 2 according to the data analysis, the most cited crm tools are the specific solutions (sap crm, saleforces, zoho, sugarcrm, microsoft dynamic crm, crm-sql software vocalcom, nobelsystem) or other management solutions. they are either integrated into erp, operated in open source configuration, internally developed or developed with the help of a professional integrator. nnn we noted the positive feedback toward practitioners dashboards generated by their crm. the periodic sales tables, marketing campaigns and performance are the most cited and produce management indicators, predictive and performance indicators. they are deployed in the decision making on several levels. however, it must be said that crm practitioners still expect more accessibility, flexibility, reliability and independence of their information technology solutions to impact the customer experience and to know them better in order to satisfy them. 4.4.1 own values, inertia percentage and percentage of accumulated inertia: f1 f2 f3 f4 f5 f6 own value 0,360 0,234 0,193 0,161 0,158 0,156 inertia (%) 19,875 12,943 10,666 8,898 8,754 8,638 %accumulated 19,875 32,818 43,484 52,383 61,137 69,775 f7 f8 f9 f10 f11 f12 own value 0,124 0,114 0,096 0,078 0,076 0,059 inertia (%) 6,840 6,313 5,312 4,321 4,201 3,239 %accumulated 76,615 82,927 88,239 92,560 96,761 100,000 table n°11: the 12 factorial axes we consider 12 factorial axes, the first tree values together account for more than 43% of the total inertia of the point cloud. beyond third factor, the difference between values becomes insignificant, so we limit ourselves to f3. 4.5 crm human resources determinant the determinant of human resources is the latest one with a total inertia ratio of 1,286. it means that practitioners disagree with a wide dispersion about the key components of human resources namely staff skills, training on crm and sensitization and assessment systems developed around crm. the analysis of asymmetric graph of variables and observations showed a big gap between the profiles of practitioners and high data dispersion. the first three eigenvalues of the hr crm are μ = 0.707, μ = 0.327, μ = 0.252. they are not at all close, which explains that there is a weak association between concepts that represent the human resources as a determinant of crm. table n° 12: semantic recurrences related to human resources crm according to practitioners concepts number of occurrences staff skills 12 crm training 30 sensitization system around crm 10 assessment and control system 16 32 4.5.1 own values, inertia percentage and percentage of accumulated inertia: f1 f2 f3 own value 0,707 0,327 0,252 inertia (%) 54,957 25,442 19,601 % accumulated 54,957 80,399 100,000 the first line represents the rank of the considered factorial axis, p = 3 factorial axes, the first tree values together account for 100% of the total inertia practitioners opinions according to hr crm determinant. we can limit our analysis to the first factor with 54% of inertia and for more significations connections we can also consider the second axis with more than 80% of the total inertia of the point clouds conclusion to conclude, crm is a strategic choice for enterprises and mainly for mobile phone service providers. they have to guide the overall strategy toward the costumer. in other words, it is essential to rethink the organization and business structure around customer service, train and develop management and it skills related to crm, implement an effective process and support it with technology. the objective is to offer consequently a quality customer experience in the use of services across crm practices. furthermore, we understand with evidence that interactive links between the determinants of crm and the determinants of the quality of the customer experience (qoe) exist. on one hand, the semantic analysis of crm determinants brings up the determinants that we found in the literature review of the quality of customer experience, like quality of service, quality of interaction with customer, claims management and customer knowledge. and on the other hand, it turns out that practitioners are aware that we should look beyond the relationship to manage the customer experience to satisfy and retain thereafter. to this end, we will propose a preliminary model built around the first four crm determinants taking into account the results obtained (figure n°1) of 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(2003), “customer relationship management: integrating marketing strategy and information technology”, hoboken, n. j.: wiley. 23 synergy between competitive intelligence and knowledge management a key for competitive advantage jihene chebbi ghannay1 and zeineb ben ammar mamlouk 2 1esct, tunis, tunisie, jihene.ghannay@yahoo.fr 2essec, tunis, tunisie, zeinebbenammar@yahoo.fr received 5 may, revised form 11 september, accepted 27 september 2012 abstract: the market orientation perspective states that organizations have no option but to look beyond internal business activities and to integrate events from the external environment. these are complex, turbulent and rapidly changing. firms today are led to utilize information and the knowledge of companies because to succeed in the information economy comes from harnessing these resources. knowledge and information become strategic, paramount and must therefore be managed. integrating knowledge management (km) and competitive intelligence encourage the use of these resources, improve their quality and allow an enterprise to respond more rapidly to changing business conditions. the aim of this article, is to present similarities, differences, benefits of km and ci for the organization through the study of current literature. besides, we present critical success factors needed to achieve a successful implementation of these two processes, and further, highlight the importance of km and ci integration for the organization to compete in the knowledge economy. keywords: knowledge management, competitive intelligence, competitive advantage 1. introduction the globalization of markets accompanied by rapid change in information technology has increased the competitiveness in most industries. in the struggle to remain competitive, many companies have turned to new technologies to improve their business activities. this development is also true for information-related activities and will directly affect the development and quality of a firm’s business and corporate level strategies. these activities are integrated in the ci and km functions of the company. deed and hill (1996) argue that ”firms that are acquiring kno wledge will be able to create and sustain a competitive advantage in the knowledge-based economy. those (firms) that are not will have difficulty maintaining their competitive position”. ci has long been recognized as a strategic management tool and a fast growing field. ci is rapidly becoming a major technique for achieving competitive advantage (davis, 2004). essentially, ci involves the legal collection of information on competitors and the overall business available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 23-34 mailto:jihene.ghannay@yahoo.fr mailto:zeinebbenammar@yahoo.fr https://ojs.hh.se/ 24 environment. the knowledge gained from this information is used to enhance the organization’s own competitiveness. as such, ci can also be viewed as a subset of km. organizations possess numerous resources, but it is the resources that are unique, inimitable, and valuable which are central to a competitive advantage (barney, 1986, 1991; prahalad and hamel, 1990; wernerfelt, 1984). an organization’s knowledge is one such resource. according to civi (2000) and gupta, iyer, and aronson (2000), the only competitive advantage that organizations will have in the 21st century is what they kno w and ho w they use it. this is because the proper management and leveraging of knowledge can propel an organization to become more adaptive, innovative, intelligent and sustainable (wong & aspinwall, 2004a). in fact, km has become an important strategy for improving organizational competitiveness and performance by applying it to production, marketing, research and development, personnel, planning and inno vation. it is also considered as creating sustainable competitive advantage for organizations (king and zeithaml, 2001; johannessen and olsen, 2003; lado and wilss, 1994; ofek and sar vary, 2001). thus, the vision of km is to improve a firm’s competitive powers or to maintain a firm’s competition powers. km is the management of knowledge assets within an organization to enhance competitive power by steering product, leadership, operational excellence, and customer intimacy. 2. literature review 2.1 defining ci ci is a current topic in the business world today. hence, workshops, seminars, training courses and books have been increasing in numbers steadily since 1980. ci has been reported as one of the fastest growing disciplines in the us (scip, 2000; miller, 2000; kahaner, 1998). the concept of ci is very vague, numerous definitions of ci available in literature are imprecise and inclusive, and the expression is often used integrally with other related concepts such as a business intelligence and competitor intelligence. practitioners and theorists have largely failed to agree on a common definition of ci. although, consensus about some aspects of the function have been achieved, fuld & co., a high profile ci consulting firm, takes an inclusive approach in defining the function of ci thus: “competitive intelligence can mean many things to many people. a research scientist sees it as a heads-up on a competitor’s new r&d initiatives. a salesperson considers it as an insight on how his or her company should bid against another firm in order to win a contract. a senior manager believes intelligence to be a long-term place and its rivals” (fuld & co, 2002). the society for competitive intelligence professionals (scip), gives a more precise definition: “a systematic and ethical program for gathering, analyzing, and managing external information that can affect your company’s plans, decisions, and operations. put it another way, ci is the process of enhancing marketplace competitiveness through a greater-yet unequivocally ethical-understanding of a firm’s competitors and the competitive environment” (scip web site, 2002). ci can be defined, also, as knowledge and foreknowledge about the external operating environment. the ultimate goal of each intelligence process is to facilitate decisionmaking that leads to action. “competitive intelligence is a formalized, yet continuously evolving process by which the management team assesses the evolution of its industry and the capabilities and behavior of its current and potential competitors to assist in maintaining or developing a competitive advantage. (prescott and gibbons, 1996). 2.2 km definition km is often viewed as multidimensional and multidisciplinary concept. there are many definitions of km in the literature, thus comparisons must be made to know the focus by each author. some of the focuses are highlighted below. professor michael sutton (2008) of the gore school of business at westminster college reported at the ickm (international conference on knowledge management) meeting in 2008 that he had assembled a library of more than 100 of them (mclnerney c and koeing m, 2009). three definitions of km ones are presented here. at the very beginning of the km movement, davenport (1994) offered the following: “knowledge management is the process of capturing, distributing, and effectively using 25 knowledge”. this definition has the virtue of being simple, stark, and to the point. a few years later, the gartner group created another definition of km, which is perhaps the most frequently cited (duhon, 1998): “a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise’s information assets. these assets may include databases, documents, policies, procedures, and previously un-captured expertise and experience in individual workers”. finally, the definition given by peter drucker (1994), whom many consider as the father of km, defines the need for this function: “knowledge has become the key resource, for a nation’s military strength as well as for its economic strength (...) is fundamentally different from the traditional key resources of the economist—land, labor, and e ven capital (...) we need systematic work on the quality of knowledge and the productivity of knowledge (...) the performance capacity, if not the survival, of any organization in the knowledge society will come increasingly to depend on those two factors”. 3. ci and km processes 3.1 ci process the ci process consists of the following steps: monitoring business environment (external data, information and knowledge), gathering, analyzing, filtering and disseminating intelligence that will support decision making process in order to increase competitiveness and improve position of organization. figure 1: ci process many versions of the conceptualization of the ci cycle can be found in the literature. to show their similarities and differences, table 1 presents the basics steps identified by several authors, each of whom divides the ci process into four to six phases. 26 table 1: models of ci cycle information management cycle (cheo, 2002) cia (2001) fuld & co, (2002) pirttila (1998) kahner(1998) miller (2000) identification of information needs (1) planning and direction (1) planning and direction (1) definition of competitor and information needs (1) planning and direction (1) identification on key decision makers and intelligence needs information acquisition (2) collection (2) secondary published information sources (2) systematic collection of competitive information (2) collection (2) collection (2) primary source collection (3) organization and storage (3) processing (3) screening analysis of collected information (3) analysis and production (4) analysis and production (4) analysis (3) analysis (3) information production and services (4) report and information information distribution (5) dissemination (5) distribution related user groups (5) dissemination (5) dissemination (5) information use (6) the models presented in table 1 are similar; however, some distinctive dimensions are evident. regarding the first step, we see that, despite the different titles, each model recognizes the importance of identifying the type of intelligence/information that is needed to begin the process. although planning should be the starting point of any process, we argue that, in the ci cycle, planning relates mainly to the identification of the intelligence needs that must be fulfilled and of the various activities and analyses that are required to fulfill such needs. each model also includes a collection or acquisition stage as a second step. fuld & co. differentiates the collection of information in two parts: secondary/published and primary sources. after the collection of information, the only ci cycle that identifies a step related to the processing of information is the cia model. in comparison to the information management cycle, the organization and storage of information is a step that is regularly overlooked by the ci community. this step is key to an effective information-related system. all ci models presented here include an analysis stage. although it is not part of the information management model, this stage is an integral part of any intelligence process. analysis transforms information into intelligence using a variety of techniques. pirttilä’s model, which omits the organization and storage step, includes “screening” in the analysis step. 3.2 km processes we earlier defined knowledge management as performing the activities involved in discovering, capturing, sharing, and applying kno wledge so as to enhance, a cost-effective fashion, the impact of knowledge on the unit’s goal achievement. thus, knowledge management relies on four main kinds of km processes. as shown in figure 2, these include the processes through which kno wledge is discovered or captured. it also includes the processes through which this knowledge is shared and applied. these four km processes are supported by a set of seven km 27 sub-processes, as shown abo ve with one subprocess — socialization— supporting two km processes (discovery and sharing). of the seven km sub-processes, four are based on nonaka (1994). focusing on the ways in which knowledge is converted through the interaction between tacit and explicit knowledge, nonaka identified four ways of managing knowledge: socialization, externalization, internalization, and combination. the other three km sub-processes — exchange, direction, and routines — are largely based on grant (1996) and nahapiet and ghoshal (1998). figure 2: km processes 4. ci and km benefits for the organization 4.1 ci, which advantages for the organization? according to prescott and bhardwaj (1995), ci practitioners believe ci programs provide the following benefits: • influencing actions of decision-makers • improving early warning signals • identifying new opportunities • exploiting competitor vulnerabilities • sharing of ideas • better serving the company’s customers prescott and bhardwaj (1995) argue that these benefits are directly identifiable, although there are no quantitative measures to support this. an improved market position and improved revenue/profits are not directly identifiable since they are “uncertain effects”. these benefits fall into the category of bottom-line measures, which are usually the most commonly requested. simon and blixt have tried to measure these uncertain effects. they describe the relevant issues to be measured when considering uncertain effects or monetary benefits of a ci program as: • quality, relevance, timeliness, and accuracy of intelligence • accuracy of data in analysis • increasing number of clients and additional business from current clients • business success and performance measured by industry benchmarking ci re veals the state of business, exposes the unkno wn, and sho ws how to tackle current market conditions. it helps recognize risks and new market opportunities earlier and act faster. good ci delivers often surprising truths, gives a head-up on what’s coming, and equips the organization with the knowledge to outmaneuver the toughest rivals. using the accurate and objective knowledge, good ci provides particularly during unpredictable and turbulent time can gain better control over their business in the future. 4.2 benefits of km 28 according to modern approaches, km is already considered as a key factor in the organization's performance and, the best resource and the only sustainable competitive advantage to individuals and organizations, because it deals with different resources that can aid decision makers in many ways (keen, 1991). most commentators writing on the subject highlight the primary purpose of km as efficiency and productivity achieved through the reuse and sharing of experience and know-how. often overlooked is the potentially important goal of promoting quality of work product and practitioner training that can be shown to increase the value of the client service. km can serve a wide variety of purposes. according to petter gottschalk, of the department of technology management at the norwegian school of management, "effective knowledge management pays off in fewer mistakes, less redundancy, quicker problem solving, better decision making, reduced research development costs, increased worker independence, enhanced customer relations, and improved service”. table 2: benefits and challenges of km benefits of km challenges of km fosters innovation requires full employee participation improves efficiency requires constant updating improves coordination and efforts must sort useful knowledge from useless information enhances customers and employee satisfaction -km projects are not always successful in term of increased profit margins and reduced costs improve response time rewards employees improves market time responsive to market changes reduces costs encourages free flow of ideas connects geographically dispersed people (e.g., customers, employees, suppliers, and consultants) foster collaboration improves information access expertise localization 5. km and ci success factors 5.1 key success factors of ci according to stanat (1990) no single system architecture can be found appropriate for developing a successful intelligence program because of cultural and structural issues. ci process is likely to be unique in each organization. therefore, there is rarely a similarity between successful ci processes. despite, some general success factors and guidelines can be mentioned. in fact, ci process should reflect the organizational culture, available resources and goals of each specific company (gilad, 1985; fuld, 1997). 5.1.1 top management support and participation the support from top management is considered the most important success factor for ci implementation success. intelligence operations should have full senior management commitment and an operating mandate from the top. an intelligence strategy must have full support at board level if it is to succeed (bord, 1997; kahaner, 1996). it is also essential to make sure top management has the available intelligence at their fingers (hering, 2000). 5.1.2 identifying ci needs 29 the company’s management must view the ci as a key resource for better decision-making. this means identifying the impending threats, becoming important and alert management to new business opportunities. 5.1.3 ci culture/ awareness for a company to use its efforts successfully, an appropriate ci culture that support open communication, team spirit, information and knowledge sharing and focus on shared goals, is necessary (olivier et al., 2003). according to calof (2000) the attitudes of people when they don’t trust ci, and are unwilling to share information is considered a main barrier that prevent firms from effectively gathering and using ci. the organization should develop programs that make people want to share their knowledge and acquire new one (iivonen and huotari, 2000; den hertog and hnizeng, 2000). 5.1.4 ci tools and resources a good ci functions must also have adequate resources to deliver the required judgments, insights, and analysis that support the management’s decisions. asking one or more individuals to “take responsibility for the company’s ci” requires providing them with the budget and resources for professional development, outsourced research, and technology tools to implement and succeed with a ci process. 5.2 key success factors of km km covers a wide range of functionalities and support different sets of activities. some factors are considered critical for the successful implementation. however, there exist different views among practitioners and researchers on how a km program can be designed and implemented in organizations. several studies have proposed several key variables for successful implementation. 6. km and ci to achieve competitive advantage 6.1 what is meant by competitive advantage? concept of competitive advantage has a long tradition in the strategic management literature. ansoff (1965) defined it thusly: “(...) (to) isolate characteristics of unique opportunities within the field defined by the product-market scope and the growth vector. this is the competitive advantage. it seeks to identify particular properties of individual product markets which will give the firm a strong competitive position”. 30 table 3: success factors of km researcher success factor for using knowledge managemenr kuan yen wong (2005) senior management support, culture, information technology, strategy and goals, measures, organizational infrastructure, activities and processes, motivational support, resources, education, human resources management mathi (2004) knowledge-base d organizations, culture strategy, systems and information technology infrastructure, systematic and effective process, measures. martins et al. (2003) organisationnel culture, motivation and skills, senior management, structures ans process, information technology moffett et al. (2003) a friendly organizational culture, senior management leadership and commitment, employee involvement, employee training, trustworthy teamwork, employee empower ment, information system infrastructure, knowledge structure reyan and prybutok ( 2001) an open organizational culture, senior management leadership and commitment, employee involvement, teamwork, information system infrastructure devenport et al. (1998) technology infrastructure, organizational infrastructure, balance of flexibility, evolution and cost-ofaccessibility to knowledge, shared knowledge, knowledge friendly culture, motivate d workers who develop, share and use of knowledge. hospal and fusion (1997) management factors, coordination, control, leadership and measures ; factors related resource : knowledge, people, financial and non-financial resources , environmental factors : competition, markets, time pressures, economic and government situation. nnn south (1981) defined competitive advantage as the “philosophy of choosing only those competitive arenas where victories are clearly achievable”. porter (1985) states "competitive advantage grows fundamentally out of value a firm is able to create for its buyers that exceeds the firm's cost of creating it." he argued that a firm’s ability to outperform its competitors lay in its ability to translate its competitive strategy into a competitive advantage. competitive strategy entails positioning the firm favorably in an industry relative to competitors. he confirmed that there are, in general, only two possible competitive advantages a firm may possess, a cost advantage or a differentiation advantage. others, particularly proponents of the resourcebased view of the firm (barney, 1991; conner, 1991), have extended the definition to include a wider range of possible advantages such as physical capital (williamson, 1975), human capital (becker, 1964), technological opportunities and learning ( teece, 1980; 1982; 1986), and organizational capital (tomer, 1987). 6.2 synergy between ci and km to obtain competitive advantage knowledge management (km) is the process through which organizational performance is improved through better management of corporate knowledge. its goal is to improve the management of internal knowledge processes so that all information required for corporate decisions can be made available and efficiently used. competitive intelligence (ci) is a process for gathering usable knowledge about the external business environment and turning it into the intelligence required for tactical or strategic decisions. both km and ci systems are designed to enhance the information resources of an enterprise, but often target different information types and sources. while ci is concerned with gathering information from the external environment to enable the company to gain competitive advantage (williams, 2002), most investigation into km has focused on capturing the knowledge stored within the minds of individual employees (nidumolu, subramani, & aldrich, 2001). bagshaw (2000), johnson (2000), rubenfeld (2001), and williams (2002) all focus on the use of km for collecting, 31 managing, and sharing internally generated knowledge. the combination of effective km and appropriate ci provide the right mix of the right information to the right decision maker at the right time. certainly, these two fields are starting to blend into the same melting pot. however, each field has some unique qualities that differentiate it from the other. table 4: a comparison between knowledge management and competitive intelligence the fields of ci and km have a number of differences as shown on in the table abo ve, but potential relation can exist if we instinctively regard them in terms of applying enterprise knowledge of the internal and external environment for long-term competitive advantage. the goal of both disciplines is to evaluate the business decisions, locate and deliver appropriate knowledge from within and without the organization and, in the end help to give it meaning and help decision makers. according to bensoussan (1996), the keys to a company’s future are not found in forecasts, predictions or media gurus, but through patiently, carefully and strategically turning a company’s knowledge into competitive intelligence”. she identifies the components of ci as available data and expert judgment, and calls for intelligence to be “future-oriented, accurate, objective, relevant, useful, and timely”. in other words, each drives the other. as sho wn earlier in table 3, although there are significant differences in the focus and activities of km and ci, they “have similar goals and are natural extensions of one another (e.g., manage information overload and timely/targeted information delivery, provide tools for data analysis, identify subject matter experts, enable collaboration)” (meta group, 1998). davenport (1999) even goes so far as to take the stance that ci can be viewed as a branch or subset of km. figure 3: the kmci relationship. (source: katherine shelfer, drexel university, 2004) the study conducted by breeding (2000) at shell services international (sii) shows how ci activities at ssi have been impacted by the extensive use of km. it is demonstrated that 32 using the ci/ km system gives more time to higher value-added tasks such as simulation, strategy. 7. conclusion as discussed above, km and ci are distinct by being both complementary and synergistic. at their core, both fields are concerned with gaining competitive advantage from better applications of information or knowledge. knowledge may perhaps be the only remaining and one of the most critical sources of competitive advantage available to an organization in the 21st century. this is true; more so, as previously available traditional resources may no longer offer any significant competitive advantage. to remain competitive, organizations must create and use new knowledge. ho wever, the current practices in knowledge acquisition, utilization, and management are mostly limited to capturing, recycling, and deploying the existing information, and making it available on a technology platform. km and ci are in this regard two important strategies or practices through which organizations could use effective knowledge to improve organizational effectiveness, improve productivity, improve decision making, and especially, obtain a sustainable competitive advantage. even if it is difficult to simplify the relationship between ci and km (johnson, 1999), it is obvious that the two approaches complement each other. km and ci are two parts of the same whole because both are designed to apply enterprise knowledge of the internal and external environment for long term competitive advantage. the synergy between km and ci indicates that greater convergence between the two approaches (parker and nitse, 2011). references bagshaw, m. 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(2016) users’ perceptions of data as a service (daas). journal of intelligence studies in business. 6(2) 43-51. article url: https://ojs.hh.se/index.php/jisib/article/view/159 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index users’ perceptions of data as a service (daas) klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article users’ perceptions of data as a service (daas) klaus solberg søilen department of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se received 3 august 2016; accepted 25 august 2016 abstract in this study, 190 market intelligence (mi), competitive intelligence (ci) and business intelligence (bi) professionals and experts were asked about data as a service (daas). findings show there were few limits or restrictions on what kind of data users could imagine buying or renting, if all types of data were available. data that is more sensitive—personal data and private data—will be difficult to buy, users think. company secrets and most data for business-to-business (b2b) industries is especially difficult to obtain. the major concerns for daas from a user perspective are confidentiality, quality, reliability, security and accessibility. besides, it is often pointed out by users that when everyone has much of the same data competition will increase. users want to see more on company metrics, less expensive, more secure and more flexible data solutions. the analysis reveals that the ethical dimension are a major concern as daas develops. an extensive discussion follows, which also addresses new points. keywords business intelligence as a service, daas, data governance, data steward, dbaas, ethics, intelligence as a service (iaas), management of data 1. introduction intelligence today is inseparable from information technology (it) systems, special software (business intelligence) and big data. now one can buy or rent data, and this is referred to as data as a service (daas). many suppliers only want users to see the actual intelligence or end analysis, not the raw data, as they are afraid that customers could sell it on or make their own analyses. like many analysts, daas providers are hesitant to describe their scientific method and calculations, hoping instead that users will accept their business models and trust them. daas is a cloud-assisted service that delivers data on demand through an application programming interface (api) (vu et al. 2012). daas can also be said to be the shifting philosophy of data ownership to data stewardship (rajesh et al., 2012, p. 26). daas was first used primarily in web mashups (rajesh et al., 2012). a mashup in this context is a web page, or web application that uses content from more than one source to create a single new service displayed in a single graphical interface. many early business intelligence companies are built on the same technology, like agent24 in sweden. daas can be seen as ready-made, or tailormade intelligence packages. the connection to intelligence is strong for vendors, for example in oracle. for them daas is “intelligence from external sources”, to create “action”, meant as something wider than decisions. daas can also be seen as a logical step from previous aas-products from infrastructure aas (amazon web services), platform aas, software aas (google email, google doc.) and database aas. for dbaas see curino et al., 2011 and seibold et al., 2012. database-as-a-service (dbaas) was brought forward as traditional relational database systems proved to be unable to efficiently manage big data datasets. it was first with cloud computing that the opportunity arose, especially with the model journal of intelligence studies in business vol. 6, no. 2 (2016) pp. 43-51 open access: freely available at: https://ojs.hh.se/ 44 known as dbaas (abourezq and idrissi, 2016). with dbaas one still owns the data. this is not so with daas. to have one’s own database feels safer that placing data in the cloud, so the question still remains open as to just how bright the future of daas is. when it comes to valuable information, consumers are particularly concerned about privacyprotection. the problem has been studied and a solution was suggested by canard and devigne (2016). there is also business intelligence as a service (chang, 2014). it offers data access through a web interface, where the implementation and details are hidden from users. the business processes are orchestrated in a simpler and faster manner (sano, 2014). what has created the right conditions for daas is the growing desire to seek competitive advantage from the use of big data and the challenge of managing increasingly complex and heterogeneous data landscapes (pringle et al., 2014, p. 29). daas is being brought forward by advances in cloud computing as it avoids the overly scaled computer infrastructure that includes not only dedicated space, but expensive hardware and software (sharma, 2015). users’ perceptions of business intelligence (bi) have been studied many times, for example by sabanovic and solberg søilen (2012) and by nyblom et al. (2012). no one has studied customers’ perceptions of daas empirically. it’s essential for suppliers to know how to package and sell different daas products. before that can happen suppliers need to know what potential customers think about daas. first they must understand what it is, and what its potential, challenges and future may be. for this an exploratory study is requested. for intelligence studies it is of interest to know how mi, ci and bi experts see daas today and how they see it developing in the future. another study should look at if mi, ci and bi experts see these questions differently from other analysts and it experts. state and military intelligence organizations have become efficient at sharing intelligence, especially since september 11th, and the appearance of the new global threat of islamic fundamentalist terrorism. these organizations are sharing and exchanging intelligence not only at national levels but also internationally. new and faster performing information technology in the form of networks (infrastructure), hard disks (storage) and devices (working stations) is making these interactions easier and more attractive. private organizations too are realizing the potential value in sharing intelligence even though the most common form of obtaining intelligence so far is to buy data from a third party, not sharing intelligence with competitors and third parties. in the future, we can imagine that private organizations will mark documents, reports and analyses that they want to sell to others and make them available on the web. companies who excel in intelligence work will be able to finance part of their own capabilities through the sales of their own intelligence reports, much like consultancy companies (such as kpmg) or journals (such as eiu) today. instead of conducting their own research—which is costly and demands special competencies— companies are more often looking to buy or rent that information. the most common product to sell is credit reports. the most common analysis is for target marketing, placing consumers into segments. companies who either sit on large amounts of data, like social media sites, or who send this data around, like ericsson and huawei, are eager to enter this new business segment. we hear companies talking about redefining their business models, like at ericsson, are now afraid that huawei will overrun them if they only focus on their core business. facebook, linkedin and twitter are all in the same business, making money by capitalizing on our personal data. what they sell—connections to friends, colleagues or anyone who cares to listen and follow us—is less important for these companies than the amount of traffic (user activities) they gather. their income is related to how well they package and present this data to advertisers. so far they have had significant success as users, like you and me, are telling them everything about ourselves in terms of what we search for, making segmentation easier and more accurate. as a consequence, they are becoming experts in getting us to “check-in” several times a day. on the surface it is all about friends, work or political debates, but as a business the data we leave can be packaged and sold. moreover, there is little information for the user about what is done with their data. in the market of market intelligence this kind of data is nothing new. for decades there 45 have been data brokers: companies who gather data in secret and sell it off, much without direct interaction with consumers. data brokers gather data from hundreds of millions of consumers, including data about characteristics, preferences, health and financial situation. they do not only gather data about home addresses and phone numbers, but also about what car they drive, how much and what they watch on tv and on the internet, and what sports they participate in. they sell products that identify financially vulnerable consumers divided into categories such as “rural and barely making it,” “ethnic second-city strugglers,” “retiring on empty: singles,” “tough start: young single parents,” and “credit crunched: city families” and score each person accordingly. data brokers have been systematically criticized for not disclosing their sources. examples of such companies today are acxiom, experian, and epsilon. from the point of view of a researcher producing science it is unthinkable not to disclose sources or to give a detailed description of the method for gathering data. the scientific article will simply not pass the review process. serious journalists also have some rules of thumb when it comes to the truth, like checking with two independent sources. the same issue of reliability and validity that we see among data brokers is also found in other industries, for example among consultancy companies and among survey companies. these organizations are not primarily focused on disclosing the truth, but instead on selling and profits. many survey companies, like novus in sweden, refuse to disclose their scientific method, viewing it as a trade secret. in a country like sweden, a hand full of survey companies set much of the political agenda, which again shapes political opinion as their findings and publications make the backbone of tv news and debates in the established newspapers. many survey companies pay respondents to fill in e-surveys as the response rate is otherwise too low. this development is increasing as internet users are less willing to take time to fill in questionnaires. thus we have a situation today were particular respondents who are attracted to e-surveys work for the money are overrepresented. as the method is not described and data are not shown, the reader never learns that respondents are not representative of the population, even though many companies have banned respondents from certain countries in western africa to avoid more blatant biases. the problem is that these surveys are likely to gain different answers from another group of respondents, which is referred to as a problem of reliability. there is no one to redo surveys and research. by the time the reports are out they are soon forgotten and replaced by new ones, but the damage to the democratic system is already done as politicians are quick to take on new results from the news and shape their policies accordingly. surveys are hardly ever called back and apologies due to surveys errors are never made by news organizations. this is the same problem we face with daas, as suppliers are selling and renting data without giving the customer the possibility to investigate the scientific method or the raw data and its calculations. this leads to higher chances of manipulation. 2. research questions among the research problems mentioned in the literature we find the question of what types of vendors are available for daas. ovum (2014) distinguishes among three types: large technology vendors like ibm, microsoft, oracle and sap with substantial experience in the management of data (1), full service advertising agencies, like dentsu/aagis media, havas, interpublic, publicisomnicon and wpp, who combine technological capabilities with business consulting (2) and data players like axciom, experian and neustar with a substantial track record in managing vast and varied data sets (3). companies see an interesting business model in combining business know-how with technological capabilities, as in the cooperation between qlik, hp and intel. this year the swedish bi company qlik was sold to thoma bravo for three billion usd. the question becomes: how do you best bundle data and software? to that end, what we do not find in the literature today is what users and customers exist for daas, what they are looking for and what they see as strengths and weaknesses with the products available today. intelligence professional of all kinds would be potential customers for daas, just as they represent a major group of customers for business intelligence products and are working with many of the same issues around quality of data and analysis. it would therefore be of 46 interest for researchers to contact mi, bi, and ci professionals to get their ideas. another research question of interest is: what kind of data sets and software do these customers want? daas addresses a number of long-standing concerns in the ci field. for example, daas could be said to be a response to those who think companies spend too much time and money building and maintaining their own systems and data. companies need to focus more time on creating value with the data instead, it is often said in boardrooms. as we have seen there is one major assumption in this equation: that the data daas provides and the analyses they perform are good. the daas providers are basically asking us to trust them, which from a critical point of view is impossible if they do not show their method, raw data or analyses. however many companies are ready to place that trust and many will receive intelligence that is good. given that the price is not too high daas will be attractive to certain groups of consumers or users. to identify and locate this group then becomes an important question. “garbage in garbage out” (gigo) is becoming a big problem for big data. big data can be divided into transaction data (erp, crm), interaction data (logs, social feeds, click streams) and observation data (internet of things such as sensors, rfid chips, atm machines). when we look at the large quantity of big data produced today, most comes from social media, e-commerce, internet of things and sensors. this includes youtube (1000 tb of new data per day), fb (600 tb), ebay (100 tb), and twitter (100 tb) (abourezq, manar and idrissi, abdellah (2016, p. 159). yet with all their computer power, amazon is still not able to tell me what book i will buy next. what daas vendors offer first is this data, gigo, not intelligence. what the customer wants, on the other hand, is the opposite: intelligence, or strategic and actionable information. this is a major challenge for suppliers in this industry. it’s not an impossible equation, but it’s clear that intelligence has little to do with the sheer quantity of data. if data brokers have been able to do it so can daas companies. the question is how. in many cases, another challenge is to get customers to accept to receive not the actual data itself the raw data but a graph or some output where that raw data is simply used. another challenge is to get buyers to accept the idea of renting – not owning – the data. so research should try to find out what types of buyers may accept these different terms and what they are willing to pay for it. for many customers daas will make sense. most businesses don’t have all that many trade secrets. they succeeded because they were first, built loyalty and delivered customer value, or simply because they never gave up. now they are looking for better demographic data. they can try to get it themselves, but it takes too much time and they are unsure about statistics. many of these companies will rent the data if it’s much cheaper. it will be good enough for a presentation at work. the next question then is how low the price must be given the drawbacks of daas listed above. from the supplier’s side the question becomes how they can produce products that are more cost efficient. there are obvious advantages in this business with economies of scale, but how does this business model look? suppliers will probably be tempted to explore lock-ins and develop sophisticated schemes for up-selling, a bit like apple does; if you have the hardware you can only access their data through their store. daas companies can offer you the hardware, the software and the data, and the total it provider. a possible advantage with this is that customers can move from one dataset to another more easily, as long as they move within the system. for some this will be fine. from the perspective of intelligence studies maybe intelligence as a service (iaas) is a more interesting domain to explore than data as a service (daas); an open web based service where intelligence is bought or exchanged. from a ci perspective a market with a few big vendors seem far less ideal. ideally we would like a marketplace for intelligence where everyone is a buyer and a seller, not least because every company has some intelligence to sell and there should be no middle men to take a profit or delay the process, but the development is not there yet. another problem with the term daas is that it can stand for two separate phenomenons, and also includes desktop as a service (daas) and to make things worse the latter meaning is, for the moment, more popular than the first. 47 table 1 research questions # questions dimension perspective 1 do you know what data as a service (daas) is? control question method 2 can you explain in your own words what daas is? control question method 3 what kind of data could you imagine buying/renting through daas? what to buy: customers’ needs based on offers business 4 what kind of data do you think it's difficult to buy/rent through daas? what not to buy: customers potential needs that cannot be fulfilled business 5 what are the biggest challenges you see with daas from an intelligence perspective? what weaknesses and challenges today: ci customers potential needs that cannot be fulfilled business 6 how would you like to see daas develop from an intelligence perspective? the ideal state, how customers would like it to be in the future: customers’ needs business another problem is what to do with stolen data, which is a market in itself. data breaches are sometimes referred to as hacking as a service (haas) (mcaffee). it can be individual hackers operating as lone cowboys or hackers engaged by companies or states. most popular are financial data; credit cards and information regarding users. this market is so large today that it has already been segmented and products priced. according to the mcaffee report a credit card and information about its user in the us will cost you 15 usd. the same in the eu costs 35 usd. the second most popular data are login access, followed by identities. there are thousands of hackers trying to get this intelligence from us right now through various techniques, everything from data fishing to old fashion theft. market intelligence and ci professionals have a constant demand for this kind of data. as a result, companies specialize in these murky waters, like kroll and its offspring, k2 intelligence. these companies work on both sides of the table, helping to advise how to protect data from attackers and gathering data by dubious means. thus the learning curve is just steeper. they do not solve the ethical dilemma, but hide it under a veil of secrecy. this is also the realm of private information warfare. daas is, by its very definition, a part of this world and we have to make ethical choices accordingly. we cannot tackle all of these research questions here, but must start somewhere from the bottom. based on the problems and research questions mentioned above we can define six questions for this study (table 1). q1 and q2 are control questions, to see if respondents know what daas is before their answers are used. q2 is a control that checks that the answer in q1 is true. q3 is a market question, finding out what types of data customers may want to acquire. q4 is the opposite question, what kind of data customers think it is difficult for daas providers to keep and sell. q5 asks about what customers see as weaknesses and challenges with daas today, and q6 is an open question about what customers think about daas in the future. these more exploratory questions should then open up to more advanced and specific studies in the future. 3. the method the population is defined as possible users of daas. the sample size is defined as a particularly strong group of possible users for daas, namely ci, bi and mi experts and professionals. five larger groups of users on linkedin were selected related to business intelligence, competitive intelligence, market intelligence and intelligence studies. these were from: 1. business intelligence professionals (bi, big data, analytics, iot), 2. veille stratégique, e 48 réputation et intelligence economique, 3. strategic and competitive intelligence professionals (scip), 4. competitive/market intelligence professionals and 5. journal of intelligence studies in business (jisib). for the four first groups the surveys ware posted as a “conversation” in the dataflow. for the last group the survey was sent as an in-mail to all users registered for the group. the five groups have 222,000 users, but many are the same so it can be estimated that there are no more than 150-200,000 unique users. the five groups in more detail, including their self-descriptions: 1. business intelligence professionals (bi, big data, analytics, iot) with 183,000 members (business intelligence professionals is the knowledge repository for bi, analytics, big data and mobile bi technologies), 2. veille stratégique, e-réputation et intelligence economique, 7,244 members (ce groupe rassemble tous les professionnels de la veille stratégique, veille concurrentielle, veille technologique, de l'e-réputation et du social media monitoring), 3. strategic and competitive intelligence professionals (scip), 25,139 members (strategic and competitive intelligence professionals (scip), formerly the society of competitive intelligence professionals, is a global nonprofit membership organization for everyone involved in the practice of competitive intelligence and its related areas. ) 4. competitive / market intelligence professionals, 6,167 members (this group is for people that were and/or are involved in ci/mi in their professional lives whether they're researching, analyzing or acting on intelligence.) 5. journal of intelligence studies in business (jisib), 721 members (jisib is a peer-reviewed, no-fee open access journal. the journal publishes articles on topics including market intelligence, marketing intelligence, strategic intelligence, business intelligence, competitive intelligence and scientific and technical intelligence, and their equivalent terms in other languages.) there are reasons to think that we would get the same result if we studied the same sample size again (reliability), even though these are questions to which the answers change with time as daas develops. the questions listed in table 1 correspond to the answers we are looking for (validity). as the research is primarily exploratory a qualitative method was chosen. at this stage we are more interested in understanding a phenomenon. the questionnaire was pretested and no weaknesses detected, so no changes were made to the final questionnaire. once launched, the initial response rates were very low, partly related to the fact that it was summer vacation but maybe more related to the fact that social media users have become more reluctant to answers surveys. the surveys were therefore sent out four times to each network during the next two months. at the end we obtained about 206 responses. out of these, 16 were removed because of incomplete or illogical answers. respondents, especially on e-surveys, tend to answer with or without knowing a topic. as we wanted experts and professionals, we started the survey with two control questions. we asked if the respondent knows what daas is (q1). if they did not no further answers were collected from that respondent. to be sure that the respondent answered correctly he or she was also asked to define what daas is (q2). if he or she did not answer correctly given a broad margin for interpretation, the rest of their answers were taken out of the analysis part. e-surveys are an easy way to gather data when it works, but it has become more problematic. respondents seem to be less interested in completing e-surveys as these become more frequent. chances are they do it quickly and without much reflection on actual questions. longer surveys are not completed. in many cases anonymous internet users are less sincere, are opinionated, promote their own interests, and do not answer questions directly. this may be related to the way the internet has developed. for our purpose it has meant that we have had to discard a large number of responses. in future research other methods should be explored, like interviews at conferences. 4. findings and analysis the analysis builds on 190 complete responses, summarized in table 2. 49 table 2 empirical findings questions answers brief analysis 1. do you know what data as a service (daas) is? 47.37% yes 21.05% no 31.58% don’t know there were few correct definitions, but about 50% give an explanation of what daas is that is more or less correct. it corresponds to the number of people who said they knew what it is. those who don’t know if they know, did not actually know. in other words respondents were honest on this point. we may assume their answers to the other questions were honest too. 2. can you explain in your own words what daas is? access to multiple data sets irrespective of the platform it is stored on, or the platform that you use for analysis, it is an access to a data warehouse through an interface, it is related to cloud computing, it might be about accessing huge amounts of data about a sector for example, paid access to data, it is a distribution model that disintermediates data from the platform/software allowing you to integrate it into your own web applications, data can be provided as on demand, a way to keep together, in a framework, the same data about a topic, pay to save our data in a safe place, provisioning of data via the cloud in a protected and affordable way to users that they can work with it on demand, data used as a service for decision making, its sharing of information, buying information from supplier, buzzword 3. what kind of data could you imagine buying through daas? market information, demographics, information about competitors, financial developments, market changes, specific products consumed each minute with a cross section of colors and geography, text, statistics, raw data of any kind, video, all data that is captured and stored digitally, documents, photos, records, videos, codes, programmes, economic, tourism, politics, company information and profiles, news and publication subscriptions, data from custom webscapes, geolocation & metadata enrichment, all kinds of quant data, social media data, any data that is collected by others; spend data, geographical data, company information, personal information, any kind of structured data, products prices, data related to the behavior of consumers, principally consumer data and multiple transaction data, analytics there were few limits or restrictions about what kind of data suppliers could imagine buying, if it was all available. 4. what kind of data do you think it's difficult to buy through daas? operational, qualitative information about b2b customer needs, or competitor intentions, more personal and private data, specific fine-tuned data, data not collected, like illicit drug use, anything that is not on the deep web, military, competitors’ plans, new planned products, secret info, humint, really valuable information that will give you an edge data that is more sensitive, personal and private will be difficult to buy, users think. company secrets and data for b2b will be especially scarce. 5. what are the biggest challenges you see with daas from an intelligence perspective? connectivity and performance of the various data sources, it has limited b2b applications since the quantity of information may be limited, secrecy of the companies, to create understanding/insight from data, data homogenization, overcoming privacy rights, updating patterns might be late of managed to be late by the acknowledged user, manipulation is also possible to generate false leads, knowing what to look for in your aggregated and combined data, counterintelligence = your activity is registered from which intel requirements can be inferred, data quality, the level of collecting, mapping, keeping and distributing, big data, bank of data, speed and accuracy, confidentiality, quality, reliability, security, accessibility, pricing, what happens when everyone has the same info? then competition will increase the major concerns from users’ perspectives are confidentiality, quality, reliability, security, and accessibility. besides, when everyone has much of same data competition will increase. 6. how would you like to see daas develop from an intelligence perspective? more information about b2b transactions and company metrics, cheaper, secure, flexible, first it is interesting to develop methods to create intelligence through the acquired data to help decision making. secondly the legislation should follow the development of daas to protect users and private data, more data mining oriented, more focus on field verification, object-based production / activitybased intelligence using resource description framework metadata models will better exploit daas, become more comprehensive, moving from renting to buying and owning data, develop connectivity based on formats between data to connect data silos and enrich the basis for analysis, more useful and timely info, more tailor made data, great flexibility from daas companies, nonstandard deliveries users want to see more on company metrics, less expensive, more secure and more flexible data. 50 in more detail, we find a number of concerns: how do you as user measure the value of the data you are thinking about buying or renting? by the time the company’s financial results are recorded it may be difficult to go back and see where the value added was created in the value chain. marketing departments may become lazy, preferring to rent the data instead of getting it themselves. field work will suffer. the risk is that marketers and other users forget about the craft of how to obtain good data and analyze it. thus chances are that those who present the figures become less critical and make wrong inferences. chances are users will defend daas not because it is better for the company, but because it makes their jobs easier. legal issues are a set of problems by themselves and already of great concern in some industries, like health care. in health care there already is some legislation in place as to how to handle private data, but it has proven difficult to enforce so far. as competitors subscribe to the same data they can expect to arrive at similar conclusions, even when these conclusions are wrong. thus we get a situation of higher competition but also a risk of systematic failure in analyses. the skills of how to produce good data and analysis are in jeopardy. with a few large daas providers, these skills will be placed in the hands of a few people. the chances of manipulation increase, as these statisticians and analyses are not checked by outsiders. big data itself is worrying as there is confusion about what it can do and what it cannot do. big data is good at sorting in existing data, such as when it comes up with the logarithm for a google search, but is poor at predicting the future, such as when amazon suggests what you may want to buy. the risk is that daas providers will not tell customers about the difference, promising too much of the data they are selling. the reason for this has to do with probability statistics, r.a. fischer and the math of small numbers (ellenberg, 2015). with plenty of data we can predict the course of an asteroid, but we can only predict the weather the next week or two and we have very little chance of predicting human behavior at all. as an example there is a very small chance that the nsa can find a terrorist by looking at our internet behavior. the chances are much greater that they will suspect innocent people. the same logic goes for commercial data. daas providers will make false predictions about who our customers are. 5. future studies in our discussion numerous research projects have been suggested, primarily related to the user perspective. it would be of interest to see if there are differences in different groups of users, where mi, ci and bi experts belong to one group. it may be that they see these questions differently from other analysts and it experts. what data do companies want to share? what data do companies not want to share? will there be a future amazon or fb of daas, one dominating company, one winner takes it all or a large group of suppliers? economies of scale and big data may suggest large players have an advantage. there are already some “super aggregators” among national signal intelligence agencies with the same reason, like the nsa. in the private side, oracle offers 7.5 trillion marketing data transactions delivered per month, 200 billion social data operations processed per hour. do customers accept only renting data, while not being able to download it? how short of a time do customers accept renting data for? in many cases renting data only means being allowed to read the data. this is different from traditional data delivery. how will customers react to this new packaging? how much are they willing to pay for it? these are some of the questions that future studies could address. 6. references abourezq, m. & idrissi, a. 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(2012, march). demods: a description model for data-as-a-service. in advanced information networking and applications (aina), 2012 ieee 26th international conference 605-612. business intelligence software 5 customers’ expectations and needs in the business intelligence software market adis sabanovic * and klaus solberg søilen * * * lund university, administration, box 117 se-221 00 lund, sweden * * halmstad university, department of business and engineering (set), box 823, 301 18 halmstad, sweden received 10 december 2009; received in revised form 19 february 2011; accepted 16 march 2012 abstract: this paper aims to find out what companies desire when choosing a business intelligence (bi) system. we look at what their needs are and what they expect and understand from this software system, which can make them work more efficient and gain better knowledge about the business they are in. a web questionnaire was used for 67 swedish companies from various industries. the results are summarized and analyzed in cross tables for comparison. a model called the pet-model of bi implementation was created as a result of the theoretical findings. the model is used to finalize the results and the conclusions of the paper. the paper provides an argument for and an analysis of what is expected from a valuable bi software solution. it provides relevant facts about companies’ bi usage habits, which again is a guideline for bi software product development. keywords: business intelligence, software, pet-model, customers’ expectations 1. introduction in the world of today the access to information is greater than ever. company leaders and other decision makers are trying to overcome this problem by investing in various sophisticated computerized solutions, also known as business available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 5-20 https://ojs.hh.se/ 6 intelligence (bi) systems. the popularity of the term “business intelligence” or “bi” has increased rapidly in the last decade. bi is today a multifaceted term that refers to processes, techniques or tools to support the making of faster and better decisions (pirttimäki & hannula, 2003). bi systems do not only help decision makers to make better and more efficient decision but also helps the entire organization to improve return on investment (roi), gain new customers and suppliers, as well as employees, and increase overall satisfaction. eckerson (2004) points out that if one bi system is implemented throughout the entire company, there is a single version of truth which helps the company to avoid misunderstandings and get everyone going in the same direction. however, expectations of what a bi software is supposed to perform, or accomplish, is differently understood by the users. bi software is used as an effective reporting and analyzing tool to better understand a company’s organizational surroundings and environment, which gives managers basic data for decision making. by a way of quantitative research, this paper explores enterprises’ expectations and needs of bi software. 2. literature review bi tools are a part of a broader market sometimes referred to as business analytics, as illustrated in figure 1. the market for bi tools includes both standalone packaged software and embedded bi tools provided by database management software vendors (vesset and mcdonough, 2007). the bi tools market is divided into two market segments, query reporting analysis and advanced analytics. these are also the two areas business analytics software performance management tools and applications financial performance and strategy mgmt. applications (budgeting, planning, consolidation, profitability, mgmt./abc, scorecards) crm analytical applications (sales, customer service, contact center, marketing, website analytics, price optimization) bi tools: supply chain and service operations analytic applications workforce analytic application analytic spatial information management tools data warehouse platform (data warehouse mgmt. and generation) query reporting, analysis (includes dashboards) advanced analytics (includes data mining and statistics) figure 1 – classifications of bi software (vesset and mcdonough, 2007) 7 of bi tool applications that this paper is concerned with. in figure 1, these areas are illustrated with two dash-boarded rectangles. query reporting analysis (qra) software includes ad hoc query and multidimensional analysis tools as well as dashboards, scorecards and production reporting tools. these tools are designed specifically to support ad hoc data access and to report building by either it or business users. these do not include other applications or tools that may be used for report building (vesset and mcdonough, 2007). yet they are justified as multidimensional analysis tools which include both online analytical processing (olap) servers and client-side analysis tools, that provide a data management environment which is used for modeling business problems and analyzing business data. packaged data marts are also included in this function. these data marts are preconfigured software used for combining data transformation, management, and access in one single package and are usually presenting the results in various business models (vesset and mcdonough, 2007). the main occupation of advanced analytics software is data mining and statistics. technologies that are used are neural networks, rule induction, and clustering, among others, in order to discover relationships in data and then make hidden, not apparent or complex predictions for reporting and to do multidimensional analysis (vesset and mcdonough, 2007). in this sector there are technical, econometrical and other mathematical operations, which provide libraries with statistical algorithms in order to process and analyze the data. common functions are frequencies, cross-tabulations and chi square, but there can also be other specialized and sophisticated functions focusing on the functional area such as industrial design, clinical trial testing, exploratory data analysis, and highvolume and real-time statistical analysis (vesset and mcdonough, 2007). an analytical application, like business intelligence, is difficult to define and many professional programmers and users of bi tools will have their own definition when explaining the tool, the technology or the architecture. in this paper, the authors use a definition that will hopefully satisfy most of the analytical application industry’s “pundits”: “an analytic application consists of a series of logically integrated, interactive reports, including dashboards and scorecards, that enable a wide range of users to access, analyze, and act on integrated information in the context of the business processes and tasks that they manage in a given domain, such as sales, service, or operations.” (eckerson 2005, p. 5). generally an analytical application consists of elements which purpose it is to build a business logic, which will take the user through a series of interactive reports. there, it will be possible to access, analyze, and take necessary action to optimize the activities in a specific business domain. analytical applications are, therefore, not about randomly created reports that a user can upload from an “inbox” or from a “my reports” folder, but about the interactive and dynamic play where the user is given the possibility to utilize something, which is valuable for his or her company’s endurance (eckerson, 2005). the first part of a bi analytical application is called logical integration and is about stepping the user through different series of interactive reports and views of dimensional data, which will lead to the important point of action or to the request for more information. different users have different knowledge or know-how when it comes to usage of analytical applications. the navigational logic is important when a user wants to navigate through different reports on the “reports page” to effectively analyze data and make decisions. interactive dashboards and scorecards are used to inform the user of what metrics or data to examine. another logic of a bi oper ation al appli catio ns realtime data integrati on compon ent realtime decision making compon ent operation al data eve nts low latency store reports, alerts & messages figure 2 real-time bi processing components 8 analytical tool is therefore offering of recommendations (eckerson, 2005). the user, novice or professional, should be given the best possible overview of the data, to make sure that important information is not missed or neglected. the key to interactive reports is giving the user the opportunity to interactively search through the reports for additional information by simply “drilling” from a top-level view to a lower level. reports should be unfixed and possible to change into tables, charts, or other transactional data. some technologies worth mentioning, which are used for delivering interactive reports, are olap cubes, parameterized reports, linked static reports, advanced visualization techniques, dashboard or scorecards, and numeric searches (eckerson, 2005). various data and information from different sources should be put in analytical applications and then stored in one single warehouse where all data is processed and analyzed once again. large companies, like continental airlines, have different analytical applications running against one single enterprise data warehouse where all data, for example tracking flight process, fraud detection, or revenues management, are put through one large analytical procedure. integrating the information will help managers avoid problems when seeking one consistent version of the enterprise information (eckerson, 2005). different business areas (domains) such as sales, service, or manufacturing, have different information requirements and analytical applications are defined by those requirements. a sales analytical application may monitor a production line performance or other sales representatives and regions or it can examine the sales and contact history. it is the interconnection of these domains that must be used and placed within a logical model since several business areas represent the same company (eckerson, 2005). 3. types of business intelligence systems in a model-driven bi system, the information or intelligence is often presented thorough a series of different models. the user can access and modify financial, optimization and/or simulation models of various kinds (hedgebeth, 2007). the basic function of the model-driven bi system is the provision of quantitative models. in data-driven systems the basic functional level occupies search tools that access simple file systems (hedgebeth, 2007). here the user has access to and can modify real-time internal and external data. in communication-driven systems, different networking technologies drive decision-based collaboration activities. examples of these are video conferencing, groupware and computer bulletin board systems (bbs) (hedgebeth, 2007). via computer storage and processing, a document-driven retrieval is made. here, via a search engine, the user may access documents, policies, images, sounds, and scanned documents (hedgebeth, 2007). in knowledge-driven systems, trained and professional users with knowledge are used to solve various problems. intelligence from a web-based system is presented via a web browser and tcp or ip (internet protocol suite) (hedgebeth, 2007). another bi system that is not mentioned under the previous heading is called real-time business intelligence system. this system is about organization’s ability to react in time and become more alert and more responsive to various changing business conditions (white, 2003). in order to make effective decisions, accurate bi is required. the problem with accurate intelligence is that it takes time to collect and deliver it to the right users and it also takes time for the users to act on this information. as shown in the delay between a business event occurring, and the action being taken, this is when the value of the information is to be determined. the technology used to deploy a real-time bi application must aim to reduce a user’s reaction time if the information value is to be as high as possible (white, 2003). a real-time bi system consists of two operational components (figure 3). one is for data-integration and the other one is for decisionmaking. the data integration component captures business events from operational systems and then integrates them into the low-latency store. 9 figure 3 – latency in business intelligence decision making (hackerthorn, 2003) the decision-making component, on the other hand, supports real-time performance management and other real-time analysis and reports (white, 2003). as illustrated in figure 3, a business event’s road to become an action consists of three latency periods, data latency, analysis latency, and decision latency (hackerthorn, 2003). the result of the three latencies is called action time or action distance and the central objective of a real-time bi system is to reduce the action time as much as possible to respond to a business happening. if the problem is in data latency or the analysis latency, the time gap can be reduced by improving the technology used. if the problem is decision latency, then the latency depends on the user. therefore, the information that is provided to the user must be improved to solve the decision latency problem. another solution could also be an automatization of some bi processes that will automatically take action on behalf of the user (white, 2003). hackerthorn (2003) describes how decision latency may be reduced by applying three requirements to the system; alerting, information and guidance. hackerthorn (2003) finds that the system should be configured in a way, which alerts the user if some unusual business situation occurs. the system should be able to show situationalspecific business information in order for the user to get an understanding of the business environment he or she is working in. the user should also be guided by the system that suggests the most suitable action for the specific situation. another aspect in realizing the benefits when working with real-time bi is recognizing that the return on investment (roi) depends on two factors. the first is the time it takes to reduce an action and the second is the organizations ability to modify its business practice. figure illustrates that there is a point (exploration threshold) beyond which reducing the action time any further has no value to the business. the smaller the action time required, the bigger the information technology (it) costs are (white, 2003). figure 4 combined with show us that a shorter action time gives higher value to the intelligence, but it also increases the costs for the investment in the required information technology. after a certain time (at the break-even threshold) the costs for the information technology will become so low that roi becomes positive. action taken information delivered data stored business event v a lu e time action time or action distance 10 figure 4 – real-time bi; action time vs. it costs (white, 2003) 4. the different user-groups of bi different users necessitate different intelligence and a bi tool’s main priority should be to provide the right user with the right intelligence system, as shown in figure 5. on the bottom axis, different user groups can be identified with specific intelligence presentation requirements (on the vertical axis). executives tend to have little or no time to read long reports and are therefore only interested in fast figures or in “executive summaries”. these can be presented in scorecards or dashboards shown as key performance indicators (kpi). analyst or senior managers on the other hand prefer to work with advanced online analytical processes and explore different ways of making analysis. longer reports are more in the interest of department managers. they are interested in reading and analyzing compiled text reports such as, sales business metrics performance production times customer churn sales totals lead analysis click through relations budgets invoices shipping documents pick list executives kpi’s scorecards and dashboards analysts, senior managers department managers employee partners production reports management reports olap exploration figure 5 – different bi user needs in the hierarchy (solberg søilen, 2008) $ action time incremental it costs business benefits break-even threshold exploration threshold 11 analysis and budgets. this will give a basis for making correct decisions. workers on lower levels in the organization work more with tactical documents such as invoices, shipping and logistics. 5. categories of bi tools and enterprise expectation most companies today use a set of different bi tools, instead of focusing only on one. the reason for this may be that different users prefer different types of bi tools. the tools may differ from reporting, ad hoc queries and olap. bi tool vendors strive to meet all these requirements allowing organizations to standardize by using one single tool and on one single vendor (dm review and sourcemedia, inc., 2005). below, a list of some major categories of bi tools is presented (dm review and sourcemedia, inc., 2005): 1. production reporting tools: used by professional developers to create standard reports for groups, departments or the enterprise. 2. end-user query and reporting tools: used by end users to create reports for themselves or others and require no programming. 3. olap tools: enable end users to "slice and dice" data dimensionally to explore data from different perspectives and time periods. 4. dashboard/scorecard tools: enable end users to view critical performance data using graphical icons and drill down to analyze detailed data and reports if desired. 5. data mining tools: enable statisticians or business analysts to create statistical models of business activity. 6. planning and modeling tools: enable analysts and end-users to create business plans and simulations against bi data. planning ‘tools supply dashboards and scorecards with targets and thresholds for metrics. a research conducted in 2005 by better management (division of a sas institute inc. which does researches about business management issues around the world) showed that only nine percent of bi software users were always provided with all the necessary information from the bi software in order for them to make effective business decisions and only 45 percent of the users did sometimes get all the information they needed (miller, bräutigam, and gerlach, 2006). these numbers indicate that many corporate leaders have high expectations of a bi software before purchasing it, but the decision makers will less often rely on the information extracted from the software. what was instead demanded, or needed, by the companies, according to the survey, were the following (miller, bräutigam, & gerlach, 2006): 1. improved quality of information available to the companies. 2. access to relevant information in easy to-use reporting interfaces for ad hoc reporting. 3. assistance with interpreting and drawing conclusions from the information. 4. access to relevant information in standard reports. 5. an overview of which data is available for analysis. 6. a formal assessment of the companies’ information needs. 7. training on how to use bi tools. based on the theory presented in this paper, the authors have created a research model or plan that can improve production requirements. with the pet model of bi implementation, the idea is to create a plan or model that will cover most of the areas of bi and investigate them strategically. for an enhanced overview and for the sake of simplicity the model is divided into three main blocks (figure 6). every block consists of several areas of investigation and each area is included in the questionnaire in form of various questions specific for each area. the first block of the research model provides a profile of the investigated companies. the block consists of five areas of investigation; company size, company type, industry, and for the sake of validity and reliability of the research, a job level of the respondent and his or her job function in 12 figure 6 – pet model of bi implementation what is expected from a bi software? what is understood by a bi software? is bi used? top management dpt. managers division heads analysts developers experts consumers responsibilities for how long how often info. perfectiveness info. effectiveness info. quality info. relevance analytical apps. modifications scope of usage requests reports financing of bi org. structure separate units? conclusion drawing data overview training finance & accounting sales marketing forecasting budgeting & planning customer service human resources shipping/logistics manufacturing procurement expansion other in organization geographically what needs do bi fulfill? b lo c k 1 b lo c k 2 b lo c k 3 13 the company. the second block consists of two large areas of investigation, understandings and expectations. the uses of strategically formulated questions are aiming at finding out what companies understand and expect from a bi software. after observing how companies relate to bi and whether or not they use it, a third research block is created. this block consists of one main area of investigation; needs. this is the part of the research which requires the most work. the needs-area is segregated into five sub-areas, (specific needs-areas) which try to find out what kind of specific needs the companies have when using bi. examples of the specific needs-areas questions are: where in the organization is bi use? what is bi used for? how is bi used and for how long? who is using the bi? the needs-area is also taking into consideration those who do not use bi, trying to detect the reason for that and also to detect what can be done to make those companies use bi. a bi research plan can be embedded into the pet model on bi implementation so that the two are completing each other. from the purchase and employment layer the companies’ understandings and expectations can be extracted, and from the bottom task layer the companies’ needs can be extracted. the following research questions are analyzed: 1. what understandings do companies in sweden have about business intelligence software? for this question it is necessary to follow the respondents’ reactions in the early stages of the contacting process. it is of importance to notice the responses received from various companies when approaching them with the questionnaire. later, an effort in analyzing the answers from the purchase and employment layer in the pet model is made. 2. what are the swedish companies’ expectations of a business intelligence software? here, the main effort will be put in the analysis of the mean values. in this case, the purchase and employment layer in the pet model will be examined. 3. what needs do swedish companies have for a business intelligence software? the main effort in this question is again to an analysis of the mean values. in this case, the task layer in the pet model is examined. 4. how can the test system (“subsoft”) be improved to meet these expectations and needs? according to the survey, subsoft’s characteristics will be compared to those that are extracted from the questionnaire. 6. methodology today, many companies use an info@ e-mail address, which is often used as a “first contact” point for secondary information about a company when we are not sure who we need to contact. there is a possibility that the email will be forwarded to the right person. the risk with an info@ address is that the response time is long and in many cases there is no response at all (saunders, lewis and thornhill, 2007). for this reason, and for the reliability and validity of the research, it was important to find the right person in the company, who had insight about the company. the method used to collect “good” email addresses was to visit each company’s web page and look for specific information via the “contact” page. from 850 companies’ homepage addresses, 408 “good” addresses were found. the e-mail-collection gave a result of about 25 companies in each industry. the rest of the contacts were either info@ addresses or phone numbers. due to time restrictions, both info@ addresses and the phone numbers were neglected in the research. 6.1 data collection data can be collected in several ways, through observations, interviews and questionnaires (saunders et al, 2007). a positivistic philosophy with a deductive approach is used in this paper. a survey was conducted. the research strategy was a web based questionnaire. this allowed for quantitative data to be compared 14 in the book business intelligence competency centers, a team approach to maximazing competitive advantage written by miller, bräutigam and gerlach, (2006) there is an example of a web based questionnaire. this was used as a starting point and as a template of the first draft of the questionnaire, later to be modified. after completing the e-mail collection, a web questionnaire was created and published online. then an e-mail with an explanatory text and the link to the questionnaire was sent to all 408 contacts. the duration of the survey was set to 19 days. a limit, or goal, was set to between 100 – 120 responses. this limit was thought to provide a good base for empirical analysis. 23 emails of 408 were directly sent back with the notice that the contact person was not available or was on holiday, business trip, et cetera. 67 responses were received, generating a 16.4 percent response rate. according to braun hamilton (2003) a total response rate of an online survey is approximately 13.35 percent, but he points out that the response rate may vary from survey to survey depending on a variety of aspects. according to saunders (2007) a cover letter e-mail and a good design of the questionnaire will help to increase the response rate. for the questionnaire design, a windows application called “e-mail questionnaire”, created by compressweb company, was used. 7. data analyze and research findings from the 67 respondents of the survey, 11 different industries were represented. the industry that returned most answers was the manufacturing industry with 18 respondents followed by the consulting or professional services with ten and information technology industry with nine respondents. since the vast majority of industries returned a low number of responses, it was not possible to carry out any tests as to generalization of the industry as a factor. all answers combined are important for other tests though. for example, the value of an answer on each question can be measured and put in a table for comparison between different industries. since the manufacturing industry had the most respondents, it was used to exemplify how one can interpret and compare data from the survey. figure 7 gives an overview of the manufacturing industry’s bi system implementation. here, the first three foundations from the pet model are shown: bi system, motive, and purpose. as shown in figure 7 there is a total number (n) of 18 respondents from the manufacturing industry. in the bi system foundation, 15 are using excel, 1 is using oracle enterprise bi server (oebis) and 2 are using qlikview. in this industry, 83 percent of the 18 companies use microsoft excel for bi. this might not be the only bi system these companies use, but they do use it for some bi purposes. according to four of the companies (22 percent) the motive, independent from the previous foundations, is that they use their bi system in order to improve their strategic planning. 17 percent answered that they experience revenue and customer growth as 15 figure 7 – survey respondents represented from different industrie well as more efficient business processes. some answered do not know on the motive question and they are, therefore, not represented in the figure. in the purpose foundation, more than one alternative could be selected. the majority of the respondents answered that finance and accounting is the biggest reason for them to work with bi systems. thereafter, they use bi for manufacturing (44 percent) and sales (39 percent). in table 2 the same type of data is presented, but with all the industries combined. the statements in the “foundations” are also tested against each other and an average value has been produced. to start with, 15 of 67 respondents in the survey said that they do not use any kind of bi tool or system in their business or organization. 69 percent of all respondents say that they use microsoft excel when they work with bi. they might use excel as a permanent standard system in their organization or they might just use it for some occasional bi work. excel is used frequently throughout all the industries which took part in the survey. 13 percent of the respondents also say that the system they are using is not listed as an alternative in the questionnaire. the second most popular system in the list is qlikview. it was mostly used in the service and manufacturing industry. the motives that the companies had for using a bi system were especially high with regard to one statement: greater visibility into the business. 28 percent of the respondents say that a bi system is helping them to better understand their business and its environment. 18 percent say that a bi system is a helpful tool for strategic planning. it is not clear what specific tool these respondents use, but 38 of 67 respondents described their job level as manager 16 and there is a possibility that these managers use bi tools for strategic planning as well as a supportive tool in decision making. 13 percent of the respondents said that a bi system helps processes to become more efficient. some respondents states that they react faster to certain events and that the coordination among groups is better thanks to the bi system. in the discovery of how the respondents use their bi systems, there seem to be four major areas of usage. 17 percent said that they use bi systems in finance and accounting, 16 percent answered that they use it in sales, 11 percent said that the bi tool is a forecasting tool, and ten percent use bi tools for marketing. nine percent of 67 respondents use bi tools for budgeting and planning while only six percent use a bi system for supervision of the business through dashboards and scorecards. some users use bi tools for shipping and logistics as well as in the production and customer service. eight of nine respondents who said that manufacturing was their purpose for using bi tools came from the manufacturing industry. a low number of respondents use any kind of bi tools when expanding their business. in table 3 the employment of a bi system is presented. more than 30 percent of the respondents answered that reduced increase in decision-making speed was the main benefit they experienced. the second largest benefit was increased business user satisfaction. 18 percent of the respondents selected this. ten percent of the respondents said that increased usage of bi tools is a benefit, closely followed by those (nine percent) who said that better understanding of the value of bi is a benefit. 22 percent like to place a bi system as an integrated intelligence tool used by everyone in the organization. 13 percent believed that only trained professionals should use bi systems. all respondents are from the manufacturing industry and the banking industry. in the food or beverage industry and in the trade industry there is a belief that a top down placement is applicable, while in the consulting professional services industry the down up model was preferred. more that 30 percent had used their bi system between one to five years and approximately 30 percent has used the system for more than five years. a large minority had worked with bi for less than a year. large minority 17 in table 4 the three last foundations from the pet model: important functions, functional areas and analysis are presented for all the industries combined. when it comes to the important functions of a bi system a majority said that microsoft office integration is important. four out of nine respondents from the it industry say that this is the case. they also believed, together with the consulting professional services industry, that the fixed or standard reports function is important. online analytical processing (olap) was also a function appreciable in the it industry as well as in trade and manufacturing industry. nine percent of the respondents would like their bi system to make predictive analysis. a bi system’s functional area should, according to the respondents, be analytics and customer relations management. 13 percent of the respondents answered that these were the functional areas that their bi system was used for. business related consulting and helpdesks were important in pharmaceutical industry, food, and it industries. the analyses that the respondents in various industries believed to be important were mainly trend or scenario analysis and swot analysis. while the swot analysis was outspread evenly over the industries, the trend or scenario analysis had the most responses in the it and manufacturing industry. all four respondents from the bank or finance industry answered that trend or scenario analysis together with forecasting was the most important analysis. in ten percent of the respondent’s bi systems, and almost in every industry, cost analysis was used. statistical analysis was more often used in the health care industry, the food or beverage industry and in the consulting professional services industry. 8. main findings in order to answer the first research question for this paper: what understandings do companies in sweden receive by a business intelligence software? it must be said that when the questionnaire was sent out, there were companies who requested extra information about the “term” business intelligence. only after the extra information was presented to them, did some choose to participate in the survey. later it was found that 15 of 67 respondents did not use any bi system at all. this is an indication that the business intelligence-term is not known in some organizations. this also confirms the conjecture that bi is still in its early development stage for companies in general. we see in particular that there is a positive correlation between company size and knowledge and usage of bi systems. some of the alternatives in the questionnaire received a high response rate (over 25 percent). this signals that more than a quarter of the respondents had the same opinion on a number of questions. those alternatives that received a response rate over 25 percent were; increased decision speed (31 percent) and greater visibility into the business (28 percent). this 18 indicates that there is a common understanding of what bi software is. a conclusion is that the companies see a bi software as an instrument that will improve their decision-making speed and gain knowledge about the business environment they operate in. the second research question is about the companies’ expectations of a bi software. expectations are related to understanding because when a person understands how something works, in this case a bi system, the expectation is instinctively based upon that specific understanding. since expectations are also about performance and mean values, the overall expectations of how a bi software shall perform, according to this survey, are spread and divided. by looking at the answers more closely, divided by the pet model’s purchase and employment layer and by each industry, a mean value of each answer can be extracted (as presented in tables 3 4). besides the expectations that a bi system should improve decision-speed and give an insight in the business environment, the main expectation is that a bi system should perform as a finance and accounting system. in addition to that, sales, forecasting, and marketing functions are the expected tasks which a bi system should perform, according to the survey. based on the understandings and the expectations firms have of bi system, specific needs can be structured. throughout all industries there was one particular function or need that seemed to be of importance, a microsoft office integration function. there was a need for having a bi tool that could write fixed or standard reports. other needs, as the analytical function of a bi system as well as the customer relations management function, were also desired. as far as analyses are concerned, swot analysis and trend or scenario analysis were the most desirable ones. to illustrate what has been said and concluded in this chapter as well as to point out the most important of bi system understandings, expectations, and needs, the pet-model of bi implementation was developed (figure 7). figure 7 – pet model after the analysis system excel qlikview motive greater visibility into the business usage time 1 year to 5 years more than 5 years placement integrated important functions ms office integr. fix stndrd reports purpose finance acc. sales forecasting marketing benefits incre. dms incre. bus incr use of bi analysis trend/scenario swot analysis cost analysis functional area analytics cms purchase task employment 19 8.1 implications for the test software according to the findings in the research and as far as the test software cover the technical functions and areas of a bi system, “subsoft” can be improved in a number of ways. currently it consists of many functions similar to those found in excel such as spreadsheets and the possibility to create diagrams, calculate costs et cetera. but compared to a software like qlikview the test software is mostly a text-analytical software. there are no dashboards or scorecards. the greatest motive for purchasing a bi system according to the survey was to gain a greater visibility into the business. the sole purpose with the test software is based upon this idea. therefore, this is a positive finding confirming that the test software can be applicable in most industries. the three biggest purposes when using a bi system is finance & accounting, sales, and forecasting. on this point, subsoft has yet to be improved. although it contains some of these functions, such as forecasting analysis, further improvements need to be done. as shown in the analysis of the research the majority of respondents thought that a bi system should be placed where it is possible for everybody in the organization to use it. this is also another positive finding for subsoft, which allows any kind of user with specific rights to access the system. on the other hand the software does not support any function allowing integration with microsoft office. however, it does write fixed or standard reports as many of the respondents requested. subsoft is an analytical tool. this is also the functional area that got the highest mean value among the respondents. 9. contribution and future research many actors on the bi market can profit from the results of the research in this paper. many applicable facts about companies’ bi usage habits are uncovered. vendors may use the results to build or improve their software. the paper is an introduction to bi for new users and those who are planning to use bi in their organization. the empirical data collected in the survey contain more than one company profile. industry was used in this analysis as one company profile. if other profile figures are analyzed they could reveal valuable information about the relation between swedish companies and bi. the number of respondents is of importance when conducting surveys where generalizations are made. for this paper, there were 67 respondents in total and as many as 18 from one specific industry. in any industry there might be hundreds even thousands of companies even in a small country like sweden and a higher sample size would have helped to make better generalizations. perhaps longer survey duration would have helped to collect more responses. one idea with the questionnaires’ results was to test the significance levels between certain answers. for that to be possible, the questions should have been asked differently in the questionnaire. every question could have been ranked on a likert scale from one to five so that the real importance level could be measured and some significance levels calculated. references braun hamilton, m. 2003. online survey response rates and times, tercent, inc. / supersurvey. dm review and sourcemedia, inc. 2005. mywire. retrieved juni 10, 2008, from mywire dm review: standardazings on categories of bi tools: http://www.mywire.com/pubs/dmreview/20 05/09/01/987459?extid=10037&oliid=229 eckerson, w. 2004. best practices in business performance management; business and technical strategies, 101 communication, chatsworth, ca hackerthorn, r. 2003. minimizing action distance. the data administration newsletter (tdan.com), bolder technology inc., 1-4. hedgebeth, d. 2007. data-driven decision making for the enterprise: an overview of business intelligence applications. the journal of information and knowledge management systems , 414-420. miller, g. j., bräutigam, d. and gerlach, s. v. 2006. business intelligence competency centers, a team approach to maximazing competitive advantage, john whiley & sons, inc. hoboken, new jersey. http://www.mywire.com/pubs/dmreview/2005/09/01/987459?extid=10037&oliid=229 http://www.mywire.com/pubs/dmreview/2005/09/01/987459?extid=10037&oliid=229 20 pirttimäki, v. and hannula, m. 2003. “process models of business intelligence”, frontiers of e-business research, 250-260. saunders, m., lewis, p., and thornhill, a. 2007. research methods for business students. harlow: prentice hall. solberg søilen, k. 2008. management implementation of business intelligence systems. hammamet 14 16 february: 1st international conference on information system and economic intelligence siie’2008. vesset, d., and mcdonough, b. 2007. worldwide business intelligence tools 2006 vendor share. idc software market forecaster database , 1 (#207422e). white, c. 2003. building the real-time enterprise. seattle: the dataware warehouse institute. the evolution of competitive intelligence in china xinzhou xie * and xuehui jin ** * school of journalism and communication, peking university, beijing, 100871, china * and ** beijing science and technology information institute, beijing, china ** key laboratory of competitive intelligence and innovation evaluation, beijing academy of science and technology, beijing, 100048, china xzxie@pku.edu.cn received 20 may 2011; received in revised form 23 august 2011; accepted 21 december 2011 abstract: following landmark events during different historic periods, this paper divides the evolution of competitive intelligence (ci) in china into three main stages: ci introduction, ci localization and ci self-conscious marketization. studies of ci developments are made based on five main aspects of the overall ci industry in china, including their historical skeleton of development, achievements and problems identified. finally a forecast for the future development of ci in china is presented. keywords: competitive intelligence, china, society of competitive intelligence in china 1. introduction since 1978 china has been carrying out economic reforms and opening policies. as a result of the reforms chinese enterprises gradually became the host of market competition and enlarged enterprises’ right to autonomous management and decision making in a system of market competition. meanwhile domestic markets in china gradually became part of the global market and enterprises faced a more intense competition. the changing of the role and the intensifying competition created new conditions for the coming and developing of ci in china. in the past institutes of science and technology information in china were mainly serving the government at a national and local level. in addition the institutes were serving science and technology organizations. from mid 1980s they began to think about their function as transferring along with general social environmental change and put forward the idea that institutes of science and technology information shall serve enterprises and develop new space for development. the introduction of ci catered to this wish. in a word, chinese enterprises’ ci consciousness and needs were awakened under a drive for new social conditions and related policies. available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 61-75 mailto:xzxie@pku.edu.cn https://ojs.hh.se/ 62 2. analysis on the stages of ci evolution in china ci is mainly composed of five aspects: ci academic research, ci enterprise application, ci market, ci education and training, ci laws and professional ethics. the former three are the dominating parts of ci and control the evolutionary speed of ci (figure 1). since significant events mainly take place in these three parts, we divided ci evolution into the following three stages: ci introduction, ci localization and ci marketization (figure 2). there are two old sayings in china: “racing each other is called competition, arguing face to face is called strife” and “know the enemy and know yourself, and you can fight a hundred battles with no danger of defeat”. the sayings proves to what extent competition and intelligence has existed as concepts in china since ancient times. modern ci aiming for the goal of serving enterprises and helping them create competitive advantages appeared from the 1980s and onwards. in 1980 xianpei yuan (changhuo bao et al., 2005) published the paper “the difference and correlation between intelligence and information”, published in no.1, of the science and technology information service. this was the first time intelligence appeared in chinese academic journals. in 1987 huaibao liu (qihao liao, 2005) published “discussion about competitive intelligence and its methods of information collection”, in no. 2 of knowledge of library and information science. in the article ci received its own chinese terminology, “ 竞 争 情 报 ”. from the early 1980s to mid 1990s institutes of science and technology information in different places in china, especially at the shanghai institute began to introduce overseas ci theories and practices into china and advocated ci research and services. the first team engaging in ci research and promotion was formed. their advocacy and activities were noticed by more and more chinese information service ci introduction ci localization ci marketization landmark events: in 1980 xianpei yuan introduced the concept of ci in china. in 1987 ci got its chinese terminology, “竞争 情报”。 landmark events: in 1994 scic (society of competitive intelligence) was founded. landmark events: in 2002 baidu, a famous it company at home and abroad, launched the first ci software, ecis. 1980-1993 1994-2001 2002-today academic activities enterprises application ci market ci education ci laws and professional ethics figure 1: five aspects of ci in china figure 2: stages of the evolution of ci in china 63 organizations and academics. thus, “introduction” is an appropriate definition of this first stage on ci in china. in 1994 the society of competitive intelligence in china (scic) was founded, as a professional organization in china. it marked that ci now took an organized and more regularized road and greatly pushed the development of ci in the country. ci got a relatively rapid development in the aspects of academic research and ci education and obtained some achievements in ci localization studies. however, ci practices and the ci market were not yet very active. at the end of the 20 th century a number of chinese information companies such as xuanxin co. ltd. and menglong co. ltd. tried to develop ci software, but their products were only used by themselves and their customers as an accessory to ci consultation. these attempts did not lead to any great response. then baidu, a famous it company in china and abroad, launched the ci software product ecis on the chinese market. this caused a strong reaction to ci and had a major effects. following baidu, many companies entered the ci market. at the same time autonomy, a british search giant, entered the chinese ci market. due to advertisements and promotions made by these companies, chinese enterprises became greatly inspired. on this stage the ci market in china was gradually formed and enterprises’ ci applications became more common than in the past. the ci academic circle was greatly encouraged by the flourish of the ci industry and saw various kinds of ci academic activities boom, including books, academic papers and ci conferences. 3. academic research 3.1 academic papers ci was first introduced in chinese academic circles in early and mid 1980s. academics kept their enthusiasm and gained achievements especially after scic was founded in 1994. before 1994 ci academic papers were rare and scattered. there were almost no ci papers in chinese authoritative databases. below we see statistics reflecting this new achievement, through two of the most authoritative databases, cnki and vip, using keywords retrieval and artificially eliminating irrelevant literature. from 1994 to 2009 academic papers on ci was 3019, keeping a steady annual rise, especially since the 2001 growth rate increased (figure 3). 3.2 scholars ci scholars were formed and developed as a result of the new active academic activities. they brought new thoughts into the chinese ci field through explorations, with academics figure 3: annual distribution of ci papers 64 such as changhuo bao (changhuo bao et al., 2006). he put forward the concept of human intelligence network, and xinzhou xie et al. systematically analyzed the operation modes and mechanism of cis (table1). table 1: ci scholars and main research directions two of the most prominent chinese ci researchers, professor bao and qin, recently retired. the chinese ci community was then facing a new era where the representatives, xinzhou xie and feng chen et al., became the more active scholars within this field in china. at the same time representatives for the new ci generation, yan li and xiaofei wu et al. established themselves. generally speaking, ci interest was still a bit weak and most scholars came from departments of library and information science or libraries at universities or institutes of information services in different provinces. the backgrounds of chinese ci academics were narrow. 3.3 core achievements of academic localization research six core topics were the focus of chinese ci academics (table2). core topic year quantity publications main authors competitive intelligence system (cis) and software early 1990s 2010 372 changhuo bao, xinzhou xie, fuyuan xu. competitive intelligence and knowledge management 2000-2010 130 tiehui qin, junping qiu. competitive technical intelligence 2006-2010 52 xinzhou xie, xiwen liu. human intelligence network 2003-2009 44 changhuo bao, xinzhou xie. national competitive intelligence 1989-2009 32 qihao liao, gang zhao. industry competitive intelligence 2006-2010 4 feng chen authors works (books) and papers research topics bao changhuo 13 works, 47 papers human intelligence network, competitive intelligence system xie xinzhou 15 works,19 papers human intelligence network, competitive intelligence system, competitive technical intelligence, competitive intelligence practices chen feng 1 work, 34 papers national competitive intelligence, industry competitive intelligence, strategy intelligence and competitive intelligence peng jingli 60 papers competitive intelligence practices, competitive technical intelligence wu xiaowei 31 papers human intelligence network, competitive intelligence system and software qin tiehui 25 papers competitive intelligence and knowledge management xu fuyuan 18 papers human intelligence network, competitive intelligence system, competitive intelligence practices li yan 17 papers competitive technical intelligence wang yuefen 13 papers competitive intelligence system and software 65 table 2: ci core topics and researchers 3.3.1 cis and ci software chinese researchers are now very interested in cis and information technologies relating to cis. they think cis is the foundation of ci, its organizational guarantee, and the symbol of a mature and modern ci field (changhuo bao et al., 2004). from figure 4 we see that research on cis has been carried out since the mid 1990s. in recent years chinese academics have paid close attention to ci. at the beginning chinese academics learned from foreign experts and introduced research on cis. then they tried their best to construct cis theory based on chinese enterprises’ actual situations. in 1992 the first cis program in china, “competition environment monitoring for shanghai automobile industry”, tried to copy the work flow for cis from american companies to chinese enterprises. in 1999 prof. bao et al. systematically studied cis’ basic structure, model, functions and operational mechanism and constructed the basic framework of cis integrating three cis sub-networks (information sub-network, organization sub-network and human subnetwork), three information sub-systems (information gathering system, information analysis system and information service system), one centre (enterprise competitive intelligence centre) and six functions (environment monitoring, market warning, technologies tracking, opponents analysis, decision-making and information security). these findings were published in research of model and operational mechanism of competitive intelligence system and supported by nnsfc (the national natural science foundation of china). the book “enterprise competitive intelligence system” compiled by prof. bao and prof. xie was published in 2002. the books pins down thoughts on ci and cis more systematically than before. this forms a theoretical foundation for cis research and development in china. in addition there appeared studies of ci software for information gathering, processing and analyzing. in early 1995 xiangyu tao (xiangyu tao et al., 1995) tried to construct a quick response system for competitive intelligence based on it. in 2003 keqiang yin (keqiang yin, 2003) developed a milestone ci software. it includes five main modules around a ci cycle, ci need identification, secondhand information collection, primary information collection, ci analysis and ci services. in 2006 wuhan university (chao sun et al., 2007) took responsibility for a program supported by nnsfc, “research on mechanism of enterprise competitive intelligence collection based on data mining”. it used advanced data mining techniques and developed an automatic classification system for enterprise competitive intelligence collection. at the beginning of the 21 st century ci software appeared on the chinese market. the number of papers increased, but their findings were seldom put into practice. 0 10 20 30 40 50 60 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 p a p e rs year figure 4: the curve of annual papers of cis and ci software 66 3.3.2 ci and knowledge management (km) in the information economy era ci and km are playing a more important role in business management. both have similarities in their research objects, methods and related technologies. that is the main reason why prof. guy d. kolb (li liu, 2007), secretary-general of scip, started to list research on the relationship between ci and km. prof. qiu and his students (junping qiu et al., 2005) discussed the correlation and difference between these two areas in 2000. prof. qin (tiehui qin et al., 2003) and prof. wang et al. (yufen wang, 2006) studied the problem how to realize the integration, including content and measures. from figure 4 we see the attention given to this problem. before 2008 the interest increased and in 2008 it reached its summit, then to experience a straight decline. we think the reason is that new research on the topic is lingering for the management level and that demand has become saturated. the problem is waiting for an in-depth theoretical and technological breakthrough. because both areas are important for chinese enterprises, ci academics in china will continue to pay attention to this problem on ci and km. 3.3.3 competitive technological intelligence (cti) before discussing this topic, we have to know something about the information service for science and technology in china. since 1956 institutes of science and technology information has been founded in several major chinese cities and an information service network has been formed in these cities. they have also engaged in public service of science and technology information. its study object is the same as we call cti, and in a certain sense the former is a predecessor of the later. their fundamental difference lies in their objects. the former is serving governments at all levels, the latter enterprises. the former is public service, the later commercial service. since the 1980s the practice of cti has appeared in some enterprises which focus on technology innovation, such as haier (wei fang et al., 2008) and bao gang (xiujuan liang et al., 2009), but it hasn’t caused much attention among chinese scholars. entering the early 21st century the chinese government stressed the importance of technology innovation for chinese economic and national development. from that time, especially in 2006, many ci scholars have paid attention to cti. although the history of cti research is short in china, the study on this topic is active and the level of research is relatively high. in 2000 prof. zhu and prof. a. proter (yan li et al., 2006) led the first cti program in china, called “study on monitor and analysis technology of high technology based on intelligent knowledge-mining” (a nnsfc program). following it came research such as technical innovation audit (jin chen et al., 2006), patent map (ping l., 2005) and cti methods framework (xianneng ke, 2008). their research caused a renewed interest for ci. the cti research boom increased in 2008 and 2010 with iticti (international conference on technological innovation and competitive technical intelligence) i and iticti ii organized by peking university and beijing academy of science and technology, attracting hundreds of people from universities, institutes of information service and companies from china and abroad. this produced hundreds of papers and gradually led to an p a p e rs year figure 5: curve of papers on the research of the relationship between ci and km 67 international reputation on ci. within less than five years, academic papers on cti published in magazines reached 52, and master thesis 3. compared to other ci topics, the scope and speed of cti research was striking. the above discussions suggest that cti will be an active research branch of ci scholarship in china. 3.3.4 human intelligence network in 1998 bao changhuo put forward the idea of human intelligence network for the first time in china, claiming that cis is composed of three subsystems: intelligence network, organization network and human network. these three networks are equally important for cis. in 2002 prof. bao et al. published two books about ci, “competitive intelligence solutions enterprise competitive intelligence system and skills” and “competitor analysis”. in 2005 chuangye yan, a ph.d at peking university, wrote his ph.d dissertation entitled “human network in competitive intelligence activities”. it was an in-depth theoretical exploration and a construction of a practical model of human network in competitive intelligence activities. it was the first ph.d dissertation to do research on human intelligence networks in china. from 2003 to 2009, papers about the topic reached 44. the overall trend of the research on human intelligence networks reached its peak in 2007. it then went down again. this indicates that academics still maintain an interest for the topic, but after completing basic research and exploration of human intelligence network, it is now in search of a breakthrough. otherwise the topic may stop to be published in scientific journals in china. 3.3.5 national competitive intelligence in early 1989 qihao liao and zuozhi zhang (qihao liao et al., 1989) wrote the paper, “anatomy of jetro’s overseas technological intelligence activities”. it claimed that jetro’s overseas intelligence activities were a state version of competitive intelligence. the concept of state run competitive intelligence or national competitive intelligence then appeared in the literature. in 2002 liao held a speech about this topic at the scic annual conference. from 2004 gang zhao (gang zhao, 2004) wrote several papers about this topic to advocate competitive intelligence at a national level. in 2008 xiang tao (xiang tao, 2008) compiled the book, “national competitive intelligence: what it is, why and how to do it”. it presents a careful explanation about the definition, importance and operational modes of national competitive intelligence. researchers then thought national competitive intelligence referred to the intelligence activities at the national level. from the definition above, there is an overlap between national competitive intelligence, generalized competitive intelligence, governmental competitive intelligence and industry competitive intelligence. a definition of the difference between these terms and others is suggested by klaus solberg søilen (klaus solberg søilen, 2005). but, because the above concepts are intercrossing and national competitive intelligence is difficult to grasp as a specialty most scholars in china have shown little interest in the topic. as a result we have seen papers about national competitive advantage decline to account for less than 0.01% of the total amount of ci papers (figure 6). research on national competitive intelligence is a useful attempt to enlarge the area of research and development of ci, but has so far not been successful. 3.3.6 industry competitive intelligence with rapid development of a global economic integration, industrial clusters have become an economic entity that governments actively cultivate. in 2008 the china institute of science and technology information set p a p e rs s year figure 6: curve for papers on national competitive intelligence 68 industry competitive intelligence as one of their research directions. for 3 years feng chen (yanning zheng et al., 2009) has been guiding colleagues and students in how to study its meaning, scope and characteristics. they divided ci into three levels from a macroto a micro-scale, corporate ci, industrial and national. their program was named “basic problems in theories and methods for industry an empirical study” (a nnsfc program). it included all their thoughts on the topic. after studying the background of industry ci, some of the literature turned towards the trend of thinking about enterprises not only as competing with each other but also as cooperating with each other. unfortunately chinese ci scholars in general are as of yet little concerned about this topic and research achievements in this area has been relatively weak. the number of academic papers on this problem is small and its research history short. 4. the practice of ci in chinese enterprises need for ci in enterprises is the basic drive of ci applications. the way of meeting ci needs generally includes two aspects: one selfsupplying, namely enterprises themselves carrying out ci; the other buying ci services from external ci companies or organizations, namely buyers establishing business relationship with suppliers to develop the ci market. there are two kinds of driving forces of ci practices in china: one comes from the external, including ci research organizations, government at all levels and ci companies; the other is self-reflecting on ci activities. 4.1 the combination of industry, officials and universities to accelerate ci applications 4.1.1 the background before the 1980s, due to the fact that china was living in a planned economy, chinese enterprises’ awareness of ci was weak, and ci practices were in a state of “hibernation”. in china universities and institutes of science and technology information encountered ci abroad for the first time. this caused great interest in ci in china. since the influence of these companies were limited, they strived for governmental support and began to penetrate the field of ci for themselves to encourage enterprises to focus more on competition. 4.1.2 major events 1. ci services specialized on public institutes of information services and universities: in 1992, as the first specialized ci service department directly working with enterprises in public institutes of information service in china was the “market research department” at shanghai institute of science and technology information. later the public institutes of information services and universities began to serve enterprises, with the “enterprises information service central” at the national library, “competitive intelligence and competitiveness research center” at peking university, and “key library of competitive intelligence and innovation evaluation” at beijing academy of science and technology. 2. ci projects funded by local governments: in 1995 there was a first ci demonstration project supported by local government in china. the beijing ci demonstration project was supported by the beijing municipal science & technology commission. it picked eight companies from eight industries to help them construct cis. this opened up for a new model to promote ci practices through a combination of industry, officials and universities. after that, respectively in 2000, 2004 and 2005, yunnan, shenzhen and hunan provinces successively started ci demonstration projects at the governmental level, involving hundreds of enterprises. these ci projects were organized to help local enterprises develop ci with the help of local institutes of science and technology information. in addition scic made efforts to introduce ci to chinese enterprises. the organization attracted many enterprises to become members and inform them about ci. in 2006 scic established a chinese competitive intelligence consulting and training center. the organization established cooperative relationship with many enterprises such as shanghai bao gang group corp., qingdao haier group, and beijing shougng group. 4.2 ci practices in enterprises 4.2.1 background in the 1980s and 1990s, with the coming of new chinese economic reforms and the opening up of the country’s economy especially the transfer from planned economy to market economy – the chinese government 69 asked enterprises to take part in more market competition in china and abroad. chinese enterprises had to depend more on themselves to survive and develop. this caused an increase in competition and meant they had to become more self-aware. this made chinese enterprises become more focused on information collection and analysis for market intelligence and competitor intelligence. many foreign companies such as ibm and sony entered the chinese market, bringing their own concepts of ci practices into china. at the same time academic organizations with their information institutions and the government encouraged chinese enterprises to meet this challenge. 4.2.2 ci practices in chinese enterprises in 1999 prof. xie and his students systematically surveyed the situation of ci practices among chinese enterprises. based on their surveys, they divided the level of chinese ci application into: 1. having no ci workflow and network; 2. being in the process of constructing and forming; 3. having a regularized ci organization and network; and 4. having a ci workflow institutionalized and having world-wide ci networks. the nationwide questionnaire survey done in 1999 shows the development level of ci in chinese enterprises (figure 7). from the figure we see that most companies, 53.47%, found themselves at level [2]. 27.78% of the companies found themselves at level [1], 18.75% at level [3] and none at level [4]. this data suggests that by 1999 most chinese enterprises were in the forming status. the level of ci was not high. with the rapid development of it and the enhancement of enterprises’ “informationalization”, acquiring information was now easier than in the past. on the other hand the information explosion made enterprises decision-making more difficult. after about ten years (2009), we visited and reinvestigated 93 companies with 87 valid questionnaires. the situations of industrial and regional distribution of ci implementation can be seen in figures 8-10. due to limited time, the regional distribution of the companies involved in the survey was insufficient. the samples are mainly limited to beijing and shanghai. beijing and shanghai have the most companies among chinese cities, and they are more developed economically than other chinese cities so far. 70 respondents were mostly mangers or ci staff in the companies. in order to grasp the basic situation of ci in their companies and to make sure that the respondents completely understood what ci is (what was measured), we explained the subject before they answered our questionnaire. we also made a survey about the degree of attention these companies pay to ci by asking the respondents: according to your own experience, do you think ci is indispensable before you make important decisions? (you can pick answer “strongly agree”, “agree”, “less agree”, “disagree” or “strongly disagree”). figure 8: ci implementation according to industrial sector involved in questionnaire survey 30% 29% 15% 6% 6% 4% 4% 4% 2% information transmission, computer service and software manufacturing commercial service petrochemical others service business transportation, warehousing and postal finance sports, culture and entertainment 59% 15% 8% 4% 2%2% 2% 2% 2% 2% 2% beijing shanghai jiangsu guangdong fujiang zhejiang hainai hubei liaoning xianggang jiangxi 56% 23% 21% large enterprises midle enterprises small enterprises figure 9: ci implementation according regional distribution figure 10: ci implementation according to company size 71 the results are seen in figure 11. in china many companies thought ci was equal to market investigation. for that reason ci was often undertaken by the market or sales department in their company (xie et al., 2001). from figure 8 we find that the awareness of ci has improved and the percent that thinks ci is indispensable for decision-making account for more than half of those surveyed (strongly agree is 5.74%, agree 56.22%). on the basis of previous divisions of ci involvement, we divided the development level of ci into: 1. no ci work at all; 2. having ci work, but no ci department; 3. formal ci department and network being planned; 4. having formal ci department and network; 5. ci institutionalized. according to the survey we found that more than half of the chinese companies dealt with ci. the sum of the levels of [1], [2] and [3] accounted for 65.52% (10.95%+17.24%+37.93%), but most companies are in the position of forming or about to form formal ci functions ([3] accounted for 17.93%). comparing this with the survey from 1999 we see that the level of ci practice in china has made significant progress. but overall the level of ci practice in china is still not very high and it has still not matured. 16.09% of chinese companies were completely unfamiliar with the ci function. strongly agree agree less agree disagree strongly disagree figure 11: chinese enterprises’ attitude towards ci figure 12: ci development level in chinese enterprises in 2009 16.09% 18.39% 37.93% 17.24% 10.35% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 40.00% [1] [2] [3] [4] [5] 72 5. the ci market in china the ci market is composed of three aspects: ci consulting, ci training and ci software. there is no absolute boundary between the above ci markets. many ci companies engage in two or three of these businesses. as an emerging market, the ci market is not in any way mature. according to our comprehensive study on the topic, we divided growth into three periods: sprouting period, growth period and bottleneck period (figure 13). 5.1 the sprouting period (1994-2001) in the late 1970s and early 1980s information consulting appeared in china and in the early 1990s reached a relatively large development level. by the end of 1991 information consulting organizations reached 236. some of them provide consulting services for enterprise strategy. in china ci services were originally undertaken by information institutes, universities, ci societies and the local government. with the ci need in enterprises increasing companies such as information consulting suppliers and information technology providers became aware of the business opportunity. in 1992 the shanghai institute of science and technology information organized a ci seminar for the first time. ci training in china then took the first step. in 1996 beijing normal university began to provide “ci further education” for enterprise staffs. several ci consulting companies such as wanfang co. ltd., beijing competitive intelligence center, beijing huamen co. ltd. and beijing huanxin co. ltd. appeared. in the same period ci websites such as china.com and humen.com appeared. in 1999 and 2001 beijing huanxin co. ltd. and menglong co. ltd. developed ci software, but didn’t strongly promote it. for that reason there was little social response. there were some ci providers in the chinese market, but their number could be counted on one hand. 5.2 the growth period (2002-2007) in 2001 china joined wto, and the chinese market was further opened to the outside world. this made the outside competitive environment that chinese companies faced more complex and ci demand increased. in addition scholars, information institutes, universities and local governments made efforts to introduce ci to enterprises. in 2003 ci professional qualification such as “information analyst” and “competitive intelligence analyst” appeared in china. this marked the arrival of the era of ci professionalization in china. in 2004 scic established the “china competitive intelligence consultation and training center” and began to give ci training as an independent training program. the number of people to take part in ci training reached about 3000 in china each year during that period. the number of companies and organizations to engage in ci services reached about 1000 (mingjin xu, 2008). during that time websites for ci training and communication were active. some ci websites such as sinoci.com.cn and zoomchina.com were particularly popular. a famous it company in china, baidu, entered into the ci software market in 2002. following baidu, more than 20 companies including uk autonomy entered the chinese ci market. in 2004 the sales of ci related software reached more than 30 million rmb, a more than 80% increase compared to 2003 (fan wu, 2005). the ci market was now in a flourishing period, but many companies especially ci software developers were more like copycats following baidu. the boom of the ci market was due to sprouting period (1994-2001) growth period (2002-2007) bottleneck period (2008 -) figure 13: the growth of the ci market 73 a leading effect, not to new product development. this indicated an instability in the development of the chinese ci market and opened for its decline, in the period to come. 5.3 bottleneck period (2008 ) after a short-lived prosperity, in 2006 many ci software companies such as baidu co. ltd. and tianxiahulian co. ltd. dropped out of ci software market. in the meantime people began to cast doubt on ci performance. chunfeng wang (chunfeng wang, 2006) published online the article “is competitive intelligence the emperor’s new clothes?”. these signals hinted to the instability of the ci market in china. in 2008 ci software developers moved to other industries, switched to other it business sectors or went silent. following the decline in the ci software market, in 2009 the ci training market also began to decline and some ci training organizations disappeared. former ci websites such as huanmen.com and zoomchina.com were closed. but there were also new ci websites appearing such as chinacir.com.cn and zitview.com. linking the above survey on chinese ci practice with the recent situation of the ci market in china, we have made an analysis about the reason for the coming bottleneck period. it’s still unlikely that the chinese ci market will be shrinking further when one considers today’s ci demand. instead the level of ci services in china today is now too limited to meet the demand. so it’s crucial for chinese ci companies to develop and update their products and services. 6. ci education with scic founded in 1994, ci education in china appeared. in 1995 china science and technology university formally enrolled graduate students for a master’s degree in ci. in 2000 china institute of science and technology information, national defense science and technology information center and peking university united to form a ph.d. in ci. at present there are 23 universities engaged in ci professional education, and there is an elaborated system of college professionals offering ci education on the undergraduate, master and doctor level. 7. establishing ci laws and regulations and a professional ethics since ci was born in china in the 1980s, professionals have advocating collecting intelligence through legal methods. due to the nature of competition, decisionmaking, value and secrecy, ci activities must be in compliance with the “rules of the game” in the market. in china there are some laws related to ci such as the law of the peoples republic of china against unfair competition, unfair competition prevention, the trade secret protection act and copyright law of the peoples republic of china. these laws are restraining ci practices, but do not limit or regulate the ci industry as such. many professionals think it is a pity that laws specialized for ci don’t exist in china. ci ethics in china is very slow area to develop and china does still not encourage any authoritative sets of ci ethics. we think the basic reason for this is that in china ci still do not play an important role for the economic development and strategy support. the scale of ci practices is limited and still underdeveloped. the support and attention given to this area from the government is not sufficient. government guidance is important for any task in a country such as china, with a strong collectivist tradition. 8. conclusions generally speaking, all aspects of ci have entered a critical phase in china. we think the future of ci development will be connected to the following aspects: 8.1 ci theory with further reforms in the market system in china, the competition that chinese enterprises will be facing will increase. the business environment will become more complex and intense. in recent years china achieved great advances in technological innovation. this has improved the position for chinese companies and the general economic and national development. with further development and professionalization of ci, ci management will become more important. at the same time this is also a weak link. we think the future direction of ci academic research in china will be focused on the following five aspects: a ci that goes in the direction of more complex competition such as dynamic and cooperative competition, cis, 74 cti, the research of integration with km and ci and ci management. 8.2 methods and technologies for ci analytical methods and technologies used for ci is mainly introduced in china from abroad, and has been lacking in innovation. it seems method and technology is the weak point of ci research. strengthening ci innovation in this aspect is key to developing ci as a science for academics around the world, maybe especially in china. 8.3 ci practices according to our surveys, in 1999 and 2009 about ci practices in china, ci applications in chinese enterprises is still performed at a medium level in the organization, gathering information and conducting market surveys. at the same time in figure 13 we saw that ci practices in china is gradually developing towards a higher level of sophistication. 8.4 ci markets the ci market in china is facing a period of decline. the situation is not clearly optimistic. we think the basic reason is that the value of ci has not been developed in depth. as a consequence people don’t know enough about ci and even doubt its value. the other basic reason is that the ci functions have in a way hidden other areas of interest such as information systems, knowledge management system, decision support system and business intelligence system. the ci role is often performed by employees without a clear ci tag, such as salesmen, r&d personnel, even managers. this has created much confusion as to what ci really is. from this perspective it would be better if a new and broader term could be found that reflected the values of all of these activities. 8.5 cultivation of ci talent it is difficult to see how someone can be an expert on ci without having in-depth knowledge of other areas. future development of ci talent mentioned above is therefore inseparable from the cultivation of interdisciplinary 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(2018) mapping the structure and evolution of jisib: a biblipmetric analysis of articles published in the journal of intelligence studies in business between 2011 and 2017. journal of intelligence studies in business. 8 (3) 9-21. article url: https://ojs.hh.se/index.php/jisib/article/view/325 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index mapping the structure and evolution of jisib: a bibliometric analysis of articles published in the journal of intelligence studies in business between 2011 and 2017 josé ricardo lópez-roblesa*, jose ramón otegi-olasoa, rubén arcosb, nadia karina gamboa-rosalesc, hamurabi gamboa-rosalesc auniversity of the basque country, department of graphic design and engineering projects, bilbao, spain; bking juan carlos university, department of communication sciences and sociology, madrid, spain; cautonomous university of zacatecas, academic unit of electric engineering, zacatecas, mexico *jrlopez005@ikasle.ehu.eus journal of intelligence studies in business please scroll down for article mapping the structure and evolution of jisib: a bibliometric analysis of articles published in the journal of intelligence studies in business between 2011 and 2017 josé ricardo lópez-roblesa*, jose ramón otegi-olasoa, rubén arcosb, nadia karina gamboarosalesc, and hamurabi gamboa-rosalesc a university of the basque country, department of graphic design and engineering projects, bilbao, spain; b king juan carlos university, department of communication sciences and sociology, madrid, spain; c autonomous university of zacatecas, academic unit of electric engineering, zacatecas, mexico corresponding author (*): jrlopez005@ikasle.ehu.eus received 18 october 2018 accepted 27 december 2018 abstract today, organizations are facing technological, economic and social challenges that require the intelligent use of data, information and knowledge. to this end, organizations are developing capabilities around intelligence. from the organizational point of view, intelligence in business is a relatively new field study, so it is convenient to know and understand what the main themes are and their evolution in order to facilitate their integration. taking this into account, the current research conducts a conceptual and structural analysis of the journal of intelligence studies in business (jisib). jisib is one of the few academic journals devoted purely to publishing articles about business intelligence, collective intelligence, competitive intelligence, economic intelligence, market intelligence, marketing intelligence, scientific and technical intelligence, strategic intelligence, and their equivalent terms in other languages. this analysis is carried out by quantifying the main bibliometric performance indicators, identifying the main authors and evaluating the development of the main themes within it using scimat as a bibliometric analysis software. to this purpose, the documents published in jisib from 2011 to 2017 were retrieved from two different sources: the jisib official web page and the web of science. in this way, the bibliometric performance analysis evaluates the impact of the scientific output based on publications and their citations, while science mapping illustrates the intellectual structure of the journal and the evolution of the main research themes. bearing in mind that jisib provides an open platform for the publication of original research articles, opinion articles, book reviews and conference proceedings about the intelligence field, this research allows to understand its structure and evolution and all the themes associated with it. it provides a framework to support intelligence researchers and professionals in the development and direction of future research by identifying emerging, transversal, core and declining themes. finally, this study includes a performance analysis of jisib. keywords business intelligence, competitive intelligence, conceptual evolution map, coword analysis, science mapping analysis 1. introduction in an age of information, organizations face the challenge of improving their competitiveness and agility through the intelligent use of data and information in the research, development and innovation process. this makes it possible journal of intelligence studies in business vol. 8, no. 3 (2018) pp. 9-21 open access: freely available at: https://ojs.hh.se/ 10 to predict situations, improve decision-making processes, increase profitability and thereby the success of organizations, mainly. both companies and educational organizations seek to respond to this challenge through the effective development of areas of knowledge such as: competitive intelligence, business intelligence, market intelligence, scientific and technical intelligence, collective intelligence and geoeconomics. nevertheless, in comparison with other fields of knowledge, intelligence in business is relatively novel, so there are not many ways in which academics and professionals can improve and share their advances and proposals. the concept of intelligence has its origins in the military and national security fields, through the processes of adaptation that organizations develop to respond to the information use challenges that they face today. it was not until 1958 when luhn defined business intelligence as the ability to apprehend the interrelationships of presented facts in such a way to guide action towards a desired goal (luhn, 1958). this definition can be considered to be one of the first in the intelligence field, because it mentions the systematic process by which the organization collects data and organizes them in the form of useful information to later analyze them and convert them into intelligence, providing the necessary criteria for the decision making process. however, the term business intelligence is more often used for internal or transactional aspects of an organization, giving space for the use of competitive intelligence in a broader, external framework. in this way, prescott and gibbons said that competitive intelligence is a formalized, yet continuously evolving, process by which the management team assesses the evolution of its industry and the capabilities and behavior of its current and potential competitors to assist in maintaining or developing a competitive advantage (prescott and gibbons, 1993; prescott and bharadwaj, 1995). bearing this in mind, it is possible to observe that the intelligence is implemented in different areas of the organization, which means that the approach given to it varies according to the people who develop it or the area where it is developed. this has given rise to different intelligence terminology, within which can be highlighted the following: business intelligence (gilad and gilad, 1985; søilen, 2017), collective intelligence (devouard, 2011; sheremetov and rocha-mier, 2004; shimbel, 1975), competitive intelligence (calof and dishman, 2007; davenport and cronin, 1994; du toit, 2003; du toit and sewdass, 2014; james, 2014; tuta et al., 2014), economic intelligence (larivet, 2009; menychtas et al., 2014; perrine, 2004; seiglie et al., 2008; smith, 1953), market intelligence (maltz and kohli, 1996; navarro-garcia et al., 2016), marketing intelligence (de' rossi, 2005; kelley, 1965; zhou and lai, 2009), science and technology intelligence (castellanos and torres, 2010; chang et al., 2007; de coster et al., 2013; mccormick et al., 2015; mortara et al., 2009), among others, such as financial intelligence, public intelligence, and competitor intelligence. nowadays, there are few scientific journals focused exclusively on the publication of intelligence articles which the practitioners of intelligence can use to share and further develop their knowledge. one of the most recognized and specialized sources in this field is the journal of intelligence studies in business (jisib), which is an open publication journal, indexed in the main scientific databases and that gathers contributions from many authors of international prestige. considering the heterogeneity, novelty and evolution of this field, intelligence professionals are interested in evaluating the evolution of the main themes and the relationship between them, in order to identify opportunities and challenges in the future. in this regard, authors such as du toit (du toit, 2015) and søilen (søilen, 2013; søilen, 2015; søilen, 2016) have carried out research to identify trends in the intelligence literature by analyzing publications, journals and authors. the objective of this article is to identify and analyze the main themes in the field of intelligence used in peer-reviewed articles published in jisib from 2011 to 2017 and its performance through the use of bibliometric techniques and tools (cobo et al., 2011b). finally, this paper is organized as follows: section 2 introduces the methodology (including the bibliometric analysis tool) and the data set. section 3 and section 4 present the bibliometric and science mapping analyses, respectively. section 5 shows the conclusions and future research lines. 2. methodology and dataset scientific journals represent one of the main knowledge sources today, so their analysis is of interest to academic, scientific and business communities (bjork et al., 2009; dewatripont et al., 2006). within the research aimed at 11 evaluating the performance of scientific journals, three main approaches can be identified: (i) bibliometric analysis based on performance indicators, (ii) thematic analysis, and (iii) research methods and techniques. in this contribution, a complete bibliometric analysis based on performance indicators and a thematic analysis of the journal of intelligence studies in business (jisib) has been carried out (batagelj and cerinšek, 2013; börner et al., 2003; gutiérrez-salcedo et al., 2017). the performance analysis is based on bibliometric indicators that measure the production of different actors, and the international impact achieved. the most cited articles (moral-munoz et al., 2016) in the field are identified using the h-classic approach (de la flor-martinez et al., 2016; martínez et al., 2014), which is based on the well-known hindex (hirsch, 2005). in general terms, the hclassic uses the h-index in order to establish the threshold cut, that is, the number of highly cited documents that correspond with the most cited paper. a longitudinal conceptual science mapping analysis and a strategic diagram based on a cowords network are developed by means of the software tool scimat (cobo et al., 2012). this thematic analysis is based on a four-stage approach: (i) research themes detection, (ii) visualizing research themes and thematic network, (iii) discovery of thematic areas and (iv) performance analysis. to do this the research themes are set out in a strategic diagram and thematic evolution map (figure 1). the first is a two-dimensions map divided in four areas according to their relevance (centrality and density rank values) where the themes are represented as a sphere and its volume is proportional to the number of documents associated with the theme (cobo et al., 2011a): a. motor themes (upper right quadrant – q1): the themes within this quadrant are relevant to the structure and develop the research field. b. highly developed and isolated themes (upper left quadrant – q2): the themes within this quadrant are relevant but are not important enough to be considered more than a very specialized or peripheral activity for the research field. c. emerging or declining themes (lower left quadrant – q3): the themes within this quadrant are weak, but this weakness can be understood as emerging or disappearing themes. d. basic and transversal themes (lower right quadrant – q4): the themes figure 1 strategic diagram (a) and thematic evolution (b) structure. the structure of the strategic diagram (a) and thematic evolution (b) used to describe the evolution of the themes related to intelligence and the field). the strategic diagram is dived into four sections: motor themes, highly developed and isolated themes, emerging and declining themes and basic and transversal themes, according to the centrality and density of the themes. the thematic evolution shows the evolution of these themes in the period defined. this figure groups these themes into thematic areas (color areas). 12 within this quadrant are not welldeveloped, but are relevant for the research field. finally, the second diagram is a longitudinal framework, which allows us to analyze and track the evolution of a research field throughout consecutive time periods. in addition, a performance analysis of a thematic area using the main bibliometric indicators was developed. this analysis focused on the documents published in the journal of intelligence studies in business (jisib). the publications and their citations included in this analysis were collected on may 1st, 2018. the publications belonging to the intelligence research field were retrieved from two different sources: jisib (official web page) and web of science. the publications were manually downloaded and included in the knowledge base. the publications available on the web of science were retrieved using the following advance query: is=("2001-015x”). these publications were compared with the publications obtained from the official website to guarantee that the publications are consistent in both sources. finally, the knowledge base was further refined and limited to articles, proceedings, opinion and reviews published in english. this process retrieved a total of 92 publications from 2011 to 2017. according to methodology used for this research (cobo et al., 2011a), to evaluate the evolution and to avoid smoothing the data, the best option was to choose comparable periods in terms of duration and characteristics. in the case of the journal jisib, the entire time period analyzed was divided in seven comparable periods: period 1: 2011, period 2: 2012, period 3: 2013, period 4: 2014, period 5: 2015, period 6: 2016 and period 7: 2017. the analysis provides a good input to the strategic diagrams and thematic evolution map (co-word analysis) to detect the main themes. 3. performance of the bibliometric analysis of jisib to understand how the jisib has progressed in terms of publications, citations and relevance, its performance was evaluated through the analysis of the main bibliometric indicators: publications, citations, most cited articles, most cited authors and h-index. for this purpose, the bibliometric performance analysis was structured in two parts. firstly, all the publications and their figure 2 distribution of publications and citations by year and period (2011-2017). this figure shows the distribution of publications and citations included in jisib per year. the bars represent the publications by year and are related to the left axis. the continuous lines represent the citations corresponding to each year (nominal and accumulated) and are related to the right axis. 13 citations were evaluated with the objective of testing and evaluating the scientific development. secondly, the main authors and publications were analyzed to assess the impact of these in the field of research. table 1 top 10 most productive authors (2011-2017). when a tie is recorded between authors all are listed in alphabetical order. pub = publications. n=92. authors pub % søilen, k. s. 16 17.39 rodríguez salvador, m. 6 6.52 calof, j. 4 4.35 du toit, a. s. a., erickson, g. s., quoniam, l. and rothberg, h. n. 3 13.04 baaziz, a., barnea, a., bisson, c., bleoju, g., capatina, a., dousset, b., el haddadi, a., hoppe, m., oubrich, m., paletta, f. c., richards, g., vriens, d. and xinzhou, x. 2 28.26 table 2 top 10 most cited authors (2011-2017). this table is completed with the information of each author in terms of production. when a tie is recorded between authors all are listed in alphabetical order. c = citations. % is given out of n=479. docs = documents. author c % docs % søilen, k. s. 83 17.33 16 17.39 adamala, s. 56 11.69 1 1.09 cidrin, l. 56 11.69 1 1.09 du toit, a. s. a. 45 9.39 3 3.26 carayannis, e. 29 6.05 1 1.09 kabir, n. 29 6.05 1 1.09 hoppe, m. 23 4.80 2 6.52 rodríguez salvador, m. 23 4.80 6 2.17 calof, j. 15 3.13 4 4.35 oubrich, m. 15 3.13 2 2.17 3.1 performance and impact indicators the distribution of publications and citations included in jisib per year is shown in figure 2. from the first publication in december 2011, the number of publications remains constant, with the exception of 2015, when there was a slight decrease. it is important to highlight that during the last years there has been a constant increase in the number of publications, which can be understood as a growing interest in the intelligence and consolidation of the journal. in addition, it is important to highlight that jisib is one of the few active intelligence journals indexed in the most important academic and scientific sources (web of science and scopus), an aspect that has allowed it to grow in terms of publications and adherents. considering these results and the previous analysis of the state of the art, it is possible to expect that the positive trend will continue. however, it is important to note that in recent years there was a false negative trend in the number of citations. according to wang there is a window period between the publication of an article and the moment when it begins to be cited, ranging from 3 to 7 years (wang, 2013). furthermore, it must be borne in mind that the evolution of the citations also depends on where journals are indexed and in how many sources they are indexed. 3.2 most productive and cited authors to complete the bibliometric performance analysis of the journal of intelligence studies in business (jisib) and to assess the main actors in the development of this field of knowledge, the most productive and cited authors are shown in table 1 and table 2, respectively. in both tables a tie was recorded between different authors, so all are listed in alphabetical order. it is important to highlight that all most productive authors are among the most cited authors during the evaluated period. furthermore, the authors' correspondence in terms of country of origin are: sweden, france, iran, south africa, usa, canada, mexico, brazil and spain. figure 3 jisib h-index publications (2011-2017). the distribution of the most cited publications and their citations according to the h-index and h-classics. the bars represent the publications by year and are related to the left axis. the points represent the citations corresponding to each year (nominal) and are related to the right axis. 14 table 3 h-classics of jisib (2011-2017). this table shows the citation classic papers identified by means of the h-classics concept. these publications are considered the main reference base within the journal. percentage of citations is indicated out of n=479. rank title #citations (%) 1 key success factors in business intelligence (adamala and cidrin, 2011) 56 (11.69) 2 big data, tacit knowledge and organizational competitiveness (kabir and carayannis, 2013) 29 (6.05) 3 comparative study of competitive intelligence practices between two retail banks in brazil and south africa (du toit, 2013) 18 (3.76) 4 competitive intelligence research: an investigation of trends in the literature (du toit, 2015) 14 (2.92) 5 intelligence as a discipline, not just a practice (hoppe, 2015) 14 (2.92) 6 competitive intelligence and knowledge creation outward insights from an empirical survey (oubrich, 2011) 14 (2.92) 7 competitive intelligence in the south african pharmaceutical industry (fatti, 2013) 13 (2.71) 8 competitive intelligence and information technology adoption of smes in turkey: diagnosing current performance and identifying barriers (wright et al., 2013) 13 (2.71) 9 a place for intelligence studies as a scientific discipline (søilen, 2015) 12 (2.51) 10 the relationship between strategic planning and company performance – a chinese perspective (jenster and søilen, 2013) 12 (2.51) 11 a risk and benefits behavioral model to assess intentions to adopt big data (esteves and curto, 2013) 12 (2.51) 12 information design for “weak signal” detection and processing in economic intelligence: a case study on health resources (sidhom and lambert, 2011) 12 (2.51) the main other journals related to intelligence in business are: marketing intelligence & planning, south african journal of information management, european journal of marketing, aslib proceedings and interdisciplinary journal of contemporary research in business. 3.3 citation classics to understand the productivity and impact of a group of publications a summary analysis of hindex and h-classics is presented (de la flormartinez et al., 2016). the jisib has an h-index value of 12. this means that relevant publications have more than twelve citations. the results of the publications retrieved for each period are shown in figure 3. according to figure 3, the relevant publications are concentrated in 2013, 2011 and 2015. this coincides with the fact that 2013 and 2011 are also the most frequently cited years. table 4 authors with the highest number of publications and their citations according to the h-classics (2011-2017). name citations % n=219 documents % n=12 du toit, a. s. a. 45 20.55 3 25.00 søilen, k. s. 24 10.96 2 16.67 adamala, s. 56 25.57 1 8.33 alistair duffy, c. b. 13 5.94 1 8.33 carayannis, e. 29 13.24 1 8.33 cidrin, l. 56 25.57 1 8.33 curto, j. 12 5.48 1 8.33 esteves, j. 12 5.48 1 8.33 fatti, a. 13 5.94 1 8.33 hoppe, m. 14 6.39 1 8.33 jenster, p. 12 5.48 1 8.33 kabir, n. 29 13.24 1 8.33 lambert, p. 12 5.48 1 8.33 oubrich, m. 14 6.39 1 8.33 sidhom, s. 12 5.48 1 8.33 wright, s. 13 5.94 1 8.33 15 table 3 shows the “citation classic” papers identified by means of the h-classics concept. the authors with the highest number of publications and their citations are shown in table 4.to compliment the results described above, the evolution of jisib is analyzed below, using scimat. 4. science mapping analysis of jisib following the methodology described above, an overview of the science mapping and the relations between core themes in jisib is provided. this section is organized in two sections: (i) analysis of the content of the publications and (ii) a thematic evolution map. 4.1 analysis of the content of the articles published in connection with the previous sections, the research themes were set out in a strategic diagram, in order to analyze the main themes published in jisib in the seven periods defined. first period (2011): four research themes can be identified (figure 4). three themes can be highlighted as key themes (motor theme and basic and transversal themes) of the knowledge field: competitive-intelligence, data-warehouse and competitive-technical-intelligence. the significant features of the motor themes identified in this period and their main research areas are below: • competitive-intelligence: competitive intelligence system, economic intelligence, text mining, weak signal, real-time business intelligence, semantic network and continuous evolution • competitive-technical-intelligence: blue ocean strategy and knowledge transfer second period (2012): continuing with the analysis, four themes are identified in figure 5. three themes can be highlighted as key themes of the knowledge field: businessintelligence, document-warehouse and competitive-intelligence. the first two themes identified as key themes are new in the analysis and the last one changed quadrant. the significant features of the motor themes identified in this period and their main research areas are below: • business-intelligence: customer expectative, visualization, strategic early warning system, pet model, pricing strategies, security issues and figure 5 strategic diagram for 2011. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). figure 4 strategic diagram for 2012. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). 16 software (design, production and evaluation) • document-warehouse: multiversion documents and multidimensional analysis third period (2013): according to the strategic diagram showed in figure 6, six themes research themes were identified and four of these are considered key themes knowledgemanagement, big-data, business-intelligence and competitive-intelligence. in this period two new key themes appear and maintain business-intelligence and competitiveintelligence. the significant features of the motor themes identified in this period and their main research areas are below: • knowledge-management: knowledge activism, knowledge creation, knowledge strategy, organizational change, strategy, tacit knowledge, analytical conversation and big data strategy • business-intelligence: data management, business analytics software and cloud computing • big-data: organizational knowledge, risk management and data benefits fourth period (2014): according to the strategic diagram shown in figure 7, five research themes can be identified for this period and the following themes could be considered key themes: competitive-technical-intelligence, business-intelligence and competitiveintelligence. in this period, one new main research theme was identified but the motor themes just include one theme. the significant features of the motor themes identified in this period and their main research areas are below: • competitive-technical-intelligence: evaluating intelligence, intelligence impact, patent analysis, technical intelligence, citation analysis and cti impact fifth period (2015): seven themes were identified in this period (figure 8). four themes can be highlighted as key themes: social-network, business-intelligence, erpsystem and competitive-intelligence. in this period two new key themes appear and others are maintained: business-intelligence and competitive-intelligence. the significant features of the motor themes identified in this period and their main research areas are below: figure 6 strategic diagram for 2013. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). figure 7 strategic diagram for 2014. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). 17 • social-network: enterprise 2.0, information systems, networking organization, social computing, social learning, social medial, social organization, strategic management, competitive advantage and computer supported collaboration • business-intelligence: enterprise resource planning, e-word of mouth, internet discussion, unstructured data and custom relation management sixth period (2016): according to the strategic diagram shown in figure 9, ten themes can be identified and six of them are considered key themes: strategic-intelligence, researchagenda, data-governance, business-strategy, business-intelligence and enterprise-systems. in this period five new key themes appear and one is maintained: business-intelligence. the significant features of the motor themes identified in this period and their main research areas are below: • strategic-intelligence: disruptive intelligence, open innovation, perspective, technology management and technology brokers • research-agenda: hhrr management, intelligence studies, market intelligence, predictive analytics, talent management, competitive advantage and employee engagement • data-governance: intelligence as a service, data management and ethics • strategy: organizational performance, organizational level competencies and organization systems research seventh period (2017): according to the strategic diagram showed in figure 10, ten themes are identified and six of them are considered key themes for the knowledge field: open-innovation, business-intelligenceprojects, technology-intelligence, strategicintelligence, decision-making and socialmedia. in this period five new key themes appear and one is maintained: strategicintelligence. the significant features of the motor themes identified in this period and their main research areas are below: • open-innovation: organizational performance, knowledge, big data, big data analytics, emerging technology and competitive intelligence • technology-intelligence: technology monitoring, patent bibliometrics, patent indicators, patent information, patent statics and strategy • bi-projects: key success factors, bi success and data saturation figure 8 strategic diagram for 2015. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). figure 9 strategic diagram for 2016. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). 18 • strategic intelligence: knowledge discovery, balanced scorecard, corporate performance management and corporate strategic management it is important to highlight that businessintelligence, competitive-intelligence and strategic-intelligence are considered key themes in most of the periods, and the rest of themes are closely linked to patents, technology, innovation, information management and social networks. 4.2 conceptual evolution map in light of these pictures, figure 11 shows the pattern of development within the knowledge area throughout the periods analyzed and the relationships among research themes. the characteristics of the line define the quality of the relation. in the jisib thematic evolution map three kinds of main thematic areas can be identified: strategic intelligence, competitive intelligence and business intelligence. these thematic areas consolidate the main themes and research areas covered in jisib. in relation to the evolution of the jisib, competitive intelligence (green area) is the most strongly representative research thematic area in the period evaluated. this thematic area has 52 documents and 319 citations. the intellectual structure is composed mainly by motor themes and basic and transversal themes in all periods evaluated (q1: 6 themes; q2: 4 themes; q3: 3 themes; q4: 6 themes). business intelligence (red area) is the second thematic area within the thematic evolution map. this thematic area has 24 documents and 127 citations. the intellectual structure is composed mainly of motor themes in all periods evaluated (q1: 6 themes; q2: 1 themes; q3: 2 themes; q4: 4 themes). strategic management (blue area) is the last representative thematic area within the thematic evolution map in terms of production. this thematic area has 16 documents and 39 citations. the intellectual structure is composed mainly of motor themes and highly developed and isolated themes (q1: 6 themes; q2: 6 themes; q3: 1 themes; q4: 1 themes). finally, business intelligence, competitive intelligence and strategic intelligence could be considered the most representative intelligence terms developed in jisib. it is important to highlight that other intelligence terms are also identified in the thematic areas and these support the growth of this research field and complement each other's development. 5. conclusions this research presents the first bibliometric analysis of the journal of intelligence studies in business (jisib). it covers 92 original research articles and it identifies the main themes and related research areas developed from 2011 to 2017. in bibliometric performance terms, the amount of literature covered by jisib shows a noticeable increase in the last years. this increase coincides with the growth of the research field in other knowledge areas, such as computer and information, business management, marketing and education. considering phenomena external to jisib but related to the concept of intelligence such as big data, smart industry and regional intelligence, it is expected that their use will be synergistic for the growth of this field of knowledge. another significant aspect of bibliometric analysis is the fact that the main authors in terms of production and citations are also referent in other knowledge fields. it reconfirms the growing interest around intelligence and its multiple approaches. based on the results of the bibliometric analysis, the main themes used in the jisib literature are the following: business intelligence, big data, competitive intelligence, information management, social network figure 10 strategic diagram for 2017. this figure sets out the research themes in four categories according to their relevance. these themes are related to intelligence within jisib for a specific period of time. the four categories are: themes included in quadrant q1 (motor themes), themes included in quadrant q2 (highly developed and isolated themes), themes included in quadrant q3 (emerging or declining themes) and themes included in quadrant q4 (basic and transversal themes). 19 analysis, innovation, technology intelligence, strategic intelligence and intelligence maturity models. furthermore, the jisib evolution map reveals that it has two different main approaches. the first is about competitive intelligence (competitive intelligence system, knowledge management, competitive advantage, innovation, knowledge strategy, organizational change, decision making and strategic planning) and the second is close to business intelligence (reporting and visualization technologies, software evolution, security issues, data warehouse, data management, analytics, cloud computing, olap, processing, architectures, algorithms and web 2.0). finally, it is important to highlight that this analysis allows for the identification of common themes that can be used to reach the research lines related to jisib's aim and objectives. in this way, the following themes could attract the interest of the academic, scientific and business communities: social media and networks, internet, artificial intelligence, machine learning, open innovation and collaborative intelligence. in addition, these research lines should be focused on all kind of organization, particularly small and medium-sized enterprises, which by volume and capabilities can serve as a driving force for the consolidation of this area of knowledge. finally, it is important to highlight that the main research themes are aligned with jisib’s objectives and its community but these could not be confirmed as trends in the intelligence field study. a further research opportunity could be to compare the main research themes in the intelligence journals and intelligence literature. moreover, it could include a detailed analysis of the authors and research groups and their research themes. 6. acknowledgments the authors j. r. lópez-robles, n. k. gamboarosales and h. gamboa-rosales acknowledge the support by the conacyt-consejo nacional de ciencia y tecnología (mexico) and dgri-dirección general de relaciones exteriores (méxico) to carry out this study. 7. references batagelj, v., and cerinšek, m. 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(2009). marketing intelligence on customer experiential values: an structural equation model approach. los alamitos: ieee computer soc. vol6no3paper3 capatina et al to cite this article: capatina a., bleoju, g., yamazaki, k. and nistor, r. (2016) cross-cultural strategic intelligence solutions for leveraging open innovation opportunities. journal of intelligence studies in business. 6 (3) 27-38. article url: https://ojs.hh.se/index.php/jisib/article/view/177 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index cross-cultural strategic intelligence solutions for leveraging open innovation opportunities alexandru capatinaa*, gianita bleojua, kiyohiro yamazakib and rozalia nistora adunarea de jos university of galati, romania; bchukyo university, nagoya, japan; *acapatana@ugal.ro journal of intelligence studies in business please scroll down for article cross-cultural strategic intelligence solutions for leveraging open innovation opportunities alexandru capatinaa*, gianita bleojua, kiyohiro yamazakib and rozalia nistora adunarea de jos university of galati, romania; bchukyo university, nagoya, japan *corresponding author: acapatana@ugal.ro received 26 october 2016; accepted 25 november 2016 abstract although the concept of open innovation has become widely discussed by scholars and practitioners, few cross-cultural studies focus on the assessment of companies’ behaviours towards “not invented here” and “not sold here” syndromes. the purpose of this paper is to investigate the profiles of japanese and romanian companies operating in two fields, it and manufacturing, from the open innovation perspective. the goal of this study is therefore to provide comprehensive empirical evidence for the adoption of inbound and outbound open innovation activities in the companies from these two target countries. data from a sample of japanese companies and romanian companies were used to test two hypotheses on open innovation behaviour, in the context of a cross-cultural comparative approach. the results show that technology isolationists are more frequently found among the romanian companies (especially in the manufacturing field), than the japanese companies, which can be explained by the fact that japanese firms are mainly based on leading innovative technologies, while romanian firms are early adopters of the advanced technologies, due to the economic circumstances. japanese companies included in the sample are defined as technology fountains, followed by technology brokers, proving their appetite for outbound open innovation. in this context, strategic intelligence solutions, once performed in collaborative culture environments, will lead to the improvement of the partners’ managerial competences and will act as enablers for competitive positioning, proving the added-value of the acquired know-how through open innovation practices. keywords disruptive intelligence, japan, open innovation, romania, strategic intelligence, technology brokers, technology fountains, technology isolationists, technology sponges 1. introduction cross-cultural strategic intelligence configuration, designed to enhance open innovation benefits, challenges managerial skills to reframe and upgrade rooted companies’ high tech patterns of cooperation, through refining drivers of associating cultural diversity and open innovation. furthermore, the cross cultural-open innovation hybrid approach requires efforts toward building new managerial capability to anchor specific coordination mechanisms, enabling the best matching of strategic intelligence configuration and high-tech partnership outcomes. this cross-cultural research is mainly focused on the assessment of the correlations between japanese and romanian companies’ profiles from an open innovation perspective and the field in which these companies are operating. the four clusters of firms, in the context of their involvement in innovationbased activities are represented by the technology isolationists (characterized by high levels of both “not invented here” and “not sold journal of intelligence studies in business vol. 6, no. 3 (2016) pp. 27-38 open access: freely available at: https://ojs.hh.se/ 28 here” syndromes), technology fountains (characterized by high levels of “not invented here” syndrome and low levels of “not sold here” syndrome), technology sponges (characterized by low levels of “not invented here” syndrome and high levels of “not sold here” syndrome) and technology brokers (characterized by low levels of both “not invented here” and “not sold here” syndromes) (lichtenthaler et al., 2011). the research question refers to the fact that the existence of correlations between the companies’ profiles (technology fountains, technology sponges, technology brokers and technology isolationists) and the field in which they are operating (it, manufacturing) depends on the target country to which they belong (japan and romania). erickson and rothberg (2013) suggest that decision-makers should be aware that a balance between knowledge sharing and protection is compulsory, giving particular attention to industry-by-industry conditions, demanding more or less protection when innovation is a high priority. as a result, they must be able to decide when to develop and share proprietary knowledge assets widely (outbound open innovation) and when not to (inbound open innovation). in their opinion, the propensity to outbound innovation increases the competitive intelligence risks. the open innovation’s approach by means of cross-cultural strategic intelligence allows the mutual adjustment of intra-firm managerial procedures, based on cultural differences harmonization and will enable collaborative learning based upon shared perspectives and lists of opportunities to target. the successful valorization of open innovation opportunities based upon cross-cultural strategic intelligence is setting new equilibria between short and long term firm interests. it allows superior understanding and early opportunities recognition/capturing and insures a better competitiveness differentiator for strategic behaviour profiling. the cross-cultural partnerships between japanese and romanian high-tech companies addresses the main issues of emergent markets’ scanning: finding the right answer to the strategic challenge (fighting or engaging in disruption) and preventing blind spots in gathering disruptive intelligence (vriens and søilen, 2014). this paper is organised as follows: in the first section, dedicated to the comparative analyses reflecting the features of open innovation within japan and romania, we highlighted the issues referring to the ways in which open innovation is perceived by the business environments from the two target countries; the second section is a description of our research methodology and tools; in the third section, we presented the main findings of the correlation study, using the facilities provided by spss software; in the last section, we presented the conclusions, the limitations of our study, its practical implications and the directions in the future research agenda. 2. theoretical background despite the interest in open innovation, a comprehensive review of academic publications in the area does not seem to exist (elmquist et al., 2009). open innovation describes an emergent model of innovation in which firms draw on research and development that may lie outside their own boundaries, revealing the fact that valuable ideas can come from inside or outside the company and can go to market from inside or outside the company as well (chesbrough et al., 2008). inbound open innovation refers to the internal use of external knowledge, while outbound open innovation refers to the external exploitation of internal knowledge. two practitioners in this field distinguish between three knowledge processes (knowledge exploration, retention, and exploitation) that can be performed either internally or externally (lichtenthaler, 2009). the main objectives pursued by open innovation strategies are the following: gaining access to new knowledge, multiplication of own technologies, learning from knowledge transfer, controlling technological trajectories, external exploitation as a core business model and exerting control over the market environment (kutvonen, 2011). the open innovation approach overcomes managerial difficulties to understand the dynamics of innovation, through balancing both disruptive and sustaining innovation (paap and katz, 2004). the open innovation approach is compatible with disruptive business-model behaviour, in the following circumstances (markides, 2006): when companies enter into a new market, where strong competitors have first-mover advantages and when they attempts to scale up an innovative product to make it attractive to the mass market. building upon cross-cultural and open innovation approaches, disruptive innovation emerges from a successful combination of 29 several smaller ideas based on observing the world differently (assink, 2006). the concept of open innovation embraces the strategic intent behind the use of both internal and external resources and is defined as the dynamic capability to manage technology both within and outside firms (suh and kim, 2012). the investigation of the reasons for which companies open up their innovation processes is a central issue in this field (huizingh, 2011). both offensive reasons (e.g., stimulating business development) and defensive ones (e.g., decreasing costs and risks) are emphasized. two empirical studies conducted in this way proved that offensive reasons were more important than defensive reasons (chesbrough and crowther, 2006; van de vrande et al., 2009). trends such as outsourcing, agility and flexibility had already forced companies to reconsider their strategies and processes in other areas and to become network organizations, which integrate open innovation into their business model (gassmann, 2006). a regularly updated technology focused-strategic intelligence process, which presents multiple technologies as options on a technology radar, leads to increased opportunity awareness of external high-potential technologies (veugelers et al., 2010). the future of intelligence studies in business continues to lie primarily with its symbiosis with new technology (søilen, 2016). the openness of the outside-in process in r&d management is of crucial importance for achieving high direct and indirect innovation output effects (inauen and schenker-wicki, 2011). from a strategic perspective, open innovation needs executive level commitment, as this is generally the most important obstacle that companies face in trying to adopt it (sloane, 2011). research undertaken in uk manufacturing firms reveals the lack of firms’ openness to their external environment, reflecting organizational myopia and indicating that managers may overemphasize internal sources and under emphasize external sources (keld and salter, 2006). the results of a survey undertaken in spain emphasizes that open innovators are smaller and less r&d intensive than semi-open ones, although larger and more r&d intensive than closed innovators (bargegil, 2010). another study developed in china has shown how firms' open innovation practices influence the national systems of innovation and how the policy-makers’ decisions can foster and speed up open innovation practices (wang and zhou, 2012). generally, open innovation doesn’t adversely affect competitive advantage, but the companies whose advantage is driven by barriers to entry, skills in innovation and anticipating customer needs, or that rely on proprietary product designs, can face difficulties in the long term (reed et al., 2012). the main findings of a survey focused on the measurement of open innovation outputs support the expectations that the ability to build inter-organizational relationships in a knowledge-rich environment increase the efficacy of inbound open innovation for gaining superior financial performance (sisodiya et al., 2013). moreover, open innovation activities strengthen the positive effects of dynamic innovation capabilities on disruptive innovation (cheng and chen, 2013). regarding innovation measurement, companies are still looking for adequate indicators that monitor the investments and the effects of open versus closed innovation approaches. in this way, there is interesting research that provides relevant answers as to how the adoption of open innovation practices is linked to financial performances of companies (michelino et al., 2014). 3. peculiarities of open innovation in the target countries involved in crosscultural research: japan and romania open innovation is in essence a cross-cultural phenomenon, involving dynamic processes of knowledge creation, diffusion and use (del giudice et al., 2012). innovative firms are more successful in international business, putting them into contact with alternative business cultures and open innovation contexts and making them more able to compete internationally (filippetti et al., 2011). the literature related to open innovation reveals minimal empirical evidence on cross-cultural surveys focused on the assessment of companies’ cultural profiles in the context of open innovation practices. a previous crosscultural survey developed in four countries (japan, romania, tunisia and turkey) emphasized the distribution of the companies’ profiles in four clusters (technology isolationists, technology fountains, technology sponges and technology brokers), but its main limitations refer to the significant gaps in the 30 distribution of companies on different sectors within the national samples and the lack of correlation tests between specific variables (yamazaki et al., 2012). according to christensen (2016, p .12), “in the period 1970-1980, japan was quite successful in generating disruptive and market-creating innovations. however, disruptive and market-creating innovations have been disappearing over the last 25 years, because the focus has changed from marketcreation to efficiency. the problem is not innovation but management style to support new ideas”. the open innovation approach in japanese firms is highly related to their capacity to incorporate promising disruptive technologies from inside and outside, in line with their program entitled impulsing paradigm change through disruptive technologies (impact). open innovation, characterized by using not only in-house but also external r&d resources (chesbrough, 2003), is perceived as a sustainable competitive advantage by the japanese companies. according to many opinions, japan’s system of innovation is mainly driven by large corporations, but external collaboration in r&d has been developed and promoted at a large scale in the last decade. capturing opportunities for managing internally, all r&d resources became a trend for japanese high-tech companies. the intelligent positioning of japanese high-tech firms resides on two pillars: searching for future growth potential through open innovation, and installing itself into new markets through globalization (motohashi, 2011). the innovation network corporation of japan (incj) insures a long-term partnership between the japanese government and major high-tech corporations. incj encourages open innovation, providing patterns for how to strategically move technology and expertise beyond the boundaries of existing organizational structures. one of the most important roles played by incj is to conduct targeted research in order to facilitate successful collaborative innovations in an open context (lippitz, 2012). the long-term cooperation between hightech firms is already specific and can be considered to be a pattern for japanese firms; smes became aware of the fact that technology plays an important role in their business models and they found solutions to support open innovation. making sense of contractual incompleteness, pertinent analyses related to japanese smes regarding open innovation, focuses on the real challenge to unambiguously deal with foreseeable contingences: whether open cooperation can be constructed, whether cooperation among organizations can be formed, who bears costs for constructing collaboration, and whether mutual trust can be formed (idota et al., 2012). a recent survey conducted in japan proposes and tests a model of innovation process management used to clarify the managerial strategies required to achieve it in japanese enterprises (ota et al., 2013). the authors found specific practices and capabilities that were statistically significant in japan's manufacturing companies. the importance of structured process in the japanese manufacturing sector was confirmed, comprising scanning, idea occurrence, strategy formulation, resource procurement, implementation and value creation. the results of a survey conducted on 180 european companies show that inbound open innovation is more commonly used than outbound open innovation, which can be explained by insufficiencies in the market or the organization, confirming its role as a complement for internal r&d (schroll and mild, 2011). the firms operating in emerging economies need not necessarily rely on entrepreneurial behaviour to sustain business growth, although involvement in open innovation may enhance business performance (chaston and scott, 2012). the emerging countries with weak capabilities, in both firms and national systems of innovation, have the opportunity to employ the open innovation approach in order to accelerate their technological learning and development (wang et al., 2012). in this context, the integration in the european union has changed the managerial mentalities within romanian companies, which previously assigned less importance to r&d activities. however, a significant lag between open innovation and technology transfer is still reminiscent in the romanian business culture (borcea and fuica, 2012). regarding the propensity of emerging economies to engage in successful crosscultural partnerships with developed countries, consistent evidence relies upon rethinking the core causality of making poorly stimulated innovation policy and fragile sme organizational capabilities. 31 re-contextualization should focus on understanding new causal factors, which best fit the socio-economic context and organizational capabilities, in order to overcome obvious technological gaps between developed countries versus emergent ones (karo and kattel, 2011). the performances related to romania's innovation system remains are smaller, when compared to other eu countries. positioned in a cohort of ‘catching–up’ countries, romania’s economic background is characterized by a positive economic trend, mainly based on low cost labour and low value-added exports; the big problem and challenge, at the same time, is represented by the low level of innovation infrastructure, at an early development stage. pro inno europe highlights that romanian innovative companies are less than a fifth of the country’s total number of active firms. the profile of a romanian innovative is the following: sme, operating in the software industry, in internet and new media. the low level of public funding for innovation (only 10% of innovative firms receive funding), correlates to very low levels of innovation expenditures (in most cases, they don't exceed 3% of innovative firms’ turnovers) explain the reality in romania’s innovative business landscape. although significant progress has been made in order to foster the weak innovation culture in the country, further measures are needed to increase the application of r&d results by business and to turn innovation into a driver of national competitiveness. a recent study focused on the perspectives of the romanian sme sector in the context of innovation and knowledge creation (purcarea et al., 2013). it emphasizes a learning orientation related to innovation, using best practices within the organization and networking with external partners as internal sources for learning, whereas in terms of external support for learning, smes consider changes that take place in the market, changes in technology and the input from experts and consultants. many romanian entrepreneurs, endowed with disruptive innovation potential, are not able to perform optimally, as there is a lack of access to relevant market information for attracting investment flows, which can finance their innovations. 4. research methodology in order to achieve the research goal, we designed and developed a questionnaire as the main research tool focused on data collection, in which 20 questions (items) were grouped in four categories, corresponding to the four types of open innovation cultures (figure 1). the five items focused on technology fountains reveal a low attractiveness for external technology sourcing and implicitly a high degree of independence of technology to different providers, associated with a high interest for commercialization strategy of the company’s internally developed technologies, without concern for losing control over them. the five items focused on technology sponges emphasize an improvement of the internal innovation process by means of acquiring technology from external sources as a result of strategic intelligence mechanisms, correlated with internal agreements which don’t allow the ip transfer to other companies. the five items focused on technology brokers reveal the situations in which companies proceed to external technology acquisitions in order to the improve the r&d process and internal technology selling in order to provide additional revenue. the five items focused on technology isolationists highlight the situations in which companies benefit from the technologies developed internally and retain full control of their intellectual property, preventing other organizations from making a profit from their technologies. figure 1 four clusters of companies’ profiles in the context of open innovation. adapted from lichtenthaler et al., 2011. we sent the questionnaire to a convenience sample formed of japanese and romanian companies from the fields of manufacturing and it. questionnaires were transferred to the selected participants through electronic mail system, including our commitment to respect the confidentiality and anonymity of the answers. each questionnaire’s results were 32 processed by means of an automatic coding scheme in spss software, in order to avoid data input errors. finally, 80 returned questionnaires per country were stored in a spss database, after eliminating the incomplete answers. the structure of the sample was the same in the two target countries: 40 companies from the manufacturing field, as well as 40 companies from the it field. consequently, two hypotheses were proposed to be tested by means of appropriate statistical methods. h1: in the case of japanese companies included in the sample, their profiles (technology fountains, technology sponges, technology brokers and technology isolationists) are positively related to the field in which they are operating (it or manufacturing). in this situation, the independent variable is represented by the japanese companies’ profiles, while the field in which these companies are operating reflects the dependent variable. h2: in the case of romanian companies included in the sample, their profiles (technology fountains, technology sponges, technology brokers and technology isolationists) are positively related to the field in which they are operating (it or manufacturing). in this situation, the independent variable is represented by the romanian companies’ profiles, while the field in which these companies are operating reflects the dependent variable. the statistical methods that we used in order to test the hypotheses are chi-square, pearson's r and spearman coefficients of correlation. the chi-square test is applied in order to determine whether there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. the use of the chisquare test involves the design of two hypotheses: the null hypothesis states that there is no significant difference between the expected and observed frequencies, while the alternative hypothesis states they are different. the level of significance (the point at which we can say with 95% confidence that the difference is not due to chance alone) is set at 0.05. the pearson's r correlation coefficient is a useful descriptor of the degree of linear association between two variables, having two key properties of magnitude and direction. when it is near zero, there is no correlation, but as it exceeds -0.1 or 0.1 there is a negative or positive relationship, respectively, between the variables; if they are close to 1 or +1, there is a strong negative or positive relationship between the variables. the sign of the spearman correlation coefficient indicates the direction of association between the independent variable and the dependent variable. if the dependent variable tends to increase when the independent variable increases, the spearman correlation coefficient is positive; otherwise, the spearman correlation coefficient is negative. a spearman correlation coefficient near zero indicates that there is no tendency for the dependent variable to either increase or decrease when the independent variable increases. 5. findings and discussions the use of the descriptive statistics methods, on the one hand, and the illustration of the indepth analyses of the research results, on the other hand, involved the distribution of the respondents’ answers in two contingency tables, reflecting the correlations between companies’ profiles and the fields where they operate, in the case of each target country. the distribution of research results corresponding to the first hypothesis involved the design of a contingency table with double entry, which allows the classification of the observed frequencies (table 1). table 1 contingency table associated with the first hypothesis test (h1). cross-tabulation results field total it manufacturing japanese companies’ profiles technology fountain 11 16 27 technology sponge 10 6 16 technology broker 15 9 24 technology isolationist 4 9 13 total 40 40 80 33 table 2 first hypothesis tested by the chi-squared method. indicator value degrees of freedom asymptotic significance pearson chi-square 5.349 3 0.148 likelihood ratio 5.432 3 0.143 linear-by-linear association 0.010 1 0.919 number of valid cases 80 table 3 first hypothesis test by means of pearson’s r and spearman correlation coefficients. a not assuming the null hypothesis, b using the asymptotic standard error assuming the null hypothesis, c based on normal approximation. int = interval, ord = ordinal. symmetric measures value asymptotic std. error a approx. tb approx. sig. c int. by int. pearson’s r -0.011 0.112 -0.101 0.920 ord. by ord. spearman correlation -0.020 0.114 -0.174 0.862 number of valid cases 80 table 4 contingency table associated with the second hypothesis test (h2). cross-tabulation results field total it manufacturing romanian companies’ profiles technology fountain 7 6 13 technology sponge 11 12 23 technology broker 16 5 21 technology isolationist 6 17 23 total 40 40 80 as we can observe from table 1, the majority of the japanese companies included in the sample are identified as technology fountains, followed by technology brokers, proving other empirical findings which emphasize the adoption at a large scale of open innovation in japanese high-tech companies. by taking into consideration the field in which these companies are operating, we can observe that technology fountains and technology isolationists are more common in manufacturing, while technology sponges and technology brokers are more common in the it field. we can state that the results are relevant to the reality of the japanese economy, in the context in which all the players from the business environment are aware of the opportunities to boost technology, in order to promote open innovation. the systematic approach of open innovation led japanese companies to gain permanently sustainable advantages, being able to successfully expand internationally. the results correspond to the test of the first hypothesis. the results of the cross-tabulation process using the respondents’ answers stored in the spss database are revealed in tables 2 and 3. in this case, the value associated to the asymptotic significance (0.148) is higher than the level of significance (0.05) and the pearson chi-square value (5.349) is lower than the chisquared value corresponding to the statistics table (7.82), with three degrees of freedom; consequently, the hypothesis is rejected, so the profiles of the japanese companies included in the sample are not influenced by the field in which they are operating (it or manufacturing). table 5 second hypothesis evaluated by means of a chi-squared test. indicator value degrees of freedom asymptotic significance pearson’s chi-square 11.143 3 0.011 likelihood ratio 11.662 3 0.009 linear-by-linear association 1.588 1 0.208 number of valid cases 80 table 6 first hypothesis test by means of pearson’s r and spearman correlation coefficients. int = interval, ord = ordinal. symmetric measures value asymptotic std. error approx. t approx. sig. int. by int. pearson’s r 0.142 0.110 1.265 0.210 ord. by ord. spearman correlation 0.146 0.113 1.303 0.197 number of valid cases 80 the results of the first hypothesis test process are also validated by pearson’s r and spearman correlation coefficients (table 3), because their values (-0.011, respectively 0.020) are negative, but situated near zero, emphasizing the lack of correlation between the independent variable (japanese companies’ profiles) and dependent variable (the field in which the companies are operating). we view the pearson's r and spearman correlation coefficients as useful descriptors of the degree of linear association between the variables related to the research conceptual model, as they revealed the lack of correlation between the variables. the distribution of research results corresponding to the second hypothesis involved the design of a new contingency table with double entry, which allows the classification of the observed frequencies (table 4). the in-depth analysis of the research results outlines the fact that, in the case of the romanian companies included in the sample, their profiles correspond mostly to technology sponges and technology isolationists, unlike the companies from japan, focused to a great extent to the other two profiles. moreover, we can observe high discrepancies in what concerns the distribution of the companies’ profiles in the technology broker and technology isolationists clusters; in the first case, the majority of firms belong to the it field, while in the second case, the majority of firms belong to the manufacturing field. these findings can be explained by taking into consideration the fast development of the romanian it and software services industry, as a result of open innovation adoption; in the situation of romanian manufacturers, we still perceive a resistance towards open innovation, reflected in a high number of technology isolationists, which can be associated with a reduced appetite for risk. the results corresponding to the test of the second hypothesis, after the configuration of the cross-tabulation process using the respondents’ answers stored in the spss database, are shown in tables 5 and 6. in this particular situation, the value of the asymptotic significance (0.011) is lower than the level of significance (0.05) and the pearson’s chi-squared value (11.143) is higher than the chi-squared value corresponding to the statistics table (7.82), with three degrees of freedom; the hypothesis is accepted, so the profiles of the romanian companies from an open innovation perspective are positively related to the field in which they are operating (it or manufacturing). the results of the second hypothesis test process are also validated by pearson’s r and spearman correlation coefficients (table 6), because their values (0.142 and 0.146, 35 respectively) are positive, emphasizing the fact that the dependent variable (the field in which the romanian companies are operating) tends to increase when the independent variable increases (the number of romanian companies’ profiles in a certain cluster). another assumption is that there is a monotonic relationship between the independent and dependent variables, determined by the existence of relevant gaps in the distribution of romanian companies’ profiles in the technology broker and technology isolationist clusters, as well as minimal differences in the case of the other two clusters. 6. conclusions, managerial implications and future research agenda tracking high tech innovation partnerships’ practices of cross-cultural collaboration, while being aware of open innovation opportunities for capture, it’s compelling to assume causally contrasting elements are challenging for setting the leveraging role of coming strategic intelligence configurations. nevertheless, the current research efforts to test theory building in searching for pertinent constructs to validate the above hybrid approach, are upgrading previous coherent relevant insights, exploring partnership coordination mechanisms—capable of overcoming cultural dissonance—while capitalizing upon open innovation opportunities. as main challenge is culturally specific, we assert that strategic intelligence solutions—as part of managerial communalities—should be designed and deployed through the hybrid organization’s internal environment adjustment, focus on cooperation perspective and not on “fixing the gaps” perspective, which is more consistent with open innovation principles. we understand that by managerial communality the cross-cultural coordination mechanism (agreed between partners)—which is considered a strategic intelligence solution— can take advantage of the cultural differences, as opposed to minimizing the gap. the above considerations also support that open innovation approach is matching the emergent new managerial models, such as “harmocracy.” the principles of both of these are common. the educated collaborative practices are evolving toward enlightened management, capable of channeling the valorisation of open innovation opportunities through a communion of scope strategy, expectations, strategic scope and results. the results provided by the hypothesis analyses are representative of the development stages of the two target countries. japan is one of the highly developed countries, while romania is still in transition towards a competitive economy. moreover, they are coherent with the actual stage of the global economy, affected by the effects of the financial and economic crisis (with important consequences in the field of business efficiency, operating cost cuts and revenue increases). thus, from an innovation perspective, both countries are characterized by appreciatively similar distributions of the companies from the research sample in the “technology brokers” cluster. this is proof that the financial and economic crisis forced companies, regardless of their country, to reduce operating costs (with the adoption of innovative technologies being a solution) and to increase revenue regardless of their nature. in romania, the companies from the it field are more aware of the benefits of open innovation than the companies from manufacturing, as they are part of an industry less affected by the crisis. a significant number of companies included in the technology sponges cluster can be found in both target countries (approx. 20% from the japanese sample and 29% from the romanian sample). the fields in which the companies act is not relevant for the behaviour in these countries, as there are firms with important financial resources which don’t pay attention on the short term to the opportunities related to revenues increases. only the evolution of the macroeconomic factors will or will not support such a behaviour. the situation of the companies included in the final two clusters, technology fountains and technology isolationists, is the opposite. in japan, fountain-type behaviour is more diffuse, being characteristic of a developed economy based on leading technologies. in romania, there are more isolationists, especially in the manufacturing field, as a consequence of the fact that gathering competitive advantages is possible only by means of an isolationist behaviour regarding selling or acquiring advanced technologies. the cross-cultural partnerships between japanese and romanian companies should be built upon two pillars: transfer of disruptive technologies in an open innovation context and romanian high-tech companies’ capability to learn from japanese high-tech companies’ 36 knowledge and anticipative capability. anchoring disruptive intelligence in a crosscultural context enlightens strategic trajectories towards opportunities to create entirely new markets. the first vulnerability to highlight is the level of accuracy in terms of predictability in the case of an obvious gap in the development stage model of the country and open innovation profiling behaviour. a better differentiator could be identified by setting output variables of open innovation to: the number of patents of each sector, intra-sectorial synergies, and the span and degree of globalization captured opportunities of each sector, for example. a qualitative approach of crisis consequences must be performed. in this way, we advance the hypothesis that open innovation and cost shrinking correlation is debatable, as it is obvious that open innovation becomes the solution for emergence from the economic crisis. we are also aware that open innovation is generating high transaction costs and it is requiring specific managerial coordination and limited transferable organizational practices: it is emerging in a new generation of managerial models, with more appropriate practices, which insure the alignment of open innovation opportunities with strategic behaviour profiling. it is hard to imagine how it will change the behaviours of the it and manufacturing firms from these two countries towards innovation. if short-term change is predictable, as our research reflects, on the long term the behaviour of these companies will face factors such as advancements in it evolution as well as the 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(2018) an e va lu a tion o f com pe titi ve an d te chn o lo gica l in te lligen ce too ls: a clu ster an a lysis of users’ perceptions. journal of intelligence studies in business. 8 (1) 5-15. article url: https://ojs.hh.se/index.php/jisib/article/view /282 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index an evaluation of competitive and technological i n t e l li g e n c e t o o l s : a c l u s t e r a n a l ys i s o f u s e r s ’ p e r c e p t i o n s fatma fourati-jamoussia*, claude-narcisse niambaa and julien duquennoya ainteract research unit up 2018.c102, unilasalle, beauvais montsaint-aignan, france; *fatma.fourati@unilasalle.fr journal of intelligence studies in business please scroll down for article an evaluation of competitive and technological intelligence tools: a cluster analysis of users’ perceptions fatma fourati-jamoussia*, claude-narcisse niambaa and julien duquennoya a interact research unit up 2018.c102, unilasalle, beauvais mont-saint-aignan, france corresponding author (*): fatma.fourati@unilasalle.fr accepted 17 march 2018 abstract the purpose of this article is to discuss and evaluate the use of competitive and technological intelligence (cti) tools by students to help designers of these tools get the best efficiency out of a monitoring process. this article introduces an application of the cluster analysis method and the competitive and technological intelligence literature. in order to evaluate the use of cti tools, we deal with two evaluation models: task-technology fit (ttf) and the technology acceptance model (tam). a survey was sent to users of cti tools addressed to engineering students and the most pertinent replies were examined. the responses were analyzed by using the statistical software spad. results showed a typology from the various profiles of users of this technology by using the method of classification. we note different perceptions between student users. although this study remains focused on the individual perspective, it requires more examination about the organizational impact of the use of cti tools. the identification of the different user profiles was done by using a cluster analysis. for the designers of cti tools these results highlight the importance of user perception, suggesting designers take into account the perception of all user types. as these tools develop, more and more companies will be looking for skills of future engineers for monitoring and management of strategic information. that’s why practical courses in cti are taught to the students in order to take into account the companies’ needs. keywords competitive and technological intelligence, cluster analysis, ttf model, tam model, user perception 1. introduction generation y students need to understand why we use information gathering tools and how these tools have evolved since their emergence. what sense can be given to the quality of information found on the web? are they able to judge the quality of the monitoring tools used and the information found? what do they need today in an engineering school? these questions prompted us to think about teaching a module entitled economic and strategic intelligence at unilasalle where we present the tools of competitive intelligence, technological intelligence, marketing intelligence and e-reputation (fouratijamoussi, 2015). we have applied these types of surveillance (french veille) to a problem related to the fields of study of our students. we have three specialties in engineering training: agriculture, food and health and geology. our approach seeks to answer two key research questions: 1. how can engineering students make a choice between different monitoring tools to collect, process and disseminate information? journal of intelligence studies in business vol. 8, no. 1 (2018) pp. 5-15 open access: freely available at: https://ojs.hh.se/ 6 2. what are the different perceptions between students using monitoring tools? to answer these questions, we propose in the second section the conceptual background about some cluster analysis applications, cluster analysis methodology, cluster analysis with spad and we define the two processes of “competitive intelligence” and “technological intelligence”. in a third section, we propose the approach of our study and the research method. in the fourth section, we present our results on the monitoring tools developed within unilasalle and cluster users’ perceptions of these tools. conclusions are drawn in the fifth section. 2. conceptual background 2.1 cluster analysis applications anderberg (1973, 2014) presented all various applications of cluster analysis, the topics covered from variables and scales to measures of association among variables and data units. he discussed the conceptual problems in cluster analysis and presented many major areas of application. these are: “the life sciences: the object of the analysis method is to develop complete taxonomies to delimit the subspecies of a distinct but varied species (for example, plants or animals); the medical sciences: the cluster may be a disease, patient (or their disease profiles) and laboratory tests; the behavioral and social sciences: the objects of analysis covered training method, factors of human performance, organizations, students, courses in school, teaching methodologies or techniques. factor analysis is a competitor to cluster analysis in these applications. the earth sciences: the object of these applications is to soils, countries, or regions of the world; the engineering sciences: the application has been relatively unused in this field. the information, policy and decision sciences: the applications to documents, the political units, products, markets, sales, programs, research and development projects.” (p. 5-6) a cluster analysis is considered to be a tool of classification, most frequently used in marketing research (punj and stewart, 1983). 2.2 cluster analysis methodology “cluster analysis is the art of findings groups in data” (p. 1), the classification of similar objects or perceptions into groups is an important human activity (kaufman and rousseeuw, 2009). berkhin (2006) defined clustering as a division of data into groups of similar objects, it is related to many disciplines and plays an important role in a broad range of applications that deal with large database with many attributes. clustering must not be confused with classification. in clustering, we must first develop a quantitative scale on which to measure the similarity between objects and secondly an algorithm for sorting objects into groups (johnson and wichern, 1998). in classification, we first separate a known number of groups and then assign new observations to one of these group according to the measurements. to carry out a cluster analysis, a wide variety of clustering algorithms is available: hierarchical techniques and nonhierarchical techniques. “hierarchical clustering techniques proceed by either a series of successive mergers (agglomerative hierarchical methods) or a series of successive divisions (divisive hierarchical methods). agglomerative hierarchical methods start with the individual objects. thus, there are initially as many clusters as objects. the most similar objects are first grouped, and these initial groups are merged according to their similarities. divisive hierarchical methods work in the opposite direction. an initial single group of objects is divided into subgroups such that the objects in one subgroup are ‘far from’ the objects in the other. these subgroups are then further divided into similar subgroups; the process continues until there are many subgroups as objects – that is, until each object forms a group” (johnson and wichern, 1998). 7 “the results of both agglomerative and divisive methods may be displayed in the form of a two-dimensional diagram known as a dendrogram. the dendrogram illustrates the mergers or divisions that have been made at successive level and looks like a tree” (johnson and wichern, 1998). this is why it’s sometimes called the “hierarchical tree”. “nonhierarchical clustering techniques are design to group items into a collection of 𝑘 clusters. the number of clusters, 𝑘, is specified before starting the clustering procedure. however, hierarchical clustering techniques are the most popular. in the following sections, we will deal with one particular agglomerative hierarchical procedure, say the ward’s hierarchical clustering method. in this method, a variance criterion is used to decide on which individuals or which clusters should be fused at each stage in the procedure. to implement this method, it’s necessary to find, at each step, the pair of individuals or clusters that leads to a minimum decrease in total between-cluster variance after merging. in other words, two items whose merging results in the smallest decrease in between-cluster variance are joined. the results of ward’s method can be displayed as a dendrogram which is often used to identify the best groups of clusters: those in which the between-cluster variance is high whereas the within-cluster variance is low. the vertical axis of the dendrogram gives the values of the between-cluster variance decrease at which the mergers occur” (johnson and wichern, 1998). beyond the identification of the best groups of clusters, it is important to know how the clusters could be described, in other words which variables are concerned by the observed similarities (johnson and wichern, 1998). 2.3 cluster analysis with spad v.8 spad is a useful statistical software used to deal with multivariate data analysis techniques such as hierarchical clustering. an exploratory factor analysis (principal component analysis or multiple correspondence analysis) is always conducted prior to a cluster analysis. the aim is to extract the meaningful dimensions in the dataset and then describe the objects that will be classified into groups by using the dimensions, which are also called factors. in fact, there are two types of attributes involved in the data to be clustered: metric and nonmetric. if the data are metric then a principal component analysis is used, if not, a multiple correspondence analysis is used. spad offers the opportunity to reduce the dimensions in the data and then use the scores from the suitable exploratory factor analysis to perform the ward’s hierarchical clustering method. after performing the clustering, the analyst is involved in two main steps: step 1: choosing the best groupings of individuals by using a visual cutting of the dendrogram. the “branches” of the dendrogram are cut with horizontal lines where the consecutive nodes are distant. in other words, the dendrogram is cut where its branches are very long. it’s good to have an idea of the best groupings even if those groupings are not necessarily stable. in practice, there are two or three possible cuttings. it is up to the user to choose one of them. step 2: description of the clusters from a chosen grouping. the significant variables are used to characterize the individuals from each cluster. that description is done when the groupings are “consolidated”. for instance, each individual is assigned to the cluster whose centroid is nearest (johnson and wichern, 1998). spad also offers the opportunity to work with a hybrid clustering technique when the size of the dataset, especially the number of individuals, is very important (more than several thousand individuals). a nonhierarchical clustering technique, such as the “𝐾-means” technique (everitt, 1998), is applied to the dataset prior to the hierarchical clustering technique. 2.4 the process of competitive and technological intelligence “competitive intelligence” (jakobiak, 1998; herring, 1998; kahaner, 1998; ruach and santi, 2001) is regarded as a specialized branch 8 of “business intelligence” (giald and giald, 1988; sakys and butleris, 2011). solberg soilen (2015) proposed the classification of intelligence studies to help place different forms of intelligence and show how they related to each other. the first concept aims to collect and analyze data on specific and generic competitive environments, it is also defined by bel hadj et al. (2016) as “a voluntary process whereby a company can begin to scan and absorb information from its socioeconomic environment in order to minimize the risks associated with the uncertainty and locate available opportunities” (pateyron, 1998). while the second focuses on the current competitors and can analyze areas such as potential acquisitions-mergers and evaluate specific country risks (lesca and caron fasan, 2006). bel hadj et al. (2016) highlighted the literature that examines competitive intelligence in relation to its integration with company strategy (porter, 1999), knowledge management (jacob and patriat, 2002), collective learning and cooperation (salles, 2006), business opportunities (marmuse, 1996) and entrepreneurial orientation (bel hadj et al., 2014). du toit (2015) listed the terms and the number of articles selected for the period between 1995 and 2014 to show the evolution of terms using the database abi/inform: competitive intelligence (75%), business intelligence (13%), marketing intelligence (8%), strategic intelligence (1%), technological intelligence (1%) and competitor intelligence (1%). he showed also the main journals that published a high percentage of competitive intelligence articles and only two journals: journal of intelligence studies in business and marketing intelligence & planning that focused exclusively on the publication of intelligence types. competitive intelligence serves to identify, monitor competitors and decrypt their strategy. technological intelligence is to follow a technical and scientific domain in time and to monitor developments (www.ie.bercy.gouv.fr). salvador et al. (2014) presented a patent analysis on additive manufacturing and showed the work of calof and smith (2010) that “consider that competitive technical intelligence (cti) and strategic technological foresight (stf) are fields with similar objectives and techniques. while the authors define cti as a practice that provides business sensitive information on external scientific or technological traits, opportunities or developments that have the potential to affect a company’s competitive position. stf according to them is a collaborative tool that draws upon the talents of many individuals (not only from the technology domain) and is an important source for technical and business intelligence.” the articles published in the journal of intelligence studies in business since 2011 were focused on developing and testing models to evaluate business intelligence systems and software. following these studies, new problems have emerged: to study the differentiation of business intelligence vendors (solberg soilen and hasslinger, 2012), to reformulate the ci problem identify competitors (touchgraph, xerfi, netvibes, sindup…) identify information sources of competitors monitor sources during the project period processing information analyze information summary of strategic information (ci note) figure 1 teaching the competitive intelligence (ci) methodology 9 classify business intelligence software based on their functionalities and performance (amara et al. 2012; nyblom et al. 2012; abzaltynova and williams, 2013), and to show the perception of business intelligence tools by professionals and students using two models of information systems literature (fouratijamoussi and niamba, 2016). this literature review has enabled the definition of a competitive and technological intelligence plan (figure 1 and 2). these two methodologies of cti were applied by all students when they reformulated and responded to their watch problems (for example: extraction of pea protein; create new food products such as ice cream and energy cake; future of renewable energies and rare metals) to apply this ci methodology, the students collected information from the competitive environment of the firm selected, they used general and monitoring tools to identify information sources of competitors, then monitor them over time (period of the watch project). finally, they organized and analyzed all information treated to understand the strategic development of all competitors. the ti methodology consists of establishing the goal of the project, then organizing a collection of patent information by using databases: espacenet and patentscope designed by the inpi (institut national de la propriété intellectuelle) and the wipo (world intellectual property organization). the students need to identify the main countries, international patent classifications (ipcs), applicants, and inventors. to exploit and analyze all pertinent patents, they used the keyword-based patent analysis (salvador el al. 2014) that represents an important method used to determine technology trends, discover technological opportunities and predict new technological advances. this method is based on patent keyword frequencies between them (choi et al. 2012). 3. the methodology and the research model 3.1 data collection the study concentrated on a certain number of variables stemming from the literature in information systems, which join the problem of the evaluation of the cti tools used within the framework of the process of strategic intelligence. a survey was built in the field of the conception of the cti tools (fouratijamoussi, 2014). through this study, we tried to show the use of the watch tools and their applications. the survey was built with the aim to operationalize the variables of the theoretical model as well as to profile the users who answered this survey. it was designed and diffused to unilasalle students after applying cti methodologies presented above. our database is composed of 265 responses for clustering the users’ monitoring tools. these respondents were from three specialties: i) agriculture; ii) food and health; iii) geology. 3.2 logic of the study to evaluate and compare the user profiles, the selected criteria were taken from the theoretical fusion of these two models: technology / task fit (goodhue and thompson, 1995) and technology acceptance (davis, 1989; venkatesh et al., 2003) as part of the literature on the evaluation of information systems (figure 3). model i: “task/technology fit” aims to evaluate the user perception towards the used system. it is defined by the degree of correspondence between the functional needs relative to the task and the technical features offered by the information technology. it was explained by four criteria (b, c, d, e): search by keywords on patent database (espacenet, patentscope) identifying relevent keywords and ipc visualization of patents following the selected search criteria comparison of search results with different tools processing information using evolution graphs analyze evolution graphs identify technology and innovation trends (ti note) figure 2 teaching the technology intelligence (ti) methodology 10 a. cti tools used: is not shown in the model but in the survey. these tools are classified into three categories (presented in table 2). b. functionalities of cti tools: were the capacities of the system to help individuals or a group, determined by the type of system used (benbasat and nault, 1990; wierenga and van bruggen, 2000). the tasks presented in the questionnaire were: search information, store, process and extract a large quantity of information, resolve the semantic and syntactic problems. c. data quality: measured the correspondence between needs and the available data, it also measured the exactness of these available data by using cti tools and the quality of data at a level of detail suitable for the tasks. d. data compatibility: between the various sources of data. e. capacity of learning: the ability of students to use these watch tools. f. the intensity or frequency of use: it was a subjective appreciation of the increase or the decrease in the degree of use. the intensity depended on the integration of the business intelligence system (grublješič and jaklič, 2014) and on the strategy adopted by the company (presented in the survey). model ii: the acceptance of cti tools is inspired from the “technology acceptance model” of davis’86, this model was explained by: a. ease of use of the cti tools (davis, 1989): measured the degree of faith of a user in the effort to supply in order to use the system. to measure the ease of use, we referred to the measuring instrument of davis (1989) which consists of six items, proven valid and reliable by doll and torkzadeh (1998). b. perceived utility of the cti tools: this element was not directly measurable. this notion came from microeconomic analysis: it was the measure of the use value of hardware or software for a user. it measured at the same time the impact of cti tools on productivity and quality. the perceived utility was defined by the degree of improvement of the performances expected from the use of the system (davis, 1989). c. satisfaction of the cti tools user: it was the degree of continuity of use by the individual. it was a positive faith of the individual perception which showed the value of cti tools. this variable was considered as a dimension of success of cti tools (seddon, 1997). it could influence the intention, but it was also a consequence of the use (delone and mclean, 2003) of the utility and the ease of use perceived. qd comp fonc peo u pu sat int app task-technology fit (ttf) technology adoption model (tam) legend: fonc: functionalities of monitoring tools peou: perceived ease of use qd: quality of data pu: perceived utility comp: compatibility of sources sat: user satisfaction app: capacity of learning int: intention of use figure 3 research model of cti tools used 11 d. intention of cti tools use: the manager can accept a system but decides when he uses it or plans to use it in the process of decision-making. the intention of a user to use a system adopted by the organization as well as its satisfaction by this use depended on the utility and on the ease of use perceived from the system. 4. results analysis descriptive statistics have been used in order to show population characteristics. we have used the statistical software spad v.8 to treat the data. 35.8% of respondents were male and 64.2% were female. 98.5% of respondents were between the ages of 20-25 years, 1.5% were between the ages 26-30 years. finally, our sample of users comes from three fields of studies: 50.2% from agriculture and 23% from food and health and 26.8% from geology (table 1). table 1 demographic profile of respondents (n=265) characteristic descriptor distribution (%) gender male 35.8 female 64.2 age 20-25 years 98.5 26-30 years 1.5 field of studies agriculture 50.2 food and health 23.0 geology 26.8 according to table 2, about 42.6% of respondents used general tools such as search engines and other free tools (google search, google alert, websites), while 35.8% used monitoring tools like databases of patents or sector studies (search engines, touchgaph, xerfi, espacenet, patentscope), and finally 21.5% used platforms to monitor the competitive environment, the e-reputation brands and social networks (geological databases, netvibes, sindup, alerti, mention, talkwalker). around 50.5% of respondents didn’t frequently use monitoring tools, 48.3% used them sometimes or often, and 1.1% always used them. using the task-technology fit (ttf) model leads to 14 variables with scale values. the ward’s hierarchical clustering technique shows that the sample of students could be split in two opposite groups before the research of the stable groupings (figure 4): the first one with 67% of students and the second one with 33% of them. table 2 respondents’ tools usage and characteristics characteristic descriptor distribution (%) tools search engines and websites 42.6 search engines and patent databases 35.8 specialized monitoring tools 21.5 usage frequency never 6.0 rarely 44.5 sometimes 35.5 often 12.8 always 1.1 the search for stability of groupings leads to two clusters whose frequencies are respectively 60% and 40%, instead of 67% and 33%. each individual is represented in a scatter plot of principal component scores by a point which is the number of the cluster it belongs to (figure 5). each cluster mean (centroid) is also classification hiérar chi que directe ( sur facteurs) 412 398 469 417 464 439 419 451 447 403 441 466 369 473 461 429 196 92 456 468 462 472 477 413 478 471 41 453 459 448 475 458 470 474 436 452 467 480 437 397 151 450 465 404 435 449 380 479 457 476 33% 67% 2 figure 4 dendrogram of similarities between 265 students according to the ttf model 12 represented by a point whose size indicates the proportion of individuals in the cluster. the categorical data (gender, field of studies, tools, usage frequency) used in the description of the groups show otherwise that the first group of 60% of respondents is mainly composed of students from the specialty “geology” who often used cti specialized tools. the characteristics of these students from group 1, according to cti tools’ perception, are shown below: the available data are either suitable for their needs or helpful for their tasks; they claim to have greater capacities of learning by using cti tools; they mostly agree with the functionalities of monitoring tools; on the other hand, it is not easy for them to find useful tools for their daily work. the characteristics of the students from group 2, according to the cti tools’ perception are certainly antagonistic, but it can be noted that the individuals who belong this second group are students from the specialty “agriculture” who never used search engines and websites. the technology adoption model (tam) leads to 25 variables with scale values. two groups of students or three groups are highlight by the cuttings of the displayed dendrogram (figure 6). in the following paragraph, the cluster description in three groups is made in order to take into account the presence of a small group of 33 students with particular characteristics. the reallocation figure 5 positioning of the two clusters in a scatter plot of principal component scores. classification hiérar chi que directe ( sur facteurs) 446 434 445 463 426 437 476 408 470 469 457 472 196 456 461 82 451 427 393 479 462 419 402 474 409 465 478 430 460 92 65 438 202 475 480 442 3 473 454 477 468 450 129 471 448 458 143 244 213 464 0.09 0.10 0.10 0.100.100.100.100.10 0.110.110.11 0.110.110.11 0.120.12 0.120.12 0.130.13 0.13 0.140.15 0.150.15 0.15 0.150.17 0.18 0.19 0.19 0.200.200.21 0.220.220.23 0.280.290.32 0.32 0.37 0.400.41 0.43 0.59 0.90 2.68 4.56 40% 60% 2 9% 40% 51% 3 figure 6 dendrogram of similarities between 265 students according to the tam model. 13 step for the grouping stability search indicates three clusters whose observed frequencies are 126, 106 and 33. categorical data are also used in the description of these clusters. general statements and characteristics of respondents in each group are: group 1: often use cti specialized tools, interest shown for cti tools (utility, ease of use, ease of learning, satisfaction and intention to use in the future). group 2: rarely use general tools, little interest. group 3: never use general cti tools, rare interest in monitoring tools. the dispersion of classes described above can be visualized on the scatter plot of principal component scores (figure 7). it shows how differentiated the clusters are. the individuals are represented on the plane by identifying them by their group number. the centroids are also represented by points whose size is proportional to the size of the clusters. 5. conclusions regarding the managerial implication, the first technology-task fit model showed two groups from those who used cti tools, ranging from source identification to the dissemination of information. we can see that the profile of the first group of users can be part of an advance monitoring unit. the second group of users were latecomers in adopting this technology. finding the monitoring tools not flexible, this implies the dissatisfaction with the quality of service offered by this technology may be due to limited use. three groups were identified in the second technology adoption model, the first group is aware of the perceived usefulness of these monitoring tools and the second is considered as intermediate because they used general tools that showed their limits to achieve a watch type. the third is not satisfied completely as first users of a watch platform as part of a monitoring project. the difficulty lies in the appropriation of these tools by students and their adaptation to the selected cti projects. we deduced that a cti tool implementation in a company is accompanied by organizational change, sometimes cultural, which tasktechnology fit and tools adoption impact were not negligible. this would explain, in part, why these tools can have both success and failure in the watch projects. the implementation of this monitoring system has shown the pervasive role of students/agents/analysts in the organization and coordination of steps in this process, from receipt of the request to the dissemination of results using different monitoring tools according to their needs of information and watch types (competitive, technological, marketing). our article provides evidence that competitive and technological intelligence (eveille: see the definition of “e-veille” in lexique de gestion et de management sous la direction de j.p. denis, a.c. martinet et a. silem, 9ème édition, dunod, 2016.) was most taught to be applied to business cases for purely pedagogic education using the free and commercial watch figure 7 positioning of the three clusters in a scatter plot of principal component scores. 14 tools (netvibes, touchgraph, google, xerfi, espacenet, patentscope, sindup) to achieve these methodologies. finally, the monitoring of open and closed data can be a full search. this study showed us how to use a cluster analysis method to identify the groups of students who differ in attitude, perception and utility of the monitoring tools by putting them in situations of watching problematic. all these indicators are important to measure in subsequent works the adequacy between the functionalities of these tools and the quality of the data and the compatibility of the sources, as well as the acceptance of the monitoring tools by engineering students. this study ensures the furthering of existing models to classify business intelligence software based on their functionalities and performance (amara et al. 2012; nyblom et al. 2012; abzaltynova and williams, 2013) and to show 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(2018) de ve lo pm en t of a com pe titi ve in telligen ce m a tu rity m od el: in si gh ts fro m moroccan companies. journal of intelligence studies in business. 8 (1) 25-36. article url: https://ojs.hh.se/index.php/jisib/article/view/284 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index development of a competitive intelligence m a t u r i t y m o d e l : i n s i g h t s f r o m mo r o c c a n c o m p a n i e s mourad oubricha*, abdelati hakmaouia, robert bierwolfb and mouna haddanic aciems research, morocco; bieee-tems; cmarco telecom, morocco *oubrich.mourad@ciems.ma journal of intelligence studies in business please scroll down for article development of a competitive intelligence maturity model: insights from moroccan companies mourad oubricha*, abdelati hakmaouia, robert bierwolfb and mouna haddanic aciems research, morocco; bieee-tems; cmarco telecom, morocco corresponding author (*): oubrich.mourad@ciems.ma accepted 2 march 2018 abstract this paper aims to assess the maturity level of competitive intelligence (ci) in moroccan companies, so as to improve theirs practices, and to justify their investment in competitive intelligence. to do so, we have identified the maturity model based on a comprehensive review of recent literature. the objectives of this paper are threefold: (1) to determine the major purposes of a ci maturity model (cimm), (2) to identify the types of ci dimensions and levels of maturity, (3) to evaluate moroccan companies in terms of ci practice. our approach is to develop a conceptual framework of the ci maturity model that articulates (1) dimensions of ci, and (2) maturity levels of ci. we note that little attention has been given in previous research to how ci is actually conducted in moroccan companies. for this purpose, an empirical study was conducted. the results discuss various perspectives and insights from a competitive intelligence maturity model point of view in the moroccan context. the results show that the majority of the moroccan companies are in an early stage of the ci levels, where the ci practice is only to employ environment scanning and the competition in the business environment is not intense. we also note the absence of ci structure at this level. most of these moroccan companies are not able to cope with changes in the business environment. the ci systems and processes are released on an irregular basis. this study is the first to investigate the competitive intelligence maturity model (cimm) in the moroccan context. the findings of this research show that there are six ci dimensions (ci culture of an organization; ci deliverables; ci sourcing; ci cycle; ci investment in terms of resources; ci users and ci application) that should be taken into account in ci implementation with regard to the ci level (early, mid, world class). keywords competitive intelligence, maturity model, information, competitive advantage, moroccan companies 1. introduction according to du toit (2003), enterprises today operate in a global market in an increasingly turbulent and volatile environment and must withstand competitive pressures both from other producers or suppliers and from new technologies and products/services, otherwise they will be disrupted. corporate management therefore needs input from competitive information and has to manage and utilize this information. competitive intelligence (ci) pulls together data and information from a very large and strategic view, allowing a company to predict or to forecast what is going to happen in its competitive environment (bose, 2007). journal of intelligence studies in business vol. 8, no. 1 (2018) pp. 25-36 open access: freely available at: https://ojs.hh.se/ 26 despite the increasing interest in ci, two critical gaps emerge in the literature. first, there are few empirical works assessing the maturity of a firm’s competitive intelligence activities. most literature addressing this issue has been focused on the measurement of competitive intelligence in the context of the developed markets of the usa, canada and europe (wright & calof, 2006; gainor & bouthillier, 2014; bose, 2007). the objectives of this paper are twofold. first, a description of the current knowledge regarding the maturity model of ci is derived from the literature. second, the paper makes a contribution to the currently empirical knowledge on the topic, particularly in the moroccan context. the central question that will be addressed is: what are the dimensions of ci involved in the assessment of a ci maturity model? this paper is organized as follows: in the first section, we present the state of the art regarding competitive intelligence and maturity models. then, in the second section, we describe the research methodology. in the third section, we discuss the main results and the important lessons learned from the empirical study. 2. background the literature reviewed for this study includes recent literature on competitive intelligence and ci maturity models. 2.1 competitive intelligence the term competitive intelligence (ci) has been around for about 50 years (luh, 1958; wilensky, 1967). over time, the definition for ci has broadened to include not only organizational and business processes, but also technological processes. for the purpose of this research, and according to gainor & bouthillier (2014), ci is described as the collection, analysis and dissemination of publicly available, ethically and legally obtained relevant information as a means of producing actionable knowledge. actionable knowledge is then a basis for the improvement of corporate decision-making and action. the overall goal of ci is to identify and act upon signals, events and discernible patterns, which can inform and enhance the organization’s decision-making activities (wright et al. 2009). bose (2008) said that the most common benefit of ci is its ability to build information profiles that helps a company to identify its competitor’s strengths, weaknesses, strategies, objectives, market positioning and likely reaction patterns. these information profiles include data needed to effectively identify, classify and track competitors and their behavior. in fact, the assessment of ci is considered an important issue. several scholars have called for research into how ci might be assessed. according to the literature (gainor & bouthillier, 2014; heppes & du toit, 2009), the maturity model can be used to assess the relevance of ci within an organization. the conceptual challenges assessing ci are: understanding what is being assessed, the reliability and validity of the maturity model selected, and how to critically evaluate the maturity of ci. 2.2 maturity models in this section, we will discuss the basic building blocks of maturity models. interestingly, albliwi et al. (2014) mentioned that there is a lack of consensus on the definition of a maturity model, and most of the definitions have only described the capability levels, behaviors and the objectives of the model. accordingly, due to the lack of an accepted general definition, it is necessary to have a closer look at maturity models from three perspectives (wendler, 2012): • an understanding of basic terms like maturity and capability • purpose, application, and benefits • structure and components for becker et al. (2009), a maturity model consists of a sequence of maturity levels for a class of objects. it represents an anticipated, desired, or typical evolution path of these objects shaped as discrete stages. the basic idea behind the maturity model is that higher levels of maturity indicate increased capabilities in managing the specific domain or process with better competitiveness and thus increasing your chance of sustained success. however, if all players are equally benchmarked of course there is no edge or advantage anymore, but then the process becomes imperative just to hold your position among your peers (rapaccin et al, 2013), the concept of maturity models is increasingly being applied within the field of information systems (is), both as an approach for organizational development and as a means 27 of organizational assessment (mettler & rohner, 2009). in fact, we can find many maturity models in the relevant literature. one of the most influential maturity models is the capabilitymaturity model (cmm), proposed in november 1986 by the software engineering institute at carnegie mellon and subsequently evolved into the capability maturity model integration (cmmi). the cmmi is based on knowledge acquired from software-process assessments and extensive feedback from both industry and government (paulk et al, 1993). since then, the maturity model has been expanded into other contexts. moreover, maturity models have been applied to several domains such as business process management (röglinger, pöppelbuß, & becker, 2012), business intelligence (raber, winter and wortmann, 2012), knowledge management (serna m, 2012), supply chain management (lockamy & mccormack, 2004) and social media (geyer & krumay, 2015). table 1 maturity model methodologies. maturity model methodology steps source 1. initial decisions 2. sources analysis 3. strategy for development 4. model design 5. draft model development 6. draft model validation 7. model consolidation salviano et al. (2009) 1. identify problem and motivate 2. define objectives of a solution 3. design and development 4. demonstration 5. evaluation 6. communication peffers et al.(2007) 1. scope 2. design 3. populate 4. test 5. deploy and maintain bruin et al. (2005) 1. comparison with existing maturity models 2. iterative procedure 3. evaluation 4. multi-methodological procedure 5. identification of problem relevance 6. problem definition 7. targeted publication of results hevner et al. (2004) whilst maturity models are high in number and broad in application, there is little documentation on how to develop a maturity model that is theoretically sound, rigorously tested and widely accepted (bruin et al., 2005). in this vein, bruin et al., (2005) proposed, in order to overcome this problem, six phases to develop a maturity model: scope, design, populate, test, deploy and maintain. becker et al. (2009) adopted hevner et al. (2004) design guidelines to formulate the maturity model framework that consists of seven phases: comparison with existing maturity models, iterative procedure, evaluation, multi-methodological procedure, identification of problem relevance, problem definition, targeted publication of results. peffers et al. (2007) proposed a design science process model, which essentially creates a methodology for following the seven guidelines. this process methodology involves six key steps: identify the problem and motivate, define objectives of a solution, design and development, demonstration, evaluation, communication. other authors have attempted to define sequential steps to guide the development of a maturity model. table 1 summarizes the main activities described in each methodology. de bruin et al. (2005) point out that the development of a maturity model depends on the purpose for which a model may be applied including whether the resulting maturity assessment is descriptive, prescriptive or comparative in nature. if a model is purely descriptive, the application of the model would be seen as a single point encounter with no provision for improving maturity or providing relationships to performance. a prescriptive model, on the other hand, provides emphasis on the domain relationships to business performance. finally, a comparative model enables benchmarking across industries or regions. a model of this nature would be able to compare similar practices across organizations in order to benchmark maturity within disparate industries. 2.3 maturity models for ci despite the vast number of applications in different management domains, to the best of our knowledge, no maturity models to assess the capabilities of ci has been developed yet. this paper aims to fill this gap. for these reasons, the maturity model for ci respects the design principles proposed by hevner et al. (2004) in their framework. in the same vein, tej adidam et al. (2012) distinguished three levels of ci maturity: primitive level, intermediate level and advanced level. the first step of the hevner et al. (2004) approach is to review, compare and contrast the existing maturity models in ci. from the 28 literature, we note that heppes & du toit (2009) developed the only ci maturity model. gainor & bouthillier (2014) mentioned that the assessment of ci would need to capture ci usage, the outputs in relation to decisionmaking and decision outcomes. to this end, we propose, according to our literature review, to assess ci practices from eight dimensions that are presented in table 3. table 2 ci maturity model. authors dimensions levels industry heppes & du toit (2009) • deliverables and capabilities • analytical products • relationship with management • sources of information • personnel • skills & training • early stage ci • mid-level ci capability • world-class ci capability retail bank table 3 ci dimensions. ci dimensions source cidim1. ci strategy and culture comai et al (2005), bose (2007), heppes & du toit (2009), oubrich (2011) cidim2. ci relationship with management heppes & du toit (2009) cidim3. ci structure calof (2002), comai et al (2005), bose (2007), heppes & du toit (2009) cidim4. ci resources comai et al (2005), bose (2007), heppes & du toit (2009) cidim5. ci system calof (2002), comai et al (2005), bose (2007), heppes & du toit (2009), oubrich (2011) cidim6. ci deliverables and capabilities heppes & du toit (2009) cidim7. ci analytical products and ci use bose (2007), heppes & du toit (2009) cidim8. ci impact bose (2007), heppes & du toit (2009), seng yap & abdul rashid (2011), oubrich (2011) 3. empirical study 3.1 research methodology we think that ci is still in an embryonic stage in morocco but is widely thought by those in the business to be growing rapidly. however, there are practically no empirical research papers at hand. this paper aims to offer an insight into the assessment of ci and by doing so, to remedy the lack, we noted, of research in the ci field. an empirical research study was developed in order to assess ci in moroccan companies, in terms of the eight dimensions and three levels of maturity (listed on tables 2 and 3). 3.2 data collection ciems research launched between september 2015 and december 2016, the first barometer on ci in morocco, and e-mail, followed by direct contact were used to invite the firms to join our ci research program. the questionnaire was sent to the sample with the objective of evaluating ci in moroccan companies, in terms of the eight dimensions and three levels of maturity. 150 questionnaires were sent, resulting in 57 usable responses (38%). the industry split was information technologies and telecommunications (12.5%), agriculture and fishing industry (8.9%), finance, banking and insurance (8.9%), media and communication (3.6%), construction industry (3.6%), transport and logistic (1.8%), manufacturing industry (1.8%), oil and gas industry (1.8%), with sales reported in excess of 3 million mad by 75%. more than 40% of respondents have a position 29 as senior/middle management, and 10.7% are at director level. moreover, 69.40% of the respondents have experience in ci between 1 and 5 years, and the rest of the respondents, which represent 30.60% have experience in ci for more than 6 years. this shows that ci in morocco is a young field as mentioned earlier. 4. data analysis and interpretation on looking back on the research question posed at the start of this study, it is possible to find the following results and analysis, which show the most common responses from the morocco companies in terms of ci practice assessment in the eight dimensions. 4.1 ci strategy and culture the perceived need for a ci strategy is determined by the intensity of competition in the market serviced by the company. if there are no competitors in the domestic market, there may be no point in wasting resources on ci. the companies that embrace ci are those which experience the most intense competition or where the competitive environment is changing rapidly. the overall goal of ci therefore is to identify and act upon signals, events and discernable patterns, which can inform and enhance the organization’s decision-making activities (wright el al, 2009). in this same vein, ci strategy assessment will depend on the level at which companies respond to change in their business environment and ci practices. according to oubrich (2009), we can distinguish between two types of ci strategy: defensive and offensive. ci defensive strategy includes mainly scanning environment and protection assets; meanwhile ci offensive strategy includes an influence approach. as for the future, there is no doubt that competitive pressure will continue to intensify in all markets. this means that the companies will have to shift their ci strategy from defensive to offensive. the findings of our study revealed that moroccan firms practiced ci at many different levels with regard to the nature and extent of the competition (very intense, intense, not intense). however, when the competition is not intense, the practice of ci is limited to scanning the environment rather than assets protection or influence. as the competition becomes fierce and more aggressive, companies should empower themselves with an offensive ci strategy. 4.2 ci relationship with management the purpose of this dimension is to gain an understanding of the ci activities that take place within organizations and how they are supported by management. according to pellissier and kruger (2011), there is a growing proportion of managers using ci in their strategic planning and decision-making. based on the results obtained, we found that the top management linked ci to protect their intangible assets (24.76%), detection of opportunities and threats (25.52%), coordination of activities (23%) and coordination of strategies (23.08%). moreover, ci helped them to stay informed about the internal and external environment (24.66%), production of new knowledge (23.70%), making better decisions (24.6%) and sale goals (23.81%). finally, the use of ci can lead to innovation (24.48%) and competitive advantages (25.17%). there is also an agreement that ci is clearly widespread across all management levels, as table 4 shows. table 4 management level of respondents. management level % of respondents top management 26.66 strategy department 16.45 marketing department 15.79 r&d department 11.18 commercial department 9.21 finance and administrative department 8.55 sale department 6.58 logistic and distribution department 5.26 export department 1.32 4.3 ci structure the ci system is often influenced by the degree of its formalization. it can be described as a formalized structure when it is governed by rules and procedures (cohen, 2004). the results of this study show that more than half of moroccan companies surveyed admit to having a formalized structure. the structure of their ci system differs depending on the degree of progress of scanning. so, the more the ci structure is developed, the more the ci approach becomes offensive. indeed, the empirical study revealed that moroccan companies with 1 to 5 years of 30 experience in ci, are satisfied with their ci structure. beyond 10 years of experience in ci, the company adopts a proactive ci approach for purposes of influence and lobbying. according to the empirical data, it should be noted that whatever approach is adopted, most companies only hire people with a higher education degree in order to develop their ci structure (80% have a masters’ degree). 4.4 ci resources watchers (martinet and marti, 1996), trackers (lesca, 1997), observers (jakobiak, 1998), and analysts (knauf, 2005), are people in charge of the collection, analysis and dissemination of information to turn it into intelligence in order to have better decisions and actions (bulinge, agostinelli, 2005). therefore, ci professional should have different types of additional skills (salvetat, 2001) such as mastering techniques of acquisition and validation of information sources and analysis, complementary skills related to the management of it tools, and openness and interpersonal skills (gilad, 1986). this survey reveals that the majority of the ci professionals surveyed hold a higher education diploma, most frequently a masters’ or phd. in addition, more than half occupy a managerial function, which reflects that moroccan companies increasingly recognize the level of skills of ci professional. 4.5 ci system hassid et al. (1997) indicate that information collection involves gathering information, identifying available formal and informal sources and analyzing the practical conditions of access and the technical arrangements for better collection. effective environmental scanning must be integrated into several formal and informal sources, both internal and external. formal sources or open sources are those where there is hard support that include the following categories: press, media, books, databases, and patents. informal sources or closed sources mainly reside in contacts with people such as customers, suppliers, competitors, laboratories, and trade fairs. this type of source often requires the mobilization of a multidisciplinary network of human resources inside and outside the company to communicate competitive information (gilad, 1995). the survey reveals that the majority of ci professionals interviewed integrate the web into their scanning panel. the scanning from the ground includes trade show, seminars, and meetings with suppliers. the trend confirmed by this survey is the diversity and complementarity of information channels (web and ground information). 4.6 ci deliverables and capabilities levet (2001), shows that diffusion and dissemination of information to the people involved is an essential step in the ci cycle of martinet and marti, (2001). dumas (2008) proposes a typology of three products of environmental scanning that intended to stimulate reflection and to help decisionmaking. it distinguishes between alert signals (warning alerts), one-off deliverables (briefing notes, scanning reports) and regular deliverables (newsletter, actors mapping). the ci professional should choose the most appropriate support and diffusion of information, and the frequency between a realtime diffusion of information. they should also analyze delayed information dissemination. our study shows that moroccan companies are willing to disseminate information. indeed, email alerts are the best-used channel, followed by newsletters. the companies also rank the presentation and scanning report highly. the findings in this study indicate that the information is not significantly processed by the moroccan structures, and it is still related to punctual consumption. this explains the early stage of the ci practice in the moroccan context. 4.7 ci analytical products and ci use one the most challenging tasks of ci use and ci analytical product methods for the professional is to analyze the information in the dynamic and competitive context as information changes and updates frequently. some research observed that analysis is critical to ci use and ci analytical product methods as it generates some kind of intelligence for the firm (calof and dishman, 2008). tej adidam et al., (2009) make sure that the critical part of the ci process (mainly ci use and ci analytical product methods) is the basis of this analysis and dissemination of intelligence to the relevant firms’ users. therefore, the relevance and quality of this analysis is very important to make effective 31 decisions. it is understood that this relevance and quality are different among ci early level, ci mid-level and ci world-class level (heppes & du toit 2009, tej adidam et al., 2012). we can state that the highest level is the sophisticated analytical techniques, which in turn generate better intelligence output (dishman and calof, 2008) and lead to better ci performance. in line with this, our empirical study shows that where information is transformed into knowledge more efficiently and effectively, companies move ahead to the world class ci practice, and the more they tend to use ci methods such as crosscheck analysis, competition, value chain analysis. however, for the early stage of ci, the companies still use the general methods (such as mckinsy matrix, patent analysis, pestel analysis) to generate intelligence. the mid-level is better developed than the early stage in terms of ci maturity, because they use both general and specific methods (such as value chain analysis and competition analysis). table 5 : ci analytical product methods (in terms of number of occurrences). 4.8 ci impact ci attitudes impact managerial ci and goal setting. different levels and modes (inactive or passive, reactive or proactive; el sawy, 1985; jain, 1984) of ci attitudes have important implications for organizations. this is demonstrated in the fact that while some managers obtain ci passively (what we called the early stage ci level), others (mid-ci level and world class ci level) engage in an active search for ci. opportunities or threats can arise from many different market sectors. managers with a ci high level tend, in a strategic vision, to be engaged in a proactive ci scanning. they rigorously try to scrutinize situational variables and seek opportunities from the market. more specifically, they are engaged to be successful, to control the environment, and to be innovative and create knowledge, have a strong motivation to conduct frequent and regular scanning for ci. between these two kinds of ci attitudes, we identified some managers who are tending to be in the world-class level but still acting only in a tactical way. our findings show clearly that managers in the early ci level are more oriented towards protecting their assets (24.79%), coordinating activities and detecting opportunities and threats in the market. table 6 early ci level data (in terms of number of occurrences). early ci level protect intangible assets detection of opportunities and threats coordination of activities top management 24.79 25.52 23.00 strategy department 15.70 16.55 16.00 marketing department 15.70 15.17 13.00 rd department 11.57 11.03 10.00 commercial department 9.09 9.66 10.00 finance and administrative department 9.92 8.97 11.00 sale department 6.61 6.90 8.00 logistic and distribution department 5.79 5.52 8.00 export department 0.83 0.69 1.00 100.00 100.00 100.00 early level mid-level world class mckinsy matrix 100 value chaine analysis 98 cross-check analysis 37 patente analysis 97 competition analysis 95 competition analysis 33 pestel analysis, 96 swot 93 financial analysis 30 bcg matrix 90 partner analysis 91 value chaine analysis 27 scenario analysis 88 resources and competence analysis 91 scenario analysis 23 resources and competence analysis 74 cross-check analysis 88 partner analysis 21 cross-check analysis 70 pestel analysis, 75 swot 19 financial analysis 67 scenario analysis 72 pestel analysis, 19 swot 65 bcg matrix 70 resources and competence analysis 19 partner analysis 58 financial analysis 67 bcg matrix 16 value chaine analysis 58 patente analysis 57 mckinsy matrix 14 competition analysis 56 mckinsy matrix 42 patente analysis 13 32 table 7 : mid ci level data (in terms of number of occurrences). mid ci level coordination of strategies stay informed about internal and external environments top management 23.08 24.66 strategy department 16.92 16.44 marketing department 14.62 15.75 rd department 11.54 11.64 commercial department 10.00 9.59 finance and administrative department 9.23 8.90 sale department 7.69 6.85 logistic and distribution department 6.15 5.48 export department 0.77 0.68 in the mid ci level, managers have more behaviors that are active in regards to the market and try to move from a passive ci level to a proactive ci level. the world-class ci level shows the importance of a proactive strategy. indeed, the top management, and the strategy and the marketing departments emphasize that ci models help to make better decisions (33%), more innovation (35%) and influence (29%) on the products, services and the activities to generate more sales (25%). in this world class ci level, managers agreed that the ultimate goal is also to create a competitive advantage (37%). 5. conclusion presently, we are unaware of any significant literature about how to define and develop a ci maturity model. the initial research published in aslib proceedings, vol. 61 iss: 1 (du toit & heppes, 2009), discussed the possible conceptual frameworks. based on du toit & heppes, (2009) and the findings of our research, we should look at a variety of different characteristics of a company in order to determine the ci maturity model of an organization. the main dimensions of ci evaluated in this research, are presented as follows: 1ci culture of an organization 2ci deliverables 3ci sourcing 4ci cycle 5ci investment in terms of resources 6ci users and ci application table 9 shows what this ci maturity model looks like, and the increasing levels of maturity. a company progresses from the early stage (basic level) towards the world-class (high level), by increasing its competitive maturity in the eight areas defined above. as a company does so, it also finds that it enjoys an increasing competitiveness and thus increasing influence in a given market. table 9 gives a summary of what one might expect to find for each of the eight evaluation areas (ci dimensions) at each of the different ci levels of maturity. by examining a company’s ci maturity level, dimensions of improvement can be identified that will help companies to move to the next step and increase competitiveness. it becomes a straightforward exercise to evaluate the organization and to identify areas for improvement. table 8 world class ci level data (in terms of number of occurrences) world class ci level making better decision innovation influence generate sale competitive advantage production of new knowledge top management 33 35 29 25 37 32 strategy department 22 23 17 16 24 22 marketing department 21 22 16 15 23 21 rd department 16 17 12 12 17 16 commercial department 13 14 11 10 14 12 finance and administrative department 13 13 13 12 13 13 sale department 9 10 9 7 10 10 logistic and distribution department 8 8 7 8 8 8 export department 1 1 1 0 1 1 33 table 9 ci maturity model. ci dimension early stage ci mid-level ci capability world-class ci capability ci strategy and culture the competition in the business environment is not intense ci practice is only about environment scanning absence of ci structure not able to cope with changes in the business environment the competition in the business environment is intense ci practices are about environment scanning and asset protection absence of ci structure able to cope with changes in the business environment the competition in the business environment is very intense ci practices are about environment scanning, asset protection, and influence existence of ci structure able to drive the change in the business environment ci relationship with management ci output is used by marketing or sale and commercial departments ci output is used by export department ci output is used by top management or strategy department ci structure the age of a ci unit within organization is between 0-5 years scanning environment activity exists ci team has less education (most with less than bachelor degree) and less years of experience the age of ci unit within organization is between 6-10 years scanning environment and protection asset activities exist ci team is composed of people who have bachelor's degrees and fewer years of experience environment scanning, assets protection, and influence activities in existence for more than 10 years ci team has advanced degrees (mainly masters or phd) and several years of experience ci resources ci human resources have less education (most with less than bachelor degree), often lower-level managers ci human resources are composed of people who have bachelor's degrees, often senior/middle managers ci human resources are composed of people who have masters or phd degrees, often top managers ci system few information gathering sources utilized annually several information gathering sources utilized monthly several information gathering sources utilized daily ci deliverables and capabilities the ci process output released annually the ci process output released monthly the ci process output released daily ci analytical products and ci use few analytical product methods and ci deliverables utilized annually several analytical product methods and ci deliverables utilized monthly several analytical product methods and ci deliverables utilized daily ci impact ci impacts operational side of an organization, mainly protection of their assets, coordination of their activities, information about the change in the environment. ci impacts tactical side of an organization, mainly access to new markets, coordination of their strategies. ci impacts strategic side of an organization, mainly allowing companies to make better decisions, create new knowledge on their products, services and processes. we successively analyze the limits of this research in the theory, methodology and the results obtained. from a theoretical point of view, this research raises some key questions related to the use of maturity models as a framework for understanding our research problem. however, the maturity models did not describe the processes themselves; they describe the characteristics of good processes, thus providing guidelines for companies developing their own sets of processes. according to our empirical study, ci in morocco is still a relatively young practice, therefore, it is very hard to assess the companies concerning levels of the maturity models described in this paper, and that is why our sample was very small. the size of this sample was insufficient for the research purpose, and did not allow us to draw generalized conclusions, but it can be considered representative of all moroccan companies. in the same vein, as most companies did not respond to our questionnaire for confidentiality reasons, there was no real strategy for the choice of companies. the findings of this paper indicate that further research related to competitive intelligence maturity models can be conducted. for instance, future 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"competitive intelligence in practice: empirical evidence from the uk retail banking sector", journal of marketing management, 25(9/10), 941-964 wright, r. eid, fleisher (2009), "competitive intelligence in practice: empirical evidence from the uk retail banking sector", journal of marketing management, vol. 25, no. 9-10, pp. 941-964. page 4 editors note vol 6 no 1 editor’s note vol 6, no 1 (2016) the width and scope of intelligence studies in business if the last issue of jisib was a special issue where the discipline was reflecting on itself, then this issues shows some of the width and scope of the field. the conceptual article by nienaber and sewdass presents a relatively new concept of workforce intelligence, and links it to competitive advantage by way of predictive analytics. the article by solberg søilen is an attempt to lay out a broad scientific agenda for the area of intelligence studies in business. empirical findings come from a survey, but in the discussion the author argues for why the study should define itself as much broader than what the survey data implies, breaking out of the current dominating scientific paradigm. the article by fourati-jamoussi and niamba is an updated evaluation of business intelligence tools, a frequently reoccurring topic. however, this time it is not a simple evaluation of existing software, but an evaluation by users to help designers of business intelligence tools get the best efficiency out of a monitoring process. the article by calof is an evaluation of government sponsored competitive intelligence for regional and sectoral economic development in canada. the article concludes that it is possible to calculate positive economic impacts from these activities. rodríguez salvador and hernandez de menéndez come back to a field that has become a specialty for rodríguez salvador: scientific and industrial intelligence based on scientometric patent analysis. this time she looks at bio-additive manufacturing using advanced data mining software and interviews with experts. as always, we would above all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2016 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 6, no 1 (2016) p. 4 open access: freely available at: https://ojs.hh.se/ jisib-vol-12_nr-3(2022).pdf journal of intelligence studies in business vol. 12 no. 3 (2022) open access: freely available at: https://ojs.hh.se/ pp. 4–5 ai-driven competitive intelligence: enhancing business strategy and decision making in the world of business, the importance of competitive intelligence cannot be overdone. as companies compete for market share and seek to gain an edge over their competitors, understanding the market and their competition becomes increasingly critical. as artipotential to impact competitive intelligence grows. companies can use ai to automate data collection and analysis, allowing them (krakowski et al.2022). ai can also be used to analyze competitors’ online activities, includand search engine rankings. this allows companies to stay up-to-date with their competition and respond quickly to changes in the market. in this issue, authors will explore the role of competitive intelligence in an ai world, examine practitioners’ thoughts on technological advances and the educational needs of their intelligence on the hiring process. the use of is becoming increasingly popular in competitive intelligence. these technologies can be used to automate data collection, analysis, cient and accurate. there is also a discussion intelligence in education research, the effect of marketing intelligence adoption on enhancintelligent trading strategies, including interacting trading strategies based on an agentbased approach. as technological advances continue to change the competitive intelligence landscape, practitioners must keep up with the latest developments to remain effective. they must also ensure that their successors are prepared to succeed in an increasingly technology-driven world. this requires ongoing education and training in areas such as data analysis, ai, and machine learning. ai is also changing the hiring process, allowing companies to use data-driven approaches to identify and recruit the best candidates. ai can be used to analyze resumes, evaluate candidate responses to interview questions, and even predict a candidate’s future job performance. this allows companies to make more informed hiring decisions and reduce the risk of hiring the wrong person for the job. marketing intelligence can also play a critiin the case of banks, marketing intelligence can be used to identify new opportunities for growth and optimize their marketing efforts to reach the right customers. this can help banks petitive advantage in the market. are also becoming more intelligent. an agentbased approach involves using ai to create a model of the market and simulate how different trading strategies would perform in that market. this allows traders to identify the most effective strategies and improve their trading performance. in conclusion, the impact of ai on the busigrow. competitive intelligence, in particular, practitioners must stay up-to-date with the latest technological developments and ensure that their successors are prepared for an increasingly technology-driven world (cekuls, 2022). ai is also impacting the hiring process, education research, marketing intelligence, and trading strategies, highlighting the need for ongoing education and training in these and other areas (stroumpoulis et al, 2022). by embracing these technological advances, editor’s note vol 12. no. 3 (2022) 5 companies can gain a competitive advantage and improve their overall performance in the market. references cekuls, a. (2022). expand the scope of competitive intelligence. journal of intelligence studies in business, 12(1), pp. 4–5. and big data analytics in smart tourism: a resource-based view approach. wit transactions on ecology and the environment, 256, 2022, pp. 99–108. krakowski, s., luger, j., raisch, s. (2022) es of competitive advantage. strategic management journal, 2022. on behalf of the editorial board, prof. dr. andrejs cekuls university of latvia, latvia jisib-vol-12_nr-2(2022).pdf 51 applying patent analysis with competitive technical intelligence: the case of plastics marisela rodríguez salvador and mario alberto tello bañuelos instituto tecnológico y de estudios superiores de monterrey (itesm), campus monterrey, eugenio garza sada 2501, monterrey, mexico marisrod@itesm.mx received 15 march 2012; received in revised form 30 april 2012; accepted 30 april 2012 abstract: this article presents a methodology that integrates patent analysis in a study of competitive technical intelligence. our approach was applied in the area of plastics. we identified areas of research, leading companies and technology trends. keywords: competitive technical intelligence, innovations, patent analysis, plastics, thermoplastic elastomers 1. introduction the oil crisis of 1974 influenced the increase in consumption of plastics, especially in the automotive industry. plastics have allowed to decrease the weight of automobiles, which have had a significant impact for example on savings in fuel consumption per kilometer. among the polymers used to reduce the weight of automobiles are polyesters, polypropylene, polyvinyl chlorides, polyurethanes, polyethylene, abs (acrylonitrile-butadiene), nylon (feldman, 2008). within this area the level of technological development is very fast so it is required to be available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 51-58 https://ojs.hh.se/ 52 continually on the lookout for events arising in the environment, for example, development of new technologies, materials, etc. this is the case of thermoplastic elastomers, which are characterized by having the elastic behavior of rubber and thermoplastic processing. in fact it has become the fastest growing segment of the polymer industry, so they are considered a great business opportunity (kear, 2003). in mexico, in the city of monterrey (state of nuevo leon) the main campus of the instituto tecnológico y de estudios superiores de monterrey (itesm) is located. within this institute the unit of competitive technical intelligence (center of quality and manufacturing) provides training, consultancy and research in that area. in 2011 a collaborative project between a mexican company and the itesm, campus monterrey, was implemented. initially this project was linked to that company, which was interested in the area of thermoplastic elastomers. at the beginning of the project, the topic was focused on alternative monomers to styrene, butadiene and/or isoprene, preferably from renewable sources. the general statistical results of that topic, based on the software matheo patent’s results, were presented to the company. after that a strong reorganization from the headquarters of the company was made and this company was closed. we decided to continue with our methodology and to undertake a general study on plastic, considering patent analysis in the topics of thermoplastic elastomers and styrene, butadiene and isoprene. the main goal was to identify technology trends that could allow to determine opportunities, including the identification of leading companies and their main areas of research. 2. competitive technical intelligence and patent analysis competitive intelligence is rooted in three areas: governmental intelligence agencies, management studies and market research (michaeli, 2006, cited by schwarz 2007). while it is true that competitive intelligence had its beginnings in the 70s, it was until 1980 when michael porter laid the foundations of this discipline in his book competitive strategy: techniques for analyzing industries and competitors. this discipline denotes an apparent novelty in latin america, but is widely used by major multinational companies, in 2001, according downham et al, cited by medina lugo (2008), over 82% of companies with revenues in excess of usd $10 000 million had an intelligence system, while 60% of those earning over usd $1 billion also had some practices of intelligence. in the mid’s 80’s in the united states the strategic and competitive intelligence professionals, scip, was established. the organization is a leading professional association dedicated to the study of competitive intelligence in the world. according to scip homepage (2011), competitive intelligence is "the process of monitoring the competitive environment and analyze the findings in the context of the problems specific to each company in order to provide support in decisionmaking." in this context we shall define competitive technical intelligence (cti), as the process focused on monitoring the competitive and technological environment of an organization, that supports decisions, especially those related to market, innovation, product design, and research and development (r & d). cti is carried out in organizations of all sizes through a continuous and systematic process that involves legal and ethical collection of information, analysis relevant conclusions, and the collection and controlled dissemination of useful results. by means of this process it’s possible to identify opportunities and threats in the environment for strategic planning processes (adapted from the scip, 2011). cti is applicable to various types and sizes of organizations to determine business opportunities, information on specific products and services from competitors, threats, etc. innovation can be achieved by cti. innovation is commonly defined as the beginning of an idea in relation to a product or process that is new for a specific company. however, innovation is the successful exploitation of new ideas: it therefore requires of two conditions: the novelty and use (alegre, chiva & lapiedra, 2009). in this context patent data are an important source of competitive intelligence that companies can use to gain strategic advantage (shih, liu & hsu, 2010). for several years patents have been considered as indicators of technological progress. through patent analysis it is possible to identify among 53 others issues: areas of technological specialization, company profiles, institutions involved in research, technological activity by countries and collaborative networks (rodríguez, 2003). moreover, the usefulness of patents has been demonstrated as a support of strategic planning for products and processes (lozano, 2003). in order to carry out the analysis of large volumes of information the field of scientometrics represents a valuable alternative. this is defined as the set of studies to quantify the process of written communication, the nature and evolution of scientific disciplines / technologies by counting and analysis of various characteristics of the communication (amat, 1994 cited by rodríguez 2003). also using analysis of co-occurrence (cooccurrence of words), with advanced techniques such as mapping technology it is possible to identify the behavior of business or technology areas in a specific field and period of time, and thereby identify opportunities and threats to innovation. patent information can be found in different databases, some of them are:  uspto patent database full text and images, united states  esp@cenet database of epo (european patent office)  google patent patent database from uspto  patentscope database of international patent applications wipo (wipo)  depatisnet database of german patent  ajp database of the japan patent office  dwpi derwent world patents index patent database from thomson reuters the use of specialized software makes patent analysis easier. one of the most recognized software in the field of patents is matheo patent from france. through this program is possible to access uspto and espacenet databases and monitor technology. we applied this software in plastics, including thermoplastic elastomers. in this area the level of technological development is very fast because of events arising in the environment including, development of new technologies, materials, etc. 3. the case of study thermoplastic elastomers (tpes) are a class of polymers within their design limits, they behave like thermoset rubber but above its melting point or softening temperature, they could be processed by thermoplastic methods with the advantage that unlike thermoset rubber, tpes can be easily reworked and remodeled. the ability to transform these materials with thermoplastic methods allows freedom of design and manufacturing that thermoset rubber does not offer (rtp, 2011). all tpes are composed of amorphous and crystalline domains. some of them are mixtures or alloys of crystalline and amorphous polymers; some are block copolymers comprising blocks of crystalline and amorphous domains along the same polymer chain. it is important to mention that the crystalline domains provide to tpes the character thermoplastic and amorphous domains give them the elastomeric character (rtp, 2011). the crystalline domains are usually known as the phase "hard" and the amorphous domain as phase "soft." although both phases contributes to the general properties of a physical and mechanical tpe, some key properties may be associated with one stage or another which guides the selection or design of a compound of tpe. as we have established before tpes can be processed as thermoplastics imitating the performance of thermoset rubbers, for this reason tpes have become the category of plastics with the most growth during the last 10 years (grande, 2008). among the main drivers of market growth of tpes are: simplified processing with fewer manufacturing steps, virtual elimination of scrap, considerably shorter cycles, lower power consumption, and lower costs per volume due to the low density of most tpes (drobny, 2007). the faster processing and low rates wastes have made tpes a niche market that continually expand in markets such as automotive, medical and consumer products (grande, 2008). in this respect, we applied patent analysis in a competitive technical intelligence process as a method to monitor the technology. 4. integration approach based on the competitive intelligence methodology proposed by escorsa & rodríguez (2000), a synergic model was designed, as shown in figure 1. 54 figure 1. method of competitive technical intelligence with patent analysis. the objective was to identify trends through patent analysis within thermoplastic elastomers area. in the subsequent paragraphs, we present a brief explanation of the development of each step, including insight obtained from the implementation of the method proposed above. 5. the methodology even though this study refers to plastics, including market information, it is important to mention that the patent analysis was focused in thermoplastic elastomers along with styrene, butadiene and isoprene. this study covers two approaches: the market approach and the technological approach one. the market approach covers market information related to chemical industry and their key companies participating in the plastic segment. on the other hand, the technological approach refers to patent analysis of in thermoplastic elastomers along with styrene, butadiene and isoprene. it also covers statistical patent data regarding plastics and thermoplastic elastomers. a. planning in this step was established the objective, time and resources. matheo patent was applied to develop the patent analysis. b. selection and gathering of information in this study, first a general search was conducted on the topic of plastics in order to get an idea of the number of patents published in recent years. this general search was carried out by uspto with the purpose of getting a high enough number of patents, to have an idea related to the progress in this field. espacenet required much more time in the process of downloading (more than 20 hours). this can complicate the analysis process. the period selected was 2000-2012. the result was a total of 5446 patents, 6535 inventors, 2519 applicants, 445 ipc 4 digits (international patent classification) and 6132 ipc (full digits). the chronology of the patents, identified is shown in figure 2. figure 2. chronology of patents issued about plastics, 2000-2012. source: data from uspto and matheo patent. a general search for thermoplastic elastomers was made with the same purpose using the uspto database and taking into account the 2000-2012 period of time. the result was a total of 1531 patents, 2038 inventors, 2519 applicants, 223 ipc 4 digits and 1948 ipc full digits. the chronology of the patents is shown in figure 3. figure 3. chronology of patents issued about tpes, 2000-2012. source: data from espacenet and matheo patent. 55 subsequently, we made a research of patents on thermoplastic elastomers and styrene, butadiene and isoprene. the espacenet database did not require a lot of time for downloading for this search. using the database in the period 20002012 the result was a total of 477 patents, 811 inventors, 352 applicants, 68 ipc 4 digits and 507 ipc full digits. the main ipc (4 digits) obtained was c08l which refers to compositions of macromolecular compounds. however, in order to apply a deep analysis of the main applicants, a group was created from the applicants with the highest amount of patents (top 5). this group was integrated by the following organizations:  michelin soc tech  michelin rech tech  mitsuboshi belting ltd  toray du pont kk  polyone corp according to this group, there are different ipc 4 digits related to all applicants, where ipc c08l has the highest amount of patents. the ipc refers to compositions of macromolecular compounds. regarding the ipc of full digits, all applicants are involved in the following, as shown in figure 4. figure 4. description of ipc full digits related to applicants involved. source: data from espacenet and matheo patent. a search regarding the keywords styrene, butadiene and isoprene in the abstract of the patents was then made. as a result we observed that the keyword styrene was related to 50 patents, butadiene to 15 patents and isoprene to 21 patents. moreover, all of these keywords were related among them to the following ipc (4 digits), as shown in figure 5. figure 5. description of ipc 4 digits related to keywords styrene, butadiene and isoprene. source: data from espacenet and matheo patent. c. analysis information i. market approach the global market for chemical products grew by 7.6% in 2010 to reach a value of usd $ 706,312.5 million. the compound annual growth rate of the market in 2006-2010 was 3.3% (datamonitor, 2011). this market is characterized by low product differentiation; the barriers to market entry are in addition the necessary capital to establish facilities and strict regulations that increase rivalry. in figure 6, we can see the influential five forces on this problem. figure 6. five forces driving the global market of chemical products. source: datamonitor, global specialty chemical (2011) 56 in the chemical industry there are several companies involved in the plastics sector, leading companies globally in this category are:  basf  the dow chemical company  ineos  lyondellbasell industries under this approach, information regarding the previous companies was gathered in order to apply the analysis of porter’s five forces, as shown in figure 7. figure 7. five forces of the main competitors driving the market of plastics. according to figure 7, there is a strong rivalry between the companies in the plastics industry; the economies of scale contribute with the growth of the multinationals in this industry, followed by a considerable capacity of buyer power. the forces concerning the entry of new firms and the supplier power are considered moderate, as greater product differentiation between firms is required. in addition, there is a small threat of substitute products. moreover, all of the companies analyzed have a strong activity in the area of polymers through their subsidiaries or business segments. ii. technology approach the main applicants as well as the keywords: styrene, butadiene and isoprene; are linked to the ipc c08l (compositions of macromolecular compounds). based on this ipc analysis, four trends were identified. these trends are detailed with information related to the main applicants involved, amount of patents, abstract of some relevant patents, as follows: trend 1: compositions of block copolymers containing at least one sequence of a polymer obtained by reactions only involving carbon-to-carbon unsaturated bonds; compositions of derivatives of such polymers: of vinyl aromatic monomers and conjugated dienes. figure 8. description of elements related to trend 1. trend 2: compositions of homopolymers or copolymers of unsaturated aliphatic hydrocarbons having only one carbon-to-carbon double bond; compositions of derivatives of such polymers, as illustrated in table below: 57 figure 9. description of elements related to trend 2. trend 3: compositions of oils, fats or waxes; compositions of derivatives thereof, as illustrated in table next: figure 10. description of elements related to trend 3. trend 4: compositions of polyesters obtained by reactions forming a carboxylic ester link in the main chain; compositions of derivatives of such polymers. figure 11. description of elements related to trend 4. 58 6. conclusions through the patent analysis it was possible to identify the main actors in the subject matter, as well as their areas of research. the trends were identified according the ipc c08l; this ipc was related to the main applicants (michelin soc tech, michelin rech tech, mitsuboshi belting ltd, toray du pont kk, polyone corp) and the keywords: styrene, butadiene and isoprene. our proposal provides results from both points of view of technology and the market; the results obtained can contribute in the future to identify opportunities. the method can be applied to any subject that considers patents as a source of strategic information. the proposed method considers a global analysis on the plastics industry, covering both market information and the leading companies. the analysis of porter’s five forces were incorporated into the stage of the analysis with good results. references alegre, j.; chiva, r.; lapiedra, r. 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(2010). discovering competitive intelligence by mining changes in patent trends. expert systems with applications, xxxvii(4). issn: 2001-015x v o l 4 , n o 2 ( 2 0 1 4 ) c o n t e n t s christophe bisson exploring competitive intelligence practices of french local public agricultural organisations pp. 5-29 o p i n i o n s e c t i o n najibeh abbasi rostami integration of business intelligence and knowledge management – a literature review pp. 30-40 pierre memheld intelligence analysis and cognitive biases: an illustrative case study pp. 41-50 abdelkader baaziz, luc quoniam patents used by npe as an open information system in web 2.0 – two mini case studies pp. 51-60 klaus solberg søilen a survey of users’ perspectives and preferences as to the value of jisib a spot-check pp. 61-66 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: prof. dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2014 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india associate professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain associate professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, hedin intelligence & strategy consultancy, sweden javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/22') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/23') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/24') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/25') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/10') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/12') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, november 10 2014 e d i t o r i a l n o t e v o l 4 , n o 2 ( 2 0 1 4 ) like in the previous issue we have admitted a large number of opinion pieces, first of all in the form of case studies but also reviews and a survey. it is quite fitting that we present two articles with cases as case studies have been requested in a recent surveys from users of the journal. the first article by christophe bisson shows ci practices at a french regional chamber of agricultura with four departemental chambers of agricultura linked to it. a survey was used to detect seven typological strands (gathering, attitude, technology support, it systems, use, location and identification). the paper finds that current practices are ineffective, inefficient and far from attaining goals for collective intelligence gathering. the second article by najibeh abbasi rostami is a literature review of the bi and km fields. in a previous issue we have discussed the relationship between ci and km. rostami presents the differences in the form of a number of models and summaries found in the existing literature. the articles conclude, not unexpectedly, that the literature clearly shows that a proper integration of the two functions are beneficial to organizations. more interesting the review also concludes that studies are needed to show how cultural aspects affect this dichotomy. the third article, the second opinion piece, is a case study by pierre memheld. the article illustrates a critical ci lesson through the use of a case presenting two major tire manufacturers troubled by a price war. the article argue that intelligence failures can be caused by particular biases which may be culture related. the fourth article by abdelkader baaziz and luc quoniam is a discussion around “patent trolls” and non practicing entities (npe). the article is illustrated with two examples, or mini cases, from the pharmaceutical industry in two emerging countries. the article shows how the use of web 2.0 technologies makes it easier to extract useful intelligence from patents. the last article by klaus solberg søilen entitled “a survey of users’ perspectives and preferences as to the value of jisib a spot-check” show what users want from the journal jisib. it concludes that more cases studies are requested, but it gives no credit to those who think there is too much or too little technology related material as opinions on this issue are balanced. a number of minor suggestions are presented and the survey shows that the question of editing language is not settled. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen editor-in-chief halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 18 a new evaluation model of erp system success abdesamad zouine 1 pierre fenies 2 1 crcgm université d’auvergne, france 2 ceros, paris x nanterre, france email: zouine.abdessamad@gmail.com received march 10, accepted may 12 2015 abstract: this article presents a literature review about the success evaluation in the information system, and proposes a new evaluation success model suited to the erp software. in the first part we present approaches, frameworks and models of the evaluation success previously used and empirically validated by researchers in the is field. then, we present our evaluation success model, highlighting its three main theoretical foundations: mathematical theory of communication, diffusion of innovation theory and adaptive structuration theory in the one hand, and we expose the main construct of this model named the esf (evaluation success factors) on the other hand. these factors are classified in three categories: technological, environmental and organizational evaluation factors. this work analyses articles published in the last decade about the success evaluation and delineates ten esf’s widely used to evaluate the success of the erp system project. keywords: erp system, success, evaluation approaches, evaluation success factors. available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 1 (2015) 18-39 mailto:zouine.abdessamad@gmail.com https://ojs.hh.se/ 19 1introduction the beginning of the 90’s was characterized by the emergence of erp system, considered as one of the most important information systems software and the most expensive information technology project. the investment in this kind of project is under increasing scrutiny and pressure to justify their value and contribution to the performance, quality, and competitiveness of organizations (gable et al., 2003). currently, and after approximately two decades, all the largest business companies are now equipped with the erp system in order to follow the environment change and business development. the integration of this project is considered as one of the most important challenges for the top management, project manager, erp consultant and vendor at different levels of the organization. the erp integration requires large investment, and it is associated with many problems in the implementation phase (markus and tanis, 2000). despite the substantial investments made by organizations, its success had been minor (davenport, 1998; davis, 1989a; gable et al., 2003; sedera and gable, 2010). in the literature review, many theoretical researches attempt to develop models to evaluate the information systems success. however, these models are not entirely appropriate for measuring erp system success (gable et al., 2003) for many reasons such as the specificities of the erp system, its characteristics, and the complexity of implementation process. organizations must support and manage the change introduced by the erp system, because its integration needs an important reorganization and transformation in the business process, at both strategic and technical level. in many cases, this resistance is considered as a major risk of erp project implementation. before the evaluation of the erp system, a framework has to be fixed and take into consideration the characteristics of the system. however, the context should dictate the appropriate specification and application of the erp system (delone and mclean, 2003, 1992). although, many success variables are proposed by researchers to evaluate the erp success and attempt to explain the causal and the process model adapted to propose their constructs and measurement variables. this question about the causal and process model has been discussed in the literature about the is evaluation. the process model suggests that an is is first created, containing various features, which can be characterized as exhibiting various degrees of system and information quality. in contrast, a causal model studies the covariance of the success dimensions to determinate if there exist a causal relationship among them (delone and mclean, 2003). to evaluate their information systems, organizations require appropriate methods and tools; (irani, 2002; uwizeyemungu and raymond, 2010) propose a new qualitative method for the ex-post evaluation of erp system based on one hand on the organizational performance, and on the other hand on the automationed, informational and transformational effects that result from the integration and the use of the system. their approach is based on a process model that takes into account at the same time practitioners’ dimension of evaluation, and researchers’ conception of evaluation that also can take two faces: qualitative or quantitative approaches of information system evaluation (irani and love, 2008). this phenomenon of is evaluation is complicated and multifaceted; it must be examined from many perspectives (song and letch, 2012) and take into account different stakeholders involvement (irani and love, 2008; irani et al., 2014; stefanou, c.j., 2001). according to the erp evaluation success, a new framework of ex-ante evaluation was proposed by (stefanou, c.j., 2001) to evaluate the erp system. this framework includes in the same time behavioral, technological and organizational perspective to evaluate the erp software which is considered as a complex system (irani, 2002; stefanou, c.j., 2001). this step of success evaluation could be classified in the pre-implementation phase of the erp integration process. it takes into account the selection process of the appropriate erp software and all variables and criteria to select the most suitable one. the process of selection based on the one hand on both financial and non-financial approach and on the other hand it combines qualitative and quantitative measures (stefanou, c.j., 2001). relating to life-cycle product, the evolution of erp integration process follows three phases: preimplementation, implementation and postimplementation. however, in this study, we include both ex-ante and ex-post evaluation in to erp success evaluation model because the evaluation is considered as a process that involves all esf (evaluation success factors) throughout the erp life-cycle. this research paper will start with a presentation of the literature review about the different frameworks, models and approaches discussed by searchers in the is evaluation success (davis, 1989b; delone and mclean, 2003, 1992; gable et al., 2003; ifinedo and nahar, 2006; irani and love, 2008; kaplan and norton, 1992; rosemann and wiese, 1999; seddon, 1997; tsai et al., 2006) then, it will expose theoretical foundations based on three main theories: firstly, the mathematical theory of communication (weaver and shannon, 1949) used by delone and mclean to develop their model about information success to explain the three levels that must be taken into account to evaluate is success (technical level, semantic level and effectiveness level). secondly, the diffusion of innovations theory (rogers, 1983) mobilized by (bradford and florin, 2003) to explain the role of the diffusion of innovation on the erp implementation success that will be used to involve and classify three principal factors in the conceptual 20 model: technological; organizational and environmental. thirdly, the giddens’ theory of structuration (1984) to explain the interaction between the variables (factors) and the performance in three levels: individual workgroup and organizational performance. in the second part, we expose our conceptual model and highlight the principal evaluation success factors identified in both theoretical models and empirical studies. after that, we will explain how these esf’s are classified taking into account the theoretical background in order to justify our conceptual perception. 2literature review about approaches, models and frameworks of erp success this part focuses on the literature review on the research in is success to summarize both theoretical backgrounds and empirical studies. the presentation will be chronologically respected in terms of frameworks, models and approaches developed in the is field. then, we will focus our attention on erp as the main subject of this study. a review of different measurement approaches about the erp success evaluation will be discussed to highlighting the importance of the measure in the information system and particularly the erp software. 2-1frameworks of erp evaluation success: developing a framework is the first step in the evaluation success that must be appropriate to the features of the information system (chand et al., 2005; irani et al., 2014; stefanou, c.j., 2001; uwizeyemungu and raymond, 2010) many frameworks have been proposed taking into account several phases and dimensions of evaluation system success: strategic, tactical and operational levels. generally, the framework explains eight categories: theoretical foundation, research approach, the object of analysis, unit of analysis, evaluation perspective, data gathering, data analysis and the methodology type (urbach and smolnik, 2008). 2-1-1 the ccp framework: a ccp proposition could be considered as an important framework to assess the success of erp system because this framework integrates three major dimensions of evaluation: content, context and process (irani and love, 2008; irani, 2002; song and letch, 2012). this new approach of evaluation answers three main questions: firstly, what is being measured (content) based on a socio-technological paradigm? secondly, why and who of is evaluation to be considered (context)? and thirdly how will it be undertaken?. many instruments could be used to answer this question like, cost benefits, roi (return on investment), user satisfaction that could be classified as an objective or subjective evaluation approach. this framework has been developed by (irani and love, 2008; irani, 2002) to assist the managers and the decision makers in the process of the benefits evaluation of the it/is. they argue that there is not a good framework for assessing the impact of is in the organization performance in the literature review and they added that there is no good framework for selecting the appropriate tools for is investment. for these reasons, they try to propose a ccp framework to assess the cost and benefits of is based on three constructs: content, context and process. but we conclude after analyzing this framework that it is too large and general to be applicable to assess the success evaluation of the erp system. 2-1-2stefanou’s framework: another framework for the evaluation of the erp system is developed by (stefanou, c.j., 2001). it focuses on the pre-implementation phase. this framework named “ex-ante evaluation of erp” assesses the selection process of erp system and takes into account the complexity and the features of the erp system. both financial and non-financial approaches for erp evaluation have been included in this framework. the financial approach is a traditional one used by the professionals to evaluate their is success based on some financial indicators such as: return on investment, return on sales, cash flow, sales growth, inventory turnover, inventory level, operating income, asset utilization, capital budgeting, market share and shareholder value (tsai et al., 2006). in contrast, in the case of erp project, these financial indicators are not always reliable to assess the erp impact because the benefits and the costs are not precisely identifiable, and they are not easily quantifiable (stefanou, c.j., 2001). the second approach adopted by some researchers to evaluate the erp success is based on a qualitative or subjective method that takes into consideration the intangible benefits such as: individual impact, learning and growth, consumer satisfaction, and the work group impact (gable et al., 2003). 21 stefanou’s framework consists of four phases: the first one considers the business vision as a point of starting for erp integration. the second phase examines the business needs and the capabilities of the company to support and fit with the erp system. the third phase requires the estimation of the costs and benefits for erp system integration. the last phase refers to the analysis of issues involved in erp operation, maintenance and evolution. table 1: the potential costs and benefits associated with erp life-cycle phases. (stefanou, c.j., 2001) phases of erp life cycle estimation of potential tangible and intangible costs, benefits and risk involved in each phase phase 1: business vision risk associated with non-clarification of business vision and blurred business goals phase 2a: comparing needs versus capabilities and constraints phase 2b: erp selection technological, organizational, human resources and financial capabilities and inefficiencies. commitment to continuous change costs/ benefits/risks associated with all-in-one or best-of-breed software options costs/benefits associated with issues costs involved in the selection process phase 3: implementation project replacing of legacy systems consulting fees users training implementation approaches implementation partners completion time phase 4: operation, maintenance and evolution continuous re-engineering software upgrades additional functionality benefits from erp maturity both operational and strategic erp users satisfaction partner/customers satisfaction business vision erp selection erp implementation erp operation/ maintenance/ evolution capabilities/ constraints evaluation of cost, benefits, risks: strategic-operational. estimation of roi/value/business case of erp phase 1 requirements phase 2 phase 3 phase 4 figure 1: major phases of erp life-cycle (stefanou, c.j., 2001) analysis 22 depending on the life-cycle approach developed above, a new proposition based on supply chain could be used to understand the different erp project stakeholders. this approach of erp success includes all the partners that operate in the integration process. this supply chain of the erp success is based on three principal parts: firstly, the organization that considered as a client or customer; secondly the software vendor (vanilla erp); thirdly the company of consulting or the integrator. the collaboration between all the different partners in the value chain is necessary. this alliance is one of the strategic benefits of the erp implementation (shang and seddon, 2002). in this supply chain, the product is the erp software, the consumer is the organization that will integrate it, and the external partners are the companies specialized in the erp integration. but the question that arises here is: which are the parts that contribute in the success or the failure of the erp system project? analyzing this question from a scm approach which considers the erp as a product will be significant to determine the contribution of every partner in the erp success. the quality of the product is one of the most important esf in the project; in this case the quality of the product means the quality of erp system. many measures are proposed to assess this quality such as: response time, convenience of access, realization of user requirements, correction of errors, security of data and models, integration of system, flexibility of the system, system efficiency, database contents, data currency, system accuracy and data accuracy (delone and mclean, 1992). both vendor and consultant quality in terms of competencies is positively related to the erp success (ifinedo and nahar, 2006). some researchers consider this factor as an exogenous factor required in the erp process success because all the partners came from the external environment. in the literature review about the erp success evaluation, many studies include the vendor and consultant quality as an independent variable in their models to assess the erp success (bernroider et al., 2014; ifinedo and nahar, 2006; tsai et al., 2012; wang et al., 2008; zhu et al., 2010). some researchers found a significant and positive correlation between the vcq (vendor/consultant quality) and the success of the erp system and they argue that it is important to take into account the competencies both strategic and technical of the partners in erp system integration. the technical and knowledge transfers to the organization by the vendor and consultants are necessary to enhance the efficiency and the effectiveness of the erp system in all phases of the project integration. for example, after the process of erp system selection, the vendor transfers all the information about functionalities of the system, degree of customization, the functional coverage and other information supports to help the organization in the selection process. combining both vendor and consultant in one factor is necessary because they are considered as an external source of expertise to the organization. (ifinedo and nahar, 2006; sedera and gable, 2010) found that vendor and consultant quality built a single factor “knowledge management competencies”. the company that integrates an information system faces several starting conditions, according to competitive position, industry, financial position, size and structure (markus and tanis, 2000). however, these conditions may not be sufficient to explain clearly the success or the failure of the erp system, but they have two principal impacts on enterprise system experience. firstly, the strategic goals and plan may not be adapted to the erp system specificities, this strategic alignment or fit will may be a problem for the organization in some cases. secondly, the customization of the system could be necessary in many cases, that it means, starting conditions may not stay the same over the erp experience (markus and tanis, 2000). erp supplier (erp editor) erp integrator (consulting company) organization (client or consumer) erp success figure 2: process of the erp success 23 2-1-3soh and markus framework: the ultimate goal of (markus and tanis, 2000; soh and markus, 1995) works is to create a new framework that enables a better understanding of the concept of ess (enterprise system success). answering these questions: how companies can succeed the integration of this technology? and what can be done to improve the chance of success? authors define the success outcome as a multidimensional concept, a dynamic concept, and a relative one (to the concept of “optimal success”, representing the best an organization can hope to achieve with enterprise system). p. 184. the success can be defined by (markus and tanis, 2000) in terms of implementation project, or in terms of business results. the first definition answers the question: did the company succeed in getting the system up and running within some reasonable budget and schedule? the second answers the question: did the company succeed in realizing its business goals for the project? based on the mergence process theories because (markus and tanis, 2000) consider that these theories combine both goals and actions with external forces and chance. they build their framework on a particular emergent process theory designed by (soh and markus, 1995) to explain how the enterprise system as a technology creates business value in organizations. 2-2models of erp system success measurement many models have been developed to evaluate the systems and technology’s success (davis, 1989b; delone and mclean, 2003, 1992; gable et al., 2003; ifinedo and nahar, 2006; sedera and gable, 2010; shang and seddon, 2002). these models have been validated empirically by many studies in information system. the results show that many case studies are investigated by applying the delone & mclean is success model by using a structural equation modeling method (dörr et al., 2013). however, these models assess the success in three levels of impact. the first one is an individual impact (davis, 1989a) that sheds light on the users’ behaviors. the second level is the group impact (gable et al., 2003; sedera and gable, 2010) interesting on the workgroup and its influence on the performance, and the third one is an organizational impact (delone and mclean, 1992). although one model could assess more than one level of impact, for example, delone and mclean model take into account two levels of impact, individual and organizational performance. (gable et al., 2003; ifinedo and nahar, 2006; sedera and gable, 2010) in their models about the erp measurement success, they take into account three levels of impact, individual impact, workgroup impact and organizational impact to assess the success of erp system. and finally davis in his model of the technology acceptance model tam, takes into account one level; the individual impact to assess the user perception and behavior. 2-2-1technology acceptance model tam (davis, 1989) this model has been widely used in the information system and considered as one of the main theoretical foundations (king and he, 2006). tam has proven to be one of the most powerful models to explain user technology acceptance and users’ behavior (wu et al., 2011). davis claims that the technology usage is determined by two factors, perceived usefulness and perceived ease of use, this individual impact is the main object of technology acceptance model. many studies apply this model to understand the behavior and attitude of erp system users and assess the satisfaction as a result of system use, the measurement of this satisfaction toward erp system use is cse computer self-efficacy (bradford and florin, 2003; kwahk and lee, 2008; scott and walczak, 2009). davis attempts to show that the user acceptance has been an impediment to the system information success; he considers that the user acceptance is the principal factor determining the success or failure of an information system project. for this reason, he investigates about why users accept or not an information technology and how users are influenced the it use process appropriate/inappro priate use the competitive process competitive position competitive dynamics it impacts organizational performance the it conversion process it expenditure it management/ conversion activities it assets figure 3: soh and markus framework (1995) 24 by the system features. to answer this question davis develops his model based on fishbein and ajzen’s (1975) (davis, 1989b) theory from psychology to explain the users’ attitudes and behaviors toward the information system use. to explain the system use, davis’ investigation focuses on two main constructs, perceived usefulness and ease of use, which are theorized to be considered as determinants of system use (davis, 1989a). the first construct is defined as “the degree to which a person believes that using a particular system would enhance his or her job performance”. the second construct is defined as “the degree to which a person believes that using a particular system would be free of effort”. the theoretical foundations for these two constructs were based on three main theories. firstly, the self-efficacy from social cognitive theory (bandura, 1999). self-efficacy is considered as the foundation of human agency. the perceived selfefficacy occupies a pivotal role in social cognitive theory because its effects action are not only direct, but through its impact on other classes of determinants as well (bandura, 1999). this concept of self-efficacy has a causal relationship with motivation, performance and job satisfaction. based on bandura’s (1982) studies, (davis, 1989b) explains both self-efficacy judgment and the outcome judgments, and claims that the “outcome judgment” variable is similar to perceived of usefulness. the second theory used by davis is the adoption of innovations theory from (rogers, 1983). davis outlines that the adoption of innovations suggests a prominent role for perceived ease of use. in the same vein, in their meta-analysis about the innovation characteristics and innovation adoption, implementation (tornatzky and klein, 1982) found that three innovation characteristics (compatibility, relative advantage, and complexity) had the most consistent significant relationships to innovation adoption. the third theory is the cost-benefit paradigm from behavioral decision theory. it is relevant to perceived usefulness and ease of use (davis, 1989b). person choice among various decision-making strategies in terms of cognitive trade-off between the effort required employing the strategy and the quality of resulting decision, the distinction between subjective decision making performance and effort is similar to the distinction between the perceived usefulness and perceived ease of use (davis, 1989b). system perceived usefulness perceived ease of use attitude toward using actual system use figure 5: technology acceptance model (davis, 1989; p: 481) 25 davis develops and validates new scales for two main variables, perceived usefulness and perceived ease of use, which are hypothesized to be the determinants of user acceptance technology. based on two studies and 152 users as a sample of study, he developed items that were pretested for content validity and then tested for reliability and construct validity. in both studies, he finds that usefulness had a significantly greater correlation with usage behavior than did ease of use, and claims that the perceived ease of use is considered as an antecedent to perceived usefulness. however, after identifying two principal variables that impact the tam construct: subjective norms and the mandatory use context. the updated of tam named tam 2 includes subjective norm as additional predictor of intention in the context of mandatory system use (venkatesh and davis, 2000). 2-2-2delone and mclean success model: d&m model is the most cited model in information system success (kronbichler et al., 2010; sedera and gable, 2010) it is one of the most famous models adopted by researchers to assess the success of information system in the last two decades. (seddon, 1997) in his article named respecification and extension of d&m model of is, criticized this model about the inclusion of both causation and process interpretations, which lead to the confusion meanings that decrease the value of the model (seddon, 1997). delone and mclean have up-dated their model based on these critics (delone and mclean, 2003). despite, this update of their model, the first version stays the most adopted and most cited in the literature review in is success. the strength of d&m model resides in his theoretical foundation based on both shannon & weaver communication theory and mason’s communication systems approach (mason, 1978; weaver and shannon, 1949). they claim that the information is considered as an output of an information system that can be measured at three principal levels: technical, semantic and effectiveness level, referring to the mathematical theory of communication (weaver and shannon, 1949) and its levels to analyze the message as a result of communication system. defining and measuring the output of any system is always difficult, especially if the output is rather intangible. information as an output is represented in symbolic form, this concept of signs is central to both information and communication; it is considered as the key link in the way one system affects another and thus involves the system’s context as well as the sign its self (mason, 1978). weaver classifies the problems of communication into three hierarchical levels a b and c: level a. how accurately can the symbols of communication be transmitted? (the technical problem). level b. how precisely do the transmitted symbols convey the desired meaning? (the semantic problem). level c. how effectively does the received meaning affect conduct in the desired way? (the effectiveness problem). system quality information quality user satisfaction use individual impact organizational impact figure 6: d&m is success model (delone & mclean, 1992) 26 d&m explain the concept of impact levels from communication theory and consider the serial nature of information as a form of communication. the information system is considered here as a sender that creates information which will be communicated to the recipient; this latter will be influenced by the content of this information. following mason’s scheme above (figure 7), the information system is considered as a production tool; the information is the product and the recipient is the user which is influenced by the content and quality of information. in the same vein d&m based on this approach they developed in their model two levels of influence or impact (individual and organizational). in this sense, they add that the flow of information throughout the production process to the use of information has an influence on individual and/or organizational performance. based on these theoretical backgrounds, d&m developed six distinct categories or aspects of information system that become the constructs of their model, these constructs are: system quality (sq), information quality (iq), use, user satisfaction, individual impact, and organizational impact. these variables are the most adopted to assess the success of an information system in the last two decades. however, the problem is the model construction that attempts to combine both causal and process explanations of is success (seddon, 1997). the result of combining both variance and process model is that many boxes and arrows can have both a variance and an event in a process of interpretation, giving a sense of different parts of the model will cause slippage from one meaning for a box or arrow to another (seddon, 1997), this later claims that the major difficulties with d&m model can be demonstrated by focusing attention on the use as a construct. this box in (figure 6) can take three possible meanings: as a variable that proxies for the benefits from use, as the dependent variable in a variant model of future is use and thirdly as an event in a process leading to individual or organizational impact. in the figure 8, seddon shows the meaning of the categories in delone & mclean model of is success, and explains the combination of three models: shanon and weaver (1949) technical level level semantic effectiveness or influence level production product mason (1978) receipt influence on recipient influence on system use system quality information quality categories of i/s success user satisfaction individual impact organization al impact figure 7: categories of is success (delone & mclean, 1992; p: 62) system quality information quality benefits from use implied by user satisfaction benefits from use implied by is use benefits from use for individuals benefits from use for organazations figure 8: the meaning of the categories in d&m’s model of is success; seddon, 1997; p: 244 27  a variance model of is success, where the system quality and information quality are considered as an independent variables, and the dependent variables are the is use and user satisfaction.  the second model is a variance model of is use as a behavior, that can take a second meaning for is use  the third model is a process model, where is use is considered as an event necessarily precedes the following constructs: user satisfaction, individual impact and organizational impact. (seddon, 1997). beyond the combination of both causation and process dimensions to explain the construction and the confusion in the meaning of the d&m model (seddon, 1997) other considerations would take place such as the level taken into account to explain the success of an information system and the performance impacts. the is evaluation success is not limited to the internal factors as claimed by d&m in their model based on shannon and weaver theory. for example the erp system quality is not only a causal variable leading to success, but also can be considered as a result of other external factors such as organizational, innovation and environmental factors (bradford and florin, 2003; ifinedo, 2011; sedera and gable, 2010). to answer for some critics considered troublesome, (delone and mclean, 2003) argue that their model is based on both process and causal considerations, the six dimensions of the model are interrelated rather than independent. based on a process considered the first event of their model begins by creating an is containing various specifies, the second event is the use of the system and its outputs. the final step is the impact result of this use on both individual and organizational performance. however, based on a causal dimension d&m explain the covariance between the independent and dependent variables to determine if there exists or not a causal relationship among the success dimensions. combining taxonomy and success, this model was to help in the understanding of the possible causal interrelationships among the six dimensions of success. despite the critics, d&m is success model stays one of the most adopted models in the information system field for two main reasons: its theoretical foundation and its empirical validation. but the question that arises is: is the evaluation process of the is success based only on d&m model? could it be possible to combine two theoretical models to assess the is success? what are the principal constructs of the combined model? what are the principal determinants of the erp system success? what are the theoretical foundations of this model? and what are the significant magnitudes of each factor in the model? 2-3 evaluation approaches many researchers tried to understand the relationship between the it investments and the performance, emphasizing five main approaches to evaluate the it projects (bellaaj, 2010). these approaches are: figure 9: evaluation approaches of is/it evaluation approach based on the economic theory (brynjolfsson, n.d.): the main goal of this approach is to understand the variance between the it investment and the organizational productivity based on some economic criteria. evaluation approach based on social psychology (davis, 1989a, 1989b; venkatesh et al., 2003): beyond the economic approach, this one integrates the human factors as a determinant in the evaluation process of the it investment and impact. evaluation approaches evaluation approach based on the economic theory evaluation approach based on social psychology evaluation approach based on processes evaluation approach based on the competitive analysis evaluation approach based on the strategic alignment 28 evaluation approach based on the competitive analysis: this approach is developed by (porter and millar, 1985) explains how the technology affects all business. authors’ outline that the information technology must be understood more than simple computers, it must be conceived of broadly to encompass the information that business create and use as well as a wide spectrum of increasingly convergent and linked technology that process the information, in their perception of the it they adopt the concept of the value chain to explain the competitive advantages gained from the it investments. evaluation approach based on the strategic alignment: this approach is developed by (henderson and venkatraman, 1993), it is widely used by the researchers in the information system to understand two main concepts; the first one is the fit between the information technology goals and the strategic objectives of the organization; the second is the functional integration (integration between business and functional domains). this approach suggests that the it strategy must be coherent with the corporate strategy in order to improve the organizational performance. evaluation approach based on processes: a new conception of the is success evaluation has been introduced by this approach based on emergent process theory developed by (markus and tanis, 2000; soh and markus, 1995). this approach highlights the inability of the economic model to evaluate the is success, and proposes à new vision of evaluation based not only on the input evaluation (it investment evaluation), but based also on the use and the impacts of the it, under a creative process value. three main approaches could be considered to evaluate the erp system success; the first one is based on the financial criteria of performance (nicolaou and bhattacharya, 2006) to evaluate the erp benefits (tangible benefits), the second approach is based on the non-financial approach to assess the intangible benefits of erp system, and the last one is a mixed approach, for example to evaluate the erp system, many perspectives of measurement must be taken into account such as the behavioral perspective (user acceptance), the strategic perspective (strategic alignment between organizational goals and erp), the economic perspective (cost, fees..) and the technological perspective (organizational fit and erp system integration). these four dimensions of erp assessment were treated separately in the literature review about the erp system success measurement. in this section, we will present two examples of evaluation approaches that synthesize the different evaluation perspectives mentioned above. firstly we will propose an ahp approach to assess the erp performance measures (tsai et al., 2006). secondly, we will present the balanced scorecard approach adopted largely by many searchers to evaluate the erp system benefits (chand et al., 2005; rosemann and wiese, 1999; velcu, 2010). 2-3-1ahp approach of erp performance assessment: the ahp approach (analytic hierarchy process approach) consists in assessing the relative importance weights of erp performance measurement; it can be used to select the main performance indicators of erp system, and explains the contribution of erp system in the organizational performance (tsai et al., 2006). this approach is applied to decision-making problems to select the best and appropriate solution according to the importance of each alternative. in the case of erp system two stages were presented by (tsai et al., 2006) to assess the relative weights of erp performance measurement. the first one consists of listing all the erp performance measurement and evaluating their importance. the second stage focuses on constructing an ahp analysis framework and achieving the relative importance weights of 80 erp performance measures by using a questionnaire with 7-point likert-type scale (1=extremely unimportant, 7=extremely important). this approach focuses the post-implementation erp stage. based on d&m model 1992, this approach proposes a new taxonomy of performance measurement: the quality category, and the impact category of measurement. the quality concerns the erp system, the information, system use and user satisfaction, the impact category concerns both individual and organizational levels. the result of this study shows that a company can select specific performance measurements according to three principal factors: goals of its erp system, their needs and the specific context of the company. this means that every company must construct its key measurement performance taking into account the three main factors mentioned above. 2-3-2balanced scorecard approach of erp performance measurement: this approach is developed by (kaplan and norton, 1992) to understand better and classify the performance measurements of the organization. they claim that the balanced scorecard allows managers to analyze the business performance from four main perspectives, financial perspective, internal business perspective, innovation/learning perspective and finally the customer perspective. this bsc framework is widely used in management science in different disciplines to assess the organizational performance. however, our attention focuses on the use of this approach to assess the performance introduced by the erp system. some researchers were interested in this question about assessing the erp system performance from a bsc approach (rosemann and wiese, 1999; velcu, 2010). they 29 explain how the bsc approach can be used to evaluate the business performance introduced by the erp implementation on both operational and strategic levels. the aim objet of using the bsc approach is to explain the performance benefits that organizations gain from erp system. this explanation follows four perspectives as defended by (kaplan and norton, 1992). after analyzing these perspectives, their application on the erp system context appeared feasible and interesting to understand the performance beyond its traditional financial approach. the figure 9 explains how the erp system contributes to the business performance from four different angles. this application of the bsc sheds some light on the understanding of three levels of erp impact on the performance, the operational level, the tactical level and the strategic level. these levels provide a framework for analyzing benefits based on organizational strategy and erp system goals throughout the erp life-cycle. 3theoretical foundations: firstly, we will present our conceptual model that is based on both theoretical and empirical background. this framework will be considered as a model of erp system success evaluation that combine a causal and process considerations to assess the success of erp project in three levels of performance: individual performance, work group performance and organizational performance (ifinedo and nahar, 2006; ifinedo, 2011; ifinedo et al., 2010; myers et al., 1997). the levels of analysis taken into account in this model were based on three theories: the first theory is the mathematical theory of communication as used by delone and mclean in there is success model to analyze the system quality and its impact on the information quality on the one hand and the impact of the information quality in users effectiveness on the other hand; the second theory is the innovation diffusion theory used to analyze and classify the different factors in three main boxes: innovation factors, organizational factors and environmental factors; and finally the structuration theory to analyze the contribution of the erp technology in the organizational performance. 3-1mathematical theory of communication the mathematical theory of communication (mason, 1978; weaver and shannon, 1949) explains the interaction between three factors: the information system, the information as a product and the impact of the information on the individual and organizational performance. this approach is used by (delone and mclean, 1992) in their model of success to develop sex constructs considered as the •what are the best practices intruduced by the erp system and how they contribute to improve the business value •how the erp system improve the internal process by introducing a new busness process reengineering •what are the main criteria for assessing the user performance, user satisfaction, perceived ease of use and perceived usefulness of the erp system •what are the appropriate indicators to measure the financial performance introduced by the erp system financial perspective costumer perspective innovation and learning perspective internal perspective figure 10: bsc perspectives for erp performance evaluation 30 main variable to assess the success of the information system. 3-2innovation diffusion theory based on the innovation diffusion theory, mainly the paradigm of variables determining the adoption of innovation (rogers, 1983), three main factors appeared: innovation/technological factors, environmental factors and organization factors. in this taxonomy, each one of these factors can be explained in the erp system context. these factors are extremely important in the erp adoption phase, and they must be integrated in the process of the erp system success (no success without technology adoption firstly). (rogers, 1983) defines the constructs that constitute the perceived attributes of innovation in his paradigm of variables determining the adoption of technology as following: compatibility: “compatibility is the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters. an idea that is more compatible is less uncertain to the potential adopter. an innovation can be compatible or incompatible (1) with sociocultural values and beliefs, (2) with previously introduced ideas, or (3) with client needs for innovations”. rogers, p: 223. complexity “is the degree to which an innovation is perceived as relatively difficult to understand and use” rogers, p: 231 relative advantage “is the degree to which an innovation is perceived as being better than the idea it supersedes the relative advantage of an innovation, as perceived by members of a social system, is positively related to its rate of adoption”. rogers, p 231 trialability (system testing: during the final stages of erp implementation, the project team should consider the inclusion of testing exercises as well as simulation before the system “goes live” (al-mashari et al., 2003; finney and corbett, 2007)) “is the degree to which an innovation may be experimented with on a limited basis” rogers, p: 231 observability “is the degree to which the results of an innovation are visible to others? the observability of an innovation, as perceived by members of a social system, is positively related to its rate of adoption”. rogers, p: 231. all these constructs take place for determining the erp system adoption as a new technological innovation introduced by the organization to improve its performance and achieve some strategic and operational goals. taking into consideration these variables is an important step in the erp system success process because we consider that there is no success outside the adoption of technology. when all the different stakeholders realize the usefulness and the perceived attributes of the erp system, the erp system adoption perceived attributes of erp system relative advantage compatibility complexity trialability (system testing) observability type of innovation decision (erp implementation strategy decision) communication channels (communication among stakeholders) nature of the social system (legacy system) extent of change agent’s promotion efforts (management change) figure 11: adopted from the paradigm of variables determining the adoption of innovation (m. rogers, 1983 p: 233) 31 success and the quality of system begin to take place. once adopted, the technology should bring productivity, efficiency, and satisfaction to individuals and organizations (desanctis and poole, 1994). main theoretical perspectives on technology and performance characteristics of each perspective examples of theoretical approaches mathematical theory of communication focus on both the information system and the information as an output in one hand, and explain their impact on the individual and organizational performance in the other. ( a process model) (mason, 1978); (weaver and shannon, 1949) (see figure, 7) innovation diffusion theory focus on the technology adoption and use (a causal model) paradigm of variables determining the adoption of innovation m. rogers, 1983 (see figure, 10) (venkatesh et al., 2003) structuration theory focus on the interactions between actors and technology (a mixed model), and explain how the technology should bring productivity, efficiency, and satisfaction to individuals and organizations acp (adaptive structuration theory) approach (desanctis and poole, 1994).(see figure, 11) 3-3structuration theory (ast approach) structuration theory associated with giddens’ institutional theory of social evaluation has been largely applied to understand and explain organizational adoption of technologies (desanctis and poole, 1994). we focus our attention only on the ast proposed by desanctis and poole, 1994 to explain how the technology brings productivity, efficacy and satisfaction to both individuals and organizations. this approach which is based on the technology school was applied and explained by desanctis and poole, 1994 in their adaptive structuration theory approach. the asp is considered as a framework for studying variation in organization change and illustrating the impacts of advanced technologies on organizations. it was tested on a gdss (group decision support system) to answer the questions about how the technology affects people and organizations that use it, and how it improves workgroup performance. we consider this ast approach as an extension of the paradigm of variables determining the adoption of technology (see figure 11), because the adoption of technology is an important step in the appropriation process leading to improve the performance in three main levels (individual, group and organizational performance). (desanctis and poole, 1994) outline the importance played by organizational members in the process to choose the most appropriate technology. table 2: theoretical perspectives 32 3-4evaluation success factors of the erp system: 4journal authors geographic area sample size evaluation phases of erp system sector respondents function evaluation success factors esf’s journal of research and practice in information technology (shih and huang, 2009) asia 165 erp project private end erp users *top management support *erp system quality *system integration *erp fit journal of computing in civil engineering (chung et al., 2008) asia 281 erp project private end erp users *top management support *vendor and consultant quality *information quality *erp system quality international conference on information systems (gable et al., 2003) australia 310 erp project public end erp users *individual implication *information quality *erp system quality journal of information technology management (ifinedo and nahar, 2006) asia 62 erp project private user/ consultant/ manager *vendor and consultant quality *work group implication *individual implication *information quality *erp system quality structure of technology: sophistication /efficiency organizational environment decision outcomes: efficiency/quality /performance social interaction knowledge and experience with the system figure 12: adapted from the ast constructs (desanctis&poole, 1994; p: 123) 33 int. j. production economics (ram et al., 2013b) (ram et al., 2013a) (a) australia 217 implementat ion private all levels of erp users *training and education *business process reengineering *project management *system integration *erp fit computers in human behavior (ifinedo et al., 2010) europe 109 postimplementati on private all levels of erp users *vendor and consultant quality *work group implication *individual implication *information quality *erp system quality information & management (law and ngai, 2007) asia 96 erp project private all levels of erp users *business process reengineering social and behavioral sciences (candra, 2012) asia 46 implementat ion private all levels of erp users *individual implication *erp system quality *information quality international journal of information management (zhu et al., 2010) asia 65 postimplementati on private cio's/ managers *top management support *vendor and consultant quality *project management *system integration *erp fit information & management (hong and kim, 2002) asia 105 implementat ion private erp project managers *business process reengineering information & management (velcu, 2010) europe 88 implementat ion private cio/ceo/cf o *business process reengineering * project management computers in industry (ehie and madsen, 2005) usa 36 implementat ion private all levels of erp users *top management support *vendor and consultant quality *business process reengineering *project management information& management (bernroi der, 2008) usa 209 postimplementati on private all levels of erp users *business process reengineering *information quality the journal of strategic information system (sedera and gable, 2010) asia 310 erp project private all levels of erp users *vendor and consultant quality *individual implication *erp system quality international journal of (bradfor d and usa 51 implementat ion private erp managers *top management support 34 accounting information systems florin, 2003) *training and education *business process reengineering *system integration *erp fit journal of manufacturin g systems (chou and hong, 2013) asia 117 implementat ion private erp users *vendor and consultant quality *individual implication information quality *information quality *erp system quality the journal of systems and software (ifinedo, 2011) europe 109 erp project private erp users *individual implication information quality *information quality *erp system quality international journal of project management (ram et al., 2013a) (ram et al., 2013b) (b) australia 209 postimplementati on private senior erp managers *training and education *business process reengineering *project management *system integration *erp fit the journal of systems and software (wang et al., 2008) asia 90 implementat ion private cio’s *vendor and consultant quality *top management support *project management *information quality computers in human behavior (yoon, 2009) asia 152 private erp senior managers *information quality international journal of human computer studies (choi et al., 2007) asia 223 learning educatio n students *training and education *erp system quality information& management (scott and walczak, 2009) usa 234 learning educatio n students *top management support *vendor and consultant quality computers in human behavior (amoako gyampa h, 2007) usa 278 implementat ion private end users *erp system quality decision support systems (wang and chen, 2006) asia 122 erp project private erp/it managers *system integration *erp fit international journal of production economics (chien et al., 2007) asia 139 erp project private senior erp managers *project management 35 information& management (tsai et al., 2012) asia 278 implementat ion private erp users *vendor and consultant quality *individual implication *erp system quality information& management (kwahk and lee, 2008) asia 273 postimplementati on private erp users *top management support *erp system quality decision support systems (chou and chang, 2008) asia 166 erp project private erp users *organizational factors computers in human behavior (grant et al., 2013) usa 122 implementat ion private erp users *organizational factors *system integration *erp fit information& management (sun et al., 2009) asia 138 erp project private erp users *erp system quality international journal of project management (bernroi der et al., 2014) europe 209 implementat ion private erp users *top management support *vendor and consultant quality *training and education *business process reengineering *system integration *erp fit the service industries journal (lapiedr a et al., 2011) europe 134 implementat ion private erp users *vendor and consultant quality 4-1evaluation erp system success model: organizational factors: *top management support *project management *individual implication * work group implication technological/innova tion factors: *bpr *erp fit *system integration *system configuration and customization environmental factors: *vendor competencies *consultant competencies *training and education *knowledge transfers information/data quality erp system quality individual performan ce group performan ce organizational performance benefits e r p s u c c e ss 36 5discussion and implications research implications: this study provides both theoretical backgrounds and empirical contribution to understand the factors that impact the erp project success, this impact was measured in three levels of performance, individual, group and organization. thus, this study proposes a new taxonomy of the evaluation success factors and explains the erp system success process using a strong theoretical foundations, mathematical theory of communication, diffusion innovation theory and ast (adaptive structuration theory). the theoretical model developed in this work explains the erp system success from two main dimensions, a causal dimension and a process dimension. the first one highlights the variables that contribute on the erp system adoption and use, based on diffusions of innovations theory (rogers, 1984). the second sheds the light on the process of the erp system success through the explanation of interaction between organizational, individual and technological variables based on the one hand on the mathematical theory of communication to explain how the system quality output impacts the individual and organizational performance (mason, 1978; weaver and shannon, 1949), and on the other hand on the ast (desanctis and poole, 1994) to explain the interaction between the human actors (erp users) and the technology, and how this later leads to improve the efficiency, quality and performance. however, we exposed the main frameworks, approaches and models interested on the erp system success and measurement in the literature. thereby, we explained the feasibility and the fit of each one of these theoretical backgrounds to be applied to evaluate the success of the erp system project including the specificities and implementation phases of the software. the theoretical model developed in this study is appropriated to the erp system; it takes into account the features of both implementation and use of the erp system. because, the erp system is considered as a project including different stakeholders, organization involvement, user involvement, vendor and consultant involvement, it success depends on the collaboration between all the organization partners. thus, the model explains how the organizational, technological and environmental critical factors contribute to the erp system adoption and use, which considered as a synonymous of the erp system quality. then, the model shows the quality output represented by data and information quality, and how this later affects the performance and the efficiency. the definition of the success adopted in this model reveals that the success is considered as a correspondence and an interaction (lyytinen and hirschheim, 1987), 1987). the correspondence highlights the fit between the erp system and the organization objectives that leads to improve the organizational performance. the interaction success represents the positive user attitudes toward the erp system, which contribute to improve both individual and workgroup performance. managerial implications: this research work provides a new tool to practitioners enabling them a better understanding of the erp system success project. information system managers, top management and erp users need to understand the implication of their actions in the success process and how they contribute in the performance improvement. thus, this work seeks to highlight the vendor and consultants contributions to perform the erp project. to face more than three quarters of unsuccessful erp project, organizations need to be able to evaluate their information system projects. this need leads us to investigate this question by developing a new model that explain the relationships between the erp partners on the one hand and propose the main evaluation factors to assess the erp project success. 6conclusion this attempt to develop a new model of erp system success evaluation is motivated by the need of companies to justify and understand their investments in this kind of information technology project. erp system project should not be considered only as a top management project but an organizational project that integrates all the actors and stakeholders, for this reason in our model of erp system success evaluation we take into consideration the role of all partners and actors for different level of analysis and different phases of erp project integration. three categories of evaluation factors were proposed: organizational factors, environmental factors and technology factors. these factors are crucial to evaluate the success of the erp system project; they contribute considerably to understand the process of the erp system success. organizations should give more attention to these factors to succeed their information system project and to get a high quality system, accepted and used by employees. as highlighted in our model the success should be evaluated from three main levels of analysis: individual level, group level and organizational level. this model combines two principal conceptions of the success concept, the first one coming from the delone & maclean model to understand the main variables of the erp system success and give more importance to the technological aspect based on the quality system as the principal starting point of the success process. however, tam model give more importance to the human factor in the technology success based on the acceptance and use as two main criteria of the system success. but, nether on nor the other outline the external factors that contribute to the success of this project, it seems that these exogenous factors are important in the erp system project acceptance as a new technology introduced by organizations. theoretical basis of these factors derived from the diffusion of innovation theory (rogers, 1983) that 37 outlines the importance of the environmental, technological and organizational factors in the technology adoption. this work proposes a set of tools to evaluate the erp project success, many approaches models and framework were proposed to understand the evaluation success process. summarizing works previously presented in the literature review about the success evaluation of the erp system project. 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(2018) business intelligence for social media interaction in the travel industry. journal of intelligence studies in business. 8 (2) 77-84. article url: https://ojs.hh.se/index.php/jisib/article/view/311 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index business intelligence for social media interaction in the travel industry in indonesia michael yuliantoa, abba suganda girsanga* and reinert yosua rumagita acomputer science department, binus graduate program-master of computer science, bina nusantara university, jakarta, indonesia; *agirsang@binus.edu journal of intelligence studies in business please scroll down for article business intelligence for social media interaction in the travel industry in indonesia michael yuliantoa, abba suganda girsanga* and reinert yosua rumagita a computer science department, binus graduate program-master of computer science, bina nusantara university, jakarta, indonesia 1148 corresponding author (*): mailto:agirsang@binus.edu received 14 may 2018 accepted 25 july 2018 abstract electronic ticket (eticket) provider services are growing fast in indonesia, making the competition between companies increasingly intense. moreover, most of them have the same service or feature for serving their customers. to get back the feedback of their customers, many companies use social media (facebook and twitter) for marketing activity or communicating directly with their customers. the development of current technology allows the company to take data from social media. thus, many companies take social media data for analyses. this study proposed developing a data warehouse to analyze data in social media such as likes, comments, and sentiment. since the sentiment is not provided directly from social media data, this study uses lexicon based classification to categorize the sentiment of users’ comments. this data warehouse provides business intelligence to see the performance of the company based on their social media data. the data warehouse is built using three travel companies in indonesia. as a result, this data warehouse provides the comparison of the performance based on the social media data. keywords business intelligence, lexicon based classification, sentiment analysis, social media 1. introduction the development of air transportation and airlines in indonesia is increasing. this is marked by the growing number of airlines that have sprung up by offering both domestic and international travel routes that make the competition more competitive. with competitive competition, many airlines offer promotions that can be an attraction for consumers. this is certainly a great opportunity for business people to use information technology. the development of telecommunication and computer technology led to changes in the pattern of instant purchasing, online reservations, and the ticketing process, which in the aviation world is often called the online system or electronic ticketing (atmadjati, 2012). in indonesia electronic ticketing providers are becoming more common, so competition is increasing. because business competition requires price matching, companies must compete to attract consumers as much as possible in order to survive. many companies use media for marketing. this includes social media, like facebook and twitter. with social media, customers can easily contact the company (customer service). businesses start looking at such technologies as effective mechanisms to interact more with their customers (ali abdallah alalwan, et al. 2017). social media has become the largest data source of public opinion (shuyuan deng, 2017). journal of intelligence studies in business vol. 8, no. 2 (2018) pp. 77-84 open access: freely available at: https://ojs.hh.se/ 78 indonesia has the fourth most facebook users in the world. therefore, this study focuses on the relationship of social media use, namely facebook and twitter, to see the interaction between companies and consumers. data that exist in social media can help us to do the analysis to help companies get feedback from consumers. the data that can be retrieved include "like, comment, and share" information. sentiment analysis can be used to process comments in order to get feedback on the nature of the comment, good or bad (he, zha, & li, 2013). poor comments can be used as advice and input for the company in the future (saragih & girsang, 2017). in this study, using existing data in social media facebook and twitter is expected to create business intelligence that can help analyze travel business companies in indonesia with social media data interaction. 2. conceptual background in this chapter, we examine the concept and characteristics of business intelligence and sentiment analysis using lexicon based classification. 2.1 business intelligence business information and business analysis in the context of business processes are the key that leads to decision-making and actions that lead to improved business performance. business intelligence can be defined as “a set of mathematical models and analytical methodologies used to exploit the data available to produce information and knowledge useful for complex decision-making processes” (vercellis,2006, williams, s., and williams, n, 2006). advantages of business intelligence: • effective decisions: business intelligence applications allow users to use more reliable information and knowledge. the result is a decision maker can make better decisions and match goals with the help of business intelligence. • timely decision: dynamic, where decisions can be taken quickly. the result obtained by the organization is that the organization will have the ability to react continuously in accordance with the movements of competitors and to change when there are important new market circumstances. • increase profits: business intelligence can help business clients to evaluate customer value and desire for shortterm profits and to use the knowledge used to differentiate between profitable customers and non-profitable customers. • reduced costs: reducing the investment needed to use sales, business intelligence can be used to assist in evaluating the organization's costs. • develop customer relationship management (crm): this is essentially a business intelligence application that applies customer information collection analysis to provide responsible customer service responsibilities that have been developed. • reduce the risk: applying the business intelligence method to enter data can develop a credit risk analysis, looking at the analysis of consumer activity, producers, and reliability can provide insight into how to shorten the supply chain 2.2 sentiment analysis sentiment analysis or opinion mining is a process of understanding, extracting and processing textual data automatically to get sentiment information contained in an opinion sentence. sentiment analysis is done to view opinions or opinion tendency of a problem or object by someone. sentiment analysis can be distinguished based on the data source, some of the level that is often used in research sentiment analysis is sentiment analysis at document level and sentiment analysis at sentence level (bo,p et al. 2002) the lexicon-based approach depends on the words in the opinion (sentiment), specifically words that usually expresses a positive sentiment or negative sentiment. words that describe the desired state (e.g. great, good) have positive polarity, whereas the words describing the unwanted state have negative polarity (e.g. bad, horrible). one common approach used in performing sentiment analysis is using a dictionary based approach. because this research is based on indonesia, the dictionary will use indonesian words. figure 1 is a positive dictionary and figure 2 is a negative dictionary. 3. methodology 79 research conducted begins based on the interest of the writer about the data that exist on social media. therefore, through this research, the author wants to create a data warehouse for social media data in order to perform analyses related to social media interactions. these include an analysis of how actively the company replies or communicates with its customers on social media such as facebook or twitter. 3.1 crawling data data retrieval is done from selected social media platforms such as facebook and twitter via the social media api available on each platform. data retrieval is done periodically by crawlers. the data is taken every wednesday and saturday. this is done because the data provided by the twitter api only retrieves data up to seven days old. for example, data retrieved on october 18, 2017 from twitter can only go back as early as october 11, 2017. data before that date cannot be retrieved. from the data that was regularly taken by the crawler, was stored on in the form of excel files. the types of data stored on each social media platform are different: • facebook: post, comment, reply, like • twitter: tweet, retweet, mention crawling data in this research uses rstudio, for crawling facebook the library rfacebook was used and for twitter, twitterr was used. 3.1.1 crawling facebook in this research, will use three months of data, from september 2017 to december 2017 from three companies. the pseudocode used to get data using rfacebook in rstudio was: load rfacebook connect to facebook api using fboauth get paget from official facebook page using function getpage get all post in page use getpost get like and comment from post (post$likes & post$comments) get like and reply from comment using getcommentreplies export to csv format 3.1.2 crawling twitter twitterr uses the twitter api to get the data. because of this, there is a seven day limitation from the day we request data. the pseudocode to get the data using twitterr in rstudio was: load twitterr connect to twitter api using setup_twitter_oauth search @from twitter@ example from:traveloka search “@” example @traveloka search “to” tweet example to:traveloka export to csv format 3.2 sentiment analysis 3.2.1 preprocessing preprocessing data data comments from facebook and twitter social media is done by preprocessing before sentiment analysis. figure 4 shows the preprocessing stages. the first step is case folding. case folding is the process of converting words into lowercase. the purpose of turning words into lowercase is to eliminate case sensitive errors. the next step is to filter the sentence. written words are figure 1 positive dictionary. figure 2 negative dictionary. figure 3 methodology 80 punctuation, number, and website address. the process of separating sentences into individual words is usually called tokenization. the easiest way to turn a sentence into words is to separate them with spaces. stemming is the process of converting words into basic words. 3.2.2 lexicon based algorithm the lexicon algorithm converts data via a function that will process every sentence in the data source. figure 5 is the pseudocode for the sentiment analysis using the lexicon based algorithm (chopra and bhatia, 2016). 1. enter the text as input. 2. divide this paragraph into tokens and store the words in an array list. 3. select the first word from array list. 4. fetch the words of database in second array named as database array. 5. check whether selected paragraph word matched with each word of database array. (i) if match found (a) find the sentiment of word from database whether it is positive/negative or neutral. (b) find the exact position of word in the paragraph. (c) highlight the word according to their sentiment; make it green if it is positive, red if it is negative and blue if it is neutral. (d) calculate the score of sentence. (e) store the results in database. (ii) else match not found (a) select next word from the array (b) go to step 5. 6. display the result to the user. 7. plot the graph according to the results. figure 5 pseudocode for the sentiment analysis using the lexicon based algorithm. 4. results result from the methodology above are shown in figure 6. there are two table facts and five dimension tables. the two fact tables are: the fact company activity and fact user activity. the five dimension tables are: dim user, dim sentiment, dim company, dim media social, and dim time. dashboard admin activity consists of four reports (figure 7). the first report is the report of admin activity trends during the month, the second report provides an overview of the activities undertaken by the admin, the third report is a report of activity per day while the latter is an hourly activity. uniquely by using the business intelligence program tableau all existing reports can affect each other, for example when we click on the first report graph on the line traveloka and september all reports on this page will show facebook traveloka data in september. dashboard user activity consists of five reports (figure 8). the first report is the report of user activity trends during the month, the second report is sentiment analysis report, the third report is the most active user in social media, the fourth is user activity by day and the last is an activity report by hour. with this dashboard we can analyze who is active during the month or day or time we choose in the dashboard. on the dashboard the activity of the companies assesed can be seen. facebook social media shows that the company pegi pegi is the most active compared to other companies. in september it was found that pegi-pegi made a ocial media strategy change, which can be seen in october with a rise of almost 368.81%. the company, ticket, had the lowest activity. in this company there is even a decline in october and december. on twitter, traveloka has the most activity compared to other companies. traveloka has more than 1,000 activities per month. other companies have almost 10 times less activity than traveloka. pegi-pegi and ticket had an figure 4 preprocessing stages. 81 increase in november and december. in november there was a decrease in activity. figure 9 summarizes the company activity on social media. the most frequent facebook activity by companies is reply to comments from customers. this was most frequently done by traveloka, followed by pegi-pegi and ticket. at pegi-pegi the most most common activity was liking comments from its customers. figure 10 shows activity by hour. the companies’ facebook and twitter activity peaked at 16:00-16:59. traveloka’s activity peaked at 19.00 19.59 while pegi-pegi was most active at 16.00 16.59 and ticket was most active at 12.00 12.59 (figure 11). research conducted during four months of social media data collection on facebook and twitter, obtained 28,445 comments and figure 6 star schema. figure 7 dashboard company activity. 82 2,379,107 liked statuses by the users (figure 12). this figure is very high, and reflects how enthusiastic the users with activities performed by the company. on social media facebook, traveloka has more enthusiastic users than the other two companies, this is evidenced by the existence of 1,386,318 user activity data points, of which 942,769 activities occurred in october. when viewed in more detail, pegi-pegi has more active users than traveloka in the last two months (november and december). from 28,445 comments, traveloka has the most negative sentiment with an average of 14.26% negative, 34.51% positive sentiment and 51.23% neutral sentiment on twitter. tickets have the best positive analytical sentiment with a value of 44.05%, compared with negative sentiment which is only 14.10% and a neutral value of 41.85%. figure 13 shows the results of the lexicon-based sentiment analysis. the last four months’ data got the names of users who most actively made comments or liked a status or comment. in every form of social media there were users who engaged in more than 100 activities in the last 4 months (figure 14). on traveloka, the top ten people engaging had an average activity of 200 interactions, while pegi-pegi had an average of 168 activities and ticket has the lowest average of 84. 5. recommendiation from the dashboard analysis various recommendations for companies studied were obtained. 5.1 traveloka on facebook social media needs to be improved again because from november there was a significant decline (23%) compared to the previous month. at 19.00 19.59 the activities of the traveloka are recommended to have more human resources in order to help solve customer problems. figure 8 dashboard user activity. figure 9 summary company activity. figure 10 detail company activity. 83 5.2 ticket on facebook, social media needs to be improved. in september there were 94 activities, but this declined considerably to 74 activities in december. on twitter, engagement should be improved again as compared to traveloka, as the activity of ticket is lagging behind. for twitter we suggest human resources should be available in the early hours, as in december at 00.00 07.00 there are only seven activities, compared with user activity on ticket’s twitter feed of as much as 85 activities. 5.3 pegi-pegi for twitter, we suggest increased human resources in early hours. in december at 00.00 07.00 there were 55 activities only compared with user activity on twitter pegi pegi as many as 244 activities. 6. conclusion based on the results of the research, there are several conclusions. by using business intelligence conducted in this research, traveloka has the most interaction in social media, as compared with pegi-pegi and ticket.com. this research provides some suggestions for the development of business intelligence for social media interaction. the classification accuracy can be further improved by using algorithms and 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(2006). the profit impact of business intelligence. san francisco: morgan kaufmann. figure 14 most active users. establishment and application of competitive intelligence system in mobile devices anass el haddadi *,**, bernard dousset * and ilham berrada ** * irit umr 5505, university of toulouse iii 118, route de narbonne, f-31062 toulouse cedex 9, france haddadi@irit.fr, dousset@irit.fr ** ensias, al bironi team, university of med v-souissi, b.p. 713 agdal – rabat, morocco iberrada@ensias.ma received 25 may 2011; received in revised form 22 august 2011; accepted 11 december 2011 abstract: the strategy concept has changed dramatically: from a long range planning to strategic planning then to strategic responsiveness. this response implies moving from a concept of change to a concept of continuous evolution. in our context, the competitive intelligence system presented aims to improve decision‐making in all aspects of business life, particularly for offensive and innovative decisions. in the paper we present xplor everywhere, our competitive intelligence system based on a multidimensional analysis model for mobile devices. the objective of this system is to capture the information environment in all dimensions of a decision problem, with the exploitation of information by analyzing the evolution of their interactions. keywords: competitive intelligence, competitive intelligence systems, xplor everywhere, business intelligence, continuous evolution available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 87-96 mailto:dousset@irit.fr https://ojs.hh.se/ 88 1. introduction companies today are faced with external risk factors linked with an increased competition in markets that are extremely dynamic and unpredictable. this is caused by new competitors, mergers and acquisition, sharp price cuts, rapid changes in consumption patterns and weak brands. in this dynamical condition the competitive intelligence system (cis) and business intelligence (bi) software becomes a main component when companies develop their strategies. today information technology is considered as a simple support for organizations, but in a strategic way it promises to contribute to a sustainable competitive advantage. for five decades the concept of a strategy has changed dramatically from being a long range planning tool to become strategic planning and thereafter ending up as strategic responsiveness. by embracing the responsiveness concept a company can be flexible and constantly evolve. a competitive intelligence system (salles, 2002) aims to improve decision‐making in all aspects of business life, in particular for offensive and innovative decisions. to face all the challenges that appear in a dynamic industry, competitive intelligence platforms are designed to provide online services. competitive intelligence (ci) can be seen as both a process and a product (haags, 2006). as a process, ci is the set of legal and ethical methods that a company uses to harness information that helps them to achieve international success. as a product, ci can be considered as an information system for analyzing data concerning competitors’ activities collected from public and private sources, what is also referred to as business intelligence. the results of the analysis can provide knowledge regarding the current and future behavior of competitors, suppliers, customers, technologies, acquisitions, markets, products and services, and the general business environment. when collecting data for analysis sources as newspaper articles, corporate publications, websites, patent filings, specialized databases, information at trade shows and blogs can be used. the issue concerning ci is how to build a cis (ci as a product) and model analysis (ci as a process). our contribution in this paper is to propose an information system adapted to the needs of a ci process. the system’s mission is to provide a methodological reference for collecting, treating and analyzing information. also an analysis of the information environment in all of its dimensions will be made. the rest of the paper is structured as follows: in section two we identify the analytical models of ci, with support from the medesiie model and the site model. in section three we explain information system adapted to the ci approach. section four presents our multidimensional analysis model for ci and section five presents the architecture of a cis. finally in section six a summary and evaluation of the method will be found. 2. the analytical models of ci through the different characteristics of ci, we identify four dimensions in the definition of an analytical model. the four dimensions are as follows: 1. the environmental dimension for a company which includes elements that may influence the strategy of a company. the environment is characterized by partners, competitors, markets and customers. 2. the human dimension which include those who are involved in the ci process, whether internal or external to the company. the human dimension is characterized by networks of collaboration, interaction and communication between different actors. 3. the strategic dimension corresponds to different models of analysis for the company, from identifying objectives to the decision and the definition of actions. 4. the technological dimension brings together all the methods, tools and techniques used in the ci process; information retrieval, collection, treatment and dissemination of information. the inclusion of one or more of these dimensions can result in various models used for the analysis (conceptual or practical) of ci. we selected two academic models built on these dimensions: medesiie model and site model. 2.1 medesiie model the medesiie model is a method for defining a information system for ci. the ci approach proposed in the project medesiie is devoted entirely to the needs analysis of small and medium-sized enterprises (sme) in ci. medesiie consider a cis as a representation of the enterprise’s knowledge. the conceptual architecture of this system is based on the definition given by seligman, wijers & sol (1989) regarding the design of cis. salles, 2003 describe a cis with four components; the way of thinking, the way of modeling, the way of organizing and the way of supporting. medesiie suggests a model to describe the company, its strategy, its environment, its needs under/within the ci and its products and services (salles, 2003). there are different types of models that the medesiie model describes. it could be a business model, that is described according to its different functions, for example production, economy / market linkages, financial and innovation / information 89 system. each function is itself composed of a set of sub‐management functions. a strategic model is represented by a set of strategic choices and areas of development such as a search of independence and business growth. an environment model is described initially by the business functions and the relationships it develops in the environment. the surrounding context includes the spatial geometry of markets, technology, competition, the financial system, supply conditions, the regulatory framework, environmental policy and geopolitics. a model of needs provides a framework for the collection of requirements and their formalization, analysis and validation. the expressed needs are represented by a set of units’ needed. the model unit requirement is described in terms of three dimensions. one, the control level of decisions for which the units are expressed (value: operational, tactical or strategic). two, the phase of the decision‐ making process associated with the unit and three, its informational content (identification of its value and function). the last example of medesiie’s models is a model of products/ services. any supply of decision making bearing the environment of a company is a prototyping tool made according to the collected needs, the cost defined, reached and powered to evaluate the effects a priori. 2.2 site model the site model includes different models of ci, proposed by the research team site‐loria. these models are based on the linking of three spaces: the space of decision problems, the space of the informational problems and the space of mediations. the three spaces are connected through exchanges between the two types of actors, the decision‐maker and the watchman. teamwork is important, thus the inclusion of the user in the information systems is important. they propose models to define the different actors, their interactions and their positioning in the ci process. we have retained the following three models: equate (explore query analysis annotated), mepd (model for the explanation of a decision problem) and wisp (watcher‐information‐search‐ problem). the equate model represents a situation of information retrieval which implies the following cognitive phases (david & thiery, 2002): exploring the word of information querying the information base analysis of the information base annotation based on individual preferences the mepd model defines different steps for a decision making problem that is based on (bouaka, 2004): modeling the decision making by its identity, personality traits, cognitive style and experience. modeling the environment by the immediate environment with customers, providers and competitors and the global environment with for example social-, economicaland political aspects. modeling of organization, by environment, its signal, the assumptions that the decision‐maker can infer the detection of signals collected. the wisp model, associated with the threedimensional mepd, is incorporating the same point of views (kislin, 2007). the three dimensions are as follows: 1. an analytical dimension that includes understanding the demand‐stake‐context, the definition of informational indicators, the operations of analysis and creation of knowledge can be achieved by studying the stored elements. 2. a methodological dimension is incorporated at two levels. the first level regards the skills of transaction of the decision problem in the information problem. the second level regards strategies by which the information is identified and knowledge is acquired. 3. an operational dimension to define the selection of an action plan and implement the various stages of resolution for the methodology associated with the model wisp. 3. information systems adapted to the ci approach for romagni and wild (1998) the definition of an information system adapted to the ci approach is an organized set of procedures, at any time, to give decision makers a representation of a company in its environment and market. the ci function provides information to assist in executive functions, management and decision‐making. it must facilitate decisions to automate a number of actions or providing decision makers with the necessary information for decision‐making. it must also coordinate the processing of information, store sustainably information and improve data processing the creation of information directly applicable for decision makers. the majority of current information systems are inadequate to manage the dynamic markets. they are mostly designed for stable and controlled environments and are built on vertical and complex organizational patterns. these types of information systems do not meet the needs of a ci process. it is therefore essential to develop information system that enables organizations to better manage information and provide a base for coordination of actions between different actors. this coordination is supported by the following motivations: 90 figure 1: transaction from a hierarchical structure to a functional global information infrastructure -the goals of the ci approach are interrelated and cannot be led separately -the need for information sharing between different actors -the sharing of knowledge gained during a process -the organization of the company in a cross‐ functional manner. due to the above mentioned motivations it’s important to move from a vertical architecture of information systems to a cross‐architecture which allows the information to reach the management overall. the cross‐architecture is based on a modular and scalable architecture structured around the projects of a company. the global information infrastructure will enable us to: reduce the number of vertical coordination by reducing management layers improve environmental monitoring opening‐up of cross‐communication achieve relationships based on complementary businesses, and make a better adaptation to market dynamics. according to the report of cigref “competitive intelligence and strategy” (2004) a portal of information management is currently the best tool to implement the concept and the culture of ci through a network. this portal is built around a software solution called here ci. the advantages of this type of information system are: project management monitoring information sharing custom-made interface collection that is more accurate and targeted processing, analysis, storage dissemination the coupling between the needs are identified in a process of ci which include different collaborative techniques from business intelligence such as workflow, groupware, data warehousing, data mining, text mining and visualization. this optimizes each step in ci process. (figure 2). it summarizes all of these techniques for each step in the ci process. the collection phase is usually through the use of databases, internet, search agents and search engine. the steps of processing can be supported by visualization tools, statistical analysis and data warehouses. the diffusion step may rely on for example push‐pull agents and emails. figure 2: the various techniques of ci 91 4. xplor: a multidimensional analysis model for ci our contribution consists of a proposal for an information system adapted to the needs of a ci approach as define above. the objective of this system is to provide a reference methodology in order to collect, process and analyze information. our system will observe and analyze the information of a decision problem in all dimensions. the approach combines two methods: knowledge discovering in text (kdt) and environmental scanning. figure 3: coupling of environmental scanning and kdt (ghalamallah, 2009) the model described is based on two main models: 1. a multidimensional representation of documents which can transfer qualitative data into quantitative. the objective of this model is to get a unified view of the documents collected. 2. a function model which aims to provide a set of generic and combinatory functions to build a different kinds of indicators needed for analysis. the cis proposed should manage the sharing of information between the different actors involved. the objective is to define a space of communication and information dissemination to provide a platform for collaboration and cooperation between different stakeholders. for this we define a user model adapted to each user profile. 4.1 planning activity the first activity of the proposed processes is planning. it is established from the informational problem defined by the users. the objective of this activity is to describe the process of guiding analysis. table 1: question 5w-1h (ghalamallah, 2009) we define this step by the method 5w‐1h: “what, why, who, when, where, how”. jakobiak (2006) developed a systemic approach for the creation of a ci project based on the 5w‐1h method (table 1). the principle of the 5w‐1h is based on following circumstances, the person, the fact, the place, the means and reasons, the manner and the time. in this way a company can provide a detailed analysis plan for the ci project. figure 4 : lifecycle of xplor model 92 we adapt this principle to describe the information needed and to guide the exploratory analysis. originally, the proposal for the question how was to describe the procedures and actions to realize when the project is implemented. in the context of our process, the question how will describe the indicators to be implemented to meet the raised informational problems. the products of the planning steps are: table 2: the products of the planning step in the planning phase an informational problem is described. this problem will be identified by the definition of its subject analysis. once the subject is defined, the user must identify the themes of analysis, plan analysis operations and identify the involved actors. the validation of the themes of analysis leads the user to define two key activities for each topic, such as source of information and a definition of analysis indicators. to enable an analysis, it’s necessary to identify sources of information. the activity of indentifying consists in listing any formal and informal sources that may contain important information about the subject for the study (el haddadi, dousset, berrada & loubier, 2010). 4.2 indicators for analysis the objective of this activity is to define indicators to be calculated and assessed. these indicators are intended to summarize and interpret the information environment of the analysis. at this level of activity we must introduce the different indicators related to the theme. each indicator was analyzed in order to identify target attributes, their granularity, their values and their relation. the aim of this decomposition is to clarify and describe the objects manipulated during processing to meet the indicator requirements. each object of this decomposition will guide us through the various activities of the proposed process. once all sub‐activities associated with the activity of planning are completed and validated, the results will be stored for later use. we define an information need by grade of n where a need n is defined as follows: n = < sa, obja, inda, acta, atta> -sa : is the overall context of the need for analysis a, -obja = < obj1, obj2, …, objm >, represents the objectives set for the subject sa. -inda = {< obji, < indi1, indi2, …, indin >>}, represents the indicators associated with each objective. -acta = {< indij, < actij1, actij2, …, actijp >>}, represents the actors identified for indicators set for a goal. -atta = {< actijk, < attijk1, attijk2, …, attijkq >>}, represent the attributes specified each actors. we define a hierarchy of concepts associated with the decomposition of indicators (figure 5). once all sub activities associated with the activity of planning are completed and validated, the result will be stored for later use. 4.3 multidimensional representation of documents the objectives of this structure are to study the evolution of interactions between variables and make figure 5: hierarchy of concepts associated with the specification requirements 93 projections in the future which is essential for making strategic decisions. our proposal is to define a unique structure of intermediate data between raw information and knowledge derived in the form of a generic data warehouse. the multidimensional structure is based on a three dimensional modeling. this allows defining dependency relationships between different elements of the mining structured corpus, body of variables, with the inclusion of timing, that is the time variable (figure 6). figure 6: example of dependency within threedimensional material and the temporal element for a corpus of documents whose structure extraction is: structureglobal extrac= < n° doc, date, author, journal,country, keywords, organism > we propose to build a three dimensional matrix which will define the dependency relationships that exist between the variables of the body by systematically incorporating the time variable. principle: our goal is to identify the dependent relationships that exist in the body between the different variables of the study. these relationships are defined by a co‐occurrence matrix. these matrixes indicate the simultaneous presence of the terms of two qualitative variables in a document. we adopt these matrixes by adding a third variable. the first two variables are qualitative associated with a multidimensional corpus. the third variable is always the time associated with the corpus, for example date and year. thus, the co‐ occurrence matrix is to indicate the presence of these three variables in a document (three‐dimensional structure). we call this matrix a cube. figure 7: data cube the cube can describe existing relationships in a corpus period. we identify two types of cubes: 1. a symmetric matrix: if we consider the simultaneous terms of a single variable and the time variable in a document the cube becomes symmetric. 2. a asymmetrical matrix: where we consider the presence of two distinct variables and the time variable in a document the cube becomes asymmetric. a corpus whose formal structure extraction is defined as: structureglobal extrac = < chp1g extrac , …, chpig extrac , …, chpjg extra >, chpig extrac corresponds to the element i of the structure. we define the types of three‐dimensional matrixes between elements of the structure as in table 3. table 3: type of matrix 94 we define the corpus associated with the multidimensional cube as: the structure of the multidimensional corpus (3d) scm3d defined as: scm3d = {< dimi, dimij, dimt, nbdoc ijt >} the multidimensional corpus cm3d defined as: cm3d = {< attx i , atty ij , attz ijt , atto ijt >} with: attx i ∈ di the set of attributes {att1 i , …, attp i } in dimension i « dimi », atty ij ∈ dj the set of attributes {att1 j , …, attq j } in dimension j associated with the dimension i i «dimij », attz ijt ∈ dt the set of attributes {att1 t , …, attr t } in dimension time « dimt », atto ijt ∈ nbd the set of attributes {att1 nb , …, attl nb } the number of documents in the three dimensions appear simultaneously. atto ijt = di x dj x dt [attx i , atty ij , attz ijt ] et atto ijt >= 1 5. xplor everywhere : competitive intelligence system for mobile xplor everywhere is a ci platform that performs global strategic analysis on aggregate or factual entries from online bibliographic databases, cdrom, internet or any other computerized source. through descriptive and statistics exploratory methods of data, xplor everywhere display in a very short time new strategic knowledge such as the identity of the actors, their reputation, their relationships, their sites of action, their mobility, emerging issues and concepts, terminology and promising fields. figure 8: xplor everywhere intelligence process 5.1 system architecture as shown in figure 8, strategic analysis and surveillance are the basic methodology of the process of information fusion in the xplor ci platform. the architecture of our platform consists of four main services as shown in figure 9: 95 figure 9: xplor everywhere architecture 1. monitoring service: a request is generated on a data source like a scientific database, patents database, rss and blogs to collect data depending on client’s needs. the collected data form the corpus. 2. homogenization and structuring service: diversity of data sources leads to heterogeneous data, format and language must be restructured. at the end, this service defines a unified view of documents in the corpus. 3. reporting service: reporting is the service responsible for presenting the analysis results to the decision‐makers according to the push strategy with iphone service (el haddadi, dousset & berrada, 2010), sms service, and e‐mail service or pull strategy with web site services. 4. security administration service: orthogonal to all three mentioned services, this service controls data access and ensures the preservation of privacy during the treatments (hatim, el haddadi, el bakkali, dousset & berrada, 2010). 5.2 reporting service the reporting is the last, important service to be accomplished in the ci process. on this level we propose four types of services, the phone service, the sms service, the web site service and the e‐mail service. with these different services, it is possible to access strategic information anywhere. in order to ease the navigability of the strategic information, we intend to integrate specific visualization techniques to each type of request like evolutionary histograms, geographical charts, social networks, profile networks, semantic networks and international networks (figure 10): figure 10: reporting service of xplor everywhere it is possible to navigate among three different types of networks. the social networks are based on relationships among the different authors, inventors, research teams, companies and the evolution of their relations. the semantic networks contain relationships among keywords in a domain and the evolution of research topics. the international networks are built on international collaboration between countries. 6. conclusion in this paper, we present a competitive intelligence system tool based on a multidimensional analysis model. a lot of strategic information comes from the relationship between and relevance of knowledge extracted, which often depends on consideration of data evolution and their interactions. in this paper we have defined a model for these relationship forms. our cis is dedicated to cover all stages of discovery, extraction and data management: without forgetting the criteria by which we get to handle any type of information, both formal and informal. with xplor and xplor everywhere, which are still mdeos but potentially soon to be commercialized, we completed an entire reporting service, including the aspect of mobility (smartphone application). with the system it’s possible to view updated information as we gain access to strategic database servers in real‐ time and daily feeds by observers. with this application it is now easy to enter information at trade shows, after customer visits or meetings. our plan for future studies is to continue our experiments on different types of relationships in order to propose a unified model to better generate and organize knowledge for companies. 96 references bouaka, n. 2 0 0 4 . développement d’un modèle pour l’explication d’un problème décisionnel : un outil d’aide à la décision dans un contexte d’intelligence economique. thèse de doctorat de l’université nancy 2. el haddadi, a., dousset, b., berrada, i., & loubier, i. 2010. les multi‐sources dans un contexte d’intelligence economique, egc, p a1‐125 a1‐ 136. el haddadi, dousset, b., & berrada, i. 2010. xplor everywhere – a tool for competitive intelligence on the web and mobile, vsst. 25‐29 octobre, toulouse france. d a v i d , a . & thiery, o. 2002. application of “equa2te” architecture. economic intelligence. ghalamallah, i.. 2009. proposition d’un modèle d’analyse exploratoire multidimensionnelle dans un contexte d’intelligence economique,doctorat de l’université de toulouse, 18 décembre. gilad, b. 2008. the future of competitive intelligence, contest for the profession’s soul, competitive intelligence magazine, 11(5), 22. haags, s. 2006. management information systems for the information age, mcgraw‐hill ryerson. hatim, h., el haddadi, a., el bakkali, h., dousset, b. & berrada, i. 2010. “approche générique de contrôle d’accés aux donénes et aux traitements dans une plate‐forme d’intelligence économique“, colloque veille stratégique et 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colloque européen d'intelligence economique, poitiers futuroscope, escem poitiers, p. 414‐427, poitiers, france. seligman p.s., wijers g.m., sol h.g. 1989. analyzing the structure of i.s. methodologies, an alternative approach, in proceedings of the conference in information systems, the netherlands. vedder r. g., vanecek m. t., guynes c. s. and cappel j. j. 1999. ceo and cio perspectives on competitive intelligence, communications of the acm, 42, 8. 21 interactive methods for graph exploration eloïse loubier i.r.i.t. (institut de recherche en informatique de toulouse), 118, route de narbonne, 31062 toulouse cedex 9 received 15 december 2010; received in revised form 25 february 2011; accepted 20 march 2012 abstract: in a strategic watch context, visualization of relational data allows transformation, coding and visualization of great data quantities. access to interactive, adjustable functionalities by the user would facilitate the domination and the precision of the analysis. from this point of view, the visugraph tool allows visualization and exploration of relational data, by the way of applicable and controllable methods of analysis. the main interactive visugraph functionalities are presented and illustrated, revealing their importance in graph exploration. the user is the heart of the tool; he or she fully controls the representation and directs the analysis according to own needs. keywords: grap exploration, strategic watch, visualization, business intelligence 1. introduction complex and bulky data sources do not facilitate relations identification and relevant tendencies. for the majority of users, useful and exploitable information search constitutes a long and tiresome process. it requires many efforts for data processing specialists who are charged to treat the requests and to generate the ad hoc reports/ratios. in a strategic watch context, analysts must be able to explore large volumes of data in an interactive way. they should be able to study tendencies, to test various approaches and especially to isolate invaluable information bringing a competitive advantage. relational data visualization allows transformation, coding and effective chart of great data volumes. this technique offers to the user a clear and readable representation of information, initially difficult of access. analysis methods of relevant data allowing exploration of the data complete this representation. thus, the base of any proposal of visualization of relational data tool supposes an interest in the three following fundamental aspects:  nature of the data represented,  way in which the components of the graph are exploited to transcribe these data, available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 21-31 https://ojs.hh.se/ 22  perception of these components by the user. the visualization objective is not simply limited to product pre-set charts, which cannot be changed by the user. indeed, an important criterion for a good visualization tool is the possibility for the user to control the representation in order to include/understand the information space and to interact with the system. visualization on this point is the concern of the field of man-machine interaction. in this article, the author presents a model of interactive visualization of relational data, named visugraph (loubier and dousset 2008). communication with the user and the system is the main interest of concern in this context as a proposal of a tool of assistance to the analysis of relational data. this information analysis approach is based on visualization interfaces. it allows data exploration by rich charts and interaction modes adapted to analyst tasks. visualization’s components and navigation help the analyst and more particularly “the watcher”, taking part in the technology’s development for a framework of economic, strategic and competitive intelligence. under the control of an expert, who chooses a suitable mode of representation (“semiologyand esthetics” rules), relational data are represented in graph form. the visualization purpose is to give a precise idea of the data and their relations. the objective is to propose an information representation allowing identification, analysis and restitution of the strategic structures. this system makes it possible to detect different connections and to analyse at a specific time the actors of a field and the concepts which they use. this tool is supplemented by processes of interactive graph analysis, which make it possible for the user to control his or her representation. in this article, we insist on visugraph tool’s interactive functionalities and particularly on the targeted and comparative study of nodes. initially, the stakes of data and in particular of cognition visualization are presented, as well as principal application scopes. in a second phase, the relational data visualization methodology proposed in the context of visugraph is exposed. the access of traditional analysis methods makes it possible to isolate particular nodes and obtain paramount information which enriches and facilitates the graphic analysis. a concrete example illustrates the effectiveness of such a tool for visualization. this example makes it possible to analyze complex interactions networks, the actors/fields and evolution by the analyses of graph structure. it is possible to detect the various tendencies, the strong signals and the weak signals. 2. stakes of the visualization of data since about fifteen years, under the impulse of researchers like card, mackinlay and shneiderman (1999), spence (2000) or ware (2000), information visualization has become a research orientation with gravitas. many contributions tried to approach available represented formalizations to restore the spacetime processes (langran 1993; gayte et al. 1997; frank, rapper and cheylan 2001). recently geographers and cartographers were also interested with these questions (passover 2007; josselin and fabrikant 2003). “the principle of information visualization is to use the power of the computer tools to represent effectively, from a cognitive point of view, abstract data which do not have necessarily usual physical representations. these techniques, which aim’ at amplifying cognition via perception, aim in particular to facilitate the discovery and the creation of ideas starting from masses of data difficult to apprehend from the quantity or the complexity of the information which they contain. ” (fekete and lecolinet 2006).  many techniques of information visualization have been proposed over the fifteen last years, as is shown in the work to identify 6 leading causes of cognition amplification by visualization (card, mackinlay and shneiderman 1999):  reduction of the cognitive resources mobilized by the user to process and analyze the data (interaction raised with the user, perception carried out in parallel and accessibility to a great quantity of information),  simplification of information search (many data in a small space, regrouping of data for example by criteria),  increasing structures detection possibilities (relations between significant data, regroupings, strategic positions and centrality),  “perceptual inference” using visual perception (problems appear using a visual representation), 23  monitoring of the events (changes of structures, appearance or movement in the reasons and regroupings),  means of handling data (interactive navigation). thus, visualization must make it possible to discover, to propose explanations or to take decisions. these actions can be done based on specific reasons (clusters, tendencies and emergences) or on the whole of elements or on isolated elements. visualization technologies make it possible to effectively communicate information via cognitive charts. this kind of representation facilitates the discovery of knowledge by the way of charts resulting from the analysis of a corpus (balmisse 2005). many techniques of data visualization were proposed to date in various applications such as clinical data study (shahar and cheng 1999), geographical data (maceachren et al. 1998), hydrometric data (kramer and jozsa 1998), personal data (such as those contained in a medical file) (liking et al. 1996) and at various ends such as significant tendencies research (harbour and al 2000), exploration of programs traces (renieris and reiss 1999), data analysis of logs (hochheiser and schneiderman 2002), temporal abstractions representation (shahar and cheng 2000) or the visualization of temporal association rules (rainsford and roddick 2000). analysis of relational information evolution is mainly based on the visualization of dynamic graphs. many researchers developed display systems of networks (di battista et al. 1999), by taking into account a cartography of connectivity related to the internet, the networks of phone calls, the networks of quotation as well as the progressive visualization of the evolutionary fields of knowledge. we study the evolution of research themes, information visualization, according to kapusova (2004), who combines aspects of scientific visualization, man-machine interfaces (human-computer interfaces), excavation of data (mining dated), imagery and graphs. for (fekete and lecolinet 2006) information visualization was detached from three related fields: the manmachine interaction, the analysis statistics and cartography, but also scientific visualization. thus, the distinction must be made between the visualization which refers to the process which leads to a chart and the interactive information chart which milked the means of interactions which use information charts. the user’s role in the tools for data visualization is a subject of major concern (grinstein 1996; fayyad, grinstein and wierse 2002). thus interactive visualization of relational data brings to the user an artificial substrate which transcribes a great amount of information. it makes function of support to its knowledge and its intuition to enable him or her to discover new relations, to help with decision making and to allow anticipation, as well as for the evolution of these data. in visual excavation of data, the interaction materializes the loop of feedback between the user and the visual aids (keim and kriegel 1996). a majority of visualization tools offer the access to powerful statistical methods of analysis but these methods are not really interactive and users can only seldom direct the totality of the chart. 3. methodology visugraph is a data visualization tool. it is developed in java (loubier and dousset 2008). the list of alliances is regarded as a document population. two actors represented graphically in the form of nodes are considered concurrent if they are present in the same alliance (there can be more than two actors per alliance). the whole of these co-occurrences is counted in a square matrix crossing, two to two, as far as the actors are concerned. the data are represented in a graph simple g characterized by two units: a unit v = {v1,v2,…,vn} whose elements are called tops, and a unit e = {e1,e2,…,em}, left the unit of the parts with two elements of v, which are called edges. g will be noted g = (v, e). g is a graph not directed (there is no distinction between (u, v) and (v, u) for u and v in v) and as simple (there is no loop (v, v) in e and there exists more than one bond between two nodes). recourse to visual artifices makes it possible to represent information as well as possible, by the means of a particular semiology on the level of tops form and colors used. in visugraph, data are represented in circle form where size is proportional to the value of the metric. bonds are represented by segments binding two nodes, coded according to color. a. interactivity on semiology graphic visualization comprehension is based on construction rules of a symbolic system. study of the signs and their significance is called semiology. it is also based on a codified use of the writings and on general aesthetic principles. bertin (1970) is regarded as the initiator in term of cartography of information. he is interested in construction of visualization by graphic symbols. 24 graphic semiology is based on:  significance of the drawings,  choice of legends, symbols, icons,  methodology to transmit a visual message. semiology quality goes with the possibility for the user to be able to control it fully. with regard to the variation of color, value is a variation of luminous intensity of darkest to the most clear, or conversely. it translates an order relation and differences (quantitative relation). however, our capacity to be recognized is much more limited than our aptitude to be appreciated:  on the one hand, differential sensitivity of the eye to luminous energy is not directly proportional to the intensity of flow. the appreciation of the ranges is lower in clear colors than in the beds,  in addition, our differential chromatic sensitivity is not uniform and specific to each one.  the tops and the edges being balanced, initially, the color makes it possible to code the value of the metric of each element of the graphs. the tops/edges of stronger metrics will be colored by strong intensity and conversely. the user can accentuate contrasts of colors used. thus, for coding by the edges color, a measurable rule is placed at the disposal of the user in order to enable him or her to attenuate or increase the intensity of the color. it is the same for labelling of the data which size and intensity can be regulated, thus making it possible to fully control the importance of this information. indeed big size and strong intensity make visualization less readable than if they are of small size and homogeneous color with the prime coat of the representation. in the following figure, five tops are extracted from a total graph. the initial police force used here as an example is based on small size and low intensity, in order not to deteriorate the legibility of the graph. the graph of the medium results comes from the increase in the value of the rules of graduation and of the intensity of the police force and the bonds between them, but also of the size of the police force. the graph of right-hand side results from an increase even more important in the values of these rules. figure 1: interactivity on the semiology of the graph. b. attraction and répulsion forces the base of any graph analysis is based on the clearness and the legibility of the representation. in the case of a no-planar graph, the number of edges crossings can quickly make the graph illegible and complicate its interpretation. much work was carried with powerful algorithms of directed placement by the means of forces (fdp: “force directed placement”) (tutte 1963; eades 1984; kamada and kawai 1989; fruchterman and reingold 1991). the algorithm fdp proposed in visugraph is based on fruchterman and reingold’s (1991) work and makes it possible for the user to intervene on the application of the forces, by increasing or decreasing them by the skew of two scales, the attraction force or of repulsion. the attraction force between the tops can be proportional to the force of the bond between them. the attraction force between two tops υi and υj is given by: (1) 25 the factor k is calculated according to a drawing surface and of the tops number. duv is the distance between u and v in the drawing. corresponds to the scale value for the attraction divided by two. it is used to define the attraction degree between two tops. k makes it possible to represent every edge in the representation window and not out of it. l represents the window length, l the width and nbtops corresponds to the number of visible tops of the graph. (2) if the tops u, v are not connected by an edge then ƒa (u, v) = 0. repulsion force between two tops u, v is defined by: (3) corresponds to the value of the scale corresponding to the repulsion, allowing to interact on the repulsion; it makes it possible to define the repulsion degree between two tops u and v. thus, the higher the attraction threshold chosen by the user, the more the dependent tops attract themselves, supporting the total drawing of the graph structure to the detriment of inter-nodes relations. in the same way, the more the repulsion threshold is raised, the more the structure is widened, the non-dependent tops are pushed back and those united by an edge are more distinguished, allowing us to obtain more burst structure. the combination of the parameter setting of these two forces leads to a more readable representation, as shown in the figure 2, where the graph (1) is a planar and on which no algorithm fdp was not applied; the graph (2) is the result of the application of our algorithm for which the rules of graduation for attraction and the repulsion were positioned, here with median values (5 for each one on scales from 1 to 10). c. transitivity navigation in the initial graph is often too complex. in order to carry out it, it is possible to work on a subgraph. we start from a particular top selected in the complete graph and gradually extend the graph by transitivity. this technique allows, by a change of x-ray, to concentrate on a relevant extract resulting from targeted information (actor, key word and concept). measurements of degree centrality and constraint privilege the local point of view. more precisely, a data is known as a power station if it is strongly connected to the other members of the graph. the concept of centrality makes it possible to specify the dominant position of an actor, or a node in the network (freeman 1979). we base our work on the algorithm of floyd (1962). it is based on a generalization to the case of valued graphs by a calculation algorithm of graph transitive closing, discovered about simultaneously in france by roy (1959) and in the united states by warshall (1962). the transitive closing of a graph g= (x, a) is the minimal transitive relation containing the relation (x, a), it acts of a graph g*= (x, a*) such as (x, y) ∈ a* if and only if there exists a way f in g beginning by x and ending by y. the calculation of transitive closing makes it possible to answer the questions concerning the existence of ways between x and y in g and this for any couple of tops (x, y). (x, a*) calculation is carried out by iteration of the basic operation ϕx (a) which adds the arcs (y, z), and asks is a predecessor of x and z one of its successors. more formally: (4) definition : for any top x, (5) for any couple of top (x, y), (6) transitive closing a* is given by: (7) in our contribution, the user selects a specific node in the graph. other tops are masked and only the initially selected node remains visible. by the means of a scale, the change of transitivity is carried out. the first step indicates the direct neighbours of the node, who are then visible, like the bond with the initial node. the more the value of the scale is increased, the more the threshold of transitivity is important. this study of the structure of the graph and in particular of the topology of a particular node makes it possible to qualify this last and to study 26 its role within the whole of the studied population. if transitivity reveals many direct links towards other data this shows that the major importance of the data represented is revealed. sub graph studies by transitivity make it possible to carry out a more pointed analysis and to detect the most important actors. however, it is interesting to compare the typology of several important graph actors in order to be able to compare them with the same element:  the number of bonds with direct neighbours (transitivity of first threshold) and it importance at the local level,  importance of the basic data studied within the total graph.  it is necessary to preserve an image of the first threshold of transitivity for each studied top. we add to visugraph a functionality allowing preserving a precise image of the top transitivity at one specific moment in the form of a small independent window. it is located near the main visualization window. the comparison of different sub graphs structure resulting from transitivity makes it possible to distinguish remarkable elements. in the following figure, the studied data are authors having taken part in a scientific congress on the topic of strategic watch. in this article context, the data are used at the end to do illustration of interactive methods, not as a complete analysis of this congress. in order to facilitate the graph legibility, we reduced to the maximum the size of wording. based on a global graph representation, we can see that stronger centrality data are distinguished and the sub graphs based on these data are extracted in order to be able to compare them. the higher graph corresponds to the total graph of the whole of the dataset. the interest is related to a node in particular which appears in the total graph which is strongly connected to the other tops. it is then interesting to calculate the transitive closing of this top and to study the structure of it. in this way, the top is isolated (3), by masking of the other tops. in the second time, using the change of graduation of the rule of transitivity, the direct neighbours of this top are obtained (4). the important number of direct connections of this node is remarkable, which means that the author is a paramount actor within his team and that he collaborates frequently with other researchers. by increasing the threshold of transitivity, we obtain the graph (5), representing the maximum threshold of transitivity for this top. comparison between this visualization and the total graph reveals the similarity between the latter. the author initially selected can thus be qualified as being one of the elements at the origin of the total structure of the graph, i.e. a very important author. 27 figure 2: extraction starting from the total graph of a specific top and calculation of its transitivity. d. filtering the filtering concept is based on the metric values. it consists in preserving only the tops and the edges of the associated graph with the values higher or equal to a threshold, according to a value fixed by the user via a scale. this procedure reveals the most representative tops, as well as the important components of the structure. the visualization of the result after filtering can be made by masking (total) adjacent edges and consequently their tops, having a value of metric lower than the threshold defined by the user. this kind of representation extracts the elements representative of the graph in terms of value of the metric (loubier and dousset 2008). e. k-core the decomposition in k-core (batagelj and zaversnik, 2002) consists in identifying particular subsets of the graph called k-core. consider a graph g = (v, e) with |v| = n tops and |e| = e edges. a k-core is defined as follows: definition a subgraph h = g (c, e|c) armature by the subset c⊆v is a k-core or a core of order k if and only if and h is a maximum subset with this property. the related subset is characterized by a “coreness” ce. it forms a cluster (a community) within the meaning of (alvarez and al, 2005). the k-core is obtained by recursive pruning of the nodes which have a smaller degree than k. the graph remaining contains only tops of degree ≥ k. k-core decomposition makes it possible to obtain a hierarchical partitioning of the tops such as the whole of coreness 1 is in top of the hierarchy and the maximum whole of coreness is at the bottom of the hierarchy. this partition depends on the degree of each top and 29 the degrees in the vicinity. complexity in time of the algorithm of decomposition in a k-core of alvarez-hamelin et al. (2005) is o (n + m) where n and m are respectively the number of nodes and edges in the network. applied to visugraph, the k-core is calculated starting from a threshold fixed by the user, via a scale. the more this threshold increases, the higher the coreness is. the obtained graph corresponds to decomposition in k-core, according to the threshold value chosen, via a scale. in the following figure, the k-core is applied for one k = 5, which means that only the nodes having at least five bonds are preserved. the results obtained allow:  to visualize the main actors having collaborated;  to distinguish the various teams, i.e. all the actors having to work more together. thus several different communities are distinguished, by the means of this method. it is noted that the global graph contains three large important teams. within each one of these groups, one distinguishes the major actors from each team, who are in the middle of the connections and thus the absence would divide the team, such as for example the nodes circled in the graph of the bottom of figure 2. figur 3: k-core (k=5). 30 4. conclusion in this article, we presented several interactive functionalities of the temporal data visualization tool, named visugraph. user point of views and user directives are taken into account, on the level of his or her needs but also on the level of its intervention when handling is dominant in the design of a tool of assistance to the analysis and for decision making. the tool and the visualization should not be fixed. the user must be free to be able to control fully his or her representation while intervening on the various statistical methods suggested, but also on the semiology suggested by the tool. within the framework of this article, we insist on the statistical analysis functionalities suggested by the visugraph tool, such as:  the tops directed placements algorithm,  transitivity,  filtering,  k-core. these various methods facilitate and improve exploration and graph structure analysis, like the particular study of specific nodes. our proposal is suggested by the interactivity offered for these traditional statistics methods. this interactivity between user and system makes it possible to control fully the chart, by means of scales and thus to target its analysis in order to obtain more precision as for the structure of the graph. thus, visugraph tool answers the principal ideas proposed by (card, mackinlay and shneiderman 1999) such as:  cognitive resources reduction via an interaction raised with user,  representation in graphic form of great volumes of data,  increase of structures detection by the way of precise and interactive statistical methods,  means of handling the data representation by semiology control. references alvarez-hamelin, j.i., dall’asta, l., barrat, a. and vespignani, a. 2005. k-core decomposition: a tool for the visualization of large scale networks. computing research repository: 41, 5255. 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http://tecfaseed.unige.ch/staf18/modules/epbljolan/uploads/proj15/paper%20(et%20dispositif)6.xml http://tecfaseed.unige.ch/staf18/modules/epbljolan/uploads/proj15/paper%20(et%20dispositif)6.xml http://www.irit.fr/publications.php3?code=3983&nom=loubier%20elo%c3%afse http://www.irit.fr/publications.php3?code=114&nom=dousset%20bernard ftp://ftp.irit.fr/irit/sig/2008_esrel_ld.pdf ftp://ftp.irit.fr/irit/sig/2008_esrel_ld.pdf http://en.wikipedia.org/wiki/journal_of_the_acm vol9no1paper2 to cite this article: bleoju, g. & capatina, a. (2019) enhancing competitive response to market challenges with a strategic intelligence maturity model. journal of intelligence studies in business. 9 (1) 17-27. article url: https://ojs.hh.se/index.php/jisib/article/view/369 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index enhancing competitive response to market challenges with a strategic intelligence maturity model gianita bleojua*, alexandru capatinaa adunarea de jos, university of galati, romania *gianita.b@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: exploring new ways to utilise the market intelligence (mi) function in corporate decisions: case opinion mining of nuclear power enhancing competitive response to market challenges with a strategic intelligence maturity model gianita bleoju and alexandru capatina pp. 17-27 how managers stay informed about the surrounding world journal of intelligence studies in business v o l 9 , n o 1 , 2 0 1 9 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 9, no. 1 2019 klaus solberg søilena pp. 28-35 kalle petteri nuortimo and pp. 5-16 janne härkönen enhancing competitive response to market challenges with a strategic intelligence maturity model gianita bleojua*, alexandru capatinaa adunarea de jos, university of galati, romania corresponding author (*): gianita.b@gmail.com received 4 february 2019 accepted 3 may 2019 abstract tracking meaningful insights about companies’ exposures to high risk of failure in competitive markets, intelligence studies in business should listen to practitioners’ signals and act in providing decision making support to systematic scanning for valuable information. in order to gain robustness in confronting unexpected events in real markets, companies should adopt an unstructured learning perspective with maturity assessment tools, while purposely pooling strategic intelligence (si) skills. by bridging organizational maturity modeling with a future orientation stream of literature and intelligence studies in business, this conceptual research aims to highlight a genuine strategic intelligence capability maturity model (si cmm), capable of purposely addressing the challenge of aligning detective and anticipatory organizational capabilities. the conceptual model highlights the degree of preparedness of four si profiles behaviors (intelligence provider, vigilant learner, opportunity captor and opportunity defender – previously developed by the authors) against seven levels of maturity. the si cmm framework outlines both conditioned scanning capabilities (the first five si readiness levels) and enablers to anticipate future market trends (the last two si readiness levels). the novel approach of the strategic intelligence readiness framework supplies companies with a valuable organizational learning tool to close the skills gap through an opportunity provider profile. the main features lie in coordination and sharing si common knowledge to enhance preparedness in forward-looking competitive pressures. the conceptual framework invites academia and the community of intelligence experts in business to evaluate the relevance of the new conceptualization, clarity of constructs and complementary nature of correlation and causation with the proposed si cmm model. keywords capability maturity model, intelligence provider, opportunity captor, opportunity defender, strategic intelligence, vigilant learner “if we are blinded by darkness, we are also blinded by light” annie dillard 1. introduction in the context of unpredictable changes, which have a huge impact on firms’ competitiveness, providing managerial tools to assess organizational preparedness for the future becomes compulsory. the performance gaps registered between competitors are due to the different degree of organizational preparedness to anticipate and react to future market trends. managerial proficiency in understanding and addressing market challenges lies with scanning for relevant information, reacting to ambiguity, developing peripheral vision and overcoming cognitive bias in weak signal journal of intelligence studies in business vol. 9, no. 1 (2019) pp. 17-27 open access: freely available at: https://ojs.hh.se/ 18 interpretation. in order to enhance future organizational preparedness, core organizational skills to embed knowledge need to be addressed and responses need to be provided, confronting the demand of decisionmakers for strategic intelligence (si) training with developing anticipative capability. the changing patterns of competition and its impact over the organizational capabilities’ alignment continue to be a challenge for scholars and practitioners in business and management. in order to deal with increasing complexity and volatility of the competitive landscape, organizations should inquire about the knowledge and skills they must develop for the managerial future orientation. current patterns of strategic behaviour are still dominated by standardized or specific models and tools which are foreseeable to deter gain from innovation and change in future markets. therefore, strategic intelligence core skills should be trained to support management decisions in providing adjustable learning tools to successfully leverage dynamic capabilities of the firms. in order to provide anticipative managerial training, a strategic intelligence framework to assess the degree of organizational preparedness is hosting a learning approach to si maturity with: • conceptual training: knowledge acquisition oriented, to match si missing skills; • interpretative and iterative: expected proficiency in knowledge sharing; knowledge transfer oriented of core si skills; actionability trough collective learning experimentation; • future oriented behavior training: knowledge capitalization oriented to enhance competitive identity of si performers; influencing the future competitive environment; developing a si supportive culture. the strategic intelligence capability maturity model (si cmm) articulates actionable organizational knowledge and provides guidelines for managerial practice to share si practices about future competitive pressure anticipation in order to identify the specific si core skills that need to be improved. the value added of the si cmm resides on an interrelated body of knowledge of strategic intelligence and competitive behavior, valorizes our up-to-date benchmarking insights over the key topics on organizational alignment capabilities to environment turbulence and underlines knowledge discovery vocation as a si unique feature to influence organizational intelligence maturity. in the following sections, the main approaches and outcomes in the field of intervention, conceptualization, constructed experimentation and adjusting within the multi-framing approach of strategic intelligence profiling are exposed, as well as the methodological matching. 2. theoretical background the value of intelligence in influencing managerial thinking builds upon business practice reports about the lack of perspectives on strategic intelligence capability importance to assist decision-makers with scenarios of aligning intelligence agendas with the anticipation of competitive pressures (gilad, 2011). developing the capability to design interpretive frameworks is particularly important, while managerial strategic decision has to anticipate future competitive pressures with unanalyzable environments. a conceptual model of collective creation of meaning emphasizes the principles of puzzle method and provides an anticipative scanning process (anticipative strategic scanning and collective intelligence) to enrich the literature and business collection of cases (lesca and lesca, 2011). qualified foresight capability is approached with a future orientation stream of literature and intelligence studies in business to enhance managerial relevance of various business toolkits to confront competitive environment complexity and volatility. intelligence studies in business highlights the importance of designing support decision making tools to share practitioners’ concerns about interpreting relevant information regarding the external environment, affecting strategic positioning. intelligence analysis toolsets, cross-disciplinary studies, foresight and industry-specific case studies are listed as uncovered areas of interest among respondents’ perceptions. the definition of ci studies in business continues to track confusion with implications in formulating precise responses to practitioners’ needs. intelligence studies in business should focus on the content of managerial training to enhance their knowledge about relevant external influences, through ethically gathering 19 actionable information. moreover, the industry-specific focus deals with the necessity to develop anticipative tools to mitigate failures and crises (søilen, 2016). furthermore, intelligence studies should help to articulate need-to-know, strong signals and trends affecting organizational intelligence preparedness. the body of knowledge should be enriched with relevant evidence of various applications confronted to real competitive context, where we expect that learning by doing bridges what we see with what we do not see about the future to generate relevant intelligence training content (søilen, 2018). enhancing competitive responses to market challenges requires managerial proficiency not only in distinguishing between key drivers of success in current markets but to anticipate future changes in complex and volatile environments. taking leadership to steer organizations in an unstable competitive landscape needs a high level of preparedness in challenges to the current status quo, mainly if successful. the market leader position is under serious threat once ordinary capabilities are misperceived as extraordinary, as the risk of non-replicating the business success is very high. new challenges arise from ambiguity and volatility, influencing leadership to change the current business model; therefore, developing new dynamic capabilities emerges. an insightful approach organizes dynamic capabilities around three pillars: sensing change, seizing opportunities and transforming the business model, which are considered critical in enhancing competitive response within volatile, uncertain, complex and ambiguous future environments. proactively upgrading key features of the current business model is decisive to ensure the successful organizational fitness to vuca environments, while reframing strategic leadership on core skills pillars is listed: anticipate, challenge, interpret, decide, align and learn. the real challenge for organizational preparedness is to reinvent the business model through purposely combining sensing, seizing and transformation to comply with unforeseeable consequences. (shoemaker et al., 2018). competitive positioning relies upon an organizational learning approach of interpreting the environment with test makers actively searching for information and test avoiders with passively interpreting information within limits. four categories of interpreting behavior are considered: enacting and discovering labels intrusive organizations, while conditioned viewing and undirected viewing labels non-intrusive organizations (daft and weick, 1984). intelligence studies in business builds upon the above seminal work and focuses upon an organizational learning approach to improve managerial interpretive skills to cope with the environment. the foresight maturity model (rohrbeck, 2010) adapts and develops the three-step model of managerial acting upon weak signals on emerging change: scanning or data gathering, interpretation of the meaning of data and enacting through learning (daft and weick, 1984). the future orientation stream of literature provides useful insights about measuring corporate foresight, maturity to reach future preparedness status, and labeled vigilant future prepared status at maturity. valuable insight features continuously perceiving through change sensors, systematically prospecting for anticipating unexpected changes, followed by probing scenarios to shape the rules of competition, as core skills to be developed (rohrbeck, 2010). the conceptual framework underlines five capability dimensions against which the respondent is assessing the level of organizational future orientation (ofo) readiness: information usage, method sophistication, people and networks, organization and culture. the quantitative benchmark research assessed the level future preparedness with a 300 multinationals longitudinal study, 120 interviews among high and medium management levels, followed by 20 case studies across industries. the study defines an optimum level of future preparedness when its corporate foresight need level is matched by its corporate foresight maturity level, with the results clustering corporate foresight practices with the sample as follows: vigilant (24%), deficiencies (26%) and in danger (50%) (rohrbeck et al., 2018). enhancing competitive response to volatile and uncertain environment challenges requires managerial core skills to understand, interpret and enact upon competitor analysis and market selection. mapping competitive pressure in different industries gives valuable insights about how to make relevant a current position to future positioning when anticipating change patterns of competition. each firm will be uniquely affected by its capacity to decide upon markets selection. therefore, to enhance the competitive 20 response, reconfiguration with alliances and targeting will be undertaken. based on common strategic intent, five types of alliances are labelled: surrogate attackers, critical supporters, passive supporters, flank protectors or strategic umbrellas will destabilize and redirect the pressure system (d’aveni, 2002). relying upon measuring the managers’ perceptions about competitive dynamics, one significant study informs about limited capability to identify and act upon sensors, once opportunities and threats dominate competitive response decisions. reflections upon developing organizational capabilities shapes plausible competitive response behavior through an experimental learning approach to align internal and external influences in anticipating early changing patterns of competition in future markets (fouskas and drossos, 2010). exploring new markets is particularly challenging for capturing opportunities, while previous performance is non-repeatable. to address the concern, a useful response lies with mapping corporate foresight activities to overcome vulnerabilities in coping with uncertainty. experimenting recipes with multiple iterations of perceiving, prospecting and probing in bottom of the pyramid (bop) segments finds distant opportunities, crucial for capitalize upon them (højland and rohrbeck, 2018). differentiation in future markets becomes particularly difficult when it comes to managing innovation-related benefits among partners engaged in coopetition, as they are sharing a common knowledge base. seeking offer differentiation colludes with a technological coopetition business model and peculiar concerns arise when analyzing radical innovation vs incremental improvements for individual firms engaged in coopetition. conflictive objectives derived from the propensity to share vs protect practices to embed relevant knowledge has implications for business model transformation. return on evidence of a cross-industrial survey in finnish markets informs about the emergence of a radical business model innovation to preserve the offer differentiation outcome within collaboration among competitors (ritala and sainio, 2014). one recent study proposes a comparative three-level (early stage ci, mid-level ci capability, world-class ci) capability ci maturity model with eight dimensions: strategy and culture, relationship with management, structure, resources, system, deliverables and capabilities, analytical products and ci use, and impact. the comparative model aims at enabling benchmarking across industries and returns on empirical evidence underlines the necessity of a holistic model to track each company’s ci practices to reach maturity (oubric et al., 2018). business and intelligence communities are seeking relevant guidance to act upon organizational competitive capital and training should provide external expertise support to focus on defining the scope of a business opportunity (liebowitz, 2006). developing competitive capital lies with selecting facilitators and enablers from organizational-environment interaction. organizations must go beyond mere awareness of si practice benefits to engaging in purposely pooling strategic intelligence skills. in order to cope with a turbulent environment, managerial practices should be enriched with engaging in sensing and seizing change, and acting before competition. moreover, a genuine learning approach to collective intelligence practices would overcome cognitive dissonance in strategic decision and activate interpretative and iterative loops to enrich si core skills for influencing future markets. si cultural identity embraces collective filtering to develop insights about distant opportunities, while strategic leadership will take lead in exploiting competitive capital though openmindedness and learning from consequential mistake experimentation. 2. strategic intelligence capability maturity model (si cmm) the conceptual model highlights the degree of preparedness of four si profile’s behaviors (intelligence provider, vigilant learner, opportunity captor and opportunity defender) against seven levels of maturity. the si cmm framework outlines both conditioned scanning capabilities (the first five si readiness levels) and enablers to anticipate future market trends (the last two si readiness levels). si cmm defines a systematic approach to pooling si core skills, leverages si expertise to 21 combine conditions affecting competitive response and enables organizational intelligence to influence future markets (figure 1). si cmm antecedents reveal volatility, uncertainty, complexity, ambiguity and competitive pressure at the external level, while dynamic capabilities, test makers and test avoiders are related to the internal level. si cmm novelty resides on the knowledge discovery vocation and the competitive capital collection cases return on experiences to share within the community or practitioners to match the future need of si core skills upgrading, while its scope deals with targeting profile-specific needs for updating si knowledge. si cmm moderators aims to assess the lack of managerial anticipative skills associated with each si profile identity. this is the coordination and sharing of si common knowledge to enhance preparedness in forward-looking competitive pressures and the development of a supportive culture to enable organizational preparedness for assisted learning consultancy-based (conceptual training), business mentoring (problem solving), and procedural animators (action oriented). si cmm outcomes reveals profile-specific roadmaps to improve si core skills tailored to four si profiles, previously developed within exploratory research conducted by the authors (figure 2). si core skills acquisition assisted learning consolidates profile-specific si competitive identity through tailored interventions and enhances profile-specific capability to si process self-improvements. drawing upon organizational intrusiveness and matching test makers vs test avoiders (daft and weick, 1984), profile-specific si performance improvement with each maturity level assessment will focus on an iterative and interpretive approach to learning progress, tailored to each si profile. the intelligence provider (ip) develops core skills to distinguish between market challenges influencing organizational fitness, explores strategic trajectories to gain si cmm novelty and scope antecedents moderators outcomes figure 1 key elements of si cmm. figure 2 the strategic intelligence profiling tool. figure reprinted from bleoju, g., & capatina, a. (2015). leveraging organizational knowledge vision through strategic intelligence profiling-the case of the romanian software industry. journal of intelligence studies in business 5(2). 22 proficiency in noise and consequential mistakes recognition, and pursues risk of failure minimization. moreover, ip is capable of engaging systematic scanning of the environment with the specific purpose of blind spot recognition, while developing scenarios of their impact. vigilant learner (vl) leverages contextdependent knowledge gain to permanent upgrade case-based experience in discerning opportunities and threats, and adopts ready-toadjust behavior in confronting future competitive contexts. opportunity captor (oc) pursues market challenger behavior by leveraging learning from imprinted consequential mistakes to recognize similarities in avoiding future failures through sensing changes and filtering among capturable challenges. opportunity defender (od) focuses on market follower capability to protect market shares though systematicly avoiding consequential mistakes. the si cmm builds upon previous informative pilot testing of the si profiling tool against four variables with high impact on organizational knowledge: strategic scope, organizational agility, organizational cultural change process and the approach of competitors. the in-depth analysis of the si cmm framework empirical testing outlines the si profile specific core skills to develop in order to overcome managerial lack of anticipative skills (table 1). si cmm claims to overcome the rigidity of a traditional maturity framework, being designed as an auto-adjustable organizational learning solution, through recalibrating the classical assessment toward a portfolio of exploring anticipative maturity profile-specific si trajectories (table 2 and figure 3). phase 1. conceptual training with basic features of each profile observed and initial skills assessment tailored to each profile need for improvement. 2.1 sirl 1: entrepreneurs’ missing skills in labeling strategic behavior. focus on understanding the benefits of the si profiling tool. the seed stage focuses on understanding the benefits of the si profiling tool, provides guidance with critical information to match organizational knowledge gaps and enhance profile alignment to industry competitive advantage dynamics. it also stimulates managerial reflections with strategic scope decisions regarding future market opportunities, key success factors and organizational configuration to meet strategic goals. the first step in estimating si readiness is to identify the strategic challenges the positions in which the start-up in seed stage, with the right combination of skills, talent, and knowledge, has the biggest impact on enhancing its anticipative capabilities. the needs to cope with frequent environmental change and to deal with the strategic decisionmaking complexity require a renewed approach to the entrepreneurs’ knowledge base. the conceptual training should adopt the open intelligence perspective (calof, 2017) at this stage. table 1 si profile specific core skills detective and anticipative core skills intelligence provider vigilant learner opportunity captor opportunity defender sharing vs protecting knowledge sharing knowledge new knowledge acquisition competence portability effective reaction against competition intelligent filtering strategic agility process focused products and services operational efficiency strategic dissonance and cultural dissonance capacity to interpret weak signals of cultural dissonance culture favorable to change culture open to change and capacity to monitor the cultural dissonance capacity to monitor cultural changes enhance competitive response permanent care for upgrades and innovations focus on meeting the clients’ needs instead of attacking rivals competitive advantage on harvesting over competences’ portability high capacity to detect competitors’ threats 23 table 2 strategic intelligence capability maturity model (si cmm). si profiles si readiness level ip vl oc od sirl 1 seed stage: missing skills in labeling strategic behavior. focus on understanding the benefits of si profiling tool non-replicable achievements knowledge discovery differentiation among competition replicable achievements fresh knowledge acquisition wake up and act! discern among opportunities wake up and pay attention to threats! sirl 2 positioning on si profiling tool actively seek information to upgrade the knowledge base learned behavior approach passively seek information about the environment contextual intelligence skills self-assessment ready-to-adjust to competitive environment customized skills to cope with threats sirl 3 understanding how to accommodate with conflicting objectives derived from market orientation vs. vision orientation improve capability to balance conflicting objectives generate nonreplicable knowledge ability to leverage market vs vision orientation in filtering conflicting objectives generate replicable knowledge unpredictable positioning payoff due to environment dependence propensity to collaboration predictable payoff because context dependent propensity to resistance sirl 4 develop profile specific core skills anticipation and detective capacity as trainable qualities recognize impactful signals before competition attention and confrontation to competitors’ signals contextual intelligence skills to deploy in specific industry competence portability effective reaction against competition protect market share sirl 5 activating profile specific core skills developing agility and calibrating competitive response strategic agility focus on anticipatory cues of the competition key future challenge recognition noise recognition within a chain of non-consequential mistakes refinement of interpreting early enough competitive challenge coordination in ready to adjust capability learning from experimenting noise with consequential mistakes react and wait! quick response to capture only specific signals from industry trends gain competitive experience wait and react! learning from own and competition failure sirl 6 foresight skills to anticipate unexpected change recognition sensing changes in competitive landscape seizing changes in competitive landscape ranking opportunities to develop sharpness in positioning ranking defense mechanisms strengthening foresight skills from small consequential mistakes sirl 7 influence future markets as trend setter strategic framing and promoting a si culture sharing cultural practices to set up new patterns of competition proficiency in overcoming cultural dissonance proficiency in leveraging cultural dissonance due to context unicity mastering cultural practices to avoid systematic failures in future markets setting up the strategic scope enables pre-profiling upon embedding knowledge from relevant experience of each profile on: • sharing knowledge differentiation among competition ip • fresh knowledge acquisition and capitalization seeking vl • competence portability oc • effective reactions to the competition’s strategic behaviour od the si preparedness journey will check ip against knowledge sharing propensity through systemically being alert to non-replicable achievements, while vl focuses on replicable achievements and will foster the acquisition of new knowledge. in turn, the oc’s propensity to wake up and act enhances competence portability, while the od’s actions (wake up and listen) enable effective reaction against competition. the si skills to develop in order to enhance competitive response will be focused on the ip’s orientation toward change anticipation through recognitional reasoning, while vl focuses on analytical skills to capture relevant 24 information and to commute it toward exploitable knowledge. oc focuses on exploring benefits while systemically leveraging market footholds to challenge competitors’ positions, while od’s concern is to protect market share and avoid consequential mistakes. 2.2 sirl 2: entrepreneurs confronting concerns about positioning on the si profiling tool to confront concerns of basic si requirements to comply with positioning on the si profiling tool, the assessment will focus on: • vl capability to learn through actively seeking information about the environment. • ip capability to frame the organizational learning landscape through actively selecting information about the environment. • oc adopting conditioned scanning for the best differentiation to discern among opportunities in a particular industry environment; seeking customizable achievements replicable across markets. • od customized skills to rank competitor threats valuable across industries. in this stage, the entrepreneur’s focus is to set specific si competencies needed to perform the strategic jobs related to positioning on the si profiling tool. the differences between the requirements needed to select an si profile and the company’s current si capabilities leads to “competency gaps” that assess the organization’s si readiness. these si missing skills are embedded in a training portfolio dedicated to the effective launch with the maturity journey. 2.3 sirl 3: the entrepreneur understands how to accommodate conflicting objectives derived from market orientation vs. vision orientation si core capabilities check market orientation vs vision orientation on each profile. leverage knowledge gains to match strategic scope and competitive pressures reveal how to act upon organizational agility to approach competitor threats: • ip vision-oriented behaviour gains depth and ability to balance conflicting objectives. generates nonreplicable knowledge. • vl’s ability to leverage market vs vision orientation in filtering conflicting objectives. generates replicable knowledge. • oc’s ability to recognize distant opportunities. distant opportunities are a challenge in bop markets because there are a high number of consumers with very low spending power, therefore opportunities for differentiation are not obvious, and high risks of competence transferability among competitors erodes competitive advantages, therefore perceiving and prospecting are core skills to train. • od’s ability to protect the market share while predictable positioning payoff is context dependent. propensity to resistance. entrepreneurs are aware that creating a si report regarding market orientation vs. vision orientation becomes compulsory. with such a report, they can analyze the si readiness of the organization at a glance, easily detecting the figure 3 si profiles maturity journey. phase 1. sirl 1-3 knowledge acquisition oriented with focus to match si missing skills: conceptual training. phase 2. sirl 4-5 knowledge transfer oriented to improve core si skill actionability, collective learning anticipative training, interpretative and iterative support. phase 3. sirl 6-7 reinforcement of profile specific core skills actionability is knowledge capitalization oriented to check proficiency upon si core skills and influencing the future competitive environment, future oriented behavior training, developing the profile specific supportive culture to consolidate each competitive identity. 25 strategic domains in which more resources are needed to converge with a particular si profile. phase 2. intermediate level with interpretative and iterative support 2.4 sirl 4: entrepreneur’s selfassessment of the capability to develop profile-specific core skills experimental matching of si capability areas and profile-specific core skills to evaluate strategic options to anticipate proficiency upon an intermediate level of si maturity: • vl develops adjustable instruments to comply with competitive environment pressures. • ip seeks to improve organizational processing. • oc develops its capability to capture distant opportunities before rivals and owns the capacity to detect the advantageous market niche. • od develops its capability to mislead competition with regard to its own strategy. entrepreneurs should avoid the risk of being overconfident in their ability to develop si profile-specific core skills. they could be tempted to have high degrees of confidence that their company is prepared to fully adapt to a specific si profile. gaining effectiveness in strategic early warning is a chance in this step. 2.5 sirl 5: activating profilespecific core skills through strategic trajectories already selected • od is capable of internally employing mechanisms focused on results protection in order to exploit the ignored opportunities. • oc is capable of anticipating the dynamics of the most advantageous market segments. • vl is primarily oriented toward change anticipation. • ip is focused on sharing knowledge designing instruments. developing agility and quickness ip strategic agility • decision making abilities • focus on anticipatory cues of the industry • key future challenge recognition • coordination with ready-to-adjust capability vl business model process agility • refinement of interpreting early competitive challenge • capacity to align managerial decisions to competitive environment • learning from experimenting scenarios with non-consequential mistakes oc portfolio agility • quick response to capture only specific signals displayed by opponents • gain competitive experience • learning from competition failures od operational agility • wait and react to minimize consequential mistakes activating the si profile specific core skills should overcome the risks of underestimating new sources of competition and/or impossibility to keep pace with disruptive trends in the next three to five years. companies have to gain autonomy in interpreting market insights if possible, to act early enough. phase 3 consolidate si core skills with sirl 6 and 7 2.6 sirl 6: developing foresight skills to anticipate unexpected changes related to industry trends (si sense-making) • ip is developing a portfolio of anticipative scenarios based on market dynamics • vl is fully aware about the importance of successfully embedding the customer experience in order to incessantly offer adaptation • oc is systematically pursuing the premium market segments • od is deploying knowledge protection early warning mechanisms the profile-specific facilitators of strategic positioning lie with oc and od embracing a flanking attack for price sensitive segments and undisputed markets due to their sharpness in picking an own battles approach. in turn, ip and vl act as savvy sense-makers and refine 26 interpretive judgment with incomplete information about positioning payoffs by carefully checking for decision biases. 2.7 sirl 7: mastering the capacity to influence future markets as a trendsetter (si sense-giving) the capacity to become proficient in future markets relies upon a cultural change approach. therefore, each profile core skill should be consolidated to enhance the effective market response. ip, endowed with sensing changes in facilitators and challenges, will become influential in promoting technological innovation. it will pursue a proactive approach to match facilitators and challenges; generate enablers to gain in the future value chain while consolidating the capability to cope with uncertainty and complexity. vl focuses on seizing changes in facilitators and challenges; it will become proficient in orchestrating matching of selected dynamic capabilities to the competitive environment’s future key success factors. moreover, vl pursues proficiency in leveraging cultural differences through ambiguity and volatility tolerance. oc will master the ability to capitalize upon its unique ability to rank opportunities with adopting sharpness in selecting its own battles. it will become proficient in leveraging cultural dissonance. due to context unicity, nonreplicable performance is at stake. od will gain strength from small consequential mistakes while mastering vigilance in avoiding systematic failure. 3. conclusions, implications and future research in the attempt to fully evolve from the fragile capacity to monitor cultural change to the most profitable capacity to recognize the value of cultural differences, a si new profile emerges, opportunity provider (op), as a repository of outliers and mismatches, due to ambiguous trajectories in each profile maturity journey. op enacts as a test maker of si core skills renewal, consistent with an emergent competitive identity prone to the knowledge discovery vocation, as si’s unique feature is to influence organizational intelligence maturity. op profile’s core responsibility is to collect and interpret outliers and mismatches of ip, vl, oc, od behavior when relying upon transient competitive advantage during an instable stage of maturity assessment. op’s main features lie with coordination and sharing si common knowledge to enhance preparedness in forward-looking competitive pressures. op will monitor the risk of strategic dissonance upon the features of organizational cultural change and experiment with a therapeutic approach, through more refined decision-making support, as a basis for nonrepeatable behavior. the op profile is built upon promoting a strategic leadership approach to master transient competitive advantage while trained to behave in an agile way, it embeds learning on organizational fitness to various competitive contexts. the op profile identity lies with competitive capital influence in mastering and tracks pattern recognition when capturing opportunities. sirl 1 to 5 provide improvements in developing the capacity of what we do with what we see, while sir 6 and 7 inquire about what we see and what we do not see, therefore op focus on blind spots to capture distant opportunities. stages 6 and 7 make sense of stages 1 to 5 of si knowledge acquisition and provide improvements on si actionability while developing foresight skills to anticipate unexpected changes. op acts as an early warning control of each profile capacity to cope with unexpected consequences associated with roadmap implementation of selected strategic trajectories on sirl1 to 5. the need for si instruction level 1 through level 7 lies with profile specific learning support, ranging from sharing common si knowledge (level 1-5), while tailored guidance should focus (level 6-7) on developing managerial capability to active experimentation of enhancing competitive response. sharing commonality focus is about gaining trust with the learning content and about capitalizing on past competitive successes and failures. the maturity gain lies with collective judgment in filtering causal associations of conditions in success and failure stories. tailored organizational preparedness guidance supposes assisted experimentation of anticipated future competitive pressures with a focus on developing new si core skills to enhance competitive responses. future research aims at exploring causal configurations of conditions (sensing change, seizing opportunities, business model innovation) affecting competitive response 27 preparedness (sirl 6 and 7) through qca methodology. 4. references bleoju, g., & capatina, a. 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(2016) government sponsored competitive intelligence for regional and sectoral economic development: canadian experiences. journal of intelligence studies in business. vol 6, no 1. pages 48-58. article url: https://ojs.hh.se/index.php/jisib/article/view/142 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index government sponsored competitive intelligence for regional and sectoral economic development: canadian experiences jonathan calofa,b,c atelfer school of management, canada; bnorth-west university, south africa; cnational research university higher school of economics, russian federation; calof@telfer.uottawa.ca journal of intelligence studies in business please scroll down for article government sponsored competitive intelligence for regional and sectoral economic development: canadian experiences jonathan calofa,b,c atelfer school of management, canada; bnorth-west university, south africa; cnational research university higher school of economics, russian federation; calof@telfer.uottawa.ca received 2 february 2016; accepted 20 may 2016 abstract can competitive intelligence (ci) be used to assist in regional and sectoral economic development? this article looks at intelligence initiatives (largely around training) sponsored by various government departments and agencies in canada and their link to regional and sectoral economic development. the article provides examples of the kind of intelligence initiatives that have been used in canada to support regional and sectoral (industrial) economic development. the article proposes a method for categorizing these regional and sectoral intelligence programs and suggests methods for assessing the impact of these programs on regional and sectoral economic development. the canadian programs are divided into three broad categories 1) government programs aimed at enhancing their own ability to develop competitive intelligence 2) programs that are sponsored by the government for industry and others to develop competitive intelligence and 3) programs sponsored by the government to help communities develop competitive intelligence for local economic development. positive economic impacts were identified using program review documents, government officer reports and anecdotal evidence from program participant surveys. however, while the evidence does support positive impact a more comprehensive approach to evaluating these impacts should be considered in the future. keywords competitive intelligence, economic development, economic intelligence, program impact, program review 1. introduction and overview making better decisions based on a proper understanding of the competitive environment (present and future) is at the heart of competitive intelligence (ci). competitive intelligence assists organizations in developing a proactive approach that identifies and responds to changes in the competitive environmental, helping organizations (companies, governments, universities, associations and others) thrive in turbulent times. this need for understanding the external environment and its impact on success has been echoed in the regional economic development planning literature. external environmental changes (the focus of ci): “have brought new opportunities to regional industries while simultaneously exposing them to increased competition both domestically and internationally” (stinson 2006, p. 4). it has also been identified as critical in designing economic policy and programs (calof et al., 2015). the objective of this paper is to look at how government competitive intelligence initiatives have been used in canada to enhance economic development at both the regional and sectoral journal of intelligence studies in business vol. 6, no. 1 (2016) pp. 48-58 open access: freely available at: https://ojs.hh.se/ 49 level. the intent of presenting both programs and evidence of program impacts is to stimulate a global discussion on how regional and sectoral economic development can be enhanced through government competitive intelligence activities. it is hoped that researchers from other countries that read this article will be encouraged to develop similar articles and provide additional program examples that can be shared amongst the competitive intelligence and government program communities. governments in canada both at the federal and provincial level have been involved in competitive intelligence initiatives largely since the mid 1990s. in this article, several of these programs will be described and discussed. this article uses, as its base for discussing these initiatives, a comprehensive review of competitive intelligence in canada (calof and brouard, 2004) and programs that the author of this article has extensive knowledge about either through active involvement in them (e.g. training programs delivered by the author, organizational systems created by the author etc.) or because the author reviewed and/or studied them for academic purposes (for example, the national research council’s competitive intelligence unit study as reported in calof, 2014). while this could lead to possible biases in terms of the comprehensiveness of programs reviewed for this article, nevertheless in depth knowledge of the programs and the government officers responsible for the programs are required to properly analyze and classify them. over one hundred government programs and intelligence initiatives are examined in this article. these are divided into three broad categories that are discussed in more detail in section 3 (including the rationale behind these categories): 1. government programs aimed at enhancing their own ability to develop competitive intelligence. this includes training initiatives (e.g. sending government officers for competitive intelligence training) and creating intelligence units. 2. programs that are sponsored by government for industry and others to develop competitive intelligence. this category includes providing or sponsoring training in competitive intelligence for canadian companies (and associations) and joint intelligence projects (both government and industry working together to develop competitive intelligence). 3. programs sponsored by the government to help communities develop competitive intelligence or local economic development. this category involves programs sponsored by the government aimed at assisting small communities in developing competitive intelligence capabilities for local economic development programs and initiatives in these three categories are then examined for evidence of economic impact at the regional and/or sectoral (industry) level. 2. government involvement in competitive intelligence government involvement in competitive intelligence has been studies and written about for many years. dedijer (1994) wrote about the french government’s involvement in competitive intelligence. much has been written about the french involvement in ci including the use of and development of ci for government economic policy purposes, french government ci assistance to companies and associations, as well as joint intelligence assistance involving chambers of commerce, industry association and companies (dedijer 1994, horne and parks, 2004, bisson, 2014). similarly, calof and brouard (2004) looked at canadian federal and provincial involvement in canadian competitive intelligence and julyeta et al. (2014) looked at examples of government involvement in competitive intelligence in indonesia. these and other authors have looked at the importance of these activities as a stimulus to regional and sectoral economic development. for example, julyeta et al. wrote ““it was then decided to used competitive intelligence not only to promote new economic and development conditions, but to move to local policy to promote in some key positions people which will have a competitive intelligence background and which will be able to facilitate a global move of the local stakeholders to new horizons.” (2014, p. 38). bisson (2014, p. 10), in looking at the work of guesnier (2004), momagri (2012) and massmann and quonniam (2010), wrote: 50 “[these authors have] pointed out the correlation between territorial governance and economic performance, and in this way ci activities should lead to better territorial economic results. a lack of information, for example, on price or technology lowers the price of farmers’ yields.” calof and brouard (2004) looked at the canadian experience with competitive intelligence between 1989 and 2004. in their research, they looked at competitive intelligence growth in terms of academic development (courses and research), corporate activity, associations, consulting and government activities. the authors noted that there had been significant development in the 1990s in terms of government involvement in competitive intelligence. for example, in the mid 1990s the department of foreign affairs developed an intelligence program for producing competitive intelligence for canadian companies and departmental officials. agriculture canada established market intelligence within their market and industry services branch for providing policy advice within the department. industry canada brought in a competitive intelligence training program to enhance their officers’ skills. the national research council established a technical intelligence unit in their organization to provide technical intelligence to departmental officers for decision making and policy development. provincially, alberta economic development brought in competitive intelligence training for their officers and also made it available to their industry clients. alberta also set up a joint market intelligence committee, which had representation from various federal and provincial economic departments. in saskatchewan, step (saskatchewan trade and export program) developed an intelligence department and established market intelligence as one of their offerings to saskatchewan business. in nova scotia, nova scotia business inc. also brought in competitive intelligence training and established market intelligence as a product offered to nova scotia business. in quebec, each quebec ministry had an officer responsible for competitive intelligence. this officer reported to a central government business intelligence committee. it is within this context of significant growth in government led competitive intelligence activity that this article is set. this article looks to provide readers with information on government competitive intelligence initiatives in canada, in particular those geared towards regional and/or sectoral economic development and their economic impact. there are three caveats on the programs discussed in this article: 1. this article does not cover all canadian programs that use intelligence for regional or sectoral economic development. it is not truly comprehensive. it includes only ones that the author has been involved with, either through studying them, running them or advising the organization in charge of them. this limitation is made to ensure that the author has sufficient information to discuss, assess and properly classify the programs. 2. although this article covers programs between 1993 and 2015, the majority of the programs discussed occurred before 2006. this arose as from 2006-2015 significant budget cutting arose both at the federal and provincial levels, making the funding of the programs discussed in this article difficult. 3. this article only looks at competitive intelligence programs and initiatives associated with economic departments. it does not look at programs associated with national security and national intelligence agencies (for example canadian security and intelligence service – csis, communications security establishment – cse). 3. canadian government activities in competitive intelligence one of the contributions of this article is that it attempts to develop a classification scheme for government competitive intelligence initiatives. in reviewing past articles on government involvement in competitive intelligence (described in section 2) the author notes that programs and initiatives tend to fall into one of two broad categories: 1) programs designed to help the government develop competitive intelligence (for example development of in-house intelligence units, training in competitive intelligence for government officers). the intent of these programs is to ensure that the department has the ability to develop competitive intelligence 51 that can be used either to assist companies or help the department make decisions. 2) programs designed to help companies develop their own competitive intelligence. the author notes several of the articles listed above written about the government providing competitive intelligence resources and training to local companies so that they can develop their own competitive intelligence (calof and brouard, 2004 and dedijier 1994 in particular write extensively about this). in spite of the limitations listed above, there have been a plethora of programs developed in canada that are focused on developing intelligence to assist in both regional and sectoral (industry) economic development. these were reviewed for the writing of this article and examined to determine their focus (departmental intelligence development vs corporate intelligence development). in looking at the mandate of the programs, reviewing reports about them (where available) and talking to those familiar with the program, further enhancements to the classification scheme mentioned above were made. table 1 provides a list of those departments and agencies and the type of programs they have had. this list is compiled from the authors’ direct experience either in developing and delivering the program or knowledge of the program through academic research. as such it is not a comprehensive list but can be seen as a convenience sample that is being used to examine the ability to categorize and later assess programs. the programs listed are divided into the following categories: 3.1 government programs aimed at enhancing their own ability to develop competitive intelligence this category covers competitive intelligence training that the government (federal or provincial) had customized to their organizations’ needs to help their personnel develop intelligence skills. some are of the classic introduction to competitive intelligence variety, while others allow participants to run an intelligence application (project) as part of the training. the general intent of the training is to enable the government officers to develop or enhance their understanding of what competitive intelligence is and work on key intelligence skills such as planning intelligence projects, collecting information for intelligence, analysis and communication to assist in their job and either contribute to sectoral or regional economic development by using these skills to provide canadian organizations with intelligence that will make them more competitive or use the skills to develop policy and programs that will enhance the economic performance of the region or sector. a) personal/department: training geared around helping officers learn how to use intelligence to assist the department/agency. the agencies/departments mentioned in table 1 have specific sectoral or regional development responsibilities. as a result, the focus for the training/skills development was on using these skills to help develop appropriate industry policy. examples of this include industry canada receiving intelligence training to help in the development of sectoral assistance programs. nrcan (national resources canada) had a module on intelligence to help in selecting the appropriate research and development programs to focus on for industrial development. agriculture canada had a project related to intelligence training that was focused on identifying sectors of the agriculture industry for further development in a 2020 exercise. b) helping others: several government departments have used intelligence training to assist in developing skills that would enable them to better provide intelligence to canadian companies. examples include the department of foreign affairs, which had provided intelligence training to most trade officers since 1993 to help them better serve canadian exporters. nova scotia business inc. and step (saskatchewan trade and export partnership) have taken extensive skills training in intelligence as both these organizations have the provision of intelligence to local companies as part of their mandate. the two categories (personal/department and helping others) are not mutually exclusive. for example, the national research council established a technical intelligence unit that helped the department develop industrial policy, helped officers make recommendations on technology investments and also helped canadian technology companies directly. also, although training is mentioned above, it is not 52 the only element of the programs: step and the nrc (mentioned above) have established infrastructure that includes specific intelligence units while nsbi (nova scotia business inc.) included it within their mandate and developed materials around it. table 1 canadian federal and provincial government department and agencies competitive intelligence programs by program category. x indicates that the program was run/sponsored by the department or agency identified. the programs and departments/agencies in this table are not a comprehensive list of all programs in competitive intelligence run in canada, but they are the ones that the author of this paper is familiar with either through research done on canadian intelligence programs (with francois brouard) or through involvement either in running the program or evaluating it for the department/agency. the programs are also limited to those that were run by departments with economic related mandates. this table is used to demonstrate the breadth of programs run in canada and to provide a demonstration of the program categorization method proposed in this article. canadian federal government departments and agencies enhancing their own (department's) ability to develop intelligence sponsored by the government for industry and others to develop intelligence programs to help communities develop intelligence personal/ department helping others intro. skills joint projects company projects trade show intelligence agriculture canada x x x x atlantic canada opportunities agency x x x x canadian food inspection agency x x department of foreign affairs x x environment canada x export development corporation x industry canada x x x national research council x x x natural resources canada x office of the national science advisor x the alliance for sector councils x x western economic diversification x x x x provincial government departments and agencies alberta agriculture x x x x x x alberta economic development x x x x x x alberta energy research x alberta innovation and science x x alberta treasury board and finance x manitoba agriculture, food and rural development x ministry of economic development and trade ontario x x newfoundland advanced technologies industries x x nova scotia agriculture x nova scotia business inc. x x x x x ontario cultural heritage x saskatchewan advanced technology x saskatchewan trade & export partnership x 53 3.2 programs that are sponsored by the government for industry and others to develop competitive intelligence. federal and provincial governments throughout canada have sponsored a myriad of programs across canada designed to help canadian organizations develop and enhance their competitive intelligence skills. some of these have been geographically focused (offered in one or more regions to help develop and enhance the local economy) and some have been sectorally focused, providing training and intelligence assistance to companies in multiple regions but in a specific sector (for example training for agriculture companies or training for technology companies). while sponsored programs have been given to a broad number of sectors, the two most frequent sectors for sponsored programs have been agriculture and technology. in work that the author has done with other governments the same two sectors have also been the most frequent focus for sponsored intelligence programs. a) introduction to ci/skills development: these types of programs introduce participants to the concept of competitive intelligence and the skills and organizational requirements to develop intelligence. these programs have ranged from one-hour keynote addresses as part of major government events (for example the manitoba department of agriculture and rural development program and ontario economic development had intelligence keynote talks as part of industry events) or as long as two day introductions to competitive intelligence programs such as some of those sponsored by alberta economic development. b) joint government and industry projects: joint projects bring industry, association and government together to work together on intelligence project with results being shared amongst all participants. an example of this is alberta agriculture, food and rural development, which sponsored an intelligence program that brought together industry, association and government participants. the joint project was to develop intelligence on opportunities for the alberta beef industry in japan. the program involved providing a basic introduction to intelligence (two-day program involving introduction to intelligence, how to collect information, planning for intelligence and analysis) to all participants who were then put in project teams (each team had industry, association and government representation) with each team developing intelligence on the japanese imported beef market. the final intelligence product (the combination of each of the team’s intelligence reports) was then shared with all participants. c) company projects: company projects are similar to the introduction to ci/skills development training but also involve participants developing and running an intelligence application on behalf of their organization as part of the training. these programs start with one to two days training and then participants go back to their organization, develop an intelligence plan (which is discussed with the program trainer) and then have weekly mentoring sessions with the trainer as they work on their intelligence project. at the end of the program (normally one month) all participants gather again with the trainer to discuss their experiences. for some of these project sessions, participants have both the trainer and a government officer helping them on the project. an example of this type of program is the atlantic canada opportunities agency (acoa) sponsored program that was focused sectorally on technology companies on the east coast of canada. acoa and the trainer provide the training and project support to companies in halifax (nova scotia), st. john’s (newfoundland) and fredericton (new brunswick). d) trade-show intelligence: a cooperative trade show intelligence approach was developed which combined small and medium sized companies, appropriate associations, federal and/or provincial government officers in a training program focused on a specific trade show. all participants were given trade show intelligence training. the training involved two days of training both on 54 competitive intelligence and trade show intelligence. for the training, specific materials from the trade show they were attending were included in the training material. for example, in training for the bio-technology trade show, participants were given a list of exhibitors that were going to the show, a list of all seminars, workshops, presentations and also social events. as part of the training program, participants were asked to develop trade show intelligence plans for the trade show that all program participants were going to (for example foodex in japan, fancy food show in san francisco, bio in washington) and to send the plan to the program trainer. the trainer then provided feedback and additional guidance to participants. government and association participants helped the companies execute their projects as well as running their own applications and the consultant/trainer also assisted. the approach was run at several trade shows and helped companies identify opportunities, assess markets, helped associations identify better ways to serve their members and government officers identify better programs and policies. one of the trade show programs from a technology trade show was written up in calof and fox, 2003 and provides details on the organization of the program. several provincial and federal departments and agencies have sponsored trade show intelligence programs across a broad number of sectors. these include nova scotia business inc., agriculture canada, alberta economic development, western economic diversification and alberta agriculture. trade show intelligence is an example of a program that can be regionally and sectorally focused. it is sectorally on the specific event and regionally in terms the regional authority sponsoring the training. 3.3 programs sponsored by the government to help communities develop competitive intelligence for local economic development this was a program developed to help small communities harness the knowledge within communities to develop their own economic development plan using intelligence. in the program, community leaders, local business owners, government officials and others were brought together in a facilitated program, taught about competitive intelligence and were then put in groups to develop the intelligence needed to support their region’s competitive advantage. all of this was then used to develop a regional economic development plan designed by the program participants and then presented to the community at large. the program involved multiple training sessions and intelligence projects and was done over an extended period (nine months). the program was designed to help small communities develop a long term economic development plan based on identifying their competitive advantage(s) and the intelligence required to exploit it. local community media have written extensively about the success of the program in their region (see dalman 2005 for an example of the program in humboldt, saskatchewan). a more detailed description of the program can be found in calof et al. (2010). 4. competitive intelligence program impact on regional and sectoral economic development section 3 provided a method to categorize government competitive intelligence programs. given that the programs mentioned above are designed to lead to regional or sectoral economic development, this section looks at documents generated by the program that would indicate that they had some sort of economic impact. 4.1 community economic development programs one of the community economic development programs (in humboldt, saskatchewan) was subjected to a full program review within a year of the program delivery. the purpose of the program was to transfer both skills that could be used to develop an economic development plan for the community that would lead to economic development and also 55 intelligence skills that could be used to help program participants in their organizations. the program review, done by impact research consulting ltd (kehring 2006) asked several questions about knowledge gained and economic development. amongst the question asked: “do you think that the process of creating the action humboldt economic development plan has produced positive gains in community capacity building knowledge and skills (including facilitation, competitive business intelligence, and networking)?” a total of 95.2% of program participants responded yes to the program reviewer. “do you think the creation of the action humboldt economic development plan has contributed in positive, tangible ways to the economic development of the region?” a total of 90% of program participants responded yes to this question. “were you able to increase your business or professional opportunities as a direct result of your involvement with the action humboldt economic development plan?” a total of 60% of program participants responded yes to this question participants were asked to list specific benefits attributable to the program. those identified by participants included: new residents moving to the region, new businesses starting up, increased employment opportunities, employee retention and the development of regional partnerships. the program review concluded with the following statement “the potential for economic development has been enhanced in the humboldt region due to the creation and the implementation of the economic development plan. there have been direct and significant results in the region due to the initiative.” (kehring 2006, p. 23) collectively, the answers to the evaluation questions coupled with the evaluators overall conclusions and analysis provide support for positive regional economic benefits arising from the humboldt community intelligence program that was sponsored by the government. unfortunately, this was the only community economic development program that was evaluated. there were other community economic development programs but no evaluations were done, therefore this section can only conclude that for the one program reviewed, a positive economic impact was found at the regional (local) level. 4.2 sponsored programs for industry despite the large number of sponsored programs for industry in canada there has not been a formal program review according to the organizations contacted for this article. accordingly, the link between these sponsored programs and regional and sectoral economic development is based more on the post-training reports provided by the sponsoring organizations and the anecdotal evidence in these reports in the form of participant comments gathered as part of the program assessment. one report written up in alberta and published in alberta treasury board and finance documents (2006) assessed the project intelligence program success using their organization’s metrics for the program. the article noted that 88% of the companies that attended the competitive intelligence course did undertake an intelligence project (a measure of success for this government agency). comments in the report included: “one company noted that the process was valuable…. a second company confirmed that they had sought out additional information leading up to a conference and it had prepared them to more effectively discuss their needs with others that could provide them with information. a third noted that they had completed a process that led them to refocus their marketing efforts in a slightly different direction. “all indicated that they found the process valuable. one company indicated that they would like three additional members of the team to take the training with another company saying ‘i was able to gain considerable information/intelligence…as a result of the training’ … finally, one company reported that the training session ‘led to discussion across divisions on how [company name] could advance its ci infrastructure.’” (p. 86) in the case of one of the joint programs (in which government, industry and associations worked jointly on a specific intelligence 56 application) a post program review had industry participants estimate the value to them (industry) as being in the six figure range. once again this provides support for economic value at both a regional (provincial) and sectoral level. in terms of anecdotal evidence from officer reports on the program and participant evaluations, here are a few examples mainly from the trade show intelligence programs. they are from a review of an intelligence program event given on the east coast of canada. for the houston offshore trade show the following comments were included in the officers’ report “the training, mentoring and support at the trade show enabled me to do three months of work in four days in houston”. the same review also looked at participant comments from another east coast program focused on the plastics industry for the national plastics exhibition trade show (npe). the following quotes were in the report “i was able to use ci techniques to optimize my info gathering exercise. a ‘focused approach’ was, i believe, the key to a productive two days… the show was huge and would have been overwhelming if not for the ci preparations.” a report on a trade show intelligence program that focused on sial (a food show in paris) included the following quotes from program participants: “i really enjoyed it. the process made me think carefully about what i was trying to find and what decisions needed to be made.” “it was valuable as a planning tool because nobody realized how big the paris sial was.” “this is something that can be a value to nearly everybody. it should be required of those that go to large trade shows. it is applicable to both governments and the private sector….the training allowed me to do much more at paris sial (food trade show) than i could have done under normal circumstances. the process yielded more and better information.” finally, a report out of alberta after a trade show intelligence program for bio (biotechnology trade show) included the following comments from the association that had jointly sponsored the training with the government “we all benefited from this process a lot…we will do this again.” “the process assisted our companies and the association itself in acquiring more reliable information in less time. it is something that we will use again and recommend to our members.” as a final measure of program impact, some of the government officers that were in charge of the programs (public servants) noted that the program had been the recipient of various recognition awards. these awards include department based awards (referred to as minister’s awards) as well as provincial awards (referred to as premier’s awards). readers are cautioned that while the results indicate positive economic impacts of these economic or sectoral intelligence programs, with the exception of the program review on the community economic development program and the valuation exercise for the joint intelligence exercise, all other results are either from officer reports or are anecdotal. there is no way to tell whether the comments in the reports and articles about the project intelligence and trade show intelligence are reflective of the majority of program participants and not just biased towards those that were most satisfied. nevertheless, the following can be concluded: 1. for the small community economic development program, a positive regional economic development impact was shown through the program evaluation results provided in this article. 2. for the joint intelligence project in alberta (beef industry) a positive economic impact both sectorally (beef) and regionally (alberta) was indicated according to the reviewers’ estimation of the value of the intelligence produced. for #1 and #2 these are a matter of public record from government conducted program reviews. 3. for all other sectoral and regional programs presented in this article that had anecdotal comments (and there were many) they (those that provided the anecdotal examples) indicated that they had received some sort of economic benefit. 5. conculsions and areas for future research this article has sought to classify government competitive intelligence programs and 57 initiatives used in canada and also examine the impact of these programs on economic development. three broad categories were identified along with several subcategories in each: 1. government programs aimed at enhancing their own ability to develop competitive intelligence 2. programs that are sponsored by the government for industry and others to develop competitive intelligence and 3. programs sponsored by the government to help communities develop competitive intelligence for local economic development. this article has sought to provide examples of intelligence programs and initiatives under each one of these categories. it is hoped that future research will look at other intelligence related regional and sectoral economic development programs to help develop a more comprehensive list and description of the kind of intelligence programs that have been used around the world to assist in sectoral and regional economic development. it is hoped that in the future, the categorization method described in this article will be improved by others applying it to programs in their countries. as well it is hoped that this kind of research will result in the development of a comprehensive list of the kinds of competitive intelligence initiatives that have been used around the world. this article only reports on canadian initiatives. finally, this article has attempted to link these programs to regional and/or sectoral economic development. economic impact was examined using program review documents but only in the case of one community economic development program. other initiative had to be reviewed using government officer reports and anecdotal evidence from participant satisfaction surveys. however, while the evidence does support a positive impact a more comprehensive approach to reviewing these impacts should be considered in the future. which intelligence programs and initiatives provide the best sectoral and regional economic development impact cannot be answered based on the way these programs were reviewed and this should be addressed in future studies. acknowledgements the article was prepared within the framework of the basic research program at the national research university higher school of economics and supported within the framework of a subsidy by the russian academic excellence project '5-100'. 6. references alberta treasury board and finance .(2006). alberta heritage trust fund magazine. an experiment in problem solving. bisson, c. 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(2004). implementing competitive intelligence in a non-profit environment. competitive intelligence magazine, 7(1), 33–36. julyeta p.a runtuwene, audy aldrin kenap and verry ronny palilingan (2014). the development of north sulawesi through competitive intelligence. journal of intelligence studies in business. 4 (1), 36-42. kehrig, randall. (2006). project evaluation: action humboldt economic development plan. massmann, o., & quoniam, l. (2010). mise en réseau d’acteurs publics et privés, et stratégies d’innovation et de développement international du territoire : l’exemple de la chambre de commerce et d’industrie du var. paper presented at the 2010 vsst, toulouse, france. salvador, marisela rodriguez and luis francisco salinas casanova (2012). applying competitive intelligence: the case of thermoplastics elastomers. journal of intelligence studies in business. 2(3), 47-53. stimson, robert j, stough, roger r, roberts, brian h. (2006). regional economic development: analysis and planning strategy. springer, united states. wright, s. and calof, j.l. (2006).the quest for competitive, business and marketing intelligence a country comparison of current practices, european journal of marketing. 40 (5-6), 453-465. jisib-vol-12_nr-1(2022) (3).pdf journal of intelligence studies in business vol. 12 no. 1 (2022) open access: freely available at: https://ojs.hh.se/ pp. 83–90 networking capabilities and digital adoption of business agility with business model innovation as a mediating variable idris gautama so richardus eko indrajit sri bramantoro abdinagoro abstract in business, agility is a method that places projects on a smaller scale and engages capabilities and digital adoption on business agility with the variable business model innovation as a mediation variable using quantitative method. the results show that all variables have digital adoption, and business model innovation can escalate business agility keywords: business agility, networking capabilities, digital adoption, business model innovation 1. introduction in the business world, agility is a method that places projects on a smaller scale and engages team members through constant collaboration and continuous iteration. this method offers an iterative and gradual approach, so it does not work sequentially and creates a product at the end of the project (xie et al., 2022). observing the current work environment, the need to have resources becomes very important, especially for workers in a company. the developthe dynamics of business and small businesses to be so volatile. therefore, it is not surprising facing change is an important component in maintaining the sustainability of a company. this also has an impact on the micro, small, and medium enterprises(msme)/usaha mikro kecil dan menengah (umkm) sector. in order to maintain productivity and maintain their income, umkms are competing to take advantage of digital platforms. coordinating minister 84 that there are around 301,115 micro, small, and medium enterprises that switch digital platforms (cepeda & arias-pérez, 2019). the agile process certainly reiterates the importance of the role of agility, especially during this pandemic. agility is an important aspect that encourages individuals to be able to quickly adjust to changes and existing situations. unfortunately, in indonesia, agility is actually a concept that has not been noticed for a long time. in fact, looking at the description of competencies that are a component of agilemployee potential, especially in the current in addition to business agility, business models are useful in modern business environments because they allow organizations to understand the value of future organizations and how companies in general operate (orvos, model can be explained, for example, capturing the functioning of the company way and creating value and providing value to customers a,nd converting customer responses into profits (bouwman et al., 2018). the application of business model innovations is expected to be able to be better useful by collecting creative ideas to be processed which then the ideas become informative innovations that are able to be implemented on innovation projects in one of the factors that affect business agility is the company’s network capability or ability to develop and establish cooperation eration. the advantage obtained from having network capability is the ease of obtaining information related to resources, markets and the latest technology that can be used to support company performance (gulati, r., n. capability is important for the company’s longterm success and viability (parida et al., 2016, 2017). previous research conducted by (majid the conclusion that network capability effectively affects the level of business agility. in addition to network capablity, the next factor that affects business agility is digital adoption. it is undeniable that by applying improve the company’s performance. so many conveniences can be achieved in various aspects of the business. digital adoption can meet the information needs of the business world quickly, precisely, accurately and relevantly. in addition, digital adoption also has an important role for companies in their competitive advantage strategy. digital adoption will affect almost all aspects of 2 business management and can provide added value if managed properly and designed into an effective information system. (karvonen et al., 2018) states that the behavioral aspect in the adoption of information technology is an important thing to pay attention to because the interaction between users and computers is the result of tions as aspects of behavior that exist in individuals as users. therefore, based on the explanations presented above, researchers are interested in conducting research on how networking capabilities and digital adoption affect business agility with the business model innovation as a mediation variable. the latest in this study is the addition of business agility variables and network cpabilities based on suggestions from previous research conducted by nasution (2004), so that it becomes four variables networking capabilities, digital adoption, business agility, business model innovation. the purof networking capabilities and digital adoption on business agility with the variable business model innovation as a mediation variable. 2. literature review 2.1 network capability network capability is a dynamic capability that creates dependence inside and outside the organization (battistella et al., 2017). network capabilities allow companies to gain access to different resources, identify opportunities and respond quickly to ever-changing marketing needs (solano et al., 2018). this variable is a company’s ability to develop and utilize interactions between organizations to gain access to various recources owned by other parties (walter et al. in chabachib, capability is the company’s ability to create, improve, and use internal and external organizational relationships. in network capability there are four aspects, which are internal communication, coordination, relationship skills, partner knowledge. coordinationconsists of the integration and synchronization of resources to ensure their effective utilization to achieve organization’s 85 goals (bengesi & le roux, 2014). the main essence of coordination is a situation in which various important organizational resources and activities are shared outside the boundaries of the organization, which connect different individuals and independent organizations together, thereby developing a network of dalam majid et al., 2019). 2.2 digital adoption (lee et al., 2021), the adoption rate is the relative speed at which innovation is adopted by members of the social system. it is generally measured as the number of individuals who adopt a new idea in a certain period, such as each year. so the adoption rate is a numerical indicator of the steepness of the adoption curve for an innovation. the perceived attributes of an innovation are one of the important explanations of the adoption rate of an innovation according to (ghobakhloo & ching, 2019), the adoption of innovation is a process of social change with the presence of new discoveries that are communicated to other parties, then adopted by society or social systems. innovation is an idea that is considered new by a person, it can be a new technology, a new way of organization, a new way of marketing agricultural products and so on. the adoption process is son hears a new 16 xxx thing until the person adopts (accepts, applies, uses) the new thing. (parra-sánchez et al., 2021) mentions that the nature and character of technology develops depending on one’s perception of technology. technology can be viewed as an object, as a process, as a science (as a knowledge), and as control (as a volition) (patil et al., 2022) technology has three domains, namely: design technology (design), production technology (manufacture), and marketing technology (pradhan et al., 2020). 2.3 business agility nowaday’s business is moving very fast, innovation and disruption are emerging every day. if organizations do not implement agile methods, then they can lose their advantage and be no longer relevant. agility itself, is the ability to think and understand the situation quickly. in the business world, agility is a method that places projects on a smaller scale and engages team members through constant collaboration and continuous iteration. this method offers a iterative and gradual approach, so it does not work sequentially and creates a product at the end of the project. the concept of agility itself is originally tems studies (saputra et al., 2021). meanwhile, in strategic management, drucker conceived agility to explain the importance of increasing (liao et al., 2019). the further research involved hundreds of companies and the results were studies on organizational agility in strategic management have been widely carried out in the study of entrepreneurship, organizational agility itself is a form of entrepreneurial action (attar & abdul-kareem, 2020). 2.4 business model innovation according to (geissdoerfer et al., 2018) one of underserved markets” is adapt business model to community realities. thus, business model innovation is one of the important keys to success. according to (colovic, 2022), broadly speaking, business model innovation is planning and designing new ways of doing business through changes, improvements, and improvements to existing business processes, both internally and in collaboration with externals so as to create new work processes that have never been done before to increase the added value of stakeholders. so in this study the author concludes that business model innovation is a unique, compleand effectiveness where it is able to create, provide and capture value. 3. research method research design this research is included in descriptive quanstates that, say that, research methods are used in the quantitative approach. according research is research that uses observations, interviews or questionnaires regarding the current state of affairs and also the subject we are researching. through questionnaires and so 86 on researcher collect data to test hypothesis or answer a question. through this descriptive research, the researcher will explain what is actually happening about the current situation that is being studied. research subject this research was conducted at culinary smes in surabaya bandung semarang jakarta this study was random sampling so that in this study a research sample of 100 culinary smes in surabaya bandung semarang jakarta data collection data collection technique done is through questionnaires that are spread using google form. the google form can ease the collection of survey research. data analysis the data analysis technique in this study used partial least square (pls). pls is a structural equation model modeling (sem) with an approach based on variance or componentbased structural equation modeling. according to (sohaib et al., 2020), the purpose of plssem is to develop a theory or build a theory (predictive orientation). pls is used to explain the presence or absence of relationships between latent variables (prediction). pls is a powerful analysis method because it does not assume current data with a certain scale measurement, the number of samples is small. 4. result a. outer model analysis in order to measure the validity or validity of a questionnaire, the researcher uses ity testing is done using convergent validity value (> 0.6). 2) uji reliabilitas in this study, researchers used 2 types of reliability tests, namely the cronbach alpha test and the composite reliability test. cronbach alpha measures the lowest value (lowerbound) reliability. the data is stated to be good if the data has a cronbach alpha value and a composite reliability score of >0.7. based on the calculations carried out, it was found that all instrument items met the requirements of validity and reliability with scores that exceeded the criteria.. 3) r square used in the measurement of how many endogables. based on data analysis carried out through the use of the smartpls program, the r-aquare value was obtained as stated in the following table in appendix. the score in the table explains that the business agility ties, digital adoption, and business model innoother variables that were not studied in this study. the table explains that the business networking capabilities and digital adoption, variables that were not studied in this study. this table is avaluable in appendix. the presentation of the hypothesis results are the results of testing the business model innovation hypothesis on business agility obtained a score of (p = 0.039) with a p value of 0.773 (p1.96) showing that there was the business model innovation variable on business agililty. this rejects the research b) effect of networking capabilities (x1) on the results of testing the networking capabilities hypothesis on business agility obtained a score (p = 0.436) with p values of 0.001 (p1.96) indicating that there was variable networking capabilities on business agility. the better the networking capabilities owned by smes, the better that are in line with the results of this study (2012) that entrepreneurial networks have or performance. then (akintimehin et al., on business performance in fabric centers the three dimensions of network capability 87 (internal communication, partner knowledge and relational skills) on performance in small and medium-scale companies. c) effect of networking capabilities (x1) on the results of testing the networking capabilities hypothesis on business model innovation obtained a score (p = 0.555) with a p value of 0.000 (p1.96) showing that there the networking capabilities variable on business model innovation. the better the sme’s networking capabilities, the better the sme’s business model innovation will be. this is in line with the research conducted by (mihardjo, sasmoko, alamsjah, & elidjen, 2018). d) effect of digital adoption (x2) on business the results of testing the digital adoption hypothesis on business agility obtained a score (p = 0.291) with p values of 0.009 variables on business agility. the better the digital adoption carried out by smes, the better the business agility will be. this is in line with the research conducted by e) effect of digital adoption (x2) on business the results of testing the digital adoption hypothesis on business model innovation obtained a score (p = 0.338) with p values of 0.000 (p1.96) showing that there is a sigital adoption variables on business model innovation. the better the digital adoption owned by smes, the better the innovation of sme business models will be. this is in line with the research conducted by (ghezzi & cavallo, 2020). f) effect of networking capabilities (x1) on the results of testing the network capablities hypothesis on business agility mediated by business model innovation obtained a score (p = 0.216) with p values of 0.009 network capablities on business agility mediated by business model innovation . the better the network capabilities owned by smes, the more it will affect business agility, this is also strengthened by the innovation of business models. this is in line with research conducted by mulyana g) effect of digital adoption (x2) on business the results of testing the network capablities hypothesis on business agility mediated by business model innovation obtained a score (p = 0.213) with p values of 0.008 (p1.96) showence between variable network capablities on business agility mediated by business model innovation. the better the digital adoption carried out by smes, this can increase business agility, as well as the existence of business model innovation variables to strengthen digital adoption of business agility. 5. discussion business agility is a relatively new paradigm painted as a solution for maintaining competitive advantage during times of uncertainty and turbulence in the business environment. quickness is about the speed with which the organization can respond to customer requests, market dynamics, and emerging technology options. this includes the time to sense relevant events, the time to interpret what is happening and assess the consequences for the organization, the time to explore options and decide on which actions to take, and the time to implement appropriate responses. resources are about the capabilities that are available within the organization including people, technology, processes, and knowledge. resources can be both tangible and intangible and they provide the basis for doing business and for instantiating change. adaptability is about how well the organization responds to changing demands, threats, or opportunities. this requires the ability to learn as well costs. agility is concerned with economies of scope, rather than economies of scale. based on the results of this research, although business agility has increased, yet it is unaffected by the business model innovation. business model innovation / bmi that has advantages to enable companies to be adaptive to market changes. through a production framework that relies on cooperation with sme partners is one of the keys to being overcome, it will make it easier for companies 88 to change resource allocation and form competitive prices. in addition, such business models form a unique attractive market segment. thus, it allows the company to provide value added to the customer and will facilitate revenue streams. in addition, the network capability possessed by entrepreneurs forms the foundation for entrepreneurial success. according to (r. as a company’s ability to initiate, develop, and utilize internal organizations as well as external inter-organizational relationships. when the network capability is increased, business agility will be able to be increased. broadly speaking, the use of digital technology is directed at increasing the company’s business agility. according to sri mulyani, the ability to create and also adopt digital technology determines how an economy and a country are able to enter the global value chain system that will increase productivity. so that with good digital adoption from smes, it will increase their business agility. other than that, based on the result of this research, the existence of business model innovation can increase more the variables that affect business agility. the ability to collaborate between smes will continue to give birth to innovations. changes in consumer needs and desires to satisfy themselves will spur companies to innovate continuously in order to create products that are in accordance with consumer desires. so that this can increase the business agility of smes. in fact, this research also shows that business network capability is said by the ability to carry out integrated cooperation between two or more parties that is harmonious, synergistic, systematic, integrated and has the aim of establishing business potential in generating companies, it will provide business model innothe diversity of insights from owners/managers in smes on technology adoption strategies generates different driving forces and barriers related to adopting, adapting and assimilating internet information technology in organizations. (bleicher & stanley, 2016) noted organizational readiness is the main reason technology adopters differ from non-adopters. a critical characteristic of technology adoption is the ability of sme executives to navigate and adapt to an environment that sets the right organizations so it may shape business model innovations. 6. conclusion based on research and discussion, it can be innovation on business agililty, there is a signetworking capabilities on business agility, variable networking capabilities on business variables on business model innovation, there able network capablities on business agility mediated by business model innovation, there variable network capablities towards business agility mediated business model innovation. capabilities, digital adoption, and business model innovation by 49.7%, and business capabilities and digital adoption, by 68.3%. the researchers hope that in the next study to replace variables that are not yet in the study so that this research becomes more reliable. references akintimehin, o. o., eniola, a. a., alabi, o. j., (2019). social capital and its effect on business performance in the nigeria informal heliyon.2019.e02024 asad, m., sharif, m. n. m., & alekam, j. m. e. 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(2018) book review: superforecasting: the art and science of prediction. journal of intelligence studies in business. 8 (1) 46-53. article url: https://ojs.hh.se/index.php/jisib/article/view/286 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index book review: superforecasting: the art and s c i e n c e o f p r e d i c t i o n klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article book review: superforecasting: the art and science of prediction. crown publishers, new york, ny. tetlock. e. philip, gardner, dan (2015) klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se throughout this review i write “the authors” referring to everything that is written in the book, even though i suspect that tetlock is the leading theorist. gardner is a journalist, it says on the dust jacket. i do not exactly know what that means when it comes to whose ideas are in the book – who has contributed with what – and i do not want to speculate. philip e tetlock is a scholar of psychology with an impressive number of publications and citation, so expectations are high right from the start. and, this is a good book, but not for any of the reasons that it pretends to be one; in fact, it is the opposite. i will get back to this at the end of this review but concentrate on the critique. forecasting is another word for intelligence work or guessing about the future. when we talk about forecasting we normally think about scientific methods that imply using more quantitative methods, on problems where such methods are thought to be of real use, as in weather forecasting. as we shall see throughout the book, the methods used for actually predicting events in this book are not quantitative but qualitative. that by itself is a problem when the term ‘forecasting’ is chosen, as it is confusing to intelligence professionals. the ‘super’ in ‘superforecasting’ sounds like something that is made up to sell extra copies of a book. for two authors who place so much value on modesty (as they describe in chapter 12) it’s an odd contradiction to throw the word “super” around in so many forms through a book about the activities one is doing oneself (for example, superforecasters, superteams, superquestions, supersmart, superquants and supernewsjunkies). i guess all professional like to be “super”, but super is something that others say about our work, not something we use to describe our own work and it is difficult to find any irony most of the time when the prefix is being used about how well the authors/project/project members did. it’s quite possible that the authors thought that the ambiguity and playing with irony would go over well with the reader, but it does not. the subtitle is the ‘art and science’. it’s a popular subtitle in english but does not say much as it suggests everything (both a science and an art), thus nothing. what is normally more interesting to know is if the authors see something as a science or an art and why. again, the impression is one of selling more copies of the book. chapter one throws arounds names and parallels like bill gates and his anthropological work and tom friedman and his thesis about the flat world. the project the authors work with is “the good judgement project,” which sounds like something pulled out of a commentary to the bible. more interesting, the authors explain how their wok is supported by the american intelligence community (ic) and that its participants have outperformed other analysts. this is a claim throughout the book which is never explained in any detail. we are not told much about how the actual competition was arranged, for example how the answers were graded. we are only given some example of questions asked and presented with names of some participants journal of intelligence studies in business vol. 8, no. 1 (2018) pp. 46-53 open access: freely available at: https://ojs.hh.se/ 47 that used the authors methods (the superforecasters) and how well they did compared to others. the book promises that the key to becoming a good forecaster using the method is not math skills, or an abundance of reading or excellent knowledge of history or geography, but comes down to some simple methods of psychology. in other words, good predictions all come down to how you think (not what you know), the authors claim. it is about thinking in a way that is “open-minded, careful, curious and – above all – self-critical. it also demands focus” (p. 20). now, if i had been a few decades younger i would have been very excited at this point in the book with the promise of a quick solution, a method available to everyone (who reads the book), but these personal qualities, as much as they are required, are just the beginning of good forecasting. at this point in the book i get the feeling that i just saw an infamous gambler ride into town. chapter two cannot wait to provoke with its title: “illusions of knowledge”. we are told some quick, smart stories from the history of medicine where the moral is that we should be critical, as in scientific rigor. then we should think about how we think, a favorite idea among psychologists. the chapter goes on to talk about kahnemann and tversky (colleague) and abruptly ends without every really explaining what illusions are found in knowledge or having ever come close to treating the topic of knowledge more than superficially. by this time it is unclear whether or not it is worth reading the rest of the book. the suspicions from having read the title and the few introductory pages are confirmed. in chapter three, entitle “keeping score,” we are introduced to an old legend, the historian sherman kent, who was one of the first people in modern times to introduce science into intelligence work. to ensure his analysts were using the same language, kent defined 100% certainty as “certain”, 95% as “almost certain”, 75% as “probable”, 50% as “chances about even”, 30% as “probably not”, 7% as “almost certainly not” and 0% as “impossible”. the idea that this would help analysts use the same measure, thus increasing accuracy in predictions. the idea was also good, but never became widespread. one could object that if you use a likert scale of seven it would make more sense to set the percentages with 14.3 percentage point intervals (for example, 10085.7%). to allow for the 50% mark, it would make more sense with a five-grade likert scale. the authors do not comment on this but conclude that the system was never adopted. what they do note is that what is here presented as objective statements is subjective. that in itself is a strange comment as it excludes the possibility that some observations are facts (100% and “certain”), and that all statements are subjective. the authors go on to say that at the end all these estimates can only be presented as opinions, which depends entirely upon what kind of questions the scale goes on to measure (for example, natural facts or predicting human behavior at time t). what did remain in ic after kent was the use of probabilities, such as when ic told obama that there was a 70% or 90% probability that the man in the pakistani compound was osama bin laden (p. 59). what that implies is more disturbing, that obama decided to lead a military operation into a foreign country (a military ally) without even consulting their government when there was a 10-30% probability that they were wrong. the same logic goes to explain why so many civilians are killed with drones and other air strikes; the us has a policy of bombing targets when they are not quite sure who the targets are. the authors go on to argue for the value of the brier score that measures the accuracy of probabilistic predictions. but they fail to note that the brier score becomes inadequate for very rare (or very frequent) events, because it does not sufficiently discriminate between small changes in forecasts. the authors fail to see the fundamental difference between predicting the weather with fewer and easier variables to measure and predicting human behavior which consists of many more variables that are more difficult to measure and that frequently vary under the same conditions, such as when a customer suddenly decides not to buy an ice-cream on a hot day even though he did so a week ago under similar conditions. not to mention the unreliability of the rationality assumptions, which are largely avoided in the book. too many analysts think ideologically, and try to fit their observations with their beliefs. what does not fit is treated as an irrelevant distraction. they are also likely to declare things “impossible” or “certain”, the authors remind us. this brings us to a key element in the method that is presented, that the “superforecasters” are taught to express themselves more carefully. this is illustrated 48 in the allegory of the fox and the hedgehog by isaiah berlin. the foxes win by “playing it safe with 60% and 70% forecasts where hedgehogs boldly went with 90% and 100%” (p. 69). this is the same in obama’s dilemma presented above. what actually happens is that the risk of mistake is transferred from the intelligence analyst to the decision maker. the decision maker is tempted to give the go-ahead if he is presented with something that has a 60% or higher probability. if things go wrong then the intelligence analyst can always say it was not his fault as there was a 40 or 30% chance of failure or mistake. does this mean we have a better method for intelligence analysis? no, of course not. it is only transferring the risk of fault from the person who is doing to analysis to the person who is requesting it or making the decision. to the extent to which it is not possible to be more certain of course then 60 or 70% likelihood will have to do. the question then becomes if the decision maker should make a decision to engage at all, given the risks. are the risks sufficiently explained to the decision maker? in the case of osama in the bunker the answer is not clear. so, is this better intelligence work and is it a better method for intelligence analysis? i think the book offers some good advice in terms of rules of thumb, which we shall come back to, but so far the suggestions made imply that the analysts have just become smarter fencing off potential criticism for potential mistakes. if this is how the authors won the competition against their colleagues in the ic – by giving vaguer answers then that is no real victory, but a statistical trick. this would also explain why they do not focus on knowledge, as they are not so concerned with ideas, but more with careful expressions. so far into the book this seems to be the essence, and a better title may have been “the art of careful expressions”. the question remains what kind of people you would like to fill your intelligence department with, well-read experts or people who have learned that careful expressions will put you in the right more often? note again that in the obama case the analysts are not really helping obama by saying that there is a 70% or 90% possibility bin laden is in that house in pakistan. it’s also odd to say “70% or 90%”, 70 to 90% would at least make some sense, but 70 or 90 is like giving two different answers. as if we are free to choose. obama is faced with two choices: to bomb/attack or not to bomb/attack, it is either or, but the answers given him are in terms of a percentage likelihood of bin laden being in that house, which is not what he needs. in other words he is not being given the intelligence he requested. if it was difficult to be sure, why not wait until they were more certain? the analysts figure obama will bomb/attack because there is only a 30% chance that bin laden is not in that house, but obama could also have reasoned that it is not worth bombing/attacking as there is a 30% chance someone else (innocent people) will be killed. another technique used by foxes is to analyze the problems using many methods/analyses and synthesize it into one answer at the end, something the authors call aggregation, but others call redundancy in method. it is a well-used method in the social sciences, so there is nothing new about it. chapter four starts with the horrifying story of how the intelligence community made up of 20,000 intelligence analysts supported a claim from the white house that iraqis had a nuclear weapons program that produced weapons that was a threat to the us and nato countries (national intelligence estimate 2002-16hc). one explanation was that the ic had been bullied by the white house to come up with documents that suggested a war. with the authors method, the ic should have said that there was a 70% likelihood or similar, but then the results would probably have been the same anyway. this just proves how dangerous the method of transferring the risk to the decision maker is. the authors struggle to find the right answer to the question. they do not start by saying that maybe the ic should have listened to dr. hans blix, the iaea director general from 1981 to 1997, who was experience with these issues and guided the agency through the chernobyl disaster. dr. blix was against the invasion from the start, as there was no evidence to suggest that the claim was true. thus, it is disheartening to see how the authors stay with their initial method in this example, they should have said 60-70%. then they would not have been completely wrong and that, the authors think, would have been better. for whom? for the estimated 1 million iraqis who died as a result of the conflict? another example that is used in the book is the use of math to make predictions on wall street. the authors suggest that the answer to intelligence is statistics and math, just like for the study of economics (probability). but how well did the quantitative analysts really do for their investors? what about the consequences 49 of the failed banks and all the pensioners who lost their retirement funds? the authors never go down that road. in general, has the study of finance succeeded with math? if one had asked that question 20 years ago most colleagues would have said yes, but today large part of quantitative finance is left behind as irrelevant, including option pricing models. some of those who received the nobel prize for their “inventions” in finance have since been discredited. chapter five is about iq and intelligence. much of the chapter and chapters in general are case allegories, small cases with no clear conclusion, as in the example of the cause of death of yasser arafat (pp. 114-117). the case is picked up in later chapters as a to-becontinued ploy for the reader to find the content interesting, it seems. chapter six is entitled “superquants”. we are told that superforcasters are not like the quants (quantitative analysists) of wall street, they don’t use that much math. it’s more careful thought-out and nuanced answers (p. 129). the authors return to the obama – bin laden example, citing mark bowden, who confirms what obama thought about the intelligence estimates he received. obama got “probabilities that disguised uncertainty as opposed to actually providing you with useful information“ (p. 135). obama acknowledged that he was left with a gamble, as we commented on earlier in the review. obama himself is quoted as having said it was a “fiftyfifty”. then a whole analysis follows about what this comment means; if it was to be interpreted literally or not. was he being sarcastic, critical or just stating a fact? it’s easier to say for those who were in the room. he may have thought that the figures presented insufficient information. one interpretation says that obama would have attacked the facility no matter how small the odds were for finding bin laden. if that is true it borders to an almost bizarre example of decision making that resembles gambling, which may or may not be what he meant. the authors and those consulted in the book cannot agree what obama was thinking when he said “fifty-fifty” or what i meant, which is not much more comforting. chapter seven in entitled “supernewsjunkies”. just the idea that extensive reading makes someone a “junkie” is offensive but fits well with the authors’ idea that it is not what you know but how you think. the chapter starts by unfolding more of the “superforecasting” method, leaving the reader puzzled as to why the method is spread around the book in small pieces. it makes the book seem scientifically unfriendly, again, as it is all about selling books and consultant services. the suggestion is to “unpack the question into components” distinguish between unknown and known and leave no assumption unscrutinized (p. 153). fair enough, but this is much more difficult than it seems and poorly explained on the following pages. “adopt the outside view and put the problem into a comparative perspective that downplays its uniqueness and treats it as a special case of a wider class of phenomenon”. “also explore the similarities and differences of your own views and those of others…” (p. 153). the author’s method consists of synthesizing these two views and the views of the crowd. this is questionable. first of all, if i am not well-read on a topic why include my opinion at all? and surely the opinion of the crowd is a function of the information spread in mass media, whatever that may be. thus to find some sort of average (another statistical ploy) on these three positions is ludicrous. why should this method bring you any closer to anything truthful? what it will give us is what the social truth is, but the social truth is very often different from the truth per se as will be obvious, for example, to anyone asking people about which religion is right. the authors go on to say that this process of gathering the three views takes time and is only the beginning of the method (but by now the reader is a bit tired of the sales talk). the reader is annoyed by the probability figures the authors keep throwing around in the chapters, like the 60% probability that polonium would be found in arafat’s body (p. 153). the authors should for once tell the reader how the analyst got to that figure, as that calculation is the cornerstone of the whole method suggested in this book. it’s not explained anywhere. the time frame of a decision is very important of course. the authors talk about “scope”, an effect that may give an answer of no today, but yes in a month or two, so the answer depends on the point in time. the “superforcasters” know this so they update their information much more frequently, on average, than regular forecasters, we are told. it makes you wonder who the regulars are, analysts at ic? i am sure they must be thrilled 50 to read how badly they do their work, all 20 000 of them. by now the reader is also annoyingly interested in learning about all the facts of the “tournament” where the “superforecasters did so well and so much better than the rest. what were the questions? who set them up? how much time was given to each question? and more fundamentally, how were they graded? i do not want to speculate but i suspect that the best answer was not in terms of right or wrong answers, but the answer that comes closest to the truth as that would favor those answer with vague answers. it should have all been explained clearly at the start, not as loose sentences spread around the book like bait to turn another page. on the other hand i guess that is how bestseller books are written, they are exiting partly because the reader hopes to know what it’s all about and keeps flipping those pages. the point about updates also makes you wonder if the “superforcasters” won because they updated their information more frequently. the article continues on the arafat question, and bill flac (one of the superforcasters) updates his estimate from 60% to 65% yes as he thinks that the delay in time the swiss laboratory has with publishing the results has to do with the operation they may be testing to rule out lead as the source of death. another issue that is interesting here is the calculation that increases with 5% likelihood. that calculation is never shown. why not? surely if focus is on psychology it would be interesting to learn about the cognitive processes that makes the difference of 5%, not least the biases if there is no clear calculation but more of a feeling. in a book dedicated to this essential topic how come the calculations are not shown? i am not saying it is easy, but others have tried and it is the central theme of the book. instead the authors talk about the briar score again, which is used as a measure of success for predictions, not for the calculation of estimates. in fact, about the only thing the method presented in the book has in common with forecasting is the briar score. the randomness of the method is clear in another example about republican voters in colorado: … “so you think that the maximum you should raise your forecast is 10%. it’s now between 1% and 10%” (p. 168) “finally you settle on 4%”. this shows clearly that this is what we call a rule of thumb, which by itself is fine, but then it should say so clearly, and there is nothing new with this approach. maybe that is the most critical part about this book: that it pretends to be about forecasting but is instead a good collection of rules of thumb. it’s a method by which new information leads to small adjustments in the estimates. another methodological problem is that if you go with a certain hypothesis and gather a large amount of information in that direction, then you are likely to get a high likelihood of true or false because each new piece of information could lead to a small adjustment. it will also depend on the information you happen to find in the language(s) you can read. there will be plenty of information that you do not see or find, there will be some stories you tend to go with so in reality this incremental approach by which likelihoods are increasing or decreasing with percentage points is not that straight forward to use. chapter nine is entitled “superteams”. it starts by telling the disastrous story of the bay of pigs invasion (1,400 terrorists were surrounded by 20,000 soldiers when they tried to invade a foreign country) and how that lead to the cuban missile crisis. much of this is true but the authors forget to mention that the russian placement of missiles was also a reaction to the american placement of missiles in turkey. that in itself is an argument for the importance of knowing history. and if you did not know that it does not help to put you into a team of other superforecasters in a superteam asking superquestions. the result is just going to look even more wrong. chapter ten raises a relevant topic for anyone who has read this far, how it is possible to be a good leader and make accurate decisions if all you are getting are vague estimates. the answer suggested by the authors seems to be based on moltke, the prussian general. the reason moltke is largely implied is because he said that everything in war is uncertain. so, don’t trust your plan. an officer should be calm and assuring, and knows that he needs to make a decision in a fog of uncertainty. as often is in these kinds of books, there is the introduction of a german magic word that is supposed to explain it all (other examples in other books: “gestalt” or “verstehen”). the word this time is ‘auftragstaktik’, or mission command in english. as valuable as the idea may be, i am not sure it is going to be a consolation for obama when he is asked to take the risk of attacking a house just outside of a pakistani 51 army base. it is not going to give me more confidence in intelligence analysts. chapter eleven is the second to last and is called “are they really so super”? so, through the whole book they have been telling me how super they are and now they are about to say that they are not super? as could be expected, the authors do not give a clear answer. this is not unusual in these kinds of bestseller books either. instead, there is an insinuation, a hint to the reader to draw his own conclusion that they are in fact super because their predictions are best, which is a claim that can never be tested. the chapter goes on to talk about conversations with general mikael flynn who was the national security advisor for donald trump for 24 days, the shortest in the office's history. (he pleaded guilty to lying to the fbi over his contact with the russian government during the trump presidential transition). flynn tells the author that he thinks “societal conflicts” are at unprecedented levels. the reader thinks that he must have forgotten about the race riots of the 1960s and the american civil war. maybe he meant during the past generation, in the us, but it does not say so. the authors criticize flynn for falling for the “oldest trick in the psychology book”, assuming that what is presented to you is all there is. flynn’s inbox is full of reports that confirm this view. the authors argue that facts show that interstates conflicts have been declining since the 1950s: it’s enough to google the question and you will see. what the authors fail to mention is that googling a question is often a poor source of information, but otherwise they may be right. much of the information found on webpages is false and most good information is not freely available. that is one reason why books continue to be so important. not to mention a good general education. then there is a lot of kahnemnan and tverksy again, but few other references to psychologists’ research. there is also a comparison between the authors and kahnemann and taleb’s ideas about predictions, where the authors claim to be right. an interesting replica of a strategic memo written by linton wells ii (not linto wells, who was his father and a well-known american foreign correspondent) is presented. it was from 2001. in it, wells ii shows examples from the past hundred years of how fast foreign relations have changes, thus drawing the conclusion that the us should plan for something unexpected, that that is the best overall strategy. another good citation here is from eisenhower, “plans are useless, but planning is indispensable” (p. 244). the memo from rumsfeld citing wells ii says nothing about what england, and later the us, actually knew or how good their guesses were about the future at that time. it just assumes that they were surprised, which is probably close to the truth for most of the examples listed. at the same time, it’s a bit like saying that the us was not very good at predictions at the time (not that any other powers are recorded has having gotten it right more often, to my knowledge). wells ii’s response was to plan for adaptability and resilience as a way to meet the unexpected. this is also close to what the us has done with its continuous massive military buildup. one problem has been that there has not been any money for this buildup, so the government has turned to massive borrowing during the past administrations. (it is often forgotten, but obama borrowed more money and engaged in more wars than any of his predecessors since the vietnam war). the us has also not been able to make money on its wars, which is the other major problem. today they are in a squeeze needing to borrow more money to keep the military strong so as not to have to repay their foreign debt, which cannot be paid. in wells ii’s defense, we can say that he did not imagine the financing part of his strategy. unfortunately for the us and its allies the us military is failing both with adaptability and resilience. the authors then go on to speculate about why china may not become the world’s leading economic power by comparing it to japan. many thought japan would become the leader, but it did not happen, they reason. the authors do not discuss the fact that china’s population is growing to ten times the size of japan’s, the fact that china has been a world economic power for most of the past 2-3 millennia, except since the mid-1600s (the enlightment). they do not discuss cultural similarities or differences either, i assume again because they do not look at knowledge but how you think. sure, china may face great difficulties and may even decline as a result, but the authors are too light on this question. the simplicity with which this parallel is treated is symptomatic of the whole book when it comes to questions of history, geography and culture. their approach is a combination of psychology 52 studies and basic statistics, good enough, but not enough by itself. chapter twelve is the last chapter. it highlights the credo, “keep scores”. it also says to analyze results, but how to do this is not shown with any clarity anywhere in the book (p. 259). keeping scores, or evaluations of past performances, is a key part of any intelligence cycle (that is why it is drawn as a cycle), which is the most basic model any intelligence analyst is shown for how to work. that evaluations are not done in the american ic (or in many other countries, i am sure) is not surprising, but that is more a question of professionalism within the working corps. it’s a fact, the “sharpest knives in the box” don’t become intelligence analysts, not yesterday and not today. the ic is not mckinsey or kpmg, not yet at least. a useful rule of thumb mentioned in the book is to try to solve the larger questions by breaking them into many small questions. a parallel is made to the technique of pointillism (p. 263), where a painter makes a painting by adding a greater number of dots on the canvas. a few dots do not look like anything, but as more dots are added we see an image emerge, the larger picture or question. of course a painter knows what he is setting out to make so no dots are wasted. an intelligence analyst may collect the wrong dots, or dots belonging to another painting and it is far from certain that enough dots or the right dots are collected to get the larger picture so the parallel is merely suggestive. towards the end the author reminds us that his friend tom friedman (who is mentioned on every other page or so it feels) was for the invasion of iraq because he thought that iraq was the way it was because of saddam hussein. another possibility is that saddam hussein was the way he was because of iraq. friedman decided upon the first alternative. the authors point to the fact that the conclusion and his reasoning was not correct. to present the conflict in such simplistic terms is shocking, to say the least. anyone with a minor grip on history will analyze this conflict from a shia-sunni perspective, which could also explain why the sunnis felt desperate enough to form the islamic state after their defeat. it was the american-led invasion that created isis. actually us foreign policy is to blame for most of the disruption of the arab world and the middle east, which started with the first gulf war but whose history goes back to the beginning of the american-saudi relationship at the end of ww2, a relationship they inherited from the british. at the end the authors explain that superforcasters are more humble than other forecasters, analysts or experts; they do not show off and know their limitations (they do not need to go to davos, but leave that to others). they can do this because they have the support of a proven record of predictions. with the briar score they ride into the sunset. somehow i was never impressed but i know some of my colleagues are. conclusion there are many things that are good about this book. philip e tetlock is a scholar with an impressive number of publications and citation. the book is well-written and easy to read, but that is also the best that can be said. the book falls into a long line of bestselling books that have an extravagantly attractive title that has little to do with the content, and a first chapter that is all about promises of what is to be delivered in the following pages. as such, this is all too common in the management literature in general as we have known it since the early 1980s, maybe even earlier. it throws around the names of famous people and stories people can relate to. but what is the problem with that, the reader may ask. well the problem is that these types of management books continue to have a significant influence on practice, much more so than scientific articles or more instrumental books on intelligence analysis. this is not a new phenomenon either but has been going on since “in search of excellence” or maybe even longer. for the most part though these books are being discredited in the long run, but then it is too late, as their content has already been put into practice. for one thing there is nothing that has been presented in the book that helps explain why the project was better at predicting events than anybody else, if we are to believe that that is true. more worryingly, the book does not say how the authors and the project beat the other analysts, if it was by simply using a more vague language in its estimates or by the way correct answers were calculated. the rules of these competitions are never explained, at least not in the book. the main idea in the book is that if you give precise questions and ask for answers expressed in numbers for specific time frames, then you can also sit back and wait to measure the results. you will then know how good you 53 are. that by itself is not a bad idea. instead we are led on a series of loose threads and assumptions, by the authors who are expert analysts because they did so – “it took years” and won. it seems like a proven way to sell consultancy, but does not convince a reader who is even half awake. clearly psychology is important for decision making and forecasting, especially when confronted with social situations where an outcome is the result of the interaction and the expectations of several individuals with different interests and values. some of these problems can be modelled using game theory, but the authors fail to see that this is only one half of the equation. the other half is what you actually know. the intelligence reality of mr tetlock is much like that of a psychologist in a poker game. he does not know what the other person knows but tries to guess it based on his behavior. that is a much riskier way of solving a problem than using resources to actually find out. good intelligence is about finding out what hand was actually dealt. this will give us certainty to know how we could win the game, or at least avoid losing more money than what was in the pot. psychology is important in knowing how the player will behave. it is this other part of the equation—that the psychological insights are valuable—that tetlock introduces in this book. it’s a good suggestion to test or check guesses to learn from them, but it’s hardly a new or novel idea. it’s true that it is “astonishing” how many organizations do not check the intelligence they produce or buy, but it’s hardly a new problem or even surprising. the book is one in a long tradition of “hype” books which are so popular and not only in the anglo-saxon world, similar to nassim taleb’s book “black swan”, which the authors also refer to. you take something that is merely common sense and present it in an appealing way, such as that complete unknowns are like black swans. the reader will not have learned anything new, but old wisdom is frightfully well packaged, thus appealing. it does not help that the authors disagree with taleb in that they think that many swans that people say are black are in fact grey (another metaphor of the same type). i said at the beginning that this is a good book. the reason for this is that it contains many good rules of thumb. unfortunately, they are not listed in any single place in the book. we should break large questions into many small questions. we should make scorekeeping an integral part of intelligence analysis (p. 259). that is a simple but important lesson. thus the book is worth reading. jisib-vol-12_nr-3(2022).pdf journal of intelligence studies in business vol. 12 no. 3 (2023) open access: freely available at: https://ojs.hh.se/ pp. 27–37 knowledge mapping for the study of literature reviews mengqi wang khunanan sukpasjaroen abstract. this study aims to provide a systematic and complete knowledge map for education. in addition, it is designed to help researchers quickly understand author collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends, and research frontiers of scholars from a library informatics perspective. in this study, a bibliometric approach was used to quantitatively analyze the retrieved literature with the help of the bibliometric analysis software citespace. the analysis results are presented in tables and visual images in this paper. the results of this study indicate that collaborative relationships among scholars need to be improved and collaborative research relationships among research institutions are more fragmented. this study also points out the shortcomings of this study: chinese educational researchers and practitioners still have a relatively vague understanding of some fundamental issues in the process of integration and development of ai and education. therefore, this paper uses quantitative research methods such as bibliometrics 28 and visualization pictures to systematically and intuitively reveal the research progress and and to provide a reference for further research on this topic in the future. keywords: 1. introduction neering of making seeded machines that exhibit human behavioral intelligence characteristics, including reasoning, learning, goal-seeking, problem-solving, and adaptability (monostori, logical force for social development, has rapidly penetrated all walks of life and become a new driving force and trend for the development of various industries.in this situation, it has worldwide to adapt education to the needs of the intelligent era and to use innovative technologies to promote changes in teaching models and the cultivation of creative talents.the u.s. ai education and expanding ai and data science curricula into developing the talent needed for ai to drive economic development (white gated by the chinese state council in july 2017 proposes to develop intelligent education, use innovative technology to accelerate the reform of talent training models as well as teaching methods, build a new education system that includes intellectual learning and interactive cial intelligence in teaching, management, and resource construction (chinese state council, plan for national education development promulgated by the state council of china also proposed to “explore new models of future education and teaching by making comprehensive use of technologies such as the internet, big (chinese state council, 2017b).as can be seen, the use of ai technology to promote change and innovation in education systems has attracted a great deal of attention from countries around the world. although china’s education reform has made remarkable progress, there are still some outstanding problems, such as unbalanced education development, an imperfect cultivation model of innovative talents, and an unreasonable allocation of quality education resources. cial intelligence will become a “powerful tool” to crack these educational problems, playing an essential role in innovating education and teaching models, optimizing talent training programs, developing students’ professional skills, and building a lifelong learning system to promote the change and development of education in the future. in recent years, domestic experts and on the connotation and critical technologies of educational ai (leun et al., 2017), the connotation and target orientation of intelligent eduet al., 2018) and the innovative educational applications of deep learning and machine et al., 2017), etc. a preliminary discussion was and practitioners still have a relatively vague understanding of some fundamental issues in the integration and development of ai and education, such as the technical framework of ai in education, application models, and development challenges. based on this, this study uses citespace software to visualize and analyze the literaintelligence in education so that the readers can understand the current situation, research hotspots, and research trends of this research china more clearly and intuitively, and thus provide references for further in-depth research education. 2. literature review citespace is a java-based information visualization software developed by professor chaomei chen of drexel university, usa. it responding visual atlases, and interpret them 29 to understand the knowledge base, research hotspots, disciplinary frontiers, and new citespace requires jre 1. 4. 2 or higher as the runtime environment for the software authoring platform. although citespace can access many web services and other information through pubmed, etc., the internet is format input to citespace is the data format output by isi. unlike other similar information visualization software, the citespace software itself comes with a data converter, which can directly convert the data format downloaded from the internet without converting the downloaded raw literature data to the correlation matrix, which can eliminate the complex steps and processing of correlation matrix conversion, which is one of the advantages of citespace software (chen c, 2004).before starting data processing with citespace, the literature data creating a new project using citespace, two ture data store and one for the project store. the project storage path allows researchers citespace is running, and the setup process is done from the main citespace interface. citespace has the following essential features. (1) the raw data does not need to be converted into the format of the matrix, and the raw data format of databases such as wos and cnki can be directly imported into the same data sample, multiple plots can be performed to show the evolutionary characteristics of the data from different perspectives. (3) the software clearly shows the change of literature data over time by marking nodes the color of nodes is represented chronologically, clearly showing the citation of different resents the earliest time when the co-citation frequency of that connecting line reaches the selected threshold. citespace has four essential functions: (1) identify critical paths in the evolution of subject areas through citation network analysis. (2) identify crucial literature for the evothe potential dynamic mechanisms of disciplinary evolution. (4) predicting disciplinary frontiers. citespace software is used to detect and analyze temporal trends in disciplinary research frontiers and their relationship to the knowledge base and to discover internal connections between different research frontiers. by visually analyzing the information in the literature on the subject area, researchers can visually discover the evolutionary path of the subject frontier and the classical primary literature of the subject area. citespace software uses the cosine algorithm to calculate the strength of collaboration between researchers or institutions, and the power of connection between nodes represents the strength of association between researchers or institutions, which is calculated by the cosine distance of the angle between 2022). equation (1) is as follows. where cij represents the number of papers published by co-authors (author i and author j), si and sj represent the number of documents published by author i and author j, respectively, and the value of collaboration intensity ranges from 0 to 1. the main principles and methods of using citespace are as follows: divide and conquer principle: the idea of the divide and conquer strategy is to divide directly into several smaller-scale identical problems and solve them separately, dividing and conquering them. the basic idea of divide and conquer is to decompose a problem of size n into k smaller subproblems that are independent of each other and identical to the original problem. the solution for each part is found, and then each part is combined into a solution for the whole problem. success breeds the success principle: if a paper is cited in more articles, the greater the probability of encountering it when reading the literature and, therefore, the greater the probability of citing it in an article. barabasi and albert (1999) showed that many real-world complex networks are not regular random networks but belong to scale-free networks and made several studies on such a class of networks’ some studies on the number of features point to two fundamental properties that determine the scale-free properties of networks such as the internet, the world wide 30 web, and collaborative research networks of scientists: node growth and preferential connectivity. minimum spanning tree algorithm. weighted graph, and if the subgraph g’ of g is a tree containing all the vertices of g, then g’ is called the spanning tree of g. the sum of the weights of the edges of the spanning tree is called the consumption of the spanning tree. among all the spanning trees of g, the spanning tree with the minor consumption is called the minimal spanning tree of g. in modern mathematical graph theory, prim’s algorithm and kruskal’s algorithm can be applied and implemented by computer programming statements. expectation maximization algorithm. the maximum expectation clustering method (em clustering for short) is a basic algorithm for large likelihood estimation in statistics, i.e., the maximum likelihood estimation of parameters in distribution with hidden state variables. the algorithm is mainly applied to estimate the missing variable x from the availplete. the e step takes the conditional expectation, and the m step takes the maximum value. this iterative optimization method is known as the em method. clustering is performed by distance characteristics of nodes publication, authorship, node centrality, halflife, number of citations, etc. the criteria for clustering are determined by statistical analysis using the maximum likelihood estimation of the algorithm. clusters of nodes shown on the graph as different colors, i.e., clusters of nodes of the same color, form the same clusleads to the expected results. word frequency analysis method. by counting the frequency of core words such as keywords, subject words, and chapter words the research hotspots, knowledge structure, the frequency of subject terms appearing in a literature set can form a clustering network of these word pair associations. the proximity chuanhui, 2010). citation analysis method. the citation and journals, papers, authors, and other analysis objects are analyzed to reveal their quantitative characteristics and internal laws. citespace generates maps with richer colors and better appearance.in addition, we can view the articles covered by the nodes, the cluster’s size and content, and the cluster’s average year from the visual image.therefore, we decided to use citespace to analyze the data from this study.this study allows us to derive visual images, obtain partnerships between authors and research institutions, and identify research trends in the research the subject of this study is the application belongs to the subject of education, and cnki collected all data on this subject.with the help of cnki data sources, this study conducted preliminary research and obtained 527 literature records using advanced search tools with education. the authors imported these 527 documents into cite space software, automatically checked the weights, eliminated non-research documents and de-weighted them, and used word frequency analysis and citation analysis to conduct the analysis. 3. research trends 3.1 analysis of the results of a survey of chinese researchers analyzing the distribution of authors is a preticular discipline. the study of authors with research of the research topic.after the data set to author, in 2003–2020, with a time cut of 1 year. set selection criteria (top = 50, selecting the top 50 strata for each year) to get the visuthe corresponding font of the author, the more the posting volume, and the connecting line between the nodes represents the cooperation relationship between the authors, the thicker 31 the degree of connection, the more the coop5 (2%), indicating that the largest group of mary researcher and xinfeng gao, li chen, collaborative research team, which accounts for only 2% of the total number of researchers. 3.2 distribution of chinese institutions for research on the application of the node type was changed to the institution, and the software was run to obtain the visual mapping of research institutions on the applithe top 10 institutions in terms of the number 32 of publications were selected to draw table 1. the college of education of shaanxi normal university and the college of education technology of beijing normal university, and the college of education science of xinjiang terms of the number of articles, with four artiuniversity, the department of education of beijing normal university, the department of education technology of the college of education of peking university, the college of education of tianjin university, and are tied for the fourth place in terms of the party school of the communist party of china beijing materials co. and the college tied for the ninth place in terms of the number of articles, with two articles.this suggests that these research institutions have not focused much on how ai can be applied in education and have not studied it in depth. that researchers in these institutions have researched the application of ai in various focusing on the application of ai to a particthe whole network mapping is more serious, which indicates that the research among institutions is still relatively independent. the cooperation is not close enough and needs to be strengthened. the nature of the institutions shows that most institutions conducting and publishing-related research are universities, indicating that the leading positions of ai in education application research are in universities, and they are credited with the rapid development of ai in education application research. 3.3 hot spot analysis of chinese research on the application of keywords are a high-level summary of the research topic and content of the literature. proper keyword analysis can tell the literature’s actual research content, and measuring the number of keywords can determine the hot spots of disciplines, institutions, and this research set the node as keywords, set the node threshold as top n = 30, selected to obtain the knowledge map of ai in educawords of the retrieved documents, the size of the circle to which the keywords belong represents their frequency of occurrence, and the connecting lines between the nodes represent the co-occurrence relationship between the keywords. the centrality is a measure of the size of the connectivity in the knowledge graph network, and a purple color at the edge of the circle indicates that the centrality value of the node is greater than or equal to 0.1. according to the keyword co-occurrence mapping and partial keyword table of ai in education, it can be seen that the frequency and education. serial number count year institution 1 4 2019 college of education, shaanxi normal university 2 4 2006 college of educational technology, beijing normal university 3 4 2018 college of education science, xinjiang normal university 4 3 2019 cunjin college of guangdong ocean university 5 3 2018 department of education, beijing normal university 6 3 2010 department of educational technology, college of education, peking university 7 3 2018 college of education, tianjin university 8 3 2018 9 2 2019 party school of communist party of beijing materials co. 10 2 2019 33 serial number count centrality key word 1 124 0.57 2 108 0.62 3 17 0.1 education 4 13 0.03 5 12 0.09 smart education 6 11 0.05 education applications 7 9 0.08 deep learning 8 8 0.06 primary and secondary schools 9 7 0.02 education informatization 10 5 0 education technology 11 5 0.01 12 5 0.04 information technology 13 4 0.03 big data 14 4 0.03 ministry of education 15 4 0.02 16 4 0 information literacy 17 4 0.02 talent cultivation 18 4 0.01 programming education 19 3 0.02 creativity education 20 3 0.03 learners 21 3 0 grace 22 3 0.03 intelligent age 23 3 0.02 24 3 0.06 information technology course 25 3 0 26 3 0.01 new engineering 27 3 0 28 3 0.02 29 2 0.01 it 30 2 0 34 centrality of “ai,” “ai education,” and “education” are in the top position. the corresponding node area is large, which indicates the accuracy of data retrieval and topic matching, and the series of keywords are consistent and comprehensive in the domestic concept.as shown applications,” “deep learning,” “primary and secondary schools,” and “education informatization” are the main research hotspots. 3.4 keyword evolution analysis of research on the application of in addition to static analysis of the distribution of research hotspots of ai in education, it is also necessary to pay attention to the time zone changes of hotspots to discover the future development direction more effectively. we set the time segmentation as 2003–2020, select the node keywords, set the node threshold as top n = 20, and output the result as “time the time-zone distribution chart of ligence in education consists of a series of keywords in the corresponding time intervals, and the keywords corresponding to each time interval indicate the hot issues of research on be seen that the research on the application of ai in education from 2003 to 2020 is rich, and the whole is developing in depth. 2003–2020, with the increasing improvement of intelligent technology, the development of 5g, wap, cloud computing, smartphones, mobile internet, and other technologies tend to mature, and user needs are more extensive, profound research direction of research was information technollum and the problems that existed. 4. conclution ogy has pointed out the direction for the intellectual development of computer network technology. applying this technology to computer network technology is conducive to enhancing the technical level of computers and better-providing quality services for social and economic development. through the visual analysis of this study, the author believes that research can be conincrease the research and development of educational ai products and improve the quality of technical services: the research and development of educational ai products and 35 the improvement of technical service quality should strengthen the cooperation between intelligence experts, and enterprise personnel to understand the current realistic needs of ligence and education, and promote the development and application of intelligent products in education.second, the functional modules of educational ai products should be continuously expanded to effectively meet students’ personalized learning needs and teachers’ teaching requirements at different stages. currently, the chinese government actively advocates the introduction of ai-related courses in primary and secondary schools, so it can develop educational ai products that go with them, such as programming-based teaching tools and software, as a way to assist education and teaching and optimize students’ learning effects.third, to establish a complete education ai product safety supervision and evaluation system, standardize industry standards, and increase market supervision and monitoring efforts to ensure that enterprises provide safe, high-quality products and services for the development of education ai. cial intelligence in education, multi-disciplinary cross-collaboration to help the development of education innovation: dig deeper into in education, expand the application space so that it can better provide services for education can break the barriers to education and effectively integrate formal and informal learning. therefore, it is recommended that the chinese government establish an ai education service platform to gather global high-quality education resources and precisely push learning resources suitable for learners’ development according to their needs. establishing an ai education management platform in china to track and record learning process data and conduct deep mining and learning analysis to comprehensively understand learners’ interests and real-life needs can help to realize personalized education and lifelong learning. build a harmonious symbiosis “human-machine combination” new ecology, enhance ligence and education is an important trend in the intelligence era.educational ai will replace the repetitive work of teachers and reduce their pressure and burden to a certain extent, allowing teachers to spend more time optimizing the instructional design to facilitate students’ personalized learning. dents’ moral qualities, values, and emotional cial intelligence and still needs to be done by teachers.therefore, “human-machine integration” will become the mainstream trend mechanical and repetitive tasks will be completed by machines, such as replacing teachers to correct homework, organizing and collecting learning materials, arranging exams, etc. teachers will focus more on emotional interaction with students, shaping students’ personalities, cultivating moral qualities, and improving higher-order thinking skills.in addition, human-machine trust is a critical factor in developing educational ai. establishing a long-term human-machine trust mechanism is a prerequisite for building a harmonious and symbiotic “human-machine combination” new ecology. therefore, it is necessary to accelerate the improvement of the ai governance system, develop and embed ethical standards, create a more powerful, safe, and trustworthy educational ai application system, and promote the peaceful development of ai and education integration. strengthen the “government, enterprise, academia and research” multi-party cooperation, collaborate to promote the rapid develeducation is a long-term and arduous task, only “government, enterprise, academia and research” multi-party cooperation to proattach great importance to the development of educational ai, establish a sound system to guarantee the system, and continue tional ai to protect the innovation of intelligent technology.secondly, enterprises should increase the design and development of educational ai products, expand product supply, improve service quality, and cooperate extensively with schools and research institutes to broaden the development channels of enterprises.again, schools should actively explore the education and teaching mode supported by ai technology, offer ai-related courses, and focus on cultivating students’ data science literacy and computational thinking skills to 36 meet the development needs of the future intelligent era and continuously deliver talents for enterprises and research institutions. the frontier of ai development, widely conduct theoretical research on ai educational applications, and build a new generation of educational ai theoretical systems. through continuous technical breakthroughs and product innovation, solve the technical problems faced in the development of educational ai and provide technical support for developing enterprise products. establishing educational ai demonstration sites and exploring the application model of educational ai: based on the principle of “pilotmoting,” we will select areas and schools with good informationization conditions to establish educational ai demonstration sites and explore the application model of educational ai, and gradually promote it to the whole counindustry or university ai experts as consultants to provide regular guidance on the construction of the demonstration site and worked to build a team of information technology personnel, including ai teachers. in addition, artito administrators and teachers in pilot district schools to strengthen education administrators’ understanding of ai educational applications and to enhance teachers’ ability to apply and guarantee system is developed to encourage teachers and administrators to innovate the application of ai technology, innovate the education and teaching model, and improve teaching standards. in the era of big data, the integration of technology is deepening. based on the charcomputer network technology in the era of big data 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(2022). knowledge mapping of research data in china: a bibliometric study using visual analysis. , (ahead-of-print). tion of educational applications and innovations of machine learning in the perdistance education, (3):11–21. cial intelligence in computer network technology in the era of big data. science and technology innovation and application, 2020(33):168–169. 57 towards an environmental awareness model integrating formal and informal mechanisms – lessons learned from the demise of nortel jonathan calof 1 , laurent mirabeau 1 , greg richards 1 1 telfer school of management, university of ottawa, canada email: calof@telfer.uottawa.ca mirabeau@telfer.uottawa.ca richards@telfer.uottawa.ca received april 20, accepted may 6 2015 abstract: this case study uses multiple lines of enquiry to better understand how nortel went from being a ‘global powerhouse’ at the turn of the century to filing for bankruptcy just nine years later. it tracks competitive intelligence as well as other environmental awareness capabilities of the company and theorizes on how they have contributed to its rise and fall. the findings suggest that nortel was a company with significant environmental awareness capability in the early 90’s that had all but lost this competency by the year 2000, which impacted their ability to make decisions consistent with a changing environment. through interviews with 48% of all nortel officers that were there during the period of interest as well as other stakeholders, the researchers identify a two-layer typology that includes a set of cognitive factors as well as three broad categories of monitoring practices that can help companies better understand their environment: 1) formal external monitoring practices, such as competitive intelligence units; 2) informal external monitoring practices such as board meetings with members with industry connections and knowledge, and 3) internal monitoring practices with external insight capability, such as performance management reviews and accounting reports. cognitive factors identified include decision maker orientation, as either technical or business, internal vs., internal focus, cognitive complexity and open mindedness. keywords: nortel, competitive intelligence, corporate failure, monitoring practices available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 1 (2015) 57-69 mailto:calof@telfer.uottawa.ca mailto:mirabeau@telfer.uottawa.ca mailto:richards@telfer.uottawa.ca https://ojs.hh.se/ 58 1.0 introductiondescription of the case study by 2001, nortel, a canadian telecommunications company with a capitalization approaching $300 billion, was accounting for nearly one third of the toronto stock exchange; the largest valuation in canadian history. macdonald (2000), in his book entitled “nortel networks : how innovation and vision created a network giant” described the company’s extraordinary success that lead to 75% of all internet traffic in north america being funneled through nortel equipment at the time the book was published. indeed, in 2001, nortel had crafted itself an enviable leadership position in optical, wireless, wireline and the business enterprise markets. yet, by 2003, less than thirtysix months later, nortel’s long-term viability was being seriously questioned by its own customers. a few years later as detailed in a 2007 note from senior management, nortel was experiencing continued erosion in the company’s ability to influence the business roadmap of an increasing number of key customers. in january 2009, the company filed for bankruptcy protection. this was the single biggest corporate failure in canadian history and one of the largest worldwide. this case study looks at the role played by the environment and the company’s environmental monitoring approaches/systems to understand both the success that culminated to nortel’s position in 2001 and the failure that brought about bankruptcy in 2009. specifically, theorizing from an extensive data set that includes both interviews and surveys, the authors seek to understand: 1. how the environment changed and in particular whether significant opportunities or threats arose. 2. given the changing environment, the extent to which nortel’s response contributed to both its success and to its failure. 3. nortel’s capabilities/approaches to understanding its environment. this study proposes a revelatory single case study of both epic success and epic failure, theorizing about the role of competitive intelligence in both the rise and fall of a company. this is in keeping with solberg søilen’s findings (2014) regarding the need for more case studies in intelligence. 2.0 case study methodology the study features multiple data collection methods, including an initial survey (343 respondents), interviews with nortel stakeholders (133 people), a follow-up survey of those interviewed (57 respondents) and a validation check of the study results with 22 of the interviewees. the methodology had at its core a grounded theory approach. grounded theory was used to ensure that a-priori hypothesis and existing literature did not bias or drive study conclusions but that the study participants drove study findings. analysis moved in an iterative fashion with data collection as initial interviews and surveys allowed the researchers to refine the interview protocol. methods for analyses included three main techniques that have been identified as prominent in process research (langley, 1999): a grounded theory approach was taken for coding the interviews (glasser and strauss, 1987), a narrative strategy was used to uncover the richness of this revelatory case (yin, 2003; patton, 2002) and temporal bracketing was used to organize the findings in building a model and uncovering monitoring practices as well as cognitive factors (eisenhardt, 1989). the initial survey consisted of open-ended questions combined with a series of seven-point likert scale questions around causes of failure. in total 343 responses were received (table 1). interviews were then conducted with those familiar with nortel’s failure. in all 133 people were interviewed (some multiple times) including 48% of all nortel officers who were at nortel at some point over the study time period (1997-2009), several key customers (interviews were with senior customer personnel generally at the “c” level), competitors (including competitive intelligence personnel of key competitors), suppliers and others that would have knowledge of the nortel failure. the second survey was sent to all informants who were interviewed (133) giving them a final opportunity to list the reasons for nortel’s failure. responses were received from 57 of those interviewed. as a final validation step and in keeping with the case methodology, the final case results were presented to 22 of those interviewed. 59 in the first step of the analysis, both the interviews and the surveys were coded using a mixed logic, as we derived our codes partly from our literature review on organizational failure and partly by letting them emerge from the data (gioia, corley & hamilton, 2012). established techniques of the field such as inter-rater reliability were applied and we conducted this work using nvivo 10. in the second step we layered temporality on the data, to identify when each failure factor happened, both in terms of the external and internal perspectives (mellahi and wilkinson, 2004). in the final step we built a narrative of nortel’s events, providing a rich account from the temporally layered fine grain data we had collected and analyzed (van de ven and poole, 1990). three temporal periods were identified: 1. 1997 to 2001, corresponding both to the ceo tenure of john roth and also the rapid rise of nortel culminating to its maximum market capitalization value in 2001. 2. 2002 to 2004 corresponding to the ceo tenure of frank dunn, rapid change in industry dynamics and a series of internal crises within the company. 3. 2005-2009 – the ceo tenures of bill owens (interim ceo appointed on the firing of frank dunn) and mike zafirovski culminating in nortel’s filing for bankruptcy protection. table 1 – data collection methods and response numbers data collection step total* officer/senior employees other employees customer external initial survey 343 60 265 53 127 initial interviews 133 46 45 18 35 final survey 57 20 18 8 13 validation interviews 22 11 0 7 6 *note that the totals do not necessarily correspond to the summation of the columns as in some cases respondents during the study period fell into two categories. for example in several cases officers/senior employees in the 1997-2004 period then moved to customer or competitor organizations in the later years. 3.0 findings: an overview of environmental changes for each period in the telecommunication industry between 1997-2009 the majority of interviewees commented on the significant industry change throughout the study period. indeed, interviewees recounted how 1997 to 2001 was a period of great opportunity in the industry; fuelled by the advent of the internet, as well as the growth in demand that accompanied the deregulation of various foreign markets, providing new vectors for market development. these created opportunities that propelled many of the firms in the telecommunications supply industry to historically high market capitalization values by 2000/2001. the second period ranging between the years 2002 and 2004 was also one of significant industry change. participants of our study described how the .com bubble bursting resulted in significant decline in demand for all industry participants. this was further complicated by new competition arising from china, which had made important strides in catching up with the incumbents in the market in terms of technology expertise. while demand was stalling, rapid technology advancement continued unabated. the third period during 2005-2009 saw continuing increase in competition and major changes in both how customers bought telecommunications product and the criteria used for acquisition. furthermore, the customers during this period began to push industry suppliers towards interoperability with other equipment makers and also sought to diversify their risk by purchasing from multiple suppliers rather than following the historical pattern of relying on a single supplier. unfortunately for nortel, as new and old competitors were gaining ground gaining access to nortel’s traditional customer base, nortel was not taking customers from rivals. 60 the global recession was also part of this third period. the events in this period, according to our data, had a significant impact on underlying industry profitability and the nature of the opportunities. indeed, while the latter period presented firms with significant opportunity due to rapid growth in both internet and wireless lines of businesses, the growth opportunities came at the expense of a more commoditized and competitive landscape. by 2009, nokia and siemens telecommunications divisions had merged to become nsn and alcatel and lucent also merged creating alu. 4.0 findings: nortel’s response to the changing environment interview and survey results overwhelmingly noted that nortel appeared to respond well to industry opportunities in the late 80’s and early 90’s but that the company had lost its way by the later 1990’s. the practices to understand the environment was not seen as being effective; nor was the company’s ability to both sense and appropriately respond to industry changes in the 2000’s. for example, interviewees talked about the fact that in the 80’s and 90’s nortel was the first company to go from analog to digital. however, many respondents in both the initial and final survey listed nortel’s failure to adapt to the market as a primary reason for failure (table 2). customers listed this as the #1 reason for nortel’s failure citing in particular lack of appropriate response to customer needs . in fact, both customers and others said that nortel was late to the internet in the late 90’s. table 2 2009 initial survey responses to environmental related questions nortel responded well to its markets and customers competition suppliers strongly disagree 13% 20% 10% disagree 18% 29% 10% somewhat disagree 23% 18% 14% not sure 9% 6% 37% somewhat agree 21% 16% 18% agree 13% 9% 9% strongly agree 2% 2% 2% findings in other reports from the nortel study provide both support and provide insight into the survey and interview observations listed about (see calof et al 2014, vasudev 2014 and mackinnon et al 2015). in examining technology choices, mackinnon et al (2015) found that research and development and commercialization activities tended to focus on legacy products which would be sold to mature markets and not innovative products for growth markets – 55% of research funds going to late life cycle products, 36.5% towards mature products and only 8.5% allocated to future and emerging products. their analysis found that in the 2000’s nortel failed to commercialize several of those products that were under development. they also did not develop products and services that could have been sold to those areas of the market that were profitable and growing. they concluded that while the products in r&d were very advanced, sometimes even exceeding customer needs, the products nortel chose to commercialize were more oriented towards existing technologies and did not support their customer’s emerging needs. the calof et al (2014) report also noted that nortel responded to the changing market conditions later than many of the other competitors concluding that they were late to both perceive and accept the changes in the environment. in summary, our data suggests that while the environment changed in a significant way during all three periods of the study, that nortel, a company that was known historically for its innovativeness, for anticipating and creating future markets, and for leading customers during the pre-1997 period, responded inadequately to these changes. more specifically we found that nortel: 61  was late to recognize and respond to environmental changes,  commercialized the more mature technologies in its portfolio and,  did not respond appropriately to new customer business requirements 5.0 findings: towards an environmental awareness model sections 3 and 4 described how while nortel had historically seen and taken advantage of opportunities created from industry change, in the period of interest from 1997 to 2009, it was late to recognize and make appropriate changes. this failure eventually led to the erosion of its enviable pre 1997 leadership position. how then could a company that had exhibited foresight in the past, go from frontrunner to laggard in the industry in such a short time span? to better understand nortel’s ability to assess environmental changes, the research team examined data collected during the case study that would shed light on nortel’s monitoring practices as well as its cognitive makeup, the way it understood its own world. in particular, we reviewed interview notes and survey written responses for specific comments around nortel’s ability to learn about and act on the environment. many of those interviewed talked about the early to mid 90’s and nortel’s extraordinary competitive intelligence unit and competitive intelligence guild (an across-lines of business “club” that brought together nortel ci practitioners and users, hogan 2001). they talked about nortel’s design and interpretive center – a unique center where nortel invited their customer’s customers (the end users of telecommunications equipment) to use the nortel products that would be sold to the telecommunication companies. this helped nortel learn more about the end user’s needs so that they could develop better products for their customers. many talked about an advanced planning function (some referred to the unit as division 6) that engaged in environmental scanning and reported directly to the top levels of the corporation and about customer surveys, something of great importance at nortel which provided a wealth of information. the competitive unit, the competitive guild, the planning unit, the design interpretive center and the customer survey, we have grouped under our first type: formal external monitoring practices (see exhibit 1). a second type that emerged from our data was practices that that also helped nortel gain insight into the external environment without being part of the formal external monitoring mechanisms, but rather were informal. for example, many talked about bell northern research (bnr) units and their work, a long-term oriented research group that conducted fundamental research for both nortel and bell. this unit through its relationships with scientists around the world, its involvement in symposium and even through its own magazine can best be described as nortel’s long-term competitive technical intelligence unit. bnr it was said in many interviews created the future environment. bnr was an important part of an external technology monitoring capability that would then translate this knowledge into design and future products. they were not intelligence personnel but scientists in what many called an ivory tower environment. their job/role was not environmental scanning but developing new technologies and in doing so they would scan the pertinent literature, attend appropriate conferences and network with various external experts, in an informal yet effective manner. several respondents also talked about how nortel learned a lot due to ongoing interaction between technical staff and nortel clients. one senior technical person commented that by listening to the clients’ concerns they could ‘in 10 minutes develop new solutions’. industry relationships were also seen as a method for gaining knowledge about the industry with many of those interviewed commenting on the closeness between nortel senior management (in particular sales management) and customer senior management, outlining the information they gained because of these relationships. one interviewee commented that the telecommunications supply industry was ‘truly a village, a community where everyone knows each other’. others talked about the valuable information gained thanks to for example board members, in particular the board members who represented bell canada enterprise (bce), a key nortel customer. having a customer on the board provided nortel with valuable information on customer’s needs and concerns as well as test sites for new technology. also mentioned was nortel’s links with universities through endowed chairs and research programs, which provided valuable insight into technology developments to nortel. trade shows and conference involvement were also mentioned as notable sources of industry information. finally, many talked about management development programs such as the princeton series, where once a year nortel senior management would attend an inhouse program in which leading management thinkers (for example drucker) would provide nortel with insights into new management techniques, management approaches and evolving market changes. while none of these activities/organizational elements were specifically designed as formal environmental monitoring mechanisms, respondents were clear that each provided valuable insights into the 62 external environment, early warning on customer needs/changes, technology changes and even early warning on competitor movements. we refer to these as informal external monitoring mechanisms (see exhibit 2). thirdly, respondents talked about internal systems such as the accounting system, and how those also provide insight into the external environment. for example, respondents talked about how by analyzing where sales were coming from (legacy products versus new technologies) they could figure out underlying customer sentiments. in addition, forms used in the sales approval process (many talked about b forms), provided insight into customer demands.. performance management practices (increasingly developed in 2007) proved to be valuable in identifying markets and research and development using the product life cycle stage model. many also mentioned that internal relationships facilitated information flow across units; that no matter how bad systems were, they were always able to call up someone they knew to get information on what was truly going on. internal relationships were used for example to provide updates on technology developments within and outside of the company. we refer to these as internal systems with external insight (see exhibit 1). thus we found three types of monitoring practices: formal external, informal external, and internal with external insights. however, our data analysis unveiled another important component to the model: the cognitive makeup of the company, which impacted its ability to make sense of the data that was unearthed by the monitoring practices. indeed, respondents talked about the mindset and cognitive abilities of decision makers when receiving information about the environment and how these abilities impacted decision maker’s sensemaking (cite weick here). our analysis indicates that it was not just about having the information, that decision makers also needed the right mindset when receiving it. for example many talked about nortel’s strong culture creating a “not invented here” type mindset resulting in the perception that management was not open minded to information about possible environmental changes that came from outside the company, especially when it was contrary to their beliefs in technology needs. some referred to this as “not invented here syndrome” and some referred to this as open-minded versus closed-minded. others talked about an external focus versus an internal focus of management. this was a particular factor brought up in the 2000’s when a series of internal crises (restatements, fraud investigation, staff cuts) focused senior management attention on activities inside the organization rather than having the time (or interest) to focus on the external environment. respondents also talked about technical versus business orientation of management. while a technology oriented company does need a mix of both technical and business orientation, many talked about the ability, or in some case the inability of senior management and board members to comprehend the technology implications of strategic decisions. specific examples were brought up where it was evident that the decision maker may not have fully understood the technical impact of the decision. finally a few respondents brought up the complexity of decisions that senior management had to make. this was referred to in interviews as their ability to handle multiple variables at one time (e.g. simultaneous consideration of multiple competitors and customers along with technology change as opposed to assessing one at a time) and overall intelligence of the senior manager. we refer so these factors as decision makers’ cognitive makeup. exhibit 1 provides the overall environmental awareness model arising from analysis of the respondents comments on nortel’s environmental understanding capability and provides a competitive intelligence perspective of nortel’s rise to prominence leading to the beginning of our three temporal periods. 63 exhibit 1 environmental awareness model: the case of nortel 6.0 the evolution of nortel’s environmental awareness over the study time period: decisions, environment and impacts. in this section we examine developments in nortel’s environmental awareness and discuss key decisions made during the three temporal periods. 6.1 1997 – the starting point of the study albeit with a few exceptions (difficulties in gathering intelligence from poor accounting systems, a culture of close-mindedness to outside ideas, and the use of non-systematic performance management systems), respondents commented positively on all but three elements included in the environmental awareness model.. based on the variables in the environmental awareness model, the 1997 starting point would be defined as good in all four elements. this assessment is based only on the existence of the factors and is not an assessment as to their quality. 64 exhibit 2: environmental awareness model: nortel, 1997 6.2 1997-2001: nortel’s growth 1997-2001 provided companies in this industry with great opportunities. john roth (ceo of nortel) saw the opportunity to significantly grow the company and developed a new vision for nortel, which he called the right angle turn, a refocusing of nortel traditional’s telephony technology to the internet protocol based technology. roth felt that dealing with rapid growth and massive market opportunity meant the need to eliminate or change any procedures that slowed down responding to customers. furthermore, since nortel did not have all the technologies required for the right angel turn, roth felt that nortel would have to engage in systematic acquisitions of external technologies. in a business sense these decisions and actions appeared to provide immense value to the company and its shareholders, and were handsomely rewarded by the stock market. in 1997 nortel’s market capitalization was $23 billion and by 2000 once the strategy was fully in place it was $250 billion; sales had more than doubled and the gross margin had improved. as well customers in general were pleased with the company. by the end of this period not only did nortel realize its ambition to grow in terms of sales and market capitalization but its organization had also grown significantly, going from roughly 30,000 to 95,000 employees. while the streamlining of decision-making did lead to both sales growth and stock growth, it also had a negative effect on nortel’s environmental awareness capability. on the acquisition side, the buying of dozens of companies coupled with nortel’s antiquated accounting systems left nortel in a situation where it was had islands of information and no sense of the integrated accounting picture. some in the interviews commented that it took several months after the quarter before the true numbers could be known. this reduced the ability of internal systems with external insight to generate accurate environmental information. but perhaps it was those changes made to speed up nortel’s ability to meet customers’ needs that had the biggest impact on environmental awareness capability. for example, nortel eliminated some of the administrative forms, including sales forms (such as b forms) opting instead to place more responsibility on salespersons for sales terms than requiring sign offs of management. while this sped up response, it also reduced the abilities of internal systems with 65 external insight. massive hiring during this period (from 30,000 to 95,000) led to reduction in the strength of internal relationships, again a downward impact on internal systems with external insight. informal external monitoring mechanisms also were reduced as an indirect consequence of right angle turn. for example, bell northern research (bnr), the central research arm of nortel was split up and placed into each of the four product divisions. in this way, research could be focused more at the division level. but, since business lines tend to be short to medium term focused, respondents stated that longer-term research and technology suffered. further, the split up of bnr also fractured the strong network and information sharing that existed within the group. another change during this period was bce reducing its ownership and involvement with nortel (eventually selling all remaining stock in the next temporal period). this reduced the influence and impact of bce at the board level, effectively removing an important voice of the customer at the table. the result of restructuring decisions and bce was therefore a significant reduction in informal external monitoring. exhibit 3: environmental awareness model: nortel 1997-2001 perhaps the biggest impacts arising from the right angle turn, was in the formal external monitoring. those interviewed talked about reductions in competitive intelligence both in terms of role and effectiveness, the competitive intelligence guild and the closing down of the design interpretive center and reduction in the role of the central planning unit (again consistent with movement towards more divisional power). collectively this meant a significant reduction in formal external monitoring. exhibit 3 highlights the changes in the elements of the model. it shows how seeking to develop a faster customer response capability had negative impact on several monitoring practices. next we look at the second period. 2002 – 2004 the market turns and internal focus begins much like the first period, 2002-2004 was a period of significant industry change. however, the change was much different: from a positive growth environment in the first period, nortel experienced a hostile retracting demand environment after the dot.com bubble. it meant that there was significant oversupply in the industry and with increased competition from asia and increasing customer power there was downward pressure on prices. 66 unfortunately, as was mentioned in interviews the decrease in environmental awareness capability during the 1997-2001 period left nortel late as many noted to react to these changes. our data shows that to remain in this industry, nortel would have needed to reduce their costs significantly or capture significantly more sales to gain economies of scale. decisions made during this period were consistent with this idea. a new ceo was hired, frank dunn, nortel’s former chief financial officer. a cfo as ceo was logical given that the challenge was a financial one. under dunn’s leadership the head count was reduced from 94,500 in the beginning of 2001 to 35,160 by the end of 2003 (versus 68,000 in 1996). the new ceo also worked on fixing structural issues and on the accounting systems. as expected, there were other significant cost cutting measures, although efforts were made to minimize the cuts to r&d. exhibit 4: environmental awareness model: nortel 2002-2004 while these measures helped to stabilize nortel’s financial situation they further weakened nortel’s environmental awareness capability (see exhibit 4). massive layoffs meant that technical staff could no longer spend as much time with customers as there was limited time outside of the main operational day-to-day tasks. needed reductions in trade show attendance, in management training initiatives, as well as lower university funding meant that informal external monitoring capability was further eroded. as well, as this period focused on what respondents said were almost weekly requirements for management to reduce headcounts meant that the focus of nortel management was now internal with limited time to focus on external environmental issues. environmental awareness capability also eroded during this period due to the wilmer-cutler investigation. wilmer-cutler, a washington law firm was hired by the board to investigate a potential financial irregularity. the subsequent investigation, according to those interviewed in the study, was very intrusive and resulted in a lengthy focus by executives of nortel on the investigation (once again a factor which further increased the internal focus). wilmer-cutler’s recommendations, which were accepted and implemented by the 67 board, included the firing of the ceo (frank dunn) and many other senior executives. the firings of senior executives along with the layoffs of some 60,000 staff also resulted in a reduction in the number and strength of relationships between nortel management/staff and customers. several customers commented on this. 2004 ended with a restructured nortel, a new ceo (bill owen, a board member who volunteered to temporarily fill the role), and a significantly streamlined organization. however it also ended with eroded capability for informal external monitoring, reduced internal systems with external insight capability and attenuated decision maker cognitive abilities (see exhibit 4). 2005 – 2009 the road to bankruptcy protection with frank dunn fired, there was a need for a new ceo. bill owens, a member of the board, volunteered to fill this void temporarily until a new ceo could be found. in november 2005 mike zafirovski was hired as ceo. the accumulating weaknesses mentioned earlier in environmental awareness capability were perhaps most visible during this period. for example, in 2006/2007 an internal document noted that the turnaround of nortel was well in hand with significant recent sales from two key customers. however, the customers themselves told the researchers that the sales were reflective of a concern about nortel’s viability and the need to stockpile nortel parts should nortel go out of business. perhaps with stronger environmental awareness capability as was seen in the 1990’s nortel management would have known this. further, as was also noted both by customers and by others interviewed, during this period (2005 to 2009) sales were predominantly in legacy products. customers were reluctant to buy nortel’s newer technology solutions, again for fear that nortel would not be around to service them. sales may have been increasing during part of this temporal era but the limited environmental awareness capability meant that nortel might not have been aware that customers were in fact stockpiling legacy replacement parts, and that the growing customer discontent had them question the company’s future. our data shows that customers wanted nortel to either merge with another company or sell business units and focus on one or two businesses rather than the current four (optical, wireless, wireline and business enterprise). however, nortel’s decisions during this period were not consistent with these expectations thus significantly eroding customer confidence. both owen and zafirovski recognized the need to improve nortel’s systems and to also deal with the various lawsuits and other legal issues confronting nortel. they also saw the need to meet with and reassure customers who were growing increasingly concerned with nortel. zafiroviski’s strength according to several interviewed was in management systems. having worked with general electric (ge) he brought with him knowledge of ge systems and methodologies, which he started implementing at nortel. he also hired several new “c” level officers with similar backgrounds. zafirovski also went about trying to improve quality at nortel and further reduce manufacturing costs by implementing six-sigma. he also oversaw the installation of a performance management system that included r&d and technology assessments. competitive intelligence was also strengthened as part of this investment in systems. nortel could see what was in front of them. but informal external mechanisms were further weakened. customers talked about not seeing technology workers as much, different kinds of conversations, and constant changes plagued their once strong relationships. the new top executives came with strong business skills, but did not have the same understanding of technology that past leaders had exhibited. both customers and technical staff cited specific what was perceived by them as strategic errors made by senior management which were indicative they said of senior management not having a sufficient awareness of the technical dimension of the job.while many interviewed did cite strong business decision making abilities within senior management it was the technology acumen that was questioned. 68 exhibit 5: environmental awareness model: nortel 2005-2009 in summary, 2005-2009 brought with it strengthening in formal external monitoring, informal external monitoring and internal systems with external insight. however, decision maker cognitive factors appeared to weaken with continual focus on internal matters (e.g. six sigma and additional lay-offs) and reduction in technical capability at the senior levels of management. 7.0 conclusion in january 2009, nortel filed for bankruptcy protection and subsequently sold all of its units. while the company had immense technology strength (its patents were purchased for $4.5 billion), the failure to see and adapt to the new competitive environment contributed to this company’s downfall. yet, strength in environmental awareness in the 90’s had contributed to the rise of the company and was a key element of their success during this period. using a multi-method approach involving multiple surveys and interviews, this in-depth case study has examined the impact of the change in environment on nortel and of nortel’s environmental awareness capability during the turbulent period (1997 to 2009). this study makes two notable contributions. first, the study theorizes building a model of environmental awareness that features three types of monitoring practices as well as cognitive factors that impact sensemaking abilities of decision makers (exhibit 5): 1. formal external monitoring practices (for example competitive intelligence, planning) 2. informal external monitoring practices (for example board members reaching out) 3. internal monitoring practices with external insight capability (for example accounting systems) 4. decision makers cognitive makeup (for example the level of open mindedness) the case study traces the development of each of these factors during the study time frame and noted that in the last time period (2005-2009) the first three were strengthened while there was not a strengthening of the fourth factor (cognitive makeup factors) with in fact the focus still being internal. this latter factor might have contributed to the customers’ perception that nortel was not responding to their concerns. as a result, customers were wary of buying nortel’s new technology offerings. second, the case study has shown how decisions that make sense from a business and environment perspective may in fact have an adverse effect on 69 environmental awareness. for example, while costcutting during the 2002-2004 period was needed given the industry dynamics, it reduced nortel’s informal external monitoring capability. similarly, organizational restructuring in the 1990’s designed to increase speed of response to customers, also resulted in a reduction in formal external monitoring capability. furthermore bce’s sale of nortel stock and subsequent exit from the board, also led to a reduction in informal external monitoring capability. accordingly the study makes a notable contribution to both the academic and practitioner communities illustrating that significant changes to strategy or organization should be examined for any unintended impact on environmental awareness capability. readers are advised however that these findings are based on a single case study. the list of items provided above under the four categories (decision maker cognitive makeup, formal external monitoring, informal external monitoring and internal systems with external insight) is exhaustive from the perspective of the nortel, however it might not be exhaustive for other companies. future research should seek to expand and to validate the model in different organizations. furthermore, no attempt is made to evaluate the effectiveness of each of the monitoring practices or the cognitive factors. further studies are required to validate these findings (calof et al, 2014). 8.0 references austen, ian. (2009). nortel seeks bankruptcy protection. new york times, january 14, 2009 as referenced on www.nytimes.com/2009/01/15/technology/com panies/15nortel.html?_r=1& calof, jonathan., richards, greg, mirabeau, laurent, mouftah, hussein, mackinnon, peter, chapman, peter (2014) an overview of the demise of nortel networks and key lessons learned. http://sites.telfer.uottawa.ca/nortelstudy/files/20 14/02/nortel-summary-report-and-executivesummary.pdf calof, jonathan (2014). evaluating competitive intelligence from the users perspective. journal of intelligence studies in business, 4 (3): 79-90. eisenhardt km. 1989. building theories from case study research. academy of management review, 14(4): 532-550. gioia, d. a., corley, k. g., & hamilton, a. l. 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(1999). strategies for theorizing from process data. the academy of management review 24(4): 691-710. macdonald larry (2000) nortel networks : how innovation and vision created a network giant. john wiley and sons. canada. mackinnon, peter, chapman peter and mouftah, hussein (2015) nortel technology lens: analysis and observations. university of ottawa school of electrical engineering and computer science. mcfarland, janet (2011). enron and the biggest corporate governance scandals of the past decade. the globe and mail, november 27 as referenced on june 14 2014 at www.theglobeandmail.com/report-onbusiness/careers/management/board-games2011/enron-and-the-biggest-corporategovernance-scandals-of-the-pastdecade/article640949/ mellahi, k., & wilkinson, a. (2004). organizational failure: a critique of recent research and a proposed integrative framework. international journal of management reviews, 5/6(1), 21-41. patton mq. 2002. qualitative research & evaluation methods, sage publications: london, uk reardon, marguerite. 2009. nortel files for bankruptcy. http://www.cnet.com/news/nortelfiles-for-bankruptcy/ accessed april 8 2015. sheppard, j. p., & chowdhury, s. p. (2005). riding the wrong wave: organizational failure as failed turnaround. long range planning, 38, 239-260. solberg søilen, klaus. (2014). a survey of users’ perspective s and preferences as to the value of jisib a spot check volume 4, no 2, 61-66 van de ven ah, poole sm. (1990). methods for studying innovation development in the minnesota innovation research program. organization science 1(3): 313-335. yin rk. (2003). case study research: design and methods. sage publications: newbury park, ca http://sites.telfer.uottawa.ca/nortelstudy/files/2014/02/nortel-summary-report-and-executive-summary.pdf http://sites.telfer.uottawa.ca/nortelstudy/files/2014/02/nortel-summary-report-and-executive-summary.pdf http://sites.telfer.uottawa.ca/nortelstudy/files/2014/02/nortel-summary-report-and-executive-summary.pdf http://archive.fortune.com/galleries/2010/fortune/1002/gallery.biggest_losers.fortune/ http://archive.fortune.com/galleries/2010/fortune/1002/gallery.biggest_losers.fortune/ https://www.globalintelligence.com/insights/world-class-market-intelligence/intelligence-benchmarking-tool https://www.globalintelligence.com/insights/world-class-market-intelligence/intelligence-benchmarking-tool https://www.globalintelligence.com/insights/world-class-market-intelligence/intelligence-benchmarking-tool http://www.fptt-pftt.gc.ca/pdf/hogan.pdf http://www.fptt-pftt.gc.ca/pdf/hogan.pdf http://www.cnet.com/news/nortel-files-for-bankruptcy/ http://www.cnet.com/news/nortel-files-for-bankruptcy/ jisib-vol-12_nr-3(2022).pdf journal of intelligence studies in business vol. 12 no. 3 (2022) open access: freely available at: https://ojs.hh.se/ pp. 6–17 competitive intelligence in an ai world: practitioners’ thoughts on technological advances and the educational needs of their successors abstract: information age trends have caused the competitive intelligence (ci) industry interested in knowing what knowledge and skills are necessary for future practitioners. in 2022, addressed this topic’s relevancy, noting increases in ci departments the question of what skill sets are needed for future ci analysts and how do instructors prepare them for an evolving and dynamic future in ci? over 130 ci practitioners were surveyed about evolution (e.g., faster turnarounds, greater client expectations). while tech-savvy skills are disciplines that analyze data for business strategy. keywords: 1. introduction since the pandemic, the importance of intelligence in the corporate world has hit new heights. as misleading information proliferates, so does the need for ci departments to aid companies in effective decision-making (kolbe and morrow, 2022). calof et al.’s (2018) comparative study discovered a widespread growth of ci over the last two decades with “87% of all responding organizations had some form of formal competitive intelligence structure and many organizations had multiple intelligence or intelligence type functions in their organization” (p. 675). a sister discipline to offering ci because “most faculty members do not view the intelligence profession as a disuniversity resistance to ci appears to be breaking down with the recognition of such ci activities as monitoring competitors, benchmarking, and war-gaming (barrett, 2010). ci skills are evolving due to technological advances. one of the most impactful is 7 the next years, ai will change learning, teaching, and education” (p. 2). gunderson (2019) notes that “these rapid [technological] changes et al. (2019) asserts on the one hand “it is important to enable practitioners to “understand which skills and capabilities they should develop,” but then notes “there is currently no set framework of ci practitioners” (p. 720). this calls into question skills are necessary for ci pracing needs of the 21st century, this study will research the following questions: environment and subsequently, the educational needs for future practitioners? can educators best prepare future ci analysts? the paper will review ci’s evolution and the discipline. methodology will cover survey development and distribution followed by pedagogy. 2. literature review the origin of ci can be traced to (porter, 1980). porter advocated both “competitor monitoring” (p. 96) and “relating a company to its environment” (p. 3). until the mid-1990s, intelligence was portrayed as a cloak-and-dagger activity (miller, 2000). by the late 1990’s publications including street journal began to endorse intelligence drawing upon practices in the u.s. intelligence ducing the ci cycle. before the information age, “the scenery of science and technology was quite stable. large and even small companies knew exactly their marketplace” (dou et al., 1992, p. 35). technological developments eliminated stability, prompting the expansion of ci presence and scope. some changes included the digitization of corporate information (sadok et al., 2019), plummeting cost of data storage the start of the 21st century, 90% of the information needed by a company to monitor competitors and their industry was available 2002). a related development has been the proliferation of software designed to facilitate and expedite the work of ci practitioners (semerkova et al., 2017). ci’s evolution has seen the rise of competitive technical intelligence (cti), a branch of ci, used by companies to ensure they have “the best information possible on customer needs, technology options…and the competitive environment” (paap, 2020, p. 41). paap expanded ci’s traditional scope from porter’s (1980) competitor focus to include customer needs and . in recent years, cti has become more useful applying ai, coupled with big data, to reveal insights that were previously unattainable (porter, 2019). to gain ci knowledge and skills, professionals often draw from trade organizations (e.g., scip: strategic competitive intelligence professionals) and academies. while universities often incorporate business, library sciresources are necessary, but recent research managing the profession’s demands. applying the ci cycle as the framework (dishman and will be discussed as it relates to the needs of strategic thinking is necessary to do the backward planning to conceptualize, and achieve, a desired corporate end state (wang et al., kula and naktiyok (2021) stated, “strategic a ci perspective, this translates into imagining the future and having vision regarding such factors as the impact of emerging technology, the implications of competitor activities, or the effects of new regulations. task force approach collaboration is stage. paap (2020) described how ci practitioners “have expertise on data collection and analysis” and turn to the company’s technical staff for expertise on technical issues (p. 44). mabe et al. (2019) also stressed the importance of “relationship building (networking) skills in order to foster collaboration” (p. 724) calling them “the most required skills for ci practitioners” (p. 726). 8 finding information. online information that is publicly available and accessible on the web (data indexed by search engines) accounts for only four percent of what available in the so-called deep web (iftikhar, and how to seek information is an increasingly valuable skill. external sources. business intelligence practitioners access dedicated data warehouses of their company’s internal information to provide diagnostic, prescriptive, and predictive information. ci practitioners acquire external information requiring a different approach because “the range of topics are too broad, and the frequency of looking at any individual area so spread out, that it is not practical to keep the database up-to-date” (paap, 2020, p. 44). rather than rely on databases, practitioners have “more reliance on external sources that are kept up to date by the service providers” (paap, 2020, p. 44). analysis analytic skills. while big data may be to achieve maximum value. saddhon et al. (2019) asserted that, “the keys to the fortunate utilization of competitive intelligence are analysis of information and synthesis of knowledge” (p. 156). experienced analysts strive to professionalize analytic work to “get analysts to challenge their arguments and judgments, defend analytical positions and more effectively determine between what was fact and what was their opinion” (walsh, 2017, p. 550). technology forecasting encompasses futu re-oriented techniques developed by the u.s. department of defense and the rand corporation to assess and predict implications of future technologies (cho and daim, 2013). ci practitioners tasked to forecast technological developments must build expertise in these techniques (paap, 2020, p. 49). papp (2020) explained that a science & technology ci practitioner “uses tools to assess shows, and other sources of technical information to identify the who, where, why, and how fast new technologies are being developed or used” (p. 43). ci data may be structured, unstructured, or semi-structured, with user required to gather, store, and process that data (gunderson, 2019, p. 9). porter (2009) described the value of technically analyzing patent information. while, paap (2020) also advocated it as it “can help you identify who the players are, new developments in a particular technical area” and provide “insights on development trends” (p. 50). cl cucle of skills needed for future analysts. 9 dissemination communication is a critical skill throughout the entire ci process. practitioners must effectively communicate with clients to understand and accurately capture information needs successfully communicated in writing and/or poor communication skills as one of the major contributors to a ci project failure. due to the volume of data, communication through visualization has become an expectation by clients via dashboards and other graphical et al. (2019) used the example of overlaying visualization and network-based metrics for competitive intelligence analyses. adaptability. ci “is characterized by nu merous ‘one-off’ intelligence efforts” seeking information from external sources (paap, 2020, p. 44). a plethora of open-source information is now widely and equally available to all companies in any given industry. the companies that are able to rapidly identify, analyze, and turn information into actionable intelligence will likely gain competitive advantage (gilad its ability to quickly adapt to changing market practitioners rely on interpersonal skills to validate requirements, function as a team, obtain information from human sources, and deliver conclusions and insights to clients. at the same time, practitioners are expected to technology to perform their craft. these developments prompted researchers to ask ci practitioners what they believe are the educational needs of the crop of college students who will ultimately replace them. 3. methodology a survey was created based on the ci cycle and respective literature to address: 1) key evolutionary trends in ci, 2) needed skills for ci and 3) respective curriculum to prepare future analysts. several curriculum-based questions were derived from mercyhurst university’s business & competitive intelligence program (established 2009). according to kolbe and morrow (2022) “academic institutions, such as mercyhurst university, are producing a new generation of private-sector focused intelligence professionals” (para 5). expert discussions from a ci council webinar on the topic of preparing future analysts along with the researchers’ own expertise also ity, questions were reviewed by ci experts and educators to ensure questions were relevant and meaningful, unambiguous, and easy to answer from the perspective of the participant (connell, et al., 2018). the survey offered several openended questions for additional insights. valid inferences from survey data, responpopulation (malhotra, 2019). to achieve this, the study included members of the ci council, scip and special librarians association, ci division. a two percent were part of scip, 40% special librarians association and or on ci boards. using proquest©, 721 individuals viewed the survey, 219 responded (30.3% response rate) and 134 were fully completed (18.6%). a growing issue in organizational research and noted “if there are no systematic differences between respondents and non-respondents, then the sample remains representative of the population and can provide valid inferences” (p. 4). the researchers deemed the response rate acceptable. managerial and higher-level positions represented 49% of the respondent pool, while perspectives at a strategic, operational, and experience, the distribution was roughly 1/3 representing the categories: 3 years or less, 4-6 years and 7+ years. respondents were equally distributed in part-time and full time positions and as sole practitioner. in terms of education, 81% had a bachelor’s or higher degree. industries represented: • it (hardware, software, consulting) 22% • consulting 18% • construction or building trades 8% • manufacturing 7% • other categories < 5% 10 4. results both quantitative and qualitative feedback were assessed to address the research questions. the following section presents the current perspective of ci’s evolution, the ci cycle categories related to necessary skill sets and feedback regarding curriculum development and future skills needed. to fully assess the future of the discipline, how ci has changed over the past decade followed by an open-ended question to gather respondents rated four factors based on degree of change. based on the mean values of the likert scale, the impact of technology represented the most change with client/customer mean standard deviation 1. impact of technology (n = 130) 3.87 .80 2. doing more ci tasks in-house (n = 129) 3.52 .85 3. nature of client taskings (n = 128) 3.52 1.04 4. client or customer expectations (n = 129) 3.26 .79 open-ended responses to w provided more insight. common terms. key quotes are presented: 1) technology’s impact • . • • 2) customer expectations • • 3) nature of tasking • 4) change in perception of ci • ential and become a trusted business 5) in-house ci • • planning and the decision maker. (2017) noted that the planning step in the ci process is to ensure that not all possible information and data is collected, but instead idenplanning is reliant on two primary conditions: a) an understanding of what ci provides an organization and b) actual decision maker support whether executive, manager or client have argued the need for leadership support in order for the discipline to grow and evolve ning stage. common themes (in order of response rate) 1) building an understanding of what ci is and its value. • 11 • • 2) time and technology limitations offer challenges. • • • 3) executive reliance on own internal resources as a trade-off to ci. • • collecting. a question regarding the colmost commonly used by practitioners. company website information and third-party sources were most common followed by news was used by only 10% of respondents identianalysis commonly includes using methodologies to evaluate collected data and information. age of structured analytic techniques (sat) they used that were taught in college. there was an even distribution of responses with approximately 1/3 representing the categories of <40%, 41-60%, and >60%. only 8% noted that they learned more than 80% of sat in college indicating opportunities to build curriculum. respondents also were to identify what ket research were most common, while future oriented technology forecasting ranked much lower. ironically, the top methodologies have been part of the ci discipline for decades. this may indicate an opportunity to build ci curriculum incorporating new techniques that address the complexity of evolving technologies. common sources for research (n = 131). 12 current ci techniques used n = 130. structured analytic techniques total % 1. swot analysis 54.6% 2. 46.9% 3. market research & analysis 45.4% 4. scenario planning / simulation & modeling 38.5% 5. 36.2% 6. benchmarking 34.6% 7. 33.8% 8. r&d / technology forecasting 33.1% 9. 31.5% 10. trade show collection & analysis 29.2% 11. win / loss 28.5% 12 counterintelligence 23.8% 13. steep/pest 23.1% 14. other 9.2% ci dissemination methods. mean sd frequency* (n=130) 1. ci research reports (ad hoc tasking) 3.75 .97 2. in-depth analysis reports 3.68 .93 3. ci reports to other co. departments 3.53 .97 4. ci newsletter 3.49 1.09 5. (n=129) 3.43 .89 6. periodic ci reports (monthly, quarterly) 3.42 .90 7. other 3.26 1.12 8. online forum (n=129) 3.02 1.06 9 electronic ci alerts 2.85 1.05 effectiveness** 1. (n=132) 3.61 1.02 2. 3.60 1.05 3. (130) 3.53 .97 4. phone (132) 3.52 1.12 5. company intranet (129) 3.18 1.01 6. email newslettermass (130) 3.18 .90 7. online forum (129) 3.06 1.12 8. printed newsletter (130) 2.97 1.03 dissemination. two questions addressed the dissemination of ci: 1) most common methods used and 2) effectiveness of methods. based on frequency of use, project reports scored highest, while more technology based online forums and electronic alerts rated neutral or nities to build curriculum expanding communication methods to incorporate more technology-based dissemination. written reports and personal dissemination were rated as the most effective methods pointing to the importance of interpersonal skills. mass communication tools like newsletters and forums rated neutral indicating direct dissemination as being more effective. practitioners were provided skill sets based on the literature and asked to rate how critical these skills were for ci (1 = not critical at strong at 0.826 et al. 2010). one-sample greater than neutral (4.5) identifying them the top three variables as analytical, research and communication representing the key stages of the ci cycle. curriculum development questions were asked regarding courses and degrees. courses were rated in terms of professional utility for ranked based on means with top courses being bi/ci, market research, and data analytics being top rated over more traditional subjects. respondents rated desirability of degrees ogy (i.e., it) were rated as more desirable over more traditional degrees. recommendations and suggestions for future see appendix for themes and key quotes. 13 5. discussion the intent of this research was to address questions pertaining to ci’s evolution with technology in the hopes of guiding educators to better prepare students. one common theme related to curriculum supported the incorporation of more specialized courses relevant to the discipline (i.e., bi/ci, analytics) and gaining experiences prior to graduation. beyond traditional business curriculum, open-ended feedback stressed liberal arts-based skills as being essential. ironically, more collection-based courses lower with several comments regarding critical skill sets for ci (n = 130) and ( = 129). skills mean sd t sig 1. analytical (n = 129) 8.02 2.01 16.79 2. communication skills 7.80 1.67 15.72 3. research 7.66 1.66 14.85 4. 7.57 1.76 13.36 5. adaptability 7.55 1.62 14.32 6. it/computer 7.36 1.57 13.56 7. 7.28 1.93 10.54 8. presentation 7.12 1.64 11.26 9. strategic 7.08 2.01 8.93 (n = 131). course mean sd 1. intelligence studies (n = 129) 7.61 2.02 2. business & competitive intelligence (130) 7.49 1.82 3. information technology 6.74 2.33 4. management 6.60 1.98 5. library science (130) 6.36 2.37 6. math (130) 6.07 2.35 7. accounting 4.99 2.16 * (n = 130) and ( = 129). course mean sd 1. bi/ci course 3.95 1.1 2. market research 3.76 .79 3. data analytics 3.74 .78 4. business 3.72 .57 5. economics 3.64 .82 6. statistics 3.61 .82 7. collection (n = 129) 3.60 1.0 8. computer programming 3.30 .95 9. library science (n = 129) 3.20 .99 10. accounting 2.95 .79 * 14 as ai had led to unrealistic expectations of data having all the answers and situations of “a world where human analysts have been as a top competency, instructors may want to ensure that research is presented holistically stressing the synergistic value of data thinking and analytical skills. respondents stressed the need for students to be versed in sats recommending more analytics focused courses. as noted in the literature, analysts are impacted by ai and navigating evolving technologies may require more 2019). based on the lower ranking of futuristic sats like technology forecasting, instructors may want to continue to build the curriculum with a focus on more technology-based techniques. denoted as essential for a ci analyst’s success. popular methods of dissemination were methods may need to incorporate more electronically based dissemination especially for executives (nohria, 2021). themes, beyond curriculum, parallel the ci cycle (dishman and calof, 2008). many comments reinforced the need of planning and having the research capabilities to know where and how in addressing the evolution of ci, technolfrom emerging platforms and big data to some interpersonal skills. with technology, ci professionals reinforced the idea that expectations are growing for more concrete and faster analysis of what it all means (especially ai) is still in pioneering stages. this may be the skills new analysts can to bring to the table. most in general as more organizations recognize its value (kolbe and morrow, 2022). 6. conclusion this study gained valuable insight into the current ci environment, its challenges and its evolution with technological advances. survey feedback supported the ci cycle regarding necessary skills from strategic thinking to research capabilities and analytical competencies. communication skills were ranked as most valuable in the discipline, while courses future curriculum. results indicate a shift to more focused degrees in intelligence studies over traditional business degrees. technologies is evolving the discipline, softer skills like communication and analytical skills will never waiver in importance. these should remain a focus in curriculum development, as synergies will ensure not only a tech savvy analyst, but a successful one too. this study serves as a starting point in building curriculum to prepare future ci analysts. expanded research could build the framecipline with the goal to evolve curriculum for the ai-enabled world. with the growing speed of technology along with rising expectations, this topic will only continue to increase in relevancy. that the submission has not been previously published and has not been submitted to or is not under review by another journal or under consideration for publication elsewhere, and, if accepted, it will not be published elsewhere in the same form, in english or in any other language, including electronically without the written consent of the copyrightholder. the anonymized research data will be made available if required and if the university ethics board permits. to the best of our knowledge there is no copyright material in this paper. no funding was received for this study. 15 reference list barrett, s. e. 2010. competitive intellicalof, j., arcos, r., and sewdass, n. 2018. competitive intelligence practices of european , springer, london. pp. 67–112. connell, j., carlton, j., grundy, a., buck, e., keetharuth, a., rickets, t., burkham, m., robotham, d., rose, d., and brazier, j. 2018. the importance of content and face validity in instrument development: lessons learnt from service users when developing the recovering quality of life measure (reqol). pp. 1893–1902. https://doi.org/10.1007/s11136018-1847-y dishman, p. and calof, j. 2008. competitive intelligence: a multiphasic precedent to marketing strategy. la tela, 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intelligence. in nd system sciences, pp. 127–136. nologies in competitive intelligence. in (pp. 804– 807). ieee. telligence on learning, teaching, and education. . luxembourg: pp. 1–47. telligence analytical practice through qualitative social research. security to achieve organizational excellence. business intelligence. in routledge, pp. 67–81. 17 appendix practitioners’ recommendations topic themes key comments strategic thinking planning • • • • research skills collecting • • • analytic techniques analysis • • • • • ci courses & experience curriculum • • • • ditter jisib 1 2011 19_28 6 final kopie using xbrl technology to extract competitive information from financial statements dominik ditter *, klaus henselmann * and elisabeth scherr * * department of accounting and auditing, friedrich-alexander university erlangen-nuremberg, lange gasse 20, d-90403 nuremberg, germany dominik.ditter@wiso.uni-erlangen.de, pruefungswesen@wiso.uni-erlangen.de, elisabeth.scherr@wiso.uni-erlangen.de received 1 june 2011; received in revised form 22 november 2011; accepted 26 december 2011 abstract: the extensible business reporting language, or xbrl, is a reporting format for the automatic and electronic exchange of business and financial data. in xbrl every single reported fact is marked with a unique tag, enabling a full computerbased readout of financial data. it has the potential to improve the collection and analysis of financial data for competitive intelligence (e.g., the profiling of publicly available financial statements). the article describes how easily information from xbrl reports can be extracted. keywords: financial intelligence, xbrl, competitive intelligence, real-time business intelligence 1. introduction competitive intelligence (ci) can be defined as the process of “gathering and analyzing information about your competitors’ activities and general business trends to further your own company’s goals” (kahaner 1998, 16). important sources of competitive information are publicly available financial statements. they provide a lot of valuable information about competitors as their financial performance (e.g., for the calculation of financial key metrics to measure the profitability of competitors) and financial position (e.g., for the evaluation of the capability to survive price wars). however, this information usually cannot be used to the full extent. the established format types of published financial statements, for example ms excel, ms word and adobe pdf, are unstructured and therefore not computer readable. software programs simply do not know how to use this information. with no information for further working, data processing systems interpret the information as on-going text. every item (in approximately 100 to 500 pages) must be manually fed into an analysis software tool or database system. the effort it takes to manually extract the required information from financial statements is time-consuming and error-prone. for this reason, ci managers are forced to acquire adjusted or structured financial data from intermediaries or business data providers. the disadvantages of this approach are the high costs available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 19-28 20 that are incurred and the fact that the data is not obtained directly from the source (i.e., the target company). the extensible business reporting language, or xbrl, has the potential to solve these problems. information within documents that are provided in the xbrl format enable automatic data processing of almost all reported items without timeconsuming manual feed of data. the idea behind is that companies have to publish their business reports in a standardized electronic structure, increasing the transparency of the reports for investors. with a little programming effort, everyone (including small investors) can access financial data directly from the source, at low cost and almost in real-time. as a side effect, xbrl also offers opportunities for ci. today only a small amount of specific literature for accessing xbrl data is available (except hoffman 2006). this article is based on hoffman 2006 and describes how information from xbrl data can be extracted and used for ci. the article shall serve as a technical guide and outlines how to get started and what instruments are required. this article proceeds as follows. first, we give a short explanation of the xbrl concept, before explaining an approach to xbrl data extraction in section 3. in this example, specific financial line items of an actual xbrl document will be extracted. because the implementation status of xbrl is very sophisticated in the u.s., all explanations for extracting and using xbrl are based on sec filings. the article closes with a discussion of the effects of xbrl on the development of ci and a short summary. 2. the xbrl concept because xbrl is a derivate of xml technologies, the fundamentals of xml will be illustrated first, followed by an introduction to the fundamentals of the xbrl concept. 2.1 fundamentals of xml the extensible markup language, or xml, is a meta-language for the creation of a self-defined document markup language (watt 2002, 10). a popular markup language is the hypertext markup language, or html. with html, it is possible to assign a specific look or layout to document content. therefore, the text or numbers of an html-formatted financial statement (file extension *.html) are tagged (marked) by specific expressions. for example, html tags can indicate that the number “14013000000” is to be displayed in bold letters or in the color green. this enables computer programs like mozilla firefox or microsoft internet explorer to interpret and present the document content in the deposited layout. the world wide web consortium (w3c) lists the applicable markups (vocabulary) and logical structure (grammar) for the creation of an html document in the html specification (w3c recommendation, 1999). xml is similar to html in the way it uses tags. however, xml markups define the meaning of document content. for example, in figure 1 the number “14013000000” is encircled by two tags indicating the start and the end of the markup. these tags tell us that the number reported is the net income of a company (and not its turnover, assets, etc). further, we can see that it is the net income for the year 2010 and that it is measured in us dollars (not euros or pounds). using this information, a suitable computer program could open the file, read the number and do any computations with it. no human beings are needed to retype the numbers on a keyboard. access to the data is much faster and less error-prone. in contrast to html, xml is a meta-language. therefore, the w3c does not regulate the vocabulary, but a set of grammatical rules for creating self-defined computer readable markups (watt 2002, 10). the name and order of elements and attributes used for the creation of markups can be arbitrarily extended. the xml specification ensures that xml markups, which consist of a logical structure of elements, attributes and values, are well-formed (w3c recommendation, 2008). figure 2 illustrates two simplified examples of well-formed xml documents with the description of identical data content. the examples a and b (see figure 2) show that there are different possibilities to describe the same issue according to <netincomeloss year="2010" unit="usd">14013000000</netincomeloss> element name attributes start-tag end-tag figure 1: logical structure of markups 21 xml rules. for xml documents to be automatically exchangeable between different senders and receivers, all participants of the communication chain have to use the same xml markup language. in other words, a uniform and consistent markup of document content must be ensured. therefore, the usable element names and attributes have to be predefined and deposited in a schema file. today it is common to do this with the xml schema language (van der vlist 2002, 2). an xml document is “valid” if the markups conform to the rules of the corresponding schema file. therefore, this xml document is an instantiation of the schema or a so-called instance document (binstock 2003, 12). xml instance documents (a technical term for a valid document with data content; file extension *.xml) and schema documents (documents in which the declared elements and attributes like netincomeloss and year are deposited; file extension *.xsd) are connected by the bold expressions in figure 2. a so-called validating xml parser (module of a software program; responsible for the reading in of an xml document) can search for the attribute schemalocation (harold 2004, 453). if this reference to the schema document is available, the parser can check the xml document for conformity against the predefined schema. in other words, by rejecting xml documents in the event of inconsistencies or markup errors, the schema can control consistency. because it is possible to select a free number of self-defined elements and attributes, two different xml markup languages may use the same name for an element. for example, in figure 2 “apple” addresses the company apple incorporated. however, in another context “apple” may mean a kind of fruit. to ensure a clear unique classification, this name conflict can be solved with xml namespace (w3 schools, 2011). a namespace is an inventory of affiliated elements and attributes that can be identified with a unique name. the namespace name must be an uri (uniform resource identifier) (w3c recommendation, 2009). because uris are absolutely unique, it is not possible for the same uri to exist again. a default namespace is defined in the start tag of the root element by the attribute xmlns = ”uri” (evjen 2007, 29). it thereby applies to all other elements that are reported within the document. in the upper example of figure 2 the elements apple and netincomeloss are associated with the namespace ”http://www.apple.com /instance/examplea”. <?xml version="1.0" encoding="us-ascii" ?> <company xmlns="http://www.apple.com/instance/examplea" schemalocation="examplea.xsd"> <apple> <netincomeloss year="2010" unit="usd">14013000000</netincomeloss> <netincomeloss year="2009" unit="usd">8235000000</netincomeloss> </apple> </company> <?xml version="1.0" encoding="us-ascii" ?> <company xmlns="http://www.apple.com/instance/exampleb" schemalocation="exampleb.xsd"> <apple year="2010"> <netincomeloss unit="usd">14013000000</netincomeloss> </apple> <apple year="2009"> <netincomeloss unit="usd">8235000000</netincomeloss> </apple> </company> figure 2: two well-formed xml documents 22 via the creation of individual, customized tags, xml is a very flexible standard for electronic data exchange. almost all transmission requirements and communication constellations can be covered with xml. however, for the structured exchange of business information a certain recognized framework has been established: xbrl. 2.2 fundamentals of xbrl xbrl was created for the automatic and electronic exchange of business data. the non-profit organisation xbrl international incorporated (xii) maintains the standard in an own specification. xbrl is a meta-language for creating markup languages for business reporting issues. but in contrast to xml, the xbrl specification provides both the grammar and core vocabulary (xbrl international incorporated 2008, 2). the xbrl syntax is based on several open, globally accepted standard specifications, including xml, xml schema, xml namespace, xlink and xpointer. the repertoire of xml technologies selected for xbrl is compiled in the xbrl specification (sec release 33-9002 2009, 11). furthermore, the xbrl specification outlines elements and attributes used to define reporting elements and to express relationships among them. therefore, the unity open-standard xbrl can be understood more precisely as the “core language” for the creation of markup languages for business reporting issues. however, with xbrl it is possible to create not only a markup language, rather more a classification system (taxonomy) (hoffman 2010, 301). there are many different types of accounting standards around the world, for example, ifrs (international financial reporting standards), us gaap, german gaap, swiss gaap, etc. each accounting system demands the reporting of different numbers and data. sometimes the differences are smaller, sometimes bigger. to make things more complicated, there are different reporting requirements in every country for banks and insurance companies than there are for industrial companies. for automatic electronic reporting purposes, each reporting standard has to be converted into a standardized structure. in xbrl, this is done with a hierarchical structure (taxonomy) to cope with the complex and extensive accounting rules. hence, taxonomies consist of xml schema documents and so-called linkbases (see figure 3). schema documents and linkbases are separate files, but they are an entity and together constitute a taxonomy (edgar online, 2011). the schema documents represent an unsorted list of declared element names and their corresponding attributes (hoffman 2010, 82). as schema documents contain a predefined list of a business report’s possible contents, taxonomies are often interpreted as “digital dictionaries” for the transmission of financial statements, for instance (hoffman 2010, 301). it would be theoretically possible to store all declared elements in one single document, but this would be difficult, due to thousands of elements that are needed for the markup of a financial statement (e.g., the usgaap taxonomy contains approximately 19,000 monetary and non-monetary element names). for this reason, the elements and their associated attributes are usually stored according to their purpose in different schema documents. elements that have been defined in an xbrl taxonomy are so-called concepts (hoffman 2006, 67). figure 4 illustrates an excerpt of an element declaration from the us-gaap taxonomy. in this figure an element with the name netincomeloss is declared. companies can use the element name for transmitting a financial line item: in this context, net income in accordance with us gaap standards. the xbrl specification provides several elements and attributes (vocabulary) that can be used to describe the declared elements in more detail. the attribute nillable (possible value: true/false) determines if there is an obligation to report this item in the instance document (sec, 2010). this concept does not need to be included in the report if the value is true. the attribute type xlink / xpointer xbrl taxonomy schemadocumenta.xsd calculationlinkbase.xml schema documents linkbases schemadocumentb.xsd schemadocumentc.xsd schemadocumentd.xsd definitionlinkbase.xml presentationlinkbase.xml labellinkbase.xml referencelinkbase.xml figure 3: basic structure of an xbrl taxonomy <element name="netincomeloss" id="us-gaap_netincomeloss" nillable="true" type="monetaryitemtype" balance="credit" periodtype="duration" /> figure 4: concept declaration 23 expresses if the concept is a monetary item, a string item, a date item and so on. the taxonomy developer may add an optional balance attribute (possible value: debit/credit) to the concept definition if it is a monetary item type (xbrl international incorporated 2008, 80). for example, it will indicate if the reported fact is an asset or a liability in the statement of financial position. the attribute periodtype indicates if the concept is an instant or duration type. the net income is a duration type because it is part of the statement of income (hoffman 2010, 89). a special feature of xbrl is to describe complex relationships (links) between different concepts (concept-to-concept link) or to add auxiliary information to concepts (one-way link). the different links are stored in separate files according to their purpose, the so-called linkbases (e.g., label links are generally stored in a separate document, the so-called labellinkbase). the supported linkbases according to the xbrl specification are shown in figure 3. the calculation-, definitionand presentationlinkbase contain concept-to-concept links, whereas the labeland referencelinkbase contain one-way links. the links are built with the help of the w3c specifications xml linking language (xlink) and xml pointer language (xpointer). every concept has the attribute id that serves as unique identifier (hoffman 2010, 88). in figure 4, the identifier of the declared concept is “us-gaap_netincomeloss”. with the help of the identifier, xpointer can locate (point to) concepts in the schema document. xlink is used to describe the relationships (links) between two located concepts or from one located concept to auxiliary information. the concrete xlink and xpointer rules can be looked up in the xbrl specification (http://www.xbrl.org/specrecommen dations). a calculation link between two monetary item type concepts enables them to be linked mathematically, but with the limitation it only allows the description of the summation or subtraction between them (edgar online, 2011). for example, the use of calculation links enables the description of net income as total earnings minus expenses. all specified calculation links between concepts are aggregated to a linkbase, in this case the calculationlinkbase. the function of the calculation links is important because it makes it possible to control if the reported monetary statements are mathematically complete and correct (xbrl spain 2005, 21). the definitionlinkbase serves to express different kinds of (inter)relationships between concepts (hoffman 2006, 67). for example, it can be deposited that an explanation to the impairment must be disclosed in the notes in the case of asset impairment. the main function of the presentationlinkbase is to display the list of unsorted concepts in a hierarchical structure according to the presentation rules of the accounting standards. additionally, for each hierarchical level the order of the concepts can be deposited according to the particular formal requirements (iascf 2010, 23). for example, within the statement of financial position the assets are comprised of current assets and noncurrent assets. furthermore, us gaap requires current assets to be displayed before non-current assets. this can be implemented with the use of presentation links. all in all, the presentation links offer the possibility to group and sort the unsorted list of declared schema elements for the human eye. the labellinkbase offers the possibility to add a human-readable name (e.g., net income) for a concept (e.g., <netincomeloss/>). if several links with human-readable names in different languages have been defined, xbrl reports can be prepared and read in different languages (van der heiden 2006, 15). for example, the company apple could provide the numbers of its balance sheet. analysts from germany could choose the german language and they would receive a report with lines like “sachanlagen”, “vorräte” and so on. an englishspeaking analyst would see “property, plant & equipment” and “inventories” on his report. by overcoming the language barrier in this way, information about foreign competitors is easier to understand. the aim of the referencelinkbase is to reference the underlying legal background of the concept and descriptive literature in commentaries. reference links may also provide documentations about the correct usage of the special concept. in summary, taxonomies consist of schema documents and linkbases. schema documents only represent a container of unsorted concepts. they will be structured with the individual linkbases. in the area of accounting, taxonomies are primarily developed and published by such standard-setters as the ifrs foundation or the financial accounting standards board (fasb). depending on the particular legal situation or xbrl adoption degree in the respective countries, the reporting companies may or are required to use the taxonomies to create and file reports in xbrl format (instance documents). due to the standardized markup structure, xbrl reports can be automatically readout and processed by computer programs. to fulfill this aim, it is important that all participants of the reporting chain use the same standardized taxonomy. how easily information from xbrl reports can be extracted shall be illustrated with the help of sec filings according to the us-gaap taxonomy in the following. 24 3. extracting competitive information from xbrl financial statements this section describes how competitive information can be extracted from us gaap xbrl reports. an actual annual report from the company apple incorporated serves as basis for the illustration. 3.1 financial data provided by the sec xbrl can be implemented for different business reporting issues (e.g., banking supervision, tax and other regulatory reporting as well as internal management reporting). however, xbrl originally has been created to improve the data exchange of financial statements. with different taxonomies, it is possible to represent the specific national accounting standards like us gaap, ifrs or german gaap. in the u.s., companies have to use the usgaap taxonomy when they are obligated to prepare their financial statements according to us gaap and sec regulations (xbrl us, 2008). in 2006, the non-profit jurisdiction xbrl us was commissioned by the u.s. securities and exchange commission (sec) to develop a taxonomy that is consistent with us gaap requirements and the commission’s regulations (sec release 33-9002 2009, 12). in 2010, the on-going development and maintenance responsibilities for the us-gaap taxonomy devolved to the fasb (fasb, 2011). the taxonomies supported by the sec xbrl mandate are listed on the web site http://www.sec.gov/info/edgar/edgartaxonomies.sht ml. because of the sec xbrl mandate (or interactive data program), many xbrl filings of listed companies are available for analysis online. beginning with fiscal periods ending on or after june 15, 2009, domestic and foreign large accelerated filers that prepare their financial statements in accordance to us gaap and have a public equity float above $5 billion were required to provide their financial statements to the sec and on their web sites in xbrl format (sec release 33-9002 2009, 42). all other public companies that fell under the definition of large accelerated filers using us gaap were required to submit their financial statements in xbrl format for fiscal periods ending on or after june 15, 2010. finally, all remaining us gaap filers and all foreign private issuers using ifrs had to comply with the xbrl requirements in year three of the phase-in (sec release 33-9002 2009, 43). for foreign private issuers using ifrs, the requirement to file xbrl reports was postponed until sec approval of the ifrs-taxonomy (sec, 2011). it was estimated that about 500 companies in year one, 1,800 companies in year two and about 12,000 companies in year three of the phase-in were required to submit their filings in xbrl (hoffman 2010, 219) to the sec electronic data-gathering, analysis, and retrieval system (edgar). anyone can access this data pool and download the xbrl filings (forms 10-k, 10-q, etc) free of charge. by providing several types of rss feeds, all xbrl filings can be downloaded to and integrated into a database or an analysis tool. in combination with the edgar system, xbrl enables competitive information from thousands of companies to be downloaded and analysed almost in real-time. 3.2 extracting apple’s xbrl data for extracting all information that an xbrl report provides, a special xbrl processor is needed. the reason is that an xml processor has no knowledge of xbrl and thus is not able to understand and handle the structure and relationships among the different xbrl documents (hoffman 2006, 494). an xbrl processor can follow the xlink and xpointer expressions and is able to put the different information together. it can read, write, control, handle or otherwise process xbrl data (hoffman 2010, 232). an xml processor can also be used to extract information; however, it is not possible to use all information (e.g., to mathematically check for correctness and completeness) xbrl documents provide (hoffman 2010, 24). an xml processor is a software program that can read, change, delete or transform xml documents. the module of the xml processor responsible for the reading-in of an xml document is called xml parser. an xml parser facilitates access to the content of an xml document by converting it into an application programming interface (api). afterward, this api can be accessed with programming languages for further processes (maruyama 2002, 21). one possible programming language is visual basic for applications (vba), which can be directly embedded in ms excel (hoffman 2006, 495). ms excel is a well-known and widely used analysis tool. furthermore, one important component is already integrated into it: an xml parser. as a result, ms excel can be a useful tool for extracting competitive information from xbrl financial statements. with only a little technical expertise, xbrl data can be extracted without the help of special software. because the built-in xml parser is used, only a stand-alone instance document and not the (extension) schema and the different (extension) linkbases can be used (note: xbrl supports creating own individual conceptextensions if the taxonomy structure does not provide the adequate concept for transmission. however, when the taxonomy structure is extended or adjusted, it is necessary to publish the corresponding extension schema and extension 25 linkbases.). nevertheless, this simple approach can generate huge benefits for ci. apple’s annual report for the fiscal year 2010 can be downloaded from the sec edgar database in the data formats html/ascii and xbrl. figure 5 shows a simplified excerpt of the xbrl report (instance document). among other data, it contains all information needed for the automatic extraction and calculation of the key metric return on sales (after interests and taxes) that is defined as the ratio between net income and sales (tracy 2009, 132). it is one way of measuring a company’s profitability (here the return on sales after interests and taxes). therefore, it is a useful key performance indicator for many competitive intelligence purposes. however, there are an infinite number of other calculations that could be automated as well. in accordance to us gaap, companies have to report their sales revenues as net value, that is as revenues earned from selling products minus sales returns, sales allowances and sales discounts. therefore, for the calculation of this key metric, apple’s net sales is inserted into the formula for the term sales. the net income is calculated after subtracting the expenses from earnings and represents the profit for the year attributable to shareholders. in apple’s instance document, the values for the numerator and denominator of the ratio return on sales are transmitted by the predefined element names salesrevenuenet and netincomeloss of the us-gaap taxonomy 2009. in order to distinguish between gaap (prefix: usgaap) and non-gaap element names (prefix: dei), a so-called prefix is used. a prefix in the start-tag of an element associates a specific namespace to single element names instead of assigning a default namespace for all element names within an instance document (see section 2, figure 2). each element name prefix is associated with an own uri (harold 2004, 65). for human beings the instance document in figure 5 might look a bit confusing. but computer programs can find a path through this “data jungle”, finding and extracting the information needed. the standardized structure enables the selective and automatic analysis of financial statements. in our approach, a few lines of vba code will need to be written (see figure 6) and the code will have to be inputted into the visual basic editor in ms excel. first, it is necessary to convert the instance document to an api so that the document content can be accessed. afterward we can search for the element names salesrevenuenet and netincomeloss and import the contained values into an ms excel spreadsheet. in figure 6 the vba code for the extraction of the net sales (see the bold expression) is illustrated. if we feed the storage location of the instance document into column a in the ms excel spreadsheet (see figure 7) and execute the vba program (or vba macro), this specific fact value will automatically be imported into the denoted column e. <?xml version="1.0" encoding="us-ascii" standalone="yes" ?> <xbrl xmlns="http://www.xbrl.org/2003/instance" xmlns:us-gaap="http://xbrl.us/us-gaap/2009-01-31" xmlns:dei="http://xbrl.us/dei/2009-01-31"> <schemaref href="aapl-20100925.xsd"/> <dei:entityregistrantname contextref="2010">apple inc</dei:entityregistrantname> <dei:documentfiscalyearfocus contextref="2010">2010</dei:documentfiscalyearfocus> <dei:documentfiscalperiodfocus contextref="2010">fy</dei:documentfiscalperiodfocus> <us-gaap:salesrevenuenet contextref="2010" decimals="-6" unitref="iso4217_usd">65225000000 </us-gaap:salesrevenuenet> <us-gaap:netincomeloss contextref="2010" decimals="-6" unitref="iso4217_usd">14013000000 </us-gaap:netincomeloss> <context id="2010"> <period><startdate>2009-09-27</startdate><enddate>2010-09-25</enddate></period> </context> <unit id="iso4217_usd"> <measure>iso4217:usd</measure> </unit> </xbrl> figure 5: simplified excerpt of apple's instance document 26 3.3 results by extending the vba code (or replacing the bold expression), the remaining columns in the ms excel spreadsheet (columns b, c, d and f; see figure 7) can be filled. after the import of the needed information into the spreadsheet, normal ms excel formulas can be applied to the values (column e and f) in order to calculate the requested key metric. for the company apple we calculate a return on sales of 21.48 % for the fiscal year 2010 with the aid of apple’s xbrl data. the result is displayed in column g. therefore, with xbrl no manual work for the calculation of the return on sales is needed anymore. if we do this calculation only once and for one company, the benefits of this approach seem to be limited. the true potential appears if we imagine that the procedure will be applied to many companies. by extending the vba macro with a few more lines of code, it would be possible to calculate a ratio (or dozens of them) for thousands of competitors in a fully automated process. it would be possible to compare apple’s performance measure with all other examined companies (or the industry average) by a pivot table (benchmarking) or further graphical analysis, for example. often used analytical ci techniques like benchmarking and competitor profiling (e.g., the profiling of financial statements) (bouthillier 2003, 54) therewith can be supported. 4. effects of xbrl on the development of competitive intelligence the ultimate goal of ci is to gather and analyse as much (external) information as possible in order to guide strategy by understanding a company’s marketplace competitiveness and its adaptability to future changes in the competitive environment. in the literature the ci process is often divided into the following four steps: (1) direction, (2) collection, (3) analysis and (4) dissemination (vrien 2004, 3). for the collection of competitive information (step (2)) there are several different sources possible. studies found that the systematic screening of the internet is among the most important and widely-used instruments of ci (vrien 2004, 11 and 17). the “internet" technology xbrl provides a lot of opportunities for ci. when all participants in the reporting chain (sender and receiver) use the same xbrl taxonomy, an figure 6: sample vba code to extract an xbrl fact value figure 7: extraction results sub extractxbrlforci() dim row as range set row = sheet1.range("a2") 'xml parser -------------------------------------------------------------------------------------dim instancedocument as msxml2.domdocument set instancedocument = new msxml2.domdocument instancedocument.async = false instancedocument.validateonparse = false instancedocument.load (row) 'xbrl extraction -------------------------------------------------------------------------------dim nodelist as msxml2.ixmldomnodelist set nodelist = instancedocument.getelementsbytagname("us-gaap:salesrevenuenet") dim node as object for each node in nodelist cells(cells(rows.count, "e").end(xlup).row + 1, "e").value = node.text next node end sub 27 automatic selection of individual desired data is possible. a time-consuming manual search through online available financial statements will not be needed anymore. in combination with other internet technologies like rss, the financial data can be extracted almost in real-time directly from the source and it doesn’t have to be acquired at high cost. besides the analysis getting faster and cheaper, a broader data basis can be examined. mass data can easily be analysed as well as textual or qualitative data (e.g., information about the company’s strategy and the managers’ forecast to the future performance) with the use of xbrl. with taxonomies (esp. labellinkbases) available in different languages, the collection of data can be driven independent from language hurdles. this will become more and more important for ci due to globalized markets. all in all, xbrl contributes to a quantitative better collection of data without reducing the data quality. the data quality rather increases. the fact that step (2) in the ci process improves, has also positive consequences for the steps (3) and (4). on the basis of better data, qualitatively and quantitatively, more reliable decisions are possible. 5. summary the article illustrates a simple approach to automate the extraction and further processing of financial statement information (e.g., for profiling of financial statements) using publicly available xbrl reports and ms excel. with the creation of a simple vba macro, xbrl data enables calculating not only one stand-alone key metric, but whole ms excel templates (e.g., scoring systems or benchmarking models) can be fed with financial data. the xbrl technology provides a lot of opportunities for ci. competitive information from financial statements can be collected and analysed independent of former limitations (e.g., data volume, language or qualitative data). designed as an open-standard, it is possible to customize the use of xbrl to own individual needs so that it can greatly simplify and speed up the analysing of financial data. references binstock c et al. 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(2007) professional xml, wiley publishing, indianapolis, indiana fasb (2011) faf/fasb xbrl taxonomy role, available online on url: http://www.fasb.org/jsp/fasb/page/ harold e and means s (2004) xml in a nutshell, third edition, o’reilly media inc., sebastopol, california hoffman c (2006) financial reporting using xbrl, available online on url: http://frux.wikispaces.com/ hoffman c (2010) xbrl for dummies, wiley publishing, indianapolis, indiana iascf (2010) the ifrs taxonomy guide 2010, available online on url: http://www.ifrs.org/nr/rdonlyres/38eab57a7 264a7491eceeef29bbe8a6/0/itg20102010 0702.pdf kahaner l (1998) competitive intelligence: how to gather, analyse and use information to move your business to the top, touchstone, new york maruyama h (2002) xml and java, second edition, pearson education inc., boston, massachusetts sec release 33-9002 (2009) interactive data to improve financial reporting, available online on url: http://www.sec.gov/rules/final/2009/339002.pdf sec (2010) xbrl glossary, available online on url: http://www.sec.gov/spotlight/xbrl/glossary.shtm l sec (2011) no-action letter, available online on url: http://www.sec.gov/divisions/corpfin/cfnoactio n/2011/caq040811.htm tracy j (2009) how to read a financial report, seventh edition, john wiley & sons, hoboken, new jersey van der heiden j (2006) xbrl in plain english, available online on url: http://www.bataviaxbrl.com/downloads/xbrli nplainenglishv1.1.pdf van der vlist e (2002) xml schema, o’reilly media inc., sebastopol, california vrien d (2004) information and communication technology for competitive intelligence, idea group publishing, hershey, pennsylvania w3c recommendation (1999) html 4.01 specification, available online on url: http://www.w3.org/tr/html401/ w3c recommendation (2008) extensible markup language (xml) 1.0, available online on url: http://www.w3.org/tr/rec-xml/ w3c recommendation (2009) namespaces in xml 1.0, available online on url: http://www.w3.org/tr/rec-xml-names/ 28 w3 schools (2011), xml namespaces, available online on url: http://www.w3schools.com/xml/xml_namespac es.asp watt a (2002), xml in 10 minutes, sams publishing, indianapolis, indiana xbrl international incorporated (2008) xbrl 2.1 specification, available online on url: http://www.xbrl.org/specification/xbrlrecommendation-2003-1231+correctederrata-2008-07-02-redlined.doc xbrl spain (2005) white paper on xbrl technology, available online on url: http://www.xbrl.es/downloads/libros/white_pa per.pdf xbrl us (2008) us gaap taxonomy preparers guide, available online on url: http://xbrl.us/documents/preparersguide.pdf 91opinion section competitive intelligence in the defense industry: a perspective from israel – a case study analysis avner barnea 1 1 ono academic college, israel avner.bar@ono.ac received november 28, accepted december 26 2014 abstract: purpose the defense industry is one of the leading business sectors in israel and also worldwide. competitive intelligence (hereafter ci) is embedded into this sector and supports its decision making process. in recent years more information about this industry and about the ci activity is available while characterized by fierce competition and quick changes in the competitive environment. it is evident that ci is used widely by the leading firms in this sector while it has become an integral part of the business activity, and its added value seems to be significant. it is possible to define a framework of ci activity in this industry and to reflect on its advantages and limitations. it is my hope that this paper will encourage further research on this topic. methodology/approach – gathering information that has been published in israel and abroad that was analyzed and thus offers insight into this issue. findings – the defense industry in general and especially in israel is using ci intensively in the highly competitive environment of defense products to support the decision making process. research limitations – for many years, the information on this sector was not https://ojs.hh.se/available for free online at journal of intelligence studies in business vol 4, no 2 (2014) 91-111 https://ojs.hh.se/ 92opinion section available. it is in now in a process of change and this enables us to build up a comprehensive picture. practical implications – this study can make a contribution to global corporations competing in highly dynamic sectors, especially those that are operating in the governmental sectors. originality/ value – this is the first work in israel on the use of ci in the defense sector. paper type: a case study analysis. keywords: competitive intelligence, marketing intelligence, defense industry, israel introduction the defense industry was one of the fastest growing business fields in israel (2010). in recent years and especially since the mid 1990's, defense export became one of israel's leading export sectors, with high profitability and stable growth. israel was considered world wide as one of the leading countries in the field of defense exports. according to national data on arms exporters in 2007, israel was in fourth place, with sales of $4.4 billion after usa; russia and france (http://www.sipri.org/yearbook/2009/07/ 07b). according to recent estimations israel's global share on the arms exports in 2009 has reached to 14% (http://jdw.janes.com/public/jdw/index.s html). in 2010 the overall spending of worldwide governments on defense has reached to $1.7 trillion while the us is responsible to 45% of it. israel's defense exports in 2009 amounted was $ 6.75 billion, which is 16% of total israeli exports in 2009 (http://www.israelwtc.co.il). this is a slight increase compared to 2008, which amounted to defense exports at $ 6.3 billion, an increase of 7%. the israeli defense exports 2010 results are indicating that they have reached to $7.2 billion in 2010 (http://www.globes.co.il/news/article.aspx?di d=1000654713). it should be noted that defense exports is one of the few areas that have been hurt less during the global economic slowdown that began at 2008 (http://www.israelwtc.co.il, http://www.prinside.com/research-and-markets-israeldefence-and-r2131715.htm). the heart of the israeli defense companies was its advanced technology. its comparative advantage was technological excellence. israeli solutions were often considered to be highly innovative and better than other solutions by the competitors. investment of hundreds of millions of dollars a year in research and development intended to maintain this advantage. israeli defense products and technologies were considered to be most advanced, http://www.sipri.org/yearbook/2009/07/07b http://www.sipri.org/yearbook/2009/07/07b http://jdw.janes.com/public/jdw/index.shtml http://jdw.janes.com/public/jdw/index.shtml http://www.israelwtc.co.il/ http://www.globes.co.il/news/article.aspx?did=1000654713 http://www.globes.co.il/news/article.aspx?did=1000654713 http://www.israelwtc.co.il/ http://www.pr-inside.com/research-and-markets-israel-defence-and-r2131715.htm http://www.pr-inside.com/research-and-markets-israel-defence-and-r2131715.htm http://www.pr-inside.com/research-and-markets-israel-defence-and-r2131715.htm 93opinion section multi-disciplinary and often long ahead of the technology used in the civil market. the primary source of israel's relative advantage in this industry was the needs for the most advanced products set by the israeli military systems, especially by the idf (israel defense forces). on the other hand, one of the most important goals of israel's economy is to increase its exports as its economy relied heavily on export of most advanced technological products. a distinct advantage of israeli defense products is the fact that they usually have gained a variety of combat experiences by the idf, which increased their attractiveness in the eyes of its customers (http://www.businessmonitor.com/defence /israel.html). although there were security limitations on defense exports to avoid leakage of secrets that could damage the state security, israel authorized a wide range of defense products for be exported. (dvir & tishler, 1998). as competitive intelligence (hereafter, ci) became recognized, and its value was more acknowledged in recent years, its direction went towards gaining strategic intelligence (montgomery and weinberg, 1979). fulfilling ci became part of the many firms' capabilities (porter, 1980). qualified ci functions have been playing growing role by israeli firms in this sector to become more competitive. the purpose of this paper is to assess the value of ci to the defense industry, especially in israel and to see how beneficial it was for the process of decision-making in this field. referring to this issue was possible through studying the performance of israel's defense firms in foreign markets, mainly in recent years. characteristics of the sector of defense industries here are the characteristics of the defense industries' markets; 1. defense equipment purchasing is determinated by states based on their assessments of military threats and on the allocations to defense budgets, usually affected by economic parameters. 2. this market was characterized by intense competition, while the leading companies were based mainly in the us, uk, france and germany. although 2010 has seen changes in these markets while us shifted its priorities, china's global rise while threats in europe have been much reduced, the competition was still fierce. 3. the targets of the sales were usually government organizations, mainly the military and the defense establishments which have high quality demands and http://www.businessmonitor.com/defence/israel.html http://www.businessmonitor.com/defence/israel.html 94opinion section were anticipating for highly sophisticated solutions. 4. usually, the sales were resulted of winning tenders. these wins have far been reaching financial and strategic significance, as often it would be leading to extended business relations, including later upgrading of the systems and expanding sales of existing systems. 5. defense export process was characterized by high entry barriers to be able to develop advanced products that have undergone a long process of field experience in complex situations and have been proved their effectiveness. 6. defense export procedures were generally long-term processes, from raising the initial demand, responsiveness, getting security clearance, selecting the winner, the start of procurement, implementation and execution of systems and acquisition returns. 7. defense exports were characterized by the participation of huge corporations with high complexity of demands that often required ad hock cooperation with other companies to increase the chances of winning tenders. that implied that these companies also required a double vision both for customers and potential customers, usually state military and security organizations and also for competitors, which often were the ones you have shared with them in the past and possible candidates for cooperation again in the future. hence, defense industries are also characterized by intense competition and also by cooperation between the rival companies (known as coopetition). the turning point in the israeli defense exports' industry was in 1993 after major political developments in the middle east: the agreement between israel and the palestinian authority and the peace agreement signed with jordan that changed the strategic position of israel and enhanced israel's rapid economic growth while the export was its leading strength. as we can see in table 1, the transformation in the external forces influenced intensively on this industry while the demand to fulfill ci needs was evidently growing. 95opinion section table 1: impact of external forces after 1993 before 1993 external forces no. developed new capabilities and advanced technological products to answer global needs and compete successfully with leading world corporations moving towards more advanced technologies in response primarily to the local needs technological 1 enhanced an international strategy by aiming towards identifying the needs of foreign customers. mainly influenced by internal politics among government and military political 2 moved towards global markets with distinctive pricing structure supplied mainly local military needs economic 3 intense competition in global markets low exposure to global competition. low competition in the local market industry competition 4 monitoring capturing of global needs of numerous military establishments monitoring local needs of the military establishment key ci needs 4 characteristics of competitive intelligence in the defense industries a survey conducted in the usa (prior, 2009) compared 152 companies actively involved in ci with 1,396 in the same 19 industries. a benchmarking study of 24 firms in aerospace and defense found that, by using ci, three companies obtained outstanding results. the study showed that the industry average: 1. bid success rate was 18 per cent, but the top three won 87 per cent, 96opinion section 75 per cent, and 57 per cent respectively; 2. return for every dollar spent on proposals was us$78, but the top three averaged us$225. the evolution of ci in israel was behind the progress achieved in the us and other western countries (prescott, 1999). one of the main reasons for this inferiority was the overconfidence of israeli executives claimed to have captured the essence of intelligence while in their military service and implemented it within the business field with no need to develop dedicated ci capabilities. this has been changed in the last ten years (barnea 2004). by its nature, ci in defense industries was more strategically oriented, then tactical. the issues ci often covered were more long term defense trends and in depth competitors and customers assessments. its customers were the top management, (but also sales teams and technological teams) and its analysis methods were advanced to meet the expectations of senior executives. the fierce competition described above brings the companies engaged in defense exports to develop strong ci units that make the best use of ci discipline for competitive benchmarking. (mcgonagle & vella, 1996). companies engage in this sector, unlike many other sectors (attaway, 1998), recognize the need for professional peripheral vision (see day and schoemaker 2006). they actually acted by applying 'informed anticipation' approach (see day 1997) to systematically identify in advance changes in the needs and in the markets and to respond by build comprehensive understanding of the technological trends that shape the future and make their assessment available to their management. here are some distinctive features of ci in the israeli defense industry: 1. ci activity was perceived as it can significantly increase the chances of winning tenders and producing competitive advantage (see kahaner 1996). one of the results was wide ci awareness among executives and members of staff in this sector. 2. defense export companies tend to allocate significant resources to develop inhouse ci capabilities. 3. ci activities in this area were characterized by the need to monitor comprehensive range of many frequent changes in the competition map with large quantities of information. it was considered more as a strategic tool rather as a tactical tool by providing important insights (general discussion on the value of ci see in prescott and gibbons, 1993). 97opinion section 4. the key intelligence topics (kit's) of ci units in this industry were mainly the requirements, intentions and plans of countries and defense establishments to improve their military capabilities by purchase defense products and competitors' activity aiming to beat the others. special attention was given to technological innovations. the price issue was a significant factor in decisions regarding winning tenders. 5. strong macroeconomic analysis capabilities were implemented to understand long-term trends and to be able to assist in solutions to strategic planning needs. 6. the development of early warning capabilities that help early identification of business opportunities and threats from existing and new players. these allowed better monitoring and enhance for understanding (for further discussion see gilad 2004). 7. assistance by external research companies to get updates through initial definition of key intelligence needs and also initiating specific research needs like assessing firms that were potential targets for acquisition or for partnership or considering entering into new business sectors close to their core business, as homeland security. 8. durable relying on the gathering capabilities and sharing of information by the sales force teams (contrary to what we know in other industries, lambert, 1990) that were also benefited from the ci analysis capabilities. sale force has become an important gathering tool and efforts are conducted to improve their ci capabilities (the conceptual issue is discussed in moncrief and marshal, 2005). 9. ci functions usually were holding highly the interrelations between them and the various business units and expected to provide added value to the decision making process. it is likely to infer as shown in table 2, that the progress of ci practices conformed to the changes in the activity of this sector supplied added value intelligence: 98opinion section table 2: changes in israeli ci activities after 1993 before 1993 ci activities no. ci dedicated capabilities became formal process of slow developing formal ci and infrequently use ci task forces ci model 1 in hq (corporate level) and also in business units mainly in hq slightly spread in business units ci unit location 2 global domestic ci area focus 3 broad: to cover world competition covers tactical and strategic issues narrow: to cover mainly local competition, usually tactical information ci topics 4 moderately becoming intensive little support by it dedicated tools 5 moderate limited extent of analysis 6 broad, mainly for gathering through open source intelligence (osint) limited extent of use of out sourcing 7 critical as the buying processes and the marketplace became more complex. not considerable ci support to the selling process 8 practical implementation of competitive intelligence usually the professional level of ci units among defense export companies was considered to be high ranked at the top, comparing to similar units in other sectors by the total resources invested in them including the use of advanced information technological systems (see discussion of the use of these tools in israel in barnea, 2009). this was the outcome as of the need to cover a wide range of information sources, regular updates of the decisionmakers and being involved in countless activities, including assessments of the state of competition. these units often 99opinion section make use of forecasting tools of the business environment being characterized by monitoring long-term planning processes (for further discussion on the challenges of business forecasting see laseter, lichtendahl and grushkacockayne, 2010 and courtney, 2001). an important part in responsibilities of ci units was early identification of business opportunities. the purpose was to find opportunities while still in the initial stage at the prospect, preferably in the stage of shaping the requirements, to be able to prepare a response ahead of the competitors. although ci in defense industries enjoyed high awareness to the importance of ci by many executives in the firm, still the implementation of the discipline of "sharing of information" had to be enhanced. the obstacles were not just the nature of people but also the security aspects which were not to be ignored. still the need to share more competitive information existed. defense industries are not alone. lovello and sibony (2010) were referring to the problematic culture of many organizations that withhold to share information and practically were strengthening the "silo thinking" while ci was often aiming towards avoiding these behaviors. accepted estimate was that anyone who could translate the competitive information received from open source intelligence (osint) combined with primary sources and translated it all into formulating an answer would have an advantage and increase the chance to win defense tenders. we could assume that a british company in the defense industry will monitor the difficulties of british soldiers fighting in afghanistan, for example, in the early detection of enemy snipers and will initiate the british defense ministry to propose a solution, even if the bureaucratic procedure of issuing a tender yet not started or completed. this information may come from a variety of sources, including social networks, publications of the department of defense, blogs of soldiers participating in the war, interviews with soldiers who have returned from the battlefield in local newspapers, publications of the islamic organizations active in afghanistan and more. key intelligence topics in the defense industries 1. military threats monitoring and assessing of military threats encountered by clients or potential clients such as defense organizations and defense forces are critical to early identification of business opportunities. for example, the threats that were faced by indian troops on the border with pakistan were different than the threats faced by the spanish intelligence and 100opinion section security organizations fighting against the basque resistance eta. being aware of military threats often led later to characterizing the operational needs and the requirements specific tools, which will reduce the threat or cancel it altogether. comprehension of the progress of the operational needs by the customers or future customers were critical factors expected to be addressed by ci units. 2. technological intelligence technological intelligence continuously monitors technological solutions offered by competitors in response to customers' needs as early as possible. the aim was to understand the existing and future products that would compete in the marketplace in the future. it was required to implement the discipline of competitive technology intelligence (cti). one aspect of this issue was the need of the ci units to build strong internal collaborations with technological professionals to estimate precisely the current and future markets. one of the challenges was determining the right priorities of the technological issues that have to be monitored at any given time. 3. marketing intelligence while technological intelligence was targeting competitors' capabilities, the focus in marketing intelligence was on the customers. marketing focuses on gathering intelligence on customer needs and rising opportunities and support decisions throughout all stages of the competition. an important tool was the company's employees who were in continuous touch with their customers. they should be briefed also to collect information on current and future marketing needs. for example – prior knowledge of budgetary limitations of potential customer, which was familiar to just a few, ended in submission of a competitive proposal that brought this into account. 4. strategic intelligence strategic intelligence was the intelligence required to assess long-term processes and intentions by various players and the marketplace. that was, which direction facing the operational requirements of the countries and armies, the extent of investments in r & d by competitors over the coming years, estimates of new directions by the competitors beyond their core business areas, their intentions to enter into new areas, whether by self-development or through acquisitions, mergers and strategic partners. for example, it was reasonable to estimate that the world's leading companies in defense were following with great interest after the business moves of their israeli competitor elbit systems, which in recent years entered into new areas of activity mostly through mergers 101opinion section and acquisitions and not by organic development and would try to assess elbit's strategy in the coming years (http://www.accessmylibrary.com/coms2/s ummary_0286-28619791_itm). sometimes these strategic reports (for example see bae systems http://www.baesystems.com/productsservi ces/bae_prod_eis_global_analysis.html) are distributed to clients (policymakers and intelligence officers) to help them to understand the threats, risks and opportunities in the international environment. 5. tactical intelligence tactical intelligence was considered to be less critical in this sector, but it was still done on daytoday basis: monitoring changes in the markets, customer insights, changes among competitors and new products (see discussion on tactical and strategical ci in sawka 2010). this intelligence often had an added value for the strategic intelligence. in conclusion of this chapter some people may think mistakenly that ci in defense industries was about price discovery offered by competing tenders. it was usually impossible to obtain this information in advance and companies competing in this area were required to expand their intelligence scoop as outlined above in order to maximize their chances to win. ci in this industry was actually in its strongest position of managing the intelligence, according with the outline that was described in the white paper by arthur d. little consultancy (2010). working programs ci functions usually fit into the annual programs of the israeli defense companies. the main task of the intelligence was to respond to the intelligence requirements according with these plans. for example, a company decided to focus on the defense market of the far east which until recently was ranked low in its priorities list. its ci unit was expected to provide information about competitors' activities in the above mentioned region, the customer's needs by defense establishments and states, to point towards new competitions (tenders) and to identify early strategic partnerships between companies that may give a joined response to the customer's needs and so on. it was assumed that it was impossible to develop a strategy of winning competitions without setting up an orderly key intelligence topics (kit's) list executed by the intelligence unit. it was also likely that the ci functions may build quickly intelligence capabilities that would meet the needs of the firms and thus http://www.accessmylibrary.com/coms2/summary_0286-28619791_itm http://www.accessmylibrary.com/coms2/summary_0286-28619791_itm http://www.baesystems.com/productsservices/bae_prod_eis_global_analysis.html http://www.baesystems.com/productsservices/bae_prod_eis_global_analysis.html 102opinion section increase their chances of winning. action plans were expected to summarize priorities in collaboration with their business units. ci units expected to work closely with the company's executives to bring on to their attention the new opportunities as a result of the intelligence monitoring. the uniqueness of ci activities in the sector of defense was the ability to act simultaneously in several areas of intelligence as mentioned above, in markets which were characterized by tough competition and often insignificant differences in products offered by competitors. therefore, it was necessary for finest understanding of customer needs, markets and capabilities of competitors to know how to produce competitive advantage that would help in pointing at the competitive price which was often a determining factor in the final decision who wins the competition. sources of information and managing the gathering efforts primary sources the defense export market was often characterized by ad hoc collaborations between companies and simultaneously fierce competition known as co opetion. therefore, it is possible that at the same time a single unit at a certain company cooperated with another company while another business unit within that firm competed against it in another sector. this modus operandi allowed skilled benefits of the primary sources among the company employees, especially among the skilled sales force and technological staff that having been working at relationships with various elements in the market. primary sources were also intensive users of ci materials and their professional expertise was playing a role in obtain important information on customers, products, competitors and opportunities, and shared it with ci professionals and other users. thus capable internal networks within the firm, supported by dedicated software often enable ci managers effectively to manage it. secondary sources what characterizes the activity of secondary sources in this industry was the challenge of utilizing enormous amounts of information gathered on military equipment needs, marketing intelligence, new technologies etc. the defense market was characterized by a lot of open source information on one hand and on the other hand, keeping secrets tight. this required high quality information management and precise direction of collection efforts, selection and analysis and distribution to the appropriate units. usually it was hard 103opinion section to expect to handle information without the assistance of dedicated information systems (see barnea 2009). managing the intelligencer efforts this competitive market required constant development of new information sources while keeping the existing sources. this was a result of the need to cover new technological solutions, new geographical regions and countries that were not in focus in the past, new products, etc. at the same time, there were sources that become obsolete as a result of changing priorities and focus in other lines of businesses. therefore, it was necessary to conduct an advanced system for managing key intelligence topics (kit's) and the targets of gathering ( firms, armies, military establishment, etc.), including answers to the needs: who was the firm initiating the request (asking for the information), who in the organization could provide the answers, monitoring and access to the answers received at any given time and information collected in response to avoid duplication and ensure optimal use of resources by the firm. by implementing the above, the ci functions were moving from occasional management of its kit's to a systematic direction. production of quality analysis complexities of strategic and technological issues in the exports' defense industries enhanced the need for qualitative analysis, including frequent use of forecasts and assessments methodologies, formulated the overall quality intelligence into the decision making process. for example, analysis of information about competitor's activity indicated that it moved into fast development of an advanced generation of technological solution, although the previous generation was relatively new. further thorough examination revealed that the existing solution did not meet the needs of the state acquired it so that competitor needed to present a suitable solution soon. this analysis also elevated business opportunity resulted in an attractive offer to the disappointed customer, a solution that proved itself but was not purchased in the past by that state in respect of the high price. this industry was often characterized by intense macro analysis of foreign economies, internal politics, international relations, social changes, and a good understanding of legal and regulation issues. this was in addition to common analysis of competitors, customer, supplies and monitoring of new technologies and advanced applications. 104opinion section using internal information systems ci units in the field of defense understood that one of the keys for their added value was on one side to give access to many people in the organization to competitive information and on the other hand to make many in the organization relate to information obtained, to evaluate the significance and bring it to the attention of others in the organization. advanced information systems were a critical support tool for the success of competitive intelligence processes but the primary challenge was to develop the awareness among the employees. these systems usually divided into two types: 1. systems developed by the companies themselves often via their information technology units 2. purchased solutions in which adjustments were implemented so that they can give the answers expected of them. the direction was to acquire and later adjust systems from the external software houses because solutions were often cheaper and enable internal information systems units to focus on their core areas. one of the challenges is to require of systems that interface with other systems within the organization, such as crm (customer relations management) and erp (enterprise resource planning), where important information was analyzed in conjunction with competitive information. for example, an army of a certain country issued an immediate rfp (request for proposals). it was required to know all "our" existing and potential capabilities to know if and how a reply could be provided. further assessments revealed that the date of the development of essential parts of the required system was two years therefore it was impossible to give an answer to that rfp. its submission date was in six months and placing the system was within a year. key success factors (ksf's) for ci function defining ksf’s (key success factors) for a ci unit is important in any industry (singh, fuld and beurschgens, 2008). it seems that the defense industry has implemented these ksf’s more than other sectors: 1. organizational culture – it is basically the development and the implementation of broad ci awareness by policy of sharing of information, streaming from both sides – from the ci to the internal clients and from them to the ci function. 105opinion section 2. procedures mainly internal procedures guaranteeing the two sided flow of information from external and internal sources and making intelligence available to those who need it to accomplish their assignments. 3. support by it technology – meaning the use of expert tools for complex demands of information attention, for the full intelligence cycle and by an easy access to the intelligence products to those who need it. the outcome using this methodology was that decision making without the contribution of ci was incomplete. these three essentials were together critical for the success of ci function in a corporation. they all had to be interrelated as shown in figure 1. figure 1: ksf's conditions to obtain needed information the following figure (see figure 2) has been prepared based on assumptions made by ci managers in the israeli defense field. it was looking towards two parameters – onethe extent of the difficulties in acquiring valuable information. the other one was the importance of the information received to significant decisions by the firm. as we can see from this figure, it was relatively easy to receive information about customers, competitors, suppliers, partners and decision makers. it was getting more complicated to acquire information about r&d planning and strategic planning while the most difficult was to get information which could directly support to win tenders. the difficulties of maximizing the value of the information were similar to those to obtain information. although a typical ci function strived to cover these topics, it was aspiring to obtain more valuable information (on new technologies, organizational culture procedures expert tools 106opinion section strategic planning, and tenders) which was harder to accomplish. figure 2: challenges of acquiring valuable information summarizing so far shows: ci units operated in the heart of the business activity in the israeli defense sector were involved in the decision making process. although there were often significant gaps of the information required, ci was expected to give assessments that could bridge the lack of focused information. this was done by successful involvement of many employees in the organization into the intelligence process, beyond the immediate scope of the ci unit. there was a good implementation of the discipline of "sharing of information" (internally), as one of the key success factors of ci in this sector. the complex challenges for ci were imposing on the structure of t ci in this field. the results were often a combined ci activity in the corporate level which actually directed the ci efforts while the business units have focused ci activity to answer their specific and often immediate needs. hard to get easy to get insignificant information valuable information competitors suppliers partners decision makers new technologies strategic information tenders customers 107opinion section decision making process by the customer i have already pointed towards the importance of intimate knowledge of the customers (including potential customers), as a key success factor of firms operating in the defense sector. the following key intelligence topics (kit's) were guiding the intelligence efforts: 1. knowing your customer a close and an intimate knowledge was a must in order to be able to make insightful decisions regarding the solutions offered and to be able to reply precisely to the implicit and explicit needs of the customer. interpreting it to actionable intelligence was the challenge of ci in defense firms. this was probably impossible without a crossorganization strategy by the ci function. growing number of firms in this sector admitted that there was no win in a competition without valuable contribution of ci. 2. customer's budget limitations estimating the over whole budget allocated for a defense project. this was included also in assessing the priorities inside the defense establishment in that country. i.e. – the allocations to air force against the needs approved to the armored forces. 3. hidden operational needs what were additional needs that went beyond those that have already formally defined, like what additional components embedded in the proposal could give a competitive edge. 4. special conditions and limitations certain limitations and conditions that were expected to be part of the over whole deal like the need to involve local manufacturing, collaboration with local contractors etc. 5. knowing the decision makers – who were taking part in the decision making process especially in the final stage of the decision about the winner in the competition. key personalities including influencers, approvers, users and buyers (see barnea 2006). obviously there was ongoing search for information that could be used to increase our chances to win. 6. past experience with the customer it was highly important to know the past of our relations with the customers and possibly their relations with our competitors. has this customer fulfilled his 108opinion section obligations? how the customer treated his partners. his suppliers. was that customer paying in time according with the agreements? history of artificial obstacles created for unjustifiable reasons? sometimes to obtain this information, there was a need to look at the experience of various sections in "our" company as customers may have lots of contacts that are unknown internally to others. 7. relations between israel and foreign countries – these relations had an immediate impact on the decision of the regulators whether to approve export of defense products to certain countries in extreme cases when it was assessed that it could harm the security of israel. i.e. – israel was exporting to turkey for many years as part of the close relations between the two states. when these relations have been hurt, it affected also on the volume of export defense goods. observations by senior executives of the role of competitive intelligence my continuous ci consulting with israeli corporations indicates that senior executives in this sector considered ci functions as follows: 1. ci functions had excellent understanding of firms intelligence needs (or the specific business units' needs) and were centering their efforts to provide competitive advantage information. 2. ci functions were integrated into the up to date priorities and had been given resources that enabled them to fulfill their missions. 3. there was an ongoing effort to assure that ci capabilities were matched to the scope of their kit's and were executed in accordance with the working plans. 4. the value of the ci was assessed continuously by the senior executives to maximize its contribution. 5. the resources allocated to ci had to be measured to make sure that shortage of resources will not hurt its activity. conclusions the recent global economic downturn since 2008 had only minor effect on this sector. the number of military conflicts is in increase 109opinion section (http://www.globalsecurity.org/militar y/world/war/index.html) and a moderate rise in global defense expenditures is expected to continue in the coming years jointly with the increase of the competition on each governmental customer. israeli firms in the defense sector enjoy a high reputation by their competitors and customers for their ci professionalism. not very much has been written about the role of ci functions inside defense companies and their effectiveness in the fierce competition in this sector (see an example in the journal of competitive intelligence management, vol.2, no. 4 2004), either worldwide or specifically in israel. the main objective of this paper is to focus on the role of ci in the israeli defense industries and its importance. it appears that ci was capable of holding an advanced position among the israeli defense firms while its capabilities were considered to be a critical success factor like in other sectors, i.e. pharma (badr, madden and wright 2006) and medical devises. this was mainly a result of the recognition by the valuable input of ci into the decision making process and its contribution to the success of companies in their various business lines. ci functions held a critical position in the strategic decisions making process. many business defense issues could not be met effectively and accomplished without ci implementation. in this sector's activity in israel, ci considered an integral part of the organizational structure and its business culture. still there was a tendency to keep the ci capabilities' secret, but this was in a swift change as it became evident that strong ci capabilities were common in this sector worldwide as in many other competitive areas. references attaway, m.c. 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"the art of systematic surveillance", arthur d. little management consultancy, www.adl.com/im internet links consulted http://www.sipri.org/yearbook/2009/07/07 b http://www.sipri.org/yearbook/2009/07/07 b http://jdw.janes.com/public/jdw/index.sht ml http://www.israelwtc.co.il http://www.businessmonitor.com/defence/ israel.html http://www.pr-inside.com/research-andmarkets-israel-defence-and-r2131715.htm http://www.accessmylibrary.com/coms2/s ummary_0286-28619791_itm http://www.globalsecurity.org/military/wo rld/war/index.html http://www.onlineopinion.com.au/view.asp?article=9465 http://www.onlineopinion.com.au/view.asp?article=9465 http://www.outwarrdinsights.com/ http://www.adl.com/im http://www.sipri.org/yearbook/2009/07/07b http://www.sipri.org/yearbook/2009/07/07b http://www.sipri.org/yearbook/2009/07/07b http://www.sipri.org/yearbook/2009/07/07b http://jdw.janes.com/public/jdw/index.shtml http://jdw.janes.com/public/jdw/index.shtml http://www.israelwtc.co.il/ http://www.businessmonitor.com/defence/israel.html http://www.businessmonitor.com/defence/israel.html http://www.pr-inside.com/research-and-markets-israel-defence-and-r2131715.htm http://www.pr-inside.com/research-and-markets-israel-defence-and-r2131715.htm http://www.accessmylibrary.com/coms2/summary_0286-28619791_itm http://www.accessmylibrary.com/coms2/summary_0286-28619791_itm http://www.globalsecurity.org/military/world/war/index.html http://www.globalsecurity.org/military/world/war/index.html 5 a longitudinal look at strategy, intellectual capital and profit pools g. scott erickson 1 and helen n. rothberg 2 1 ithaca college, ithaca, usa 2 marist college, poughkeepsie, usa gerickson@ithaca.edu hnrothberg@aol.com received september 15, accepted october 16 2015 abstract: explores the link between the disparate fields of knowledge management, intellectual capital, competitive intelligence, and strategy. using an existing profit pool study of the digital economy, looks at the key industry sectors involved and their revenue levels and profit margins. these data include results from both 2002 and 2010. the profit pool observations are then compared with additional data on intangible assets (knowledge and related assets) and competitive intelligence activity in each sector. explores but generally dismisses the idea that sector revenue and/or profitability might be linked to high levels of intangibles. similarly, demonstrates that the link between sector revenue and/or profitability and competitive intelligence activity may be generally weak (though pronounced in some specific high-growth circumstances). alternatively, does provide some guidance for more indepth study, identifying the knowledge strategies necessary for success across sectors as well as what competitive intelligence attitude may be needed to move from one sector into another. keywords: knowledge management, intellectual capital, competitive intelligence, profit pools, strategy available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 2 (2015) 5-13 mailto:gerickson@ithaca.edu mailto:hnrothberg@aol.com https://ojs.hh.se/ 6 1. knowledge management and intellectual capital with the advent of the “knowledge economy,” practitioners and scholars have taken a new interest in the potential for strategically managing intangible assets. study of the phenomena encompass a number of different fields, overlapping in both content and concepts. this paper builds on several different literatures in order to examine how a better understanding of intangibles can be combined with other strategic planning tools to achieve competitive advantage. intangible assets were typically connected to innovation studies early on, including schumpeter’s (1934) work on creative destruction, wherein the new ideas came from knowledge combination and subsequent learning. evolutionary theory (nelson & winter 1982) brought innovation more squarely into the mainstream of economics, suggesting that skills, learning, and similar intangibles were the drivers of competitive advantage and economic growth. similarly, the resource-based view of the firm (wernerfelt 1984) sought sources of competitive advantage in unique resources employed by firms, including organizational knowledge or related intangibles. this perspective was further delineated by the knowledge-based view of the firm (teece 1998; grant 1996) and some came to consider intangible assets, as incorporated in personal knowledge or related concepts, as the only really differentiated, sustainable, defensible asset held by these organizations. while early attention in this area focused on innovation and intellectual property, it soon became apparent to both scholars and practitioners that intangible assets might include more than such formalized mechanisms. as just noted, part of the field became focused on the more general concept of knowledge, the know-how, learning, and skills that enhance job performance but don’t necessarily lead to formal patents, copyrights or such. definitions congealed around ackoff’s (1989) dikw hierarchy suggesting that intangibles progressed from raw data to information, then to knowledge and wisdom. “intelligence” has often taken the place of wisdom in more contemporary applications. in knowledge management (km), scholars have often focused on the lower three levels, specifically differentiating between data as observation, information as data in context, and knowledge as data subjected to experience and reflection (zack 1999b). classically, the field has explicitly and emphatically designated knowledge as being the only intangible of real value, data and information are only precursors. the related discipline of intellectual capital (ic) has also gone in this direction, focusing on defining and measuring knowledge assets (bontis 1999; edvinsson & malone 1997; stewart 1997) though some of its methods, as we shall see, are likely to include a wider range of intangibles in the metrics. regardless of measure, however, the field generally looks at human capital (individual knowledge), structural capital (organizational knowledge such as culture, routines), and relational capital (knowledge concerning and relationships with external publics, including customers). km studies deal more with what to do with these knowledge assets, how to apply and grow them. as such, distinctions in the nature of the knowledge and the nature of the organization are important in that they can affect successful development of the intangibles. at the heart of the field is the distinction between tacit and explicit knowledge (nonaka & takeuchi 1996; polanyi 1967) the former being personal and hard to express and the latter more expressable, codifiable, and sharable. nonaka & takeuchi went on to frame an approach to different types of exchanges (e.g. tacit to tacit) establishing the inclination in the field to recognize that singular aspects of knowledge called for distinct km approaches (choi & lee 2003; schulz & jobe 2001; boisot 1995). consequently, both tacit (communities of practice, storytelling) and explicit tools (it systems) exist for managing knowledge, adaptable to circumstance (brown & duguid 1991; matson, patiath & shavers 2003; thomas, kellogg & erickson 2001). other knowledge characteristics identified in the literature include complexity and stickiness/specificity ((mcevily & chakravarthy 2002; zander & kogut 1995; kogut & zander 1992). organizational characteristics can also make knowledge easier or harder to manage. these can include absorptive capacity (cohen & levinthal 1990), social capital (nahapiet & ghoshal 1998), and social networks (liebowitz 2005). there are strong incentives to better manage knowledge, as it can lead to competitive advantage (zack 1999a; grant 1996). but as circumstances vary, there is also a distinct theme in the literature that the appropriate strategy needs to be discerned and employed. there is no one-size-fits-all solution to knowledge development and application. 2. beyond knowledge a more strategic approach can lead in several other directions. not only should knowledge management initiatives be appropriate to the circumstances, but as we widen our perspective to other intangibles, their presence and relative importance can be evaluated as 7 well. in some ways, this is a different approach for the knowledge asset community, both km and ic scholars and practitioners. in other ways, there are indications of the fields already moving in these directions. various business disciplines have brought either intelligence, from one end of the dikw hierarchy, or big data, from the other end, into the conversation. intelligence can take a number of forms according to the vernacular, from business intelligence to marketing intelligence to competitive intelligence. andreou, green & stankosky (2007), in an attempt to organize the various disciplines, created the list of operational knowledge assets including the various intellectual capital designations and intelligence directions. in general, the disciplines moving from knowledge to intelligence suggest some additional level of insight or understanding. knowledge, information and/or data subjected to analysis and applied to decision-making can be considered intelligence. this perspective is perhaps best seen in the field of competitive intelligence (ci), the “intelligence” discipline with the longest practitioner history and most developed scholarship. ci concerns the practice of discerning, anticipating, and reacting to competitor strategies and tactics. this understanding comes from acquiring relevant data, information, and knowledge and applying specific analytical techniques resulting in actionable intelligence (prescott & miller 2001; gilad & herring 1996; fuld 1994). similar to km and ic, competitive intelligence relies on intangible assets as inputs, though it scans a wider range than simply knowledge. it also improves as operators gain experience (wright, picton & callow 2002; raouch & santi 2001). but ci can also differ from the knowledge approaches. high-level practice includes specialized analytical tools and applications (fleisher & bensoussan 2002; mcgonagle & vella 2002), drawing actionable insights rarely seen in km. intangible assets gathered for analysis are also more likely to be obtained from directed search rather than study of existing knowledge, filling designated information gaps. in this way, they are collected for a purpose, aimed at specific actions (gilad 2003; bernhardt 1993). km can be actionable but is more often concerned with developing the knowledge base and then leveraging it through sharing. the example of ci also points to the potential importance of intangible assets at the other end of the hierarchy. intelligence disciplines tend to be not so dismissive of data and information inputs, noting that insights can come from anywhere. indeed, at its base, most knowledge practitioners and scholars would probably agree that review of data and information can lead to new knowledge, that the former are precursors to higher level knowledge assets (and the even more advanced level of intelligence). the recent trend toward employing big data for business analytics and business intelligence both reinforces this view while also establishing the idea that data and information might have value in and of themselves, especially when we are talking about market valuations or capitalizations. big data, business analytics, and related terms all refer to the trend of organizations accumulating huge amounts of data, storing and processing them on increasingly inexpensive systems (often in the cloud), and mining them for insights (beyer & laney 2012; laney 2001). as an extension of how we’ve thought of intangibles from a knowledge perspective, there are clear connections. scholars have explicitly made the connection (bose 2009; jourdan, rainer & marshall 2008). indeed, a case can be made that the field fits comfortably within the accepted wisdom of the km/ic framework, with a structure running from data to explicit knowledge to tacit knowledge to the unknowable (simard 2014; kurtz & snowden 2003) with the latter perhaps including the unique insights coming from intelligence or wisdom. in a number of ways, ackoff’s dikw remains relevant even in this new context. as alluded to earlier, this is the area where all the fields can come together. the established scholarship and practice found in km and ic could be enhanced through more attention paid to preknowledge inputs such as data and information. alternatively, there are concepts about the workability of intangible asset management systems (trust, motivation for use, etc.), particularly how humans interact with it structures that are highly relevant to managing big data operations (matson, patiath & shavers 2003; thomas, kellogg & erickson 2001). but we aim to take cross-discipline integration even further. the intersection of the knowledge and intelligence fields also begs the question of asset vulnerability, as valuable intangibles spread ever more widely throughout an organization and its extended network can be particularly subject to competitive intelligence efforts. km, ic, intelligence, and now big data all call for ever increased sharing of valuable proprietary intangible assets throughout companies and even extended partner networks. this wider dispersion can raise vulnerability as competitors seeking these assets have more choice in targets (liebeskind 1996). at its heart, this is a cost/benefit evaluation, the additional benefits from greater employment of 8 intangibles vs. the potential costs of losing the intangibles to competitive intelligence or economic espionage. the appropriate levels of intangibles development, protection, and counterintelligence are a matter of strategy, with individual firms evaluating their particular circumstances in their particular industry (erickson & rothberg 2012; liebowitz 2006; rothberg & erickson 2005). but the strategy connection can be pursued more fully. as decision-makers evaluate strategic opportunities, we believe that a deeper understanding of intangibles and the intangible asset standing of a firm can be an aid. in particular, in the strategy literature concerning innovation or growth opportunities across industry sectors, part of the question is the firm’s “fit” with circumstances. if intangible assets really are the critical component of competitiveness, then understanding them, and their need in different industry sectors, may be key to correctly identifying strategic opportunities. when combined with tools such as porter’s (1979) five forces to assess sector attractiveness, a better understanding of intangibles could provide the explanation for why a sector is appropriate for entry by a specific firm (or not). similarly, christensen’s (1997) innovator’s dilemma posed the question of whether standard metrics such as market share were appropriate for judging success, let alone competitive capabilities. where standard metrics may not be enough to help with decisions concerning strategic direction, a better understanding of intangibles, particularly knowledge and these related assets, may be the missing piece in the equation. 3. conceptual framework and methodology this paper combines data on knowledge assets, competitive intelligence, and industry sector attractiveness. we assess the data over time, trying to get some sense of the relationship between intangibles and related capabilities against industry sector success (and potential success in other sectors). in order to do so, we employ profit pool analysis, added to our own databases concerning knowledge asset levels and competitive intelligence activity. profit pools describe revenue and profits within an industry, specifically in each sector along the industry value chain (gadiesh & gilbert 1998a). a profit pool map is sometimes constructed as a visual aid, contrasting horizontal revenue with vertical profit margin, yielding instant comparisons of the size and profitability of designated industry sectors (gadiesh & gilberg 1998b). more depth often comes from analysis of sector details such as segmentation and customer buying behaviour, product offerings, distribution channels and geographic options, particularly as similarities are seen across sectors that can be pursued as growth opportunities. continued tracking of changes in the profit pool over time can add even more dynamism to the analysis. here, we use profit pools of the digital economy constructed by booz consultants (standridge & pencavel 2011), showing conditions in both 2002 and 2010. the size and profitability of the industry sectors changes over time, as shown in the following table. this changes the attractiveness of the different sectors, creating new opportunities for cross-sector innovation and/or entry. standridge & pencavel note apple’s success, for example, in moving into downstream sectors with potentially higher margins than devices proper and offering higher margin services to go along with the devices it does offer. similarly, competitors from google to microsoft to amazon.com are all looking for new opportunities in sectors, potentially more profitable, where they haven’t traditionally competed. but sector attractiveness doesn’t shed light on organizational capabilities for exploiting such new opportunities. how can a firm assess its own potential for innovation within or across sectors? how can it assess competitors’ competencies? we believe the study of intangibles, especially intellectual capital, might lend some insight. if the firm knows what it knows, and it knows what competitors know, it may be better placed to predict, act, and counteract moves across industry sectors. in this study, we combine our own databases of intellectual capital level and competitive intelligence activity (erickson & rothberg 2012) with the standridge and pencavel profit pool. in measuring ic, a variety of metrics are available (tan, plowman & hancock 2007; firer & williams 2003) though only a few really make sense if evaluating a large number of firms (sveiby 2010). consequently, we employ a variation on tobin’s q (tobin & brainerd 1977). tobin’s q estimates intangibles by comparing the firm’s value with its level of tangible assets, specifically market capitalization to replacement cost of assets. as the latter figure is often hard to obtain, market cap to book value is a commonly used variation. we often take it a step further and use market cap to asset value as well (which removes liabilities, for our purposes the ownership of the assets isn’t usually material), though we have yet to see a consistent material difference between the two metrics in various comparisons. tobin’s q has the added advantage of implicitly containing all intangibles, from data and information to knowledge and intelligence. 9 our data come from i/b/e/s and include all firms listed on north american exchanges, 2005-2009, with annual revenues over $1 billion. the end result is over 2,000 firms and over 7,000 entries organized by industry (sic number). an earlier database, also included in this paper, covers over 500 firms from 1993-1996. we drew the market capitalization and asset levels from these databases. competitive intelligence data is drawn from two different sources. the 2005-2009 period contains data from a benchmarking study conducted by fuld & company, a major ci consultancy. over 1,000 ci practitioners from around the world answered self-reports on the maturity and proficiency of their operation. then added up by industry and indexed, they provide us with evidence of the level of ci activity in a given industry. similarly, data from the 1993-1996 group includes membership and activity reported from the then society of competitive intelligence professionals (scip) records. arranged again by industry, the relative level of activity in each sector can be assessed. note that the two ci metrics are not directly comparable. 4. results and discussion table 1 presents the more current data. the first two columns come from the profit pool constructed by standridge and pencavel. the latter three come from our database, constructed as detailed above. so the market cap columns show data retrieved from financial reports and the latter from the fuld & company database. the index employed for competitive intelligence combines self-reported proficiency with number of industry participants. the very high number for the software sector, for example, is indicative of multiple firms with ci operatives who report a high level of proficiency. for the intellectual capital/intangible asset columns, the global means for the entire database (thousands of observations) are reported for perspective. table 1: digital industries profit pool, intellectual capital, competitive intelligence 2010 industry revenue ($billions) ebit market cap/book (2005/2009) market cap/assets (2005/2009) ci index (2005/2009) content providers broadcast print 400 15% 1.56 2.53 0.73 0.74 0 2 service providers telecom wireless 2400 20% 1.99 3.90 0.54 1.02 12 16 equipment providers networking storage 300 11% 2.72 3.13 1.74 1.64 0 7 software 150 33% 3.89 2.14 113 net software and services 150 17% 3.48 2.08 19 devices computer communication 900 8% 4.48 2.73 1.58 1.56 22 17 total 4300 2.68 (global mean) 1.02 (global mean) table 2 includes similar information, but from the older databases. the first two columns of data again come from standridge and pencavel, this time their 2002 numbers. we pair that with our older database, from 1993 to 1996. this is obviously not an ideal match but does provide some basis for comparison between the older and newer data in the two tables. while our older data doesn’t exactly match the s&p time period and is more limited than our more recent database (in terms of number of firms), it does again provide multiple years of observations, smoothing the data somewhat and muting the effect of one-time events that may skew the results of individual firms. what we end up with is a comparison of data from 2010 and preceding years to be compared with 2002 and preceding years, even if the gap is somewhat different. it still provides a basis for analysis of what 10 happens in a profit pool and its related intangible asset levels. table 2: digital profit pool, intellectual capital and competitive intelligence, 2002 industry revenue ($billions) ebit market cap/assets (1993/1996) ci index (1993/1996) content providers broadcast print 500 12.5% 0.94 1.83 0.91 0.63 service providers telecom wireless 2200 17.5% 1.79 3.11 3.23 0.92 equipment providers networking storage 200 3% 2.68 0.82 software 100 25% 4.29 0.82 net software and services 100 -2% ---- devices computer communication 700 3% 1.25 2.65 1.62 1.16 total 3800 1.76 (global mean) our initial thought in conducting this type of analysis was that more attractive industry sectors (higher margins, though perhaps also higher revenue) would show indications of higher levels of intellectual capital. essentially, that more knowledge would be needed in high profit sectors. similarly, we hypothesized that higher levels of competitive intelligence activity would also be found, as competition would be fiercer where high potential existed. in a previous study on healthcare, we noticed some connection with ci but not much evidence of a relationship with intellectual capital. here, the exploratory evidence is decidedly mixed. the very highest ebit sectors show pretty high levels of intellectual capital, but the relationship is not exclusive. there are high ic ratios associated with some very low profit margins as well. in some ways, the details make some sense of the results with wireless, for example, showing high ic in the high margin service providers sector while traditional telecom does not—one would imagine that wireless is driving the profitability. another likely explanation is that fast growing areas with high profit potential might also require heavy investment and/or debt. either could drive down the ic rating, at least market cap/book. one can see some of the effects of such leverage in the relatively higher market/book vs. market/assets rating in 2010 in the wireless and print sectors. one really interesting result is the virtually uniform increase in profitability across sectors during the profit pool analysis period. at the same time, cap/asset ratio has gone down everywhere except computer devices (and the previously non-existent internet category). given the pattern, it seems much more likely that something appreciable has changed across all sectors (increased productivity, decreased labor, increased outsourcing, etc.) as opposed to any general insights about intangibles we might draw. the only real conclusion to be made is that software was and remains highly profitable while requiring substantial knowledge assets. at the same time, telecom seems a low-profit commodity with few and declining required knowledge assets, something seen to a lesser degree with content providers. equipment providers are in the unattractive situation of requiring extensive knowledge assets but with relatively low (though now growing) profitability. in terms of the competitive intelligence results, telecom and devices showed the highest level of ci activity in the early time period. these sectors remain relatively active, but have been eclipsed by software. while it was relatively docile in the midnineties, it is now way above other sectors and is, in fact, one of the absolutely busiest industries in our entire dataset. net software and services have shown similar growth. this might be tied to the high levels of profitability seen in the sectors. as competitors noticed the margins to be had in these industries, it seems quite likely that they attracted increasing ci 11 investment and attention. the possibility of correlation between high margins and ci is more pronounced than that seen between margins and intangible assets. there is certainly more to be studied in the general results, but our inclination now is that the more valuable insights may come from more indepth studies of selected sectors. as we’ve found in other areas, the application of both km and ci tend to be strategic. in some cases, it makes sense to invest in developing knowledge assets, in others not. it depends on the nature of the assets (tacit, explicit, human capital, relational capital, sticky, specific, etc.) and how effective and profitable km techniques might be. similarly, in some cases ci activity and/or protection make sense. investment in an aggressive ci operation may make sense when circumstances are right (again, the nature of the knowledge or other variables such as product life cycle stage or position on the industry value chain). in others, it may make little sense. in some circumstances, substantial counterintelligence may be right, in others, it may be a waste of money. the answers will be found in deeper understandings of the nature of knowledge and ci in the industry sectors. where is the valuable knowledge and what is its nature? how transferable might it be? the answers to those questions will also bring us back then to profit pools. by understanding the knowledge development and competitive intelligence imperatives in different industry sectors, individual firms will have a better idea about whether their capabilities and competencies would help them in a different environment. if a highly profitable sector demands extensive explicit knowledge, big data, and an advanced km system like software, for example, then a firm looking to come from a different sector without such tendencies (content?) might think twice or look to buy the required competencies as an entry method. similarly, if the ci activity is fierce and focused on a particular type of knowledge or activity (again, software), then once again a firm with no experience with such competitive conditions (broadcast, networking equipment) might again give pause before entering. finally, these metrics can provide deeper insight as the conditions change over time. when we see profitability and/or revenues change dramatically over time (as in net software and services), a fuller understanding of knowledge and ci details can provide interested firms with deeper insights as to the how, why, and what to do questions that naturally arise. acknowledgement the authors gratefully acknowledge the contributions of fuld & company and strategic and competitive intelligence professionals (scip) for providing some of the data used in this study. references andreou, a.n., green, a. & stankosky, m. 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(1995) “knowledge and the speed of transfer and imitation of organizational capabilities: an empirical test”, organization science, 6(1), 76-92. jisib-vol-12_nr-1(2022) (3).pdf journal of intelligence studies in business vol. 12 no. 1 (2022) open access: freely available at: https://ojs.hh.se/ pp. 34–43 sharia compliance, islamic corporate governance, and fraud: a study of sharia banks in indonesia dedik triyanto received 29 june 2022 accepted 17 november 2022 abstract this study aims to examine the effect of islamic corporate governance and sharia compliance on indications of fraud occurring in indonesia’s islamic banks from 2016 to 2020. the independent variables are islamic corporate governance and sharia compliance with islamic commercial banks. the population in this study were all islamic banks registered in the purposive sampling method. in this study, there were 11 islamic banks with a 5 years research period so that the total sample used in this study amounted to 55. the analytical method used in this study was logistic regression which was processed using spss version 25. the results of this study indicate that the islamic corporate governance variable has a positive in islamic commercial banks while sharia compliance with the proxy of islamic income ratio does not affect the indications of the occurrence of frauds in islamic commercial banks. keywords: 1. introduction the existence of a type of bank clinging to the islamic principle shall promise the public trust towards the security upon things that against islamic sharia. on the contrary, the indonesian public trust on the sharia bank is far less compared with conventional that implements its activities based on islamic sharia principles stated in the al-quran and banks must adhere to the rules and regulations that apply to the contracts in the islamic commercial transaction jurisprudence or . with its nature of existence which inherently following the islamic principle, there should entail the people’s trust guarantee in security to avoid things that are not folin the practice of indonesian public trust, the trust in islamic banks is still very less than that of conventional banks. based on data the islamic bank market share in march 2019 occupies only 5.94% of the total banking market share in indonesia (otoritas jasa keuangan, 2019). this shows that public interest in islamic banks is still relatively very low. the performance evaluation applied to the islamic banks tends to prioritize solely on its performance obliges the same ratio as found banks should not neglect the islamic principle that needs to be applied to islamic banks ria elements themselves cannot promise the guarantee that an institution is free from fraud. recall that as of now, there are still 35 fraud cases that occur in islamic banks. one of the fraud cases at bank syariah mandiri for idr 1,100,000,000,000 where the submission of debtor funds did not used according to the proposal when the money was disbursed referring the indications that the funds although fraud-prone to occur anywhere, fraud in islamic banks is very contrary to islamic principles adhered closely to islamic banks. the corporate governance weaknesses found related to governance weaknesses in islamic banking companies, namely (marheni, 2017) the banks are required to carry out regular self-assessments on the implementation of good corporate governance based on rankings of 11 factors that are concluded as complete values, then the results of the assessment will be ranked (1 to 5) with the smaller indicates the better (nelson, 2014). ironically, real-world implementation of bank mandiri syariah which is cases) compared to ranked-2 (good) btpn syariah with no fraud committed in 2017. according to (abdi, 2017), the implementation of good corporate governance can be used in efforts to prevent fraud in the islamic banks. islamic corporate governance is an important issue related to governance weaknesses in the islamic banking and is also dominated by the sharia bank compliance with the sharia principles since sharia bank management is deemed unable to guarantee sharia compliance in the banking services provided (ansori, 2014). the low compliance with sharia principles provides an opportunity for fraud committed in the islamic banks. according to marheni (2017), the islamic disclosure index can be utilized to measure sharia compliance indicators and the indicators employed in this study is islamic income ratio is the income derived from islamic activities and investments in compliance with the principles of islamic law. the islamic income ratio is the ratio between the halal income obtained compared to the total income consisting of total islamic income and non-halal income. with the implementation of islamic principles and corporate governance in islam, the practice of fraud will be reduced. the higher level of compliant bank syariah to islamic principles in its governance is, the muamalat bank whose islamic income of 87% of its total income, there were still 35 cases of fraud in 2017. while in mega syariah bank with 75% islamic income ratio, there were only 3 cases of fraud occurred in 2017. it suggests that despite the good adherence to islamic principles, it does not necessarily indicate the lean possibility of fraud. according sharing ( and partnership sharing ( a sharia bank has implemented a strong shabased on sharia principles, the possibility of fraud will even be smaller. reduces the possibility of fraud at the islamic banks. panin syariah bank, with a profit-sharing ratio of 84% higher than that of bni syariah bank with 23%, has fraud occurrence was spotted. this study refers to research conducted by rahmayani & rahmawaty (2017), the difference in research lies in the independent variable used is sharia compliance. they further noticed that islamic corporate of fraud at islamic commercial banks. according to mohamed i, cholins g, opong, & avison (2017) found that dynamic corporate according to in’airat (2016), corporate fraud. this is in line with the study conducted by sitti (2016) where dynamic corporate governance has a positive effect on fraud. prevention. it means that the implementation of the corporate governance mechanism in islamic banks by observing and implementing all islamic principles could decrease the occurrence of fraud abdi (2017). in addition, accordgovernance prone corporate management to commit fraud. 36 according to marheni (2017), the islamic effect on fraud. the research aligns with ratio has a negative effect on fraud, but sharia compliance which is proxied by islamic income (2013) suggest that sharia compliance does not affect sharia banking compliance with sharia principles. based on the phenomenon upon the aforementioned cases and the inconsistencies in the previous research, the research related to fraud in islamic banks becomes interesting to be revisited. this study aims to determine the partial effect between islamic income ratio governance. also, it is to understand partially ratio and islamic corporate governance to the indication of fraud. the last, it is to observe sharing ratio on indications of fraud through islamic corporate governance. 2. theory 2.1 the effect of islamic income ration on islamic corporate governance the performance of sharia bank could be measured with the following indicators: islamic 2020). to obtain good performance, decent company management is required. prior studies indicated that islamic income ration has a positive correlation on islamic corporate governance (meilani, 2016). this reveals that the higher the level of islamic income ration or performance 2.2 the effect of islamic income ration on islamic corporate governance the performance of sharia bank could be measured with the following indicators: islamic 2020). to obtain good performance, decent company management is required. prior studies indicated that islamic income ration has a positive correlation on islamic corporate governance (meilani, 2016). this reveals that performance of sharia bank is in correspondence with the implementation level of islamic corporate governance on sharia bank. 1: islamic income ratio has positive effects on islamic corporate governance in sharia bank islamic corporate governance one of many reasons that sharia bank has of management ability to monitor operational activities, or in other words, it has a low implementation of islamic corporate governance (sapuan, sanusi, ismail, & wibowo, 2016). prior study found the positive correlation between ratio, the higher the management implementation based on sharia laws (alhammadi, archer, padgett, & abdel karim, 2020). 2: has positive effects on islamic corporate governance in sharia banks. 2.4 the effects of islamic income ratio on fraud the sharia principle forbids usury, and actions. therefore, sharia bank only procure the income from halal source as a study found that islamic income ratio has a negative effect on fraud (marheni, 2017) when a sharia bank adheres and conducts its business according to sharia principles by reducing non-halal income or usury, minimize fraud is expected because the management of funds is based on islamic principles and prudence. thus, if islamic income increases, the possibility of fraud will decrease because islamic income that is following sharia principles is an indication of islamic bank compliance with sharia principles. so, the hypothesis proposed in this study is: effect on fraud on sharia bank. on fraud on sharia principles. per uu no. 21 of 2008 coning in sharia banking is carried out through and contracts 37 pliance with sharia principles is low, it will potentially initiated fraud. therefore, a guarantee is needed for the application of sharia principles in all customer fund management. studies conducted by marheni (2017) fraud indications in sharia bank. thus, when nant in islamic banks, the fraud gets lesser. so, the hypothesis proposed in this study is: 4 effect on fraud in sharia banks 2.6 the effects of islamic corporate governance on fraud cial institution based on islamic principles becomes a demand for sharia banks in implementing good corporate governance and following islamic corporate governance. islamic banks have a higher management risk if compared to conventional banks. thus, a management that is per islamic principles requires wulandari, 2016). by implementing islamic corporate governance, it should be an added value to sharia banks in giving indications and impressions to the public that islamic institutions, especially sharia banks, are safer and more eager to avoid cheating practices, even though fraud can occur anywhere (mahmood & islam, 2016). this is supported fraud can occur due to a lack of proper management. sharia banks are obliged to adhere to sharia principles in carrying out their business and are expected to minimize fraud. according to abdi (2017) and ansori (2014), good corporate management negatively affects internal fraud. the islamic corporate governance model, if implemented properly, will have an impact on reducing the level of razimi, 2016). so, the hypothesis proposed in this study is: 5: islamic corporate governance nega3. data and methods 3.1 study characteristics according to sugiyono (2016), research is a sciposes. this study uses a quantitative method, a method that uses data in the form of numbers (statistics) or can be in the form of qualitative data that is converted into numbers (scoring). regression equation are islamic income corporate governance as the dependent variable. the independent variables in the second regression equation are islamic income ratio, governance with an indication of the fraud occurrence as the dependent variable. 3.3 population and sample in this study, the population is all islamic commercial banks registered with keuangan) in the 2016-2020 period. moreover, the sample is sharia bank registered with 2020 period which was selected by meeting the sample requirements using a purposive h3 h1 h5 h2 h4 islamic income ratio (x1) profit sharing ratio (x2) islamic corporate governance (y) fraud (z) 38 sampling technique. purposive sampling or judgment sampling is a sampling technique that is based on certain criteria (sugiyono, 2016). the criteria for sampling in this study are as follows: 3.4 data analysis technique and hypothesis testing according to sugiyono (2016) data analysis techniques act as quantitative data processing. in quantitative research, the characteristics of the sample in proportion, percent, or mean and standard deviation are described by the authors. estimation of the strength of variable relationships and statistical hypothesis testing is also conducted by authors. in this study, panel data regression analysis and logistic regression analysis were used. 3.5 panel data regression analysis according to basuki & prawoto (2016) panel data regression is a combination of cross-section model in this study has 2 independent sharing ratio, and a dependent variable: islamic corporate governance. the panel data regression formula is as follows: information: : a : constants : : 3.7 logistic regression analysis according to sekaran & bougie (2017), logistic regression as a mathematical model approach that can be used as a description of the relationship between several independent variables and a bound variable consists of two categories. because the dependent variable is of two categories (fraud and not fraud) leaves the logistic regression analysis as the most appropriate to be used in the second research model. essentially, the logistic regression analysis holds the same principle as discriminant analysis, but the difference lies in the type of data from the dependent variable (siyoto & ali, 2016). besides, the purpose of using logistic regression is to predict the size of the dependent variable in the form of a binary or dummy variable. the equation form of logistic regression according to ghozali (2013) is as follows: ln = fd1 – p where : ln = fd 1 – p : fraud committed in the sharia banks a : constant : islamic corporate governance : islamic income ratio 4. results the sharia compliance variables characterized ratio hold a ratio scale data that can go through sampling criteria, no. criteria quantity 1 13 2 sharia banks with consistent gcg report and annual report (2016–2020) (0) 3 sharia banks with unpublished gcg and annual report but have complete required data (2016–2020) (2) 4 sample quantity of sharia bank 11 5 study ample quantity (11 x 5) 55 descriptive statistic analysis of the data ratio. variable n minimum maximum mean std. deviation 55 .561 .997 .91880 .09385 55 .007 1.00 .45307 .28063 39 mean, standard deviation, minimum point, and maximum point. based on table 2, the results of descriptive statistical analysis show that the islamic income ratio variable has the lowest and the highest value of 0.561 and 0.997, respectively. besides, it has the mean or average and the standard deviation of 0.91880 and 0.09385, respectively. the average value which is greater than the standard deviation indicates that the islamic income ratio data is grouped and does not vary or does not spread far from the average. the results of descriptive statistical analythe lowest and the highest values of 0.007 and 1.00, respectively. whereas the average value and a standard deviation are 0.45307 and 0.28063, respectively. the greater average value compared with its standard deviation does not vary or group. islamic income ratio percentage of sharia bank within the period of 2016-2020. islamic income ratio sample percentage mean (0.91880) 55 100% 36 66% 19 34% based on table 3, 2016 to 2020 data for 55 samples of sharia commercial banks consists of 29 sharia banks (66% of sharia commercial banks) showed an above-average value. this means that 36 out of 55 samples have performed their islamic income ratios well or have complied with sharia bank principles by making more income based on sharia principles. the remaining 19 sharia commercial banks, i.e. 34% sharia banks, are below the average. this means that there are 19 out of 55 samples shave not complied with sharia principles and there are still large amounts of non-halal income the above and below average samples of islamic income ratio, it suggests that the above-average is superior. it can be concluded that the private sharia banks’ adherence to the principle is categorized as averagely good. sample percentage mean (0.45307) 55 100% 27 49% 28 51% based on the table 4, 2016 to 2020 data for 55 samples of sharia commercial banks consists of 27 sharia banks, i.e. 50% of sharia commercial banks, showed an above-average value. it means that 27 out of 55 samples of sharia commercial banks have complied with the remaining 28 sharia commercial banks or 50% sharia banks are below the average. this means that there are 28 sharia commercial banks out of 55 samples remains lack comthe above and below an average sample of tributed. thus, some private sharia banks have complied with sharia principles by it-sharing principles, namely and contracts. on the other hand, some private sharia banks have not complied neling more funding with other contracts other analysis of descriptive statistic of islamic corporate governance descriptive statistic of islamic corporate governance. criteria frequency percentage excellent 18 33% good 31 56% acceptable 6 11% jumlah 55 100% based on table 5, sharia banks holds a excellent predicate with a total value of less than 1.5 for islamic corporate governance from 2016 to 2020. it means that 18 of 55 samples or 33% of sharia banks have implemented good corporate governance very well. islamic banks possessing excellent predicate includes bank bca syariah, bank syariah mandiri, and bank panin syariah. islamic banks with good predicate with a complete value of 1.5 to 2.5 are 31. it means that 31 out of 55 samples or 56% of islamic banks have implemented good corporate governance well. sharia banks with good titles include bni syariah bank, bri syariah bank, mega syariah bank, btpn syariah bank, and bukopin syariah bank. then the sharia banks with acceptable predicate with a value of 2.5 to 3.5 are as many as 6. it means that 6 out 40 of 55 samples or 11% of sharia banks are acceptable in implementing good corporate governance. sharia banks with acceptable titles include bank muamalat, maybank there are no sharia banks with the predicate of bad or having a value of more than 3.5. it means that in this study, there is no sharia the implementation of islamic corporate governance. in this study, from 55 samples of sharia banks in the 5 years of the study period, the average sharia banks had a value of 1.5 55 samples or 56%, meaning that more sharia banks with islamic corporate governance were categorized as “good”. 4.1 descriptive statistic analysis on the fraud occurrence indications occurrence indications. criteria frequency percentage non-fraud 21 38 fraud 34 62 total 55 100 table 6 shows that in the variable indication of fraud from 55 samples of islamic banks, as many as 21 samples or 38% did not indicate fraud. during the 5 year study period of sharia banks, a fraud was not spotted including bca syariah bank (2016 to 2020), btpn syariah bank, bukopin syariah bank, and maybank syariah (2016 to 2017), and bni syariah banks (in 2020). whereas 34 samples or 62% were indicated as committed a cheat or indicated fraud. the number of companies indicated by fraud indicates that the internal control in the islamic banks is not robust enough. also, it means that more sharia banks have ever indicated fraud. based on data for 5 years of the study period, fraud cases at islamic banks occurred more prevalently at bank muamalat. in the last two years, there have been 83 and 35 cases of fraud committed by permanent employees in 2019 and 2020, respectively. 4.2 regression analysis of the data panel model r r square std. error of the estimate 1 .122a .15 .59613 table 7 shows that the r square value of 0.15 is obtained. this can be interpreted that the combination of sharia compliance which is indicated by the islamic income ratio and on the islamic corporate governance variable by the amount of 15%. while 85% of islamic by other factors. b s.e. sig. icg 1.324 ,836 ,051 step 1a iir -20.385 3,269 ,059 psr -1,324 1,662 ,368 constant 1,404 3,436 ,683 as shown in table 8, the islamic corporate effect on fraud indication in sharia bank. 4.3 the effect of islamic corporate governance on fraud indication logistic regression testing on islamic corporate 1 hypothesis. thus, could be said that islamic corporate governance partially has no effect on fraud indication. description fraud indicated not fraud indicated total n percentage n percentage higher than the average (>1,89) 22 73% 8 27% 30 lower than the average (<1,89) 6 43% 8 57% 14 total 28 16 55 the sharia bank has a complicit value of 1.52.5 with 1.89 as the average. all of 55 samples, 30 of them have higher than the average 41 value while the rest of them have lower than tioned, 22 samples (73%) have fraud indication, and the other 8 (27%) have no fraud indication. in line with the theory, the higher the complicit value, the more fraud will be indicated. whereas from 14 samples with lower than the average value (<1.89), 6 of them have fraud indication and the other 8 have no fraud indication. complicit value of <2.5 shows the excellency of management in or very good management systems are still having fraud indication, both from higher or lower than the average category. the effects of islamic indocme ration on logistic regression result of the islamic 2 hypothesis is rejected. thus, the islamic income ratio partially does not affect fraud indication. description fraud indicated no fraud indicated total n percentage n percentage higher than the average 16 56% 13 44% 29 lower than the average 12 80% 3 20% 15 total 28 16 55 based on research (marheni, 2017), when islamic income ration is high and the fraud indication is low, it means that the sharia bank already executed the sharia principle. bank with fraud indications mainly comes from the group with iir higher than the averthe average, as many as 16 samples (56%) have fraud indication and the other 15 samples (44%) have no fraud indication. thus, although the islamic income ratio is well implemented, there is no indication that sharia bank is clear from fraud. this also shows that income activity with the sharia principle has no effects on fraud. this study is aligned with another study that there is no effect of islamic income ration on fraud. 3 hypothesis is rejected. sharia banks. description fraud indicated no fraud indicated total n percentage n percentage higher than the average 11 50% 11 50% 22 lower than the average 17 77% 5 23% 22 total 28 16 55 both of the groups with psr higher and lower than the average. but, from 22 samples with iir lower than the average, as many as 17 samples (77%) have fraud indication. therefore, sharia banks with psr lower than the average is more likely to have fraud indication. indication, as many as 11 samples came from from 16 samples with no fraud indication, 11 of those data, could be concluded that the level of psr of sharia bank does not affect its fraud indication, with the proof from table 11 that both groups with psr higher and lower than the average have fraud indication. path analysis of direct and indirect effect. variable direct indirect total 0.480 0.136 -20.385 0.636 -19.749 -1.324 0.180 -1.155 1.324 attained that the direct effect of islamic income ration on fraud is -20.385 that is greater than cient of 0.180. these data reveal that islamic corporate governance is not an intervening variable which correlate islamic income ration 42 5. conclusions and implication corporate governance from common sharia banks from 2016-2020 has the complicit average value within the “good” category. thus, there were more sharia bank with good islamic corporate governance implementation. the sharia banks that possess the highest bank from 2016-2020 and mandiri sharia bank from 2016-2020. the other sharia bank with the “rather good” category is muamalat bank from 2016-2020. moreover, sharia compliance with islamic income ratio proxy in sharia banks from the 2016-2020 period, there was 29 out of 55 banks have higher than the average. thus, more sharia bank has implemented its islamic income ration or already following the sharia principle by focusing on islamic income and reducing usury. the average islamic income ratio is lower than its deviation standard, which means that the data are clustered and not far-placed from the average. on sharing ration proxy on sharia banks from 2016-2020; there were equally 22 banks with lower and higher than the average value out of 55 samples. these data depict that sharia banks is not stern on sharia principles in terms deviation, which means that the data is not varied and not scattered away from its average. on fraud indication on sharia banks from 2016-2020, there were 28 out of 55 samples have fraud indication. the other 16 have no fraud indication, and they are bca sharia bank from 2016-2020, btpn sharia bank from 20162020, bukopin sharia bank from 2016-2017, maybank sharia from 2016-2017, bni sharia sharia bank on 2016. simultaneously, islamic corporate governance and sharia compliance with islamic income ratio proxy are affecting fraud indication. islamic corporate governance is partially affecting fraud indication on common sharia bank with positive direction. sharia compliance with islamic income ratio proxy is partially not affecting fraud indication sharing ratio is partially affecting fraud indication on sharia bank in a negative direction. based on dan testing, the value of is 0.35, which means that the combination of islamic corporate governance and sharia compliance with ratio proxy are capable to explain the detection of variable on fraud indication as much as 35%. the other 65% is explained by other factors than in this study. thus, future studies expected to add other independent variables, for instance, the sharia compliance with moreover, more samples also expected since this study is focused on sharia banks thus of this study, the complicit value could be used as consideration for customers to decide where whose goals are improving market share and garnering customers, it is integral to pay attention to factors than affect fraud, since sharia bank has a strength that should be potential if managed properly. not to mention in the country with a predominantly muslim country such as indonesia. sharia bank should pay attention more to sharia principles that could affect since by abiding the sharia principles embedded with proper management, sharia bank could reduce the fraud potential. references abdi, s. 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(2016). . bandung: alfabeta. trieved january 23, 2019, from https://www. cnnindonesia.com/ekonomi/20200214172620 78-276222/bank-syariah-mandiri-diduof banking customers for product development in islamic banking in indonesia a maslahah pyramid approach. https://doi. ceptual study on islamic corporate gover, 4(6), 357. https:// doi.org/10.11648/j.ijefm.20160406.17 36 evaluation of e-word-of-mouth through business intelligence processes in banking domain lucie šperková, petr škola, tomáš bruckner department of information technologies, faculty of informatics and statistics, university of economics, prague, czech republic lucie.sperkova@vse.cz petr.skola@vse.cz tomas.bruckner@vse.cz received september 1, accepted october 3 2015 abstract: social networks and internet discussions are valuable sources for a company’s marketing research and public relations management. the internet is full of public communication in an unstructured form and reflects recent movements of contributors' perception of the company, brand, products, competitors or whole market. as one of the approaches to achieve a better view we propose to design metrics which should be followed in order to get valuable insight where the company stands in terms of its customers. this paper focuses on obtaining an e-word-of-mouth in the banking sector using publicly available data. the main goal is to design metrics and dashboards evaluating customers’ perception of a bank’s services based on the analysis of public facebook sites and web discussions related to several banks in the czech republic. we studied several approaches to unstructured data analysis. thus we present complementary findings in classification of the unstructured data analysis presentation as a set of summarised metadata, top peaks of primary qualitative data and results of automated semantic analysis of the unstructured data. based on the result we discuss the possible value of an unstructured data analysis and related systems. we find out that the value could be in the identification of opportunities and threats in the market by unexpected movements in public opinion of the internet crowd, which we suggest to explore in future research. the benefit of this report is to describe the processing of data that can be obtained with emphasis on their content, their further enrichment, and their users. keywords: marketing, business intelligence, e-word-of-mouth, elasticsearch, banking, unstructured data, internet discussion, facebook available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 2 (2015) 36-47 mailto:lucie.sperkova@vse.cz mailto:petr.skola@vse.cz https://ojs.hh.se/ 37 1. introduction the phenomenon that people talk and recommend their favorite products and services to their friends and followers plays an important role in shaping their behavior (goyyette et al. 2010). deeper understanding of these talks may be crucial in creating a successful marketing strategy in online communities. the most common method for monitoring these data is now online monitoring. but there are another data from different sources as internal and external databases, crm, erp, etc. in data warehouses of the companies which could be put into context with the data from online communities. in marketing field these talks of customers are known as customer voice or word-of-mouth (wom). the unstructured data gained from the internet is also known as digital (hu et al. 2006), electronic (ewom) (choi and scott 2012) or online word-of-mouth (wu and zheng 2012). the most developed definition of the ewom which captures present and future development of communication more complexly is stated by bronner and de hoog (2010) : “any statement – positive, negative or neutral – made by potential, current or former stakeholders about a product, service, company or person, which is made available to a multitude of people, organisations or institutions, via a digitally networked platform.” potential of ewom data can be used to obtain information to a broader audience as companies, professionals, and retrospectively users themselves. any consumer in the world can connect to the internet and read the opinions of others. the emergence of various social media like blogs, microblogs, social networks, forums, online reviews etc. is an important step for customer voice research. users share there their personal experience with the companies, products and services and those are then followed by their transfer to other users. simultaneously these sources create opportunity for companies to be visible and convince customers by communication on the quality of its services. dellacoras et al. (2007) noted that the practice of reviewing products online significantly increases the potential for an empirical understanding of ewom marketing. breazeale (2009) states that digital platform is changing our understanding and the essence of the ewom meaning. while the articulated evaluation disappears shortly after they were spoken, and it is very difficult to capture and analyze it, online statement lingers long after it was written and is not necessarily spontaneous. it is also immediate and accessible by others. similar to classic wom research shown that in internet environment ewom may have “higher credibility, empathy and relevance to customers than marketer-created sources of information on the web” as stated gruen et al. (2006, p. 449). the importance of wom in shaping consumers’ attitudes and buying decisions led many researchers to examine its effectiveness in stimulating demand within various industries. there are researches including wom influence on the buying decision and sales (e.g. senecal and nantel 2004; tsang and prendergast 2009; chevalier and mayzlin 2003), quality control (ashton et al., 2014) or user and service experience (hedegaard and simonsen 2013; pai et al. 2012). there are studies investigating ewom in social networks (wu and zheng 2012) and estimating the social influence of individual nodes in social networks (lü et al. 2011). choi and scott (2012) focus on the relationship between the use of social networking, user social capital, sharing knowledge and ewom. the result shows that the intensity of use of the networks linked with confidence and identification, which has a positive impact on knowledge sharing. study conducted by almossawi (2015) proved that “wom has a positive influence on the youth’s decision-making process when choosing where to open a bank account”. this result can also lead to the importance of the customer segmentation according to their characteristics and preferences which they share on social networks and the data the banks has in their data warehouse. banks can thus connect the characteristics from the social profile with the customer’s behaviour. banking services are one of the industry where analysis of wom can be crucial to stay competitive in the financial market. the potential is in identification what clients attracts, how the trends in banking look like, what is necessary to improve in services and also in what is necessary to help the clients and how to communicate with them in the space of social networks. lack of confidence in the banking services might also be the result of an increase in perceived risk, which can reduce customers’ willingness to use banking services (aurier and siadou-martin 2007). wom can be a competitive advantage through banks can increase acquisition of prospects and retention of customers. the study of shirsaver et al. (2012) found that the major determinant factors of positive wom are corporate image, relationship marketing, perceived value, perceived risk, satisfaction, and loyalty. there are also studies which put in context wom, service quality and customer satisfaction of the banking services (e.g. yavas et al. 2004; lymperopoulos and chaniotakis 2008). wom affects individuals’ decisions and influences organizations’ operations. it has very important implications for a wide range of management activities, such as:  building brand and reputation,  increasing conversions, i.e. sales transactions,  acquiring and retaining customers,  product development,  quality assurance. also business managers start to pay attention to social networks communication and new type of business intelligence is emerging (chen 2010). in business process management bringing together the 38 worlds of structured and unstructured data can add significant value to the enterprise. it can help to find the priority clients, problems relating to products and services, customer sentiment, find the next best step in business, identify activities of the competitors and customers, their reactions, etc. tremendous strides were made in recent years to automate the analysis of unstructured text data. the problem of semantic analyses is that their results should be quantifiable. complexities in the analysis of unstructured textual data often results in only minimal use of the data (ashton et al. 2014). so it is necessary to find a way how to generate outputs consumable to service providers. we are convinced that due to established culture, knowledge and technologies in companies the new methods has to adapt as much as possible to end users. according to adamala and cidrin (2011) the business intelligence solution must be built with end users in mind, as they need to use it. 2. motivation of the research today data warehouses of banks contain mostly structured data as an asset they can easily measure. business intelligence (bi) is primarily directed to the presentation and analysis of numerical business data. reporting systems, commonly based on dashboards, prepare quantitative data based on metrics in a report-oriented format that might include numbers, charts, or business graphics (kemper et al. 2004). according to kimball (2010) the metrics from the point of bi view are expressed on the basis of dimensional modelling as indicators and their characteristics, analytical dimension and their characteristics and the relationship between dimensions and indicators. cobit 5 emphasizes the importance of business metrics. metric is meant as degree, the extent to which company management is satisfied with the contribution of it to meet business strategy. dashboards are applications that allow to organize pre-selected key performance indicators (metrics) in a clear and intuitive graphical form (pour et al. 2012). at dashboard metrics can be viewed from many dimensions, for immediate use in decision-making processes in the organization. for business users dashboards bring the visibility and clarity of all monitored metrics and their instant overview of improving or deteriorating. thus users can immediately assess the plan or reality and save their time. management of unstructured data determines how efficiently the company will deal with their customers in the future. the danger threatens from the ignorance of unstructured data can be sorted from dissatisfied customers, very loud customers, rapidly rising costs for customer service and their departure to breaching trust in the organization, the customer knows more than its employees. the new approach allows companies to consolidate unstructured data to central data warehouse is able to communicate consistently through all channels. the customer then feels that company knows him when he communicates with his counterpart, whether it's agent or vendor, or attends a customer portal. also customer service operations at the same time can reduce costs while maintaining customer satisfaction. integration of unstructured and structured data were discussed on presentation level (e.g. becker et al 2002) where structured data are accompanied with relevant texts. the structured data selected as a results of metrics viewed from different dimensions and relevant documents are presented side-by-side. another integration exits on the level of extracting metadata from collections of unstructured data (e.g. keith et al 2005; sukumaran and sureka 2006). identifiers of the content items are treated as facts that are subject to analysis, whereas metadata fields (e.g., author, date of creation, length, and addressed product) are used for classification purposes and thereby act as analysis dimensions. this allows associate individual documents with numerical facts directly, based on shared dimensions and to investigate document frequencies, e.g., the number of documents that cover a certain topic and are connected to certain segment of customers. an integrated framework of business intelligence with the inclusion of unstructured data was constructed by (baars and kamper 2008), but they focus more on classic enterprise data and data from crm. they do not include ewom as a possible source of data to bi process. we are convinced, that ewom is specific source of data which has to be handled in specific way. our intention is also unique with its focus to banking domain, which has specific requirements to business. this paper follows results and expands article of (šperková 2014) and (šperková and škola 2015), where the first content analysis of banking data were conducted. our purpose is automation of the process of gaining the data and their pre-processing for further analysis. automation can reduce cost and timeconsuming, manual and comprehensive analysis conducted by people like reading posts and search links in them. it is not able to capture the full transfer of expertise that customers write anywhere on the internet. but at least in monitored publicly available sources can be analysed topics that interested users. furthermore, these themes can automatically evaluate categories of sentiment and thereby obtain the distribution of subjects with positive or negative customer experience. there are many studies conducted to mine the sentiment and opinion from the wom and using the computer aided methods like latent semantic analysis (ashton 2014) or machine learning classification (pai et al. 2012). these methods are well known but are uneasily to implement in service practice. for this purpose, the powerful tool elasticsearch seems to be adequate. there are only a few academic articles, which use elasticsearch in their research. these articles are focused on library science (johnson 2013) and full-text searching (divya and goyal 2013) or big log data (bai 2013). textual data analysis was the part of theses 39 elaborated at the department of information technologies at the university of economics in prague this year. these thesis uses unstructured data as the input and elasticsearch as a tool for data analysis. methodology used in those thesis are wellconceived and executed but lacks business context. the nature of unstructured data in contrast with structured data usually presented in bi solutions is different and its meaningful presentation may differ from usual bi dashboards. we discuss the possibility of measurement and dashboard presentation relevant to the nature of the data and its business importance. 3. objective and methodology the main objective of this research is to create a periodic review of the data evaluating banks according to the context in which their users speak about them on the internet. our approach is built on the methods used in bi and knowledge from unstructured data processing in bi. the insight will be given based on metrics which have to be defined on the base of facebook and web comments. after processing of information from those comments, metrics are counted and visualized on dashboards. the results is an overview of the sentiment of the talks about the bank in specific period and its position in monitored metrics compared to other banks in the market. the research is conducted as a case study and proof of concept which will be followed by other studies and anchored in a methodology. our approach is conducted according to established business intelligence process (kimball 2010) and data mining, eventually text mining methodology, specifically according to crisp-dm (chapman 2000) as the main aim of this integration is effective customer retention management. the lifecycle of the crisp-dm contains 6 steps – business understanding, data understanding, data preparation, modelling, evaluation and deployment. compliance with these procedures we outlined basic methodology of the research as follows: 1. identification of the web pages and social network sites where regular information from customers and users of banking services can be obtained – business and data understanding 2. creating a system that will ensure downloading of the necessary data from the internet and storing them in repository – data preparation 3. processing and data analysis – data preparation and modelling 4. design of metrics and characteristics, which evaluate the bank from the customers’ point of view – modelling and evaluation 5. design of the dashboard for the visualising the metrics and more detailed information – evaluation and deployment result of this paper is a dashboard which serves to further actions which should lead to better decision making and increasing performance. figure 2 shows a general model of the decision making process from the unstructured data used at this research. the findings will provide important insights into the business impact of social media and user-generated content an emerging problem in business intelligence research. further this model can be easily integrated to the traditional, on structured data based, bi process. figure 1: model of the decision making process from unstructured data (authors) 3. data collection and processing from the marketing research point of view, east (2007) claims that it is not difficult to find the data on the internet, but the problem may occur, if the data are only from one source/server. the ewom may be affected and rather be negative or positive. for this reason, we apply more than one data source. for the purposes of analysis and design of the metrics we chose comments that relate to banking occurring on the czech website or facebook profiles of czech banks. five czech banks with the largest balance sheet total in 2012 and with the facebook profile are shown in table 1. 40 table 1: chosen banks with facebook profile entering the analysis (authors) name of the bank facebook profile ceska sporitelna ceskasporitelna komercni banka komercni.banka unicredit bank czech republic unicreditbankcz raiffeisenbank raiffeisenbankcz ge money bank gemoney.cz pages that a web discussions are downloaded from must meet several requirements. pages must relate to the topic of finances and banks to put assume a high proportion of the discussions that deal with banking services. further discussions must have wellstructured and tagged html code, so they can be easily identified in the whole html page script. from the web sources we chose czech financial forums http://www.mesec.cz/ and http://www.penize.cz/. 4.1 connectors for downloading the data from the internet forums we programmed a web crawlers for automatic browsing website content by using java language and open source crawler4j library under the apache licence v2. in crawler4j we set up rules which domain to browse and optionally specified rules for browsing urls that were interesting in their content. a list of text strings in the url which should not be contained at pages was also defined for more efficient browsing. this crawler received information which parts of the site not to attend because they contain no user comments. parts of the html code, containing identification of the contributor, text (comment), date of the comment and eventually the number of reviews of the comment by other users, were separated and prepared for further processing. for acquisition of data from facebook we used java library restfb which contains classes for working with facebook objects. to login we used credentials (assigned app id together with access token) for the application created below the private facebook profile. the advantage of this log is access the data without the need to renew the validity of credentials. the objects of downloading from facebook are posts on the wall of czech banks and the data about the facebook page which are downloaded from. post can be represented by text, picture, link etc. every post can contain comments from other users. the download these objects are accomplished by withdrawing feed objects first. for each object is determined whether contains a comment. if so, this comment is downloaded. comments on facebook are in two layers. for each comment, users can respond by sub-comments, these are downloaded as well. for each object type post is also necessary to determine the number of likes a positive evaluation of the object. 4.2 repository as a repository and analysis tool of gained data we used open source elasticsearch software based on apache lucene library. elasticsearch is a distributed scalable system for real-time search and analysis tool whose main function is the full-text search. it also supports structured search, geolocation and recording the relationships between data. in elasticsearch, the data from all sources are collectively analysed. the data from both connectors are stored to elasticsearch in json format. every document contain unique identification under it is stored. this id enables to start connectors over again each day because elasticsearch saves one document under one id. downloaded data were enriched by other two java programs, which connected sentiment analysis and evaluation of named entities contained in posts. elasticsearch provides built-in support for analysis in the czech language. outputs from elasticsearch were then processed and visualized in kibana application. plugin head for simplification of indexes (data file) and application carrot2 for clustering documents were also used. 4.3 sentiment analysis sentiment analysis were conducted by open source opennlp library which is used for programming the various tasks of natural language processing like detection of sentences, tokenization, document categorization etc. evaluation of sentiment contributions are made through opennlp document categorizer based on the principle of maximum entropy. for the training of the categorization model we used data from the university of west bohemia as an output of sentiment analysis of data from the czech facebook sites and reviews from the czechoslovak film database web using machine learning with a teacher. 5. wom information extract before the design of metrics we explore which type of information could be extracted from the unstructured ewom data. the successful bi initiatives, as shown in (adamala and cidrin 2011) share factors like orientation on choosing best opportunities (“low hanging fruit”) or alignment to specific needs of business sponsor. in our case the generic best opportunity could be found in fast, easy and simple understanding of movements in public opinion related to the company and its competitors. the business vision or specification of unstructured data analysis is difficult due the fact that the content of the data is not known in advance. thus, the dashboard can be designed mostly by:  summarised ewom metadata,  top peaks of ewom primary data,  automated semantic analysis of ewom data. 41 the metadata such as source, type or time of the contribution enables easy summarising and graphical representation. these data are easily integrable to current bi environments. the reason of these data in ewom analysis is to understand time, typological and quantitative differences, and recent and past movements in ewom data. the metadata are source for identification of top peaks in primary data such as topics with the highest absolute or incremental rate of appearance or the persons with the high influence. these primary data should be shown to the dashboard user as a primary, non-summarised content, because it entails the semantics not easily evaluable by computer. for example, when rate of appearance of terms such as “availability”, “outage” or “failure” grows in conjunction with a competitor, it could be valuable information about technical conditions of competitor’s e-banking system. also topics widely discussed about the company, e.g. social network campaigns started by unsatisfied customers, can be intercepted in its beginning. the automated semantic analysis is represented mainly by sentiment analysis, ie. identification whether the contribution is neutral, positive or negative. the output to dashboard can be the quantity of the customer’s statements of different sentiment to measure the mood of the internet public opinion or direct indication of sentiment of the top peak contributions. the example of a reason for semantic analysis could be an early cognition of negative or positive mood movements in the crowd after controversial marketing campaigns, thus is possible to avoid or intensify them. 6. metrics design the main purpose of metrics is to highlight the important facts that corporate resources or people need to be focused. metrics summarize various aspects of the data in aggregate form and are comparable among the surveyed companies. from downloaded and indexed data is necessary to draw metrics and other characteristics evaluating banks from the customers’ perspective. if the characteristics are of the quantitative type they are defined in proposed metrics in table 2. nominal characteristics are understood as dimension according them the metrics as measurable indicators can be calculated and sliced. metrics along with dimension form the value for gaining the ewom from the data. the highest value have dimensions created from textual analysis. some results of metrics can be further used as dimensions to slice other metrics. for example one metric can be the calculating sentiment of different comments. further this result can be used to slice metric most active contributors and show only those with negative sentiment. to better understand the content of posts and comments, the list of keywords has to be designed for better search of contributions according to user requirements. this is a domain knowledge of every enterprise which wants to use our procedure. this list can be always updated. keywords are attributes for different dimensions. considered dimensions in our case are:  time period (e.g. month, week, day, date)  source of the data (facebook, web forum)  type of the contributor (facebook user, bank, follower, user (cookie))  type of the page (individual facebook page, individual forum page)  type of the contribution (comment, post)  name of the bank (keywords)  name of the product (keywords)  specific  generic  sentiment (positive, negative, neutral)  topic table 2: definition of designed metrics (authors) name of the metric definition calculation unit of measure number of likes indicates people who liked the page/post/comment, shows the popularity of the bank on facebook summary of individual likes like number of posts shows the activity of the bank and its followers or other facebook users, indicates how many objects of the type post are on the wall summary of individual posts post number of comments indicates how many objects of the type comment are on the wall/under the post summary of individual comments comment 42 the ratio of the number of comments that contain the name of the bank or the product to all comments evaluates how important it is to monitor the website and its discussion number of comments containing the specific topic / all comments % frequency of the topics/keywords summarizes themes, a common signs of comments that occur most frequently summary of topics/keywords topic/keyword incidence rate of topics together with keywords indicates topics occurring together with the keyword number of pairs of specific topic and the keyword/ number of occurrences of the keyword % sentiment of the topic/contribution count the overall sentiment of the topic or contribution. serves for example for comparison between banks. (number of positive – number of negative contributions) / number of all contributions sentiment most active contributors users contributing the most – potential opinion makers summary of contributors contributor net promoter score evaluates measure of customer loyalty % of loyal customers – % of disloyal customers nps reach summary of users who were reached by the post/comment summary of users who read the post/comment (number of impressions) user/cookie 6. dashboards design designed metrics need to be placed to the dashboard. in our case the dashboard is realized in an application kibana. dashboard overview shows defined metrics and contains a set of visualizations that correspond to the quantitative questions about the stored data. topic analysis dashboard shows topics or words that frequently occurred, or may be potentially interesting. it is designed to gain insight on the topics discussed in the context of the stored data. dashboards are used for analysis of indexed data and are preparing for the final visualization. 43 figure 3: preview of the overview dashboard (authors) figure 4: preview of the topic analysis dashboard (authors) data can be viewed from different angles, search allows querying specific subsets of data. data which contain the specific shapes of searched word or phrase are then displayed. all objects defined in table 5 and placed to dashboards also serve as filters that allow view data according to user interest. for 44 example, finding where there are many negative posts, which source caused a blip in the number of contributions etc. another option is to enter a query into the search and thus, for example, determine whether the messages contained some of the key words or how often a name of the bank occurs. issues which were of interest of commenting can occur in several ways with objects frequent terms and top unusual terms and a frequency of posts in the course of time. table 3: defined objects placed in dashboards (authors) object description note activity development of the number of posts in time filter allows to limit data, e.g. to period of high activity of users page names of the pages and number of documents filter by clicking on the name and change the sort by number of documents source number of documents from different sources filtering by sources type number of documents saved in single type of bank index filtering by the type of sources page likes development of the number of facebook likes in time popularity of sites can be compared between themselves comments count number of comments on individual pages filtering by contributors posts count number of posts on individual pages filtering by contributors sentiment summary of the sentiment evaluation sentiment is flow number from -1 to 1 user activity most active users users with the highest number of comment or posts frequent terms most frequent words contained in posts and comments identification of themes related to the contribution. it shows the word in the form after stemming rules and frequency of occurrence. top unusual terms terms that are statistically unusual terms which occur more frequently than they according to statistical model by other data should. it highlights the novelties in selected data 7. further findings and implications of the study the results of reporting design may serve as indicator of the marketing department for the evaluation of bank in relation to others in the market, as a feedback for new product introduction, overview of the competition or the discovery of the customer wishes. it indicates what bank is customer friendly and what bank and issues people talk about. longerterm monitoring of metrics can therefore tell where to apply banking products. from a managerial perspective, our results suggest that firms should pay attention to textual content information when managing social media and, more importantly, focus on the right measures. therefore we also suggest closer cooperation of the people taking care of the social sites like facebook and bi analysts. this approach could lead to higher customer satisfaction and growth of agility, profitability and orientation to the customers. though we consider the metrics and the dashboard design itself as a main result of our study, we are able to extract a typology of a possible information value and thus present a distinctive business value which could be requested from similar cases. we can also discuss the consideration of overall business value of unstructured data-based intelligence systems. 45 the following unstructured data value typology is made by observation of the data presented on the designed dashboards. deployment of this typology to action in several situations is a base for future research. we suggest to perform a qualitative study by a sample of power users over the analysed data to authenticate the acceptance of the typology. • content / quantity • primary qualitative data / metadata • dynamics: static (absolute) / dynamic (change) • predictability: expected / surprising • object of business information value: market / competition / customer / product / brand • business impact quality: threat / opportunity • source of information: single / nests / distributed we are able to find value even in the primary information itself, such as in the content of public contributions, or in the amount of the contributions or similar quantitative values. while the static data representing the absolute value are predictible, dynamic information representing changes such as topics or words with the highest change rate of appearance creates unexpected value. that leads to further exploration of reasons and origins of the information. such origin sometimes lead to one source, sometimes to a/the competitor’s campaign, sometimes to a single internet personality with extended influence. such an influencer could be a possible partner in public communication. the overall business value of the unstructured data analysis is a sum of all of the expected business value described above. this makes similar systems very difficult to evaluate and to calculate a business case. a lot of value could be found in the area of unexpected, surprising information. it can create a big opportunity or prevent an extensive threat. such value cannot be calculated in a simple business case, because it is impossible to set probability of a rise of such surprising information from the ewom. then the value and roi of unstructured data intelligence systems could be considered similarly as in business continuity management approach; as the avoiding the possible business impact of not having the information, eg. in our case, as possible business impact of ignorance of the internet public opinion. conclusion the purpose of the research was to design a comprehensive overview of customers’ ewom based on web forums and facebook comments. after a study of the approaches to unstructured data analysis and wom analysis, we discussed the nature of the unstructured data analysis and possibilities of its dashboard presentation. we defined quantitative metrics evaluating individual aspects of customers‘ perception of the bank, dimensions and the way they can be displayed on the consolidated dashboards. we chose the czech banking industry and facebook pages and relevant websites with extensive discussions. the results were designed with respect to a possible future integration of the ewom to business intelligence process and data structures in banks. the advantage of our approach is its extensibility. connectors can be added for new sources of data; new metrics can be defined and incorporated to the dashboard. this approach can be also used besides banking in other enterprises. the main outcome is the design of the metrics and the dashboards over the analysed public banking market data. the main findings are the way of the unstructured data analysis presentation as a set of summarised metadata, top peaks of primary qualitative data and results of automated semantic analysis of the unstructured data especially the sentiment analysis, designed in the specific banking data dashboard. furthermore, we discussed, generalised and classified the possible value of unstructured data analysis and related systems. we found out that the value could be in the identification of opportunities and threats within the market by unexpected movements in the public opinion in the internet crowd, which we suggest to explore in future research. in the case of positive results of the typology validation, the future research could contain automatic classification of the data to identify the type of business value of information presented on the dashboard and thus transfer more intelligence from humans to automated unstructured data processing. 8. acknowledgements this article was prepared with the financial support of the research project vse igs f4/18/2014 and with contribution of long term institutional support of 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(2015) intelligence as a discipline, not just a practise. journal of intelligence studies in business. vol 5, no 3. pages 47-56. article url: https://ojs.hh.se/index.php/jisib/article/view/137 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index intelligence as a discipline, not just a practice magnus hoppea aschool of business, society and engineering, malardalen university, sweden; magnus.hoppe@mdh.se journal of intelligence studies in business please scroll down for article intelligence as a discipline, not just a practice magnus hoppe school of business, society and engineering, mälardalen university, sweden; magnus.hoppe@mdh.se received 27 august 2011; reviewed october 2015; accepted 5 december 2015 abstract this paper is a call for a new research agenda for the topic of intelligence studies as a scientific discipline counterbalancing the present domination of research in the art of intelligence or intelligence as a practice. i argue that there is a need to move away from a narrow perspective on practice to pursue a broader understanding of intelligence as an organizational discipline with all of its complexities where the subject is seen as more critical and is allowed to reflect on itself as a topic. this path will help intelligence academics connect to theoretical developments gained elsewhere and move forward, towards establishing more of an intelligence science. the article is critical of what the author sees as a constructionist line of thinking. instead the author presents a theory of intelligence as learning how to “muddle through” influenced more by organizational theory. the author also argues for an independent scientific journal in intelligence. [editor’s note: this article was originally presented in 2009, before the appearance of jisib.] keywords ideal informative flow, ideal organizational thinking, intelligence academics, intelligence scholars, intelligence science, organized intelligence 1. introduction in this paper i’m discussing two different perspectives on intelligence research: intelligence as a discipline (1) and intelligence as an art (2), where i argue that both are needed, but that research on intelligence as a discipline is underdeveloped. the current focus on the art has created a strong insider perspective that limits our understanding of what the intelligence domain contains, does and means to organizations. in accordance with this reasoning i start by suggesting a more critical stance towards the intelligence cycle (ic), the most used model for explaining intelligence as an example illustrating what is lacking with the arts perspective. ic has clear deficits as it supports a false belief that an ideal informative flow not only can be created but is of importance to organizations. the false belief that results from this thinking leaves us with an array of intelligence challenges unaccounted for when theory does not fit with reality. the continuous use of the ic is puzzling, but can be explained by its conceptual values (it's easy-to-use and understand) and that it works as a symbol bringing legitimacy both to those organizations implementing formal intelligence activities and to intelligence professionals who aim to manage this idealized informative flow. i argue that there will never be a true science of intelligence until the field opens up to other research questions and traditions other than those currently in favor. several initiatives can support this development, where i hope for the development of arenas that will allow for more dialogue on the topic of intelligence to prosper. we need to find and agree upon a term depicting our new perspective for the study, free from the narrow focus in use. my suggestion is organized journal of intelligence studies in business vol. 5, no. 3 (2015) pp. 47-56 open access: freely available at: https://ojs.hh.se/ 48 intelligence work. researchers adhering to this call will strengthen their positions as intelligence academics, counter-balancing the present domination by intelligence scholars. in addition, i argue that we must accept different and complimentary perspectives on the discipline of organized intelligence work. instead of just supporting formal decision making through an informative flow apparent in the ic, it's possible to view organized intelligence as a discipline for supporting ideal organizational thinking, thus helping to improve the competiveness of the organization (cf. hoppe, 2013a). viewing intelligence in different ways will enable researchers to move beyond the focus on a limited number of models, where the ic is a good example. 2. research as we know it when discussing intelligence research, one often comes to the conclusion that the present status is everything but satisfying. solberg søilen [2005:16] however writes, "the study of private and public intelligence has barely started as a positive area of research, 'a science' probably being too big a word." many researchers claim that there's lot to be done. there are often arguments for more systematic research [e.g. ganesh, miree and prescott 2003; svensson kling 1998], more quantitative studies [e.g. calof 2006], or just better research [e.g. fleisher, wright and tindale 2007]. however, there are fewer suggestions as to what this new and better research may be. some research areas are also neglected. in the call for papers to this conference – the third european competitive intelligence symposium (ecis) in stockholm 2009 – one could read "there has been a tendency to focus on the larger enterprise such as multinationals, with less attention being paid to business development and business creation, or entrepreneurship." to this, non-profit organizations and ngos could be added as well. according to these examples, it seems apparent that there's a need for more (and better) research. but to me, this picture of an immature field of research is not acceptable. the most prominent problem is, in my judgment, that the current research paradigm has limited itself to the art of competitive intelligence and is constructed too close to practice. the effect is a prevailing emphasis on practice – how to do and organize intelligence – and insufficiently on the creation of organizational theories including what intelligence means and does in organizations. and this is not to mention societal effects due to the continuous expansion of organized intelligence activities. the current research tradition creates results with only limited value to those researchers and laymen who are not familiar with the subject of intelligence. it neglects the larger issues. one might argue that we have at least over the years developed a deep understanding of how we ought to do intelligence, but i'm not that sure that this is true. even though current research is focused on how-to-do-intelligence, too often presented studies fall back on definitions of the art that are not solidly grounded in science. instead the study remains too much of a management practice unconcerned with its internal logic as long as it sells consultant hours. the abyss of the problem is apparent when, for example, jonathan calof [2006:11-12], summarizing an academic track on a scip conference, stated that there is a need to investigate what intelligence managers actually do and that "it's been suggested that the [intelligence] model may be prescriptive, not descriptive." to me this is not only a suggestion but a fact, and in that perspective calof’s statement can be read in the sense that most research up to 2006 (at least) is based on questionable prescriptive models followed by other ungrounded assumptions of what intelligence managers actually do. it is not built on unprejudiced empirical studies of what is actually being done. 3. what support and what decisions? but, as some might argue, there are theories about what intelligence does to organizations; it supports the decision-making processes inside the organization. even though i agree to some extent with this description, i'd like to pose two questions: is this all that intelligence does to organizations and does it really support all kinds of decisions? these questions are of course rhetorical, but still important as they question the normal way of defining intelligence. intelligence and those creating it do a lot of other things in and with organizations, but current descriptions of intelligence as decision support tend to limit the intelligence subject to more formal decision-making, leaving all other kinds of organizational perspectives unaccounted for. 49 from this brief overview we can derive a possible explanation as to why intelligence appears to be prescriptive instead of descriptive, and why this creates problems for researchers. as long as we chose to describe intelligence in the context of formal decisionmaking, intelligence will be nothing less than the logic and deductive result derived from an idea that organizations are the result of formal decisions. intelligence will, in this perspective, be explained as the process that makes formal decision possible, feeding correct information to the decision-makers in order for rational choice to be a correct assumption. theories come before empirical data, which in consequence allow for a poor fit with reality. as a consequence, we will only be able to study those aspects that theory permits us to study, and at the same time we will be blind to aspects that are not accounted for in the theories guiding our understanding. this deductive way of reasoning favors those aspects that are apparent in the intelligence cycle, the model that comes with favored theories. this will not give a viable account of reality, which is where most research is conducted and why it will also give researchers problems in handling data that do not comply with guiding theories. for those who still like to limit the field of intelligence to this restricted view on knowledge, the value of formal decisionmaking has long been discussed and questioned, since the rise of empirically based decision making theories in the late 1950s. lindblom’s article the science of muddling through [1959] and march and olsens garbage can theory [1979] are just starting points for a discussion of how organizational decisions are really made. we could also add simon’s extensive work on bounded rationality [1945, 1982, 1991] that leaves all humans with just one option: to seek satisfying decisions instead of ideal decisions. what these theories are saying is that rational decisions can't be made. they are ideals resting on obsolete perspectives on organizations that surfaced about a hundred years ago with weber, fayol and taylor. the only places where we find them are in our dreams, and in textbooks on strategy, mintzberg, ahlstrand and lampel [1998] would add. to resolve this troublesome situation we'd better accept the limitations of formal decisionmaking [see e.g. brunsson 2002; mintzberg 1973; mintzberg et al. 1998], but also accept that most decisions inside organizations are of other types, as lord and maher [1991] argue. besides this, by focusing on decisions we will not fully understand what other organizational activities are in need of intelligence, and how they are related to one another (see hoppe, 2013b, for an example of how scouting is related to intrapreneurship). of course there are still formal decisions, and they do count. but, according to my research based on interviews with different intelligence professionals and their clients for my phd, the big formal and strategic decisions are exceptions to the rule. what my research has brought to light is that the art of intelligence, just like the art of management, is the art (not science) of “muddling through”. it's focused on the everyday troubles of the intelligence clients, where the intelligence staff struggles to make their clients take more contextual aspects into account in their work, instead of relying on their present limited understanding of things. it's also a much more symbiotic relationship where information not only is retrieved, analyzed and disseminated. instead, information is shared in a two-way game, and analysis is created within conversations expanding beyond the formal intelligence discipline. as an example, one of my informants let the analysis evolve by letting it pass through different discussions where each discussion added different perspectives to the analysis but also helped to decide what the next step would be and who else to involve. at the same time, those involved shared their information and ideas (aka knowledge) of the subject at hand, and in this manner created a common and actionable understanding of aspects important for the organization. 4. an ideal way of organizational thinking judging by my empirical data, a complimentary view of what intelligence professionals actually do is to say that they are supporting an ideal organizational way of thinking. this is a thought that will contribute to the well-being of the organization, which can be defined in three dimensions: • think beyond what’s happening right now. expand your reasoning into possible future developments. • think beyond those aspects closest at hand and the actors and organizations that are directly affected by each issue. expand your reasoning to aspects, 50 actors and organizations that are indirectly affected. • think beyond your own and your organization’s interests. judge the situation from several perspectives and chose the path that's the best for your organization, not for you. through their actions, products and tools, the intelligence professionals i studied aim at making people expand their reasoning in these three dimensions: beyond their own bounded position in time, room and interests. but it's also about making their clients aware of their shortcomings, to never be satisfied with their present understanding of things and taking action to do something about it. the products – the artifacts of intelligence – are just tools to accomplish this changed reasoning. just because intelligence artifacts exist doesn't mean that they have a real value as ends in and of themselves. they are means, not ends. regretfully, we are likely to view them as ends if we rely on models like the ic for describing intelligence (as many do, according to ganesh et al. [2003] and treverton [2004]). relying on the ic, it's quite easy to argue that the effectiveness of intelligence can be found in its material output (reports, dissemination), as the cycle defines intelligence as a production process. it's a seductive stance that invites us to think intelligence can be easily described, controlled and measured. as this view rests on an assumption of disciplinal rationality and control, one might also claim that intelligence professionals set to work in this process are neutral, putting together objective intelligence for the outspoken need of others. but once again, these are ideas that crumble in contact with reality. all people who deal with information are limited to their own bounded abilities to search, value and analyze information [simon 1945, 1982, 1991]. but that's not all, where jeffrey pfeffer [1992] writes: "our belief that there is a right answer to most situations and that this answer can be uncovered by analysis and illuminated with more information means that those in control of the facts and the analysis can exercise substantial influence. and facts are seldom so clear cut, so unambiguous, as we might think. the manipulation and presentation of facts and analysis are often critical elements of a strategy to exercise power effectively.” [247248] this is a troublesome statement for those who believe that intelligence professionals serve decision-makers with non-biased information and analysis [e.g. furustig and sjöstedt 2000; murphy 2005]. but if we instead chose to see intelligence professionals as organizational agents for an ideal organizational thinking then this problem ceases. according to this perspective, intelligence professionals are aiming to influence and exercise power. they are trying to manipulate the information to make their clients change their thinking, reaching beyond their present understanding of things. my informants engage in war games and workshops. these two examples can be viewed as the most effective tools to reach the main objectives of intelligence: to help people think and act better to make better decisions. this is the true mission of intelligence work, not the production of intelligence artifacts. viewing intelligence as something that goes beyond the material output and the clear-cut boundaries of the intelligence discipline will open up unexplored dimensions of intelligence. these dimensions will add to our understanding of what intelligence managers exactly do (to comment on calof’s statement above) and what intelligence does to organizations. these dimensions have no definite end, and intelligence will accordingly never be fully explored, not to say easily defined and measured. 5. “intelligence is bubbling” this calls for another note of caution as most writers in the field of intelligence indirectly suppose that the art of intelligence is restricted to those who have it in their job descriptions. this is not at all true, as i argue above. but i'm far from the first to notice this. john prescott wrote this 20 years ago [prescott and smith 1989], but it has also been touched on in later studies [e.g. gibbons and prescott 1996]. this is done even more explicitly so in sven hamrefors [1999], who forcefully argues that all people inside an organization seek the meaning in their specific situation, creating their own intelligence if no one else helps them with it. unfortunately, these studies are more or less neglected by researchers. what this research tells us is that intelligence is created everywhere. "it bubbles," as one of my informants put it, continuing to explain that it was her job to support this bubbling intelligence. and this is not a small remark at 51 the side of the page. what this tells us is that we can't restrict the intelligence subject just to those who have it in their job descriptions. all employees work to improve their information sets. all employees are thus working with intelligence. this is the true face of intelligence work, not formalized business intelligence teams, etc. furthermore, it also tells us that at least some intelligence professionals right now strive to support the creation of useful intelligence wherever it might surface. stating this, it becomes apparent that we no longer can limit the creation of intelligence to some specific formal unit and the use of intelligence to some other formal place. if we do, we risk adjusting empirical data so it will fit with our theories, or we sell consultancy ideas that will never be implemented because organizational life is never this way. to raise the stakes, i'll argue from my observations that for most organizations, informally constructed intelligence is much more important than formal intelligence [see also gibbons and prescott 1996]. this is mainly because informally constructed intelligence is created closer to the user, those who are supposed to act on it. acting is much more dependent on what we feel and think and not on so-called impartial information, especially when it comes in writing [brunsson 2002]. with reference to hamrefors [1999], it can also be argued that informal intelligence activities always precede formal intelligence. therefore, it's not surprising that most of my informants actively seek to involve their clients in the analytical processes of intelligence. remember, the intelligence processes and artifacts are just tools to support and strive for ideal organizational thinking. to make the organization’s members do intelligence, and do it better, is inside the normal definition of the job. the intelligence i'm describing is the intelligence carried out in live organizations, not theoretical organizations. the live situation is what real intelligence professionals adapt to. they do not adapt to artificially prescriptive ideas of how intelligence is supposed to work, according to dominating theories on intelligence. furthermore, intelligence is in its adaption a much more emergent task than planned. my informants are pretty much left to themselves to create results that make a difference [see also treverton 2004, 106]. to view them as simply answering the commands and whims of formal decision makers does not do them or their profession justice. this is actually also one of benjamin gilad’s [2008] main points when he spurs the new intelligence professionals to go for the fun. 6. the importance of water but how does this agree with the normal way of describing intelligence? can intelligence still be regarded as restricted to intelligence managers preparing analytical support for formal decision-making? with this question comes a choice. it's quite possible to answer "yes," but with this yes comes an obligation to clearly state that the knowledge searched and gained is only viable within a restricted part of a wider field of research. those who pursue this path cannot, at the same time, state that they cover the whole intelligence field. those who make this choice will also be of little help building an intelligence science, covering other aspects and perspective on intelligence that their outspoken position will restrict them from acknowledging. as i've argued that a more becoming answer is "no," as this will allow us to explore intelligence more candidly. unfortunately, there are many writers and researchers who don't agree with me, where the most outspoken of which seems to be benjamin gilad [e.g. 1988, 1996, 2003]. even though gilad often takes a pragmatic stand, his writing usually revolves around formal structures for the creation of formal intelligence for formal decisions at the top levels of organizations. to carry it further, gilad’s works can be viewed as important contributions to a writing tradition that focuses on practical advice and analytical aspects of intelligence, according to solberg søilen [2005]. with this i agree, but i must disagree when solberg søilen asserts that we should stick to this tradition in building an intelligence science, especially as solberg søilen states "it should be a positive science in the sense that it should not mix science with too much philosophy."[ibid:14] on the contrary, if we want a true science to emerge then we need to accept different philosophical foundations for its knowledge constructs. but that's not all. there will never be a true science of intelligence as long as researchers fail to recognize the existence of different knowledge interests, and/or just keep researching the art and discipline of intelligence. the problem with this path is that it most likely will hinder those pursuing it to 52 create a fertile distance between themselves and the subject they are researching. as a lot of intelligence research is constructed today, it lacks independence from the practice and, consequently, will never gain the trust of academia at large. the how-to-dointelligence tradition of the field has created an insider perspective that works like a paradigm for how to think and do research on intelligence. of course people, especially on the inside, might call this a science, but this doesn't mean that those on the outside will agree. the media theorist marshall mcluhan [1995:35] once said ”we don't know who discovered water, but we are pretty sure it wasn't a fish.” building on this metaphor it can be argued that as long as most researchers are swimming in the same water as the practitioners, they will never be able to discover how much the water is influencing both their perception and their chances to give a viable account of what intelligence is really about. of course there are a lot of good things to be known about the swimming habits of fish, but these will not tell us anything useful about the water or how seagulls regard fish (except that fish better stay clear of the surface). what we need is a reflective division between the practice and the science, where we once again can use the idea to divide the topic respectively between the art and the discipline. to find ideas about how to make this division, we can learn from others who already have done it. my suggestion is that we turn to the subject of marketing. 7. learning from the emergence of marketing ingmar tufvesson [2005] describes how marketing, over a hundred years, became both a practice and a science. the marketing subject was formed in the 1950s, but it was not until the 1980s that a more independent and critical research tradition formed [see also vironmäki 2007; svensson 2007]. one of the problems slowing down the process was that both practitioners and researchers shared the same theories, models and concepts but due to different knowledge interests gave different meanings to the symbols and words used. tufvesson illustrates this clash of contexts in figure 1. due to this conflict, a lot of time and energy was wasted in disputes over how marketing was to be approached and understood. a conflict that, in retrospect, could have been resolved sooner if those involved would have shown a more benign attitude towards one another’s thinking. over the years, more and more researchers took an interest in marketing, more business schools put marketing into their curriculum and after a while independent periodicals emerged. these periodicals were very important as they allowed researchers to develop their ideas independently from more practical demands from marketing professionals. today a situation has developed where business schools, according to vironmäki [2007], incorporate both "marketing academics" (focusing on marketing as a topic), and "marketing scholars" (focusing on marketing as a discipline). both are necessary, as they serve different knowledge interests, vironmäki concludes. i believe that there are some important things that the field of intelligence can learn from the development of marketing. first, we must accept that the process of creating a science will take time. second, there is most likely a need for both intelligence academics and intelligence scholars, and both have a rightful place in the business school environment, not to mention in creating knowledge about intelligence. a clear division between scholars and academics is to be regarded as a theoretical simplification for the sake of argument. this also poses a question: how do these two groups balance today? judging by my research, most contemporary writing focuses on the art ! marketing as a function marketing as a topic theories/ models/ concepts research context actor context figure 1 tufvesson’s model describing the clash of contexts in the development of the marketing subject (interpreted from tufvesson 2005) 53 of intelligence, not the science, and therefore can be classified as knowledge constructs for intelligence scholars. the writings and knowledge for intelligence academics are thus left wanting. the situation is worsened by a limited amount of intelligence academics, but also through the lack of independent periodicals and conferences where the topic of intelligence can be discussed without the influence of the more practical aspects and concerns. fleisher, wright and tindale [2007] touch upon the problem with present intelligence writing when they encourage researchers to produce better articles: "the field would be better served in both the short and medium term [...], by articles appearing in well-established disciplinary and cross-disciplinary outlets. it could be argued that until, and unless, high level research is carried out and published through wellaccepted or well-read outlets, ci will never achieve its place at the board table or in the curriculum of degree-based programs at top business schools.” [44] although the authors’ solution is to make intelligence studies fit into already existing outlets, they indirectly argue that most intelligence research today doesn't have the right qualities for getting published anywhere besides scip’s periodicals. another way of putting it is that most of the present research isn't interesting enough for other academics. it fails to connect. scip’s ongoing project of redesigning the journal of intelligence and management so that it will become more accepted in academia, is a welcome initiative. [author’s note: this was written in 2009, before the journal was closed.] but, i must regretfully admit that i do not think this will do at all. as long as scip is mainly a practitioners' organization, there will always be restrictions for its periodicals to become the main arenas for discussions on the topic of intelligence. i would also like to stress that i don't suggest that either scip or its periodicals should change. the point is instead that those of us who are interested in the topic of intelligence can't expect someone else to do the job for us. instead we have to form our own forums, but also start to question existing and limiting ideas of the field, the normality that is maintained by the prominent inside perspective. those who adhere to this call will, at the same time, attract attention to themselves, and in due time an avant-garde of intelligence academics will form. 8. coming to terms with organized intelligence work returning to the example of marketing, intelligence is not a field that has come together over one single dominating term. there are numerous discussions whether the intelligence field should be labeled competitive intelligence, business intelligence or something equivalent. i suggest that we leave all the existing labels of the art to the practitioners. instead we, the intelligence researchers, have the opportunity to find a term of our own. this term can separate the academic field from the intelligence practice, but also allow us to embrace all intelligence activities that are carried out, regardless of the label. let us focus on what's actually being done instead, and find a term that describes what we study. my own suggestion is that we should use the term organized intelligence work. today this term is unaccounted for and relates to one of the first (and still viable) academic works on intelligence: harold wilensky’s book organizational intelligence – knowledge and policy in government and industry [1967]. unfortunately, wilensky’s term organizational intelligence is used in a discussion about organizations displaying human-like intelligence (smartness), constraining the direct adoption of this particular term. by picking up the term organized intelligence work we will also free ourselves as academics from unnecessary restrictions that epithets such as "business" or "competitive" bring to mind. hence, this will give us a chance to research the field without being forced to accept – or worse, adapt to – current definitions set by practitioners. 9. out of the water in the process of taking this necessary step out of the water and addressing questions about the meaning of organized intelligence, i've conducted an extensive reading of current ciliterature and literature on organization, decision-making and leadership. in addition, i've collected empirical data on intelligence from four different swedish multinational companies. these studies were carried out in 2003 and 2006 and encompass twenty semi-structured interviews. the final results are presented in my thesis the myth of 54 the rational flow [hoppe, myten om det rationella flödet, 2009]. some of the arguments i've put forward in the present paper are based on this research and writing, but there is more to be extracted. i've already discussed the idea of ideal organizational thinking and touched upon the idea of ideal informative flow. i will now expand a bit on the latter as it can help us understand why many organizations use the ic to explain why they chose to implement organized intelligence activities. in this discussion i'm distancing myself from the intelligence discipline and getting closer to the topic of intelligence in general. 10. the idea of an ideal informative flow supposing decision makers knew what they needed to know, that sufficient intelligence could be collected to fulfill these needs, that all organizational interests could be satisfied in each decision, that decision makers could agree on the meaning of the collected intelligence and gain a common understanding of things, and that the rest of the organization would easily adhere to the decisions taken – only then would the ic give an exhaustive description of how intelligence is created and used. as both practitioners and academics know, these occasions are rare. still, many organizations use the ic for explaining the adoption of intelligence, and one might ask why. new institutional theory will provide us with an appealing answer. all organizations are in need of symbols that tell their interest holders that the organization is run in a rational way and that the management is in control [brunsson 2002; meyer and rowan 1983; powell and dimaggio 1991; røvik 2000; sjöstrand 1997]. to be able to implement intelligence by describing it in accordance with the intelligence cycle – as a discipline for formal decision-making – is just the type of easily used symbol of rationality organizations crave. that the true organization and true intelligence doesn't live up to this ideal is of less importance to an organization in need of legitimacy. to the intelligence professional the ic also comes in handy to describe what intelligence conceptually is about and why intelligence professionals, like themselves, are important to the organization. according to my research, these are the most important aspects (besides the unreflected tradition) in explaining the continuous use of models like the intelligence cycle. in this respect, the ic follows a political logic, not the logic of empirical description. as with the ic, the idea of an ideal informative flow has political value and it will also most likely live on for a long time. what we, intelligence researchers, should do is accept this, but also recognize that we need other complimentary models and descriptions of intelligence work: models and descriptions that will give us the freedom to develop an empirically grounded intelligence science based in reality, not how things are supposed to be, or we wish they were. the new intelligence science must be descriptive. 11. summary in this paper i've compressed a vast and difficult discussion that revolves around some problems with contemporary intelligence research and also the possibility of forming an intelligence science. with inspiration from the emergence of marketing, i've suggested that our understanding of intelligence can become better if we work together exploring the topic of intelligence in all its complexity, hence building a foundation for intelligence as a discipline. doing this, the first step would be to acknowledge the existence of different, but still legitimate, knowledge interests. the second step is to find a term that depicts the unit of study for those interested in researching intelligence. for this second purpose i promote here the term organized intelligence work. we also need to find other models and perspectives of intelligence that will allow us to view this important organizational phenomenon in new, more realistic ways. the prevailing reliance on models like the ic is unfortunate as it rests on theoretical ideas that exhibit severe drawbacks when confronted with empirical data and observations. to solve this situation i suggest we should pay less attention to the material output of intelligence and instead focus on intelligence as a tool for supporting better organizational thinking. 12. references brunsson n (2002) the organization of hypocrisy : talk, decisions and actions in organizations, malmö: liber calof j (2006) the scip06 academic program – reporting on the state of the art, journal 55 of competitive intelligence and management, 3(4), 5-13 ecis call for papers (2009) ecis 2009, the third european competitive intelligence symposium, stockholm, sweden, june 1112, 2009 fleisher c s, wright s and tindale r (2007) bibliography and assessment of key competitive intelligence scholarship: part 4, (2003-2006) journal of competitive intelligence 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sveningsson s (ed) (2007) organisationer, ledning och processer (chapter 14), lund: studentlitteratur treverton g f (2004) reshaping national intelligence for an age of information, cambridge university press tufvesson i (2005) hundra år av marknadsföring, lund: studentlitteratur wilensky h l (1967) organizational intelligence, knowledge and policy in government and industry, new york/london: basic books vironmäki e (2007) academic marketing in finland: living up to conflicting expectations, diss, åbo: åbo akademi vol5no3 article3 coverpage vol5no3 article3 48 leveraging organizational knowledge vision through strategic intelligence profiling the case of the romanian software industry gianita bleoju 1 and alexandru capatina 2 1 dunarea de jos university of galati, romania, postdoctoral researcher – al. i. cuza university of iasi, romania 2 dunarea de jos university of galati, romania gianita.bleoju@ugal.ro alexandru.capatana@ugal.ro received june 7, accepted august 10 2015 abstract: this paper presents the empirical testing of a strategic intelligence profiling tool customized for software development companies that we have previously designed, through an abductive methodology. we conducted a quantitative survey to identify the associations between the strategic profiles embedded into the profiling tool (intelligence provider, vigilant learner, opportunity captor and opportunity defender) and four variables with high impact on organizational knowledge: strategic scope, organizational agility, organizational cultural change process and the approach of competitors. we found that the relevance of our strategic intelligence tool’s variables is a consistent base for testing the robustness of the model in software industry, in order to validate the profiling instrument. we consider that the originality of the strategic intelligence profiling tool, tailored to software industry requirements, resides mainly in the foresight capability of the firm, which is highly dependent on less acknowledgeable factors such as: anticipative versus non-anticipative signal processing; the profile specific equilibrium of recognitional versus analytical strategic decision and rising the actionability of tacit managerial knowledge through collective intelligence reliability. keywords: strategic intelligence, maturity model, software industry, vigilant learner, opportunity captor, opportunity defender, intelligence provider available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 5, no 2 (2015) 48-58 mailto:gianita.bleoju@ugal.ro mailto:alexandru.capatana@ugal.ro https://ojs.hh.se/ 49 introduction our research is focused on the empirical testing, by means of appropriate statistical methods, of a conceptual strategic intelligence matrix reflecting four strategic profiles related to software development companies (vigilant learner, opportunity captor, opportunity defender and intelligence provider). we conducted a quantitative survey in view to identify the correlations between the strategic profiles embedded into the above mentioned profiles and four variables with high impact on organizational knowledge modeling: strategic scope, organizational agility, organizational cultural change process and the approach of competitors. the statistical methods that we used in order to analyze the hypotheses are cross-tabulations and chisquare tests, on a sample of 106 companies from the romanian software industry landscape. the paper is organised as follows: literature review, research methodology, findings and results, valorizing similarities of organizational knowledge vision approaches and we conclude with current and future industry challenges addressed by the profiling tool. 1. strategic intelligence in software industry: a literature review strategic intelligence should provide a company with the information about its business environment; thus, it will be capable to predict changes, design appropriate strategies that will create business value for customers and facilitate the future development for the company in new markets within or across industries (xu, 2007). mcdowell (2008) considers strategic intelligence as being the ability of management to shape itself to fit the particular informational needs of the organization, providing the type of analysis that relates directly to achieving the strategic goals. according to pellisier and kruger (2011), strategic intelligence is the result of the synergy between business intelligence, competitive intelligence and knowledge management, allowing organizations to embed all their information into an easily manageable system in order to meet the intelligence requirements of management’s strategic planning. in the software industry framework, with such intense competition, a company needs a method of analyzing its environment that is more fundamental than the typical methods of scanning and trend analysis. software companies confronted with major uncertainties and life-threatening competition should implement the scenario analysis method. moreover, identifying the interrelationships of the relevant trends that will significantly affect the software industry represents a challenging strategic intelligence task that can be achieved through specialized tools such as influence diagrams and causal maps (schoemaker, 2012). software development projects require knowledge embodied in project managers and software developers, as well as knowledge embedded in technological systems. according to leonard‐barton (1992), “the closer the alignment of project and core knowledge set, the stronger the enabling influence”. ethiraj et al. (2005) suggested that strategic capabilities of software development companies are context-specific and evolve over time through the joint effects of deliberate, persistent firm-specific investments and learning-by-doing approaches. software companies can prepare for technological innovation by sharing intellectual assets through knowledge intensive alliances, recognizing their great use in setting the leading edge of technology and shaping the marketplace (duysters et al., 1999). in this context, the strategic intelligence radars allow them to capture the collaborative opportunities. the emergence of new technologies makes software development more efficient, but at the same time, it is difficult for developers to become proficient with a new technology and managers to understand its impact (lindvall and rus, 2002); in our opinion, the best way to face this challenge is to capture knowledge from the software industry, using the appropriate strategic intelligence tools. embeddedness and knowledge transfer are key determinants of software industry clusters that lead to global competitiveness (dayasindhu, 2002); by taking into consideration these findings, we can state that, dealing with strategic intelligence programs, software development organizations are able to design processes for knowledge transfer and build strategic management capabilities. ajila and sun (2004) investigated two approaches to delivering knowledge to software development projects: “push” and “pull”. first approach is based on tools which allow identifying and providing knowledge to potential users, while the second approach considers that users themselves have to use repositories and other tools to identify relevant knowledge. in both cases, strategic intelligence capabilities are highly required, in order to facilitate the knowledge transfer. the agile methodologies embedded in software development practices can be considered the most significant outcomes of strategic intelligence processes. we have in view four methodologies (meso and jain, 2006): incremental (small software releases with rapid development cycles), cooperative (a close customer and developer interaction), straightforward (considering the possible adjustments during the development process.) and adaptive (an ability to make and react to unpredictable changes). moreover, they address flexibility at the project/product level, but higher level portfolio and product management are beyond the scope, improving performance and reliability through situationally specific strategies, processes and practices (kettunen, 2009). one of the main findings of a research coordinated by aurum (2008) in the software 50 industry reveals that software developers believe in the usefulness of knowledge sharing; the role played by personal networks in capturing and spreading tacit and implicit knowledge was considered as a pillar to foster a culture that encourages it professionals to share their knowledge with others from the software industry; we appreciate that this process is the key enabler of the collaborative innovation networks’ development. the main findings of a research conducted by von krogh et al. (2001) reveals the fact that by sharing existing knowledge on competitors and regulatory environments, the software organizations become increasingly aware of competitors’ moves and possible policy changes that could affect the performance of the company. in their goal to effectively manage speed and change in software development process, the strategic outcomes of agile software companies cannot be predicted in the normal sense of cause-and–effect relationships, but they can be generated by means of patterns, generated through strategic intelligence systems, that have previously produced similar results (highsmith, 2013). 2. research methodology on the basis of a previous research (bleoju and capatina, 2014), based on abductive methodology, reflecting four strategic profiles related to software development companies (vigilant learner, opportunity captor, opportunity defender and intelligence provider) according to their positioning into an innovative strategic intelligence maturity model – simm (figure 1), we developed a conceptual model (figure 2) and four hypotheses to be tested by means of appropriate statistical methods. we chose abductive methodology in the process of designing strategic intelligence maturity model, due to its power to capture and take advantage not only of the systemic character of the empirical evidence from business world, but also of the systemic character of our theoretical model. thus, the dimensions of analysis and the names of simm profiles were previously discussed and validated by experts from software development companies, before their integration into the current research conceptual framework. figure 1 – strategic intelligence maturity model – simm (source: primary research) having in mind the strategic profiles highlighted in simm, we state four hypotheses in order to determine the existence of associations with four relevant variables (strategic scope, organizational agility, organizational cultural change process and approach of competitors’ threats).  hypothesis 1: the strategic profiles of the romanian software companies included into research sample are related to their strategic scope.  hypothesis 2: the strategic profiles of the romanian software companies included into research sample are related to their organizational agility.  hypothesis 3: the strategic profiles of the romanian software companies included into research sample are related to their organizational cultural change process.  hypothesis 4: the strategic profiles of the romanian software companies included into intelligence provider vigilant learner opportunity defender opportunity captor strategic intelligence (si) radar focused on competitor analysis strategic intelligence (si) radar focused on the analysis of industry trends propensity for knowledge sharing propensity for counter intelligence practices 51 research sample are related to their approach of competitors’ threats. figure 2: conceptual model of the research each hypothesis aims at identifying the associations between the strategic profile of the software development companies and relevant features related to each variable, according to the table no. 1 table 1 – assumptions of relevant variables associations according to simm framework no variable intelligence provider vigilant learner opportunity captor opportunity defender 1. strategic scope differentiation through knowledge sharing acquisition of new knowledge competences portability effective reaction to strategic movements of the competitors 2. organisational agility strategic agility process agility portfolio agility operational agility 3. organisational cultural change process weak signals of cultural dissonance culture favourable to changes capacity to value the cultural differences capability to monitor the cultural changes 4. approach of competitors’ threats permanent care for upgrades and innovations focus on meeting the clients’ needs instead of attacking rivals competitive advantage on harvesting over competences’ portability high capacity to detect competitors’ threats due to the fact that we embedded nominal variables in the conceptual research model, we analyzed the data by means of cross-tabs and tested the hypothesis with chi-square method, which is used to investigate whether distributions of our variables differ from one to another. the chi-square compares the observed count in each table cell to the count which would be expected under the assumption of association between the variables included in cross-tabs. a low p-value (<0.05) indicates greater statistical significance, outlining a greater confidence and confirming that the observed deviation from the null hypothesis is significant. 3. findings and results in this section, we will outline the results of the four hypotheses tested through chi-square method, as previously mentioned. hypothesis 1: the strategic profiles of the romanian software companies included into research sample are related to their strategic scope. strategic profile according to simm vigilant learner opportunity captor opportunity defender intelligence provider strategic scope organizational cultural change process organizational agility approach of competitors’ threats 52 table 2 – cross-tabulation between strategic profile and strategic scope table 3 – chi-square tests related to first hypothesis value df asymp. sig. (2-sided) pearson chi-square 32.647 a 9 0.000154 likelihood ratio 31.176 9 0.000276 linear-by-linear association 13.480 1 0.000241 n of valid cases 106 as p-value determined in this case (0.000154) is smaller than the level of significance (0.05) and pearson chi-square value (32.674) is higher than its standardized value reflected by chi square distribution table for 9 degrees of freedom (16,919), we can conclude that there is an association between strategic profiles of the romanian software companies included into research sample and their strategic scope. the in-depth analysis of the research results outlines opportunity captors and opportunity defenders’ behavior, as regard new knowledge aquisition and effective reaction against competition, while the other two profiles intelligence provider and vigilant learner are validating their identity upon featuring sharing knowledge and competence portability respectively. the strategic scope features: knowledge sharing differentiation; acquisition of new knowledge; competence portability and effective reaction to strategic movements of competitors are best matching the si profiling role upon leveraging organizational knowledge vision. our simm claims to overcome the rigidity of a traditional maturity framework, being designed as auto adjustable actionable learning solution, through recalibrating the classical assessment toward a portfolio of exploring anticipative maturity profile specific trajectories. the observed strategic scope could become a relevant precursor for setting up a strategic trajectory portfolio based on renewal organizational knowledge vision statement, consistent with an emergent competitive identity. hypothesis 2: the strategic profiles of the romanian software companies included into research sample are related to their organizational agility. differentiation through knowledge sharing acquisition of new knowledge competences portability effective reaction to strategic movements of the competitors count 9 1 2 2 14 expected count 4.1 4.2 3.0 2.6 14.0 % within strategic scope 29.0% 3.1% 8.7% 10.0% 13.2% count 11 21 7 2 41 expected count 12.0 12.4 8.9 7.7 41.0 % within strategic scope 35.5% 65.6% 30.4% 10.0% 38.7% count 5 5 8 4 22 expected count 6.4 6.6 4.8 4.2 22.0 % within strategic scope 16.1% 15.6% 34.8% 20.0% 20.8% count 6 5 6 12 29 expected count 8.5 8.8 6.3 5.5 29.0 % within strategic scope 19.4% 15.6% 26.1% 60.0% 27.4% count 31 32 23 20 106 expected count 31.0 32.0 23.0 20.0 106.0 % within strategic scope 100.0% 100.0% 100.0% 100.0% 100.0% opportunity defender total strategic scope total strategic profile intelligence provider opportunity captor vigilant learner 53 table 4 – cross-tabulation between strategic profile and organizational agility table 5 – chi-square tests related to second hypothesis test value df asymp. sig. (2-sided) pearson chi-square 32.783 a 9 0.000146 likelihood ratio 30.739 9 0.000328 linear-by-linear association 6.752 1 .009 n of valid cases 106 a. 4 cells (25.0%) have expected count less than 5. the minimum expected count is 3.30. the second hypothesis tested outlines that strategic profiles of the romanian software companies are related to their organizational agility and is validated by chi-square test, which indicates an association between the variables strategic profiles and organizational agility, as a result of a p-value equal to 0.000146. the organizational agility main characteristics, identifying and capture opportunities, prove to be sustained by opportunity captor process focusing, vigilant learner focalized on products and services, while opportunity defender’ main feature is operational efficiency. we observe also the expected intelligence provider identity based mainly on strategic agility. the organisational agility is the locus of understanding the rationale of the simm conceptual approach and highlights its leveraging role by structuring distinctively the organizational knowledge vision. mapping the bundle of organizational capabilities, simm is also empowering the intelligent filtering through prioritized opportunities, both internal (oc and od process and operational agility) and external (ip and vl strategic and portfolio agility). hypothesis 3: the strategic profiles of the romanian software companies included into research sample are related to their organizational cultural change process. strategic agility process agility portfolio agility operational agility count 6 2 3 3 14 expected count 3.6 3.7 3.4 3.3 14.0 % within organizational agility 22.2% 7.1% 11.5% 12.0% 13.2% count 8 20 7 6 41 expected count 10.4 10.8 10.1 9.7 41.0 % within organizational agility 29.6% 71.4% 26.9% 24.0% 38.7% count 8 2 10 2 22 expected count 5.6 5.8 5.4 5.2 22.0 % within organizational agility 29.6% 7.1% 38.5% 8.0% 20.8% count 5 4 6 14 29 expected count 7.4 7.7 7.1 6.8 29.0 % within organizational agility 18.5% 14.3% 23.1% 56.0% 27.4% count 27 28 26 25 106 expected count 27.0 28.0 26.0 25.0 106.0 % within organizational agility 100.0% 100.0% 100.0% 100.0% 100.0% total organizational agility total strategic profile intelligence provider opportunity captor vigilant learner opportunity defender 54 table 6 – cross-tabulation between strategic profile and organizational cultural change table 7 – chi-square tests related to third hypothesis test value df asymp. sig. (2-sided) pearson chi-square 14.608 a 9 0.102273 likelihood ratio 15.266 9 0.083873 linear-by-linear association 2.679 1 0.101681 n of valid cases 106 a. 5 cells (31.3%) have expected count less than 5. the minimum expected count is 2.77. as regards to the third hypothesis test process, we observe a lack of association between the analyzed variables: strategic profile and organizational cultural change process, due to a p-value (0.102273) higher than the level of significance (0.05) and pearson chisquare value (14.608) smaller than its standardized value reflected by chi square distribution table for 9 degrees of freedom (16,919). we also remark some in depth profile communalities in terms of the tested issue that we consider relevant to underline. first and foremost a culture opened to change is mostly approached by opportunity captor followed by the capacity to monitor the organisational change, which is also prevalent for opportunity defender. vigilant learner confirms its capacity to capitalise upon cultural diversity, while the intelligence provider is slightly more prone to the propensity of organisational change. we consider that the invalidated hypothesis could be explained to the context sensitivity of cultural change process, due to both dynamism of the industry and heterogeneity of corporate culture that inertial declare the openness to change, but less serve to consolidate competitive identity. as a maturity model, the si profiling is validating its early warning role by signaling a risk of strategic dissonance upon the features of organizational cultural change and claim a therapeutic approach, through more refined decision making support, as based on non-repeatable behavior, in the attempt to fully evolve from the fragile capacity to monitor cultural change to the most profitable capacity to recognize the value of cultural differences. hypothesis 4: the strategic profiles of the romanian software companies included into research sample are related to their approach of competitors’ threats. weak signals of cultural dissonance culture favourable to changes capacity to value the cultural differences capability to monitor the cultural changes count 5 3 3 3 14 expected count 2.8 3.4 3.7 4.1 14.0 % within organisational cultural change process 23.8% 11.5% 10.7% 9.7% 13.2% count 7 16 7 11 41 expected count 8.1 10.1 10.8 12.0 41.0 % within organisational cultural change process 33.3% 61.5% 25.0% 35.5% 38.7% count 4 1 10 7 22 expected count 4.4 5.4 5.8 6.4 22.0 % within organisational cultural change process 19.0% 3.8% 35.7% 22.6% 20.8% count 5 6 8 10 29 expected count 5.7 7.1 7.7 8.5 29.0 % within organisational cultural change process 23.8% 23.1% 28.6% 32.3% 27.4% count 21 26 28 31 106 expected count 21.0 26.0 28.0 31.0 106.0 % within organisational cultural change process 100.0% 100.0% 100.0% 100.0% 100.0% total organisational cultural change process total strategic profile intelligence provider opportunity captor vigilant learner opportunity defender 55 table 8 – cross-tabulation between strategic profile and the approach of competitors’ threats table 9 – chi-square tests related to fourth hypothesis test value df asymp. sig. (2-sided) pearson chi-square 14.906 a 9 0.09355 likelihood ratio 14.774 9 0.09732 linear-by-linear association 6.824 1 0.00899 n of valid cases 106 a. 6 cells (37.5%) have expected count less than 5. the minimum expected count is 2.51. the lack of association in the case of the fourth hypothesis corresponding to a p-value (0.09355) higher than the level of significance (0.05) and pearson chi-square value (14.906) smaller than its standardized value reflected by chi square distribution table for 9 degrees of freedom (16,919) outlines the idea that opportunity defender and opportunity captor strong competitive identity and capacity to detect and react to competition atacks, while intelligence provider is consistent with its originary extraction position on competitor analysis and industry trends. the strategic intelligence undertake of this competitive identity profiling is proving useful for upgrading the perspective market oriented versus vision oriented behaviour of the firm and replacing it with the deeper organisational knowledge vision leading role on approaching organisational behaviour. starting with the third invalidated hypothesis we can observe the importance to redefine the organizational knowledge vision framework through anchoring our strategic intelligence profiling instrument and expose its leveraging role. organizational cultural change approach is further analyzed on a comparative basis with another empirically validated complementarity research perspective of the literature. 4. valorizing similarities of organizational knowledge vision approaches the methodological relevance of the complementarily approaches (action research and abductive methodology) outlines a strong validation of both si profiling and risk failure factors of strategic scanning projects. their theoretical and managerial relevance is addressed in terms of maximize market opportunities for the former and minimize industry dissonance for the later. strategic scanning projects failure factors identified (lesca & caron-fasan, 2008) and validated (lesca et al. 2012) are consistent with the simm because of key objectives similarity of both strategic scanning projects and si profiling – leveraging competitive information-through specific permanent care for upgrades and innovations focus on meeting the clients’ needs instead of attacking rivals competitive advantage on harvesting over competences’ portability high capacity to detect competitors’ threats count 7 1 5 1 14 expected count 3.0 2.5 4.0 4.5 14.0 % within approach of competitors’ threats 30.4% 5.3% 16.7% 2.9% 13.2% count 8 10 11 12 41 expected count 8.9 7.3 11.6 13.2 41.0 % within approach of competitors’ threats 34.8% 52.6% 36.7% 35.3% 38.7% count 4 3 8 7 22 expected count 4.8 3.9 6.2 7.1 22.0 % within approach of competitors’ threats 17.4% 15.8% 26.7% 20.6% 20.8% count 4 5 6 14 29 expected count 6.3 5.2 8.2 9.3 29.0 % within approach of competitors’ threats 17.4% 26.3% 20.0% 41.2% 27.4% count 23 19 30 34 106 expected count 23.0 19.0 30.0 34.0 106.0 % within approach of competitors’ threats 100.0% 100.0% 100.0% 100.0% 100.0% total approach of competitors’ threats total strategic profile intelligence provider opportunity captor vigilant learner opportunity defender 56 patterns of recognitional versus analytical decision making systems. the performance differentiator organizational capitalizing on anticipative capacity will enact as leveraging organizational knowledge vision, because encompasses a cognitive process approach of organizational cultural change. some fresh reflection is worth to highlight; the need of increased foresight capabilities at the organization level is already perceived as decisive for the future positioning, what it is not yet obvious and as such, compulsory to be acquired, is the tailoring of the optimal balance of both analytical and recognitional decision systems. the misbalancing position however is stimulating the keep choosing alert, which defines a qualified ready to adjust perspective of organizational knowledge vision. this qualified organizational statusquo explained by profile specific precursors of cultural dissonance is measuring the capacity to deal with competing interests and conflicting objectives. what we define “ready to adjust perspective” is a cultural based specific internal environment selection prone to address the collective intelligence awareness, emergence and sense making, accordingly. the ready to adjust approach to organizational decision system is consistent with inductive behavior presumption of fully awareness therefore assumed consequences and the subjectivity of any choice. organizational ready to adjust perspective and the role of our strategic intelligence profiling instrument by experimenting a whole range of strategic trajectories, from market oriented to vision oriented behavior, allow us to discriminate on types and breadth of decisional support. in formulating the needed decisional guidance it is compelling to distinguish between the following roles: a. consultancy-based upon sector specific deep understanding and suitable solution to be implemented; it contains the know what of the sector and adjust the knowhow of the profile. we advance the high risk of portability incongruence for collective intelligence sense making, but good enough for awareness assessment and emergence, as it is based on similarity of the solution already implemented. the uniqueness of the solution remains doubtful. b. business mentoring, being problem solving focused is distinctively offering decision making support to firm specific equilibrium, in terms of the suitable recognitional analytical framework. it assists top management to identify organizational anticipative capacity needs in terms of knowledge deficit and profile positioning through organizational’ future competence identification. the learning focus is to insure the development of the foresight capability of the firm through establishing the anticipatory capacity dimensions of a specific competitive identity and the future relevant capability of the firm by setting up the ready to adjust perspective. the solution is more profile tailored; therefore it will insure sustainability to assess industry dissonance risk. c. procedural animators, being action oriented, their role is to channel the leadership reflection and profile/firm specific capitalization (collective sense making) through qualified expertise (externally-therefore objective) minimizing any cultural dissonance (competing interests / conflicting objectives) in order to insure internalization of knowledge as organizational competence. very probable an organizational reconfiguration is compelling, in order to insure the rising of the actionability of tacit managerial knowledge through experimenting (learning by doing approach) and the reliability of empowering collective intelligence. the capitalization on collective intelligence sense making becomes performance differentiator, through monitoring at best both cultural and industry dissonance risks, being based on commonalties trained and learnt. the most valuable insight of this solution is the development of organizational collective intelligence role settings based upon own knowledge based interaction (revealing practices of collective creation of sense by exposing reflection mechanisms). we consider this role more context sensitive and therefore it is discriminating better between firms’ competitive identities. we denominate this solution as qualified organization status-quo, as tailored to serve at best the foresight capability. 5. conclusions and future industry challenges addressed by the simm the preliminary conclusions about the simm’s robustness test on empirics in romanian software market is consistent with current debate around balancing inductive with analytical approach for better identify and address the conflicts between the different dynamics of theoretical and managerial framework in order to accommodate the methodological mix. we consider that the literature neglects the following useful insights and we advocate that they could be relevant. one first issue to underline is that our model does not claim to anticipate patterns of organizational strategic behavior, but to channel the debate among researches toward the practitioner’s emergency to dispose of conceptual toolkit. exposing accountable tracking empirics will enable the managerial competence as qualified to discover, consolidate or adjust profile specific rules and routines, based upon commonalities trained and learned. more specific to our case, the invalidation of the third and the fourth hypothesis highlights one significant difference between opportunity captor 57 and opportunity defender profiles as regards organizational cultural change process and approach of competitor threats; these results are consistent with the propensity to repeatable versus non repeatable behavior approach, revealing practices of collective creation of sense, and their respective deriving organizational rules and routines. however, the two profiles (oc and od) will adopt the ready to adjust perspective by consolidating their internal decisional structure with appropriate decisional support business mentoring and procedural animators, accordingly. as regards expected capitalization over profile specific identity, we assert that ready to adjust perspective in the case of oc is to be the best positioned for industry future opportunity mapping, while od will successfully address niche strategy design through the anticipation of the most favorable differentiation. the intelligence provider behavior’s best matching the organizational knowledge vision by capitalizing upon strategic resources, being prone to successfully approach the it sector’s most difficult future challenges, by means of its profile specific competence, best fitting to knowledge intensive demand. as the most illustrative example we can mention cyber security issues, better addressed by the multiplier effect of ip behavior as source of strategic intelligence solutions to be tested by the other tree profiles (vl, oc, od) of our profiling tool embedded into simm. the specific profile approaches to security issues and competitively (=separately) capitalizing on solutions, is becoming an unsustainable strategic behavior, not only due to the magnitude and spread of this threat, but because of envisaged software industry requirements, which will be successfully fulfil only by organizational foresight capability development. the current key success factor –minimizing the customer concern (transaction cost approach) and detriment (targeting) outline the different profile’s capacity to deal with it and is emphasizing a waste of knowledge resources. we advance that simm not only reveals the specific gap of market versus vision oriented behavior, but it is also able to support the managerial design of a portfolio of sustainable strategic trajectories to be deployed through profile specific collective intelligence instruments. using tacit managerial knowledge through experimenting and empowering collective intelligence reliability is the best solution for gradually improving the anticipative capacity of the firm insuring quasi-full coverage of future threats and taped opportunities. we consider that simm and its experimental role is a powerful tool enabling the foresight capability of the firm through specific awareness focusing on knowledge resources modeling allocation. the above mentioned waste of knowledge resources can be avoided or adjusted by an disruptive approach based upon less acknowledgeable factors as: anticipative versus non-anticipative signal processing; the profile specific equilibrium of recognitional versus analytical strategic decision and rising the actionability of tacit managerial knowledge through collective intelligence reliability. the broad outline of the foresight capability approach requires a preliminary analyze against critical influence factors: power, resources and independence on software industry, which reliability’s the source of strategic capitalization upon successful anticipative capacity of the firm. acknowledgements this work was supported by the european social fund through sectorial operational programme human resources development 2007 – 2013; project number posdru/159/1.5/s/142115, project title “performance and excellence in postdoctoral research in romanian economics science domain”. references: ajila, s. a., & sun, z. 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(2007). managing strategic intelligence: techniques and technologies. igi global. jisib-vol-12_nr-1(2022) (3).pdf journal of intelligence studies in business vol. 12 no. 1 (2022) open access: freely available at: https://ojs.hh.se/ pp. 6–19 relationship between emotional intelligence, emotional labour, job stress and burnout: does coping strategy work? banji rildwan olaleye abstract this study seeks to examine the mediation effect of surface acting (sa), deep acting (da), and job stress (js) between emotional intelligence (ei) and burnout (bo) and also the sequential mediation of sa-js and da-js between ei and burnout. it also deepens understanding of the moderating role played by mindfulness meditation (mm) as a coping strategy on the effect of js on burnout. a cross-sectional plan was designed, whereby a survey was randomly used to obtain data from 338 medical personnel from private hospitals in nigeria, and a partial least square structural equation modeling was used to test hypotheses contained and the moderating role of mindfulness meditation as a copying strategy, as well as conducting the study among medical personnel of privately-owned hospital in nigeria health care sector. keywords: emotional intelligence, emotional labour, job stress, burnout, mindfulness meditation, health sector 7 1. introduction emotion has been part of our daily lives, most especially when it comes to handling negative and even positive feelings. emotional intelligence (ei) has been a very key factor in determining employees who can handle stress in the workplace and those who cannot. meanwhile, ei could be either negative or positive, thereby necessary to maintain a moderating balance. extant literature opined on creating a considerate on how ei helps employees minimize emotional labour (el), job stress js, and burnout in an organization. the study conducted by (barchard, brackett, & mestre, 2016) as cited by (maría carmen, cándido, lucía, david, & josé manuel, 2019) shows traits and what controls the stable ability to be able to identify and act in emotive situations such as optimism, motivation, and enthusiasm. secondly, ei ability is mostly referred to as the use of emotions which enables individuals to adapt to their environment and situations, especially during decision making. according to the study conducted by jung tions that have employees with a high level of ei result in higher productivity and perengagement. meanwhile, cho, mohammad & kim (2019), focused on the mediation effect of el and js on ei and burnout with the moderation effect of some coping strategies like direct action, social support, and avoidant only the aforementioned coping strategy which warrants more study to be conducted using other forms of coping strategy as mindful mediation to serve as a moderator, also the study was restricted to only south korean front-line employees of hotels. this warrants broader research to be conducted in a different envithe subject matter, thereby the need for which this research is based. employee with a high incidence of emotional intelligence tends to be more productive in an organization due to their ability to minimize el, js, and burnout. this means employees with lower ei will bring the effect of low productivity. also (maría carmen, cándido, lucía, david, & josé manuel, 2019) with their view on ei as a trait in individuals, connotes that an employee can have the required skill set needed for a particular task, but having a lower level of ei, which brings about the need to balance the skills set with a good level of ei. therefore, a study is necessitated to proffer a solution on how this can be managed using some coping strategies such as mindful meditation as a moderator to help employees cope with el, js, and burnout. this paper discusses the relationship between ei and its effect on el, js, and ultimately burnout with the moderating factor of mindful meditation in employees with a focus on the workforce population of some private hospitals in nigerian. as studies have been conducted previously with restriction to only front-line employees, this is being replicated within the health sector, since staff from the hospital are expected and even demanded to show a happy and welcoming gesture irrespective of their inner feelings. therefore, this research seeks to offer quantitative ripostes to the following questions: a) is there any positive effect of ei on employees’ el and js? b) is ei only important for front-line employees or is it equally important to health workers? c) is there a moderating effect of mindful meditation on the nexus between js and burnout? to show the level of importance of ei and how it affects employees’ job stress magnitude, which will enable organizations to work towards training their employees on how to 2016) studied “why is employees’ emotional intelligence important? the effects of ei on stress-coping styles and job satisfaction in the hospitality industry” concentrating only ied emphasizing mindfulness meditation as an immediate way of moderating an employee’s el and js so as not to experience burnout and ultimately low harmonize diverse previous studies, and proceed further to cover the gap in the area of the health sector and within the african continent, especially focusing on nigeria, which will give a different viewpoint on the pressing matter in extant literature due to different beliefs and cultures. the present study is being made to provide a broader thoughtfulness of ei, and its connection to el, js, and the effect of 8 burnout in employees. this study will seek to understand the upshot of ei on el, js, and its effect on burnout, and also the moderation role of mindful meditation on the nexus between el and burnout. 2. literature review 2.1 conceptual review emotional intelligence (ei) ability to identify others’ emotions and also to of relating to others (salovey & meyer, 1990; ji, songshan & pingping, 2019). this entails an individual’s ability not only in recognizing his emotions but also that of others and make his/her emotions relate to others favorably, as there can be negative relationships and positive relationships. emotional intelligence (ei) is basically of two concerns; the trait and the ability view (barchard, et al., 2016; maria et al., 2019). the emotional intelligence trait is responsible for an individual’s personality which enables him/her to identify processes and action emotive situations such as enthusiasm, optimism, and motivation, while the ability ei is responsible for a personality’s capability to solve problems and adapt to a new or chang(2017), view ei as an individual’s capacity in dealing with shreds of evidence favorably and successfully. emotional labour (el) emotional labour (el) was outlined by cited by (nuran, serpil, & salih, 2012) that it’s the hassle a personal make in designing and dominant his emotions to bring on organizations needed show of emotions within the individual’s social relationship within the organization.) ji, songshan, and pingping (2019) submit that workers will manage their feelings to own a positive show of facial and bodily expressions and this can be done principally to secure a grip or to aim for a decent wage. also, (ji, songshan (sam), & pingping, 2019) cited (diefendorff, croyle, & gosserand, 2005) that el can be operational in three strategies of surface acting, deep acting, and, genuine acting. (1983) and ji, songshan, and pingping (2019), assumes that employee adjusts his/her facial and bodily expressions in step with the principles of the organization once in an exceptional real sense, the individual’s felt emotions don’t seem to conform to the organization’s performance rules required. according to grandey (2000), deep acting (da) occurs once an employee individual’s felt emotions don’t change to the organization’s needed performance, and this warrants the individual using imagination, deep psychological thinking, and memory to suppress the negative emotions to expertise the organizations needed emotions. job stress (js) the requirement of a job or task is more than the capabilities, resources, and needs of the worker (chien-wei, 2010). it is seen as the interface of work settings with workers’ personalities changing usual psychological roles and triggering limits and negative effects. js is a multi-faceted delinquent that incorporates an individual’s features, the sit (cullen et al., 1985; parker & decotiis, 1983; xiachong et al., 2017). summarily, factors relating to stress at work vary based on job nature, the exact stressor’s kind, and the scope of the relationship between stress, and strain. type, and stressor diverges based on job level and type (chien-wei, 2010). burnout burnout as opined by (grandey, 2000) is a situation where an employee experiences emotional exhaustion from a job due to the depletion of energy from an extensive task with a limited source of replenishing energy. also (grandey, 2000), opined that this connotes that employees experiencing burnout can make the individual lose a sense of esteem and accomplishment which will result in lower productivity to the organization. burnout is categorized into three groups; “ 9 ” (carlson, is also a resultant outcome of employee exhibition of emotions of brained emotional energy once a worker is saddled with a responsibila high rate of repetition. the repetitive nature of the work will lead to the employee experiencing burnout which will result in the feeling of a low sense of accomplishment (chiang & job stress, and they are very closely related as the former leads to the latter. 2.2 conceptual framework and hypotheses formulation emotional intelligence (ei) and emotional labour (el) deep acting (da) which is part of emotional labour (el) is affected by the employee’s use of emotions (uoe), which is under emotional intelligence (ei), thereby establishing a link between ei and el. consequently, the hypothesis below was considered. emotional intelligence (ei), job stress (js), and burnout in the study conducted by (lee & ok, 2012) that employees who lack emotional intelligence (ei) usually suffer from consistent job stress which eventually leads to burnout in such employees. this is an indication that there’s a link between ei and burnout through job stress and also considering the connection between ei and el (jung & kim, 2019). brotheridge and grandey (2002) and choi, mohammad, and kim (2019) consider ei as deep acting (da) and surface acting, since observations were made on workers with higher ei regulating their emotional behavior if the need arises. this goes to show that there is a mediating effect of el (da & sa) on ei and developed. mindfulness meditation (mm) as a moderator between job stress (js) and burnout different scholars have shown the moderation roles coping strategies have played on job stress; and burnout. among them are the contributions of various authors such as (devereux et al., 2009) who observed from their study how social support moderates the relationship among perceived job demands, and burnout among workers with disabilities. a study conducted by (wen et al., 2019) highlighted that social support and avoidant coping tend to increase stress in china rather than reduce it. choi et al. (2019), concluded that social support and avoidant coping are both effective coping strategies in their study conducted in south korea. charoensukmongkol (2013), stated that mindfulness mediation is when an employee observes an exercise of calmness by observing either his/her breathing and or walking step as a way of controlling stressful or negative emotions, and also stated that employees who adopt this coping strategy tend to focus more on problem-solving steps to cope with stress and enjoy (2019), stated that job stress in employees is a sign that the employees are about to experience burnout, and that to moderate or control this burnout, organizations should have a training and development program for their employees to teach them some coping strategies that will help them manage the job stress effectively. these coping strategies can be social support, direct action, avoidant coping, meditations, etc. considering the study focuses solely on mindfulness meditation as a coping strategy as a moderator for his study, the following hypothesis was considered. tantamount to erstwhile discussions on extant literature, given below is the heuristic model for the study: 10 2.3 theoretical framework in human resources management and social science in general, there are different theories of general management and human resources supporting ideas about emotions. these theories sometimes may not explain or give an accurate understanding of the concept under study, but they can serve as a basis or foundation upon which a concept is built. this is because they give a rationale for the interpretation of a concept or an ideology. in regards to this study, some theories were considered in understanding the relationship between ei, el, js, and burnout. conservation of resources (cor) theory is a major theory anchoring the connection with the present study, was being espoused by choi et al. (2019), which states that every employee pursues in protecting and conserving his/her resource and in this regard, the mental, physical and emotional energy of such an employee is the energy the individual seeks to protect, which will, in turn, engage the employee in emotional labor as he/she seeks to protect his/her collective energy. another theory that was adopted was the emotional theory of rationality (etor) that emotions are the integral part of humans that allows the brain to function at its highest and best possible level. this further explains why individuals as employees will seek to conserve their emotional energy as explained in the cor theory. 3. methodology participants and measures the study participants constituted a total of 2801 medical personnel from some private hospitals within six states in nigeria, which were recorded to have the highest number of hospitals or medical centers within the nation. ten private hospitals were randomly selected from domly selected to give a total of three hundred. afterward, the sample size determined was doubled, to resolve the non-response problem, questionnaires were valid for the study, implying a 56.3% response rate. a well-structured survey was designed in obtaining responses as adopted from the extant literature. emotional labor was operationalized using a dimensional context from diverse previous studies conducted by brotheridge & grandey (2002), with three items each for surface acting and deep acting. meanwhile, emoitems from the study conducted by chin-shan & ing strategy was measured with three items from a study conducted by irene, therese, and junvie (2019), while job stress was measured with three items (jin, sun, jiang, wang & wen, likert scale was adopted to elicit responses. h4 h1a h3a h2a h1b h3c h1c h2b h3b ei elsa js mindfulness burnout el-da research model. ei: emotional intelligence; el-sa: emotional laborsurface acting; el-da: emotional labordeep acting; js: job stress 11 data analysis the analytical procedure deployed in this study comprises both descriptive and inferential statistics. spss was utilized in describing the sample population frame, in terms of frequencies and percentages, while correlation analysis was run to ascertain the nature of the relationship between variables, and the proposed structural model was subjected to strings of tests; psychometric and multi-collinsquare structural equation modeling (plsexamined using the bootstrapping method. 4. results and discussion 4.1 findings descriptive statistics explored on respondents shows respondents’ appropriateness for the study. the sample comprises three hundred and thirty-eight (338) workers from federal hospitals in nigeria. out of this sample, there were 66.6% females and 33.4% males in this sample. the average age of respondents was 36%, the majority falling within 30-39 years, while the least age fell within the range of 50 years uate degree, while the least response (9.2%) accounted for postgraduate studies. meanwhile, the designation revealed that the majority interviewed were nurses, while an equal proportion (15.4%) came from physicians and therapists, correlational analysis the intercorrelations among the latent and observed variables; burnout, emotional intelligence, job stress, and emotional labour are shown in table 2. explicitly, uoe is positively connected to emotional labour (deep acting r = 0.30; surface acting r = 0.28, p < .01) and job stress (r = 0.21, p < .01), with a moderate and low correlation respectively. a moderate and positive relationship was found between sa (r = 0.36, p < .01), job stress (r = 0.38, p < .01) and burnout, while da had a positive, but low correlation with burnout (r = 0.29, p < .01). also, deep acting (r = 0.71, p .01), and surface acting (r = 0.69, p .01) are strongly and variables categories freq (n = 338) percentages gender male 113 33.4 225 66.6 age below 30 years 70 20.7 30–39 years 141 41.7 40–49 years 50 years & above 98 29 29.0 8.6 education graduate postgraduate 101 206 31 29.9 60.9 9.2 designation physician nurse therapist medical assistants 52 197 52 37 15.4 58.3 15.4 10.9 observed and latent variable correlation. variables mean sd burn da uoe js mm sa burnout 3.340 1.003 1 0.29** 0.45** 0.38** 0.03** 0.36** deep acting 3.644 1.087 1 0.30** 0.71** -0.00 0.77** emotional intelligence (uoe) 3.567 0.835 1 0.21** -0.03 0.28** job stress 3.607 1.186 1 0.02 0.69** mindfulness meditation 3.581 1.258 1 -0.02 surface acting 3.419 0.979 1 12 test of hypotheses the two-stage model of the partial least squares (pls) technique suggested by andersen and gerbing (1988), was used to assess both the structural model and the measurement model. the measurement model was sures the degree to which several items in an composite reliability (cr), were all examined to determine the convergent validity. as suggested by igbaria et al. (1995) and lin & wang (2012), all the items recorded outer loadings above 0.5 and for composite reliability and its sister metrics (cronbach’s alpha and rho a), all constructs measurement model. latent variables convergent validity internal consistency discriminant validity indicators ca rho_a cr ave f-l emotional labour (sa) 0.808 0.811 0.886 0.722 0.850 sa1 i resist expressing my true feelings 0.849 sa2 i pretend to have emotions i don’t have 0.856 sa3 i hide my true feelings about a situation 0.843 (da) 0.819 0.820 0.892 0.735 0.857 da1 i make an effort to feel the emotions that i need to display to others 0.870 da2 i try to experience the emotions that i must show 0.874 da3 i try to feel the emotions i have to show as part of my job 0.827 emotional intelligence 0.878 0.891 0.910 0.669 0.818 uoe1 i always encourage myself to try my best 0.817 uoe2 i am a self-motivated person 0.784 uoe3 i always set goals for myself and try my best to achieve them 0.827 uoe4 i can always calm down quickly when i’m angry 0.827 uoe5 i seek out activities that make me happy 0.833 job stress (js) 0.862 0.862 0.906 0.708 0.841 js1 there are a lot of aspects of my job that makes me upset 0.818 js2 when i’m at work, i often feel tense and uptight 0.823 js3 i am usually under a lot of pressure when i am at work 0.856 js4 a lot of time my job makes me very frustrated or angry 0.867 mindful meditation (mm) 0.912 0.806 0.931 0.817 0.904 mm1 you see for yourself? 0.948 mm2 enhanced your learning abilities? 0.845 mm3 mindfulness meditation? 0.917 burnout (burn) 0.827 0.835 0.884 0.657 0.810 burn1 i feel i treat some residents as if they were impersonal objects 0.775 burn2 i’ve become more callous towards people ever since i took this job 0.842 burn3 i worry that this job is hardening me emotionally 0.800 burn4 i don’t care what happens to some recipients 0.823 ca = cronbach’s alpha, cr = composite reliability, rho = rho_a reliability indices, ave (f-l) = 13 return values greater than the 0.70 thresholds, in the measurement model has converged. convergent validity is maintained, as demonvalues being over the 0.5 criteria (olaleye et al., discriminant validity discriminant validity, inter-construct correlalarcker’s approach (1981). meanwhile, in while the inter-construct correlation is shown larger than the inter-construct correlation of each construct, the measurement model is larcker’s criteria, which is used to determine discriminant validity, have recently been tive, a monte-carlo simulation was used to inant validity, the two-threshold proposed by values for all items fell below limits of less than 0.90, demonstrating a prevalence of discriminant validity among those constructs included in the model. structural model in addition to the measurement model, the structural model was evaluated in this study. causation constructs in an instrument are often tested using the structural model uses bootstrapping of 5000 re-sampling the r-squared, as well as other statistics such as t-statistics, p-value, and f2. direct and indirect effects using the predictor variable’s direct effects on the outcome variables, researchers discovered that emotional intelligence have a positive impact on emotional labour; surface acting 1a: = 0.279, t = 5.378, p < 0.05); deep acting 1b: = 0.298, t = 5.802, p < 0.05), but insignif1c: = -0.017, t = 0.646, p > 0.05). meanwhile, the indirect effect of emotional labor (surfaced acting and deep acting) on the relationship between emotional intelli2a: = 0.098, t = 3.857, p 2b: = 0.131, t = 4.753, p for the hypothesized indirect path contained 3, sa mediates the relationships of emotional intelligence and burnout, while deep acting and job stress could not play a mediating role between emotional intelligence and burnout. 3b 3c are rejected. interaction effect (moderation) mindful meditation (mm) indirectly moderates the direct effect of job stress on burnout was a graph, showing how mindful meditation mm values (-1 sd, mean, and +1 sd), the blue, red, and green lines show how mm affects the path. it becomes ostensible that high levels of mm involvement dampen the positive effect of job stress on burnout, while low levels of mm involvement strengthen the effect of job stress on burnout. variables burn da uoe js mm sa burnout deep acting 0.349 emotional intelligence 0.526 0.343 job stress 0.444 0.840 0.235 mindfulness meditation 0.042 0.029 0.045 0.031 surface acting 0.422 0.842 0.319 0.817 0.058 14 ) commonly referred to as the effect size, be reported in 2). using cohen’s (1988) threshold of 0.02, 0.15, and 0.35 as a standard, they also advocate interpreting the amplitude of effects of small, medium, and large in magnitude, respectively. 2 is greater than 0.15 but below 0.35), all reported effect sizes were of small magnitude, falling below the 0.15 threshold. path analysis result. relationship nfi = 0.809 srmr = 0.055 x2 = 849.050 hypotheses std. error t-value p-value f2 r2 decision direct effects h1a: ei 0.279 0.052 5.378 0.084 0.078 supported h1b: ei 0.298 0.051 5.802 0.097 0.089 supported h1c: ei indirect effects -0.017 0.037 0.460 0.646 0.001 0.548 not supported h2a: ei h2b: ei h3a: ei h3b: ei h3c: ei moderation effect h4: mod*js 0.098 0.131 0.062 -0.020 -0.004 -0.113 0.025 0.028 0.029 0.025 0.009 0.055 3.857 4.753 2.169 0.828 0.469 2.045 0.408 0.639 0.112 0.171 0.022 0.002 0.038 0.548 0.548 0.179 0.179 0.179 0.179 supported supported supported not supported not supported supported path analysis. 15 16 close to 1, and the srmr value of 0.055, which 4.2 discussion the works of previous scholars have established the different relationships between ei-el, ei-bo, ei-el-bo, ei-el-js-bo, ei-el-js-bo with the moderation of avoidant coping, active coping, and social support as moderation variables. with all these previous studies focusing previous study used mindfulness meditations as a moderation variable and also with no consideration to the health sector. therefore, this study focuses on the mediation of el and js on ei and bo with the moderation effect of mindfulness mediation on the health sector using nigerian hospitals as a case study. et al., 2019) on the mediation role js plays between el and burnout, this study also showed the mediation role js plays between ei, el, and burnout. as evidenced from the result, the effect of ei on burnout is mediated by js and also a sequential mediation of sa-js and da-js, revealing that el does not have a direct mediating effect between ei and burnout without the sequential support of js. this implies that without the effect of js, both sa and da do not result in burnout for the medical staff even though ei may impact a resulting sa and da on the staff. this means over-exhibition of ei will result in el i.e., both sa and da but not burnout, and a prolonged el that transfers into js can lead to burnout among medical personnel. in consideration of the previous study by (choi et al., 2019) who took into consideration three different coping strategies to alleviate the effect of js on burnout, i.e. they considered direct action, active and seeking social support. eration role of mindfulness meditation on js and burnout as was supported by the works of medical staff employ to conserve their energy, as explained by the conservation of resources theory (choi et al., 2019). the results showed that when the staff used a high level of mm, it helps in moderating the effect of js on burnout, contrarily, if they apply it at a lower level, it strengthens and increases the effect of js on burnout. 5. conclusion the present study remains high cognizance as it explores various connections between ei, el, js, and burnout and also tried to understand the moderation role mm plays in managing js, of not resulting in burnout among healthcare medical personnel in an african setting like nigeria. this will serve as a basis upon which scholars can investigate this phenomenon not only in asian or european or american countries, but in an african setting, and previously studied focused in the hospitality industry, but with now focusing on health care setting; gaining a wide range of area for further research. practical and managerial implications gested some practical steps for the health care practitioners. because health care work has a lot of emotional demand on the employees, managers need to bring up programs that will train employees on how to adopt and utilize various coping strategies in alleviating js, not only mm but also other coping mechanisms that will help them cope with the high emotional, mental and physical demand of the job. secondly, managers need to ensure in house interviews and reviews are conducted to understand the ei levels of their employees and to assign tasks that will be at a manageable level for such employees that are prone to js. this is because especially as the lives of the patients are at stake and an exhausted employee is a danger to a patient. thirdly, managers can support employees by encouraging them to have time for self-development on ei and also medical schools need to integrate the teaching of ei skills to students studytor and observe employees who are exhibiting signs of js and also advise employees to always speak up when they are experiencing js so that immediate intervention can be made, as js is a sign the employee will soon experience burnout which will impact negatively on the lives of patients, lastly, managers should also design rotations that will not be over tasking on the staff as that can help moderate the rate at which the employees will experience js and or burnout. 17 limitations and suggestions for future research despite all contributions from this study, limits such as a small number of hospitals were being sampled in nigeria, therefore, the cultural factor and the limited data from the few hospitals may have an impact on the conclusion, and focus can also be made on replicating the study in other sectors or country or continent. secondly, the research only focused on mm as the only coping strategy, therefore, future studies can be done integrating other forms of coping strategies like religious coping strategy, especially considering nigeria is a religious country. this will further broaden ies can investigate questions like how does ei tively can they use mm so as not to underuse it and increase their chances of burnout? with these questions answered, contributions will emanate not only to the african healthcare sector but extend to other parts of the world. lastly, the study is a cross-sectional design, with variables measured purely with a sura longitudinal study on a causal effect among variables for a long-range period of observation. references anderson, j. c., & gerbing, d. w. 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(2018) competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses. journal of intelligence studies in business. 8 (3) 32-44. article url: https://ojs.hh.se/index.php/jisib/article/view/327 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses leonardo a. garcia-garciaa and marisela rodríguezsalvadorb* auniversity of sussex, school of engineering and informatics, england btecnologico de monterrey, escuela de ingenieria y ciencias, monterrey, n.l., mexico; *marisrod@tec.mx journal of intelligence studies in business please scroll down for article competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses leonardo a. garcia-garciaa and marisela rodríguez-salvadorb* a university of sussex, school of engineering and informatics, england b tecnologico de monterrey, escuela de ingenieria y ciencias, monterrey, n.l., mexico corresponding author (*): marisrod@tec.mx received 5 august 2018 accepted 25 december 2018 abstract additive manufacturing (am) is revolutionizing the health industry, where it provides innovative solutions for the production of personalized devices, such as hand orthoses. however, the scientific research dynamics in this topic have not yet been investigated. this study aims to fill this gap through the application of a competitive and technology intelligence (cti) methodology enhanced by a scientometric and network map analysis. major advances in the fabrication of hand orthoses using am, the presence of collaborations, and the most influential authors were determined. specifically, network map analysis, bibliographic occurrence and bibliographic coupling were conducted on documents retrieved from scopus and the web of science (wos), and on patents from more than 104 authorities. results showed only nine published patent families and 34 research articles on this topic from 2006 to 2016. ten papers concern static orthoses, while 24 deal with dynamic orthoses and exoskeletons. the indegree and outdegree parameters and the betweenness centrality of these documents enabled us to determine the most cited authors and instances of collaboration (papers co-authored between institutions). dr. paterson a. m. j. was the most influential author, with four publications with the highest betweenness centrality in the network (189), which accounted for the most cited document with five citations. the institution with the most publications was loughborough university, with four papers, and the collaboration between affiliations was rare. these documents review important aspects of manufacturing orthoses using am, and additionally pay particular attention to the importance of personalised orthoses where am contributes. notably, these papers focused primarily on studies for the development of a methodology for the fabrication of hand orthoses using am, but they do not present any application. this research provides insights to better understand the dynamics of research and development in the orthopaedics domain, specifically for hand orthoses. keywords 3d printing, additive manufacturing, betweenness centrality, bibliographic coupling, competitive intelligence, hand orthoses, network map analysis, scientometrics 1. introduction the competitive and technology intelligence (cti) methodology is a process where information is systematically and ethically gathered to be analysed and further transformed into valuable results that can strengthen decisions for innovation and product development (rodríguez-salvador and journal of intelligence studies in business vol. 8, no. 3 (2018) pp. 32-44 open access: freely available at: https://ojs.hh.se/ 33 tello-bañuelos 2012). public documents, such as patents or scientific publications, represent useful sources of information for cti purposes. while patents register technological inventions (archibugi and pianta 1996), scientific documents aim to publish original research advances. both represent valuable resources to identify and monitor the progress of science and technology (s&t) including predominant research areas, emerging technologies, top researchers, most active institutions in the field and collaborations. they also support decision-making processes for research and innovation efforts (archibugi and pianta 1996; bonino et al. 2010; fabry et al. 2006; rodríguez-salvador et al. 2014). when analysing such documents, applying scientometric methods with cti can provide a better assessment of s&t production (bornmann and leydesdorff 2014; mingers and leydesdorff 2015). these methods use complex tools to process information from dozens to thousands of patents or scientific publications, not only from well-established research areas, but also for emerging technologies such as am (bakhtin and saritas 2016; leydesdorff et al. 2015; leydesdorff and milojević 2015; oldham et al. 2012; porter and youtie 2009; rotolo et al. 2015). although new developments have less information available than established technologies, using scientometric tools is required to significantly dispel the uncertainty surrounding emerging technologies. tools like bibliographic occurrence and bibliographic coupling can be applied to determine the impact, growth or evolution of science (biscaro and giupponi 2014; mccain 1990; white and griffith 1981; zhao and strotmann 2008). while bibliographic occurrence evaluates the presence of specific references contained in scientific documents, bibliographic coupling refers to the frequency of references shared between two or more scientific documents. the higher the bibliographic coupling, the higher the impact of the cited documents (biscaro and giupponi 2014). of the two tools, bibliographic coupling is more suitable for the identification of fundamental research domains (kuusi and meyer 2007; small 1973; zhao and strotmann 2008). additionally, the authors with more influence in a certain area of research can be determined using indegree and outdegree parameters or centrality measures, which are commonly applied in network map analysis. the indegree parameter counts the times that each analysed document is cited by other publications, and the outdegree counts the publications cited in the analysed documents. furthermore, the betweenness centrality measurement has high value for network map purposes. it enables grading of nodes according to their positions. a grade is applied based on the shortest number of paths that pass through a particular node. if a node is in a position that connects different aggregates of nodes, this node will have a higher betweenness centrality (brandes 2001). this measure was used in this research to determine the most influential author by noting if an author is connected to more authors, not only to documents in reference lists. institutional collaboration can be clearly visualised and analysed through network map analysis, which shows the interaction between them. recently, rodríguez-salvador et al. (2017) applied scientometric tools on scientific and patent literature from 2000 to mid-2016 to uncover the knowledge landscape of 3d bioprinting. we also presented a first approach to study the incursion of am on hand orthoses at the 3rd international conference on progress in additive manufacturing (pro-am) held in singapore in may 2018 (garcía-garcía and rodríguez-salvador 2018). this research determined that am is already used in the production of hand ortheses. materials, processes and methods for data acquisition were also detected. however, the current study focuses on the identification of the most influential authors and co-authoring institutions that have carried out research for the use of am in hand orthoses. such orthoses are of significant relevance for treating hand disabilities related to broken bones, congenital conditions or cerebrovascular diseases (colditz 1996; colditz 2002; coppard and lohman 2015; fess 2002; imms et al. 2016). they are used as part of rehabilitation programs to support the affected limb by immobilising it. the most common orthoses are static, but there is also another type of orthosis: the dynamic orthosis. this type of orthosis provides the patient with a limited amount of movement through a mechanical assembly— such as rods, pins, and springs connected to the orthosis’s main body—which is made using the same materials as conventional, static orthoses. static orthoses are fabricated using diverse materials. plaster of paris is the most common, but thermoplastics is also widely used (cassell et al. 2005; colditz 2002; coppard and lohman 2015; fess 2002; fess 2005; schultzjohnson 2002; schwartz and janssen 2005). 34 normally, orthoses can be manufactured in batches using standardised hand measurements (such as small, medium or large), but using personalised orthoses according to the patient’s anatomy and type of treatment, allow for better patient recovery (fess and mccollum 1998; kim and jeong 2015; paterson et al. 2015). am is a technology that can be used for the fabrication of personalised orthoses. am, also known as 3d printing, rapid prototyping or free-form fabrication (fff) (espalin et al. 2010; ventola 2014), is a novel manufacturing process used for fabricating objects by depositing materials in layers from digital models. the models can be generated either through computer aided design (cad) software or image acquisition methods, such as computerised tomography (ct) scans, magnetic resonance imaging (mri) or 3d scanning. am has many advantages over traditional manufacturing, such as reducing material waste, minimising manufacturing cost for complex parts and manufacturing unconventional, personalised shapes (banks 2013; basiliere and shanler 2015; davey et al. 2011; espalin et al. 2010; paterson et al. 2010; schubert et al. 2014; ventola 2014). this increases the attractiveness of am technology. it is a very versatile technology that has the potential to fabricate personalised medical devices, such as prostheses or orthoses. 2. methodology the scientometric tools of bibliographic occurrence and bibliographic coupling, as well as network map analysis, were used within the competitive and technology intelligence (cti) methodology of rodríguez-salvador et al. (2017), with the aim of determining the most active and most influential author and understanding the level of collaboration (coauthoring) between institutions working on the fabrication of hand orthoses using am. the process began with the determination of the most suitable keywords with which to build a search query for both scientific and patent databases. this stage included a review of publications on rehabilitation, therapy and orthopaedics (garcía-garcía et al. 2018). the terms obtained were then assessed by experts on hand therapy who asked to remain anonymous. four main keyword categories were determined as follows: anatomy (e.g., hand, finger, phalangeal), technology (e.g., 3d printing, am), application (e.g. rehabilitation for stroke) and medical devices (e.g. orthosis, splint). figure 1 shows a venn diagram of the keyword groups. these keywords were used to build a general search query in which boolean operators, proximity terms, truncators and wild cards were applied. a set of 100 searches was performed before arriving at a final search query approach. the general query used was based on the following: title-abstract-keyword(((("3d print*") or ("rapid prototyp*") or ("additive manufact*") or ("solid free form fabric*") or ("fuse deposit* model*") or ("selective laser sinter*") or (stereolithography) or (photopolymeri?ation) or "reverse engineering") and ((hand or wrist or finger or "upper limb") w/5 ("static progressive splint*" or "serial static splint*" or "casting motion to mobile stiffness" or orthos?s or orthotic* or orthop?edic or splint* or brace* or cast* or rehabili* or aid or paresis or "poststroke")) or ((dynamic w/10 orthos?s) and ("prototype")) or (dynamic w/10 splint*) or (exoskeleton)) where w/# indicates a search within a specified number of words. this general query was then modified according to each of the databases consulted. patseer, an online patent platform that covers more than 104 leading patent authorities, was used to collect and analyse patents (sinha and pandurangi 2016). to figure 1 main terminology categories. keywords grouped by anatomy, technology, applications and medical devices. 35 search for scientific documents, scopus and the wos were utilized (garcía-garcía et al. 2018). scopus, at the time of the search, contained information from more than 20,000 journals (elsevier 2016), while the wos covered information from more than 13,000 journals (thomson reuters 2011). the time frame to be searched was defined as 1980 to 2016 (2016 was the year in which the information gathering for this study concluded). the year 1980 was chosen because the first reported works on 3d printing technology were published in the 1980s (dormehl 2018). the next step in the methodology was the cleaning process, in which those publications not related to the topic of interest were discarded. during this step, publication titles and the names of authors and institutions were homogenised and the data deduplicated, eliminating repeated items from the data set. then, a bibliographic network map of the publications was generated to identify the most cited authors on the subject. this was achieved through bibliographic coupling, determining the betweenness centrality and finding the indegree and outdegree parameters. a collaboration analysis was also carried out using network mapping to find partnerships between the main affiliations advancing the fabrication of hand orthoses using am. 3. results the overall number of publications obtained from the searches of the three databases (scopus, wos and patseer) was lower than expected. only 15 published patent families were identified in patseer, while a total of 46 publications were obtained from scopus and 33 from the wos. a further cleaning process homogenised the titles of patents and articles, the names of the authors and inventors and the titles of affiliations or institutions. the cleaning process also eliminated duplicates and those patents and articles that, despite containing the terms of the query, were not related to the topic. after this process, a total of 9 published patent families were obtained from patseer and 34 research articles were obtained from scopus and the wos. figure 2 shows the number of publications per year, from 2006 to 2016 (1980 was considered initially, however no information was detected), for each database. the patent families are listed in reverse chronological order in table 1. seven patents were published between 2014 and 2016, one patent in 2010, and the remaining one in 2007. the analysis also showed that the united states has five patents published, making it the most prolific country in the field. from the patents retrieved, only two were closely related to orthoses: ‘methods for integrating sensors and effectors in custom three-dimensional orthosis’ from turkey and ‘systems and methods for generating orthotic device models by surface mapping and extrusion’ from the united states. only one author published more than one patent: james schroeder, whose patents were published in 2007 and 2010 and are related to the customization of implants, prostheses, and surgical instruments and methods of manufacture. of the 34 research articles from scopus and the wos, 24 were about developing dynamic orthoses or exoskeletons for rehabilitation, and only ten were related to static orthoses. as a preliminary result, it was observed that the article with the most citations was a. m. j. paterson’s, published in 2010 (paterson et al. 2010): ‘a review of existing anatomical data capture methods to support the mass customisation of wrist splints.’ a further bibliographic network map (figure 3) was generated to visualize the connection between the publications and their references, and to carry out bibliographic coupling. the map was plotted in gephitm, using the force atlas algorithm. this algorithm is commonly used to emphasise complementarities and to spatialise networks with a small amount of data (bastian et al. 2009; jacomy et al. 2014). figure 3 shows the network map of the documents and their references, where the size of the nodes is proportional to the indegree parameter, which displays the number of citations each document has (gmür 2003) and thus identifies highly cited publications. on the other hand, the outdegree parameter is proportional to the number of references contained in each document. figure 2 publications and patents per year for the wos, scopus, and patseer. 36 table 1 patent families gathered from the patent search in patseer. patent no (pub. date) title assignee inventor priority country br102014029649a2 (31 may 2016) manufacturing process articulated prostheses from a combination of rigid and flexible material in one piece (gomes da fonsêca et al. 2016.) fundaçao universidade de brasilía gabriela freitas gomes da fonsêca,jeferson andris lima lopes, jorge ribeiro cunha da silva, lucas coelho de almeida, marcelino monteiro de andrade brazil wo2016071773a2 (12 may 2016) methods for integrating sensors and effectors in custom three-dimensional orthosis (karasahin 2016) deniz karasahin deniz karasahin turkey us2016101571a1 (14 apr 2016) systems and methods for generating orthotic device models by surface mapping and extrusion ( schouwenburg et al. 2016) sols systems inc. kegan l. schouwenburg, daniel bersak, jeff smith, ciaran n. murphy united states us2015328840a1 (19 nov 2015) use of additive manufacturing processes in the manufacture of custom wearable and/or implantable medical devices ( zachariasen and cropper 2015) joseph t. zachariasen dean e. cropper joseph t. zachariasen, dean e. cropper united states wo2015095459a1 (25 june 2015) robotic finger exoskeleton ( deshpande and agarwal 2015) board of regents, the u. of texas system ashish deshpande, priyanshu agarwal united states jp2014533975a (18 dec 2014) customisable embedded sensors (ranky and mavroidis 2014) northeastern university richard ranky constantinos mavroidis richard ranky, constantinos mavroidis japan cn203935304u (12 nov 2014) novel bionic exoskeleton artificial limb controlled by cable wires (xiogjiao et al. 2014) xing xiongjiao yuan ning zheng haolin xing xiongjiao, yuan ning, zheng haolin china wo2010120990a1 (21 oct 2010) personalized fit and functional designed medical prostheses and surgical instruments and methods for making (schroeder 2010) james schroeder james schroeder united states wo2007045000a2 (19 apr 2007) personal fit medical implants and orthopaedic surgical instruments and methods for making (goodman et al. 2007) steven l. goodman, kyujung kim james schroeder vantus technology corp. steven l. goodman, kyujung, james schroeder, vantus technology corp. united states these categories have the highest frequency of occurrence. patents, letters, notes and standards were also cited in the documents obtained, but so infrequently that they are barely visible on the map. the higher numbers of nodes are for publications related to dynamic hand orthoses, as seen in figure 3. however, the analysis showed that bibliographic information related to am of dynamic hand orthoses came mostly from conference papers (80 percent), and the majority did not have citations up to 31 december 2016. the documents related to static orthoses were mostly journal articles, 37 and only ten percent were conference papers. these documents and their references are circled in figure 3. the lack of interaction between publications related to dynamic orthoses and those for static orthoses can also be seen in figure 3. only one such connection can be noted: ‘hopkinson (2006)’ (hopkinson et al. 2005), which is shown in light green, on the far-right side in the middle of the map. this single connection was cited by paterson et al. (2014) from the set of static orthoses and by madden and deshpande (2015) from dynamic orthoses. the most cited author from the analysed documents was paterson, who published four pieces across a six-year period: paterson et al. (2010), paterson et al. 2012), paterson et al. (2014) and paterson et al. (2015). these publications discussed methods for image capturing and fabricating orthoses using 3d printing. additionally, the betweenness centrality was estimated to identify the authors with more influence on the topic. this parameter is often used to grade nodes on network maps according to their spatial position, based on the number of shortest paths between two nodes that pass through a particular node (brandes 2001). for instance, a node has a high betweenness centrality if it connects different parts of the network to each other, like a train station—different trains from different places running through one centralized station. from the information retrieved, only eight nodes had a betweenness centrality value (table 2), while the value for the other nodes was zero. these eight nodes have an actual betweenness centrality value because they connect, not only to nodes of references, but also to some of the different publications retrieved. it should be noticed that paterson is displayed three times in this list—with values of 189.0, 130.0 and 34.5—which shows the notable influence of the author on the flow of the knowledge network. figure 3 bibliographic network map based on the indegree parameter and kind of document. the colours indicate document type. magenta = papers, dark green = conference papers, blue = websites, grey = manuals, orange = reviews, light green = books, turquoise = theses. the size of the nodes are proportional to their indegree parameters. 38 table 2 weighted indegree, weighted outdegree, and betweenness centrality of the eight nodes with a betweenness centrality value. times cited = times cited in retrieved documents only. publication label weighted indegree weighted outdegree times cited betweenness centrality paterson (2010) (paterson et al. 2010) 5.0 33.0 5 189.0 paterson (2012) ( paterson et al. 2012) 3.0 41.0 3 130.0 madden (2015) (madden and deshpande 2015) 1.0 27.0 1 44.0 weiss (2013) (weiss et al. 2013) 1.0 23.0 1 41.0 palousek (2014) (palousek et al. 2014) 3.0 15.0 3 34.5 paterson (2015) ( paterson et al. 2015) 1.0 44.0 1 34.5 velho (2011) (velho and zavaglia 2011) 1.0 11.0 1 11.0 tang (2013) (tang et al. 2013) 1.0 12.0 1 8.0 figure 4 shows the map of the bibliographic coupling carried out among the publications about static hand orthoses, while figure 5 shows the map of bibliographic coupling for dynamic hand orthoses. in both figures, the size and colour of the nodes are proportional to their indegree parameters; the higher the value, the bigger and darker the node. similarly, the citations received by each node are represented by incoming arrows, while the outgoing arrows are connected to the citing documents. the bibliographic coupling analysis observed that the highest number of coupled cites was 12, between paterson et al. (2014), shown on the right side of the map in figure 4, and paterson et al., (2015), located in the map’s upper corner. however, though the number of shared references was high, these sources were selected by the same author and were, thus, negated for our research purposes. the second set of documents coupled were paterson et al. (2015) and palousek et al. (2014), with four citations in common (namely, faustini et al. (2008), cook et al. (2010), mavroidis et al. (2011) and paterson et al. (2010)), as in figure 4. both paterson (2015) and palousek (2014) described methods for designing customised splints using 3d printing, while the cited papers from faustini (2008), cook (2010), and mavroidis (2011) dealt with the use of am for foot orthoses, serving as referents for figure 4 bibliographic coupling for publications in static orthoses for the hand. figure 5 bibliographic coupling for publications in dynamic orthoses for the hand. 39 researching methods applicable to personalised hand orthoses. for dynamic orthoses, there was a reduced number of papers coupled with their references. this was because there were no documents sharing more than two resources. as this resulted in a bibliographic coupling of less impact, the most cited documents were listed instead. table 3 lists the documents with more citations (4-5). from the documents listed in table 3, paterson et al. (2010) was the only one from the set of static hand orthoses, and this document was published by the institution with the most articles on the subject, loughborough university. the number of institutions with most publications was found to be limited. despite this, loughborough university had the most publications (four papers), followed by the national university of singapore and shanghai jiao tong university, with two articles each. 4. discussion this study applied the scientometric tools of bibliographic occurrence, bibliographic coupling and collaboration network analysis to identify the institutions working on the development of hand orthoses using am. results revealed that the implementation of am for developing personalised hand orthoses is not present in a high number of publications and collaboration between different institutions to publish jointly is rare. from the 34 scientific publications detected, a total of 42 affiliations were identified. a network map analysis was carried out using gephitm, in which only the affiliations with documents cited at least once were considered. this resulted in 20 affiliations. the highest number of affiliations working collaboratively was three: loughborough university coauthored with the university of manchester (paterson et al. 2015) and the royal derby hospital (paterson et al., 2014). this was considered an important collaboration, not only for the number of affiliations involved, but because one of them is a medical institution. a second collaboration with a medical affiliation was found in australia, where curtin university’s school of physiotherapy and exercise science partnered with the mechanical engineering department. these, however, were the only multidisciplinary collaborations the analysis discovered. the limitations of this study lie in the novelty of applying am to medical devices. while the first searches did not produce results when using terms related to dynamic orthoses, this changed after adding exoskeleton terms. exoskeletons provide enormous advantages as, in many cases, they include sensors and electronic systems to improve rehabilitation (iqbal et al. 2010; worsnopp et al. 2007). for this research, a co-citation analysis could not be carried out because of the small number of citations of the documents retrieved. further analyses might embrace a higher number of publications as the application of am in the development of orthopaedic devices is growing quickly. table 3 publications with four or more citations. reference (number of citations) title cited by: paterson et al. 2010 (5) a review of existing anatomical data capture methods to support the mass customisation of wrist splints ( paterson et al. 2012), (palousek et al. 2014), (kim and jeong 2015), ( paterson et al. 2015), (baronio et al. 2016) polygerinos et al. 2014 (5) soft robotic glove for combined assistance and at-home rehabilitation (cincotti et al. 2015), (low et al. 2015), (chin et al. 2016), (yap et al. 2016), (bianchi and buonamici 2016) worsnopp et al. 2007 (5) an actuated finger exoskeleton for hand rehabilitation following stroke (iqbal et al. 2010), (weiss et al. 2013), (tan and robson 2016), (chin et al. 2016), (bataller et al. 2016) bouzit et al. 2002 (4) the rutgers master ii: new design force-feedback glove (winter and bouzit 2006), (iqbal et al. 2010), (velho and zavaglia 2011), (weiss et al. 2013), (tang et al. 2013) schiele and van der helm 2006 (4) kinematic design to improve ergonomics in human machine interaction (reimer et al. 2014), (madden and deshpande 2015), (omarkulov et al. 2016), (bianchi and buonamici 2016) 40 5. conclusion the scientific documents and patents involved in the personalisation of hand orthoses using am were tracked back to 2006 through an enhanced cti analysis using scientometric and network map analysis tools. the main knowledge area involved in this technology was found to be engineering. this information was corroborated in the collaboration analysis, which also disclosed that there has been minor participation of medical affiliations. the analysis uncovered that the relevance of the information retrieved depends highly on the search strategy, which was carried out through the building and testing of different queries that were later validated by experts. despite the low number of publications and patents obtained, the tools used to perform the analysis were useful for identifying main authors, institutions, and collaboration networks. bibliographic occurrence and bibliographic coupling also constituted a valuable resource to understand knowledge diffusion through citations and to determine the dynamic of the research in a specific field. furthermore, network map analyses enabled identification of publishing collaborations among affiliations. the methodology presented in this paper can be implemented to obtain a more complete analysis of the institution’s research dynamics, particularly of emerging technologies. the tools used in this research can be applied over a wide range of areas to better understand the interaction between authors and affiliations, and to identify those most influential in their fields. the proposed method would require future improvement by comparing results with opinions of experts to validate the main outcomes. 6. acknowledgements this work was funded by tecnologico de monterrey through the escuela de ingenieria y ciencias, and it was also supported by a postdoctoral scholarship granted by the mexican national council for science and technology (conacyt). the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 7. conflict of interest the authors declare that they do not have any conflicts of interest. 8. references archibugi, d. and pianta, m. 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(2008). evolution of research activities and intellectual influences in information science 1996-2005: introducing author bibliographic-coupling analysis. journal of the american society for information science and technology, 59(13), 2070-2086. http://doi.org/10.1002/asi.20910 vol8no3paper5 to cite this article: ottonicar, s.l.c., valentim, m.l.p. and mosconi, e. (2018) a competitive intelligence model based on information literacy: organizational competitiveness in the context of the 4th industrial revolution. journal of intelligence studies in business. 8 (3) 55-65. article url: https://ojs.hh.se/index.php/jisib/article/view/329 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a competitive intelligence model based on information literacy: organizational competitiveness in the context of the 4th industrial revolution selma leticia capinzaiki ottonicara*, marta lígia pomim valentima, elaine mosconib ainformation science department, graduate program in information science at sao paulo state university (unesp), marilia, brazil; bbusiness management department, graduate program in business management at université de sherbrooke (udes), sherbrooke, canada *selma.leticia@hotmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: mapping the structure and evolution of jisib: a biblipmetric analysis of articles published in the journal of intelligence studies in business between 2011 and 2017 exploratory study of competitive analysis in mexico eduardo rafael poblano ojinaga pp. 22-31 competitive and technology intelligence to reveal the most influential authors and inter-institutional collaborations on additive manufacturing for hand orthoses journal of intelligence studies in business v ol 8 , n o 3 , 2 0 1 8 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 8, no. 3 2018 leonardo a. garcia-garcia pp. 32-44 and marisela rodríguez characterizing business intelligence tasks, use and users in the workplace. leonardo a. garcia-garcia pp. 45-54 and marisela rodríguez josé ricardo lópez-robles, jose ramón pp. 9-21 otegi-olaso, rubén arcos, nadia karina gamboa-rosales, and hamurabi gamboa-rosales a competitive intelligence model based on information literacy: organizational competitiveness in the context of the 4th industrial revolution selma leticia capinzaiki ottonicar, pp. 55-65 marta lígia pomim valentim, and elaine mosconi a competitive intelligence model based on information literacy: organizational competitiveness in the context of the 4th industrial revolution selma leticia capinzaiki ottonicara*, marta lígia pomim valentima, and elaine mosconib a information science department, graduate program in information science at sao paulo state university (unesp), marilia, brazil; b business management department, graduate program in business management at université de sherbrooke (udes), sherbrooke, canada corresponding author (*): selma.leticia@hotmail.com received 12 may 2018 accepted 20 december 2018 abstract this paper investigated how information literacy and competitive intelligence are connected in business management and information science fields. it demonstrates the contribution of information literacy in the phases of the competitive intelligence process. this paper is relevant, since the model supports creativity and collaborative innovation in small businesses in the context of industry 4.0. furthermore, it contributed to connect the information science and business management fields, so it is multidisciplinary. it also proposes a theoretical model of information literacy and competitive intelligence in the context of industry 4.0, which can be used for applied research. the methodology was developed based on a systematic literature review (slr) of information literature and competitive intelligence. these concepts contribute to the development of a framework and a conceptual model in which the three themes are interconnected and demonstrate that information literacy can efficiently contribute to the competitive intelligence process, especially in the context of the fourth industrial revolution. keywords competitive intelligence; industry 4.0; information literacy; systematic literature review 1. introduction information literacy is understood as lifelong learning (belluzzo and feres, 2015; bruce, 1999; lloyd, 2017) and it is useful to competitive organizations. information literacy enables organizational individuals to better understand information and convert it into knowledge. the knowledge constructed during the professional life contributes to the densification of critical thinking about the consulted information, so individuals can understand their backgrounds (lloyd, 2017). competitive intelligence (ci) is based on scanning and monitoring information that significantly influences the market. in this perspective, the development of ci tools provides organizational individuals with more adequate conditions to face challenges. ci generates analyzed data and information that can be integrated into the organizational business (tisluk et al., 2015). it also provides insights from external contexts, supports decision-making, and contributes to medium and long-term strategies. ci reduces uncertainties about the competitive environment (valentim and souza, 2013). the competitive environment became more complex in the context of industry 4.0, which refers to the 4th industrial revolution. industry 4.0 is related to the digital journal of intelligence studies in business vol. 8, no. 3 (2018) pp. 55-65 open access: freely available at: https://ojs.hh.se/ 56 transformation and many technological drivers that allow organizations to create and innovate their products, services, and processes, whose differentials will be key to remaining in the marketplace (anderl and fleischer, 2015; schwab, 2016). an increased amount of data generated by different technologies becomes available for individuals, but the value creation coming from the usage of data needs more investigation (bordeleau, et al., 2018). moreover, individuals who are involved in this revolution need to know how to intelligently access, evaluate, and use data and information in the ci process in order to improve decision making and better orient business strategy. information literacy is a significant predictor of online information search competencies (çoklar et al., 2016), which is important to access information. however, having information access offers no guarantee that the information will be well evaluated and used by individuals. librarians pointed out the relevance of effective instructions in order to fill gaps in the curriculum and prepare students to improve their skills to get and use valuable information (howard and stonebraker, 2018). considering information literacy is a critical competency in digital age, it can help managers to identify relevant information for decision making in business management. this paper has three purposes: the first one is to investigate how information literacy and ci are connected in the business management and information science fields. the second one is to demonstrate the contribution of information literacy in the phases of the ci process, which supports creativity and collaborative innovation in small businesses in the context of industry 4.0. the third purpose is to propose a theoretical model of information literacy and ci in the context of industry 4.0, which can be used for applied research. in the context of industry 4.0 and digital transformation, a large amount of data and information is generated in all digital activities. managers and employees need to know how to search and use information to construct meaningful knowledge. they can construct knowledge through information literacy. this process also happens with ci professionals because they also need to access external information (ottonicar, 2016). information literacy and ci are relevant elements to industry 4.0 since they allow individuals to access different information sources. this paper is organized as follows. the next section discusses the concepts of information literacy, ci and industry 4.0. the subsequent section explains the methodology and shows some results of the slr. the discussions and results section show the inter-relation between information literacy and ci in the context of industry 4.0. furthermore, it demonstrates a conceptual model that can be applied in business as future research. the conclusions highlight the directions for further research, the limitations of the paper and its relevance to businesses management and information science. 2. theoretical references 2.1 information literacy the information literacy concept emerged parallel to social changes, which resulted from the renewal of means of production. these changes influenced educational systems and libraries, since they are both traditional environments of information storage and dissemination (gomes and dumond, 2016). furthermore, information literacy is fundamental to citizens and to their social integration. this literacy helps people to access, choose, manage and evaluate information (belluzzo and feres, 2015). information literacy is present in different organizations. it is related to individuals’ capabilities and behaviors which were developed in their lives (ottonicar et al., 2016). information literacy is studied in the field of information science, which is interdisciplinary. because of that, information literacy is related to the political, technological, educational and organizational context (ottonicar et al., 2016). furthermore, this literacy is connected to individuals’ experiences, since it shows how they seek, evaluate and create information (demasson et al., 2016). information literacy has become more than individuals’ abilities and skills. bruce et al. (acrl, 2014) demonstrated that information literacy is also relational. it depends on the context studied and described in a complex information environment. the advantage of this approach is the creation of many information literacy models in different fields. according to ala (2016, 3) information literacy is the set of integrated abilities encompassing the reflective discovery of information, the understanding of how information is produced and valued, and the use of information in creating new knowledge and participating ethically in communities of 57 learning. it is also understood as “the ability to think critically and make balanced judgements about any information we find and use. it empowers us as citizens to develop informed views and to engage fully with society” (cilip, 2018). in the context of the workplace, information literacy contributes to employability, and it helps individuals to develop work analysis, solve problems (cilip, 2018) and support efficient decision making (ottonicar, 2016; yafushi, 2015). these studies demonstrate that information literacy research is increasing in the field of business and management (rader, 2002). according to sproles et al. (2013, 409) “information literacy has become an integral part of the library literature and has been adopted and implemented outside the traditional venues of reference and instruction services”. information literacy is fundamental for business processes within organizations (jinadu and kiran, 2014, 2016). strategic, tactical and operational levels can benefit from identifying and using critical knowledge. this knowledge inspires creativity, innovation and competitiveness (ottonicar, 2016). 2.2 competitive intelligence the term competitive intelligence (ci) was coined in 1980 and its purpose was to monitor the external environment. this process allows the integration of information and data in real time and influences decisions that are useful, considering time and speed in data generation nowadays (souza, 2016). information and data are different. data is understood as facts, measurements and statistics. information is defined as the action of informing, and knowledge involves the development of experience through learning. intelligence is the ability to understand and use knowledge practically (bouthillier and shearer, 2003). the main purpose of ci is to access, interpret, evaluate and disseminate information. this information is gathered in the external context of the organization. the analysis of external information is fundamental to the process, since intelligent information contributes to product and service innovation. furthermore, it influences innovation speed and the quality of the final products (hassani and mosconi, 2017). ci is a continuous process, since it has no beginning, middle or end. that process works in a business environment continuously (valentim, 2004). it allows the explanation of data through graphics, charts and tables, so individuals can construct knowledge from that information (teixeira, 2014). other professionals such as business managers also need to understand the opportunities and threats that influence organizations (hoffmann and chemalle, 2006). innovative technologies contribute to ci since a professional can use potential information available in social media and in emergent technologies that are catalyzers of the 4th industrial revolution (hassani and mosconi, 2018). in the past few years, only formal information sources were analyzed, but it is not enough anymore (tisluk et al., 2015; cubillo, 1997). according to jin and ju (2014) the complexity of the task influences the professional to access more information sources, making information literacy fundamental to guide individuals to analyze the quality of these sources. calof (2016, p. 48) explains that: “competitive intelligence assists organizations in developing a proactive approach that identifies and responds to changes in the competitive environmental, helping organizations (companies, governments, universities, associations and others) thrive in turbulent times”. this intelligence is useful for many kinds of organizations. ci has many concepts in both the business management and information science fields. in this paper, ci is understood as a process that is the result of individuals’ actions. professionals need to access and evaluate data to transform it into information. the use of that information allows for knowledge construction, decision making, problem solving and innovation. 2.3 industry 4.0 the first industrial revolution occurred through steam engines in 1784. the second one started in 1870 because the machines worked with electrical power. the third industrial revolution started in 1969 with the arrival of electronics and information technology. this technology evolved and connected to cyberphysical systems (cps), so those connected technologies became more complex. it includes the internet of things (iot) of objects and services. (kagermann et al., 2013). therefore, industry 4.0 is an ongoing process (kagermann et al., 2013). xu et al. (2018, 2942) agree with kagermann et al. (2013), since they emphasize: “during the fourth industrial revolution, the use of cyber 58 physical systems (cps) has triggered a paradigm shift in industries, in particular the manufacturing sector” (xu et al. 2018, 2942). industry 4.0 is a current phenomenon and it will influence the production of society. cps are a fuel that encourages that revolution. cps are objects with software and computer skills, so the products are smart. the objects are based on connectivity and self-management (almada-lobo, 2015). mass production is disappearing; there are more and more customized products based on clients’ needs. the production chain is becoming transparent and its elements are becoming integrated, since the physical fluxes are controlled by digital platforms (almadalobo, 2015). because of that, industry 4.0 will influence business in a positive way, and it can be used in developing countries (silva et al. 2018). in this paper, the iot is not understood as a synonym of industry 4.0, because it involves objects and biological technology. the iot is part of the industry 4.0 processes. the iot allows the dissemination of electronic information between objects. therefore, the family, logistics and public management will be affected by those changes (dutton, 2014). industry 4.0 is transforming individuals’ lives (schwab, 2016), and furthermore, it encourages competitiveness and process improvement (anderl and fleischer, 2015). 3. methodology this methodology was developed based on a systematic literature review (slr) of information literacy and ci (sampaio and mancini, 2007; cook and mulrow, 1998). the primary study is the first step of the slr, in which we analyzed the title and the keywords of papers. they were “information literacy” and “competitive intelligence”. table 1 shows the protocol of the slr followed by the authors to get the results. table 1 – the connection between information literacy, competitive intelligence and industry 4.0. the information on literacy standards, indicators and expected results developed by belluzzo (2007), the steps of competitive intelligence based on concepts and results of industry 4.0 to business and society. this table allowed to connect these three themes, and also demonstrate the importance of competitive intelligence based on information literacy. therefore, information literacy can help in every step of competitive intelligence, so information can be gathered in a more effective way. information literacy contribute to competitive intelligence because it helps individuals to find quality information and evaluate the information source critically. the context of industry 4.0 ci steps information literacy standards, indicators and expected results the context provides a lot of information identify the niches of external and internal intelligence. s1 individuals identify the nature and extent of the information need. i. 1.1 define and recognise information need; i. 1.2 identify a variety of formats and potential information sources; i. 1.3 consider the costs and benefits of information acquisition; smart and connected technology emergence, such as smart factory prospect, access and gather data, information and knowledge in the internal and external context of the organization. s2 individuals access needed information effectively; i. 2.1 select the appropriate research methods or information systems; i. 2.2 construct and implement search strategies established effectively; i. 2.3 seek information electronically or with people. use a variety of methods; i. 2.4 rework and improves the search strategy when it is needed; i. 2.5 extract, register and manage information and its sources. the information sources are humans, technology, biological and digital elements select and filter data, information and knowledge relevant to people and organizations s3 individuals evaluate information and its sources critically; i. 3.1 demonstrate knowledge about the information gathered; i. 3.2 apply evaluation criteria to information and its sources; the smart technology transforms data in information adding value to the information treat and add value to data, information and knowledge i. 3.3 compare the new knowledge of the previous knowledge to determine the value added, contradictions, or other characteristics of information; new systems of information storage in groups of technology in real time store data, information and knowledge through technology focusing on quality and safety s4 individuals use information effectively to reach a goal or a result individually or in a group; i. 4.1 individuals are capable of synthesising information to complete a project, activity or task; the smart technology and factory share information in a massive way disseminate data, information and knowledge through services and high valueadded products r. 4.1.2 understand how to use an author’s citations, paraphrases or texts to support ideas and arguments. this item is used for writing activities, reports, documents and manuals; i. 4.2 communicate the results of the projects, activities or work effectively; r. 4.2.1 use documentation norms and formats properly to develop a project, activity or work task. the smart technology and factory bring new issues to be debated. for example, the disappearing of some professions and unemployment create mechanisms of feedback to generate new data, information and knowledge s5 individuals understand economic, legal and social issues of information use. also, they access and use information ethically and legally. i. 5.1 understand the legal, ethical and socioeconomic issues which involve information, communication and technology; i. 5.2 respect laws, rules, institutional policies and guidelines related to information access and information source use. i. 5.3 indicate the information source in the communication of results; 59 the downloaded papers fulfilled the inclusion and exclusion criteria described in table 1. the search terms constructed used the keywords described in table 1. after the transcription of keywords in search mechanisms, we read the title and keywords to apply the inclusion and exclusion criteria. extracted information referred to contributions of information science and business management in the competitive context. the information search was performed in five databases: scopus, web of science, proquest library and information science abstracts (lisa), proquest central and ebsco library, and information science and technology abstracts (lista). table 2 results of rsl. the quantitative results of the systematic literature review. the papers were found in 4 data bases: scopus, web of science, proquest library and information science abstracts (lisa), proquest central and ebsco library, information science and technology abstracts (lista). the first column shows the names of the data bases, and the second one shows the numbers of papers found. after an analysis of the title and key words, we showed the quantitative results. after, the authors read the abstract and selected the papers that studied both information literacy and competitive intelligence in a multidisciplinary perspective. articles database total found chosen (based on title, keywords) total (after abstract review) scopus 42 10 3 web of science 0 0 0 proquest (lisa) 161 58 2 proquest central 39 16 0 ebsco (lista) 65 3 2 in the second phase of the slr we analyzed the content of the abstract to identify information literacy and ci in a business context. most papers that were selected referred to libraries and students, and only a few focused on business or innovation. the slr found a total of 7 articles related to the theme published in academic journals. in the end, there were only 4 articles, because three of them were duplicated. the slr shows that information literacy and ci are not studied very often by researchers. there is a gap of knowledge about the theme, especially in the context of industry 4.0. 4. results and discussion the connection between ci and information literacy is fundamental to competitive businesses (ottonicar, 2016; silva et al. 2016, ottonicar et al., 2018). this happens because information literacy guides the ci process (teixeira, 2014) and focuses on quality information and its sources. the ci process contributes to organizational survival in the market (tarapanoff et al. 2016; souza, 2016; teixeira, 2014). companies are essential to the economy of a country (porter, 1998), since they create wealth and employ people. small businesses need to develop processes to add value to products and services, so they can use ci (hassani and mosconi, 2016; hoffmann and chemalle, 2006) based on information literacy (silva et al. 2016; ottonicar et al, 2018) to achieve competitiveness, as well as larger companies. the paper “how information literate are you?” is a self-assessment by students enrolled in a ci elective authored by barbie e. keiser. the text was published in the journal of business and finance librarianship in 2016. this paper studied students’ information literacy in a ci course. the results demonstrated the use of information literacy to learn and develop skills influenced by the information behavior of students (keiser, 2016). the paper was focused on the field of education, but it was considered in the slr because the appropriate information literacy can be used by individuals who work with ci processes. furthermore, the paper values the librarian profession as fundamental to information access, especially in companies. the paper also pointed out that students have difficulties to learn which information can help them to face challenges (keiser, 2016). the second paper perceived environmental uncertainty, information literacy and environmental scanning towards a refined framework focuses on the context of businesses and uses the term environmental scanning, which is also understood as ci. it was written by zhang et al. and it was published by information research in 2012 (zhang et al., 2012). forty-two travel agents in singapore answered the questionnaire. the authors found out that information literacy is fundamental to the steps of ci. furthermore, they showed that information quality is not related to information quantity. the quality of information is based on the process, 60 organization, dissemination and evaluation in an effective way (zhang et al., 2012). these same authors also published another two papers that are based on information literacy in the context of businesses and environmental scanning. the first paper, entitled the role of information literacy in environmental scanning as a strategic information system a study of singapore smes, was published in 2010. zhang et al. (2010) explained the importance of information literacy to business management in a practical context. in that paper, environmental scanning is understood as a strategic information system and they discuss information literacy in small and medium-size companies. they researched smes in singapore thorough a questionnaire which guided the quantitative analysis and an interview which contributed to a qualitative analysis (zhang et al, 2010). another paper was published in 2010 in the journal of information science with the title environmental scanning: an application of information literacy skills at the workplace. the authors studied information literacy to monitor the external environment of organizations to achieve a competitive advantage (zhang et al. 2010). there are only a few researches that connect the scan of external context and information literacy. furthermore, few researches have studied information literacy as a tool to achieve businesses competitiveness. the authors applied information literacy in every step of environmental scanning. they concluded that scanning can be used by every organizational level, it is not limited by the strategic one (zhang et al., 2010). the slr showed that there are no researchers who focus on ci and information literacy in an interdisciplinary perspective. because of that, this study is fundamental, since it aims to use concepts from information science and business management. we strongly recommend that those fields should work together in order to share knowledge and apply research through research groups and researchers. information literacy needs to be incorporated in the business management field, since studies have demonstrated its relevance to improve processes and competitive advantage (yafushi, 2015; ottonicar, 2016; santos, 2014). other researches have emphasized the applicability of information literacy for decision-making (yafushi, 2015) and for creativity and innovation (ottonicar, 2016; ottonicar et al., 2018). we would like to emphasize the importance of zhang et al.’s work (2012, 2010, 2010) as an international parameter to connect information literacy and ci to others researchers in the field. furthermore, this paper developed an interdisciplinary connection between information literacy and ci to help business in the context of industry 4.0. the results were based on valentim’s (2002) ci steps, since it explains seven main actions developed in this process. belluzzo’s (2007) information literacy standards and indicators were chosen, since it was based on international standards from the international federation of library associations and institutions (ifla). according to valentim (2002), ci has the following steps: identify the niches of internal and external intelligence; prospect, access and gather data, information and knowledge; select and filter data, information and knowledge which are relevant to people and organizations; treat and add value to data, information and knowledge which are mapped and filtered in order to seek interactions language of users and systems; store data, information and knowledge in information technology focusing on quality and safety; disseminate and transfer data, information and knowledge through services and high-value-added products. the goal is to develop people and organizations; create mechanisms of feedback in order to generate new data, information and knowledge to feed back to the system. the information literacy standards and indicators can be used as a tool to evaluate the process. they serve as a guide of the activities developed during the process. the context of the fourth industrial revolution allows physical and biological technology to produce data and information in real time (schwab, 2016). during the ci process, the professional must understand information needs to identify the ‘niche’ of external and internal intelligence (valentim, 2002). therefore, professionals can develop a 61 strategy to define a research topic or information. they verify the value and potential information sources, and they seek information in several formats through a checklist (belluzzo, 2007; ottonicar, 2016). after that, there is information access (ottonicar, 2016). in industry 4.0, access occurs through smart and connected technology. that technology is capable of producing information and disseminating it to other platforms (almada-lobo, 2015). the ci professional needs to prospect and monitor internal and external data (valentim, 2002) which are shared by iot and other tools. the professional selects information systems that are available, observes the type of information in smart technology, creates keywords based on specific vocabulary and uses people, services and other media to access information (belluzzo, 2007; ottonicar, 2016). it is fundamental to be attentive to the information source, because information sources are people, objects and biological technology in the context of industry 4.0. because of that, the professional selects and filters data to create smart information and to contribute to competitiveness (valentim, 2002). the information needs to be created based on the quality of sources. individuals need to read and learn from gathered information, develop criteria to evaluate information sources, observe the hidden intentions and understand the factors that influence information sources such as culture, geography and history (belluzzo, 2007; ottonicar, 2016). there is the information treatment and addition of value in ci (valentim, 2002). therefore, professionals can aggregate their previous knowledge and new information during information seeking (belluzzo, 2007; ottonicar, 2016). they need to understand the language used between the user and system (valentim, 2002), and furthermore, they understand the information dissemination through smart technology. they compare the knowledge constructed with other information, which is a result of different sources to learn a new perspective (belluzzo, 2007). in the context of industry 4.0, systems are integrated and store information together. because of that, professionals understand how to store data securely (valentim, 2002). they synthesize and organize information and also understand smart technology to adjust it based on its structure (belluzzo, 2007; ottonicar, 2016). the convergence of smart technology allows the systems to share information in real time and make people’s lives easier. the ci professional uses those technologies to share smart information in order to contribute to organization members’ decisions (valentim, 2002). therefore, individuals need to understand the ideas developed based on reports, manuals and documents. furthermore, they need to communicate intelligent information through systems and technology. they respect the rules of documentation in businesses (belluzzo, 2007; ottonicar, 2016). the ci professional must know the legal and ethical issues of information use (belluzzo, 2007; ottonicar, 2016). they create new mechanisms of feedback to retrieve smart and ethical information in the future (valentim, 2002). after the professional understands the context, he or she can realize the impacts of actions on competitiveness, innovation and creativity. in industry 4.0, technology has been replacing some jobs, especially the ones that can be replaced by smart machines. an individual who works with ci understands the impact of the profession on society. therefore, information must be made available in an ethical and legal way. the connection shown in figure 1 allowed the construction of a theoretical model to demonstrate how information literacy can contribute to every step of competitive intelligence in the context of industry 4.0. information literacy is present in every step of the ci process, so it can contribute and guide this process during the new changes resulting from iot and other technologies of industry 4.0. the first phase of the ci process is to identify the ‘niche’ of internal and external intelligence. that is equivalent to the ‘information need’ phase of information literacy. professionals need to observe the information they need to explain the context of the organization and competitors in terms of production, services and competitiveness. in the context of industry 4.0 there is a lot of information available through technology, so the challenge is to identify information needs. the next step is the storage of accessed information in physical and biological technology. the purpose is to know how to access technology and use strategy to find information. the most useful information is 62 chosen and filtered. this process is based on information quality through the evaluation of the source. after that, information is treated and new knowledge is added to it to add value. in that moment, the organization and information systems are connected in every organizational level. the goal of this process is to use information efficiently through creativity, innovation, problem solving and decision making. smart information also needs to be used by other people, so it is disseminated through communication. professionals share information with people and smart systems, following documentation rules. they evaluate the performance of the process and create mechanisms of feedback in order to criticize the ci process. therefore, individuals need to understand the economic, social and legal results of that process to smart organizations. 5. conclusions the slr showed that information literacy and ci need the development of interdisciplinary studies between information science and business management. the concept of information literacy should be studied in the business management field in order to develop practical studies. this literature review showed that the theme is emergent, so both fields can improve their body of knowledge. the information literacy standards and indicators can be useful in the ci steps, especially in the context of industry 4.0. in that context, biological and physical technology are the main sources of information to understand the demands and variations of the market, as well as the main channels of communication and dissemination of their products and services. businesses that use information literacy and ci can find market opportunities in the 4th industrial revolution. the model of information literacy and ci in the context of industry 4.0 can guide both small and large businesses to have better information quality. information quality is essential to solve problems and take decisions in an effective way. managers may work based on information literacy concepts and standards, especially when monitoring competitors. therefore, reliable information can contribute to decision making, problem solving and innovation. future research may use the model as a guide to develop a practical study, for example, creating a ci process based on information literacy to encourage innovation and creativity. furthermore, academics may investigate if the technology of ci will be capable of analysing the information source. researchers may analyze this gap of information literacy. artificial intelligence modernized some figure 1 competitive intelligence and information literacy in industry 4.0. information literacy is represented by the standards and indicators in yellow, and the steps of ci are demonstrated in green. this shows a conceptual model that can be used by business and competitive intelligence professionals to guide the information seeking process about competitors. there are 7 green rectangles that represent competitive intelligence. the yellow contains information literacy standards, indicators and results based on the table 3 (third column). industry 4.0 is represented as the context in which firms operate nowadays. the words around industry 4.0 represent keywords extracted from the first column of the table 3. these words can be connected to a technology, a process of the consequences of transformation to society. 63 technologies, so maybe it will be capable of doing ci. also, managers can use information literacy models and adapt them into their context, especially in developing countries. future studies could address this aspect and adapt tools such as trails 9 (syazillah et al., 2018), which guides the translation and adaption of information literacy models. 6. funding we would like to thank the coordenação de aperfeiçoamento de nível superior (capes) and the fonds de recherche du québec nature et technologie (frqnt) for supporting this research. 7. references american library association (ala). 2018. framework for information literacy for higher education. http://www.ala.org/acrl/standards/ilframewor k almada-lobo, f. 2015. the industry 4.0 revolution and the future of manufacturing execution systems (mes). journal of innovation management, 03 (4), pp. 16-21. anderl, r., and j. fleischer. 2015. guideline industrie 4.0: 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management in a changing world, pp. 95-109. zhang, x.; majid, s.; foo, s. 2012. perceived environmental uncertainty, information literacy and environmental scanning: towards a refined framework. information research, 17 (2). jisib-vol-12_nr-1(2022) (3).pdf journal of intelligence studies in business vol. 12 no. 1 (2022) open access: freely available at: https://ojs.hh.se/ pp. 4–5 expand the scope of competitive intelligence in today’s fast-paced business environment, having a strong understanding of the competitive landscape is more important than ever. as the old saying goes, “knowledge is power,” and this is especially true when it comes to staying ahead of the competition. competitive intelligence is the process of gathering, analyzing, and disseminating information about the products, services, and strategies of a company’s competitors in order to gain a strategic advantage. it involves studying the strengths and weaknesses of competitors, as well as trends and developments in the industry, in order to inform business decisions and strategies. the scope of competitive intelligence is broad, and can include a wide range of activities and sources of information. some common sources of competitive intelligence include public information, such as company websites, press releases, and industry reports, as well as private information, such as sales data, market research, and customer feedback. that can be gained in shaping the environment in which organizations operate. competitive intelligence can also be a valuable tool in the development of a company’s strategic plans and decision-making processes. by providing a comprehensive view of the market and the competition, competitive intelligence can help a company to make more informed decisions about where to allocate its resources and how to position itself for success. recent research shows that competitive intelligence is beginning to cover an ever wider range. source: web of science (14.12.2022) editor’s note vol 12. no. 1 (2022) 5 in this issue, the authors propose to consider various aspects related to the work environment, e.g. emotional intelligence, emotional labor, work stress and burnout. the impact of which can be seen in different ways. the study was conducted to analyze the situation and identify approaches to reduce fraud. a number of studies have been conducted on knowledge management as one of the ways to increase the level of work performance and support the entrepreneurial orientation of companies. by referring to the company’s goal, customers, entrepreneurial orientation can modify and innovate another study was conducted on the impact of information and communication technology on new product competitive advantage and new product vision through the partial mediating role of organizational learning capability. decision making and understanding of ict behavioral approaches and business model innovations. i would like to especially thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, prof. dr. andrejs cekuls university of latvia, latvia editor-in-chief, jisib o p i n i o n s e c t i o n 61 a survey of users’ perspectives and preferences as to the value of jisib a spot-check klaus solberg søilen 1 , 1 school of business and technology, halmstad university, sweden email: klasol@hh.se submitted november 10, accepted november 20, 2014 abstract: the journal of intelligence studies in business (jisib) has performed a survey, or done a spot-check, to learn more about its users at the end of three years of publications. users were found via the journal’s site on linkedin and a web-survey was sent from there as an announcement. 18 respondents answered completely. this was only 3,2% of the total member group, but we still think we can draw a number of conclusion from it, also as compared to feedback gathered during the years. users are looking for more case study material in the articles. there is an even balance between those who think there is too much technical material and too little. the discussion about what languages to publish articles in is likely to continue. it is not given that this should be exclusively english in the future. at the same time publishing non-english articles present a number of challenges. keywords: the journal of intelligence studies in business, jisib, spot-check, annual report 1.0 introduction the journal of intelligence studies in business (jisib) has now existed for three years. during that time it has been accepted to ebsco and scopus. as journal is opens source it is also available over doaj. as its platform it uses the software system open journal system (ojs). the content and format of the journal was much decided based on previous experience with other similar journals. the process to start up the journal took about two years. during that time the available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 2 (2014) 61-66 https://ojs.hh.se/ o p i n i o n s e c t i o n 62 failure with the previous journal was much discussed and a consensus was formed around the possibilities to form a new journal. the most important venues for these discussions were competitive intelligence (ci) conferences. users’ preferences and perspectives were not considered simply because there were none. to find out what users think a survey was conducted. by “users” we refer to a large group then “readers” even though the latter is a more common term for these surveys. many contributors are not necessarily ardent readers of the journal. consultants likewise, may just check out a model in an article. some companies may be interested in the journal more for publicity, etc. similar article are also often referred to as “reader spotchecks” or “report to readers”. 2.0 theory and method there cannot be said to be much relevant theory for this field, as it is highly applied. jisib has previously published an article about a review of two previous ci journals (solberg søilen, k., 2013), but that was by no means an analysis of users or readers. other papers have found that readers want more material that is interesting for practitioners, but also more case studies, for example fairlie, r., & holder, d. (2010). some journals operate with a kind of annual report to readers where surveys are a part, for example sullivan, r. n. (2014). there are many potential dimensions which can be surveyed. anonymous. (2003) lists high marks for "article length," "career applicability," and "timeliness of topics." the survey went out by email to 569 members of the jisib group on linkedin. after 1 week 18 users had responded with complete answers to the survey table. that is a 3,2% response rate. this is a low rate, also considering that the users were well targeted, as all were members of the jisib site on linkedin, and the questions to be answered were few. the introduction letter asked for 5 minutes time from the users. the first four questions were about the value of jisib. answers were given by likert scale of five grades. the second question was about what topics users would like to see in the journal. the third question was about how to improve the quality (not popularity) of the journal. the last quest was about the role the user could imagine playing for the journal, for example to be an author, reviewer or to get involved during conferences. 3.0 results and discussion the average score for “the value of the siib journal to me” was 3,78 which means that most users think that the journal has value to them. the average score for the value of the journal for the development of intelligence studies was even higher, 4,22. this was the highest score for the survey. for the moment there are two other journals which focus specifically on intelligence in business; both are open source. there are also journals on intelligence studies in the political field and of course in the military domain. we do not know if the users are familiar with these or if they thought that the question was only for business related journals. the lowest score was given to the question if the journal was of value to their company/organization, with average of 3,28. even though this was the lowest score it was still positive/above neutral (=3). the second highest score was related to whether or not jisib publishes good science. the average here was 3,89. it is clear that questions 2 and 4 assume the respondents know what good science is. from question 4 we could see that most users were in fact academics and researchers themselves (the survey was anonymous, but here users could write their contact info if they wanted to and many did). many have also contributed directly to the journal. o p i n i o n s e c t i o n 63 table 1: answers on value of jisib the second question was about what topics users would like to see published in the journal. the information given here was very useful and again showed that the users who answered were in many cases at least experts; working with/in intelligence related areas. one response was given two times, which indicated it was same person. the most common request was to publish more case studies. secondly it is not clear whether or not users want to see it related material in the journal, as has been the tendency so far. one user says he is against it, while another user wants to see more on big data. other suggestions include: articles on competitive strategy, more related to developing countries, more critical studies (critical theory) and more articles related to innovation. all of these topics have indeed been covered in the journal. we have also published case studies, including in this issue. one conclusion could be to try to find even more case studies. this has also been requested by ci consultants. there is one problem with critical theory and case studies from a scientific perspective and that is that it tends to become more difficult to be acknowledged as a scientific. in most ratings and evaluations scientific implies a dominance of empirical articles. we have solved this question by divining the articles into articles and “opinions”. in some recent issues the number of “opinion” articles has been rather large. this may be a difficult trade off, as many readers want “opinions” and evaluators/peers want science/empirical material. o p i n i o n s e c t i o n 64 table 2: user preferences as to jisib content the third question was about quality improvement. it is implicit here that a comparison between the answers of question two and three is interesting as it shows if suggested improvements for better quality is the same as the material users want to see more of in the journal. we see that for most part this is not the case. instead there is a list of specific suggestions directly related to quality. the first point is the editing and implicitly the grammar and syntax. this has been a major issue for the journal. if we should reject articles which are not written in proper english we would have to disregard a large amount. this would also have the effect that most articles would be from authors form anglo saxon countries. too a certain extent we have tried to help some authors, but this has also been difficult due to time restraints. we will continue to make efforts to improve this part. another user suggests the invitation of guest editors. this is absolutely a possibility and the same person got an invitation directly, as he has also published with us before and have been active in the community for many years. the next suggestion is to expand the editorial committee. it is quite possible that this can be done, and we will loom into it, but at the same time, few journals have a more diverse editorial committee. in addition jisib has an active co-editor on each continent. committee members are evaluated every second year based on their net contribution. new members will then have the possibility to enter and contribute. it is probably only healthy for the wellbeing of the journal with a certain turnover here. another suggestion is to allow for more articles in more languages. at the start of jisib there was some talk of having a bilingual journal, french and english. it is still an open question. at the same time the language of science tends to be english, even though there are a growing number of articles in other languages, first of all chinese. if we play with the idea of having articles in several other languages it is a question how many of our users would in fact be able to read the articles. one user also wants us to use more appealing images in the articles. this is possible, but normally not associated with scientific articles. it also takes many resources, which we do not have. there are some good exceptions to, like the journals “science“ and “nature”, but these stand in a class by themselves. o p i n i o n s e c t i o n 65 table 3: user perceptions about quality improvements of jisib the last question was more an open invitation to get users more involved with the journal. when the journal started it was clear that it was only going to be possible if a large number of people volunteered with their own free time. this is still the building block for the journal five years down the road. as the survey was anonymous we could not see who sent in the different answers. we used the web service qualitrics to gather the actual data, and it shows the approximate gps coordinate for the ip number only. i personally consider this information not to be acceptable, but did not know about the function before afterwards, as i have used other services before. still it was not possible for us to see who the respondents were. however, in question four the respondents could disclose who he was, and many did. their information is not presented i the table below, which is then more of a figure. many users showed here that they are already active, writing articles, being reviewer and participating at conferences. some users also volunteered to do work (write, review and even edit) which is a great thing for the journal. figure 1: what role users would like to fill in jisib 4.0 conclusion to keep the conclusion short users think the overall value of the journal is high, but they are looking for more case study material in the articles. there is an even balance between those who think there is too much technical material and too little. one conclusion that is not suggested by any one user, but which could be explored is to invite guest editors to publish a whole issue in their own language. there could be a special french issue, as many contributions continue to come from france and a spanish special issue, as we have several contributions from mexico and spain. it could also o p i n i o n s e c t i o n 66 be imagined that we do a portugese issue, to accompany the interest in portugal and brazil. it can be a good idea to do a users survey every three years or so, also to see how the journal changes and to see to what extent it is following recommnedations by users. references anonymous. (2003). journal readers share their opinions. information management journal, 5. fairlie, r., & holder, d. (2010). readers' views: idm journal: survey of readers. journal of direct, data and digital marketing practice, 11(4), 265-267. doi:10.1057/dddmp.2010.8 solberg søilen, k. (2013). an overview of articles on competitive intelligence in jcim and cir. journal of intelligence studies in business vol 3, no 1, pp. 44-58. sullivan, r. n. (2014). 2013 report to readers. financial analysts journal, 70(1), 10. 63 disruptive intelligence how to gather information to deal with disruptive innovations dirk vriens 1 , klaus solberg søilen 2 1 radboud university, netherlands email: d.vriens@fm.ru.nl 2 halmstad university, sweden email: klasol@hh.se received november 15, accepted december 5 2014 abstract: disruptive innovations are innovations that have the capacity to transform a whole business into one with products that are more accessible and affordable (cf. christensen et al. 2009). as christensen et al. argue no business is immune to such disruptive innovations. if these authors are right, it might be relevant to be able to recognize these innovations before they disrupt a business. incumbents may use this information to protect their business and others may use it to participate in the disruption. either way, gathering information about potential disruptive innovations is a relevant activity. the production of this information (we call this information “disruptive intelligence”) is the topic of this paper. in particular, we analyze disruptive innovation theory and formulate several intelligence topics which may help in predicting disruptive innovations. in addition, we formulate several ‘biases’ which may impair the production of ‘disruptive intelligence’. keywords: disruptive intelligence, disruptive innovation, business models, disruptive blindness available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 3 (2014) 63-78 mailto:d.vriens@fm.ru.nl mailto:klasol@hh.se https://ojs.hh.se/ 64 1. introduction disruptive innovations are innovations that have the capacity to transform a whole business into one with products that are more affordable, convenient and accessible (cf. christensen et al. 2009). the idea of “disruptive innovation” (and its related theory) was developed by christensen and colleagues (e.g. christensen, 1997, christensen and raynor (2003), christensen (2006), christensen, grossman and hwang (2009) christensen and eyring, (2011)) and has attracted attention by scholars and practitioners alike. a disruptive innovation, as christensen defines it, is initially a new product or service with inferior performance on the attributes most appreciated by mainstream customers of the old product or service and, hence, it doesn’t appeal to these customers. it does, however, attract the less demanding, more price sensitive customers of the old product and/or customers who value the innovation’s other performance attributes. in time, the innovation improves in such a way that it also appeals to mainstream customers of the old product (cf. christensen and raynor, 2003; christensen et al., 2009, govindarajan and kopalle, 2006b or schmidt and druehl, 2008 for a similar description of disruptive innovations). as pointed out by christensen (christensen 1997; christensen and raynor, 2003 or christensen et al., 2009) “[…]incumbent firms often fail to recognize the threat posed by a disruptive innovation.” (schmidt and druehl, 2008). as disruptive innovations target “less profitable customers in less attractive tiers of the markets” (christensen et al. 2002, p. 23) or even nonconsumers of the old product, incumbents lack the motivation to compete. the effect is often that incumbents, when the disruptive innovation has evolved into a product that appeals to their mainstream customers, are too late to react and may even lose the competitive struggle. in such a case a disruption of the business has occurred. christensen and his colleagues give many examples of disruptive innovations that had a dramatic impact on incumbents. for instance, in the 1950s sony’s portable transistor radio disrupted the then existing radio-business; in the 1970s the mainframe business was disrupted by the invention of the micro-processor enabling the production of pc’s; amazon.com has (to some degree) disrupted the traditional bookstores and ebay disrupted (to some extent) the traditional auction-business (examples taken from christensen et al. 2003, who provide an extensive list of disruptive companies – e.g. pp. 56-65). as christensen et al. (2009) argue, no business is immune to disruptive innovations. if this is true, then, of course, it is of utmost relevance to be able to recognize these innovations before they start to disrupt a business. this is true for incumbents who may want to prevent their demise and for those who want to launch or participate in disruptive innovations. either way, gathering information about actual or potential disruptive innovations is a highly relevant activity – a notion that has been put forward by other authors as well (e.g. christensen et al., 2002; adner, 2002; paap and katz, 2004, danneels, 2006; schmidt and druehl, 2008). we call this information “disruptive intelligence” and the main question for this paper is how to produce such intelligence. to understand the production of disruptive intelligence, it is necessary to understand the nature of disruptive innovations. that is, we need to understand what a disruptive innovation is (which is a difficult task in itself, as danneels (2006) points out) and, as adner, 2002, noted, we need “… an understanding of the conditions that give rise to disruptive technologies […]” (p. 667). based on “disruptive innovation theory” as developed over the past decades we can gain such understanding and use it to guide the production of disruptive intelligence. it should be noted that gaining insight into information needed to deal with disruptive innovations is a topic that has already been addressed by several authors (e.g., paap and katz, 2004; christensen et al., 2002, christensen et al., 2003). however, since these attempts, disruptive innovation theory has matured (cf. christensen 2006 about the development of the theory, and christensen et al., 2009 for an updated version). in newer versions the understanding of the relevant characteristics of disruptive innovations and their drivers has evolved. based on this improved understanding we are able to give an updated version of the required “disruptive intelligence”. the main question of our paper is important, not only because of its relevance for strategy formulation (fighting or engaging in disruption), but also because a systematic, up-to-date attempt at answering it seems to be lacking in the existing literature. 65 to deal with the question of producing disruptive intelligence, this paper is organized as follows. first, we summarize disruptive innovation theory (section 2). this will present us with a description of disruptive innovations and with an overview of their drivers. in section 3, we use relevant aspects from disruptive intelligence theory to discuss three important topics related to the production of disruptive intelligence: (1) how do we know whether a market is prone for disruption? (2) how do we know whether disruption is going on?, and (3) how can we prevent blind spots in gathering disruptive intelligence? 2. disruptive innovation theory to understand how intelligence needed to deal with disruptive innovations can be produced, we first need to describe disruptive innovations in some more detail. in particular, based on an understanding of (1) the concept of disruptive innovations and (2) their drivers we will be in a position to direct intelligence efforts. this section discusses disruptive innovations and their drivers based on disruptive innovation theory as it has been developed over the last twenty years. section 3 will go into disruptive intelligence. 2.1 disruptive innovations to explain what disruptive innovations are, christensen often starts with explaining so-called sustaining innovations (e.g. christensen et al., 2003; christensen et al., 2009). a sustaining innovation is an innovation that improves the performance of an existing product or service “[…] with success measured along dimensions historically valued by their customers” (christensen et al., 2009, p. 4). these innovations set out to improve the performance on the attributes valued by mainstream customers (cf. govindarajan and kopalle, 2006b, p. 27). typical examples are innovations leading to faster cars, disk drives with better storage capacity, or radio’s and tv’s of better quality (cf. ch 2003; 2009) as christensen explains, a series of sustaining innovations typically results in products and services that “over-serve” costumers they lead to a performance that most customers can no longer utilize (christensen et al., 2009, p 5). at some point, for instance, faster cars don’t really make sense given the constraining circumstances for using this speed (christensen et al., 2003, p. 32-33; christensen et al., 2009, p. 4). as the market for particular customers can be divided into different tiers, christensen et al., (2003, p. 33) explains that the degree of over-serving is different for each tier. typically, the low-end, less demanding and/or price sensitive part of the market may be “over-served” sooner than the high-end part of the market. the reason for the focus on sustaining innovations is that incumbents “[…] are striving for better products that they can sell for higher profit margins to not-yet-satisfied customers in more demanding tiers of the market” (christensen et al., 2003, p. 34). in all, “[…] a sustaining innovation targets demanding, high-end customers with better performance than what was previously available”. (p. 34). given this explanation, disruptive innovations are contrasted to sustaining innovations. disruptive innovations do not aim to make existing products better, rather, they introduce products that actually underperform compared to existing products (cf. christensen et al., 2003, p. 34). yet, “[…] they offer other benefits – typically they are simpler, more convenient, and less expensive products that appeal to new or less-demanding customers” (christensen et al., 2003, p. 34) and not to mainstream customers. some of the examples christensen and his colleagues provide us with are: disk drives with less storage capacity but increased portability; cheap, portable computing devices with less computing power (early “pc’s”), and cheaper cars with less functionalities. as christensen et al., 2009 argue, these disruptive innovations offer “affordability, accessibility and convenience” over the performance attributes that are valued by the mainstream customers. now, as disruptive products gradually improve – due to their own sustaining innovations, they eventually appeal to the mainstream customers of the old product. (christensen et al., 2003; christensen et al., 2009). in terms of the examples christensen provides: personal computers improved up to the point that they appealed to the users of mainframes; transistor radios improved to match the quality of the large vacuum tube radios, the storage capacity of portable disk drives increased to match the performance of their less portable predecessors. the improvement of a disruptive product may eventually lead to a disruption of the business: which starts to occur when mainstream customers prefer the new product. in his earlier work, christensen et al. made a distinction between “new market disruptions” and 66 “low-end disruptions” (christensen et al., 2003). a low end disruption targets at the low end tiers of the market – costumers who are less demanding and more price sensitive. these are the customers with a high degree of “over-serving” who are quite willing to buy a product with less functionalities – they would buy less powerful cars; disk drives with less storage capacity, pc’s with less processing speed, etc. gradually, the product improves “from the lowend up” and starts appealing to more demanding tiers of the market. a typical feature of low-end disruptions is that they “grow by picking off the least attractive of the established firms’ customers”. (christensen et al., 2003, p. 46). christensen discusses the example of “so-called steel minimills”, mills that were able to produce steel far more efficiently in far smaller settings than the established steel mills. at the outset, the new technology enabled these mini-mills to produce steel of a quality that only appealed to the least demanding tier of the market. however, as technology improved, mini-mills were able to produce steel of a quality that also appealed to the more demanding tiers (christensen et al., 2003 pp. 35-39). a new market disruption introduces products that “compete against non-consumption” (christensen et al., 2003, p. 45). that is, they open up for a new market of customers who couldn’t afford the old product and/or who are attracted by the new product’s additional performance attributes. the first portable sony transistor radios were of less quality than the existing “table top” radios. however, their low cost and portability appealed to a new type of customer: teenagers who could now listen to music whenever and wherever they pleased (cf. christensen, et al. 2003, p. 104/5). in general, christensen argues, new customers are attracted by affordability and or additional attributes like accessibility and convenience. in his language: the products enabled new customers to realize a job they wanted to have done, something the old product couldn’t. after a series of sustaining innovations, these products improve and start to appeal to customers of the old product. it should be noted that disruptions can also be “hybrids’ (christensen et al., 2003, p. 47). for instance, the introduction of the cheap toyota corolla (made possible because of toyota’s efficient production-system) is an example of a hybrid as it appealed to low-end “over-served” price-sensitive customers, while it also attracted new customers who previously couldn’t afford a car (christensen et al., 2003, p. 64). an important aspect of christensen’s work is that incumbents fail to react adequately to disruptive innovations. when a low-end disruption occurs, stealing away their less profitable customers, incumbents are often not willing to compete. in such a case, they will be motivated to focus on the more profitable tiers of the market (cf. christensen et al., 2002, p.23) – a reaction they may later regret. when a new-market disruption occurs they may have even more trouble to react, as the product doesn’t even target their existing customers. govindarajan and kopalle (2006b) list several reasons why incumbents have a hard time reacting to disruptive innovations. for instance, the new product does not appeal to mainstream customers because it has a different “package of performance attributes at the time of introduction” (p. 191), and because it performs less on the attributes valued by them; moreover, the new product may be “[…] introduced in an emerging or insignificant niche market” and “[…it…] offers a lower margin” (p. 191). as a result, a recurrent theme in the history of disruptive innovations is that incumbents often realize too late that their business is being disrupted. 2.2 drivers of disruptive innovations after having discussed the idea of disruptive innovation, a next question is how these innovations are brought about. to answer this question christensen et al. (2009) identify three drivers or enablers: a “technological enabler”, a suitable “business model” and an adequate “value network” (2009, p. xx ff). 2.2.1 technological enablers a technological enabler of a disruptive innovation refers to “sophisticated technology whose purpose it is to simplify, it routinizes the solution to problems […] (christensen et al., 2009, p. xx). technology is taken to be a broad concept, as it refers to any “[…] way of combining inputs […] into outputs of greater value” (christensen et al., 2009, p. 1). and if such a “way of combining inputs” is simpler and/or more affordable than the existing technology, then it is a potential enabler for a disruptive innovation. defined this way, a technological can refer to a technical innovation (e.g. the micro-processor – making the task of 67 “computing” simpler and more affordable) or to a specific organizational structure and way of performing tasks (e.g. the toyota production system – making the production of cars more efficient and hence the cars themselves more affordable). a technological enabler can be used to make products simpler, more convenient or more affordable (e.g. the micro-processor enabling the production of personal computers which were much simpler devices than mainframes) and/or it can make the process of production simpler and more cost-efficient and hence, its resulting products more affordable (e.g. the toyota-production system made production more cost-efficient, and as it happened, the micro-processor also simplified the process of design and assembly – christensen et al., 2009). as a final remark, it should be noted that disruptive technology doesn’t always need to be a new technical invention – it can also refer to a new use of existing technology (e.g. using the internet in a way that may disrupt a business, like ebay did according to christensen et al., 2009, p. 31). 2.2.2 business models as enablers of disruptive innovations. in the course of developing disruptive innovation theory, business models became more central (christensen, 2006). in later versions of the theory, it is argued that disruptive innovations can only come about if there is a “supportive” business model. a relevant question then becomes: what is a business model and how does it enable disruption? business models christensen identifies a business model as a particular arrangement of four components: a value proposition, processes, a profit formula and the organization’s resources (cf, stabell & fjeldstad, 1998; christensen et al., 2009, p. 9). a value proposition, in essence, refers to the value offered to customers. it indicates how a product or service may help “[…] customers do more effectively, conveniently, and affordably a job they have been trying to do” (p. 9). although each firm has its own specific value proposition, christensen discusses three types of value propositions (following thompson (1967) and stabell and fjeldstad (1998)). he identifies a “value adding process” (with its basic value proposition to transform inputs into outputs – e.g. retailing, restaurants, or car-manufacturers) a “solution shop” (with its basic value proposition to solve clients’ unstructured problems – e.g. a professional service firm) and a “facilitated network” (with its basic value proposition to link clients / supply and demand – e.g. a bank) 1 . the processes-part of a business model refers to the primary process activities and how they are related (stabell and fjeldstad; 1998) – although christensen et al. define it broader (including the primary and secondary “way[s] of working together to address recurrent tasks in a consistent way” (2009; p. 9, 10). as stabell and fjeldstad (1998) argue, three different types of process-activities and relations can be identified (related to the three types of value propositions discussed above). if a value proposition falls in the class of “value adding process”, its primary process activities are typically those of porter’s value chain: inbound logistics, operations, outbound logistics, marketing and service (porter, 1985, 39-40). these activities are mainly related sequentially and contribute – in sequence – to the final product or service. as thompson (1967) explains, these activities and their sequential ordering make sense if the process is structured; well understood, predictable and/or routine to a considerable degree. if a value proposition aims at dealing with unstructured problems (a solution shop), then the main process activities are diagnosis (problem finding), design (propose a solution to the problem), implementation (of the proposed solution), and evaluation (of the implemented solution) (cf. stabell and fjeldstad, 1998, p. 415). moreover, as these problems are unstructured, the activities are mostly carried out in a “cyclical or spiraling” way (cf. stabell and fjeldstad, 1998, p. 415). that is, carrying out activities is based on the feedback received during or after the execution of activities, and based on that feedback it may be necessary to redo those activities (cf. thompson’s (1967) description of intensive technology). if the value proposition is to link clients (facilitated network), the main primary activities are network promotion, service provisioning and infrastructure operation (stabell and fjeldstad, 1998, p. 415). moreover, as the authors point out, these activities can be carried out in parallel. so, each of the three types of value 1 even though the basic distinctions derive from thompson ‘s technology typology identifying long linked, intensive and mediating technology, we will refer to the three labels used by christensen et al. (2009, p. 20 ff). 68 proposition is related to its own set of processactivities. a profit formula refers (1) to the profit and cost drivers, and (2) to the way customers pay for products and services. with respect to the first aspect of the profit formula, christensen et al. write: that it “[…] defines the required price, markups, gross and net profit margins, asset turn, and volumes necessary to cover profitably the costs […]” (2009, p. 9). it refers, for instance, to the choice to make products in large volumes with low margins or in small volumes with a high margin. christensen further specifies the way customers pay for products and services into three classes: fixed price, fee-for-service and membership fee. again, dependent on the type of value proposition, a particular profit formula is more or less suitable. as a value adding process relates to predictable routine processes, its key profit drivers are (economies of) scale and a fixed price can be charged. similarly, as a solution shop deals with unstructured, hence unpredictable problems, charging a fee-for service is more appropriate moreover, given their unstructured nature, processes cannot profit from capacity utilization made possible by routinization. instead, they depend on the (expensive) human expertise with carrying out unstructured processes. therefore, a key profit driver is the reputation of those involved in the process while a cost driver is their expense (cf. stabell and fjeldstad, 1998). the mediating value proposition may also profit from scale and capacity utilization (as it can, for instance, use the same technical network to connect many clients) and it can and often does supply its services for a membership fee (see christensen et al. 2009, p. 20 ff.). the last element of a business model, as described by christensen et al. 2009, refers to the resources that are employed to carry out the processes and deliver the value proposition – including both human and other resources (tools, ict, machinery, etc.). again, a difference can be made according to the type of value proposition. in a value-adding process the focus is on technology enabling the swift sequential operation of activities (e.g. conveyer-belt technology, or systems optimizing the work-flow) and on low cost human resources. in a solution shop, human expertise is the most valuable asset (although tools and equipment are not unimportant either). in a mediating value proposition the focus is on the infrastructure enabling the network (e.g. ict/internet and those facilitating the network). in all, as stabell and fjeldstad (1998) describe, three basic business models can be identified, each having their own characteristic business model components: (1) a value adding process business model (with as its value proposition: transforming inputs into outputs; with porter’s value chain process-activities, with standardization and economies of scale of profit drivers, charging on a fixed price basis and with the focus on resources enabling standardization and low cost). (2) a solution shop business model (value proposition: solving unstructured problems; process activities related to iteratively dealing with unstructured problems (diagnosing them, designing and implementing solutions and evaluation); relying on expensive experts of good reputation and charging on a fee-forservice basis). (3) a mediating business model (with its value proposition to link clients; process activities related to promote, operate and facilitate the network linking clients; with capacity-utilization of the network as its profit-driver and charging a membership fee). business models as enablers of disruptive innovations after describing business models, it is relevant to discuss how they enable disruption. as christensen argues, disruptive innovations always entail a change in a business model (i.e. a change of one or more of their constituent components). they always entail the change of the value proposition. that is, based on some disruptive technology, a new value proposition is to bring to the market a product or service that can help customers to do more effectively, affordably, conveniently a job they have been trying to do than the products or services that are currently available. this is the case in lowend disruptions, in which the new value proposition is to sell more affordable products with less functionalities to “over-served” customers. it is also the case in new-market disruptions, in which the new value proposition is to target new customers with a product that helps them to do a job that the old product wasn’t able to do. 69 following a change in value proposition, processes and resources should be formulated and aligned to fit the new value proposition. if the new value proposition is to serve the low-end, price sensitive part of the market, the business model typically needs to allow a firm to “compete profitably while pricing at deep discounts” (christensen et al., 2002, p. 26). this, in turn, requires a different profit formula, more efficient processes and/or resources than what incumbents have. a different alignment of business model components is also required if a value proposition targets at new customers with a product having other performance characteristics. in fact, one of the important “lessons” from disruptive innovation theory is that disruption always needs a change in business model. according to christensen, a common theme concerning disruptive innovations is that incumbents are often aware of the disruptive technology but refuse to change their business model, because it is – to them a sound way of making money. the new technology doesn’t serve their mainstream customers as good and profitably as the products they currently produce. so, why change their value proposition, processes and resources? even if the new technology starts to lead to better products taking away customers at the low end of the market – incumbents tend to stick to their business model in the hope to make money by serving the more demanding customers (with sustaining innovations). as christensen (2006) summarizes: “[…] a disruptive innovation is financially unattractive for the leading incumbent to pursue, relative to its profit model and relative to other investments that are competing for the organization’s resources” (p. 49). in other words, a business model may present a form of “disruptive blindness” on the part of incumbents. in fact, christensen’s advice to incumbents, who want to react properly to a disruptive threat, is to start a new business unit with a different business model tied to products with the new disruptive technology. so, disruptive innovations require a change in business model. in this way, they enable disruption. christensen et al. (2009) go on to discuss two different types of disruptive business model change: one in which the type of value propositions stays the same, and one in which the type of value proposition changes. a disruptive business model change that doesn’t lead to a new type of value proposition is one in which a firm either attracts the low end of the existing market or targets at non consumers with a similar type of value proposition but with a different profit formula, different resources or more efficient processes. examples of such a business model change regarding low end disruptions include the steel mini-mills or toyota (see earlier examples). their basic value proposition remained the same (value adding process), but a new processtechnology (efficient mills) or a more efficient way of relating process activities (toyota) made (low end) disruption possible. an example of a change in business model within the same type of value proposition attracting non-consumers might be sony’s transistor radios appealing to a new type of customers: a new market disruption in a business with a “value adding process” value proposition. a business model change can also result in a new business model with a value proposition of a different type – for instance hbo and netflix are currently disrupting the home-video market. until recently, this market was dominated by dvdproducers (with sustaining innovations like blue-ray dvd). hbo and netflix offer customers to watch movies and series whenever they want by offering them access to their network containing movies and series. in essence, their value proposition belongs to the facilitated network type while the dvdproducers had a value-adding process business model. amazon did something similar for the business of selling books, taking it from a value adding process to a facilitated network business, serving the low end of the market according to christensen et al. (2009). christensen et al., 2009, argue that a business model change which succeeds in moving from a solution shop business to a value adding process or a facilitated network business are especially powerful. solution shop value propositions are – given their nature – business models leading to expensive products that can only be made by experts. if a technology becomes available which enables doing solution shop activities in a predictable, routine way, a business may be disrupted. this is so because making these products no longer relies on complex esoteric knowledge and experience of expensive experts, but based on the new technology, it becomes possible to standardize and routinize production, requiring less expertise. an example may be the diagnosis of infections (example adapted from christensen et al., 2009). once, this was the exclusive realm of medical specialists who might determine the type of infection based on trial and error and their vast 70 body of experience. as such it was a solution shop activity. once diagnostic tests became available based on which a range of infections could be determined with certainty – the process of determining infections became much more affordable and accessible. most of these tests can now be administered routinely by less expensive medical staff, taking less time to determine the result (although of course, specialists are still needed if standard tests yield no results). christensen argues that ford did something similar for the automobile industry: by standardizing the process of assembling cars he changed from a solution shop activity to a value adding process (resulting in much cheaper cars). something similar holds for changing from a value adding process business to a facilitated network – which often allows for delivering services at lower production and overhead cost. so, disruptive innovations always need a change in business model, so as to support the potential of the disruptive technology. in the first place, a disruptive innovation always entails a change in value proposition (as simpler, more convenient and/or more affordable products are offered). this change can result in a different type of value proposition. next, a disruptive innovation requires a reformulation and realignment of business model components (relative to the business model of incumbents) so as to make sure that the disruptive product can be brought to the market as a low-end or new-market innovation. in fact, as christensen et al., 2009 argue: to make disruptive innovations succeed, they require their own proper business model (which should be different from the business model of incumbents). in christensen, grossman and hwang, 2009, the above logic of business models as enablers of disruption is further extended. the authors argue that organizations trying to mix different types of business models are at a disadvantage. in such a case, an organization may produce a product requiring solution shop activities and one which can be produced with value adding process activities. if they use the same resources and the same profit formula with respect to both types of products, then the value adding process product may become too expensive. in general, christensen et al. (2009) argue that mixing types of business models in this way often leads to less affordable and accessible products. as a simple example, consider a group of psychologists offering two types of services: tailormade psychological counseling to deal with difficult psychological disorders and more routine services like administering iq-tests. the first type of activity is a solution shop activity requiring expertise and iterative problem solving, while the latter is a routine value adding process activity requiring far less expertise. now, if both types of activities are carried out by the same set of specialists charging a fee for service, the routine activity ends up being relatively expensive. a better idea is to make sure that the two types of activities have their own “business model” – e.g. their own set of resources, activities and profit formula. one line of business would be tied to routine activities (like iq tests). the associated business model has a value adding process proposition, routine and standardized activities, relatively inexpensive personnel and it could charge a fixed price. the other line of business would house the solution shop activities carried out by the more expensive experts. iq tests can become cheaper and experts can focus on delivering complex counseling. both lines of business may improve. although this is a simple example, christensen et al. (2009) explains that “disentangling” business models, as he calls it, and making sure that value propositions of a different type are served by different business models is a powerful way of improving business models (one he uses to “disrupt healthcare institutions”, christensen et al., 2009). by discussing disentangling business models, christensen argues that if you mix business models, you may not reap the benefits of a potentially disruptive innovation. this is a specific reformulation of the adage that “disruptive innovations need their own proper business model” – as discussed above. however, given existing technology, disentangling business models may sometimes itself be a way to make products more affordable and accessible (as the example above shows – and christensen et al., 2009 provide many more in the context of health care disruptions). 2.2.3 a value network as enabler of disruptive innovations a disruptive innovation does not only require disruptive technology and a supportive business model – it also needs a “value network”. a value network is a “commercial infrastructure” […] through which […the disruptive product or service…] is delivered. (christensen et al., 2009, p. xx and p. xxviii). it consists for instance of companies that help to market, produce, sell and 71 provide services for the new product; a network of e.g. producers, suppliers, service-companies, and vendors. selling mainframes, for instance, relied on a different value network than selling pcs (which could, for instance, be sold by retailers). as christensen et al. argue disruption innovations need a fitting (and often different) value network. producing and selling in high volume and low margin (low end disruption) requires a value network aimed at low cost. similarly, attracting new customers (new market disruption) requires at least a value network with access to these new customers. a change in value proposition type (e.g. moving from a value adding process to a facilitated network business) also means a different value network (e.g. one helping to build and maintain the facilitated network instead of one sustaining production processes). to summarize, this section discussed both a description of disruptive innovations (as an innovation leading to more affordable, accessible and convenient products) and their three drivers (technological, business model and value network) – see table 1. in section 3, we use these ideas to discuss disruptive intelligence. table 1: description and drivers of disruptive innovations. 3. disruptive intelligence the goal of this paper is to understand the production of “disruptive intelligence” that is, information that may help to see whether a disruption is possible or whether a business is being disrupted. to structure the discussion of disruptive intelligence, it is helpful to see that the main question concerning disruptive innovations is: is (will) a technological innovation (be) available that can be used, along with an appropriate business model and value network, to bring a product or service to the market that may eventually grow into a product that is more affordable, accessible and/or convenient than the products that are currently available? we will call all information that may help to answer this question (before a business is actually disrupted) “disruptive intelligence”. this intelligence is relevant for incumbents as they may want to protect themselves against and make sure they react adequately to disruptions. it is also relevant for those considering participating in disrupting a business as they may want to know whether a potential disruptive innovation may stand a chance. regarding the production of disruptive intelligence, three related questions are relevant. the first is: are disruptions possible in this business? this question relates to whether a particular business is susceptible to disruption. based on this information it becomes possible to anticipate a possible disruption and pro-actively deal with it. this information is also relevant for those planning a disruptive attack; the prospects of such an attack are of course better in a disruptionprone business. the second question revolves around finding out whether a disruption may currently be happening. have new entrants (or disruptive innovation drivers of disruptive innovations description: an innovation eventually leading to more affordable, accessible and convenient products types: low-end (starting at low end of existing market); new market (attracting nonconsumers of old product) 1. technological innovation (making products or processes simpler) 2. business model ch components value proposition processes -resources -profit formula 3. value network (for making and selling the new products) type of business model -solution shop -value adding process facilitated network 2. business model change 72 incumbents) introduced a disruptive innovation? obviously, the sooner incumbents have this information, the sooner they can react. moreover, for those who are engaged in a disruptive attack, it is relevant to have an idea of the potential competition and whether their innovation is indeed a disruptive innovation. a last question relates to “disruptive myopia” – a bias in the capacity to produce disruptive intelligence. it seeks to make clear whether incumbents (and even the disruptive aggressor) may have (developed) systematic barriers preventing them from seriously answering the two above questions (and hence from discovering disruptive intelligence). below, we will deal with each of these questions and in doing so we will present some intelligence-topics that could be pursued to answer the question. we want to note, however, that we don’t claim that these intelligence topics form a complete list – but we do argue that these topics will help to increase the possibility to deal with disruptions. 3.1 are disruptions possible in this business? finding out whether a business is “disruptionprone” it is relevant for two (related) reasons. the first is that you may want to know whether a business is susceptible to a disruption at all (this knowledge can raise ‘the level of disruption awareness’ – which may help incumbents to be alert and would-be entrants to discover opportunities). the second is that you may want to find out whether a particular innovative idea has a disruptive potential. 3.1.1 is any disruption possible in this business? following christensen and his colleagues, a business may be disrupted if its existing products or services are expensive, difficult to access and/or may not be convenient. christensen et al. hold that “nearly every industry, at their outset […offered products and services…] that only people with a lot of money can afford them, and only people with a lot of expertise can provide or use them.” (2009, p xix). so, nearly every industry was or is disruptionprone. moreover, after a disruption occurs, a business may be disrupted even further… leading to more affordable, and accessible products. so, a first – very crude – indicator of “being disruptive-prone” is the degree to which a business has products or services that are not affordable and inaccessible. with respect to the degree of unaffordability we need to identify whether the products “can only be bought by people with a lot of money. ”here, we need to be careful though, because (as a disrupted business may be disrupted again) “a lot of money” seems to be a relative measure. in disruptive innovation theory, the degree of accessibility relates to several ideas. it sometimes refers to the degree to which a product can be provided by people with a lot of expertise (like eye-surgery once was), sometimes to the degree to which a product can be used by people with a lot of expertise (like mainframe computers), and sometimes to the degree to which customers can get access to a product or service (e.g. if one has to buy it at some central location, or if acquiring it means waiting – like many healthcare services). often, difficult-toprovide and difficult-to-use products have these characteristics because they rely on ‘solution shop’ activities. an innovation transforming these activities into a value-adding process or facilitated network business may be disruptive (e.g. innovations have made certain eye-operations routine-activities decreasing their cost dramatically cf. christensen, 2009). a facilitated network may help to solve problems with acquiring products (e.g. access to films and series via hbo solves going to a retailer). so – a first indicator is the degree to which a business provides expensive and inaccessible products / service. a second indicator refers to the degree to which current products and services help clients to “do a job they have been trying to do” (cf. christensen et al. 2003, christensen et al. 2009). this is an extremely relevant point but also difficult to examine. if an existing product doesn’t help clients to do their job properly – the introduction of a product that does, may disrupt the business. this is, of course, a truism, but as it turns out many companies have a hard time pinning down the job of customers as they often frame their markets in terms of productor client-characteristics (which are categories used by those selling the products), while the “job” “should be the fundamental unit of marketing analysis” (christensen, et al. 2009, p. 11) as it represents that for which “customers hire a product or service”. so, markets shouldn’t (only) be analyzed using lists of productand customer categories as they may miss the job customers hire a product for (this was already pointed out by early intelligence authors, like geroski, 1988). discovering the true “job” requires a different approach than existing marketing techniques. it requires a deep understanding of the life of 73 customers and the role existing products have therein, which calls for a more ethnographic approach in which customers’ socially embedded desires and actions are related to the use of products. a further indicator of a disruption-prone business is the degree to which customers are “over-served’ as christensen et al. 2009 call it. as discussed, this refers to the difference between the functionalities offered by a particular product or service and the functionalities that costumers are able to utilize. the higher this ‘value’, the more susceptible the business is for a low-end disruption. this indicator may even be determined for different tiers of the market; and especially relevant information would be how many of the current customers would be willing to buy a product with less functionalities. another related idea is to determine how many customers would still be interested in buying the product if it was stripped of its non-essential, excess functionalities (some research shows how markets can be approached in this way – e.g. adner, 2002) establishing whether a new market disruption might be possible is difficult as it needs to research the demands and behavior of non-consumers. for a part this overlaps with the indicators stated above for low-end disruptions (as current non-consumers may be non-consumers because they don’t have enough money to buy the product). however, if a product is to appeal to non-consumers for other product characteristics – one needs to find them. this, in turn, means gaining an understanding of the ‘job’ of (non) customers in order to identify possible other contexts of use or competing products. an idea might be to identify groups of non-consumers and ask under which conditions they would use a similar product (again, other authors have put forward “methods” that can be used to identify relevant non-consumers – e.g. geroski, 1988). if such products can be identified (and if these conditions include the use of products with less functionalities than the current ones) it may indicate that a business is disruption-prone. an example in this case would be the discovery that portable radios could be used by teenagers who were happy with them because it meant that they could listen to music whenever and wherever they wanted – which they valued more than quality of the transmission. a related indicator relating to a low-end and new-market disruption may be the degree of saturation of the “dominant product characteristic” – the characteristic most valued by mainstream customers (cf. paap and katz, 2004). the saturation-value is the value above which “more of the characteristic” doesn’t present extra value to a customer (in fact, this value may be one way of operationalizing the degree of “over-serving”). paap and katz (2004) give the example of storagecapacity of disk-drives. at some point it exceeded the capacity that customers could use and valued. hence, they argued, other characteristics may be introduced that can be of value (in the example: the portability of disk-drives). so, the moment saturation is reached, a business may become vulnerable to disruption. in all – to determine whether a business is “ready to be disrupted” one might consider the following indicators: 1. the degree to which a business revolves around expensive products; 2. the degree to which a business revolves around inaccessible products; 3. the degree to which a business delivers products that do not completely fit the “job” customers are trying to do; 4. the degree of “over-serving” of products in a business; 5. the degree to which consumers would be willing to buy the product if it were stripped of its non-essential functionalities; 6. the degree to which other contexts of use can be identified for simpler versions of the product; 7. the degree of saturation of the dominant product-characteristic (relates to 4). 3.1.2 is this innovation potentially disruptive? the above indicators give a general impression of the possibility that a business can be disrupted, creating a certain “disruption-awareness”. the question we now turn to starts off with an idea for an innovation and aims at finding out whether this particular innovation might be a disruptive innovation. in part, this question has already been addressed by christensen et al. (2002, 2003). in these texts, he gives so-called ‘litmus-tests’ for determining whether an innovation is potentially a low end disruption or a new market disruption. here, we briefly summarize these tests, as they may be guiding the production of disruptive intelligence. 74 in a new market situation, christensen et al. (2002) give three tests (1) the innovation must be a simple product appealing to non-consumers (p. 2425) (as the authors write, the apple ii was introduced as a toy for children; ibid p. 25); (2) the innovation should help customers to do a job they have been trying to do “more easily and conveniently” (p. 25). for instance, people have for a long time been trying to get rid of goods they no longer needed (e.g. through garage sales or occasional flee-markets), and applications offering online auctions (e.g. ebay) were a way of helping people to do get rid of their stuff more conveniently, reaching a far larger audience (cf. christensen et al., 2009, p. 31). (3) the innovation should target customers who were unable to do a particular job because of “lack of money or expertise”. (c 2004, p. 24). the online auction-sites offered mentioned above offered the majority of people who could not afford the services of a real auction-company to participate in an auction. (cf. christensen et al., 2003 and christensen et al., 2002, p. 24-25. for the three tests). according to christensen et al. 2002, if an innovation is to bring about a low-end disruption it should pass the following two tests: (1) the degree of “over-serving” should be high enough and (2) it should be possible to make a low-cost business model (“[…] one that enables entrants to compete profitably while pricing at deep discounts” (christensen et al. 2002, p. 26). so – given an innovative product of service (based on some technical driver) the above tests can direct intelligence efforts. but besides these tests, disruptive innovation theory presents more clues to determine whether some innovation may disrupt a business. these clues relate to the possible changes in the business model an innovation may bring about (christensen et al. 2009). for instance, if a particular innovation enables the routinization or standardization of solution shop activities, then a business will most probably be disrupted. something similar holds for an innovation that enables a change to a facilitated network business. a helpful question here is whether an innovation may help customers to help themselves (e.g. by some online or network service). yet another clue relating to business model change is whether a disentanglement of a particular business model (of form of business model innovation, as christensen et al. 2009 call it) may help to offer products or services more affordably. as we discussed earlier, making sure that different types of value propositions are served by different business models can often make products more affordable and accessible. so, disruptive intelligence can entail a form of “business model introspection” with the aim of trying to find out whether disentanglement is possible in your company. so, topics for disruptive intelligence regarding the question whether a particular innovation (either a new product or service or a business model innovation) is potentially disruptive are: 1. “is the innovation a simple product appealing to non-consumers?” 2. “does the innovation allow customers to do a job more easily and conveniently?” 3. “does the innovation target at customers who haven’t been able to do a job themselves because of lack of money or expertise?” these 3 topics are christensen’s (christensen et al., 2002, p. 24-25) “litmus tests” for new market disruptions. 4. does the innovation target at a market in which the current products have a high degree of ‘over-serving?’ 5. can the supportive business model be changed in one that produces at low prices? these 2 topics are christensen’s (christensen et al., 2002, p. 26) “litmus tests” for low-end disruptions. 6. does the innovation make a change in business model type possible (e.g. by routinization or by offering a mediating network)? 7. is it possible to disentangle the current business model? 3.2 is disruption going on? in this section we deal with information that may help to establish whether a business is currently being disrupted; i.e. whether some disruptive innovation has been launched. this is a difficult question: others may introduce some innovation sharing the characteristics of a disruptive innovation (e.g. it may underperform and only appeal to some of your customers) but it may well be that this product just doesn’t turn into a disruptive product. that disruptive innovations 75 have certain characteristics on the outset, doesn’t mean of course, that all innovations sharing these characteristics will be disruptive. the problem of predicting whether an innovation which is launched is potentially disruptive has been noticed by several authors (e.g. christensen et al., 2003; danneels, 2006; govindarajan and kopalle, 2006a, b). yet, based on disruptive innovation theory we feel that some clues may help to increase the possibility of establishing an answer to the question whether a business is being disrupted. first of all, it should be noted that all information gathered to answer the question from the previous section (is our business a disruptiveprone business?) is helpful to answer the question in this section. if we know that we operate in a disruptive-prone business then we need to be extra alert and take threats of disruptive candidates seriously. moreover, if we notice that an innovation has been launched sharing some of the characteristics of a disruptive innovation, we may want to acknowledge whether it passes christensen’s “litmus tests”. if so (combined with knowing that the business is a disruptive-prone market) we should be very alert. on top of this information some other clues may be helpful. for instance, if an innovation seems promising one may expect a certain number of start-up firms (christensen, et al. 2011). what may even be more telling is when an incumbent starts a different business model tailored to this innovation. as christensen et al. argue an incumbent cannot incorporate a disruptive innovation in its current business model; it needs to launch it from a different business model (like ibm who started a separate business unit to produce pcs – cf. christensen et al. 2009). so, information on incumbents starting up a new business unit with a new business model is relevant disruptive intelligence’. an interesting technique for predicting the disruptiveness of an innovation that has been introduced is using s-curves which describe the sales-pattern of most disruptive innovations (e.g. paap and katz, 2004; christensen and eyring, 2011). sales of disruptive innovations usually follow an s-curve pattern, with few, but steadily growing number of sales at the beginning, followed by a abrupt growth in sales, again stabilizing eventually. if sales of a new product have reached the steep part of the s-curve, it may be too late. so, the trick is to predict whether some sales-growth (at the start of the s-curve) will turn into a sudden growth in sales (in the middle of the s-curve). one method that may shed light on this issue is to rescale sales on a logarithmic scale. as christensen (2011, 96) shows, the s-curve then turns into a linegraph based on which it may be easier to see whether the initial sales fit in an s-curve, and hence are predictive of a sudden growth. another relevant indicator has to do with losing tiers in a market. finding out that incumbents have lost the least-demanding low-end tiers of the market and concentrate on the more profitable tiers is a relevant indicator of a disruption. in fact, the more tiers that are lost, the more one can be sure that the innovation is disrupting a business. unfortunately, this information may be a very late warning signal. yet another indicator has to do with a change in value-network. as the disruptive innovation targets at different customers or may entail a change in business model, one may expect a change in firms that are part of the value network. once, for instance, retailers are willing to give the new product a chance, this may signal such a change. one may also expect a growth of start-up firms in the value network. a last indicator we want to mention here is a change in business model of (new) competitors. it may be a sign of disruption if new entrants have a different type of business model, or if competitors disentangle their business model. so, in order to determine whether a business is being disrupted, the following indicators (besides the ones mentioned in the previous section) may be relevant: (1) the number of start-up firms (2) are incumbents starting up a new business unit with respect to the new innovation? (3) are sales of the innovation following the usual pattern of disruptive innovations? (4) are incumbents losing (low-end) tiers of the market? (5) is the value network changing? (6) do new entrants have different (types of) business models? (7) are competitors disentangling their business models? 3.3 do we suffer from disruptive blindness? the last intelligence related topic we want to discuss in this paper is whether a company may have developed systemic biases preventing it to produce disruptive intelligence and act on it. following disruptive intelligence theory, 76 incumbents are often not motivated to react to disruptive attacks as they aim for the least attractive tiers of the market. in the face of such attacks, incumbents are motivated to focus on the more attractive, profitable tiers of the market. moreover, as christensen and raynor, 2003, argue, incumbents favor sustaining innovations as they target at the profitable tiers of the market, and hence, increase (short-term) share-holder appreciation. investments in (uncertain) innovations that target at less profitable tiers simply do not appeal to shareholders. so, the current way of doing business may prevent incumbents to engage in disruptive innovations and often realize that they should have reacted when it’s too late. phrased differently, because their way of doing business is deeply rooted in one particular business model, they fail to see the threat of disruption. this is a common theme in disruptive innovation theory and if incumbents want to protect themselves against disruption, it is relevant to investigate to what extent they suffer from such ‘disruptive blindness’. in this section, we suggest some indicators of this blindness, which can be used to create a certain awareness of existing biases. before we discuss some indicators of “disruptive blindness” we would like to point out that some of the “business blind spots” that were put forward by gilad (1996) in the context of competitive intelligence, can be reframed in terms of the reaction-pattern of incumbents to disruptive innovations. gilad (1996) discusses, for instance, “false or biased assumptions” as a blind spot which may impair strategic decision making. an example he gives is the biased assumption of many large firms that they do not have to pay attention to smaller players on the market. but often, as he describes, large players pay dearly for this blind spot when a small player launches a successful product. based on disruptive innovation theory, it becomes possible to better understand this blind spot. in fact, disruptive innovation theory shows that this assumption may in fact be a valid assumption with respect to sustaining innovations. it also shows that new entrants (often small players) most of the time win the battle for disruptive innovations, because incumbents are stuck to their business model (in which the newly introduced, inferior product, not appealing to their mainstream customers doesn’t make much sense). so, based on disruptive innovation theory it can be understood that “not paying attention to small players” may not be a bias per se, but that it fits a response pattern of incumbents to disruptive innovations. a first indicator of “disruptive myopia” might the answer to the following question: “do we actively try to answer the above two questions (3.1 and 3.2) related to disruptive intelligence?” obviously, if no effort is put in answering these questions, one probably has no clue about whether one operates in a disruptive-prone market, whether particular innovations have a disruptive potential, or whether a disruption may be going on. in fact, in order to produce disruptive intelligence, one needs to make an effort, which should translate itself in an infrastructure related to producing intelligence. it should, for instance, be someone’s responsibility; and time and resources should be made available. not having an infrastructure tailored to producing disruptive intelligence is an indicator of disruptive blindness. another indicator of disruptive blindness relates to the “forces that shape the process of innovation” as christensen and raynor 2003 (p. 9 ff.) describe. as these authors argue, innovative ideas are “sifted and shaped” by middle managers in many organizations, who “typically hesitate to throw their weight behind new product concepts whose market is not assured” (christensen and raynor, 2003, p. 11). they need to be as sure as possible about a product’s potential (as both budget decisions and their career depend on it) and often rely on the feedback of “significant customers”. but as a disruptive innovation often does not appeal to these customers, disruptive ideas tend to be deselected. sustaining innovations, however, do appeal to this set of customers, thus having a tendency of being preferred. so – the process of innovation of incumbents has a bias towards sustaining innovations (and against disruptive ones). to deal with this blindness (i.e. to at least become aware of it) it may be an idea to keep track of the innovative proposals and the reasons for their selection or rejection. this list may indicate the degree to which sustaining innovations are preferred over potentially disruptive ones. and, against the background of knowledge about the degree of disruptive-proneness of a business (e.g. operationalized by the degree of over-serving customers) one may decide whether the actual proportion of sustaining/potentially disruptive ideas is dangerous or not. another idea might be to make sure that reasons for selection/rejection do not only refer to the feedback of significant customers, but also to a kind of ‘disruptive reasoning’. ideally such 77 reasoning includes an (“job-to-be-done”-related) analysis of the appeal of the idea to the low-end of the market or to non-consumers and an analysis of the potential of the product in appealing to mainstream customers. a third indicator relates to the reaction if one is confronted with losing a part of the (low end of) the market. often, as christensen and raynor, 2003, describe, incumbents are quite happy to focus on the more profitable tiers of the market. however, precisely this attitude is an important indicator of disruptive blindness. a fourth bias that incumbents often display may be called the “business cycle fallacy” which roughly goes like this: if business is booming, we don’t need to invest in innovations whose prospect is unclear and if business is in a slump we can’t afford to invest in innovations whose prospect is unclear”. this, again, is a “disruptive innovation de-selection”-mechanism. as christensen et al. 2002 argue it should be the other way around: if things are looking good – see if a separate business unit around a potential disruptive innovation can be set up; if things look bleak, you may well be too late. a last indicator, related to disruptive blindness we want to mention in this section has to do with knowledge about disruptive innovations. the degree to which all involved in the process of innovation has knowledge about disruptive innovations and their drivers is an important indicator of blindness. without such knowledge, one cannot help to fall into the traps of biases deselecting disruptive innovations (cf. christensen et al., 2002, p. 30). 4. conclusion in this paper, the idea of ‘disruptive intelligence’ is presented. basedon disruptive innovation theory, we discussed the nature of disruptive innovations and their drivers. it is apparent that if one wants to deal with the threat (or opportunity) of a business disruptions one needs to produce “disruptive intelligence”. that is, one needs to produce information about (1) whether a particular business is “disruptive-prone” and (2) whether a disruption may be happening. in this paper, which is purely analytical and descriptive, we have provided several indicators that can be helpful in answering these two questions. in fact – these indicators can be taken to be helpful indicators in producing disruptive intelligence. moreover, we discussed some indicators that may reveal if companies are suffering from “disruptive blindness” – i.e. indicators showing that companies may have difficulties producing disruptive intelligence. even though we think that our paper contributes to a more systematic description of the information needed to deal with disruptive innovations, we are not there yet. in particular, the list of indicators can be extended – based on further conceptual and practical explorations. empirical studies should also follow. 5. literature adner, r., 2002, when are technologies disruptive? strategic management journal 23(8): 667-688. christensen, c.m., 1997. the innovator’s dilemma. boston ma: harvard business school press. christensen, c.m., 2006. the ongoing process of building a theory of disruption. journal of product innovation management 23: 39-55. christensen, c.m., and eyring, h.j., 2011, the innovative university. san fransisco (ca): jossey-bass. christensen, c.m., grossman, j.h., and hwang, m.d., 2009, the innovator’s prescription. new york: mcgrawhill. christensen, c.m., johnson, m.w., and rigby, d.k., 2002.. foundations for growth: how to identify and build disruptive new business. mit sloan management review. (spring 2002): 22-31. christensen, c.m., and raynor, m.e., 2003, the innovator’s solution. boston (ma): harvard business school press. danneels, e., 2004, disruptive technology reconsidered: a critique and research agenda. journal of product innovation management 21: 246-258. geroski, p., 1988, thinking creatively about your market: crisps, perfume and business strategy. business strategy review 9(2): 1-10. gilad, b., 1996., business blindspots (2 nd edition). calne (gb): infonortics. govindarajan, v., and kopalle, p.k., 2006a. the usefulness of measuring disruptiveness of innovations ex post in making ex ante predictions. journal of product innovation management 23: 12-18. govindarajan, v., and kopalle, p.k, 2006b. disruptiveness of innovations: measurement and an assessment of reliability and validity. strategic management journal 27: 189-199. 78 paap, j., and katz, r., 2004, anticipating disruptive innovation. research technology management (sept-okt 2004): 13-33. porter, m., 1985, competitive advantage: creating and sustaining superior performance. new york: free press. schmidt, g.m., and druehl, c.t., 2008. when is a disruptive innovation disruptive? journal of product innovation management 25: 347-369. stabell, c.b, and fjeldstad, ø.d., 1998. configuring value for competitive advantage: on chains, shops and networks. strategic management journal 19: 413-437. thompson, j.d., organizations in action. new york: mcgrawhill. issn: 2001-015x v o l 5 , n o 2 ( 2 0 1 5 ) c o n t e n t s g. scott erickson and helen n. rothberg a longitudinal look at strategy, intellectual capital and profit pools pp. 5-13 a.s.a. du toit competitive intelligence research: an investigation of trends in the literature pp. 14-21 amine aziza, mourad oubrich and klaus solberg søilen the impact of crm on qoe: an exploratory study from mobile phone industry in morocco pp. 22-35 lucie šperková, petr škola, tomáš bruckner evaluation of e-word-of-mouth through business intelligence processes in banking domain pp. 36-47 gianita bleoju and alexandru capatina leveraging organizational knowledge vision through strategic intelligence profiling the case of the romanian software industry pp. 48-58 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: prof. dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2015 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), groupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief prof. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg nordic editorial advisory board: prof. svend hollensen, university of south denmark (denmark) prof. göran svensson, markedshøyskolen (norway). t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india associate professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain associate professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, hedin intelligence & strategy consultancy, sweden mourad oubrich, president of ciems, morocco javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, october 15th 2015 e d i t o r i a l n o t e v o l 5 , n o 2 ( 2 0 1 5 ) it is always a pleasure to realize, at the time of writing this editorial note, that the articles published by jisib come from many parts of the world and from many industries. this is not intentionally even though we strive for diversity as we do not know what articles actually make it through the review process for each issue. our rejection rate is now more than 80%. some see that as a sign of quality. in this issue of jisib we publish three articles on intelligence studies presented at the eckm 2015 conference. there is also an article by oubrich et al. presented at the aim 2015 conference. in addition asa du toit gives an updated analysis of the intelligence studies field. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen editor-in-chief halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 editor-in-chief: klaus solberg søilen included in this printed copy: social competitive intelligence: socio-technical themes and values for the networking organization lars degerstedt pp. 5-34 a place for intelligence studies as a scientific discipline klaus solberg søilen pp. 35-46 intelligence as a discipline, not just a practice magnus hoppe pp. 47-56 journal of intelligence studies in business v ol 5 , n o 3 , 2 0 1 5 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 5, no. 3 2015 the journal of intelligence studies in business (jisib) is a double-blind peer reviewed, open access journal published by halmstad university, sweden. its mission is to help facilitate and publish original research, conference proceedings and book reviews. focus and scope the journal includes articles within areas such as competitive intelligence, business intelligence, market intelligence, scientific and technical intelligence and geo-economics. this means that the journal has a managerial as well as an applied technical side (information systems), as these are now well integrated in real life business intelligence solutions. by focusing on business applications, this journal does not compete directly with the journals that deal with library sciences or state and military intelligence studies. topics within the selected study areas should show clear practical implications. open access this journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. there are no costs to authors for publication in the journal. this extends to processing charges (apcs) and submission charges. 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statement is based on cope’s best practice guidelines for journal editors. it outlines the code of conduct for all authors, reviewers and editors involved in the production and publication of material in the journal. an unabridged version of the journal’s ethics statement is available at https://ojs.hh.se/. publication decisions: the editor is responsible for deciding which of the articles submitted to the journal should be published. the editor may be guided by the policies of the journal's editorial board and constrained by such legal requirements as shall then be in force regarding libel, copyright infringement and plagiarism. the editor may confer with other editors or reviewers in making this decision. fair play: an editor will evaluate manuscripts for their intellectual content without regard to race, gender, sexual orientation, religious belief, ethnic origin, citizenship, or political philosophy of the authors. confidentiality: the editor and any editorial staff must not 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not publish manuscripts describing essentially the same research in more than one journal or primary publication. submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behaviour and is unacceptable. acknowledgement of sources: proper acknowledgment of the work of others must always be given. authorship of the paper: authorship should be limited to those who have made a significant contribution to the conception, design, execution, or interpretation of the reported study. the corresponding author should ensure that all appropriate co-authors and no inappropriate co-authors are included on the paper, and that all co-authors have seen and approved the final version of the paper and have agreed to its submission for publication. disclosure and conflicts of interest: all authors should disclose in their manuscript any financial or other substantive conflict of interest that might be construed to influence the results or interpretation of their manuscript. all sources of financial support for the project should be disclosed. fundamental errors in published works: when an author discovers a significant error or inaccuracy in his/her own published work, it is the author’s obligation to promptly notify the journal editor or publisher and cooperate with the editor to retract or correct the paper. archiving this journal utilizes the lockss system to create a distributed archiving system among participating libraries and permits those libraries to create permanent archives of the journal for purposes of preservation and restoration. publisher halmstad university, sweden first published in 2011. issn: 2001-015x. owned by adhou communications ab journal of intelligence studies in business editorial team editor-in-chief prof klaus solberg søilen (sweden), halmstad university founding editors prof henri dou (france), groupe escem prof per jenster (china), nimi honorary editors prof john e. prescott (usa), university of pittsburgh prof bernard dousset (france), toulouse university regional associated editors africa prof adeline du toit (south africa), university of johannesburg america prof g scott erickson (usa), ithaca college asia prof xinzhou xie (china), beijing university europe prof sahib sidhom (france), nancy university nordic prof svend hollensen (denmark), university of south denmark prof goran svensson (norway), markedshøyskolen editorial board prof karim baina, école nationale supérieure d'informatique et d'analyse des systèmes, morocco dr eduardo flores bermudez, bayer schering pharma ag, germany assoc prof jonathan calof, telfer school of management, university of ottawa, canada prof blaise cronin, indiana university, usa dr sbnir ranjan das, university of petroleum & energy studies, india prof henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france prof bernard dousset, toulouse university, france prof adeline du tout, university of johannesburg, south africa prof g scott erickson, ithaca college, usa prof pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assoc prof per frankelius, örebro university, sweden prof brigitte gay, esc-toulouse, france prof malek ghenima, l'université de la manouba, tunisia prof uwe hannig, fachhochschule ludwigshafen am rhein, germany prof mika hannula, tampere university of technology, finland prof per v jenster, nordic international management institute, china prof sophie larivet, ecole supérieure du commerce extérieur, paris, france prof kingo mchombu, university of namibia, namibia dr michael l neugarten, the college of management, rishon lezion, israel prof alfredo passos, fundação getulio vargas, brazil dr john e prescott, university of pittsburgh, usa prof sahbi sidom, université nancy 2, france prof kamel smaili, université nancy 2, france prof klaus solberg søilen, school of business and engineering, halmstad university, sweden assoc prof dirk vriens, radboud university, netherlands prof xinzhou xie, beijing science and technology information institute, china dr mark xu, university of portsmouth, uk managerial board way chen, china institute of competitive intelligence (cici) philippe a clerc, director of ci, innovation & it department, assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director, acrie competitive intelligence network, france hans hedin, hedin intelligence & strategy consultancy, sweden raíner e michaeli, director institute for competitive intelligence gmbh, germany mourad oubrich, president of ciems, morocco copyright © 2015 jisib, halmstad university. all rights reserved. editor’s note vol 5, no 3 (2015) a review of competitive intelligence as a discipline this is a special issue of jisib where the discipline is allowed to reflect on itself. included are three articles that aim to take a new, critical look at the discipline of competitive intelligence and its equivalents in other cultures. degerstedt rethinks the whole discipline of ci and is, as seen from a larger sociological and technical perspective, which in many ways resembles ideas of social intelligence introduced by stevan dedijer. solberg søilen bases his reflections about the scientific standing of intelligence in business around a survey with two questions: what is unique for ci and is as disciplines and what analyses are unique for ci and is? the article by hoppe was presented at the ecis conference in stockholm in 2009 and was submitted to the new journal of jisib in 2011. the article is a call for a new research agenda for the study of intelligence in business. the author wants to move away from a narrow perspective on practice to pursue a broader understanding of intelligence as a discipline. finally, as always, we would first of like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2015 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 5, no 3 (2015) pp. 4 open access: freely available at: https://ojs.hh.se/ journal cover vol 5 no 3 page 2 to 4 jisib-vol-12_nr-3(2022).pdf journal of intelligence studies in business vol. 12 no. 3 (2022) open access: freely available at: https://ojs.hh.se/ pp. 18–26 intelligence on the hiring process mohamed beraich imane amouri cheklekbire malainine abstract: in this paper, we proposed a decision support tool for recruiters to improve their the process opted by the methods and techniques related to data mining. as a result, after completing the modelling process, we were able to obtain a model capable of obtained a model with an accuracy of 99% as well as with a very low error rate. support tool for recruiters while minimising the cost and time of processing applications and maximising the accuracy of the decisions made. keywords: (ai), digital enterprise, recruitment 19 introduction in the current era of globalisation and the emergence of new technologies, as well as the competition of the global business market, companies cannot afford to continue to adopt traditional methods in the various business the smooth running of the company, especially the hiring process follows important steps such as the selection and appointment of suitable candidates for such a vacancy post. every enterprise invests a lot of money and and wastes resources in searching for potential candidates. the total investment becomes a loss if the selected candidates do not meet the company’s requirements after completing the whole hiring process. therefore, the objective of this empirical study is to propose a decision support tool to improve the hiring process neural network (ann) method to build a predictive model of the decision in the hiring process. our methodology consists of adopting the process applied by data mining techniques, starting with a pre-processing and exploratory analysis of the data, then building our model uating the model using the proportion of test data, using the various validation metrics emanating from the confusion matrix. 1. literature review the importance of exploiting new methods from ciplines. to build a model capable of analysing the performance of students’ academic records as well grade in different classes (excellent, average, poor), however the results obtained revealed the robustness of these methods. in the employment market, and more intelligence techniques in the hiring process, several studies have been carried out in this sense in order to improve the said process. therefore, the study conducted by (d. alao et al., 2013), the authors constructed a set of rules using the decision tree method in order to build a model capable of predicting new employee attrition, however, the results obtained yielded a model with an accuracy of 74%. a decision support model for ranking candidates in the employee hiring process using a variachieved a maximum accuracy of 88.24% using the decision tree method. 2. hiring process sound tactics into the hiring process. owever, the hiring process can be internal or external, therefore, it can take many forms that differ from one company to another, but remains faithful to the single purpose of choosinterview is a crucial step and represents more than 50% of the rating assigned to the pre-selected candidates. 3. artificial neural network (ann) research that deals with learning and reasonniques, unlike parametric techniques, anns neural networks, as systems capable of learning, implement the principle of induction, i.e., learning from experience. by confrontagrated decision system whose generic character depends on the number of learning cases encountered and their complexity in relation to the complexity of the problem to be solved. ally composed of a succession of layers, each of which takes its inputs from the outputs of the previous layer. each layer i is composed of ni neurons, taking their inputs from the n 1 20 called the input layer and the last layer, composed of a single neuron, is called the output layer. the intermediate layers are called hidden layers. networks (ann) posed of a succession of layers, each of which takes its inputs from the outputs of the previous layer. each layer i is composed of ni neurons (nr) taking their inputs from the neucalled the input layer and the last layer, consisting of a single neuron, is called the output layer. the intermediate layers are called hid 3.2 structure and operation of an that receives input from other neurons and weights it with real values called synaptic coefconsider the neuron of a layer i. let us note x , x , ..., x the n 1 inputs from the layer i–1 to the neuron of the layer i. we also consider the n 1 weights denoted , , ..., . the neuron calculates the sum of its inputs cients, to which it adds a constant term called the bias b . this gives the formula: = + the bias is an external parameter of the neuron . it can be integrated into the weighted sum, as the signal which takes the value 1, weighted by the weight whose value is equal to the bias : the sum can thus be written as: = + 1 2 0 1 2 1 2 3 the hidden layer or the i-layer the output layer (s) 0 0 1 2 21 to this sum the neuron applies an activation or transfer function to obtain an output the output (output) of the neuron neuron in the i layer is sent to other neurons or to the outside. 3.3 matrix writing we consider the layer i layer composed of m1 neurons. with 1 < < mi we put: so: = = . = . we pose: so: we put: so: the outputs of the mi neurons of the layer are then written: + + the weighted sum the applica on of the ac va on func on the predic on of the neuron ( ) 22 so: the transfer function = . the summation function architecture and functioning of ann (source : author). the list of activation functions (source: author). the function title the function the graphic representation sigmoid relu 23 3.4 activation function the transfer function or activation function or thresholding function, also called the activation function, is the function used to propagate information from layer to layer. the most common functions cited in the literature are listed in the following table (table 1): 3.5 error functions to calculate the correct weights (parameters), the error between the expected output and the output produced by the network must be calculated. methods for calculating the error include: • : with: • : m the number of individuals or objects to be predicted or the number of observations. : network the vast majority of neural networks have a “training” algorithm which consists of modifying the synaptic weights according to a set of data presented as input to the network. the purpose of this training is to allow the neural network to learn from the examples. if the training is carried out correctly, the network is able to provide output responses very close to the original values of the training dataset. but the interest of neural networks lies in their ability to generalise from the test set. it is therefore possible to use a neural network to ory. supervised learning occurs when the netstate as it is presented with a pattern. in contrast, in unsupervised learning, state when presented with a pattern. ann learning can be achieved, among other things, by: i) changing weights, (creation or deletion of neurons or connections, or layers), iii) the use of appropriate attractors or other appropriate steady state points, iv) the choice of activation functions. since backpropagation training is a gradient descent process, it can get stuck in local minima in this weight space. it is because of this possibility that neural network models are characterised by high variance and instability. back-propagation backpropagation consists of backpropagating the error committed by a neuron to its synapses and the neurons connected to gation of the error gradient is usually used, which consists of correcting errors according to the importance of the elements that have actually participated in the making of these errors: the synaptic weights that contribute to ated a marginal error. how to choose the number of layers and neurons the number of neurons and layers directly of prediction quality. indeed, to determine the number of hidden layers, we can follow a process that consists in starting with a single hidden layer and adapting it to reach the ideal architecture. so if one layer does not produce satisfactory results, then we automatically have to think about adding another until we get satisfactory results. the same goes for the number 24 of neurons, we try to modify it until we get the desired results. the number of neurons in each layer must not exceed the number of input variables. so, you have to think about doing several tests to arrive at a relevant and powerful ann in terms of accuracy in predicting the output variables. on the other hand, the more layers you increase the capacity of the network, the more you risk overlearning if you exaggerate in terms of the number of layers or neurons, and the same thing if you decrease the number of layers, you risk underlearning. to avoid the problem and we try to divide the data into 4 parts and try to alternate the combinations between these parts. by applying this technique, we will have a perfect test of the data since all parts will be used for the test. 4 methodology, metrics and data 4.1 methodology the aim of this empirical study is to build a model that can be implemented as a decision support tool for recruiters to effectively hire intelligence, for which we adopted the process of data mining techniques. this process is initially based on the preparation of the data, followed by the splitting intended to train the prediction model, while the second serves as a test proportion for the accuracy of the resulting model. 4.2 metric to evaluate the model obtained from the modmetrics to assess the performance of the model sion matrix using the test data set. given that the test data set represents 25% of the overall data and the training set represents 75% of the overall data. allows us to indicate the number of correct predictions for each class and the number of incorrect predictions for each class organised according to the predicted class. each row of the table corresponds to a predicted class, and each column corresponds to an actual class. confusion matrix. true positives (tp) true negatives (tn) with: applicant database (accepted or rejected) the entry layer training the neural network 1 2 3 predict whether a candidate will be accepted or rejected 25 ratios can be calculated: 4.3 data in the data preparation stage, we used a database that includes 1000 rows of applicants from a recruitment agency. in addition, this database has 8 explanatory variables and only one dichotomous variable to be explained which takes 2 binary values (accept / reject), so we coded all categorical variables according to the table below (see table 3): 5. results after preparing the data for the modelling, the function function is used to train our model over 50 iterations, allowing us to coding of explanatory variable values. code 1 2 3 4 5 speciality computer science secretariat management right current status unemployment assets french level a1 a2 b1 b2 c1 english level a1 a2 b1 b2 c1 computer level beginner medium advanced excellent decision reject (0) accept (1) the architecture of our neural network. figure 6. the evolution of the error of our model. figure 7. the evolution of the accuracy of our model. 26 choose the right values for the weight matrix w. the calculations are performed using the gradient descent method. the training data used are stored on (starting values) and the evolution of the accuracy and the error (loss) of the model in the training phase. decreases and the accuracy increase with iterations, as the training algorithm continuously updates the weights and biases in the neural network according to the training data. we curves (blue and orange) are very close for both test and train data sets, which means that the model has been well trained. we also notice the test and train data sets decrease towards 0, which means that the model performs well. thus, we calculated the metric for the training and test data and obtained an accuracy equal to 99,33% using the test data indeed, according to the value of the metric obtained, we can conclude that our model has a fairly high level of predictability, which will help us to make accurate predictions of the recruitment decision. 6. conclusion selecting and hiring the right candidate is a daunting task for the company. therefore, companies are looking for tools that can collect, sort and analyse a large amount of information about candidates to assess their personintelligence provides to improve this hiring process. it is in this context that our paper is written, we have tried to detect the importance of using these techniques in the construction of a model capable of predicting the recruitment decision of new candidates for a company. so we have exploited a database that includes a range of explanatory variables that describe the level of competence of candidates. after following the process adopted by data mining techniques, we were able to achieve racy obtained at the end of the modelling process, which exceeds 99%, reveals the robustness of the model obtained, which will improve the hiring process for companies. references [1] c. e. a. pah and d. n. utama, “decision support model for employee recruitment tional journal, vol. 8, no. 5, 2020. [2] d. alao and a. adeyemo, “employee attrition analysis using decision tree algorithms”,computing, information systems, development informatics and allied research journal, vol. 4, no. 1, pp. 17–28, 2013. [3] dana pessach, gonen singer, dan avrali, irad ben-gal, “employees recruitment: a prescriptive analytics approach via machine learning and mathematical programming”, decision support systems 134 (2020). ligence to recruit employees”, citations ume 18, 2021. enterprise human resource management computer hardware”, microprocessors and microsystems 82 (2021). gineering students’ performance for retechniques”, international journal of computer science, engineering and technology, vol. 3, no. 2, p. 31, 2013. mance analysis of engineering students mining techniques”, samrat singh et. al 31–37. o p i n i o n s e c t i o n 41 intelligence analysis and cognitive biases: an illustrative case study pierre memheld 1 1 institut de traducteurs, d'interprètes et de relations internationales, university of strasbourg, france email: pierre@exmergere.info received october 25, accepted november 3 2014 abstract: this case study is foremost an educational tool. it involves two european and asian multinational tires manufacturer for otr, off the road, or “off road” and a problem of price competition. it shows how an initial intelligence effort is led astray. instead the solution is a combination of approaches, better known as competitive intelligence. it is built on the external vision of the company craft, the use of all information sources characteristics of an intelligence field dedicated to the business world. it is not a new discipline but a transdisciplinary approach for information exploitation which is using elements from financial analysis, swot (strengths, weaknesses, opportunities, threats) matrixes, and value chain analysis. in the above case, the company eurotires used mostly the following sources: internet, scientific and patent databases; public administrative sources; customers interviews, industrial experts (manufacturing and distribution), and marketing analysis. keywords: intelligence analysis, competitive intelligence, cognitive bias, case study 1.0 introduction “cognitive bias is a common tendency of filtering input through one’s own likes, dislikes, and experiences to acquire, retain, and process information » (black, 2014). this phenomenon is well documented, studied, and identified, but is it known by most of the people having to make decisions? in order to limit the range of what ‘making a decision’ is, we will focus on a specific available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 2 (2014) 41-50 https://ojs.hh.se/ o p i n i o n s e c t i o n 42 case: information analysis in a commercial environment. this case study is illustrative as it groups analytic methods’ applications and several biases. the author, when conducting a competitive intelligence project, was confronted with a double cognitive bias syndrome: personal biases but also ones indigenous to his customer’s culture. recent researches have been conducted on how a second language reduces bias in analysis (wheaton, 2013). language is part of people’s culture and education. but a company’s culture is more complex because, in addition to the employees’ backgrounds and educations, a company creates a specific environment: employees from various regions, educational tracks, working on various issues and markets. in this case study, the origin of the bias was the organization’s behavior, another important factor. the analytic methods themselves can create a bias: they have their own history, origins and applications. does a military intelligence method apply to economic issues? does a scientific method apply to international relations? in this case, the methods first used were technologically oriented when the solution was organizationally, logistically and commercially oriented. we can call this difference of original field of application a dimensional difference. despite the fact that involved employees, mainly engineers, and analysts master these various methods, the cultural and dimensional factors became predominant resulting in four months of vain research, misunderstandings and time/money spending, a common problem in the business world. the full case study will present all the factors, reflections, methods used and a posteriori (by observation) noticed biases in a cultural perspective, from language to education, behavior, interactions and finally how the solution was found. but this case study is foremost an educational tool as it allows us to cover various issues from analytic methods to intelligence production, and from organizational behavior to personal/group/corporate biases. solving this case is not a question of mastering analytic methods or having an experience in the industry or as an engineer. we have conducted this case study with students of different levels (from bachelor to master/mba) several times and the solution can be found without any experience of tires manufacturing or supply chain management. surprisingly, students with a basic training in information collection and an access to information sources are the least efficient or effective in finding the solution. this is because they are searching without clear instructions, tasks sharing, and never stop (which can become a bias by itself), they don’t produce even partial outcomes which is an essential part of the intelligence cycle. from our experience the best results from this test were obtained by using five groups of four or five students without any access to information sources. instead of searching, the students were exchanging ideas, testing solutions between themselves with similar perceptions among the different groups, a kind of competition or comparison. this business case, from which we deduced some practical tips for further analytic case studies, should lead to further research on other actual cases and comparisons. from a research perspective, it would be useful to compare engineers, production managers or decision makers’ personality profiles and their ability to analyze problems from different domains. but as noted, the most interesting lesson of this scenario based training is the collaborative analysis of the students without information. students and groups were sharing information, despite the fact it was not authorized by the trainer: as quoted in a recent publication analysts, using “effects of implicit sharing in collaborative analysis” (goyal, 2014), were, in our case, more efficient in finding the solution than other teams working alone in structured and separated groups. based on this experience, we could hypothesize that analysts without information access or inferred biases may be more efficient than skilled and trained ones. the case study is structured as a didactical scenario to be played during one or two full days. the first day is dedicated to the presentation of the base assessment; the challenge being for each group to follow the initial research phase. this generally leads to a similar conclusion: the students don’t find the solution. from time to time, the author delivers information inputs, answers some questions and even tries to lead students down wrong tracks. as already noted, the most interesting phenomenon is not the research’s results, but how the students reflect and interact as teams. some search endlessly o p i n i o n s e c t i o n 43 for solutions; some state hypotheses; some inject their own experiences: but most of them don’t cast doubt on the base statement nor the research logic. as we will see, this reaction follows what happened during this case study. the second part of the day, or the second day, it is necessary to give students clues not to solve the case, but to eliminate different hypotheses. most of these hypotheses are linked to the low costs production issue as the most logical explanation. the case is structured to make students react, make them think about how they reflect, and create frustration in them. as stated, not all the students find the solution, or even a part of it. the limit of this approach is the constrained training period. at the end of the day, or day two of the session, there is a mandatory evaluation phase and the conclusion giving the solution. as much as possible, these phases must remain interactive, as the previous ones: the solution is not just released but the students might deduce it from more and more precise information or clues. the case below might be seen as the transcript of these training sessions, from the beginning to the conclusion. the authors gave different type of training sessions, from a more lecture-oriented session to this interactive approach. it groups together research techniques--inputs to analysis and evaluation-based on a real case. students can discover information, enhancing their involvement. they interact and it is interesting to see how groups are formed: if the mix of student competencies are arranged randomly or based on persons’ proximity and personalities. is it possible, inside a company, or a governmental body, to mix various backgrounds and personalities in order to optimize the brainstorming? the answer is logically yes but as we will see, some biases were induced by the variety of backgrounds and professional behaviors involved. putting the participants in a ‘think out of the box’ situation would be the solution: outside of the organization; making hierarchy a low priority and using an engaging situation such as war games or serious games. 2.0 the otr case study 1 1 disclaimer: despite the fact that the facts and details presented in this article are realistic, as is the in 2003, a european tires manufacturer (”eurotires”) was hoping to understand how one of its asian competitors (“eastires”) offers to its customers “40% discounts on sales prices for the off the road (“otr”) segment”. otr is a small business segment, compared to other companies’ segments, but very competitive and the technical: tires for mining or construction machines have specific characteristics. in this case, for eurotires, the logical explanation was that eastires has invented a new manufacturing process, but after several months of internal technological and industrialization research, this explanation appeared as not true. eastires did not invent a new process, did not modify its manufacturing lines, and had not changed its suppliers. but a 40% discount is a significant drop on the sales prices if we consider the normal industry profit margins of a few percent. eurotires interacted with customers in order to see if the tires themselves have changed. from brazil to australia, usa to japan, the main customers were contacted, including construction and mining companies and airlines companies; airplane tires being a subsegment of the otr market. research was conducted with the end users, mine managers or airlines technical services. once again this track did not lead to an explanation. users did not observe radical changes in the tires technical characteristics: eurotires considered that, due to specific constraints these tires support, technical changes were the explanation. eurotires is a company of engineers; thus the solution was necessarily inside the tires. thanks to publicly available information, eurotires was able to analyze the chemical rejections of one competitor’s factory. this analysis did not show particular elements for the r&d department. so a reverse engineering approach to solving the mystery was not successful. studying the scientific and professional publications made by eastires inside industry or research centers journals revealed there was no particular tires’ components change. then researchers tried to determinate if the analysis based on them, the names, industry and locations have been changed due to confidentiality issues, but chosen because they present the same characteristics as the original case. similarly, the expressed opinions are only the ones of the author. o p i n i o n s e c t i o n 44 mechanical characteristics of the tires were changed, using laser testing benches. they did this with the belief that, you can gain in productivity by automating the testing process. eastires’ suppliers for raw material and machinery were well known and often the same used by eurotires. previous research phases showed that no particular changes occurred for supplies or manufacturing lines. eurotires did not succeed in analyzing this 40% discount. at this stage a consultant suggested to widen the research outside the engineering approach. the idea was to analyze the whole value chain of the manufacturing of the tires from conception to raw materials, to manufacturing, to sales, to distribution and to services. the first three steps were analyzed without finding enough factors explaining this price drop. could the solution be in the following steps? in fact the attention of eurotires was focused on the production costs while the customers were speaking about sale prices. otr tires, due to their specific uses are distributed through specialized resellers (independent or brands owned) or directly shipped when orders are important enough. for example, mining and airlines companies are regular users of otr tires. airlines are submitted to security constraints which oblige them to change tires when they reach a determined level of wear. mines don’t have the same constraints but must reach production and profitability objectives. mines have a specific characteristic as their own supply chain is constrained: ores are transported either by trains or ships from often isolated regions (southern chile or north west australia). in both airlines and mines cases, too frequent tires replacements, or not planned ones, lead to delays, production decrease and thus exploitation losses or even financial penalties from their customers. these two industries have a common characteristic: they can precisely plan the utilization of their equipment and then the tires’ wear. planes’ rotations are planned on long term, so the number of take offs and landings, the main wear factor, and the runway rolling distance are known. a mine can be compared to a manufacturing line: each machine has a determined function and does not change; trucks have always the same itinerary, loads the same weight, on known distances and grounds (more or less abrasive). these two industries can coordinate with their suppliers, including tires manufacturers, precise replacement parts needs on a long term basis (depending on the economic activities: evolution of flights programs or variation of the ores demand). maintenance services of concerned companies have tires stocks but limited in order to optimize stocks costs. in these conditions, a tires manufacturer can offer a ‘just in time’ service, the exact number of tires being delivered ‘on time’ based on the constrained replacement program. this planning can be done for existing customers and large quantities, emergency replacement or new customers/sites being specific cases. the ‘just in time’ service presents advantages both for the customer and the supplier. the customer is ensured to not suffer delays in a plane’s rotation or production interruption. the supplier can plan its own supplies, manufacturing programs and products delivery. all these elements can be translated in financial terms. has eastires been able to precisely simulate its activity in order to offer such a discount representing an optimization of its production and post-production costs? eurotires discovered that its competitor, present in asia, north america and europe has gone further with this planning approach, making concurrent commercial strategy, supply chain and production. in fact eastires has changed its function. instead of selling a number of tires, eastires offers a service, providing for a predetermined period, a permanent availability of tires, delivered on time at the right site to synchronize with its customers’ business cycles. from a commercial point of view, eastires offers its customers multi-year service contracts in return for which the manufacturer negotiates a significant unit price discount. more than production, and supplies, including its own raw materials and transport prices negotiation, eastires can guarantee to its shareholders several years of visibility in terms of turnover. 2.1 analysis methods convergence this case study demonstrates the necessity to use varied analytic methods since a strictly scientific approach (r&d, components, processes, patents) was not appropriate as the solution was outside this domain. tires’ performance and wear indexes were known due to manufacturing monitoring; the manufacturer can predict the replacement time. this technical factor, despite not explaining the price o p i n i o n s e c t i o n 45 discount, was essential to define the commercial strategy and negotiations. the upstream supply chain analysis did not show changes explaining the price drop (same raw material, same transport means, and same delivered quantities). it’s possible to find the solution by combining these different approaches, the specific needs and constraints of the customer. this combination of approaches, this external vision of the company craft, this use of all information sources, are the characteristics of an intelligence field dedicated to the business world; competitive intelligence. it is not a new discipline but a trans-disciplinary approach for information exploitation which is using either financial analysis, swot (strengths, weaknesses, opportunities, threats) matrix, or value chain analysis. in the above case, eurotires used the following sources: internet, scientific and patent databases; public administrative sources; customers interviews, industrial experts (manufacturing and distribution), marketing analysis. this approach allowed the company to reconstruct its otr distribution organization, from manufacturing factories to resellers stocks, distributors and users. otr tires have long life cycles, low margins, good planning potential, a second hand market and a constant demand. eastires objective was to effectively provide a solution for this predictable demand at the best price. it’s a supply chain re-engineering with economies of scale, precise planning, which leads to upstream and downstream logistical chain organization. these supply chain levers have direct consequences on financial results: logistical costs optimization, negotiations on large amounts of raw materials, production planning depending on the country and demand’s cycle; stocks optimization and human resources organization. the ‘just in time’ organization has another consequence: there is no more delay between orders and deliveries as eastires anticipate needs and on site deliveries. eastires has also improved the after sales services: used tires are collected, new ones are mounted on site and there are fix or mobile recasting units to reuse the tires: refitted tires are authorized for planes and it’s a useful option for mines, when security criteria are respected. the supply chain management is optimized by influencing costs, prices and services. thanks to this, eastires won market shares by differentiating from its competitors while improving its profitability. for otr tires, heavy and bulky, logistic costs are high (factory, transport, distributor, and user). eastires, considering its quality of services strategy, should even internalize distribution under its own brand in order to lower some costs and improve its image. one way to reduce costs is to optimize huge shipments towards important market areas and then break down the distribution to specialized companies: to identify these portions is also possible. 2.2 open information and anticipation existing customers, and their premises, are well known: an airline is not created from one day to another and a mine does not appear from nowhere. more, due to heavy competition and economic situation, we can observe a concentration phase in the airline and mining industries. means of production and routes of shipment are easily identifiable, due to the specificities of otr tires. many logistic companies’ records, and even customs data, are made available on internet or through industries experts. even if this market is specific, we can extend this analysis to various sectors. monitoring information sources to identify new commercial leads, best practices benchmarks and innovative strategies is a permanent task that any company might conduct using legal and ethical methods, which are the characteristic of competitive intelligence. why was eastires able to identify key success factors, while eurotires took so long to identify the same information? eastires succeeded because the company took into account all possible elements and sale steps, not only production issues. this strategy can be duplicated because: it is not dependent on technology; the number of actors is limited, as the number of suppliers and services providers. similarly, tires for transport trucks are not anymore seen as products but services, the user paying a fee based on kilometers and the manufacturer being in charge of regular maintenance and replacement. this service approach is also used in the heavy machinery business: caterpillar also offers its customer to anticipate their needs and replace/repair parts in their machines. o p i n i o n s e c t i o n 46 3.0 analytic cultures and biases despite the fact that eurotires lost some market share in the otr segment, the company is a leader on the global tires market. once the key success factors and organization used by eastires were known, eurotires set up the same kind of pivotal logistic centers; specialized distributors that were able to repair and recast tires, and adapted its contracts with customers. with its important industrial capacities, present worldwide, eurotires has rapidly regained the lost terrain. however, we can state that eurotires faced a strategic surprise and, without external intelligence, would not have been able to adapt its organization in the long run. eurotires engineers and researchers are at the top of their profession, with universities r&d collaborations worldwide. commercially speaking, they are in contact with their customers. so why was this leading company surprised? we can assert that such kind of strategic move is not really a surprise which is by definition something we cannot imagine and thus anticipate. was that the case for eastires? no, the company had simply reorganized its existing means of production and distribution to articulate a new sales strategy. as we saw the company did not invent a new manufacturing process, did not change its production lines, its suppliers and service providers. at the beginning, eastires did not gain new customers but consolidated and retained existing ones. and eastires did not communicate it’s reorganization. so, was it eastires that took the initiative or eurotires that did not watch its competitors’ moves and customers’ needs? at this stage of the case it could be helpful to stress how the initial information was collected and analyzed, along the lines of cognitive bias and information collection (margit and grosjean, 2012) the information source was a commercial agent visiting prospective customers who told him that eastires was offering a 40% discount on sale’s price. but when expressed inside the competitive intelligence request, this was redacted as: ‘a 40% decrease of the sale’s price because eastires has a new manufacturing process’. this is not a bias by itself but a falsification of the information which resulted in useless research and internal misunderstandings. but this can also be seen as a ‘framing effect’, the fact to elaborate “different conclusions from the same information, depending on how or by whom that information is presented” (ackerman, 2003, p.7). the consultant did not collect himself the raw data but received an interpretation from eurotires management. the first error was to not request a direct contact with the source. from a consultant perspective, it can be hard to cast doubt on a customer’s opinion and request. the customer, in that case the r&d director, was using misinterpreted information as true and expressed his opinion as a logical conclusion. this can be seen as ‘subjective validation’ the “perception that something is true if a subject’s belief demands it to be true” (iverson, brooks and haldnack, 2008, p. 248). in that case, as quoted, the customer was an industrial company focused on its technology. so for the r&d director, the obvious solution for a price change is technical and this despite the fact that the information was clearly commercial or at least financial. so for him, any other explanation does not satisfy his belief, or personal explanation. so even the absence of confirmation, from his initial research, and the consultants, was not a noticeable fact. this can be seen as a reversed confirmation bias, the “tendency to search for, interpret, focus on and remember information in a way that confirms one's preconceptions” (tversky and kahneman, 1974, p.430). at each mission’s intermediary report, the absence of facts was confirming the belief of the director that eastires has really innovated in a secret way. so it was necessary to keep on searching and using different sources and methods, as described. and despite the fact the initial mission’s request was apparently erroneous; all parties decided to keep on spending money and time to look after the hidden innovation. the economic relation between the customer, an industry leader, and the consultant, a specialized but much smaller company, also played a role. it’s a question of technology knowledge, the gap between industrial experts and management consultants. even if these last can improve their sector’s learning curve for each new mission by interacting with experts, they don’t have the experience and the education background to understand all facts and data. this can be seen as a ‘curse of knowledge’ “when better-informed people find it extremely difficult to think about problems from the perspective of lesser-informed people” (ackerman, 2003, p.7). each collected element was judged as irrelevant by the customer, as not as o p i n i o n s e c t i o n 47 technical as expected, and not confirming the director’s belief. the main mismatch was the fact that the initial information, the technology belief and the real explanation were not in the same domain. due to his educational background, and company culture, the r&d director did not find the information, or the lack of information, relevant. in a way, the solution had technology factors since eastires would not have reached this result without an efficient manufacturing line, able to produce requested quantities, a complete information system from customers to distributors and support companies to the manufacturer, and the ability to recast used tires. even if tires are simple products, their production and quality proofing are based on technology. in these conditions, why would the solution not have been technological? this can be seen as an anchoring bias, the “tendency to rely too heavily, or anchor, on one trait or piece of information when making decisions” (iverson, brooks and haldnack, 2008, p.248). this preconception led to a misinterpretation of the collected information. the technological explanation and the logistical/commercial explanation can be seen as two unrelated elements so there was not a correlation in terms of analysis (tversky and kahneman, 1974, p.430). 3.1 analysis and organizational behavior why did such an experienced manager not look into account disconfirming evidences? despite the fact that the collection methods were all legal and ethical, as the society of competitive intelligence professionals define it in competitive intelligence best practices it publishes, they covered a large array of means and variety of information sources (fehringer and hohhof, 2006). the fact that no patent, scientific publication or industry journal was evocating any specific innovation should have been a disconfirming evidence for the initial intelligence statement. this is defined as the ‘backfire effect’ “when people react to disconfirming evidence by strengthening their beliefs” (sanna, schwartz and stocker, 2002, p. 497). it took four months for the consultant to explore all possibilities, write several detailed but meaningless intermediary reports and finally conclude there was a problem of mission’s request. the consultant and the customers were also confronted to the ‘observer-expectancy effect’), “when a researcher expects a given result and therefore unconsciously manipulates an experiment or misinterprets data in order to find it” (skepdic, 2014). as the collected elements were not confirming the initial request, they were misinterpreting these in order to keep the request as the only relevant information. the most interesting point is that the answer was “obvious” and was even given by one contacted source, an industry journalist who gave the consultant a clue when discussing the price’s drop statement. since the initial request was considered as valid, it was used as a ‘key intelligence topic’ (kit) in order to determine the consecutive ‘key intelligence questions’ (kiq) and thus list the intelligence indicators which are the possible elements to answer the questions (herring, 2005). so the whole collection plan has been determined and planned by the initial request. this having been proved as erroneous and misleading, the whole intelligence process, from planning to analysis, production and dissemination was going on the wrong track. in addition to the other biases of the collector/analyst/consultant, we can quote the ‘congruence bias’ the “tendency to test hypotheses exclusively through direct testing, instead of testing possible alternative hypotheses” (iverson, brooks, and haldnack, 2008, p. 248). all the collected elements were tested following one unique hypothesis: a technological innovation has allowed eastires to reduce its production cost and thus lower the sale’s price. before the four months of endless research for the mysterious innovation, no other hypothesis derived from the initial request has been tested, without even casting doubt on the request itself as expressed by the customer. this is also a form of ‘conservatism’, the “tendency to insufficiently revise one's belief when presented with new evidence” (ducharme, 1970, p. 66). we stated that this phenomenon was reinforced by the financial relation between the consultant and the customer, the technological aspects mastery and the wrong orientation of the intelligence process. the conservatism, respect of beliefs and conclusions of an older and more experienced person, can be explained by the initial education of any person: it’s a form of social bias. in the hierarchical organization of any company, whatever be the model, there is a structure, especially in old heavy industrial companies, which has a direct impact on the information circulation, sharing and analysis (fischoff and chauvin, 2011). if eurotires is since a o p i n i o n s e c t i o n 48 long time a globalized company, with suppliers, factories and customers worldwide, it remains a traditional company with a strong national identity. most of the main managers and executive directors are from the same culture, educational background and even often from the same school. this organizational behavior, engineers selling technological products with a long history of successes and innovations logically is a specific approach to any problem, even more with this ‘mate’s community’ managing the company (watkins, 2013). the consultant, while not from the same background, was from the same culture and using different languages to collect elements and redact reports. all elements and sources were in english, or else, speaking and thinking while the ‘intelligence’ was produced in french. the clue given by the journalist was translated in french and then sidelined as to confirm the initial request and kit. next we have to ask, what would have been the methods to improve or prevent these biases, from a consultant and a company perspective? 4.0 how to educate decision makers the consultant, while not having a long experience, was aware about intelligence analysis and used many information sources. most of all, he collected the clue from the industry journalist who said, during a phone interview, that eastires reorganized its distribution, support and services systems in order to lower the delivery time and offer a prospective planning. this indication did not clearly state that reorganization had an impact on the sales price. the fact that this clue was not determinant as an indicator to answer the kiqs lowered its relevance. moreover, the source being a journalist, not a manufacturer or a customer, this also lowers the subjective relevancy of his information. it’s clearly an error if we consider the information and its sources to be quoted independently. but the answer being out of the initial request domain was the most important factor to sideline this information. another factor was the necessary translation of the information to meet the customer’s language request. does the language have an impact on analysis? the recent "reduce bias in analysis by using a second language" article quoted a study that presents essential points when put in perspective with our case: “emotion, language processing and cognitive biases aside, the intriguing question remains: would you make the same decision in english as you would in, say, chinese?”…being less risk averse means that people more systematically assessed the problem and came to a more rational conclusion…the ability to make decisions driven more by rational thought and less by emotion” (kaiser and hayakawa, 2012). in the above situation, the difference was between collecting in english, whatever can be the mother tongue of the sources, analyzing and reporting in french. the sources were thinking in their own languages before giving information and because of these differences, cultural and educational, they already analyzed from a different perspective. the consultant was reporting intelligence through all these deforming lenses. if analysis methods are widely used, when redacting a document, each ‘culture’ has its own logic: french is using longer sentences, longer texts’ structures and a different logic: the conclusion, the real intelligence input is most of the time at the end of the text following an ‘introduction, thesis, antithesis, synthesis, and conclusion’ model. if the introduction, kit, thesis, kiq are erroneous, how could antithesis, synthesis or conclusion have been relevant? with a clue not complying with the kiq, kit and belief, it was difficult to test different hypothesis and use critical thinking to call into question the whole process and mission. all these factors are directly linked to culture: language, education, experience, hierarchy, logic, and writing. the consultant was also facing a biases’ blind spot: the “tendency to see oneself as less biased than other people, or to be able to identify more cognitive biases in others than in one’s self (pronin and kugler, 2007, p. 565). is it possible to prevent these syndromes by education? inside intelligence oriented diplomas, the answer is yes because this is the place but even this depends of the intelligence culture of the considered country. we can testify that inside french competitive intelligence curriculums, the biases’ issue, or the blind spots one, are rarely addressed because they cast doubt on the ability of students, and teachers, to call into question their own competencies, studies and experiences, not from a skills’ perspective but from a personal and psychological perspective. if we consider that culture and education build up from the very o p i n i o n s e c t i o n 49 beginning, in childhood, then changing the curve of learning is difficult. when analysts, or engineers, and managers reach their positions of responsibility, where what they say, write and decide, have practical and financial consequences, we should say it’s already too late: some biases and education/work behaviors are set up. at that stage, and depending on the level of decision, there are a few solutions to solve the problems we faced: for analysts, trainings on biases and cases, or even psychological profiling to assess potential blockages and blind spots; for managers, similar trainings and for decision making profiling, it’s possible to rely on standard human resources management tools as the myers briggs type indicator (mbti) or fundamental interpersonal relations orientation (firo) personality tests. the training of 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(2018) investigating the competitive intelligence practices of peruvian fresh grapes exporters. journal of intelligence studies in business. 8 (2) 43-61. article url: https://ojs.hh.se/index.php/jisib/article/view/309 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index investigating the competitive intelligence practices of peruvian fresh grapes exporters christophe bissona,b*, maria mercedes tang tongc adicen, site val d’europe cité descartes 5 bd descartes 77454 marne-lavallée cedex 2; bessec, 3 avenue bernard hirsch, 95021 cergy-pontoise, france; cuniversidad de lima, peru *christophe.bisson@essec.edu journal of intelligence studies in business please scroll down for article investigating the competitive intelligence practices of peruvian fresh grapes exporters christophe bissona,b and maria mercedes tang tongc a dicen, site val d’europe cité descartes 5 bd descartes 77454 marne-la-vallée cedex 2; b essec, 3 avenue bernard hirsch, 95021 cergy-pontoise, france; c universidad de lima, peru corresponding author (*): christophe.bisson@essec.edu received 17 may 2018 accepted 15 august 2018 abstract this paper reports an empirical study of peruvian fresh grapes exporters with the aim of delineating the behavioral and operational typology of their competitive intelligence practices. cluster analysis was used as an exploratory tool to determine the correlation, if any, between the size of the company, grapes exports share of total exports, the percentage of the red globe variety in total grapes exports and the size of the grape farm with the typology and the average price received at export between august 2016 and july 2017. the behavioral and operational typology of competitive intelligence practices model, developed by wright et al, (2012), was used. the findings reveal that exporters have a positive behavior towards competitive intelligence practices, but cannot make good use of them due to a lack of knowledge, and deficiencies in organization and in technological and it systems support. as 37 companies participated in this experiment, this study could be extended to all non-traditional peruvian agricultural exports. it has been possible to identify areas where changes are needed to enable these exporters to perform at a higher level of competence. in addition, it appeared that a slightly higher level of attitude and it systems support pays off as medium-sized companies achieved a higher price per ton compared to big companies. this study is the first to present a typology of competitive intelligence practices in peru and is one of the very first to study competitive intelligence in this country and agriculture. keywords behavior, competitive intelligence, grapes exporters, peru, typology 1. introduction as companies face fiercer competition and a more uncertain environments, competitive intelligence (ci) is gaining ground (blenkhorn and fleisher 2005; bisson and yasar diner, 2017). the global intelligence alliance (gia), using data from surveys done on the same sample in 2009 then in 2011, reported that the percentage of companies integrating ci functions increased from 63% to 76% in this period (gia, 2011) and that decision making was 15% more efficient in companies that utilize ci functions (gia, 2013). ci originated from military intelligence and dates back to sun tzu and is thereby an art in addition to being a science (prescott, 1999). its systematic use in the commercial and business world is fairly recent and many academics have studied their country’s ci practices (calof et al., 2015). soilen (2013) reviewed fifty-one articles written by eighty-three authors, mostly from the united states, canada and the united kingdom, published in the journal of journal of intelligence studies in business vol. 8, no. 2 (2018) pp. 43-61 open access: freely available at: https://ojs.hh.se/ 44 competitive intelligence and management (jcim) between 2004 and 2008. he found that the main topics of research were the development of ci in general or in specific countries, followed by studies defining ci and studying its growth in time, and finally, business intelligence and its applications. little research has been conducted on the application of ci in developing countries (ifan et al., 2004; zhan and chen, 2009; wright et al., 2013; du toit, 2013; du toit and sewdass, 2014; rodriguez salvador and salinas casanova, 2012; rodrigues and thome e castro, 2017) with only a few isolated efforts focusing on the spanish speaking communities of south america (aguirre, 2015; guarrochena and paul, 2013; salazar et al., 2014; villaroelg et al.,2015). thus, this study explores for the first time the ci practices of export companies in the fresh grape sector in peru. hence, it could inspire peruvian companies and promote more studies of ci in south america. in addition, very few studies about ci in agriculture have been undertaken (bisson 2014). the purpose of this study is to create a typology of peruvian fresh grapes exporters’ ci practices and to investigate the relationship between the size of the company, the share of grapes exports in total exports, the percentage of the red globe variety in total grapes exports and the size of the farm with their ci practice levels and the average price received at export. the remainder of the paper is organized as follows: we first provide a brief comparison of the conception of competitive intelligence in english and spanish literature, then we deal with ci in peru followed by the importance of fresh grapes in peruvian exports. the methodology used in this research is described and the results are then presented and discussed. finally, we conclude with an examination of the implications and limitations of this research and suggest further research that may be undertaken. 2. theoretical background 2.1 the competitive intelligence conception in english and spanish literatures in the english literature, there is no universal definition of ci accepted by all (du toit, 2015; wright et al., 2009). haddadi et al. (2010) emphasize that the lack of an accepted definition renders this field unstable. ci was developed in the early 1980s (presscot, 1999) in the us, focusing originally on competitors under the influence of porter (1980) and was then broadened to include all actors in the market. although it is commonly accepted that ci makes use of information from outside the organization (and is thereby based on monitoring or scanning the organization’s environment), some authors (e.g. wright, 2011) consider that ci should also encompass internal information to fulfil the needs of decision makers. calof et al. (2015) categorize the definitions by those who focus on the objectives of ci, i.e. to enlighten decision makers and those who explain it by how ci is performed thereby centered on the intelligence cycle. this cycle has four steps (kahaner, 1997): i) planning and direction; ii) collection; iii) analysis; and iv) dissemination. thus, after defining the key intelligence topics, information is gathered, analyzed and the results are disseminated to people who triggered the cycle. pellissier and nenzhelele (2013) studied 50 ci definitions and determined that 38 referred to ci as a process and 4 as a product. in terms of its objectives, ci has been defined by du toit (2013, 30) as “… a strategic tool to facilitate the identification of potential opportunities and threats”. in the same vein, presscott and miller (2001) define it as any actionable intelligence that could provide a competitive edge. as a process, kahaner (1998, p.16) states that “competitive intelligence is a systematic program for gathering and analyzing information about your competitors' activities and general business trends to further your own company's goals”. likewise, fleisher (2004, 56) defines it as a “… systematic process by which organizations ethically gather and analyze actionable information about competitors and the competitive environment and, ideally, apply it to their decision-making and planning processes to improve their performance”. in contrast, rouach and santi (2001, p.553) suggest it is a creative process, or “the art of collecting, processing and storing information to be made available to people at all levels of the firm to help shape its future and protect it against current competitive threats: it should be legal and respect codes of ethics; it involves a transfer of knowledge from the environment to the organization within established rules”. soilen (2016) argue that definitions of ci and marketing intelligence are quite similar and overlapping, addressing the same phenomenon, but studied by different academic 45 disciplines. du toit (2015), based on 338 published peer-reviewed articles from 1994 to 2014 in the abi/inform database, found that the most popular term used in the literature is ci, followed by business intelligence and marketing intelligence. compared to the english literature, the main difference in the spanish literature is that competitive intelligence is linked to the term ‘technological watch’ in accordance with the norm une 166006:2011 (the spanish association for standardization and certification [aenor 2018]) and has risen in the spanish speaking community independently to the english speaking ci and marketing intelligence academic communities. for instance, professor escorsa has written numerous articles in spanish about technological watch while dealing with ci (see, for example, escorsa and maspons, 2001). in a similar vein rodriguez salvador and slinas casanova (2012) suggest that the ultimate objective of ci is to support innovation. 2.2 competitive intelligence in peru in peru, based on the largest number of publications found by the search engine of the peruvian repository for theses and academic papers, the most common terms associated with ci are business intelligence followed by marketing intelligence (concytec, 2018). from the total of 375 titles that appear in a search carried out on march 27th 2018, all were monographs or news items and there were only nine peer-reviewed articles, from which only two are related to the research topic. these two articles are a study that covers ten in-depth interviews about factors needed to promote foresight and competitive intelligence in 2040 (inche mitma et al., 2016) and a survey of 28 peruvian exporters and importers about implementations of market intelligence programs in their companies (tang tong, 2015). the lack of peer-reviewed articles about intelligence processes or programs to scan the environment in order to be more competitive in peru reflects the poor efforts to promote ci as well as the lack of human resources needed to develop ci as stated in the report by the national council of science, technology and technological innovation (concytec, 2017): i) there are only two public institutes of research which have technology transfer units and that perform activities of technological surveillance; one of these is the peruvian technological institute of production (itp). itp has been recognized as the first organization in latin america to obtain a certification for technological watch and ci according to the norm une 166006:2011 (aenor, 2018); ii) only two companies are offering this service of technological surveillance in the domestic market; iii) there are very limited educational offerings at universities and institutes. recently, concytec launched a five yearprogram (2017-2021) to promote capabilities in technological watch and ci as a means to achieve higher innovation, following the successful experiences observed in argentina and colombia. indeed, these two countries have set up technological observatories, providing access to scientific, technological and competitive knowledge that can be adopted nationally (concytec, 2017). some efforts to help exporters have been made through the peruvian export and tourism promotion agency (promperu), providing research studies of main export markets, which were developed by the market intelligence unit and are available on their web site (promperu, 2018). however, there are no reports monitoring the main markets. 2.3 the importance of fresh grapes in peruvian exports since the beginning of the 21st century, peru has emerged as one of the fastest-growing and most stable economies in latin america, with an average annual growth rate of 5.1% between 2007 and 2016 (the central reserve bank of peru [bcrp], 2018; world bank group, 2017). non-traditional agricultural exports, with fresh grapes making up the largest share, have shown an impressive compound annual growth rate (cagr) of 13.4% in the same period, accounting for 13% of total exports in 2016 (the national superintendence of customs and tax administration [sunat], 2017). the peruvian fresh grapes exports sector has been developing since the end of the 1990s and has grown at double digit rates driven by private investments and modern technologies, and the sector is vertically integrated and created with the sole purpose of serving the exports market (meade et al., 2010; world bank group, 2017). as a result, peru is the world’s fifth largest exporter of fresh grapes, accounting for 6.3% of worldwide grape exports in 2016 (international trade center [itc], 2017). the ministry of agriculture and irrigation of peru (minagri, 2017) estimated that the total production was 689,800 metric tons (mt) in 46 2016. this number has more than doubled since 2010, as a consequence of a wider growing area. the last census in 2012 estimated there to be about 43,800 hectares dedicated to grapes, covering both wine production and fresh grapes for consumption (the national institute of statistics and information [inei], 2013). this figure is likely to have also increased and it is estimated that there are 30,000 hectares in peru dedicated to fresh grapes, where the red globe variety is the most common with 80% of the total production (fernandez-stark et al., 2016). the increase in growing areas is mainly due to the perfect match between the peruvian production months and the months of lower production in the northern hemisphere. almost half of the production is exported during the higher production season i.e. from august to april, when the export price is on average three times higher compared to the local price (bcrp, 2018; minagri, 2017; sunat, 2018). as more companies got involved in exporting grapes due to higher prices, peruvian exports grew rapidly with a cagr of 24.2% between 2010 and 2016, impacting the world supply and leading to lower prices in recent years (itc, 2010-2017). 3. methodology 3.1 sample and procedure for the purposes of this study the model developed by wright et al. (2012) is used, a behavioral and operational typology of ci practice applied to smes and construed as being robust (ross et al., 2012; gaspareniene et al., 2013; smith, 2012; bisson, 2013; toker et al., 2016). this model was itself adapted from the study of wright et al. (2002) of ci active firms in the uk which addressed four strands: attitude, gathering, use and location. this model has inspired further work and replication studies carried out by adidam et al. (2009), april and bessa (2006), bouthillier and jin (2005), dishman and calof (2008), liu and wang (2008), oerlemans et al. (2005), priporas et al. (2005), rodrigues and thome e castro (2017) and wright et al. (2009). wright et al. (2012) added two new strands: technological support (“as degree of investment made to assist with gathering competitive information”) and it support (“as the type of systems used to manage the flow of competitive information”). in this way each strand is related to specific questions that later can be translated into a typology verdict for each exporter. a questionnaire using both closed and open questions was used to gather the data set. selfdeclared position statements were also included in the questionnaire to either confirm or contradict answers given within each section. the latter served as a clarification mechanism to identify any contradiction in a typology verdict. the questionnaire was available on-line in spanish and a secured link was created for each exporter. the target group was the peruvian grape exporters that had exported grapes according to the harmonized tariff code 08.06.10.00.00 in 2016 available in sunat (2017). peruvian customs provided a list of exporters that was then cleaned for the purposes of this research. the eligible sample comprised 80 export companies. all companies were contacted by telephone and/or reached by e-mail to be invited to take part in this study between october 2017 and march 2018. a total of 37 questionnaires were completed. the sample used in this research represents more than 60% of the total exporters (detailed in table 1). the unit price achieved by the companies of the sample was higher than the average for all companies. companies were classified as being a big, medium, small or micro company using as a reference the european union definition of an sme in terms of turnover and employee numbers (eu commission, 2003). table 1 characteristics of the sample size no. of companies total exports$ exports $/mt size no. of companies total exports$ exports $/mt big 14 8% 280,716,249 40% 2,267 big 8 22% 187,290,212 44% 2,336 medium 26 15% 191,600,688 28% 2,404 medium 15 41% 167,838,700 39% 2,518 small 51 30% 175,494,106 25% 2,080 small 10 27% 60,790,851 14% 2,309 micro 81 47% 46,430,922 7% 1,922 micro 4 11% 9,639,173 2% 1,988 total 172 100% 694,241,965 100% 2,225 total 37 100% 425,558,936 100% 2,391 the season starts in august and finishes in july the following year. universe season 2016/17 sample season 2016/17 47 more than half of the interviewees were top management, holding positions of ceo or chairman of the board, one fourth were management positions reporting to the ceo, and the remaining respondents were those reporting to first line management. most companies stated that they exported more than 75% of their sales and 32 out of 37 companies were vertically integrated throughout the main steps of cultivation, harvesting, processing and export. five of the companies did not cultivate grapes but acted as processors and exporters on behalf of other producers. the size of the farm was asked to those involved in cultivation and most companies stated they had more than 100 hectares for grapes cultivation. according to the last farm structure survey carried out in the european union in 2013, the largest agricultural holding size was found to be more than 100 hectares and these made up 2.7% of 12 million farms accounting for over 30% of standard output across the eu (european commission, 2013). similarly, in the latest peruvian agriculture census carried out in 2012, the largest farms were also found to be larger than 100 hectares and they were estimated to be 0.9% of 2.2 million farms (inei, 2013). 3.2 analytical approach the same set of descriptors utilized by wright et al. (2012) was used (see appendix 1), and the findings from this study were applied to this behavioral and operational typology of ci to reach verdicts regarding levels of gathering, attitude, use, location, it systems and technology support. furthermore, cluster analysis was used as an exploratory tool (kaufman and rousseeuw, 2005) to investigate whether there was any correlation between the size of the company, grapes exports share of total exports, the percentage of the red globe variety in total grapes exports and the size of the grape farm with the typology and the average price received at export between august 2016 and july 2017. 4. results and discussion 4.1 gathering this section asked about the type of information they collected, the sources they used, how much competitive information they obtained from their own employees, how they prepared their employees to address competitors, what type of financial return they expected from their ci effort and how much financial support was provided for ci activities. with regards to the type of information they collected, 284 responses were recorded, with customers, competitors, products in their market, suppliers and scientific articles and publications taking the top five places, closely followed by job market, laws, economy, politics and taxation policies. the items that were revealed as being of less interest were iso standards, patents, industrial processes, social and finance. interestingly, only one respondent included weather information, which is of utmost importance in agriculture, another respondent included certification requirements, which are compulsory for this kind of business due to food safety and traceability issues, and another respondent included yields in other countries, and phytosanitary barriers among non-tariff as well as tariff trade barriers. the most popular source of information was stated to be trade fairs followed by industry experts and industry magazines. this is indicative of reliance on a well-informed set of sources. an additional source of information was input received from employees, as 86% of respondents stated that they obtained either a moderate or high amount of competitive information from their own employees. however, the most sophisticated sources such as written evidence from verified sources, competitor research obtained from an external source, media analysis, management consultants and forecasting models were the least used. about 70% of respondents stated that they always or often trained and prepared their employees before they went to trade shows, exhibitions, conventions and other public events to make them aware of the type of information they should look for. however, the remaining 30% did this only ‘occasionally’ or ‘never’. only 59% of respondents said that they always or often briefed their employees on what they should not talk about to competitors, which demonstrates that companies are paying less attention to this area. this leaves 41% who are either naive or reckless about the importance of protecting the company’s sensitive information. considering that 81% of respondents stated that they evaluated the reliability of their sources of information, it is interesting to note that this task is not an easy one as the top three barriers to effective competitive information 48 gathering in the open question section, were reported as: i) access to the information; ii) reliability of the information; iii) lack of resources (mostly time) which were indicated by 57%, 54% and 38% of the respondents, respectively. concerning the financial support given by the organization for the task of monitoring the competitive environment, about 57% of respondents considered the support given to be adequate to do a reasonable job or enough to do a good job. on the other hand, 30% stated that: i) no funds were available as the tasks were done by interested people rather than intelligence experts; ii) funds were provided if an immediate financial benefit could be produced; iii) minimal support was provided to cover the basic tasks and simple gathering. the remainder stated that the activity received a set budget or that funds were available on request. based on the provided answers, the overall verdict inclined towards a hunter gathering level. however, the self-declared control statement showed that the verdict may be more nuanced as half of the companies used only public domain sources for their competitive information. thus, the verdict is hunter gatherer, but several of these companies take their desire for real as they are not using sophisticated ways to collect information. 4.2 attitude regarding how often the firm collected information about competitors, technologies and customers, the most frequent answer was weekly for customers and competitors while both monthly and irregularly were answered ‘when it becomes available or required for a project’ for technology. even though there seems to be a regular process to gather data, 41% agreed that it is not an organized process, and only 5% of the companies had a written process and a system dedicated to ci. therefore 95% of firms have no formalized process or dedicated system to handle gathered information. furthermore, 11% claimed that their companies provided ‘full commitment for understanding competitors’ and 70% stated that there was either ‘active support for current activities’ or ‘just about sufficient for immediate needs’. these findings are in line with the self-declared control statement in which 30% ‘try to understand specific questions for one-off projects’, 41% ‘try to understand the market in the short term’ and 22% had an integrated competitive information process where competitors were monitored to anticipate their moves and to plan a reaction. only 8% agreed that ‘we are too busy thinking about today to worry about tomorrow’. here the verdict was a task-driven attitude but significantly biased towards both an immune and operational stance. 4.3 use when asked how they used the collected information, 68% of respondents stated that they use it for both short and long-term decision making and 54% for scenario planning, leading to a verdict of strategic user. however, 41% stated that ‘there is no organized process for feeding ci output into the decision-making processes, leading to a verdict of joneses user. concerning the impact different factors have in the company decision making, ‘customer demands’ was the most frequent choice, followed by ‘competitors’ long term predicted behavior’, ‘competitors’ short term predicted behavior’ and ‘technological/technology standard changes’. these are congruent with the self-declared control statement in which 38% ‘use competitive information to help make decisions about price changes and promotional efforts’ and 46% use competitive information to identify opportunities and threats as well as to build scenarios. these findings suggest a verdict of strategic user but with a strong tendancy towards a joneses user stance. 4.4 location in this section, participants were asked whether employees knew who to pass information on to when they acquired it, and 92% of respondents stated either ‘always’ or ‘often’, with only 8% stating they knew ‘occasionally’. the top four departments that took responsibility for collecting ci were first sales (59%) and then general management (43%), followed by manufacturing & production (27%) and research & development (22%) with 22% of respondents stating also that all departments take responsibility. the latter response suggests that some companies work in a loose manner as they do not have a clear idea of who should take overall responsibility. when asked whether a dedicated intelligence unit is essential to successfully accomplish the monitoring task, only 16% responded with ‘always’ and 30% ‘sometimes’ 49 while 38% stated this to be ‘a good idea but not always essential’. the remainder responded with either ‘not needed at all’ or ‘it seems to work well without a dedicated unit’. based on the above findings, it came as no surprise that 89% of respondents stated that they did not have a dedicated intelligence unit, although 54% did have a person in their firm whose job is to gather, analyze, disseminate and store the competitive information, and in 65% of the cases this person participated in senior management meetings. in sum, the verdict was an ad-hoc location approach. 4.5 technology support this strand deals with the type of tools used by the companies to gather information. the most frequently used tools were websites (92%) and google (86%), followed much less frequently by specialized databases such as derwent, dun & bradstreet and euromonitor (41%) and specialized websites, for example espacenet for patents (22%). this is in line with the selfdeclared control statement in which 72% of respondents stated they ‘use common, freely available tools for web searching, such as google’. however, 14% of respondents ‘use full versions of meta-search engines and are also familiar with specialist databases for patent and financial information’ and 14% ‘use software that allow users to collect, analyze and disseminate information automatically’. the verdict was overwhelmingly a simple technology support stance. 4.6 it systems this section addresses the it systems used to manage competitive information in the companies. about 49% of the respondents stated that they did not use any systems at all to manage their competitive information and agreed with the statement that ‘it is in our minds and we rely on our memories’. this contrasted with the next largest categories, chosen to a much lesser extent, with 16% stating that ‘we use it systems to manage competitive information but to ensure the safety of our information we prefer paper records and do not really like relying on computers, or somebody else’, 19% stating they used off-the-shelf and 14% stating they used a bespoke development. this is in line with the control selfdeclaration in which 38% agreed they did not use it systems to manage competitive information and ‘rely on our memories and the good will of staff to share what they learn’ and 22% stating they ‘prefer to stick to traditional methods of managing competitive information by using paper records’ and agreed with the statement that they ‘do not really trust computers’. however, this is in contrast to the 22% which claimed to have designed their own in-house system unique to the firm and its needs. here the verdict was a dismissive it systems stance with a strong tendency towards bespoke it systems. 4.7 the typology of peruvian grape exporters’ ci practice levels the verdicts for each strand i.e. gathering, attitude, use, location, it systems and technology support are summarized in figure 1. the peruvian grape exporters appear to be aware of the importance of ci but they lack knowledge, organization and dedicated it. hence, thanks to the evaluation carried out in this study, companies can see the path to follow that should lead them towards higher ci practice levels to help them better address a faster and harsher competitive environment. 4.8 cluster analysis by size of company with regards to the six strands of the ci typology studied, practices among big, medium, and small & micro companies are rather similar to the findings for the total sample as shown in table 2 (for more details, see appendix 2). however, big companies have a more immune attitude compared to the task driven attitude of medium companies and the operational attitude of small companies. furthermore, about the use of information, if big and small & micro companies are at a strategic level, medium companies are the lowest one. in general, for all the ci strands, the percentage of small & micro companies are at higher levels. one can construe that these small & micro companies need to be more aggressive to survive as they compete with bigger companies and that consequently they seem to be more aware of the value of information for competitiveness. despite this, medium companies registered higher average prices (free on board [fob] peruvian port us$ 2,518 per metric ton) compared to big companies (fob us$ 2,336 per metric ton). the small & micro companies registered the lowest average price (fob us$ 2,259 per metric ton). this cannot be interpreted to mean that big companies have a 50 more challenging job placing their grapes in the market compared to medium sized companies as it is shown later that the larger the grape farm the better results in price per ton. this suggests that a positive behavior towards ci pays off as medium sized companies show a higher level in this strand compared to big companies, with more cases of technology and it support being utilized. this also suggests that the ci level is independent of the size of the company in line with the results of priporas et al. (2005). 4.9 cluster analysis by percentage of grapes exports in total exports this cluster confirms that those companies that do not concentrate primarily on grapes, with grapes representing less than 75% of their total exports, have a stronger attitude towards an operational stance compared to those which are less diversified and tend towards a taskdriven attitude. however, it shows that a concentration as opposed to a diversification strategy pays off as the price per ton is significantly higher in those companies concentrating on grapes (fob peruvian port us 2,677 per metric ton) compared to those that do not (fob us$ 2,133 per metric ton). 4.10 cluster analysis by percentage of red globe variety in total grapes exports companies with a concentration of the red globe variety higher than 50% received a significantly lower price (fob peruvian port us$1,881 per metric ton) compared to those that have less concentration in this variety (fob us$ 2,605 per metric ton). however, this cluster shows homogeneous results compared to the sample. it is worth noticing that higher value grapes increase the labor and handling costs, which moderate the variety choice (fernandez-stark et al. 2016). 4.11 cluster analysis by size of farm this cluster was analyzed based on those companies that have grape cultivation. it indicates that the companies with less than 100 hectares and more than 501 hectares behave differently from the average sample. indeed, those companies with less than 100 hectares show a stronger attitude towards an operational stance, which somehow is figure 1 the behavioral and operational diagnostic typology of peruvian grape exporters’ competitive intelligence practice. 51 translated into a higher level of it systems use, and the use of the information strategically. on the other hand, those companies with more than 501 hectares also show a stronger attitude towards an operational stance, which is also translated into different levels of higher it systems with more technology support, but they do not use the information strategically. this cluster confirms that the largest grape farms, with more than 501 hectares, obtained a better price (fob peruvian port us$ 2,444 per metric ton) compared to the lower prices seen for 101-500 hectare grape farms (fob us$ 2,413 per metric ton) and much higher prices than 100 hectares grape farms (fob us$ 1,932 per metric ton). this can be interpreted to indicate that there is an advantage in having a higher critical mass volume for exports, since some importers prefer larger volumes from a few growers that can ensure quality consistency, food safety and traceability. 5. conclusion this paper aims to create a typology of peruvian fresh grapes exporter ci practices. overall, this sector shows positive behaviors towards ci but cannot make the most of it due to the lack of technological and it systems support, lack of knowledge and dedicated organizational structures. the first verdict is that this sector displays the hunter gathering stance, which is a key indicator to engage in ci practice. however, evidence also suggests that there is still too much effort spent on easy gathering from public sources producing volume, not value. the second verdict is that exporters show a task-driven attitude where questions are asked and answered with little value added. in order to reach the ideal state of a strategic attitude, top management should embrace ci as essential for future success, addressing ‘what if’ questions for both short and long-term decisions, anticipating changes and planning possible courses of action. the third verdict is that this sector is a strategic user, which is the optimum state but is strongly biased towards joneses user as the knowledge learnt is not retained for the future. the fourth verdict is ad-hoc location instead of dedicated location for ci practice, despite the fact that almost half of respondents have a person who gathers, analyzes, disseminates and stores competitive information. in order to have a successful ci program, it is necessary to define roles and responsibilities with a specific location within the organization. this way strand gathering attitude technology information system use location cluster verdict verdict verdict verdict verdict verdict company size* big g2 a1 ts1 is1 u4 l1 medium g2 a2 ts1 is1 u1 l1 small & micro g2 a3 ts1 is1 u4 l1 % of grapes exports in total exports** higher than 75% g2 a2 ts1 is1 u4 l1 lower than 75% g2 a3 ts1 is1 u4 l1 % of red globe in total grapes** lower than 50% g2 a2 ts1 is1 u4 l1 higher than 50% g2 a2 ts1 is1 u4 l1 total g2 a2 ts1 is1 u4 l1 grapes farm size lower than 100 hectares g2 a3 ts1 is1 u4 l1 between 101 and 500 hectares g2 a2 ts1 is1 u4 l1 higher than 501 hectares g2 a3 ts1 is1 u1 l1 total g2 a2 ts1 is1 u4 l1 sources: * peru: top publications (2018) ** sunat (2016-2017) table 2 cluster analyses. 52 redundant work is avoided and it empowers the person in charge to develop technical and cognitive skills to deliver the right ci to the right person at the right time. the fifth verdict is that this sector uses very simple tech support, which does not require specific knowledge, commonly using spreadsheets for their analysis and accessing web sites displaying old information that provides limited value. with globalization, increasing data complexity and speed of change, it is of the utmost importance to invest in integrated systems (e.g. scanning systems) that provide information in real time and allow this information to be aggregated. the last verdict is dismissive it systems support as companies do not use any it systems to manage strategic information. the second aim of this paper explored whether the size of the company or the export level of these companies impact their ci practice level. according to the cluster analysis by size of company, ci practice level is independent of the size of the company as big, medium and small & micro companies show almost homogeneous results among the six strands. however, it seems that a slightly higher level of attitude and it systems support pays off as medium companies show a higher price per ton compared to big companies. this does not mean that large companies have to struggle more to place more volume as cluster analysis by size of farm makes it clear that the larger the grapes farm size the higher the price per ton. the cluster analysis of grapes exports in total exports suggests there are advantages to specialization instead of diversification, as companies with grapes exports representing more than 75% of their total exports receive a higher price per ton compared to those whose grapes exports were below 75% of their total exports. finally, the cluster analysis of the ratio of the red globe variety in total grapes exports, shows that significantly lower prices are received by companies that have more than 50% red globe in their total grapes exports. however, this cluster shows homogeneous results compared to the sample. the results of this study provide empirical evidence to the peruvian government authorities about the need to promote training and the adoption of dedicated technology among companies in order to achieve higher levels of ci practices. furthermore, peruvian authorities as well as other south american governments can benefit from the experience of other countries that have government sponsored ci programs, specifically canada (brouard, 2006; tanev and bailetti, 2008; tarraf and molz, 2006), france (bisson, 2010, 2013; salles, 2006; smith et al., 2010) and switzerland (begin et al., 2007). 5.1 limitations and further research as the sample size is limited, this experiment could be extended, for example, to all nontraditional agricultural peruvian exports to confirm the findings reached in this study and to be able to address smes, which are known as pymes in latin america, to help peruvian authorities to better address their needs. based on the experiences 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(2009). competitive intelligence monitoring in the risk prevention of sme's. journal of service science and management, 2(3), 230-235. 56 7. acknowledgement the authors thank all participants who helped in the study and the universidad de lima, peru which supported the fieldwork of this research. 8. appendi̇ces attitude immune attitude a1 task driven attitude a2 operational attitude a3 strategic attitude a4 too busy thinking about today to worry about tomorrow. thinks that the firm is either so small, so big or so special that it enjoys immunity from competitors and thus ci is a waste of time. minimal or no support from either top management or other departments. finding answers to specific questions and extending what the firm knows about its competitors, usually on an ad-hoc basis. departments more excited about ci than top management who don’t see the benefits. a process, revolving around the company as its centre, trying to understand, analyse and interpret markets. top management usually trying to develop a positive attitude towards ci because they can see it might increase profit, and therefore personal bonuses. unwilling or unable to think about the application of ci for the long term. an integrated procedure, in which competitors are determined as those who are satisfying our customer's needs, current and/or future. monitoring their moves, anticipating what they will do next and working out response strategies. receives both top management support, cooperation from other departments and is recognised by all as essential for future success. 57 gathering easy gathering g1 hunter gathering g2 firms which use general publications and/or specific industry periodicals and think these constitute exhaustive information. unlikely to commit resources to obtain information which may be difficult or costly to obtain. always looking for an immediate return on investment. firms knowing that easy gathering information is available to all who care to look. realise that if ci is to have a strategic impact then additional, sustained effort is required. resources are available which allow researchers to access sources within reasonable cost parameters, back their instinct, follow apparently irrelevant leads, spend time talking, brainstorming and thinking about ci problems without always being pressured for “the answer”. firms which appreciate and support intellectual effort. 58 use joneses user u1 knee jerk user u2 tactical user u3 strategic user u4 firms trying to obtain answers to disparate questions with no organisational learning taking place. has commissioned a ci report from a consultant because that is what everybody else has done. firms which obtain some ci data, fail to assess its quality or impact, yet act immediately. can often lead to wasted and inappropriate effort, sometimes with damaging results. such firms are most vulnerable to planted mis-information by competitors who are more ci aware. ci used mostly to inform tactical measures such as price changes, promotional effort. some firms can successfully argue that ci loses its impact and timeliness if it gets stuck at the strategic level but are, nevertheless, acutely aware of its potential value to the business. ci is used to identify opportunities/threats in the industry and to aid effective strategic decision making. all levels of staff, both management and operational, are aware of csf’s and their attendant ci requirements. continuous, legal measures are used to track competitors, simulate their strengths and weaknesses, build scenarios, and plan effective counter attacks. decision makers are involved in a high number of “whatif?” discussions to which ci data is applied. contingency planning and counter intelligence is a part of normal strategic thinking. action plans are implemented and mistakes are seized upon as learning rather than firing opportunities. open and facilitative management culture which displays trust and encourages involvement. 59 location ad-hoc location l1 designated location l2 firms with a specific intelligence unit, full time staff, dedicated roles, addressing agreed strategic issues. staff have easy access to decision makers, status is not a barrier to effective communication. no dedicated ci unit. intelligence activities, where undertaken are on an ad-hoc basis, subsumed into other departments, with intermittent or non-existent sharing policies. technology support simple technology support ts1 average technology support ts2 advanced technology support ts3 high technology support ts4 the company is just using the free web such as a search engine or looking at some web sites which require no specific knowledge. also use general office software such as spreadsheet. using “off the shelf” products such as meta-search engines which simply reorganise publicly available information for the firm use. the company might use web site which require specific knowledge (e.g. espacenet) and pay to use some specialised websites and databases (e.g. patent and finance). this information system holds vital and high level information as well as operational and tactical material. is fully integrated across the business and continually evolves to meet the firm’s requirements. content analysis (e.g. statistical analysis) provided. in addition to advanced tools, firms use “clever” algorithms aimed at understanding automatically the competitive information collected. these algorithms are based on semantics. 60 it systems dismissive it systems its1 sceptic it systems its2 standardized it systems its3 hosted it systems its4 tailored it systems its5 bespoke it systems its6 a standard existing system is purchased from a software vendor and installed on computers located within an organization. a standard system is used, but it is not managed by the company itself (e.g. pay per view system). in a tailored development, an off-the-shelf system or hosted solution is tailored according to an organization’s needs regarding its competitive information. unique to the firm system which has been designed in-house and aiming at collecting, analyzing and disseminating competitive information. does not use any it system to manage competitive information has a system to manage competitive information but prefers to use paper based records. does not trust it systems sufficiently and is wary of their reliability 61 page 4 editors note vol 10 no 3 editor’s note vol 10, no 3 (2020) labeling or science-by-buzzwords: the semantic trap in academic research and how to get out of it the social sciences are drowning in new fancy academic terms or buzzwords, labels with unprecise definitions, rebranding phenomenon that somehow seem familiar. we are all surrounded by smart cities, innovation, and sustainability. what do these terms mean that we could not express earlier? introducing them also raises new questions, which at first may seem provocative: are there dumb cities too, if so where? do we carry out research at our universities that is not innovative? does the literature on sustainability make our products more sustainable? above all, these new fields are formulated in almost suspiciously positive terms attracting the attention of our politicians and echoed everywhere. how can anyone be against smart cities, innovation and sustainability? it must be good, important and therefore it deserves funding. creating new terms to describe what is mostly old and familiar problems (relabeling) is not helping move science forward but instead hindering its development as it leads the researcher to believe he or she is setting out on a new quest, while often just ignoring past literature, especially that written in french and german languages, which then suddenly does not apply. the same is true for intelligence studies. “research” today is too often reduced to searching for articles in one of two commercial databases: web of science (clarivate analytics) or scopus (elsevier), basically consisting of articles that has been written during the past two generations. here we are supposed to cite the most cites articles, even though the same ideas (but with different words) have been expressed numerous times before in older articles, books or are just common sense, so that whoever wrote the first article become popular. this then is the pyramid scheme of the brave new world of the social sciences, a system that creates academic peacocks the majority of social science researchers today are not first of all knowledgeable in say economics or business, but of how to produce articles. that is a skill that has less to do with what is happening in the real world of social behavior. that is the price we must pay, some say, but the actual production of research also attracts very little attention outside of the circle of academics who contribute to it. moreover, it makes our business education less relevant. ask yourself, if today’s business education was relevant, why are the chinese outperforming the west? why are there so few famous business schools in economically successful countries like germany, taiwan, or south korea? who teaches you how best to succeed in business life, the authors of the most cites scientific articles in business and management or the chinse classic authors, like confucius or sun tzu? when i got interested in intelligence as a business student it was based on the notion that better information can make organizations more competitive. this was still during the first generation after the start of what was called the information age, when companies realized that information and knowledge, not physical assets, were the most important ingredients for business success. there was no internet, nor mobile phones. i was interested in the following questions: 1. how do organizations work with information? 2. what is the most effective way for organizations to work with information to obtain a competitive advantage? 3. why are organizations not working more effectively with information? i was interested in these questions from an international perspective, curious about the relationship between specific cultures and production. so, much like marco polo, i asked myself: journal of intelligence studies in business vol. 10, no 3 (2020) p. 4-7 open access: freely available at: https://ojs.hh.se/ 5 4. what can we sell to other countries and what can we buy from them? 5. what is the best way of doing this? i am still predominantly interested in these questions and marco polo seems to follow me in my thoughts wherever i go and seek new knowledge. i am not interested in the semantics surrounding these questions, the new terms that are introduced more as labels than to give a more exact definition of the underlying phenomenon we are looking at. to make things even worse, these new labels change, and quite frequently, in what looks like ever-shorter life cycles of social science research fields, replacing each other after quick overlaps. it is much like watching trends in the clothing industry. suddenly you realize that your corduroy pants that work perfectly and have no holes in them need to be changed out. your surroundings demand it. to take a more fitting example: i was interested in how people work together with information as we started a research project on why employees hide information. here, i am not interested in collective intelligence, competitive intelligence, co-creation, wisdom of crowds, knowledge management, complex systems, or systems theory, just to take some examples. i am first of all interested in the problem. many academics mix labels with theory. theory does not mean to name labels, but to present similar problems in other studies, to say if they reached similar or different results and to try to explain why this may have been the case and what it means for our own study. this can be done almost completely without using labels. still, i tend to spend more time on semantics than on actual problems, very much against my own will. it’s like my academic surroundings impose this on me. it seems that most business researchers fall into the same semantic trap. it’s not only due to how we label problems with key words in databases, but also to the way we organize ourselves as researchers. the process can be explained as follows: business researchers quickly try to own the terms that they become interested in instead of focusing on the problems and problem areas that they are interested in. instead of broadening the field, we narrow it, becoming specialists in ever smaller parts, all with their own labels. after a few rounds we are no longer in contact with business life anymore. there is another variation of this problem and that is when the academic discipline is in close contact with industry even though it is erroneous. to me the scariest example of this is the study of economics after keynes, which is sometimes referred to as neoclassic economics. it seems clear to me that the major reason that banks, the financial sector and the organizations supporting this industry pay lip service to the study of modern economics is that it legitimizes a corrupt and close to bankrupt system that does little good to others outside of its own members. any problem can be studied from the perspective of numerous terms. often it does not matter which term we use as there are many terms that overlap and can be relevant simultaneously. instead of accepting this, academics strive to own the terms they chose to use and to disown others, especially those that are closely linked. as soon as we identify ourselves with one term, we start to oppose other, similar terms, treating them almost as competitors, as we often compete for the same or similar research positions and grants. new academics come along and pick their label, often by accident, for example, when adopting the preferred label of a supervisor, until each term forms or constitutes an academic tribe. these academic tribes then develop their own conferences and journals, and an internal struggle finds place, a race to establish legitimacy around an internal hierarchy most often built on the popularity (impact) of articles, and less so on the quality of the content or its relevance. it’s also possible to be in several tribes at the same time, even though academics normally have a clear preference of one above the other, simply because it’s difficult to excel in more than one area. as an example, authors in the field of collective intelligence also study artificial intelligence, collective behaviour, swarm intelligence, complex systems, machine learning, human-computer interaction, multiagent systems, sustainability, information systems design, crowd work, evolutionary computation, social decision making, empathy justice, foresight, futures research, crowdsourcing, information systems network, and/or democratic theory. collective intelligence is used synonymously or in combination with co-creation, wisdom of crowds, opens source, social systems, and social complexity, all with their own tribes. within intelligence studies we have sub-tribes in the form of competitive intelligence, market intelligence, competitor intelligence, business intelligence, enterprise resource planning, social intelligence, all of whom deal with the problem of collective intelligence. close by there are the tribes of futures studies and foresight. in a corner sits the library sciences. across the road there are the tribes of decision making, decision sciences, information sciences. all are quite familiar with the same phenomenon studied as collective intelligence. in other disciplines there are similar labels and key words, for example collective behavior in the study of sociology. the problem is that researchers seldom direct their attention outside of their own tribe. this is not only an odd scientific process, but we are witnessing an enormous waste of intellectual ability and potential. so, how do we solve it? 6 to become more relevant academic research must redirect its focus from buzzwords to problems, not just smart “research gaps” in the literature. instead of listing keywords, researchers, academic journals and academic databases should list problems (1), and the problems should be stated in full sentences (2) using as few (3) and as simple words as possible (4). we should also insist on clear, mutually exclusive definitions. by searching for problems instead of labels it will become much easier to find relevant research across different labels and disciplines. we need to be much stricter when admitting new labels. if a new term is not exact and not much different from a previous term it should be declined. focus should be on what the germans since the 19th century understand by “verstehen”, as the "interpretive or participatory" examination of social phenomena, not on coining new terms. today new terms often come to life because we did not read enough, or we thought more about internal marketing and our own self-promotion instead of focusing on problems that are important for humanity. we are all guilty of this to a certain degree as it’s difficult to escape the logic trap that is our current social science research system. we need to instill a new critical process of thinking by asking: what problem does this field of study lay claim to? are there other studies that lay claim to the same problem? if yes, go back to the previous field. if it does not exist anywhere, and if you are 100% certain, only then can you coin a new term after consulting with your peers. this process would lead to the merger of most of all existing social science research today. the same could then be done with conferences and academic journals. larger academic groups will again improve the quality of journals and conferences, thus improve the advancement of science. to complicate things further labels are sometimes decided outside of academia. the world of business is basically changed by its practitioners, not by academics. as an example, competitive and market intelligence is now often replaced by competitive and market insights (cmi) in many major companies. the intelligence label was always problematic and the association to the world of spying never quite washed off. it did not help that many successful business intelligence companies functioned more as private eyes with aggressive methods despite organizations like scip setting standards to the contrary. many were also skeptical to what they understood as an anglo-saxon and predominantly american agenda to spread the practice of industrial espionage advocated by consultants centered around langley. the difference between the term intelligence and insights is not significant. it basically means the same: valuable information, need-to-know for the competitiveness of the firm. put differently, there is hardly any part of insights that cannot be seen as intelligence and vice versa. however, it could be argued that market insight is a broader take on business information. it could be said that it brings together a wider group of fields, both practitioner and academics, some of whom were left behind in the process when smaller academic tribes were created. market researchers, business intelligence specialists and all kinds of information scientists are now lured back together under the umbrella of earlier pioneers like the visionary businessman alvin toffler, the mathematician claud shannon, and gabriel naudé, the father of library sciences, just to give a few examples. the “insight people” have already started to form their own group. academics are likely to follow. other academics are already finding themselves sitting in groups that are no longer relevant wondering what happened. the academic projects that are the most successful will always be those that follow the development in business life. the discipline of digital marketing is a good example. digital marketing is fundamentally different from the old “brick marketing,” to the point that if you do not understand its logic today then your education is not relevant any longer. it took academia a long time to understand this and for a few years the whole discipline of marketing was terribly far behind reality. the advancement of the field still almost exclusively finds its place in business organizations. academics are mostly trying to run after and catch up with the practitioners in this field of study. one reason for this is that advancements in digital marketing demand substantial it infrastructure that academics do not have easy access to. the situation is similar in business intelligence, which is basically about new software today. the leading ai experts do not work in academia but in the major tech companies. it is all about being relevant and useful. in intelligence studies there is a demand on us that we integrate business practices with more technology (hardware and software). only then can we hope to make real academic contributions in this field. we stand in front of an almost awkward situation: the intelligence field has never been more relevant in the history of mankind as information has become the most important ingredient for competitive advantage. and the more information, and the better information, the more valuable the company. all the new and major mnes around us are living proof of this, whether it be alphabet (google), netflix, spotify, facebook or alibaba. to understand and be able to contribute to this domain we must be interested in the same problems that they are trying to solve. to this aim the labels are often just distractions, asemantic trap. the first three articles in this issue deal with different forms of literature and domain analysis, linking competitive intelligence to other fields of study. 7 the article by miguel-ángel garcía-madurga and miguel-ángel esteban-navarro entitled “a project management approach to competitive intelligence” examines the relationship between competitive intelligence (ci) and project management (pm). the article by mouhib alnoukari is entitled “an examination of the organizational impact of business intelligence and big data based on management theory”. according to a literature analysis done by the authors, both the dynamic capability view and resource based theory are the most dominant organizational theories that have been used to investigate bi & bd related issues. the article by stefan zwerenz is entitled “the linkage between competitive intelligence and competitive advantage in emerging market business a case in the commercial vehicle industry”. the results of this case help businesses to improve ci, its constructs, its products and process for a better linkage to competitive advantage and firm performance. the last two articles are related to accounting. the article by phan thi bao quyen and nguyen phong nguyen entitled “the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use” studies the accounting benefits of adopting erp systems. the authors conclude that there is support for perceived accounting benefits of erp systems on enterprise success. they also argue that this conclusion is supported by effective system use. the article by muhammad ikbala, irwansyaha irwansyaha, ardi pamintob, yana ulfaha, and dio caisar darmac entitled “financial intelligence: financial statement fraud in indonesia” deals with the problem of financial fraud in indonesia. the results of the non-parametric relationship analysis show that although there is a possibility that the more experienced the auditor will be the more able to detect fraud and manipulation in the organization, the relationship is relatively weak. findings also show that all auditors who have a cfe certificate find it easier to find fraud in the company. with this issue jisib celebrates 10 years of publications. during the first years it was difficult to get enough quality articles for every issue, but now we get interesting and relevant articles submitted every week and reject more than 80%. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. take care in these strange times when a new virus, covid-19, is ravaging the planet. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2020 jisib, halmstad university. all rights reserved. o p i n i o n s e c t i o n 51 patents used by npe as an open information system in web 2.0 – two mini case studies abdelkader baaziz 1 , luc quoniam 2 1 aix-marseille university, france 2 university of sud toulon var, france email: kbaaziz@gmail.com, mail@quoniam.info received september 23, accepted november 1 2014 abstract: the information systems around patents are complex, their study coupled with a creative vision of “out of the box”, overcomes the strict basic functions of the patent. we have, on several occasions, guiding research around the patent solely-based on information, since the writing of new patents; invalidation of existing patents, the creation of value-added information and their links to other information systems. the traditional r&d based on heavy investments is one type of technology transfer. but, patent information is also, another powerful tool of technology transfer, innovation and creativity. indeed, conduct research on the patent, from an academic viewpoint, although not always focusing only on financial revenue, can be considered as a form of “non practicing entities” (npe) activity, called rightly or wrongly “patent trolls”. we'll see why the term “patent troll” for this activity is controversial and inappropriate. the research we will describe in this paper falls within this context. we show two case studies of efficient use of patent information in emerging countries, the first concern the pharmaceutical industry in brazil and the second, the oil industry in algeria. keywords: open information system; open data sources; knowledge database discovery (kdd); patent information; patent invalidation; patent troll; non practicing entities (npe); reverse engineering. available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 2 (2014) 51-60 mailto:kbaaziz@gmail.com https://ojs.hh.se/ o p i n i o n s e c t i o n 29 1.0 introduction “whoever finds what he seeks, he has done generally a good job as a schoolboy, focusing on what he wants, he often neglects the signs, sometimes small, that bring something over than the object of his forecasts. the true researcher must pay attention to signs that reveal the existence of phenomenon that he does not expect.” (1) this quote (freely translated) of the french physicist louis leprince-ringuet (1957) shows perfectly the research that can be conducted on open data and particularly on “patent” information. the information systems around the patents are complex, their study is coupled with a creative vision of “out of the box” (swinner & briet, 2004), overcomes the strict basic functions of the patent. we have, on several occasions, guiding research around the patent since the writing of new patents, invalidation of existing patents, the creation of value-added information and their links to other information systems (quoniam, 2013). the patent is undeniably one of the more important tools of technology transfer, innovation and creativity. indeed, talking about patent is talking about research & development (r&d). however r&d without marketing is expensive. marketing is also expensive, where the needed steps of “licensing” are worth to dispense with r&d or marketing. this is one kind of technology transfer. but “generic”, “public domain”, “open data” and “reverse engineering” are other forms of technology transfer, without necessarily financial reward. thinking that way is looking at the patent with other eyes (quoniam, 2013). those who act in this manner are called rightly or wrongly, “patent trolls” or, in less pejorative term “non practicing entities (npe)”. 2.0 patent trolls & non practicing entities a non practicing entity (npe) is a person or company that amasses patent rights. the patents typically belong to a single technological field, or a grouping of related technologies. the npe does not practice the patents, meaning that the npe does not 1 louis leprince-ringet in “des atomes et des homes”, fayard, paris, 1957, page 57. produce any goods or provide any services based on the patents rights that are held (halt & al., 2014). a patent troll is defined as one type of npe. patent trolls use the licensing and patent litigation as a business model (quoniam, 2013). they purchase large numbers of patents, often from bankrupt firms, with the intention of launching patent infringement suits against companies and individuals that they maintain have illegally used some element of something for which they hold the patent. a highly publicized case was that of research in motion (rim), manufacturer of blackberry mobile phones, which was ordered to pay $ 612.5 million to new technology products (ntp) to stop the litigation instigated to the courts. however, patent trolling is not a new phenomenon. already in 1878, senator issac christiancy seemed to have patent trolling in mind. he rightly noted: “among a host of dormant patents, some will be found which contain some new principle … which the inventor, however, had failed to render of any use in his own invention. and some other inventor, ignorant that such a principle had been discovered . . . had the genius to render it of great practical value … the patent-sharks among the legal profession, always on the watch for such cases, go to the first patentee and, for a song, procure an assignment of his useless patent, and at once proceed to levy blackmail upon the inventor of the valuable patent.” (2) in fact, the term “patent troll” appeared in the late 1990s and was used at least once in 1993 with a different meaning, to describe countries that file aggressive patent lawsuits. excessive patent protection by the big firms may hamper further innovation, especially when they limit access to essential knowledge, as in the case of emerging technological fields. in this context, too broad a protection on basic inventions can discourage follow-on inventors if the holder of a patent for an essential technology refuses access to 2 as quoted in gerard n. magliocca, blackberries and barnyards: patent trolls and the perils of innovation (2007), notre dame law review, june 2007. available online: http://ssrn.com/abstract=921252. o p i n i o n s e c t i o n 53 others under reasonable conditions. this concern was often expressed for new technologies in the fields of genetics and software (oecd, 2004). 3.0 “the good, the bad and the ugly” conduct research on patents, from an academic viewpoint, although not always focusing on financial revenue, can be considered as a form of npe activity (quoniam, 2013). the research that we will describe in this paper falls within this context. we'll see why the term “patent troll” for this activity is controversial and inappropriate: first, this activity may be described as "soft research and development" because it relates to innovation i.e., conducting r&d, discovering and creating new knowledge without the traditional r&d laboratories, but solely from the information available in open data sources including the patent databases; second, from research based solely on the information, it can lead us to invalidate existing patents or write new patents in a given technical field; third, this research could be described as research social responsibility (rsr), with legal and legalistic action, similar to corporate social responsibility (csr) activities for academic research; fourth, it refers to an unconventional form of thinking “out of the box” by setting strong links between “hard technologies” and “soft technologies” (jin, 2005), and establishing transitions from one to the other and vice versa, based on open data sources and patent information. shrek, a good friendly ogre and famous in the movies industry, has supplanted all the bad ogres and other ugly trolls of medieval legends. this caricatured picture illustrates the differences between the forcing exerted by the bad ogres (the big firms that create barriers to innovation), the blackmail used by ugly patent trolls in the common sense of the term (licensing with purely financial goal), and actions taken by the good patent trolls (technology transfer mediator, knowledge disseminator and know-how sharer). we therefore suggest a new term for naming the good trolls, why not patent robin-hoods? 4.0 conceptual frameworks and foundations intellectual property consists of two parts: copyright and industrial property rights. the latter includes inventions (patents), trademarks, industrial designs and indications of geographical origin. the relationship between intellectual property and economic development is obvious and has been the subject of many publications. it is part of the tangible manifestations of intangible activities related to “knowledge societies” (binde, 2005). in industrial property, patent plays a key role, by its strategic importance as it represents a property right for an invention, for a product or process that provides a new technical solution to solve a problem. the conditions for obtaining such ownership, conditions of validity of these rights and how to enforce them, are described in the literature (quoniam, 2013). we are interested here in a patent from a strictly informational viewpoint and opportunities for exploitation thereof for purposes other than strict property rights. the patent is seen as a way to communicate to the market purely technical and technological research. we show that the patent can be a way to conduct research, well beyond strict technical research. it allows you to work on many fields related to “soft technologies” (jin, 2005) and put into perspective the evolution of “hard technologies” to “soft technologies”. 5.0 criticism of maslow’s model (1943) & aziz ungku’s model (1983) o p i n i o n s e c t i o n 54 fig. 1. maslow’s pyramid (1943) fig. 2. ungku aziz’s pyramid (1983) the main criticism of maslow's model is based on the assumption that the individual pass from one level to another only once he has satisfied the needs of lower level, yet every human being does not necessarily have this mode of prioritization of needs, not in his personal or professional life. observations in organization show inversion or coexistence of levels. also, maslow's model cannot explain the lack of motivation. thus, according to this model, it‘s not possible to do a good job with a small salary. conversely, an excellent salary does not guarantee a strong motivation. in our humble opinion, the same main criticism is opposable to the aziz’s model. this means that the organization pass from one stage to another only once satisfied with the requirements of a lower stage. each of the stages of technological evolution considered as a prerequisite to the successful realization of the preceding stage. thus, according to this model, there is no way of jumping straight into the higher stages and bypassing the earlier preparatory stages (idris, 2000). using patent information integrated in information systems field, we demonstrate the invalidity of these models. in “the creative evolution”, the french philosopher henri bergson (1907) defines the concept of “homo faber” as (freely translated): “… intelligence, in its original sense, is the faculty of creating artificial objects, especially tools to make tools, and to vary indefinitely its makings.” (3) this approach applies to patents and was adopted by the world intellectual property office (wipo) which accurately describes the ultimate stage of technological development as defined by ungku aziz (idris, 2000; idris, 2003): “the sixth stage consists in learning to make machines that produce machines, as well as learning to innovate and being ready to approach the frontiers of modern technology in such fields as computers, robotics and biotechnology, using energy and raw materials without causing irreparable damage to the environment, and becoming an exporter of high technology products. the intellectual property system is already integrated into r&d activities.” (4) 3 henri bergson in “l’évolution créatrice”, p. 100, originally published in 1907. les presses universitaires de france, 1959, available online: http://classiques.uqac.ca/classiques/bergson_henri/e volution_creatrice/evolution_creatrice.html 4 ungku aziz, “must patterns of change in developing countries follow the west? what other possible patterns?” in technological innovation: universities of the commonwealth, birmingham (august 1983). cited by kamil idris (wipo) in “a brochure on intellectual property rights for self-actualisation self-esteem love, affection & belongingness safety physiological or survival construct machines that produce others. innovate skills to support the entire production for the local needs adapt imported techniques & organization to local context repair & replace imported technology learn technical maintenance & repair handle & use simple imported machines http://classiques.uqac.ca/classiques/bergson_henri/evolution_creatrice/evolution_creatrice.html http://classiques.uqac.ca/classiques/bergson_henri/evolution_creatrice/evolution_creatrice.html o p i n i o n s e c t i o n 55 “tool to make tools transform its environment, shapes it with his feeling and his hands”. this brings us closer to the concept of “stigmergy” (5) , addressed by charles victor boutet for the information sciences in light of the web 2.0 (boutet, 2011), and defined as a form of selforganization that produces complex, seemingly intelligent structures, without need for any planning, control, or even direct communication between the agents (wikipedia). to use the patent as an object of research, we need to mobilize these concepts to overcome the available tools for the patent analysis and create other tools, to analyze machines that create tools and increase the degree of complexity. the european patent office proposes its base (over 70 million patents) and an application programming interface (api), a tool which has already created many tools but offer to researchers in information systems the ability to create tools to create tools that help understand and transform the environment. the only limit to analysis with the api is our own imagination. it is therefore not necessary to follow all the stages recommended by ungku aziz to reach the ultimate stage. for us, a research activity is situated around the concept of “homo faber”, so as not to confine research activities to the role of passive spectator, without interaction with the society that houses them. it also responds to the need to conduct research into multi-skilled teams. in the field related to patents, it quickly becomes indispensable. we will show along this paper, the contribution of science information, but also knowledge on law of industrial property, analyzed technical field (chemistry, materials, pharmaceuticals, medicine), information technology, corporate social responsibility, sustainable development, innovation, creativity, without being exhaustive, are quickly needed, forcing them to work in multi universities and r&d institutions in african countries”, june 2000, isbn 92-805-1097-7 5 the term "stigmergy" was introduced by french biologist pierre-paul grassé in 1959 to refer to termite behavior. he defined it as stimulation of workers by the performance they have achieved, and captures the notion that an agent’s actions leave signs in the environment, signs that it and other agent’s sense and that determine and incite their subsequent actions (wikipedia). skilled teams, which often justifies multi-author approaches in the literature. 6.0 patent information as open information system the international patent classification is a unique system to show technology. each patent must be described in it. as a corollary everything "patentable" is described by it. it was set-in place by the strasbourg agreement concerning the international patent classification of march 24, 1971, amended september 28, 1979. ipc was developed in two “official languages: french and english”, divides technology into eight sections with approximately 70,000 subdivisions described by symbols. this classification is useful to search on patent documents in the context of research on the “state of art”. a patent database, free and freely accessible online, allows to do research in this classification. thesaurus allows browsing in the classification with 22798 english keywords and 25676 french keywords. ipc is the core of an interface between different languages for describing “patentable subject matter”. it is the means to see what is patented around a subject matter in another language without knowing the language. it can also enable quick dialogue between experts communicating in different languages, in the same field. generalizing a little more, it is technically possible to describe an entire problematic. this is the case of the green inventory according to ipc, developed by the experts committee of ipc union based on climate change mitigation technologies (ccmts) in order to facilitate the search for information on patents related to environment technology. this green inventory was built with a list of terms established by the united nations framework convention on climate change (unfccc). this application is proof of using ipc as a pivot system between societal and environmental issues and their declination to industrial realities, providing tracks of application into the market realities of societal evolution as “sustainable development” or “corporate social responsibility”. this is also a crossing point between “hard technologies” and “soft technologies”. o p i n i o n s e c t i o n 56 fig. 3. patenting activity is taking off in several green-tech sectors. (source: wipo, 2014). this example is adaptable to many other sectors. it could be an investigation framework of reconciliation between public and private sectors, in order to search funding under development based on the “triple helix” model (etzkowitz, 2008) where synergies “government research private sector” are sought. during his study of the bibliography of a theses sample (586 from brazil and 580 from u.s.) in the field related to technology research, juliana ravaschio found only 15% of theses that have patent citations (ravaschio, 2010). this result shows the lack on “patent” knowledge in the academic world. lack in part, due to the use of different vocabularies and concepts, cleavage of communication. it was on this ground that the research “automatic mapping of scientific and technical bibliographies databanks using the international patent classification (ipc): contribution to the rapprochement between sciences and technology” was developed by pascal faucompré. this research considers the ipc as a pivot system with keywords for indexing scientific databases, has set glances descriptions of academic research with an industrial description of these research (faucompré, 1997). a patent granted is legally valid at a given period. beyond this period, the patent becomes invalid. wanise barroso (2003), a patent examiner in the patent office in brazil upon completion of her research, worked on the subject. she proposed the creation of a sub-base of this patent office, containing only “public domain patents” for distribution to smes in order to facilitate technology transfer. this was possible by querying the database on the field which informed the legal status of the patent. she showed that more than 30% of the brazilian patent base became in public domain in 5-6 years and around 40% of the base was in public domain which may be used freely as technological support, since applications patent must be written to be able to reproduce what is claimed. if we assume on equal proportions in other available databases, would bring to 28 million, the number of available patents in full text and freely “reusable” in the world as “technical and technological encyclopedia”. this number does not include the geography to the territory for which it was filed and paid patent rights. although having no precise estimate, the number becomes really significant. this fact can be used systematically to try for example to develop natural products or to add value to them. there is a source of development assistance, regardless of the country. at least it represents a source of inspiration and creativity almost without limit. indeed, the free use of a patent is legal from the moment it falls into the public domain or is invalidated by the courts. technology disclosed in a patent document may be in the public domain if: o p i n i o n s e c t i o n 57 the patent application has not been filed in a given country; the patent has not been granted; the patent term has expired, or the patent has not been renewed; the disclosed information is not covered by the claims. in any case, the information is always in the public domain. according to karnik (2008), the strategies for the invalidation of a patent which are followed by attorneys in the judicial courts are: invention claimed in the patent is not novel; subject of the claim of the patent is not an invention; patent was wrongfully obtained by a person other than the person entitled; insufficient disclosure of the invention; obviousness; the claims included in the patent are not fully substantiated by the description provided; failure to disclose information relating to foreign applications; principle of “first to file – first to invent”; patent holder did not exercise diligence in pursuing the patent application process (patent grace period). 7.0 patent information as knowledge database discovery to respond to this problematic: “how to find substances that interact with all the symptoms of a disease without anyone had made the relationship between these substances and disease?” jean dominique pierret (pierret, 2006; pierret & al., 2010) conducted research on “methodology and structure of a knowledge discovery tool based on the biomedical literature”. this research led to filing four new patents based on new medical indications of molecules previously patented in order to reach the market. this proves that it is even possible to “invent” and “patent” by a recombination of existing knowledge on technical documentary barely developed. this kind of methodology could be generalized to materials, processes, etc. the experience of jean dominique pierret is to our knowledge, the first creation of “patentable subject matter” starting from documentary research. to go further in this field it will be necessary again to use the concept of “homo faber” to improve document interfaces to systematize this kind of queries. the methodology called “diseases physiopathology molecules (dpm)” is part of methods grouped under the term “knowledge database discovery (kdd)”. this is indeed, weak signals which pierret (2006) attempted to show through the kdd process. the results are spectacular as they allowed jean-dominique pierret and his colleagues of galderma r&d, to file five (05) new patents based only on information: titles publication numbers publication date use of a dipyridyl compound for treating rosacea us20120322829-a1, ca2782048-a1, ep2506851-a1, wo2011064508-a1 20/12/2012 administration of tropisetron for treating inflammatory skin diseases/disorders us2009048289-a1, ca2644458-a1, ep1993542-a1, wo2007099069-a1 19/02/2009 use of azasetron for the treatment of rosacea, and pharmaceutical compositions wo2007138234-a1 06/12/2007 use of zatosetron for the treatment of rosacea, and pharmaceutical compositions wo2007138233-a3, wo2007138233-a2 06/12/2007 use of granisetron for the treatment of sub-types of rosacea, and pharmaceutical compositions wo2007138232-a3, wo2007138232-a 06/12/2007 table 1. patents list filed by galderma r&d based on pierret’s works o p i n i o n s e c t i o n 58 8.0 case studies: proof by doing “i hear and i forget. i see and i remember. i do and i understand.” confucius, chinese philosopher (551 bc 479 bc) 8.1 the tenofovir case study (health / medicine fields) the federal constitution of brazil establishes, in article 196, that health is a right of all and that it is the duty of the state to do this right to be guaranteed. this constitutional right is regulated by a 1990 law that, among other regulates the unified health system (uhs) to ensure full therapeutic assistance, including pharmaceutical assistance (miguel & al., 2010). the cost of this legal provisions exceed r $ 1.4 billion (580 million €), with a number of pharmaceutical products distributed evolving from 15 in 1993 to 243 in 2007 (carias & al., 2011). brazilian scientists were early interested in this (2003), using information systems to find ways in order to contain costs (barroso & al., 2004) by a joint team of brazilian and french researchers. they were interested in the tenofovir case and they filed an opposition on patent application in conjunction with a research team in india for the antiretroviral used in the treatment of aids (barroso & al., 2010). the patent was invalidated and the implications of the research disclosed in the press (6) . it was important to manufacture this drug in a generic form, at significantly lower costs (50%), so more patients treated by the free health system and more released resources (r$ 110 million saving in 4 6 various press: “blanver entrega ao governo os primeiros lotes de genérico contra aids” in “tribuna da bahia online”, available online: http://www.tribunadabahia.com.br/news.php?id atual=81752 , may 2011. “sida: le prix des médicaments baisse dans les pays pauvres” in « le figaro.fr », available online: http://sante.lefigaro.fr/actualite/2011/07/12/110 13-sida-prix-medicaments-baisse-dans-payspauvres , july 2011. “funed produzirá genérico contra aids” in “o reporter”, available online: http://www.oreporter.com/detalhes.php?id=402 02 , february 2011. years) could be allocated for other types of free health access. “for the first time, aids patients in developing countries will have access to the same drugs as those living in rich countries”, says philippe douste-blazy, unitaid director. this research, conducted without any funding since the financing was refused in france by the national agency for research on aids and viral hepatitis (believing that the research does not lead), was awarded an innovation prize in brazil (quoniam, 2010). 8.2 drill-bit design case study (mechanical engineering / oil & gas fields) this work conducted on behalf of an algerian stateowned firm specialized in drilling tools manufacturing, led to a publication that shows the innovation opportunities offered by the use of reverse engineering combined with patent information in the oil & gas industry. a case study of drill bits design and optimization for oilfield drilling was proposed with outlining a parallel cognitive process associated to the technical process of reverse engineering (baaziz & al., 2014). the results of this work is a significant performance achieved during drilling operation of 12 ¼ section of brnp#1, an exploration oil well located in berkine east basin. on may 2014, the pdc tool 12 ¼ diameter, designed by the engineering team according to the process described above, has achieved this performance by drilling 769 meters in less than 34 hours and the rate of penetration (rop) has approached the threshold of 23 meters per hour and peaked at 22,92 m/h without additions (connection). this is the best performance to date for such tools in berkine basin area. the tool wear parameters were acceptable given the performance achieved which allowed to the client to reduce non-productive time (npt) and costs of drilling operations. this study had multiple benefits for the firm and its client and, following the performance achieved: the used pdc tool is in its third remodelling (repair), which represents a saving of 40% of the price of a new drill bit; cost savings for the client are of the order of usd 137,000.00 for 12¼ phase; time recovery is over three days of drilling. this study identified 7259 patents on the matter “drill bit” for the period from 1907 to 2013 http://www.quotationspage.com/quotes/confucius/ http://www.tribunadabahia.com.br/news.php?idatual=81752 http://www.tribunadabahia.com.br/news.php?idatual=81752 http://sante.lefigaro.fr/actualite/2011/07/12/11013-sida-prix-medicaments-baisse-dans-pays-pauvres http://sante.lefigaro.fr/actualite/2011/07/12/11013-sida-prix-medicaments-baisse-dans-pays-pauvres http://sante.lefigaro.fr/actualite/2011/07/12/11013-sida-prix-medicaments-baisse-dans-pays-pauvres http://www.oreporter.com/detalhes.php?id=40202 http://www.oreporter.com/detalhes.php?id=40202 o p i n i o n s e c t i o n 59 including 2442 patents fallen into the public domain due to expiration of the protection period. baaziz & al. (2014) have rightly noted that it is interesting to verify the legal status of the patent legacy of firms currently being acquired or merged. this information can be verified by looking inpadoc legal status of patents. indeed, the successive mergers and acquisitions incurred by the firms may generate dysfunctions in the intangible assets management. patents can fall into the public domain due to these legal flaws. 9.0 conclusion this paper gives two examples from the field of information systems. it is for readers who would be interested to evoke new insights in patent matter and reciprocally, who in the field of industrial property would like to gain a deeper understanding of what could bring him the prism of information systems. it is also a plea for those who believe that there are alternative voices for technology transfer and innovation in both developed and developing countries through the use of patent information. we’ve tried to demonstrate the usability of patent matter as a field of research in information systems, by restricting around research experience and research directions that we may have in this field. it is obvious that given the vastness of the subject and its interconnections, it is not treated exhaustively here. the integration of patent studies in information systems field had the potential to support a development strategy that burns stages and borrows shortcuts in order to avoid heavy investments like “hard r&d” processes. this contributes to reduce the gap between developed countries and developing countries. looking to the future, it seems that the possibilities of burning stages are even more promising through the opportunities offered by web 2.0 technologies, which facilitate the flow of information. many constraints of time and distance are abolished due to the variety of “open” formats used to disseminate knowledge and create links between researchers and professionals. references baaziz, abdelkader; quoniam, luc ; khoudi, abdenacer (2014), « l’information brevet au service de l’industrie pétrolière : cas de conception et optimisation des trépans par reverse engineering », accepted paper @ journal of information systems and technology management (jistem), sao-paulo (br), issn 18071775, 2014 barroso, wanise b. g. 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http://www.wipo.int/edocs/mdocs/pct/en/wipo_pct_nbo_09/wipo_pct_nbo_09_www_121096.ppt http://www.wipo.int/edocs/mdocs/pct/en/wipo_pct_nbo_09/wipo_pct_nbo_09_www_121096.ppt http://www.wipo.int/edocs/mdocs/pct/en/wipo_pct_nbo_09/wipo_pct_nbo_09_www_121096.ppt http://portal.saude.gov.br/portal/arquivos/pdf/da_excepcionalidade_as_linhas_de_cuidado_o_ceaf.pdf http://portal.saude.gov.br/portal/arquivos/pdf/da_excepcionalidade_as_linhas_de_cuidado_o_ceaf.pdf http://portal.saude.gov.br/portal/arquivos/pdf/da_excepcionalidade_as_linhas_de_cuidado_o_ceaf.pdf http://www.oecd.org/science/sci-tech/24508541.pdf http://www.oecd.org/science/sci-tech/24508541.pdf http://www.wipo.int/pressroom/en/stories/green_tech.html http://www.wipo.int/pressroom/en/stories/green_tech.html https://webaccess.wipo.int/green/ knowledge and social networks: new dimensions of economic interaction between firms michael steiner * and michael ploder ** * university of graz, department of economics, universitätsstr. 15 f/4, 8010 graz, austria ** joanneum research, institute of technology and regional policy, elisabethstr. 20, 8010 graz, austria michael.steiner@uni-graz.at michael.ploder@joanneum.at received 20 august 2011; received in revised form 20 november 2011; accepted 29 december 2011 abstract: the paper explores the form and content of economic interaction of firms based on various concepts of agglomeration and social networks. it uses a case study of the machinery sector in the region of styria as empirical background. starting with types of clustering – the model of pure agglomeration, the industrial-complex model and the social-network model the paper argues that certain geographical agglomerations allow different types of networks and different patterns of behaviour. thus different forms of learning, knowledge sharing and knowledge creation. some “stylized facts” in support of this perspective are derived from an analysis of a regional network. this network comprises individualistic open systems consisting of several areas which overlap. physical linkages between these networks are weak, but intersections based on cooperative r&d and r&d infrastructure, qualification and informal exchanges are evident. from a regional perspective it can be seen to dominate. despite evident sectoral concentrations direct links to the prevailing science base appear more significant as binding factors than long term supplier networks. these relationships are interpreted in terms of their need for proximity, their durability and above all their direction of knowledge dependency. keywords: agglomeration, knowledge transfer, social networks, co-evolutionary development available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 49-60 mailto:michael.steiner@uni-graz.at mailto:michael.ploder@joanneum.at https://ojs.hh.se/ 50 1. introduction while we are well aware that it is most likely impossible to provide one single theory of clusters and their networks there is nevertheless a certain consensus that several elements of specific theories may help us understand their forms and functions. they offer a certain unity of approach in identifying the important elements which are needed for explaining the changing character of the innovation process. recent debate has begun to focus more on how far, and in which ways, clusters foster knowledge creation and organizational learning. it has also emphasized the organic-evolutionary dimension of cluster-based industrial agglomerations. knowledge has been recognized as a major source of competitive advantage in an increasingly integrated world economy (dosi and malerba 1996, grant 1996, foss 1999, nonaka et al. 2000). the most successful regions are perceived to be those whose firms display innovative capacity, i. e. those whose firms are able to adapt to a rapidly changing marketplace and stay one step ahead of competitors. the emphasis of cluster interpretation has changed from an analysis of forces of agglomeration to the various forms and contents of organizational learning and knowledge exchange. the original concentration on clusters as mere geographic concentrations of sectors and firms has been transformed into a search for institutions for knowledge management and organizational learning emphasizing the organic-evolutionary dimension. growth of the knowledge base depends on intended and unintended individual processing of experiences. i.e. ‘learning’, while the interpretation, transfer and use of experiences is influenced by interaction between individuals and between organizations (cohen and levinthal 1989, andersen 1995, hartmann 2006). these insights have shifted the emphasis from material links to immaterial knowledge flows within clusters. they have also pointed to the need for connectivity between different agents concerning knowledge creation and diffusion. this has led to further questions concerning the degree to which clusters are to be regarded as non-market devices, by which firms may seek to coordinate their activities with other firms and knowledge-generating institutions. ongoing learning processes between firms and within clusters stress the importance of institutional arrangements for the generation of knowledge and learning networks which are not available in markets (maskell and malmberg 1999). since the necessary knowledge may lie outside a firm’s traditional core competence, interfirm alliances and networks are widely recognized as an important organization form of innovative activity (gay and dousset 2005). in this paper, we emphasize the ideas of agglomeration and knowledge exchange.we discuss to what extent this approach has specific regional or spatial dimensions while focussing on the necessity and forms of proximity, especially with respect to knowledge exchange. by means of network analysis we develop some “stylized facts” for the various dimensions of interaction within a given network of medium-tech firms in styria, one of the nine provinces (regions) of austria. the final section is used to interpret the findings. 2. geographical agglomeration and local networks since marshall (1890), weber (1929) and hoover (1948), many authors have dealt with the phenomenon of geographical agglomeration. in the discussions of ‘clusters’, ‘networks’ and agglomerations, and particularly in those relating to ‘industrial districts’ and agglomerations, there are certain common traits and frequently terms are only weakly differentiated. the basic idea of geographical agglomeration was presented by marshall (1890) and the three sources of economies of agglomeration he mention is input sharing, labor market pooling, and knowledge spillovers, correspond with the core-elements of the current cluster-concept. in this form it has been discussed since the early nineties in industrial countries. a more recent attempt to distinguish various cluster forms has been made by belussi (2006) by contrasting geographical agglomeration and active clustering (as policy or firm-driven strategy). while implicitly focusing on geographical agglomeration and economies of agglomeration we stress a dimension of externalities beyond the tangible dimension of direct co-operation. on extending the basic idea of economies of agglomeration, we see that externalities are widely enforced by informal and non-economic dimensions. amin and thrift (1995) use the term “institutional thickness” to address the existence of a supporting environment beyond firms (institutionalized cooperations and networks). geographic agglomeration (and concentrated versus dispersed location patterns) set a framework for economic interaction and material and immaterial linkages between economic actors. the existence of a cluster doesn’t necessarily imply the coexistence of all defining characteristics of a geographical agglomeration. on the other hand, a geographical agglomeration may also exist in the absence of a cluster or network. while the existence of a pure geographical agglomeration (e.g. a city) favours the development of clusters; growing networks and clusters can also cause the emergence of a geographical 51 agglomeration. this was the case perhaps in silicon valley in california. myrdal’s (1957) idea of cumulative causation corresponds with a dynamic view of a co-evolutionary development of economies of agglomeration and growing clusters (without yet formalizing interdependency as was done by kaldor (1972) and dixon and thirlwall (1975). in other words, additional local linkages and relations strengthen tendencies of concentration and agglomeration. networks and clusters are possible means of overcoming constraints of exchange within and between geographical agglomerations and also facilitate the definition and defence of rules of exclusion, as already pointed out by marshall (1890). yet, what is still an open question is the micro-perspective. economies of agglomeration and dimensions of interaction could be selective in respect to the actors since they regulate the extent to which the latter are able to participate or gain from externalities: e.g. with respect to exchange of physical goods versus r&d, or labour market pools for blue collar workers or engineers. in addition to direct physical exchange, input sharing and common labour market pools, systematic knowledge exchange and knowledge spillovers have gained considerably in importance as an argument for geographical concentrations of activities. a frequently used argument is that the collaborative nature of innovation processes has reinforced tendencies toward geographical clustering because of the advantages of locating in close proximity to other firms in specialized and related industries (storper, 1995 and 1997). transaction costs such as transportation costs and spatial communication costs in particular, reinforce the relationship between individual environment and the development of embedded social networks (granovetter 1994). firms establish a variety of types of interactions and relationships each of them having different impacts on the knowledge generation and diffusion process. mariotti and delbridge (2001) speak of the necessity for firms – in the face of knowledge ambiguity, knowledge related barriers, tacitness and complexity of knowledge to engage in the management of a portfolio of ties. organizations are therefore likely to engage in inter-organizational relations that show a variety of types of ties. they can have quite different dimensions and can be defined according to the character of social relations between actors, the regulation of the relationship, frequency of use, length and duration of the relationship, and also in terms of the nature of the information exchange itself (mariotti and delbridge 2001). it is also important to distinguish between both content (i.e. the type of relation) and the form (i.e. the social structure of relations), as has been outlined by powell and smith-doerr (1994). one additional question that needs to be addressed in this context concerns the legitimacy of a pure micro-level, individual firm approach in analysing the incentives for clustering. individuals and firms alone are, from an economic point of view, not capable of delivering sufficient amounts and varieties of knowledge. we are confronted here with one of “the most troublesome issues in the social sciences …” (felin and foss 2006, 1). the question of the adequate level and unit of analysis. a question of whether the individual or social collectives (firms, networks, regions …) have explanatory primacy is of course part of an old debate in economics, sociology and the philosophy of science and is often now dealt with under the heading of “methodological individualism” versus “methodological collectivism” (hayek 1945, popper 1957, coleman 1964, douglas 1986). further potential for conceptual differentiation relates to the forms, channels and mechanisms of knowledge exchange. as this exchange occurs through interaction, the structure of the interaction therefore influences the extent of knowledge diffusion (gay and dousset 2005). this coincides within the view that “spatialities and temporalities are not neutral frames, but constitutive elements of socioeconomic transformation” (colletis-wahl et al. 2008). the cross-sectoral dimension of knowledge spillovers is also a source of contention in the literature. following marshall (1890) and arrow (1962) knowledge is predominantly industryspecific. knowledge spillovers may therefore arise between firms within the same industry. jacobs (1969), on the other hand, mentioned the significant fact that knowledge may spill over between complementary rather than similar industries. the significance of geographical agglomeration and networking is strongly determined by the particular sector (industry) and the leading technology. there seems to be a clear agreement in the recent literature about cross-sectional differences in agglomeration forces: as has been emphasized by botazzi et al. (2001 and 2002) and also gordon and mccann (2000), huge intersectoral differences in spatial agglomeration outcomes can be identified. following gordon and mccann (2000) agglomeration economies appear particularly relevant in “scale-intensive sectors” hinting at the forms of hierarchical agglomeration discussed above and in “supplier-dominated sectors”. conversely, they appear the least relevant in “science-based” sectors. the importance of agglomeration depends on the prevailing sectoral and technological pattern. the following argumentation takes up two approaches to differentiating typologies and focuses on the different dimensions of agglomeration and 52 clustering viewed as helpful guidelines in the discussion of the network observed in styria and in answering the key-questions of the empirical analysis. an attempt is also made to combine and differentiate the “agglomeration” approach with the additional insights mentioned above. gordon and mccann (2000, 15) define and discuss three theoretical approaches for industrial clustering which reflect different (more or less idealized) perspectives on agglomeration: the model of pure agglomeration, the industrialcomplex model and the social-network model.  the phenomenon of economies of agglomeration as an intrinsic motive for clustering, in the sense of spatial concentration of economic activity, is attributed more or less exclusively to the traditional idea of marshallian industrial districts. following in the footsteps of thünen in the field of locational economics, and smith’s idea of division of labour, the model of pure agglomeration – which in the tradition of marshall (1890) is based on a local pool of specialized labour, on the increased local provision of nontraded input specific to an industry, and on technological spill-overs may contribute to an “evolving localized environment of learning” (gordon and mccann 2000, 517). the marshallian approach was quickly developed and extended by hoover (1948) by distinguishing between localization economies and urbanization economies. following marshalls (1890) positive externalities of agglomerations are defined by regional non-traded inputs, knowledge and information spill-overs, and a local pool of skilled labour. from the perspective of knowledge flows and learning processes favoured by agglomeration, such externalities occur more or less unheard of and unseen. knowledge exchange and learning occurs unconsciously via transfer of human or material resources. the most important point seems to be that the approach is not bound to the idea of direct supplyrelationships among the bulk of actors involved. following the traditional idea of marshallian industrial districts, interaction is primarily led by the needs of industrial production.  a second group of approaches pooled by gordon and mccann (2000, 517) under the term of industrial complex models systematically tries to justify spatial concentration by the quantification and minimization of spatial transaction costs (reflecting of the origins of the approach, primarily transportation costs). the industrial complex model is associated with cumulative learning from sources inside the industry, non-transferable experience, the role of leading firms and power asymmetries (iammarino and mccann 2005). although the implicit concealment of (unplanned) economies of agglomeration didn’t mean that they were not relevant. attention shifted nevertheless to innovation as an interactive process involving the sharing and the exchange of different forms of knowledge between actors (lawson and lorenz 1999) – knowledge and competence as developed interactively and within subgroups of a (regional) economy (freeman 1979, lundvall 2002). the critique here has been concerned with the question of whether this interaction is an outcome of (neoclassical) rational behaviour or the result of a more ‘associative-relational’ mode of organization, or what has been termed ‘associative governance’, leading to the creation of clubs, forums, consortia and other institutional schemes of partnership (cooke 1998; cooke and morgan 1998). there are elements of knowledge sharing in the sense that adopting the perspective of specific clusters represents a quasi-monopoly for the internalization of the benefits of innovation created within (more or less) “closed club”.  the social-network model as the third type – relying on trust and social embeddedness as the dominant link between the cluster firms (and therefore not on deliberate economic decisions based on the minimization of different transaction costs) – also favours the exchange of knowledge. however, such exchange is here based on strong interpersonal relationships that transcend firm boundaries and allow for diverse forms of knowledge sharing. following iammarino and mccann (2005) traditional and recent approaches of social networks may be differentiated. the traditional approach corresponds to the ‘marshall-stimulated’ industrial districts where knowledge is mainly codified and oriented to process innovation transferred by personal contacts and social and political lobbying. while in the traditional approach the network seems to be based on geographical proximity rooted in historical experience, the new approach of social networks seems to be 53 based on relational and organizational proximity. the links between actors are then all the stronger the more they are based on elements of social embeddedness: norms, sets of common assumptions, habits formed by culture, history, and of course (but not necessarily) spatial proximity. they form social capital that favours the explicit and implicit sharing of knowledge. new physical technologies are not just there, innovations do not just happen, but need social technologies as pathways to coordinate human action. as iammarino and mccann (2005) mention, much of the discussion in the literature is based on ideal types, whereas in reality all spatial clusters and industrial agglomerations will contain more or fewer of the above characteristics. furthermore, clusters may mutate from one typology to another. from another perspective this is also outlined by rychen and zimmermann (2008, 768): the concept of cluster “usually considered as a spatial concentration of industrial and technological activities” has to be enriched. “it is more important to understand how and why firms build links and how the structure of links will give sense to the colocation of actors.” it is therefore important to incorporate the dimension of collaboration, the basic conception of firms is a “network-driven economic strategy built on collaboration among the participants” (reid et al. 2008, 2). the following section is dedicated to interpreting the case network investigated in the light of the approaches discussed above. the suppositions that context, typology and significance of geographical agglomerations and embedded networks change, seems to be reflected in the case of the machinery sector in the region of styria. 3. the empirical analysis – a qualitative context oriented approach based on social network analysis the empirical analysis starts with an analysis of relevant regional data and expert interviews and then continues with a case study analysis of the relations of engineering firms in styria. 3.1 interaction in the observed network network analysis is a well established method in the social sciences. recently, the method has also been applied to the analysis of production clusters (krätke 2002), innovative activity and knowledge exchange (giuliani 2005), and alliance networks (gay and dousset 2005) or r&d networks. social network analysis is a helpful tool for discussing the structure of networks since it allows the mapping and measuring of the relationships (communication and transaction) between different actors, i.e., the existence, context and portfolio of relations between actors in a regional network. it is a method for revealing relations between different actors. such relations are phenomena that cannot be reduced to the properties of individual actors or firms themselves and thus need to be interpreted as properties of systems than of individual actors. 3.2 the empirical database the present network analysis is based on an empirical sample of firms identified by a snowballing method of sampling in cluster and network investigation. this corresponds with the relational approach and is developed by means of the references to actors as revealed by previous respondents (frank 1979, scott 2000). our starting point was a large system supplier in the automobile sector located in the region of styria/austria. the snowball method produced firms belonging to different sub-sectors of the manufacturing sector and related supply-chain and innovation-strategies. starting with the initial firm, a sample was developed. following a citation path of regional suppliers (production or commercialization of goods and services) and of regional partners in the field of research and development (cooperative r&d and related activities and exchange). in this way the database for the subsequent network analysis was extended to 23 firms, of which 18 are producers (with different positions in the supply-chain such as system-suppliers, component suppliers and tollmanufacturers). the remaining 5 are technical business services. additionally nine r&d institutions (universities, co-operative r&d institutions) are included. the information and data collected are based on extensive qualitative interviews and supported by a quantitative survey concerning specific data. 3.3 indicators of interaction qualitative indicators revealing individual strategies of innovation are helpful discussing individual strategies and their aggregation at the level of networks. they are selectively used here to find – via network analysis the structural features of the network of 32 actors. the selected indicators of the relations cultivated by the organizations cover three dimensions of interaction: direct delivery relations, r&d, and technological innovation in a competitive and a pre-competitive context. (deliv): the firms were questioned concerning direct delivery relations (goods or services) to clients, suppliers or partners (in the case of synergetic product bundles)..the direct delivery 54 of goods and services is not reduced to the material dimension since it also covers questions of innovation in information management or capacityextending investments. (pre-comp): the dimension of interaction in the context of pre-competitive r&d was also analysed. pre-competitive research and development aim to extend the product spectrum, as well as introduce new processes and alternative materials. pre-competitive research includes fundamental research, which is an activity designed to broaden scientific and technical knowledge not necessarily linked to industrial or commercial objectives, as well as industrial research, i.e. research aimed at developing or improving new or existing products, processes or services in so far as it is also not directly connected with a client tender, offer or an existing business relation. (comp): competitive research and development and innovation processes are short and medium term oriented and mostly associated with direct expectations of return or with a direct tender or offer etc. in contrast to pre-competitive r&d which is long-term oriented. 3.4 structure of the network and network density following the socio-centric approach, the density of a network is given by the ratio of relations realized to the total number of potentially maximum possible relations. we dichotomized the relations in that we only differentiated between existence and non-existence of a relation between two actors [0; 1], and therefore disregarded the intensity of the relations (in our case the frequency of interaction) surveyed. this enabled us to avoid the problems typically associated with the measurement of the intensity of evaluated graphs (scott 2000). network density yields information on the general structure of the network as a whole. one of the core features of an actor identified in network analysis is its centrality. using the concept of centrality (in different forms) we gain insights into the specific features of the interaction of the actors in the network and their specific position and/or embeddedness in the network. while density focuses on the properties and general structure of the network as a whole, centrality tries to capture the position of individual actors or groups of actors within the network. this is again based on the relations revealed by the actors, where the relations are valued ordinally in terms of frequency of interaction. the potential centrality of an actor is determined by a broad range of industry or sectorspecific factors (cohen et al. 2000), by capacity and individual motivation (bayona et al. 2001, theter 2002). a high centrality is positively associated with multiple possibilities for receiving and generating knowledge. keeping in mind that interregional and international relations exist and may be of major priority, e.g. direct delivery relations the analysis below focuses on regional interaction. table 1 presents the density measure for the three dimensions of relations between the actors. relational dimensions density (deliv) direct delivery relations 0.068 (precomp) interaction in the context of precompetitive r&d 0.143 (comp) interaction in the context of competitive r&d and 0.074 table 1: density of the observed dimensions of networking direct delivery relations have the weakest density. although the datasets have been dichotomized and therefore relations with a very low frequency of interaction have been “up-graded” the density of the network of direct delivery relations is lower than the density of knowledge intensive innovationrelated interaction. regional input-output relations were reduced in order to focus attention more on international markets. while competitive r&d and innovation processes, especially in the case of domestic system suppliers, are partially similar in density to direct delivery relations, the regional density of the network in pre-competitive r&d is much higher. r&d institutions are of negligible significance in respect of direct delivery relations, the network is based to a considerable degree on relations with cooperative r&d institutions. the relational data can be used to provide a graphical representation of the transaction network for the organizations observed. while network diagrams offer a traditional and basic methodology for formalizing network analysis, and are a very helpful mean of interpretation and discussion, clarity suffers greatly as the number of actors observed increases. a quite useful method of graphical representation which is implemented in most software packages follows the approach of the kamada and kawai (1989) spring embedding algorithm. this is employed below. 55 gives an overview of all relations recorded and combines the three dimensions discussed above. it also takes into account the valuation of the relations in terms of frequency of interaction. the shape of actors (nodes) corresponds with the different types of organizations. the size of the nodes corresponds with the size of the organisation, and the length of lines corresponds with the distance between the actors observed. figure 1: network of firms and knowledge generating institutions figure 2: legend a further interesting dimension of network analysis is ‘coreness’, which follows basically the idea of core and periphery. here we use the concept of the k-core (seidman 1983, scott 2000). a k-core is a sub-graph in which each actor is adjacent to at least k other actors in the sub-graph. that is, for all nodes in the sub-graph minimum the number of the actors’ direct relations within the sub-graph is k (in our case eight). k-core analysis complements the measurement of density, since the latter is not able to reflect structural features of the network. the kcore is an area of relatively high cohesion. as can be seen at first glance, we can differentiate between those actors in the core of the network (coloured black) and those actors more or less on the periphery of the network (coloured white). the diagram reveals the high density of the realized relations calculated in the previous paragraphs. in the k-core of the diagram we find a group of institutions that seem to interact multilaterally. in the “core” of the network we find r&d institutions, large system suppliers and toll manufacturers (surface-treatment, heating etc.) which maintain multiple but weak relations with a broad range of regional clients. 3.5 spotting a leading firm in the network here we focus on a specific firm, ss 20 in the total network. this is a highly specialized manufacturer who measures equipment for science and industry. their success is based on the direct application and transfer of scientific knowledge gained in the measurement of physical or chemical phenomena. the firm is highly vertically integrated and is embedded in smaller network following niche strategies. the partners of the firm in direct delivery (component and toll-manufacturers) and its partners in competitive and pre-competitive research and development (key clients, highly specialized business services, universities) are not identical. on the delivery side, the observed firm interacts with component suppliers in the field of die casting, spray casting, plastics processing, electronics, sheet metal forming, and manufacturing of high performance glasses. originally, the firm was a pure converter, producer and specialist in marketing. this division of labour has changed since the 1980s. a well established cooperative base allows access to university partners and to an independent research laboratory which provides exclusive science driven r&d. the firm enjoys a relatively high in-degree systems supplier component supplier toll manufacturer technical business services r&dinstitutions systems supplier component supplier toll manufacturer technical business services r&dinstitutions2 1 56 centrality in respect to direct deliveries. the outdegree centrality of the firm in the region, with respect to deliveries, is low owing to the high export intensity. a high share of the turnover is reinvested in r&d activities, 10% for intramural r&d and an additional 10% of the turnover for external r&d. the degree centralities in respect to r&d (precompetitive and competitive) are higher than for the average of the leading firms in the network. the core competences of the firm are based on combining and applying findings from basic research, in precision engineering and electronics. while radical innovations and market novelties mostly emanated from r&d or client-partners, incremental improvements are promoted by internal r&d. r&d and production and marketing of new products are concentrated within the region. as the firm is not located in the core of vehicle manufacturing but in the interface with other sectors such as manufacturing of plastic products or measurement techniques it has a relatively high value for betweenness centrality. the findings for this specific firm serve to strengthen the thesis that firms acting in market niches demanding highly specialized cooperation tend to work for long-term cooperation. 3.6 the historical background and changing role of geographic agglomeration in the medium-technology sector in styria the majority of the observed firms have been in the region for more than 10 years. the current situation and recent developments cannot therefore be adequately analysed without considering the historical background and structural change of the regional industry over the last few decades. in the late 1960s and 1970s the networks in the medium-technology sector were dominated by large state-owned firms that were highly vertically integrated and had lost their headquarter functions to the city of vienna. while supply-side linkages to the region still existed agglomeration took a very limited traditional form. in most cases, planning, r&d and marketing/distribution functions, i.e. those functions responsible for the monitoring of markets and technology, had been lost. clearly observable lock-in effects had let to agglomeration becoming a mere by-product of path-dependence with none of the advantages of agglomeration mentioned by botazzi et al. (2001). against the background of a history of outward dependence and nationalized standardized mass production the traditional indicators used to measure the strength of social networks had become weak. according to iammarino and mccann (2005) social networks exhibit the following characteristics: knowledge is largely codified and mature and mainly oriented to process innovation, transmitted essentially by way of personal contacts; there is extensive social and political lobbying, backward and forward linkages. as far as social networks still existed (e.g. in the machinery and the automobile sector) they became a fruitful base for the restructuring in the 1990s. during the developments of the last few decades the typology of agglomeration and the role of networks have changed considerably. many large firms were re-privatized and downsized at the end of the 1980s. firms thus needed to learn to collaborate and develop their potential for innovation as a strategic resource. this entailed abrupt and long overdue changes from a fordist to a more flexible mode of production. a massive structural change took place, beginning in the 1990s, especially in sectors related to steel production such as mechanical engineering and the automotive industry. high degrees of diversification and broad unspecified clients were replaced by a focus on market niches and technological specialization, while higher lot sizes enabled higher cross-functional integration and raised flexibility by leaving a scope for automation. technological upgrading (including the introduction of quality and measuring standards) opened doors to new clients. this was accompanied by extending their responsibilities for tool making and sourcing capabilities and also by shifting the responsibility for quality and price from clients to suppliers. innovations in these sectors were influenced by applications of specialized knowledge in the field of materials, tooling and processing techniques, or by the need to solve very specific problems in the machinery sector. on the supply side, hierarchical, spatially localized relations were developed. these have been formed around elite r&d-intensive export-oriented large firms. 3.7 human resources and the regional labour market a typical characteristic of agglomerations, in the sense of the model of pure agglomeration mentioned by gordon and mccann (2005), following botazzi et al. (2001) namely, a more or less common labour market pool – was not observed. for the investigated component supplier firms (here in more or less rural and isolated areas) it is still the case that they operate with reference to very local labour markets, binding traditions and a low mobility of employees. small and medium sized supplier firms exhibit family-based traditional structures, sometimes over generations. concerning the qualification structure, there are deep differences between original equipment manufacturers or system-suppliers with r&d units on the one hand, and basic technology providers, 57 extended work-benches or third party subcontractors on the other hand. this is true for both lower as well as high skilled workers, where employee turnover is normally a more or less excepted instrument of knowledge transfer and networking among firms. because of the immobility of the local labour force and the restricted capacity of the regional labour market most of these firms were able to retain keypersonnel and competences and the regionally integrative potential of their personnel. yet, by the same token, this implies only little mobility of qualified personnel coming from europe (for language reasons, predominately from germany). also due to official restrictions labour inflow from the new eu member countries remains limited. 3.8 discriminative capabilities and heterogeneous strategies in the case of r&d and innovation as already mentioned, leading firms do not play a dominant role on the demand side. the broad range of material input-output linkages is directed outward and direct material linkages on the regional level areweak. in fact the opposite seems to be true. in the case of large firms, agglomeration phenomena based on knowledge complementarities (botazzi et al. 2001) seem to be clearly evident. the r&d capacities of the observed firms were highly varied. nearly half of the investigated firms (mostly smes) do not employ permanent r&d staff. the leading firms have intensified r&d activities and formal co-operation with knowledgegenerating institutions since the mid of the 1990s. especially in the case of pre-competitive r&d cooperative publicly supported projects or participation in cooperative r&d institutions has gained an increasing role as a policy measure during the last decade. in respect to knowledge-driven activities, elements of agglomeration phenomena based on knowledge complementarities were observed (following botazzi et al. 2001). these were also in line with the exclusivity characteristics suggested by the industrial complex model (gordon and mccann 2005). the large r&d intensive firms observed here, constantly seek forms of regional pre-competitive r&d cooperation. this may result in the formation of “clubs” (gordon and mccann 2005, cooke 2000) of closer interaction especially in respect of r&d, or in some cases cooperative r&d institutions. while material input-output linkages are spreading widely and are outward oriented the r&d-oriented sphere is concentrated on the local context. this to a large extent supported by intensive direct and indirect social interaction (informal exchange, contacts in the local technical community). during the past few years, in terms of innovation firms already active in r&d have undergone a shift from being demand pull driven (responding to market demands) to technology push driven (firms have become proactive in their search for new technologies and usps). this has increased the motivation to be integrated in the regional (technical) science community. the main spheres of economies of agglomeration have shifted considerably during the last few decades. the newly identified research ‘clubs’ in publicly supported r&d-projects are able to utilize economies of agglomeration primarily concentrated in the field of r&d and science. as long as natural spill-overs are high and competitive conflicts are manageable (e.g. in the case of material sciences) larger firms accept weaker partners and smaller firms and are willing to integrate them into their activities. low spill-overs and a higher market orientation favour more restrained, sometimes exclusive behaviour from the stronger party. this corresponds with the findings in the literature for partner selection in r&dcooperations (atallah 2005). this form of agglomeration, partially taking place beyond formal networks, also corresponds with the idea of a new type of social network mentioned by iammarino and mccann (2005). firms engaging in cooperative pre-competitive r&d and knowledge generation appeared to seek suitable equal partners. the qualitative interviews strengthened the notion that firms attempt to generate a portfolio of cooperative partners which consciously combines specialization and flexibility. in terms of knowledge generation and exchange, the geographic dimension is relevant as long as the actors are able to utilize knowledge potential. while larger firms with noticeable r&d-capacities are able to utilize international contacts in research and development activities, smaller lowor mediumtech firms stick to the region and to their regional partners. smaller firms are confronted with a selfreinforcing combination of low r&d capability on the one hand, and limited market demand on the other. in agreement with the concept of absorptive capacity, it was found that firms with low r&d and innovation potential (mainly component suppliers, where innovation is predominately directed by investment) found it difficult to build up and retain adequate relations with knowledge generating organizations. the medium-tech component suppliers observed here, proved to be unable to maintain continuous relationships with knowledge generating institutions. they were not capable of defining, setting up and managing relevant projects. these low and medium-tech firms did, however, partially utilize opportunities to establish long-term contacts with individual public or semi-public r&d-institutions (dealing with basic technologies 58 such as material sciences). they also tried to gain from possible spill-overs from appropriate events or informal inquiries. here we found that, in direct delivery and in competitive and pre-competitive research and development (as far as existent) is not identical. in addition, two interesting long-term partnerships between small knowledge intensive technical business services and large systems and component suppliers were observed, in the network analysed here. they were based on long-term trust and informal exchange. 4 final remarks the roles of clusters, networks and geographical agglomeration are subject to considerable coevolution. different approaches concerning forms, channels and mechanisms of knowledge exchange offer different conclusions with respect to the significance of geographical agglomeration in knowledge exchange. in the case study analysis different dimensions of interaction can be observed. there are networking-dimensions of material, supply-oriented transactions and networking-dimensions of knowledge sharing. the first belongs to the process of division of labour dealing with the exchange of goods and services, the second with knowledge. the main differences reside in the form of interaction and in the impact of interaction. the spheres of physical interaction (subcontracting relations) differ considerably from the spheres of knowledge intensive and r&d-driven interactions. they are different in respect to actors involved, spatial extension, and significance of geographic agglomeration. the observed network is, in its regional dimension, dominated by knowledge intensive relations. the qualitative evidence gathered by numerous in-depth interviews reveals that the highest number of interactions was reached in precompetitive r&d knowledge exchange and that immaterial dimensions dominate the material ones. the (industrial) firms do have extensive supplier relations but only to a very limited extent within the region and within the network. there is no automatic parallelism of interactions. this does not necessarily exclude automatic spill-over of knowledge connected with supplier relations, but it does emphasize that higher intensities of knowledge exchange, as indicated by the revealed forms of interaction are actively chosen and not a mere byproduct. knowledge oriented relations within the network are to a large degree regionally concentrated. proximity per se is not sufficient to generate knowledge between firms. the diffusion of knowledge within clusters is highly selective and depends strongly on the position of firms within networks and their absorptive capacity. especially in pre-competitive research, local universities and cooperative r&d institutions play a dominating role and assume gatekeeper functions. firms with a relatively high r&d capacity also take up such a role, thus indicating the necessity of a welldeveloped internal knowledge base. the 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development in a global economy. guildford press, london. theter b.s. 2002. who cooperates for innovation, and why: an empirical analysis. research policy 31: 947-67. weber a. 1929. theory of the location of industries. the university of chicago press. chicago. issn: 2001-015x v o l 3 , n o 2 ( 2 0 1 3 ) c o n t e n t s sheila wright, christophe bisson and alistair duffy competitive intelligence and information technology adoption of smes in turkey: diagnosing current performance and identifying barriers pp. 5-29 a.s.a. du toit comparative study of competitive intelligence practices between two retail banks in brazil and south africa pp. 30-39 zhanna abzaltynova janice williams developments in business intelligence software pp. 40-54 francisco carlos paletta brazil evolutions in ci and some aspects of a current scenario pp. 55-61 o p i n i o n s e c t i o n francisco carlos paletta and nilson dias vieira junior ict lifecycle and its major role in the development of strategic intelligence pp. 62-78 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2013 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden dr. sofiane saadi, directeur général du laboratoire en organisation et gestion des entreprises (loge) algeria. managing director nt2s consulting inc. north vancouver, bc, canada javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') 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halmstad, august 25 2013 e d i t o r i a l n o t e v o l 3 , n o 2 ( 2 0 1 3 ) the sixth issue of jisib marks the journal’s second anniversary. again we are delighted to welcome contributions by academics from so many different countries, with so many different backgrounds. the academic contributions of our female authors continue to show also in this issue. if this issue should have one common theme it would be related to brazil. it is not a special issue on brazil, but we saw the possibility to include three articles which relates to the experience of competitive intelligence in this country. however, the first article by sheila wright, christophe bisson, and alistair duffy entitled “competitive intelligence and information technology adoption of smes in turkey: diagnosing current performance and identifying barriers“ is on another topic and deals with smes need to improve intelligencebased output to decision-makers. based on empirical findings the aim has been to identify and classify ci behaviour and attitudes of smes in turkey. the second article by a.s.a. du toit is entitled “comparative study of competitive intelligence practices between two retail banks in brazil and south africa” , where it is concluded that respondents in the bank in brazil cope better with changes in the external environment. the next article by zhanna abzaltynova and janice williams entitled “developments in business intelligence software” is an evaluation of bi vendors and software with extensive rankings. the article by francisco carlos paletta entitled “brazil evolutions in ci and some aspects of a current scenario”, is a summary of research done on the introduction of competitive intelligence in brazil. the article also gives a brief idea about its current status. in the opinion section we have included an article by francisco carlos paletta and nilson dias vieira junior entitled “ict lifecycle and its major role in the development of strategic intelligence”. it is an evaluation of the existing ict framework for competitive intelligence in brazil. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 pp. 5-29 francisco carlos paletta francisco carlos paletta and nilson dias vieira junior vol6no2paper2 salmas et al to cite this article: salmasi, m.k., talebpour, a., and homayounvala, e. (2016) identification and classification of organizational level competencies for bi success. journal of intelligence studies in business. 6 (2) 17-33. article url: https://ojs.hh.se/index.php/jisib/article/view/157 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index identification and classification of organizational level competencies for bi success maryam khalilzadeh salmasia, alireza talebpoura and elaheh homayounvalaa acyberspace research institute, shahid beheshti university, iran journal of intelligence studies in business please scroll down for article identification and classification of organizational level competencies for bi success maryam khalilzadeh salmasia, alireza talebpoura and elaheh homayounvalaa* acyberspace research institute, shahid beheshti university, iran *corresponding author received 14 june 2016; accepted 25 august 2016 abstract business intelligence is a technology-oriented solution that businesses need to survive in today’s competitive and constantly changing market. to gain the benefits of bi systems, it is important to evaluate, assess, and improve factors that have an influence on bi success. organizational competencies can provide answers to the question of how companies could gain more benefits from bi systems. while investment in bi systems is increasingly growing, measures to evaluate effective organizational competencies leading to bi success are gaining more importance. therefore, this research identified a number of effective organizational competencies that contribute to bi success. using the developed questionnaire for determining the effect of organizational level success on bi success, the research data was gathered for the study. a chi-square test confirmed the effectiveness of all nineteen identified competencies. then, an exploratory factor analysis (efa) was carried out on the data in order to identify the underlying dimensions. in addition, competencies were grouped into six categories, namely data management, information system/information technology (is/it) development, financial resources, relationship management, is strategy and human capital policies. as a result, these competencies can be used as a measure to evaluate an organization’s status in holding some of the effective factors for bi success. keywords bi success, business intelligence, exploratory factor analysis, organizational level competencies 1. introduction 1.1 bi success business intelligence (bi) is a modern information technology that helps organizations to collect, manage and analyze structural or non-structural data (lin, tsai, shiang, kuo, & tsai, 2009) (nyblom, behrami, nikkilä, & solberg søilen, 2012). bi has a fast growing market (abzaltynova & williams, 2013) that continuously introduces new trends such as cloud bi, social bi, and mobile bi and in the future “customized” bi (wang, 2015). nowadays, business environments are constantly changing (hoppe, 2013), highly competitive, and increasingly uncertain (banerjee & mishra, 2015) that organizations’ solutions for avoiding bankruptcy depend on successful bi (ranjan, 2008). in addition, organizations that utilize bi successfully can gain competitive advantages. in successful bi, information technology and the business process and strategies must be aligned together, so enterprises can manage and benefit from their investments in bi by allocating bi resources, prioritizing projects, and minimizing the risk associated with bi implementations (ranjan, 2008). successful business intelligence can help organizations to make the best decision at the best time through integrating and analyzing data with decision support systems (muntean, gabriel cabau , &rinciog, 2014). furthermore, successful bi provides the right information to the right people throughout the organization to improve strategic and tactical decisions (li, shue, & journal of intelligence studies in business vol. 6, no. 2 (2016) pp. 17-33 open access: freely available at: https://ojs.hh.se/ 18 lee, 2008). company return from it investment is an important part of successful bi. in other words, when a bi system is successful, the company gains tangible benefits from their investments in it. the opposite side of successful bi implementation is bi failure. reports of bi failures can highlight the importance of successful bi. about 50%80% of business intelligence applications fail due to technological, organizational, cultural and infrastructural issues (adamala & cidrin, 2011). in addition, they report that most bi failures happened because of a number of issues, such as ignoring bi as a cross organizational business initiative, lack of management and sponsor commitments, lack participation of the business side and representatives, unavailable skilled staff, ignoring business analysis activities, lack of appreciation of the impact of dirty data on business profitability and lack of understanding of the necessity for and the use of meta-data (chuah & wong, 2013). all the failure reasons show that a number of organization and staff characteristics, which are called ‘competencies,’ play a crucial role for bi success. competencies are related characteristics that prepare an organization to attain certain objectives. these characteristics can be categorized in two levels: organizational and individual. the effect of organizational level competencies on bi success is the topic of our study. as worley et al. (2005) mentioned “competencies can be analyzed at the level of an individual, gathering all the techniques allowing to facilitate the emergence, maintenance and development of personal competencies, but also at a collective level or even at an organizational level” (worley, chatha, weston, aguirre, & grabot, 2005). individual competencies are human resource capabilities that lead to better achievement of the predetermined objectives such as human resource skills, motivations, and behaviors that influence their performance and at least productivity. although individual competencies are also very important in applying bi systems we limited our research scope to organizational level competencies. in general, organizational competencies are an organization’s ability for optimizing use of available resources, setting shortand longrange goals, and developing the strategies and policies to achieve such goals. the concept of competencies first found its way into is/it studies in an attempt for supporting organizational it/is goals. competencies have been found to have the potential to impact organizational success and to be relative to bi in particular. specifically, it has been related to an organization's ability to derive benefits from their investment in is (chasalow, 2009). the aim of this research is to determine the organizational level competencies that are necessary for bi to be applied successfully according to the bi success factors. since the major reason that a large number of bi projects are considered to be failures is related to ignorance of organizational characteristics, the emergent competences identified in this research can help organizations understand the competencies that they need to build in order to benefit from their bi investments (chasalow, 2009). therefore, this research is directed towards developing a theoretical model for bi success. although bi success is the positive value that an organization obtains from its bi investment, its definition differs from one organization to another. it depends on what benefits that organization expects (sabanovic & solberg søilen, 2012) from its bi initiative. benefits that are gained from improved profitability, reduced costs, and improved efficiency can be defined as bi success in an organization. for the purpose of this research, bi success is defined as the positive benefits of bi, which the organization may achieve as a result of implementing bi competencies as important elements in the success of information systems, and appear to have the potential to be of particular value in explaining achieving benefits from bi. this research will therefore seek to develop a model to help explain the organizational level competencies that would support the attainment of business value from bi. the developed model can be used as an instrument to improve the likelihood of an organization achieving benefits from their bi investments. 2. literature review there are few studies about competencies that affect bi success. in this section, we study organizational level competencies related to is/it in addition to bi related competencies. first, competencies are described and then competency related research studies are introduced. the literature review is summarized in table1 and appendix a. 2.1. competencies “competencies have been studied from two different perspectives: (i) as assets, skills, or 19 resources belonging to the company that allow an activity to be performed systematically (ii) as the activities themselves, that is, the operations that the firm is able to carry out by integrating a series of assets, emphasizing what the company does as opposed to what the company has” (en escrig-tena & bou-llusar, 2005). previous literature includes studies that have adopted different competency-derived approaches such as the strategic management field (anderson & sohal, 1999;penrose, 1959; selznick, 1957), the resource-based view (danneels, 2002; montealegre, 2002; tyler, 2001; wilcox kingl & zeitham, 2001), the dynamic capability theory (huang, 2011), the competency-based competition (en escrigtena & bou-llusar, 2005), the knowledgebased theory (harzallah & vernadat, 2001), core competencies of strategic business units (bhamra, dani, & bhamra, 2010; prahalad, 1994; wang, lo, & yang,2004), competency for developing human resource (worley, chatha, weston, aguirre, & grabot, 2005; lee, 2010), and competency management within—and at the intersection of—knowledge management (javanmard, mashayekhi nezamabadi, & larki, 2010), project management (crawford & hassner nahmias, 2010), supply chain competencies (scc) (green jr., inman, birou, & whitten, 2014), and computer science (zouine & fenies, 2015). some of these studies on competency deal with is/it. since the early 1990s, the researchers considered the sustainability of competitive advantage from it (peppard & ward, 2004). the present research addresses the competencies studied in the is/it field. these competencies can be related to organizational factors or introduced as is/it capabilities that lead to better achievement in an organization. competencies are usually divided into two groups: organizational level competencies and individual competencies. organizational competency is a term that has been used in the world of performance management for many years. it is routinely used by human resource professionals and by organizational change consultants to refer to the variety of employee skills (nienabera & sewdassb, 2016) that the company must have in order to achieve their plans (coates & associates, 2008). the current research focuses on non-individual competencies (organizational level competencies) studied in the is/it field. 2.2. bi related competencies competencies within the sphere of bi first appeared in the bi practitioner literature beginning with the business intelligence competency center (bicc). bicc encompasses a lot of issues: better use of bi across the organization, greater alignment and collaboration between business units, a bi strategy that supports the corporate strategy, standardized bi processes and initiatives, consistency of definitions, processes, and methodologies, and higher roi from bi (miller, bräutigam, & stefani, 2006). miller and et al. (2006) introduced comprehensive competencies modeled in three dimensions: business skills, analytical skills, it skills to support the development and support of bi in an enterprise. but, these competencies are primarily technical in nature and their focus is not on organizational level competencies (miller, bräutigam, & stefani, 2006). furthermore, chasalow (2009) presented five competency factors on the organizational level: learning organization, participative leadership style, clearly defined business goals, technological resource availability, and financial resource availability. he argues that these five factors have an impact on business intelligence success (chasalow, 2009). as chasalow mentioned in his dissertation, his work is one of the few studies that have been done on organizational factor effects on is systems and also these studies are still in an initial stage. also, his study did not attended to some factors like relationship management that have been introduced in this research and are one of a company’s challenges for implementing information systems in some organizations. in addition to that, ghazanfari (2011) presented an expert tool to evaluate the bi competencies of iranian enterprises and identified six factors for his evaluation model: analytical and intelligent decision-support, access to related experimentation and integration with environmental information, optimization and recommended model, reasoning, enhanced decision-making tools, and finally, stakeholder satisfaction (ghazanfari, jafari, & rouhani, 2011). their view of bi competencies is limited to bi specification. their study is not about organizational level competencies, but they mention some competencies like stockholder’s satisfaction that we recognize as organizational level competencies. 20 furthermore, isık et al. (2013) studied the effect of the decision environment on business intelligence capabilities for achieving bi success. according to their study, technological capabilities such as data quality, user access and the integration of bi with other systems are necessary for bi success (isık, jones, & sidorova, 2013). although their study focused on technical capabilities, some of the capabilities, like data quality, are grouped into organizational level competencies in other studies like chasalow’s study. 2.3. studies on organizational level competencies in the is/it field because there are few research studies in the field of bi-related competencies, organizational level competencies in the is/it field have been studied too. since bi is an is system, not only studies about competencies in the is/it field have been studied in our research, but they can make our literature review more inclusive. competencies related to an is facilitate the relationships between organizational processes and structures for beneficial use of is resources in order to accomplish organizational tasks and obtain organizational goals (tarafdar & gordon, 2007). one of the most cited articles about is related capabilities is by feeny and willcocks (1998) in which they offer a competency model (feeny & willcocks, 1998). their model, which was revised in 2006, suggested four tasks and nine capabilities that grouped into three categories: business and it vision, delivery of it services, and design of it architecture that can help a company benefit from the technology (willcocks, feeny, & olson, 2006). furthermore, there are other studies that have addressed the problem of value creation from is investments in an organization as opposed to an is functional perspective. peppard, lambert & edwards (2000) developed a framework for mapping macro competencies and identified their related micro competencies. four years later, peppard and ward (2004) offered an is model that identified six domains of is competencies which are themselves composed of micro is competencies—25 in all. these domains involve strategy, is contribution definition, it capacities definition, exploitation, solutions and supply. it projects that help operational performance of the organization go back to 30 years ago (doherty & terry, 2009). as such, wade and hulland (2004) defined three is resources and capabilities that can be used for gaining market opportunities. they also proved that is resources rarely have a direct effect on sustained competitive advantage (sca), but they can indirectly lead to sustained performance (wade & hulland, 2004). in another study, doherty & terry (2009) examined the impact of is capabilities on competitive positioning at the process level. also, ravichandran (2007) presented how is capabilities can offer digital options that lead to firm agility by investing in it. similarly, tarafdar and gordon (2007) illustrate how six is competencies could affect the conception, development and implementation of process innovations. on the other hand, some studies addressed it competencies as components of other concepts. for example, ngai, chau and chan (2010) defined it competencies (it integration and flexibility) as supply chain competencies. also, the theory of competency rallying (tcr) was presented for the first time by katzy and crowston (2000). crowston and scozzi (2002) then introduced the tcr model and tested it in the context of oss projects as a virtual organization (ghapanchi, 2013). while all the studies on is/it discussed above have adopted the resource-based view of is/it competencies, some other research studies have introduced different views. for example, caldeira and dhillon (2010) categorized organizational competencies into two groups: facilitating competencies and fundamental competencies that lead to information technology advantages within organizations (caldeira, mário; dhillon, gurpreet, 2010). additionally, chen & wu (2011) developed a model of it management capability of cios and found that information technology competencies affect it management activity. although these is related studies did not consider some competencies that are more important for bi like data quality or metadata that are mentioned in bi related competencies, they mentioned important competencies that are necessary for bi implementation as an is system. is related studies are summarized in this research, because considering is related studies beside bi related competencies can show their similarities and differences. a review of the related literature is summarized in table 1. table 1 constructs for is/it competencies source competency constructs dependent variables feeny & willcocks, (1998) and willcocks, feeny & olson (2006) is/it governance, business system thinking, business-is relationship building, designing technical architecture, making technology work, informed buying of it services, contract facilitation, contract monitoring, vendor development none peppard & ward (2004) strategy formulation (business strategy, technology innovation, investment criterion, information governance) is strategy (prioritization, is strategy alignment, business process design, business performance improvement, systems and process innovation) it strategy (infrastructure development, technology analysis, sourcing strategies) exploitation (benefits planning, benefits delivery, managing change) solutions (applications development, service management, information asset management, implementation management, business continuity and security) supply organizational performance doherty & terry (2009) outside-in (external relationship management, market responsiveness) spanning (is-business partnerships, is management/planning) inside-out (infrastructure provision, is technical skills, is development, cost-effective is operations) sustainable improvements to competitive positioning wade & hulland (2004) external relationships management, market responsiveness, is business partnerships, is planning and change management, is infrastructure, is technical skills, is development capability, operational efficiency ravichandran (2007) digital option (it infrastructure flexibility, application platform scope), is capabilities (planning sophistication, development capability, support maturity, operations capability), it investment orientation organizational agility tarafdar & gordon (2007) knowledge management, collaboration, project management, ambidexterity, it/innovation governance, business-is linkage, process modeling process innovation ngai, chau, & chan (2010) it integration, it flexibility supply chain agility caldeira & dhillon (2010) fundamental competencies in delivering it benefits which entail the following capabilities (conducting it strategic thinking and planning, aligning it with business processes and objectives, deploying cost effective applications and systems, conceptualizing the maintenance of data integrity and confidentiality, facilitating behavior enrichment for technology adoption, ability to ensure compliance with standard it methods and procedures) facilitating competencies in delivering it benefits include the following capabilities (selecting and managing it staff, providing ongoing it training, acquiring top management support in it projects, designing business processes for effective use of it expertise, maintaining systems consistency, involving users in it projects, instituting slas (service level agreements) with it suppliers, identifying and setting it standards and procedures, developing software in-house, selecting and contracting it vendors and is consultants, deciding on software sourcing strategies, maintaining or decreasing system response time, ensuring user application knowledge, identifying business is requirements, increasing the credibility of the it department, increasing service accountability, developing an is architecture) delivering it benefits chen & wu (2011) it infrastructure, business application, business technology integration it management activity effectiveness miller, brautigam, & stefani (2006) business skills (linking to business strategy, defining priorities, leading organizational and process change), it skills (data quality), analytic skills (the ability to discover and explore, developing business rules, developing user skills), business skills, it skills, and analytic skills overlap (defining bi vision, managing programs, controlling funding, establishing standards, technology blueprint, mythology leadership, adaptable infrastructure, extracting data, identifying data) business needs organization and processes tools and applications data integration chasalow (2009) individual competencies (strategic hr management) organizational competencies (learning organization, participative leadership style) decision making (clearly defined business goals, technological resources availability, financial resources availability, human resources availability) bi success rouhani, jafari, & ghazanfari, (2011) analytical and intelligent decision-support, providing related experiment and integration with environmental information, optimization and recommended model, reasoning, enhanced decision-making tools, stakeholders’ satisfaction bi success popovic, hackney, simoes coelho, & jaklic, 2012 data integration, analytical capabilities, information content quality, information access quality, use of information in business processes, analytical decision-making culture bi systems maturity isık, jones, & sidorova, 2013 data quality, integration with other systems, user access quality, flexibility, risk bi success 3. research methodology to answer the research question of “what are organizational level competencies for bi success?”, first we identified organizational level competencies from the literature review. then a questionnaire was designed to answer the question “are these identified competencies effective in bi success?” in order to test whether the designed questionnaire was valid and reliable, and 22 effective for answering the research question, we performed a validity test like efa that classified constructs. the research steps as are follows in figure 1: (1) specifying the domain of the construct, (2) identifying the competencies by literature review and making the semi-structured interviews, (3) constructing an initial framework, (4) designing the questionnaire, (5) collecting data (6) testing the hypotheses, (7) assessing construct validity and reliability of the measures. in the following sections, each step is elaborated in more details and some of the steps are explained in section 4: data analysis and results. 3.1 specifying the domain of the construct according to what is described in the literature review, there are different competency-derived approaches. moreover, competency-based studies on bi are in their infancy and limited. however, there are more research studies on is/it related competencies in the literature. therefore, additional competencies were extracted from other competency-based studies including both bi and is/it, which use a more resource-based approach to competency indices. the literature identifies two levels of competencies: individual level and organizational level. the present paper addresses the organizational level. 3.2 identification of the competencies from the literature review and interviews the first step is to identify the competencies. this can be done through adopting either a qualitative or quantitative approach. in our case, the competencies were developed through reviewing the literature on is/it and birelated competencies. initially, 35 is/itrelated competencies at the organizational level were identified. the next step was to examine the competencies identified for content validity. content validity is whether or not the elements in a given construct represent the underlying concept to be measured. in our case, we used two methods for determining content validity: 1) conducting interviews to investigate if variables are transparent enough, appropriate and relative. some variables like knowledge management, project management, and change management that are more reflective than formative were eliminated. as a result, 19 competencies were extracted from a total of 35 by eliminating or merging the elements. appendix a outlines these 19 competencies and provides their related sources. 2) developing an initial theoretical framework by grouping competencies in relevant constructs by an inductive reasoning method and via the help of experts who reviewed the elements in each group that are explained in the following sections. 3.3 constructing an initial framework for determining the importance of competencies in bi success concepts comprise categories which in turn create the basis for the formation of a theory (allan, 2003). the aim of categorizing competencies is indirectly to determine the importance of competencies in bi success, that is, how these 19 competencies lead to bi success. the competencies were grouped into three bi related categories: it infrastructure, it governance, and resources. these categories and their variables are shown in appendix a. a) it infrastructure group: miller et al. (2006) argue that “infrastructure refers to the hardware, software, networking tools, and technologies that create, manage, store, disseminate, and apply information”. figure 1 the research steps 23 a business intelligence infrastructure has to be responsive to various needs of a business on demand and in real time. also, well-defined infrastructure ensures data quality and availability. the v1 to v7 group of variables was assigned to the it infrastructure category as critical it assets. it is crucially important to build and expand the necessary data and analytic infrastructure that is agile, stable, scalable, and integrated. data quality and stewardship especially are important for developing metadata (miller, bräutigam, & stefani, 2006). b) bi governance: this is a new term that a few references mentioned it. turban et al. (2010) used bi governance for prioritizing bi projects and appropriate planning and forming an alignment with the business strategy as a factor for bi success. beth (2006) also developed a bi governance framework and application portfolio that deals with the funding process, exceptions process, bi development process, tracking and measurements, and communications plan as governance mechanisms. the v8 to v 15 group of variables were assigned to the bi governance category, emphasizing the importance of strategy thinking to both sides of is and business alignment to ensure bi success. it is evident that is strategy is critical, however, it would be a waste of resources for both sides to overlook the business needs, and the alignment of business and is strategy. c) facilitating resource: this is critical for determining the relative success or failure of it adoption. in fact, resource facilitation supports fundamental competencies (caldeira, mário; dhillon, gurpreet, 2010). chasalow (2009) refers to financial resources and strategic human resources as organizational competencies for business intelligence success. moreover, miller et al. (2006) describe human capital as an important factor for bicc. v16 and v17 as financial resources and v18 and v19 were grouped into the human capital policies category that was included in facilitating resources. the implementation of bi systems does not just occur on one day and end there; they rather take place gradually over time and through data collection, hence there is the need for more financial support and budget allocation. on the other hand, even the best systems without utilizing skilled users could not amount to much, as a study asserts that inadequate education and training and lack of employees’ morale and motivation cause the failure of erp projects (amid, moalagh, & zare ravasan, 2012). 3.4 questionnaire design in the third step, a questionnaire was designed with three main sections. the first section of the questionnaire consisted of questions about the characteristics of the interviewees. the content of the second section entailed the description of bi success as described in the literature review. and the third section of the questionnaire included questions about the effect of the 19 competencies on bi success using a five-point-likert scale ranging from (5) “highly effective” to (1) “highly ineffective”, and additionally an “uncertain” option. the third section of the questionnaire was designed to measure the effect of the 19 organizational competencies on bi success in the organization. 3.5 sample size and data collection using purposive sampling, the target population of this study was determined to include consultants and it department members of the ministry of industries mines and trade. this study was conducted in iran, because the environment in which iranian organizations operate today is becoming more and more complex. moreover, organizations and departments that are situated inside organizations face problems such as reduced budgets and amplified pressure from top managers to increase performance and profit and also from markets and consumers to lower the prices. in this kind of environment, managers must respond quickly, innovate, and be agile. both private and public organizations are cognizant of today's business environment and pressures (turban, sharda, delen, & king, 2010). in october 2011, the ministry approved a sizable budget for bi implementation that came into effect. the sample size was a major 24 limitation in our study in terms of the available time. additionally, some experts were not interested (e.g. due to lack of familiarity with the research subject) in cooperating with the research, especially, with the electronic form of the questionnaire. consequently, the data was collected from questionnaires which were distributed among the minimum sample size of 80 individuals after removing none approved samples. there are different ideas about the minimum sample size in factor analysis. according to lawley & maxwell (1971), 51 more cases than the number of variables are enough. although the subject-to-variables (stv) ratio of the sample size is 4.2 (that is under 5), expletory factor analysis was conducted because the kmo is 0.62, which is above the ‘‘average’’ threshold of 0.5 (amid, moalagh, & zare ravasan, 2012; kaiser, 1974), and the bartlett test p-value is less than 0.05, which suggests a good correlation. demographically, 5.8% of the respondents had a phd degree, 46.37% had an m.e. degree, and 47.83% had a b.e. degree. of these, 4.48% of the respondents were classified as university professors, while 41.79% were executives/managers, and 53.73% were it department employees that they had work experience in the area of bi tools. 4. data analysis and results in this stage, the collected survey data from the questionnaire was used for testing the research hypothesis. it was necessary to determine the statistical distribution of the collected data from the third part of the questionnaire. subsequently, based on the distribution of data, either a parametric or non-parametric test was performed to prove the hypothesis: h1: do v (i=1 to 19) competencies have effects on bi success? the next step in the development of this type of measurement was to test the construct validity and reliability. construct validity exists if the items accurately represent the underlying concepts that are being measured (boudreau, gefen, & straub, 2001). therefore, some tests were performed on the data collected from the third part of the questionnaire. 4.1 hypothesis test in order to evaluate the effectiveness of 19 competencies on bi success, the results should support the hypothesis. as previously mentioned, these 19 items were included in the third part of the survey questionnaire constituting the hypothesis: h1. do v (i=1 to 19) competencies have effects on bi success? one of the most accepted ways to identify the distribution of the data, statistically, is the one-sample kolmogorov–smirnov test. the kolmogorov–smirnov test compares the observed cumulative distribution function for a variable with a specified theoretical distribution, which may be normal, uniform, poisson or exponential (lilliefors, 1967). many statistical parametric tests require normally distributed variables. the one-sample kolmogorov–smirnov test can be used to test whether or not a variable is normally distributed (hollander & wolfe, 1973). according to our test results, the p-value of all 19 items was less than 0.05, which shows that their distribution was not normal; hence there was a need for a statistical non-parametric test to prove h1. therefore, a chi-square test was used to determine whether the frequencies of the upper categories of likert questionnaire, (5) “highly effective” and (4) are higher than other categories (i.e. 1, 2, and 3). that is, the residual (r2) values of categories (5) and (4) of the likert scale are to be higher than categories (3), (2), and (1). the chi-square test procedure (cochran, 1954) tabulates a variable into categories and computes a chi-square statistic. this goodnessof-fit test compares the observed and expected frequencies in each category to test whether all categories contain the same proportion of values or test that each category contains a user-specified proportion of values. a significance level below 0.05 for all the 19 items indicates that the observed frequencies differ from expected frequencies in each category and the average rate of frequencies do not significantly differ by category. on the other hand, the residual (r2) of each category of items, which is equal to the observed frequency minus the expected value, shows that differences between observed frequencies (nonparametric tests, chi-square test) in (4) and (5) are a lot more than the expected frequencies and are completely positive. thus, based on the significance level and residual test for all items, it can be concluded that all of the 19 competencies are highly effective for bi success in an organization. 4.2 exploratory factor analysis in this study, we use an exploratory factor analysis (efa) as a statistical approach to determine the correlation among the variables in a dataset. this type of analysis provides a 25 factor structure (a grouping of variables based on strong correlations). efa is good for detecting "misfit" variables. in general, an efa prepares the variables to be used for cleaner structural equation modeling. an efa should always be conducted for new datasets (statwiki, 2012). an efa was used to examine the dimensions evidenced in the data and the loading of the items on the empirically specified dimensions of effective organizational competencies for success. principal component analysis was used to extract the factors with the varimax rotation method to simplify the interpretation of the factors. the guttman-kaiser rule was applied to determine the number of capability factors. at this point, only factors with eigen values of one or more were retained. a kaiser-meyerolkin (kmo) and bartlett's test were conducted prior to the efa. in addition, the kmo (kaiser, 1958) examines whether the partial correlations among variables are small (momeni & mehrafzoon, 2013). bartlett's test determines (bartlett, 1950) whether the correlation matrix is an identity matrix, which would indicate that the factor model is inappropriate. the kmo is 0.62, which is above the ‘‘average’’ threshold of 0.5 (amid, moalagh, & zare ravasan, 2012; kaiser, 1974), and the bartlett test p-value is less than 0.05 which suggests good correlation. according to hair et al. (1998), factor loadings over 0.3 meet the minimal level, over 0.4 are considered more important, and 0.5 and greater are practically significant. it is also suggested that the loadings over 0.71 are excellent, over 0.55 good, and over 0.45 fair (amid, moalagh, & zare ravasan, 2012). the factor analyses conducted in this study are assessed according to these criteria and because the chi-square test proved the effectiveness of the factors before the efa, factor loadings over 0.45 are considered suitable for efa. the 19 variables were grouped into six categories of factors which had an eigen value greater than one and factor loading greater than 0.45, and the interpretation variable was 70.8. moreover, the extraction variances of the 19 variables were greater than 0.61. table 1 summarizes the results of factor loading. table 2 the results of efa and reliability test factor1 factor2 factor3 factor4 factor5 factor6 factor (1), data management: v7: metadata tools availability 0.8 v6: data quality improvement 0.78 v5: well-defined data environment including stewardship and metadata 0.74 v4: integration of data sources 0.48 factor (2), is/it development: v3: applications development 0.84 v2: it flexibility 0.81 v1: is architecture framework 0.64 factor (3), financial resources: v16: funding for acquiring bi tools and building related systems 0.82 v15: sourcing strategy 0.74 v17: funding for building and maintaining an analytical data environment 0.73 factor (4) relationship management: v8: external relationship management 0.8 v11: stakeholder planning and management 0.66 v10: service level definition 0.65 v9: it vendor and consultant development 0.51 factor (5) is strategy: v12: business processes and is/it alignment 0.77 v13: is strategy alignment 0.77 v14: is prioritization strategy 0.46 factor (6) human capital policies: v19: ongoing it training 0.85 v18: selection, evaluation and management of (especially it) staff 0.71 eigen value 5.08 2.51 2.04 1.44 1.24 1.14 % of variance 26.75 13.21 10.73 5.58 6.52 6.02 cronbach's alpha 0.79 0.8 0.77 0.69 0.6 0.61 4.3 factor denominations the factors were named based on the meaning and functionalities of the competencies that were related to each factor (momeni & mehrafzoon, 2013). the names and content of the six factors are shown in table 2. the following section offers an elaboration of each of the factors, which are based on explanations or model dimensions of their criteria-related resources. factor (1) data management: this refers to capturing, storing and maintaining a large volume of data to support bi analysis (chasalow 2009). qualitative data is the most important part of an analysis. capturing and storing metadata helps to create various reports from various dimensions. here, data management is defined as how data can be integrated and validated in a proper way to be more profitable. factor (2) is/it development: this refers to the competencies that allow an organization to develop or experiment with new technologies. so, infrastructure must be flexible and is architecture has to be designed in a way that allows development (wade & hulland, 2004). factor (3) financial resources: first described by chasalow (2009), financial resources deal with the availability of financial resources to support the collection and maintenance of bi tools. many is implementation projects failed because of a lack of financial resources. although availability of the resources facilitates bi success, financial resources are an important competency that determines success and failures of these projects. factor (4) relationship management: the aim of relationship management is to increase the connectivity with consumers, suppliers and other trading partners. one of the is systems’ (like scm, crm) tasks is facilitating relationships of organizations with their partners (aziza, oubrich, & solberg søilen, 2015). so well defined management systems can lead to is systems like bi. schaarschmidt, walsh, kortzfleisch (2015) mentioned interacting with external parties on a macro level of governance, which we considered a relationship management factor in it governance groups. factor (5) is strategy: this is defining organizational strategies in a way that integrates is with business (peppard & ward, 2004). for bi success in an organization, organizational strategies must be well defined in a way that information systems meet the business needs. besides, business strategy must consider is needs. factor (6) human capital policies: this is a very well defined system that can benefit an organization without well trained users. the human resources importance for is success, especially in bi, is clear as described before and is considered to be individual competencies. but, human capital policies are permanent and continuing policies and the processes of an organization for selecting, evaluating and training it and business staffs in a way that helps bi implementation and usage. table 2 illustrates which competency (vi) has been grouped into which factor (j). on the other hand, appendix a illustrates relationships of the initial theoretical framework with competencies (vi) and factors (j). as described earlier, the research theoretical framework groups competencies into three categories. the framework was then revised by efa, so competencies which were assigned to the it infrastructure category were divided into factor (1) and factor (2); the bi governance category was divided into factor (4) and factor (5); the facilitating resources category was divided into factor (3) and factor (6). v15 (sourcing strategy) which was primarily grouped as one of the it governance category, by efa has been grouped into factor (3). figure 2 also shows the factors and the initial framework relationships. 4.4 reliability reliability is another aspect of the measurement scale to be evaluated in this step. this concept refers to the extent to which repeated use of the measurement scale would give the same results (straub, 1989). the analysis of reliability is reported in table 2 as composite reliability, and was entirely consistent with the factor analysis. table 1 outlines cronbach's alpha based on standardized items where values above the minimum of 0.6 for f4, f5, and f6 are unacceptable, and above the minimum of 0.7 for f1, f2, and f3 are considered acceptable. for the reliability of the questionnaire, the cronbach’s alpha was estimated to be 0.86 (greater than 0.7), which implies good reliability of the instrument (amid, moalagh, & zare ravasan, 2012; nunnally, 1978). 27 4.5 discriminant validity discriminant validity refers to the extent to which factors are distinct and uncorrelated. the rule is that variables should relate more strongly to their own factor than to another factor. two primary methods exist for determining discriminant validity during an efa. the first method is to examine the pattern matrix. in order to have discriminant validity, variables should load significantly only on one factor. the second method is to examine the factor correlation matrix, as shown in table 2. correlations between factors should not exceed 0.7. a correlation greater than 0.7 indicates a majority of shared variance (0.7 * 0.7 =49% shared variance) (statwiki, 2012). as can be seen from the factor correlation matrix in table 3, correlations between all factors are under 0.7 which supports the discriminant validity. table 3 correlation matrix of factors f(1) f(2) f(3) f(4) f(5) f(6) f(1) 1.000 f(2) .361 1.000 f(3) .260 .512 1.000 f(4) .122 .278 .357 1.000 f(5) .338 .425 .385 .356 1.000 f(6) -.161 .170 .295 .215 .220 1.000 5. discussion this paper presented a competency model as illustrated in figure 2. interpretations of factors and practical usages of this model are discussed in the following sections. 5.1 interpretation of factors according to our findings, there is no similar research that has presented effective competencies for bi success by studying previous research in is fields. one of the differences between research studies about is and bi related competencies is the emphasis of bi related research studies on data management and its factors that also were shown in efa results. efa shows that the data management factor has the highest variance, among other factors. this is due to the fact that a bi system’s goal is analyzing data for exploring useful information for decision makers and it makes data management a critical factor for bi success. the importance of data management is highlighted in many sources and articles, such as işık (2010) who defined data sources, data types, and data reliability as bi capability; or cox (2010) who identified information availability, information quality, and information quantity as effective elements that improve decision-making speed and quality. factor (2), is/it development, is an organization’s ability to develop applications, architecture and infrastructure of is without which data cannot be gathered and managed perfectly. therefore, this factor is considered to be a base or infrastructure for data organizational competencies for successful bi implementation facilitating resources bi governance it infrastructure : data management : is/it development : relationship management : is strategy : financial resources : human capital f(1) f(2) f(4) f(5) f(6) f(3) 0.57** 0.83*** 0.64*** 0.66** 0.87*** 0.42* r2=0.33 r2=0.69 r2=0.41 r2=0.44 r2=0.76 r2=0.19 * indicate that the coefficient is significant at p ≤ 0.05 ** indicate that the coefficient is significant at p ≤ 0.01 *** indicate that the coefficient is significant at p ≤ 0.001 figure 2 the model of organizational level competencies effects on bi success 28 management. most of the articles in which factor (2) is referred to have mentioned application development capability as a competency and they have ignored the importance of architecture and system flexibility for implementing new information systems or developing new features for existing systems. in this article, is/it development refers to both soft (application) and hard (infrastructure) abilities and their flexibility of an organization for bi success. financial resource is not considered to be an is ability, however, it provides the ground for other capabilities and because of their importance in is implementation, we cannot overlook them, especially in bi implementation which is a time-bound development process. the importance of financial resources ignored in most articles related to is competencies except chasalow’s study that emphasized its importance. as an initial classification, the sourcing strategy is classified into it governance groups and funding for acquiring bi tools funding for building and maintaining an analytical data environment, classified into resource facilitation groups. sourcing strategy that is classified into financial resources refers to both sides of the funding strategies of sourcing and selection of supplies. by grouping the sourcing strategy competency into financial resources factors, the first side of the competency (funding strategies of sourcing) was highlighted. both internal and external data gathered from suppliers and stakeholders are important to determine bi success. on the other hand, continued relationships with it vendors (solberg søilen & hasslinger, 2012) and consultants are necessary for having a better understanding of an organization's it needs. therefore, relationship management is another important ability, as well. it is one of the top and long-running concerns of the senior management that the organizational strategies are in alignment with the business strategy as well as the is strategies. research studies show that businesses rely on it to execute the company strategy and the top priority is building the foundation for execution, which is the it infrastructure and digitized business processes that automate the core capabilities of the enterprise. businesses should have strategic directions about is investments that lead to alignment between it strategy and business processes (peppard, lambert, & edwards, 2000). the requirement for alignment of the organization’s is/it strategy with the business’s underlying goals and objectives was apparent. in is strategy definition, is/it governance imply an important role for integrating the it effort with business strategy and processes (willcocks, feeny, & olson, 2006). in a similar way, bi governance responsible for arranging strategies, structures, processes, and activities of bi for a business is an important factor for bi success. factor (5), is strategy, is a strategy part of bi governance that refers to is and business strategy and their alignment. this factor is the most referred to, directly and indirectly, among other factors that suggests the importance of is and business strategies and their alignment. human resources determine how bi has been used in the organization. skill, knowledge, and motivation of users (both business and it users), such as it skills, statistical and analytical knowledge, creativity and market knowledge are critical for working with bi systems, which are achieved through selecting, evaluating, and managing staff and ongoing it training. although human resource abilities refer to individual competencies, management of individual competencies and an organization’s policies for directing them refer to organizational level competencies. some articles like peppard & ward (2004) or chasalow’s study have mentioned human resource strategy and development importance. there is more need for specific studies about its importance in information systems; the gap is obvious among research studies in this subject area. 5.2 practical usages the results of the factor analysis indicate that the organizational competencies for bi success can be evaluated based on six main factors. to measure the maturity of these factors, an organization should be evaluated by nineteen criteria through questions about organizational competencies. using the extracted loads of each criterion within its factor, the maturity of the organizational competencies can be measured and depicted on a chart (for the six factors). by comparing the “as is” situation of these six factors with the “to be” situation the probability of bi success can increase as revealed through interviews with the experts of the studied organizations. since bi success criteria may differ from one organization to another, in addition, the criteria defined for bi success have influence on the importance of defined competencies; bi 29 critical success criteria must be defined in the organization first. also, defining bi success criteria helps the organizations that is going to implement bi to measure the fulfillment of these criteria. periodic evaluation of success criteria and their relative competencies can lead to continuous system performance improvement and better utilization of the information system. the present research introduced a new measurement instrument by using a competency-based approach to bi, which helps companies achieve bi success. it should be noted that the authors utilized a case study to propose a valid measurement model. nevertheless, it is believed that it can be generalized to apply to similar organizations, which plan to implement bi. the authors believe that the results of this research can help organizations make better decisions with regard to implementing bi, and shed light on effective organizational competencies according to critical success factors (csfs) of bi implementation. 6. conclusion and future research the purpose of the study was to introduce new competency measurements on the organizational level for bi success. in this way, first we reviewed related literature about competencies and bi success. after we specified our research domain to the organizational level and is/it or bi related competencies, competencies of presented models in this domain were extracted and decreased to 19 competencies by combining and interviewing. then, the questionnaire was developed that asked about the 19 competencies effect on bi success in its part 3, which contains an explanation of the bi success definition in part 2 (part 1 was assigned to the respondent profile). all 19 of the competencies effects on bi success was approved by a chi-square test. an efa, conducted to test the validity, grouped the 19 competencies into six factors that are grouped in the initial framework (it infrastructure, bi governance, and facilitating resources). the six factors are named and described completely in this article. bi systems are new to iranian companies and there are only limited numbers of companies that are familiar with bi systems. that was a limitation for this study. on the one hand, the number of experts who were qualified enough for participating in the study was limited. nonetheless, some experts declined to participate and answer the questionnaire. indeed, this study is not comprehensive in relation to organizational competencies for bi success. this is because the scope of the study is limited due to the elimination of some competency constructs: knowledge management competencies (alpar, engler, & schulz, 2015) that incude the capturing, filing and categorization of the information (oubrich, 2011), business process competencies, project management competencies, and learning organization competencies (which were among the 40 competencies explored). since these competency constructs can be in turn defined as independent study projects for future research, we found them to be beyond the boundaries of a single study. 7. references abzaltynova, z., & williams, j. 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(2015). a new evaluation model of erp system success. journal of intelligence studies in business, 5(1), 18-39. 8. appendix a the organizational competency descriptions and related sources. id competency the ability related sources it i nf ra st ru ct ur e v1 is architecture framework the type of is architecture framework determines the development and maintenance ability of the system (caldeira, & dhillon, 2010)(chasalow 2009)(feeny, & willcocks, 1998)(j. miller, bräutigam, & stefani, 2006)(peppard & ward, 2004) v2 it flexibility it flexibility is a part of the it infrastructure ability that facilitates quick and easy adaption of new technology launches (some references mentioned connectivity, compatibility and modularity as it flexibility factors) (miller, bräutigam, & stefani, 2006)(ngai, chau& ,chan, 2010)(ravichandran, 2007) (agostino, solberg søilen, & gerritsen, 2013) v3 applications development to develop/acquire and implement information, systems and technology solutions that satisfy business needs (not only to develop applications in-house but also to contract out it products and services) (caldeira, & dhillon, 2010)(doherty & terry, 2009)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000)(wade & hulland, 2004) v4 integration of data sources to link information systems and share information among different functions and parts of a supply chain (chasalow, 2009)(chen & wu, 2011)(miller, bräutigam, & stefani, 2006)(ngai, chau& , chan, 2010) v5 well-defined data environment including stewardship and metadata to manage and maintain metadata and to administer technical metadata and ensure its adjustment with business metadata (stewardship) (chen & wu, 2011)(miller, bräutigam, & stefani, 2006) v6 data quality improvement to have and improvement cycle for collecting, correcting, accreting, and validating data and improving data quality (caldeira, & dhillon, 2010)(chen & wu; 2011)(miller, bräutigam, & stefani, 2006) (fourati-jamoussi & niamba, 2016) 33 v7 metadata tools availability to have and use metadata tools regularly across the organization (chen & wu, 2011) b i g ov er na nc e v8 external relationship management to manage linkages between the is function and stakeholders outside the firm (doherty & terry, 2009)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000)(wade & hulland, 2004) v9 it vendor and consultant development to have an outreach list and contact it/ebusiness service suppliers. the ability to have long relationships with vendors and consultant that sure supporting the implemented system (caldeira, & dhillon, 2010)(feeny, d.f; willcocks, l.p, 1998)(j. miller, bräutigam, & stefani, 2006)(willcocks, feeny, & olson, 2006) v10 service level definition the establishment of service level agreements, and their monitoring, evaluating, measuring, and managing; which is an element of informed buying (caldeira, & dhillon, 2010)(feeny, & willcocks, 1998)(j. miller, bräutigam, & stefani, 2006)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000) v11 stakeholder planning and management to identify key business, human resources, and technical stakeholders to clarify the benefits of the change; and planning and managing their expectations (caldeira, & dhillon, 2010)(ghazanfari, jafari, & rouhani, 2011)(miller, bräutigam, & stefani, 2006)(peppard & ward, 2004) v12 business processes and is/it alignment to integrate it efforts with business purposes and activity and to determine how is can deliver the ‘best practice’ in operational processes and organizational activities (caldeira, & dhillon, 2010)(peppard & ward, 2004)(tarafdar & gordon, 2007)(wade & hulland, 2004)(willcocks, feeny, & olson, 2006) v13 is strategy alignment business strategies should support and be aligned with is strategies and vice-versa (i.e. strategic alignment). according to the alignment is and business are in the same direction ( caldeira, & dhillon, 2010)(miller, bräutigam, & stefani, 2006)(miller, bräutigam, & stefani, 2006)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000) v14 is prioritization strategy to prioritize technology investments and to balance information technology demand and resource requirements to maximum return from investments (chen & wu, 2011)(miller, bräutigam, & stefani, 2006)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000) v15 sourcing strategy to stablish criteria and processes to evaluate the cost-benefit of supply options and contracts with suppliers, to outsourcing it services, and custom designed applications ( caldeira, & dhillon, 2010)(feeny, & willcocks, 1998)(willycocks, feeny, & olson, 2006) f ac ili ta ti ng r es ou rc es v16 funding for acquiring bi tools and building related systems to provide and anticipate required funding to develop an enhanced use of the systems (chen & wu, 2011) v17 funding for building and maintaining an analytical data environment funding for maintaining or improving systems’ response time and the level of it service delivery and funding for improving data quality and availability (chen & wu, 2011) (agostino, solberg søilen, & gerritsen, 2013) v18 select , evaluate, and manage (especially it) staff to recruit an individual who was involved in bi projects and evaluate their technical skills ( caldeira, & dhillon, 2010)(miller, bräutigam, & stefani, 2006)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000) (amara, solberg søilen, & vriens, 2012) v19 ongoing it training to develop staff skills to use computers and software applications and to deploy their skills to ensure technical, business and personal skills meet the needs of the organization ( caldeira, & dhillon, 2010)(chen & wu, 2011)(peppard & ward, 2004)(peppard, lambert, & edwards, 2000) vol6no1paper1 nienaber and sewdass to cite this article: nienaber, h. and sewdass, n. (2016) a reflection and integration of workforce conceptualisations and measurements for competitive advantage. journal of intelligence studies in business. vol 6, no 1. pages 5-20. article url: https://ojs.hh.se/index.php/jisib/article/view/139 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a reflection and integration of workforce conceptualisations and measurements for competitive advantage hester nienaber and nisha sewdassa adepartment of operations management, ajh van der walt building, university of south africa, pretoria, south africa, nienah@unisa.ac.za; bcollege of economics and management sciences, ajh van der walt building, university of south africa, pretoria, south africa, sewdan@unisa.ac.za journal of intelligence studies in business please scroll down for article a reflection and integration of workforce conceptualisations and measurements for competitive advantage hester nienabera and nisha sewdassb adepartment of operations management, ajh van der walt building, university of south africa, pretoria, south africa; bcollege of economics and management sciences, ajh van der walt building, university of south africa, pretoria, south africa; *corresponding author: nienah@unisa.ac.za received 15 march 2016; accepted 8 may 2016 abstract workforce management is important in organisational performance. however, executives lament that their workforce management efforts remain ineffective. this comes as no surprise, as workforce measurement poses a challenge for several reasons: the many different conceptualisations of the workforce, which developed in parallel, and flawed workforce analytics, hence inadequate workforce intelligence, are among the most significant. to have the right people available requires timely and accurate information and intelligence to make evidence-based decisions. in order to achieve this proper measurement is required, which forms part of the information system that ensures the availability of the right people, at the right place, at the right time. people measurement/metrics, is a neglected area of research, which is receiving increased attention. though little, if any, attention is devoted to the link between people as dimension of competitive advantage and metrics to ensure the availability of the right people, at the right place at the right time. our conceptual paper attends to this omission by reflecting on the different conceptualisations of ‘workforce’ by integrating the diverse and fragmented literature, which has not been done before, and linking it with workforce measurement. in so doing, we provide a more comprehensive understanding of ‘workforce’ and workforce measurement, ensuring alignment with organisational strategy to secure a competitive advantage and, thus, organisational performance. we also propose an integrated framework to measure and manage the workforce. it transpired that of the many tools available, predictive analytics emerged as the most effective means to measure and manage the workforce successfully. our paper benefits both academics and practitioners as theoretical ambiguities and tensions are clarified while ensuring the availability of the requisite workforce. keywords competitive advantage, organisational performance, predictive analytics, strategy, workforce, workforce analytics, workforce intelligence, workforce metrics 1. introduction workforce management, in whatever guise it appears, has emerged as the answer to promote competitive advantage, ensuring sustainable organisational performance (owen 1813; lepak and snell 2002; sirmon et al. 2011; campbell et al. 2012; vaiman et al. 2012; ployhart et al. 2014; teece 2014; wright et al. 2014; collings 2015). in brief, workforce management is generally seen to involve utilising people with the right sets of competence, across occupations and hierarchies, in a particular context, to ensure organisational performance (i.e. goal achievement) both now and in the future. these sets of competence comprise knowledge (tacit and/or explicit; declarative and/or journal of intelligence studies in business vol. 6, no. 1 (2016) pp. 5-20 open access: freely available at: https://ojs.hh.se/ 6 procedural), skills, abilities/capabilities, experience, attitudes/motivations and physical and emotional health. although organisations recognise the importance of workforce management in sustaining organisational performance, their efforts remain ineffective (ashton and morton 2005; lawler 2006; beechler and woodward 2009; harris et al. 2010, 2011; vaiman et al. 2012; boudreau 2013; dries 2013a,b; winkler et al. 2013; bersin et al. 2014; gelens et al. 2014; kinley and ben-hur 2014; phillips and phillips 2014; collings 2015). a range of reasons is advanced for this state of affairs. on the one hand, it is argued that 'workforce,’ especially in the talent guise, and 'organisational performance' lack conceptual clarity, influencing their measurement and consequently their management. this creates a dilemma for organisations when employing and deploying workers to ensure the organisation’s performance. it stands to reason that we can only manage what we can measure, and we can do so only as well as the intelligence derived from the measurement. in addition, workforce management is compounded by challenges such as globalisation, skills shortages and the accompanying war for ‘talent,’ the mobility of workers, changing demographics and the recessionary lay-off of workers, all of which adversely affect access to workers and, thus, organisational performance (axelrod et al. 2001; lepak and snell 2002; ashton and morton 2005; beechler and woodward 2009; farndale et al. 2010; ployhart et al. 2011, 2014; schuler et al. 2011; sirmon et al. 2011; vaiman et al. 2012; thunnissen et al. 2013; collings 2014, 2015; teece 2014; gallardo-gallardo and thunnissen 2016). on the other hand, it is argued that organisations do not use workforce analytics to derive intelligence based on proven measurement tools. this affects effective decision-making to ensure the availability of the required workforce when needed. put differently, organisations generally do not use formal, relevant, business-focused metrics and intelligence to measure the impact of their workforce on goal achievement (i.e. organisational performance). and this is the case, despite the accessibility and demonstrated success of some measurement methods and tools (bersin et al. 2014; boudreau 2010, 2013; collings 2015; harris et al. 2010; harris et al. 2011; kinley and benhur 2014; lawler 2006; phillips and phillips 2014; vaiman et al. 2012; winkler et al. 2013; zula and chermack 2007). it stands to reason that decisions regarding the workforce and their consequent impact on organisational performance are only as good as the intelligence/analytics yielded by the metrics used. we define 'analytics' as the information/intelligence that results from the systematic analysis of the data or statistics collected by the instrument(s) chosen to measure a specific workforce aspect to be managed. to capitalise on the promise of workforce management, researchers call for further research (boudreau 2013; collings 2015; dries 2013a; gelens et al. 2014; lepak and snell 2002; vaiman et al. 2012) towards a finergrained examination (ployhart et al. 2011) of unresolved issues in the literature (wright et al. 2014), while drawing on and (better) integrating various related literatures (thunnissen et al. 2013; vaiman et al. 2012) to more fully understand (collings 2015; thunnissen et al. 2013) and making a lasting contribution to workforce management and measurement (thunissen et al. 2013; vaiman et al. 2012) theory and practice. this paper aims to respond to the above calls and contributes to the debate on this important issue by integrating significant sources from the diverse and large body of management literature on the different workforce guises, specifically (strategic) human capital (resources), talent management; strategic human resource (hr) management; strategy, particularly the resource-based view; engagement; and metrics, while providing top metrics that are used to make informed workforce decisions supporting strategy implementation, competitive advantage and, thus, sustainable organisational performance. the workforce literature centres on people in the organisation and their (collective) contribution to sustainable organisational performance. although progress has been made in this regard (vaiman and collings 2013) there is still room for improvement (boudreau 2013; davenport et al. 2010, dries 2013a, vaiman et al. 2012) because of the incomplete representation, which limits organisational performance. the need to integrate these literatures stems from both theory and practice. the theory indicates ambiguities and tensions (collings 2014, 2015; dries 2013a,b; thunissen et al. 2013; vaiman et al. 2012), while practice indicates that the required workforce is not available when needed, jeopardising the strategy implementation and, 7 consequently, competitive advantage and, ultimately, the sustainable organisational performance (bersin et al. 2014; collings 2015; vaiman et al. 2012). a better integration of views across the literature in explaining phenomena is not uncommon and can, in certain cases, even be desirable (mayer and sparrowe 2013) as it will produce a more holistic understanding of workforce measurement and management, benefitting the practical application of the phenomenon and, ultimately, the competitiveness and sustainability of organisations. thus our paper contributes to the body of knowledge, as it makes a synthesis that has not been made before and thus adds to knowledge (about workforce management and measurement) to support successful strategy execution, and thus organisational performance, in a way that has not previously been done (see phillips and pugh 2015, p. 26). hence, our theoretical paper provides an overview of how to approach this topic strategically, culminating in a framework. the article begins by discussing people and their role in organisational performance. this is followed by a discussion of workforce analytics that can be used to ensure that organisations make sound decisions for unlocking the availability of the right ‘workforce’ when needed. the article concludes with a framework showing how metrics can be used to measure – and hence manage – the workforce to ensure organisational performance. 2. method the basis of this reflection was 86 texts, including peer-reviewed, full-text articles available in english, reporting on people contributing to organisational performance, whether conceptual or empirical in nature, and/or in combination with workforce metrics. these articles were gathered by merging our personal collections of texts on these topics with texts retrieved from a literature search from the web of science and ebscohost limited to the period from 2000 – the year in which the first articles on the ‘war for talent’ appeared – to 2016. search terms used were ‘(strategic) human capital (resources)’; ‘strategic hr management’; ‘talent management’; ‘engagement’; ‘strategic management’; and ‘metrics, intelligence and analytics’. only 17 of these texts specifically addressed workforce measurement in organisational performance, and only to a limited extent (see references). 3. people and their role in organisations the role of people in sustainable organisational performance has been recognised since the early management publications (see owen 1813). people are acknowledged as the most valuable resource of organisations (lewis and heckman 2006) because of their potential to (collectively) drive organisational performance (crook et al. 2011; lockwood 2007; ployhart and moliterno 2011). limited empirical evidence in this regard is available (collings 2015; guest 2011). thus, people have been studied for a number of years from a variety of viewpoints, including (strategic) human capital (resources) (becker 1962; campbell et al. 2012; ployhart et al. 2011; ployhart et al. 2014; wright et al. 2014), strategic hr management (huselid 1995; lepak and snell 2002), talent management (collings 2015; thunnissen et al. 2013; vaiman et al. 2012), engagement (cheese et al. 2008; crook et al. 2011; kahn 1990; macey and schneider 2008; saks 2006) and strategic management (barney 1991; sirmon et al. 2011; teece 2014). in short, these studies have explicitly or implicitly examined the availability of people with the required competence to execute organisational strategy successfully from an hr perspective or, to a limited extent, in combination with (business) strategy. these studies were largely developed in parallel and do not incorporate engagement and/or workforce measurement to enable management to make evidenced-based decisions on the availability of people with the required competence in support of its strategy execution. organisational performance stems from the competence people bring to the organisation, which should be aligned with the (common) purpose and goals of the organisation to support successful strategy implementation (boxall 2013; campbell et al. 2012; collings 2014; ployhart et al. 2011; ployhart et al. 2014; thunnissen et al. 2013; wright et al. 2014). it should be noted that competence is not fixed or static and may change owing to changes in the workplace and/or environment (bartlett and ghoshal 2002; campbell et al. 2012; collings 2015; lewis 2011; lockwood 2007). it can therefore affect successful strategy implementation and, consequently, goal achievement, otherwise known as organisational performance. moreover, competence by itself does not achieve organisational goals. the worker embodying 8 the competence must be ‘available’ to dispense the competence in pursuit of organisational goals (wright and mcmahan 2011). availability depends on both the worker and the employer (see blumberg and pringle 1982; boxall 2013) and needs elaboration as it entails more than the mere physical presence of the essential number of persons embodying the requisite competence. availability also means that the employee must be able and willing to expend the embodied competence in pursuit of organisational goals. this ability and willingness to act depends on a host of factors, including whether the person has the physical and mental health and the opportunity to dispense his/her competence. we interpret the drivers of engagement identified by cheese et al. (2008) as the availability of people to act in pursuit of organisational goals, which we will briefly elaborate on. opportunity may include being deployed in the correct position, which includes the physical, cognitive and emotional demands that the job makes on the worker, the sense of achievement that the job offers, the opportunity to learn or discover new things, and whether it is meaningful and leads to some form of satisfaction. opportunity is furthermore influenced by whether the worker has been given the means to handle the job and whether his/her goals are achievable. handling the job involves knowledge, skills, technology, accurate and timely available information, systems, processes, training, a favourable working environment, supportive managers and colleagues, work practices that reduce effort rather than adding to it, reasonable workloads and health. furthermore, the worker must perceive that he/she is receiving fair financial compensation and is recognised for his/her contribution to organisational performance. in the main, being fairly compensated is a feeling of being equitably rewarded for his/her contribution and understanding how this is evaluated; he/she must thus experience the process as fair. compensation that is reasonably marketrelated signals recognition. moreover, the worker must experience a sense of community, that is, there should be a feeling of positive social interactions in the workplace. the work should be perceived as fulfilling, meaningful, enjoyable, fun and done in a supportive or collaborative environment, rather than a confrontational environment. in addition, the employee must perceive congruence, which consists of agreement between the individual and organisational values and alignment of expectations and values that have been met. workers must also perceive an alignment between their career and life expectations and aspirations over both the short and the long term, including work–life balance. they must also perceive whether the organisation is investing in them and whether they can shape their own destiny. based on these drivers of engagement, workers then choose to engage themselves (more or less) in pursuit of organisational goals via strategy implementation. the level of worker engagement is, in turn, influenced by, inter alia, the conceptualisation of the workforce, which is the key to strategy implementation. 4. workforce and strategy implementation strategy is a ‘potentially powerful tool to cope with change, but a somewhat elusive concept’ (ansoff and mcdonnell 1990). simply put, strategy is the tool management uses to achieve organisational goals and, in so doing, secure organisational performance (andrews 1987; ansoff 1988; drucker 1954; grant 2016; nilsson and ellström 2012; ployhart et al. 2014; porter 1985, 1998). it is common practice to express goal achievement in financial terms (drucker 1954; nag et al. 2007; nilsson and ellström 2012), the ultimate litmus test for long-term sustainability. this, however, may deflect attention from non-financial measures, whether employee, customer or social good (andrews 1987; boxall and purcell 2011; collings 2014). this observation resonates with the purpose of an organisation, namely to deliver products/services that are valued by its customers, provide employment and contribute to wealth creation (drucker 1954; teece 2014). wealth creation is a broader concept than profit maximisation, involving more stakeholders than only shareholders. moreover, profit maximisation does not necessarily equate with efficacy and, on its own, is not sufficient for organisational sustainability (teece 2014). additionally, there is more to employment than meets the eye. because workers are not inanimate resources, they think about their work and how they contribute to goal achievement (griseri 2013; rothbard 2001; wright and mcmahan 2011). thus, workers are not merely vessels embodying competence, but actively assess (cognitively and affectively) how they contribute to organisational performance in 9 discharging their duties (fearon et al. 2013; kahn 1990; rothbard 2001). as such, workers ‘do’ strategy when discharging their duties in pursuit of organisational goals (jarzabkowski and spee 2009). hence, workers and, in particular, their competence, in concert with other resources, are key in shaping a competitive advantage (heinen and o’neill 2004; campbell et al. 2012; collings 2014; pease et al. 2014). other resources include assets, systems, processes, information, firm attributes, technology and the like. the resource configuration enables the organisation to conceive and implement strategies that improve its efficacy (see barney 1991; cheese et al. 2008; lepak and snell 2002; ployhart et al. 2014; teece 2014; sirmon et al. 2011; wright et al. 2014) in creating value for customers in the arenas where the organisation chooses to compete. according to barney (1991), resources can be classified in three categories: (i) physical capital resources; (ii) human capital resources; and (iii) organisational capital resources, though not all of these have (the same) strategic relevance for the organisation. yet all resources are required in differing degrees to compete successfully (lepak and snell 2002; ployhart et al. 2014; sirmon et al. 2011; teece 2014). the workforce must be prepared to expend their competence (available) (wright and mcmahan 2011), individually and/or especially collectively, to ensure a competitive advantage, as was discussed previously. management plays an important role by creating an environment in which people will be available, as well as combining accessible resources to shape a competitive advantage (campbell et al. 2012; lepak and snell 2002; ployhart and moliterno 2011; sirmon et al. 2011; teece 2014). 5. competitive advantage competitive advantage, the hallmark of an effective strategy (barney 1991; campbell et al. ployhart et al. 2014; porter 1985; 1998), means the organisation does something better than the competition. it attracts customers based on value offered (peteraf and barney 2003; porter 1985, 1998) by combining the resources at its disposal (huselid 1995; ployhart et al. 2014; ployhart and moliterno 2011; sirmon et al. 2011; teece 2014) to leverage their benefit for sustainable organisational performance. this description of competitive advantage shows that it is linked to the resource-based view of the firm. barney (1991, pp.106-111) describes competitive advantage in terms of the characteristics of resources, namely valuable, rare, inimitable and non-substitutable: ‘resources can be valuable only to the degree that they enable an organisation to conceive of or implement strategies that improve its efficacy. resources are rare when they are not abundantly available to competitors to implement a value-creating strategy. valuable and rare resources can only create and sustain a competitive advantage if they cannot be obtained by competitors and thus are imperfectly inimitable. non-substitutability means that there must be no strategically equivalent valuable resources that are themselves either not rare or inimitable.’ thus, competitive advantage is deemed to be embedded in the organisation, and resources play a key role. of all the resources, the workforce is the most important. 6. workforce management and challenges hence, for some authors, competitive advantage is achieved by a few key positions (huselid 1995; whelan and carcary 2011) and/or top performers (axelrod et al. 2001; gelens et al. 2013; vaiman et al. 2012) in the organisation creating an advantage over rivals. in some instances, authors refer to these performers as ‘talent.’ the debate about ‘talent’ covers the following, either as opposing positions or in some combination: whether it is subject (person) or object (competence); exclusive (a gifted few akin to top performers) or inclusive (all people but to differing degrees); unique (company-specific) or generic (applicable to a variety of contexts); and whether competence is innate (a predetermined and fixed capacity) or malleable (can be developed) (becker 1962; boudreau 2013; campbell et al. 2012; dries 2013a,b; farndale et al. 2010; lepak and snell 2002; ployhart et al. 2011; ployhart et al. 2014; schuler et al. 2011; tansley 2011; teece 2014). given the dynamic nature of relationships, the contribution of individuals to organisational performance is greater than merely aggregating individual actions (boxall and purcell 2011; campbell et al. 2012; lepak and snell 2002; pfeffer 2001; ployhart et al. 2011; ployhart and moliterno 2011; pugh and dietz 10 2008; sirmon et al. 2011; teece 2014; wright and mcmahan 2011). hence, the notion that collaboration creates synergy emphasises that competitive advantage cannot be achieved by a position or person or competence acting on its own. some combination is necessary, as shown by, inter alia, boxall and purcell (2011), campbell et al. (2012), lepak and snell (2002), pfeffer (2001), ployhart et al. (2011), ployhart and moliterno (2011), pugh and dietz (2008), sirmon et al. (2011), teece (2014) and wright and mcmahan (2011). thus the view taken on the workforce influences its management, which depends, inter alia, on its consequent measurement, including investing in the development of availability of a future workforce, in particular making decisions about the workers in pursuing organisational performance. moreover, the decisions about having the right workforce available to shape competitive advantage are influenced by a myriad of factors, notably globalisation, global skills shortages, the mobility of skilled people and changing demographics, as mentioned earlier (beechler and woodward 2009; farndale et al. 2010; holtom et al. 2008; nilsson and elstrom 2012; schuler et al. 2011; vaiman et al. 2012). of these factors influencing the availability of the right workforce, skills shortages, of which analytics, are the most important (boudreau 2013; harris et al. 2010; harris et al. 2011; kinley and ben-hur 2014; lawler 2006; phillips and phillips 2014; winkler et al. 2013). moreover, workers can voluntarily relocate (holtom et al. 2008), which is influenced by many factors and can be synthesised as ‘inducements and contributions’ (see march and simon 1958; holtom et al. 2008). the reasons most often advanced for voluntary turnover are improved career opportunities and enhanced work–life balance, suggesting that available workers are not properly utilised, thus affecting availability. to capitalise on the workforce and their contribution to competitive advantage, employers – and particularly line managers – should create an environment in which people feel motivated to expend their ability when given the opportunity to do so. workforce metrics and, in particular, the intelligence gained from analytics play an important role in making sound decisions on the utilisation of workers and their competence, as well as developing competence (boudreau 2010, 2013; davenport et al. 2010; harris et al. 2010; harris et al. 2011; kinley and ben-hur 2014; phillips and phillips 2014) to shape competitive advantage and, thus, organisational performance. hence, in considering the workforce and their contribution to organisational performance, attention should be given to the purpose of the organisation and the goals it pursues; strategy, and specifically competitive advantage on which strategy is based; and particularly people – in terms of numbers required, the competence needed, occupations and hierarchies affected, other resources needed to assist the workforce to discharge their duties in pursuing organisational goals; and the configuration of the people and other resources needed to achieve organisational goals, which are influenced by the environment in which the firm operates. these considerations are relevant in introducing or changing workforce metrics to gauge the impact of the workforce on goal achievement (performance). as such, these considerations are variables forming the basis of the framework we propose, which is illustrated in figure 1. workforce metrics can be used to assess one or more of the components in figure 1. depending on the component to be measured, an appropriate metric/metrics must be selected to collect data that will yield the information and intelligence, on analysis, to make relevant decisions. such decisions can then be assessed for their impact. 7. workforce analytics while hr metrics, human capital metrics, talent analytics, hr scorecards and the hr information system (hris) are valuable for workforce management, it is suggested that there are differences in approaches (khatri 2014, p.2). human resource metrics and human capital metrics are qualitative in nature. human resource metrics focus on the figure 1 workforce and their contribution to organisational performance. 11 efficacy of the role, purpose and accomplishments of the human resources function. human capital metrics inherently focus on employees’ expressing their skills, knowledge and ability, and attempt to explain employees’ contribution to organisational performance. hr scorecards, on the other hand, assist managers to determine what the hr department’s worth is and they attempt to aid in hr measurements. hence, hr scorecards focus more on the strategic requirements of the organisation. there are various hris software programs for managing hr activities. it has become important for organisations to examine the effects of their investment in their workforce on the returns that they gain from such investments (zula and chermack 2007) in terms of organisational performance. hence, organisations need to re-examine their workforce planning processes regularly. this will ensure that they are aligned with the objectives and initiatives of the organisation and applied appropriately so that resources are allocated to support strategy execution and thus enhance the achievement of organisational goals. regular re-examination can benefit organisations by providing evidence of their workforce configuration and can help them to measure and plan for the correct development, allocation and alignment of people so that the organisation can sustain a competitive advantage. when workforce practices and processes are strategically managed, organisations can gain a competitive advantage by utilising their greatest assets, namely their people (lawson and hepp 2005). zula and chermack (2007) caution that when managing the workforce of the organisation, it is important to take note of the metrics adopted to determine if the endeavour is a success. the use of inaccurate or inappropriate metrics may result in incorrect measurements, or even in measuring the wrong thing, thus adversely affecting competitive advantage. typically, the metrics used to measure workforce practices include numbers and costs related to the hiring, training, time to deliver services, ratios of people to budgets and benchmarks (fitz-enz 2009). since these measurements focus mainly on those activities that cost the organisation money and do not provide much relevant information on the value-adding aspects of the people’s performance in the organisation, they do not excite management. pease et al. (2013) concur with this view and indicate that most data collected in organisations mainly focus on the past, including records of sales, expenses, productivity and past performance data that cannot be managed any longer or make a difference to the current situation in the organisations. hence, it has been suggested that measurements are needed on leading-edge indicators such as leadership, engagement, readiness, culture and retention. such information can provide management with clues about the future of the organisation. for instance, engagement surveys have become prominent tools, as reflected in the bain & co survey (see rigby 2015). the latest and more advanced forms of metrics are leading indicators and intangible metrics that are able to predict what is more likely to happen to the workforce. these metrics offer a much higher level of analysis and can address issues that have an effect on the current organisational operations, instead of focusing on past events. this type of metrics is proving more beneficial to organisations and has been reported to attract the attention of management (fitz-enz 2009). with the turbulence in the 21st century economic and business environments globally, most managers want to be forewarned about what is going to happen in the future so that they can make sound investment decisions regarding workforce measurement and management. 8. predictive analytics to deal with the challenges that contemporary workforce changes present in organisations, more powerful means of planning and deploying appropriate development and training of people will be needed. predictive analytics is emerging as a game-changer in current business environments (pease et al. 2014). predictive analytics has been defined as the use of quantitative methods to extract insight from data and then using these insights to assist organisations to make informed decisions and to forecast and improve their final business performance (pease et al. 2014). khatri (2014) indicates that it is a valuable tool for employees’ career planning and the organisation’s strategic planning. predictive analytics can also be used for assessing employees’ training needs, as already discussed. with reference to the white paper on predictive analytics, dey and de (2015) state: 12 ‘several organizations have proactively adopted predictive analytics for their business functions such as finance and risk, customer relationship management, marketing and sales, and manufacturing and it enables them to make informed decisions across a range of activities such as customer retention, sales forecasting, insurance pricing, campaign management, supply chain optimization, credit scoring, and market research.’ furthermore, several new opportunities are offered by predictive analytics that are useful for all the core workforce processes, such as competence acquisition, attrition risk management, employee sentiment analysis and capacity planning. predictive analytics can be applied to workforce learning initiatives to improve the impact of the learning and development initiatives offered in the organisation, thereby shaping competence. it gives the organisation insight into the types of employees that can benefit from the learning initiatives and those that will receive very little or no benefit at all. in this way, employees can be selected that will benefit from the learning initiatives, increasing the impact of their performance in the organisation. organisations can then provide for those employees who would otherwise gain little or no benefit from training, saving costs by investing in suitable learning initiatives that will affect all employees, improving their performance and ability to execute the organisation’s strategy and achieving organisational goals, thereby sustaining organisational performance. it has also been suggested that the best workforce metric for an organisation is the long-term performance of the organisation, which is influenced by leadership and management. investing in people is not new. organisations have anecdotally been using onboarding, skills training and development programmes for a long time now (pease et al. 2014). however, these initiatives have not been able to indicate exactly where and how they are of value and benefit to workers or the organisation. by applying predictive analytics to these learning investments, both the organisation and workers can benefit. the organisation benefits by reducing its expenditure on training for workers that will not benefit, while improving their performance. furthermore, it can focus on improving other business metrics. workers benefit because they attend training and development that can actually help them to improve their performance and that is worthwhile for their specific operations. in turn, appropriate training can contribute to their increased engagement and retention in the organisation (pease et al. 2014). this is in line with the findings of becker (1962), lepak and snell (2002), sirmon et al. (2011) and teece (2014). predictive analytics uses scientific data as evidence for planning, developing and deploying learning and development programmes for workers. 9. reasons for using predictive analytics for workforce management we agree with pfeffer (2009, cited in fitz-enz 2009), who stated: ‘if competitive success is achieved through people – if the workforce is indeed an increasingly important source of competitive advantage, then it is important to build a workforce that has the ability to achieve competitive success that cannot be readily duplicated by others’. pfeffer’s statement resonates with the research of barney (1991), campbell et al. (2012), collings (2014), lepak and snell (2002), ployhart et al. (2011), ployhart et al. (2014), sirmon et al. (2011), vaiman et al. (2012) and wright et al. (2014). according to a 2013 global study by the american management association and the institute for corporate productivity (cited by reilly 2014): ‘58 percent of business leaders indicated that they believe that analytics is a vital part of their organisation today, while 82 percent of business leaders indicated that they expect analytics to be a big part of their organisation in five years’. sullivan (2014) concurs with this and indicates that the traditional metrics used in workforce measurement have a very limited impact since they are backward-looking and focus on the past. predictive analytics is regarded as offering higher value and quality for organisations, as it focuses on analysing past and current data. it looks for patterns and trends that can assist managers to predict possible future people problems, as well as emerging opportunities that they can capitalise 13 on. the global human capital trends report (bersin et al. 2014:117) also found that 78 percent of large organisations that have over 10 000 people in their employ realise that workforce, and specifically competence, analytics is ‘urgent’ and ‘important.’ hence they have placed analytics as one of the top three most urgent trends for workforce management in the 21st century. the report also purports that organisations that make use of analytics successfully to manage their workforce are in a much better position to outperform their peers and competitors as far as the implementation of workforce configuration strategies is concerned. workforce analytics, in particular, is able to provide a significant combination of workplace data and business data that can assist workforce managers to make more informed and appropriate decisions about their people for the sake of sustainability. sullivan (2014) indicates, inter alia, the following reasons why hr (and line) managers need to use predictive analytics for workforce management: § it engenders a forward-looking mindset and routinely making informed decisions based on evidence about what the future will hold for the organisation. § it alerts managers well in advance to emergent problems and challenges so that they can prepare for their effects and minimise any damage. § it allows managers to act strategically, ensuring that their hr plans are integrated into the organisation’s strategic business plans. § the root cause of problems can be easily identified with predictive analytics, allowing talent managers to devise appropriate solutions that solve the exact problems instead of alleviating the symptoms. § since predictive analytics is specifically designed to increase some form of execution to solve or enhance a situation, hr managers have a more positive attitude to accepting and reading the analysis. it also provides in-depth information, such as the estimated costs of future problems and their effects, as well as the cost to the organisation if no action is taken to improve the situation. it furthermore helps managers to prioritise problems that need immediate intervention in support of business priorities. § because predictive analytics is comprehensive, more integrated and usually available in an electronic form, it can provide answers to decision-makers’ enquiries in a timely and consistent manner that other forms of workforce metrics usually lack. § this form of analytics allows management to develop several scenarios or models for a specific problem situation, to pretest the decision that they want to make, see its effects and, where possible, make adjustments before implementing it in the organisation. § predictive analytics allows the organisation to gain a far better workforce and competitive advantage, as compared to those competitors that do not implement predictive analytics to assist them in decision-making. 10. the future of predictive analytics for workforce management to enable an organisation to leverage predictive analytics and obtain maximum benefits from the workforce data that it produces, it is essential to link these data sources to its strategic business outcomes, that is, it should be results-driven, as already pointed out. predictive analytics can be used in workforce management in the following areas, as identified by dey and de (2015): 10.1 employee profiling and segmentation predictive analytics can benefit workforce management by profiling and segmenting employees, helping managers to get a better understanding of their workforce and their contribution to organisational performance. workforce data such as demographics, skills, educational background, experience and designation can be combined with information on roles and responsibilities to create segments that can be used to effectively deploy people. this is congruent with boudreau (2010) and lepak and snell (2002), who claim that the workforce will feel a higher degree of satisfaction in their jobs and their relationship with their employer will improve drastically if they are selected to attend relevant programmes that are going to benefit them the most, contributing to their availability to pursue organisational performance. this 14 analytic forms the basis of workforce planning and engagement surveys, to mention a few. 10.2 employee attrition and loyalty analysis predictive models of attrition can be used to measure the attrition risk score of individual employees. in this way, the organisation can prevent the potential attrition of their workforce that forms part of its competitive configuration. workforce demographic data, performance, compensation and benefits data, market data, rewards and recognition data, training data, behavioural data and workforce survey scores can be used for this analysis. this metric contributes to workforce planning, employee satisfaction and commitment measurements. this analytic will ensure that organisations have the required workforce available at all times. 10.3 forecasting of workforce capacity and recruitment needs organisations are in a better position to optimise resource utilisation and sustain appropriate growth and margins when they are able to predict the requirements for workforce capacity and recruitment. accurate forecasting enables managers to determine their future staffing requirements. factors such as attrition risk scores, business growth forecast and pipelines, number of employees and competence in each department, productivity level and past performance of each employee can be incorporated to enrich the predictive models. again, this analytic equips organisations to be in a better position to do workforce planning. table 1 top five workforce management analytical tools. analytical tool purpose of the tool total cost of workforce this tool is used on a macro level to measure the alignment of the workforce (e.g. competence, ‘availability’ and configuration) with the objectives of the business in support of strategy implementation and to make better strategic decisions in terms of workforce management. this tool can be used effectively in combination with workforce planning, in particular, because it also helps managers to link investments in the workforce to the organisation’s results. management span of control management span of control is regarded as the best tool to measure cost and structure of management staff in an organisation. it is used to assist organisations to capitalise on productivity and efficiency and can evaluate the entire organisation or specific divisions or business units in relation to business results. this tool is useful because it connects well to workforce planning, as the objectives can be displayed on a real-time basis. high-performer turnover rate this tool helps the organisation to see how many employees providing a competitive edge it has lost over time; to some extent, this tool is predictive in that it also indicates the value of the loss of these employees over a period of time. it also provides clues as to how productive the workforce is, which can be linked to business results. career path ratio this tool provides two important measures that reflect the mobility of employees, namely total promotions and total transfers. this measures career path mobility and any internal movement of employees. this metric can be used in combination with employee retention and performance metrics, they are also able to provide valuable links to critical workforce issues, particularly productivity and organisational performance. talent management index this index helps an organisation to evaluate and analyse its talent management practices for recruiting, mobility, managing performance, training and development. the above metrics can all be linked to this metric in order to ensure that the organisation’s workforce is properly measured and, thus, managed. this metric can therefore be regarded as an overarching or holistic tool to manage the workforce. 15 10.4 appropriate recruitment profile selection attrition of employees in specific roles that entail high costs of hiring can lead to significant losses for the organisation. dey and de (2015) indicate that ‘by analysing the data for current employees, including performance and productivity indices, attrition details, and life-time value’, the talent manager will be in a position to create the right profile for each potential employee. moreover, a statistical relationship can be identified between employee value and profile variables such as education and experience. this will then assist managers to identify the most suitable profiles for their organisation. the organisation can then increase the quality, productivity and customer satisfaction scores, while at the same time reducing its recruitment cost and creating sustainable value for the organisation where the strategy can be achieved, thus feeding directly into workforce management. 10.5 employee sentiment analysis it has been suggested that ‘employee sentiment analysis is more effective than annual employee surveys in getting honest, useful feedback’. employee sentiment analysis involves the tracking, analysing and dissecting of key issues regarded as the most relevant to employee sentiments over time, or that can be related to a specific real-time issue. managers then obtain a better understanding of how an hr initiative, policy, organisational change or event is being received by employees at that specific time. internal data related to the respective hr initiatives or changes, together with data from external social media such as facebook, twitter and linkedin, can be used for this analysis, thereby providing the organisation with a clear understanding of the impact that various organisational factors have on productivity, business growth or other objectives. this directly promotes proper workforce management. 10.6 employee fraud risk management predictive analytics can be used by organisations to identify employees who are at high risk of non-compliance with the organisation's security policy or other rules and regulations. the organisation can strengthen its internal fraud risk management by analysing the employee activity data and incident data, using statistical modelling techniques, and then creating a fraud risk score for employees so that appropriate proactive steps can be taken to protect the organisation’s brand image and reputation and prevent possible financial losses. this metric demonstrates a link to workforce management. it may be necessary for hr managers, in particular, as they drive workforce-related issues, to collaborate with other business units in their organisations that are already using predictive analytics to get a better understanding of how to use this measurement tool. the correct application of predictive analytics can transform workforce management from a reactive to a proactive process. it will provide accurate early warnings that can support strategy more comprehensively and help the organisation to sustain itself in the long term. furthermore, the organisation will be in a better position to solve its business problems and reduce its costs, at the same time improving business performance, employee engagement and satisfaction. if this is accomplished, organisations will be able to prove that the ‘generally acceptable idea that organisations can create a competitive advantage from their workforce and their management practices, as reported by shrimali and gidwani (2012)’ is indeed a reality. in sum, predictive analytics can give effect to the ideas proposed by barney (1991), becker (1962), campbell et al. (2012), cheese et al. (2008), collings (2015), huselid (1995), becker and huselid (2006), kahn (1990), lepak and snell (2002), macey and schneider (2008), ployhart et al. (2011), ployhart et al. (2014), saks (2006), sirmon et al. (2011), teece (2014), vaiman et al., (2012) and wright et al. (2014). moreover, this observation corroborates boudreau’s (2010) observation that hr metrics needs retooling. to assist practitioners in applying predictive analytics, we present the top five workforce analytical tools next. 11. top five workforce management analytical tools for the 21st century predictive analytics, workforce analytics or even ‘people analytics’, as it is more commonly referred to by hr managers, has been used extensively by organisations such as humanyze, which assists managers to ‘find surprising and unsuspecting connections and insights in data about what its most effective employees do differently’ (kane 2015). the ceo of humanyze, ben waber, is of the 16 opinion that people analytics can assist managers to gain a better understanding of patterns that are usually hidden about why some employees are more successful at the jobs that they do than others. in this case, the analytics enable managers to read employees in the same way that they usually read statistics. the saba white paper (2014) confirms that most of the world’s advanced organisations use human capital metrics and analytical tools for managing their workforce. these tools provide managers with a more visual understanding of their workforce and enable evidence-based decision-making. the top five practical analytical tools for human capital and workforce management have been identified by saba (2014) and are indicated in table 1. these tools can assist firms to identify and prioritise key questions about their workforce, especially the individuals who give them a competitive edge. these include identifying and quantifying the (strategic) competencies of people, who constitute the most important resource of the organisation, together with other resources, particularly information and technology, which enable the organisation to implement its strategy successfully. moreover, these metrics can also show how the performance of the workforce, in concert, helps to enhance these capabilities, resulting in effective strategy implementation, as discussed in this article. in summary, we provide an integrated workforce management framework in figure 2. 12. conclusions for organisations to remain competitive, they should use workforce analytics effectively, particularly predictive analytics, derived from proven metrics suited to their context. these tools will allow the organisation to make informed decisions about workforce measurement and management and its availability in support of strategy figure 2 integrated framework to measure and manage the workforce. 17 implementation, thus securing organisational sustainability. organisations that are successful at leveraging this form of datadriven decision-making will most certainly position themselves to outsmart their competitors and sustain a competitive advantage. at the same time, they will sustain a higher return and value to all stakeholders and society at large, and they will be able to better position themselves for the challenging business world of today, as well as the business demands of the future. 13. theoretical and practical implications this theoretical article demonstrates that investments in the workforce – whether employment, deployment or training and development – contribute to organisational performance. in this regard, an integrated approach should be followed, starting with a consideration of the purpose and goals of the organisation and the strategy employed to pursue those goals. more particularly, attention should be given to the competitive advantage on which strategy is based, particularly people, in terms of numbers required, the competence needed, and occupations and hierarchies affected. in addition, other resources needed to assist the workforce to successfully discharge their duties in pursuing organisational goals, as well as the configuration of the people and other resources needed to achieve organisational goals, should be considered. moreover, the environment in which the organisation operates, which influences organisational performance, should be considered. it is imperative that managers (whether hr or line) focus on results rather than inputs to ensure the analytics are forward-looking rather than backward-looking and provide relevant workforce data per ‘segment’ (like the quadrants suggested by lepak and snell 2002) – indicating future needs, including training and development per segment. 14. contribution the suggested conceptual framework is theoretical and requires empirical testing. it serves as an outline for future research that can be used universally by researchers. 15. future research given that limited empirical evidence is available on the use of predictive analytics in the workforce, we suggest a practical investigation of how organisations (i) conceptualise their workforce; 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schilke, 2014; kahupi et al., 2021) by for example achieving cost leadership or being differentiated in what it offers, or having developed a strategy that is value-creating and not being implemented by competitors (barney, 1991). according to nevo and wade (2010) and chatterjee (2021) value refers to the ability of exploiting market opportunities; rarity refers to competitors; inimitability relates to the costs non-substitutability refers to the nonexistence of equivalent resources. among the characteristics of a competitive environment are spread of novel technologies, quicker obsolescence or products and changes in customers’ needs 45 (knudsen et al., 2021). managers also noticed tions is their human resources. therefore, organizations must provide a continuous stream of novel and innovative products and expand their markets in order to maintain their success which necessitates organizational learning (gomes and wojahn, 2017). novel organizational approaches consider learning to be an organizational culture and seek to integrate personal, group and organizational learning. in this approach, in order to pay attention to external challenges and proper use of opportunities, an organization needs certain internal abilities and capabilities that use different styles of learning to acquire novel ideals from organization’s environment and institutionalize these ideas in the organization (ashton and thorn, 2007). the concept of organizational learning capability emphasizes the importance of factors facilitating learning or trend toward learning in the organization (kalmuk and acar, 2015). in fact, organizational learning capability shows the capacity for creating and implementation of ideas in order to deal with various organizational barriers using innovations and management methods (nwankpa and roumani, 2014). organizational learning alone is not enough, but its ultimate goal of improving performance and gaining, maintaining and enhancing competitive advantage must be achieved. organizational learning is an important and vital component for innovation through which a new product is developed (sutanto, 2017). before an organization can improve its innovation behavior, management must analyze the learning that is common in the organization (petra et al., 2002). in fact, organizational learning has become an important strategy to create competitive advantage in considered valuable resources for the organization (saro, 2007). organizational learning can also help the organization to achieve its vision and performance goals (gah, 2003). therefore, it is important to pay attention to the concept of learning and measure its capability in is possible by acquiring knowledge from various sources and applying it in the organization. organizations therefore seek to enhance the performance of innovation by improving their knowledge base, by adapting to customer needs, and by rapid learning (gilbert et al., product development processes, the ability to acquire existing knowledge and competencies, and knowledge development, i.e. the concepts that underlie organizational learning capability. based on this, it can be said that organizational learning is an important factor that can lead to the success of a new product (callanton, 2002). organizations must cope with an increasingly changing environment. such a change derives essentially from the evolution and changes in customers’ needs, technological advances to satisfy those needs and the evolution in business management (lee et al., 2013). therefore, the business ability to build and defend a competitive position in the market depends to a great extent on the capacity to invest and use information (weber and kantamneni, 2002; mithas and rust, 2016). in this regard we can consider information technology to be a key factor for the organization’s success. the literature considers information technologies to be an important source of competitive advantages for the company (gil-saura et al., 2009; amuna, 2017). ict industry plays an essential role in most countries (ministry and pitner 2014; talib ict manufacturing and ict service. in both may emerge and provide products and services with new functions and values. unlike other industries, ict-based industries show the most diverse characteristics of convergence (an et al. 2016). ict industry leads to sustainable national competitiveness because it creates greater linkage effects than any other industry and accelerates innovation in related sectors (xing et al. a pivotal role in increasing the productivity of the entire economy (asikainen and mangiarotti 2017). given that the automobile industry has a vital role in the economic development of a country and is considered as one of its economic infrastructures, iran also seeks to become strong in this industry. given that automobile industry in iran is developing, this industry seeks to increase its market share, especially in the middle east, by launching new products. in this regard, paying attention to factors such as vision and competitive advantage in new products can lead to the growth of this indusin iran has been studied. on the other hand, so far no research has been done on the role of information and communication technology and organizational learning capability in improving the new product vision and competthis gap. accordingly, the purpose of this study is to investigate the effect of information and 46 communication technology on the new product competitive advantage and new product vision by considering the partial mediating role of organizational learning capability. the results of present research can help government or managers and contribute to future relevant researches. 2. literature review 2.1 information and communication technology at the start of the millennium, information and communication technology has affected the entire world and has changed the foundations of many systems (jerez-gomez, céspedessocieties” (sar and misra, 2020). the ict also stimulates initiative and creativity (chai, koh, and tsai, 2010; ómez mediavilla, 2021), enables individualization and makes knowledge acquisition more accesicts are an important part of every country’s national infrastructure. technological readiness refers to the speed with which an economy utilizes existing technologies to improve the productivity of its industries, with speactivities and production processes to achieve (salehan, kim and lee, 2018). ict profoundly affects economic and social development (wang, communication technology in many aspects of human life had turned the world into what is known as an information society. the rapid emergence of modern ict has substantially changed the type of skills that are needed to successfully participate, communicate, and work in a modern society (gnambs, 2021). today, access to internet and other information sources is increasing exponentially and all societies try to use these new technologies by creating the necessary infrastructures. icts may have promoted and advanced an individual’s (and a community’s) radicalization process (parra, gupta, and mikalef, 2021). the application of ict across different sectors of the global economy has become a game changer (ayisi nyarko and kozári, 2021). all experts and policy-makers state that information and communication technology creates great potendevelopment. to this end, many countries have information and communication technologies many nations consider ict to be a strategic tool for improving welfare, wealth, equity and better access to information are considered to be wealthier. this means that today, the main power of countries is not based on polluting factories or destructive war machines but instead based on having access to more information in a timely manner (pelgrum, 2001). in fact, ict emphasizes the role of information and information processing, storage, transfer and retrieval facilities. it is worthy to note that other than communicative infrastructure, other forms of media such as radio and television also play important roles as information transfer channels (colecchia and schreyer, the set of tools, machines, know-how, methods and skills used in creating, trading, processing, retrieval, transfer and use of information and includes all levels of information processes from simplest to the most complex (akshay and dhirubhai, 2005). in general, ict is the use of information management tools services used for creating, processing, storage, distribution and transfer of information (rama rao, 2004). studies show that one of the factors separating organizations from each other is information technology and the extent of its use in them. many factors affect the use of ict in organizations (alexandru, 2006) some of which are investigated in this study which include the folmirghani et al., 2010); attitude factors (alam beigi et al., 2009; mooij and smeets, 2005); training factors (alam beigi et al., 2009); 2009); environmental factors (khuong, 2008); et al., 2015). 2.2 organizational learning capability organizational learning is a process through which organizations learn new information. according to experts, organizational learning is an essential process for every organization in today’s competitive environment and is the sum of all organizational and management characteristics that facilitates learning in 47 2015; sutanto, 2017). many experts state that there is no consensus about measures of organizational learning; this is mostly due to the fact that organizational learning is the result of several stages, each with its own measures of success (birchall and giambona, 2010). the concept of organizational learning emphasizes the importance of factors facilitating the natural inclination or tendency of the organization toward learning (goh, 2003; nwankpa and roumani, 2014). an organization’s learning capacity is one of its organizational and mantions in which it is possible for the organization to learn (alam beigi et al., 2009). it can be said that factors facilitating learning in an organization are the same as measures of its learning capacity. the learning capacity of an organization is the result of individual and group learning in the organization, carried out in management actions or conditions can facilitate or hinder this process. therefore, if one can determine the management actions that facilitate learning (nwankpa and roumani, 2014), then it is possible to measure the organization’s learning capacity. this information can help managers focus on efforts that facilitate organizational learning (chiva, alegre and lapiedra, 2007). organization’s learning capacity is the intrinsic ability of the organization in creating, developing and use of new knowledge in order to compete with its compet2005). in order to create the capacity to learn in an organization it is necessary to have an effective innovation process through activities such as experimentation, constant improvement, team work and group problem solving, observing the activities of other employees and participatory decision-making (goh, 2003). in his study, chiva (2004) tried to determine the factors facilitating organizational learning. in this later work, chiva et al. (2007) developed their measurement tool for organizational learning capacity and determined that organizational learning has several dimensions including 1-experimentation, 2-rrisk-taking cabrera, 2005), 3-interaction with external environment (chiva, alegre and lapiedra, 2007), 4-dialogue (chiva, alegre and lapiedra, 2007) and 5-participatory decision-making (bapuji and grossan, 2007; scatt-ladd and chan, 2004). 2.3 new product competitive advantage a pivotal determinant to its performance and survival(barnett & mckendrick, 2004; barney, and sustain competitive advantage is the funmust consider decisive factors that may enable in terms of product image, sales, market share, and new market opportunities (liao, kuo, and ding, 2017). according to the resource-based tage is attributable to the valuable and rare resources that it currently possesses (cao et al., tage provided that the resources are non-tradable or imitated barney, 1991; barney and clark, 2007; chadwick et al., 2015). globalization of markets, development of dynamic technologies, shortening of product life cycle and rapid changes in customer demands; all of this means that companies’ competitiveness strongly depends on their ability to meet customer demands and needs by creating more value in products and services. these forces companies to upgrade their ability and capacity to create and deliver value to stakeholders, especially customers. in dynamic global markets, companies face varying degrees of competition. rapid technological changes, shortening the product life cycle, and the increasing complexity of technology have forced companies to outsource their technical development (banrent and tishirki, 2004). in a product development environment with new to complexity and uncertainty. competitive advantage includes strategies that companies use to perform better than competitors in product markets. the environmental competitive advantage can be further categorized into cost and differentiation advantage (lópez-gamero et al., 2016; miotto et al., 2020). organizations can gain competitive advantage if they can create value for customers. launching new products is one of the strategic sources of value creation (miles and covin, 2000; walsh and dodds, 2017). so the competitive advantage of a new product is actually the advantage that the new product has over the competitors’ products. competitive advantage requires companies to have particular control over production costs to ensure that their products are priced competitively. dunk (2004) showed that competitive 48 advantage has a positive role on the extent to which organizations use the cost of product life cycle. organizations will have a competitive advantage when they produce and deliver their goods and services better than competitors. in this study, the competitive advantage of the new product is measured by following the research of singh and sang (2007) with seven indicators. 2.4 new product vision objectives and mission (oswald et al., 1994). proactive environmental strategy (pes) entails organizational members’ support, involvement and commitment in attaining sustainability goals of an organization (albertini, 2019; journeault 2016). thereby, shared vision is critical in fostering employees’ participation and commitment in environmental decision making and actions (aragón-correa et al., 2013; garcía-morales et al., 2011). it facilitates effective communication of sustainability-integrated goals, strategies, practices and technologies among organizational members (johnson, 2017) and develops a sense of collectivism and a sustainability-driven working culture (ketprapakorn and kantabutra, 2019). in addition, it provides goal clarity and strategic directions by mitigating ambiguities according to the above description, it can be expressed that the new product vision is in fact a goal and strategic direction that is considered for the product launched to the market. the sector and industry in which the company competes, and how to create value for future customers. all of these factors set the company apart from its competitors (abel, 2006). in new organizations, psychological differences between departments affect the performance ple, if a subsidiary feels that the parent company has a clear picture of a common goal, then it will perform better in competition. the new product vision creates a psychologically safe work environment for teams and also clearly explains development goals to members. lane collaboration and support for the group’s clear and sustainable goals. organizations and their internal departments, with a particular insight into customers and market situations, have to interact with and coordinate with external marketing trends, especially when products members of the new product development team must have the same vision for the product so that they can create a kind of synergy between different departments and organizations. in modern business environments, the success of new product development depends on collaboration between suppliers, research and development, production, sales, marketing, sales channels, and management support (chen and james lane, 2011). in this study, the new product vision is measured by following tsarola’s (2007) research with three indicators. 3. framework and hypotheses development this study which is investigated in the following hypotheses. 3.1 ict and olc information technologies have improved information and communication. in addition, the continuous development of information technologies constantly poses new challenges for people so that they improve, learn and adapt. the communication within an organization, and need to invest in organizational learning, and master the capabilities of knowledge generation, appropriation and exploitation. learning has become valuable because knowledge is an important resource (mai, do and phan, 2022; productivity and competitiveness are a function of knowledge generation and information processing and so modern information and communication technology (ict) acts as (2000), ict might support knowledge-sharing. consequently, technology is important for facilitating knowledge-sharing between organization members. knowledge-sharing can be for managers wishing to help their organizaencourage members to share and transfer their knowledge (bock et al., 2005). according to 49 dewett and jones (2001), information technoland innovative by making knowledge “visible” and accessible; encouraging sharing and applieffective to dismantle communication barriers de ridder (2004) emphasized that the use of it cess. technology can play a central part in providing the media and infrastructure for learning in and between knowledge communities. ing and knowledge transfer and integrated ict development and usage as key characteristics of a successful knowledge community. bennet and shane tomblin (2006) emphasized that organizational learning is also concerned with knowledge and the use of ict helps modern cient, be better coordinated, and create more and varied links between human and knowledge resources in modern ol and km efforts. based on the discussion above, this study offers the following hypothesis. hypothesis 1 information and communication technology affects organizational learning capability. 3.2 olc and npca the results of studies on organizational learning show that learning capabilities can lead to competitive advantage (gah and ryan, 2008) and organizational learning capabilities are in fact a set of organizational and the organizational learning process and allows the organization to learn and play a vital role in the learning process (chiva et al., 2007). in today’s global marketplace, maintaining a competitive position is a constant concern. technological innovations and economic uncertainty have changed the face of competition and made the survival of organizations dependent on the competitive advantage of their new prodnizations should seek to ensure the competitive advantage of their new products by learning and acquiring new knowledge of the envithis study offers the following hypothesis. hypothesis 2 organizational learning capability affects new product competitive advantage. 3.3 olc and npv companies are looking for ways to reduce product development time while at the same time developing quality and reducing costs a strategic and key activity for many companies through which new products will have a signif2005). in fact, new products are an important factor for the success of organizations in the market (gonzalez and palacios, 2002). more . information and communication technology experimentation attitude factor training factor human and managerial factor environmental factor economic factor organizational learning capacity new product vision new product competitive advantage personal factor risk-taking participatory decisionmaking dialogue interaction with external environment h1 h4 h5 h2 h3 50 organizational learning capability can increase the possibility of providing a clear statement of objectives along with the mechanism of providing a path for the rapid development of new products in the form of product vision (winklen, 2010). based on the discussion above, this study offers the following hypo thesis. hypothesis 3 organizational learning capability affects new product vision. 3.4 ict and npca recognized as a primary driver of competitive advantage (chadee and kumar, 2001). icts are an important part of every country’s national infrastructure (salehan, kim and lee, 2018). ict related research has suggested that information processing capability 2003). information processing capability as an essential component of company’s ict has (premkumar et al., 2005; wang et al., 2013) and asset productivity and business growth (chen et al., 2015). recently, practice-oriented research suggests that information processing capability based on business analytics is likely to help companies to gain competitive advantage (e.g. davenport et al., 2001; kiron & shockley, 2011; kiron et al., 2012; cao et al., 2019). nevertheless, a direct link between ict-related capability and competitive advantage seems highly plausible and has been supported by a number of studies underpinned bharadwaj, 2000; barua et al., 2004; mithas (2003) show that a company’s information capability affects its competitive advantage in american high technology companies; sookstrate that information processing capability is positively related to competitive advantage while lim, stratopoulos, and wirjanto, (2012), senior it executives help develop superior it capability, which in turn has a positive impact on competitive advantage. gunasekaran, subramanian and papadopoulos (2017); saeidi et al. (2019) and mao et al. (2016) also state that information technology can lead to a competitive advantage. also competitive advantage requires companies to have particular control over production costs to ensure that their products are priced competitively (liao, kuo and ding, 2017). technological readiness refers to the speed with which an economy utilizes existing technologies to improve the productivity of zation of icts in daily activities and production competitiveness (salehan, kim and lee, 2018). also, according to cao et al. (2021) competitive advantage can be achieved by introducing new technology-based products. based on the discussion above, this study offers the following hypothesis. hypothesis 4 information and communication technology affects new product competitive advantage. 3.5 ict and npv over the last decade, competition has intenrestructure and improve their business pracobtain competitive advantage in order to for a wide range of business processes and improves information and knowledge manageformance (gargallo-castel and galve-górriz, 2012). information and communication technology can promote the economic development 2017; torkayesh and torkayesh, 2021). also information and communication technology affects organization productivity (garicano, affect the communication within an organizarole in all organizations. information technologies are a key tool in the process of knowledge and stafford (2010) investigated how employees in large companies observe communication is the best accepted, but employees believe way of sharing information. information and communication technology can optimize production process and enable capital to replacing labor (acemoglu and restrepo, 2020; autor that guides strategy, policies, and tasks; it is also a key source of cultural formation and susrole in an enterprise’s development, acting as a bright light directing the business towards (2003) found that vision and strategy are 51 foster business strategy. thus, the extent to which organizational members support and understand the vision is a key factor affecting performance (balduck et al., 2010; james and lahti 2011). the adoption of information and communication technologies (icts) in organizations promises to better connect managers with people, increase public participation service delivery, decrease uncertainty, and improve information dissemination (welch can help create a clear vision for new products by improving knowledge sharing, speeding up reducing uncertainty, and improving information dissemination. based on the discussion above, this study offers the following hypothesis. hypothesis 5 information and communication technology affects new product vision. 4. research methodology the main method in examining the hypotheses in the present study is the structural equation modeling method. sem can provide a more quantitative and conceptually appropriate or satisfying understanding of the relationships ment differs from other modeling approaches in that it tests both the direct and indirect effects 2016). the advantage of sem is the ability to incorporate unobserved latent factors whose implied values can be estimated from multiple observed indicators. since these indicators are assumed to be caused by the latent factor or factors (taucher and oschlies, 2011; chin, marcolin, & newsted, 2003). 4.1 data collection and statistical population data gathering methods are divided into two ods. the statistical population of this study include managers of companies active in automobile industry in iran. 4.2 sampling method and sample-size in this study, simple random sampling method was used which was carried out from among managers. sample size was calculated to be 203 managers of companies active in automobile industry in iran. 4.3. measures and instrument development information and communication technology was the independent variable. in this study, alam beighi et al. (2009) questionnaire was used to measure the ict. it measures six aspects included personal factors, attitude factors, training factors, economic factors, environmental factors and human and managerial factors. organizational learning capability was the mediator. in this study. chiva et al. (2007) questionnaire was used to measure the olc. tation, risk-taking, interaction with external environment, dialogue and participative decision making. in this study, the new product competitive advantage and new product vision were dependent variables. new product competitive advantage was measured by following the research of singh and sang (2007) with seven indicators and new product vision was measured by following tsarola’s (2007) research with three indicators. based on prior literature, the present research utilizes a 5-point likert-type rating scale, containing both the extreme points as to accumulate responses for the multi-item constructs. all these studied measures have been adapted from prior researches which establish their validity, however, to check their validity in context to this study a series of tests relating to construct validity and reliability have been performed. 5. empirical analysis and results partial least square–structural equation model ing (pls-sem) is a non-parametric ap proach that makes no distributional as sump tions and can evaluate small samis a research instrument utilized to quantify dynamic cause-effect relationship models with latent variables in various disciplines (cepedathat pls-sem’s methodological toolbox could accommodate more complex model structures and handle data inadequacies such as heterogeneity. this emerging statistical approach 52 could substantially provide higher statistical power, making it a better alternative to covariance-based structural equation modeling, as supported by leguina (2015). pls-sem has now become a popular statistical technique (kumar and purani, 2018). the analysis of this approach can be aided by smart pls, a robust software application with an accessible graphical user interface (sarstedt and cheah, 2019). an sem model combines the attributes of two the multivariate relationship between latent variables and the measured variables and among the latent variables. the measurement model and the structural model together the observed variables into several common and then analyze the direct and indirect relationships between variables through path analysis (ignacio et al., 2019). validity and descriptive statistics variables are measured through observed variables (kang and ahn, 2021; abuzaid, moeilak, and alzaatreh, 2022). each construct contains a set of indicators (lin et al., 2005). to evaluate the measurement model, three cases of index reliability, convergent validity and divergent validity are used. the reliability of the index is measured by three criteria: 1cronbach’s alpha (cronbach, 1951; cronbach and shavelson, 2004), 2composite reliability (cr) (bagozzi & of each criterion must be checked and if this ca6=0.382, and olc11=0.084 are less than ing the indices with a factor loading less than 0.4. reliability indicates the internal consistency of the items and evaluates the extent to which these items are free from random error (rahman, 2022; kuei and madu, 2001). (2010); al-refaie (2011); kim et al. (2020); basak et al. (2021) and al-refaie et al. (2011), the unique and distinct items assigned under each construct. after the analysis, as shown in table 1, the calculated composite reliability 53 the recommended value of 0.7 and thereby, studied under each construct (cronbach and shavelson, 2004). similar test has also been conducted by lu and ramamurthy (2011) to examine the reliability of their studied variables. the instrument’s validity is determined by how well it measures the construct it was validity test, two separate tests such as the convergent and discriminant validity of items have been conducted. the estimated average variance extracted greater than the standard value of 0.5 conation explained by a construct in its criterion variables compared to the total varialso been conducted to determine the t-statistics values which are found to be significant (since, all p < .05) for all the factor loadings and thereby, establish the convergent validity criterion. similar test has latent constructs cr ave mean sd s.e. mean experimentation 1.000 1.000 1.000 4.6495 .47961 .04870 risk-taking 0.759 0.828 0.707 4.5155 .45331 .04603 interaction with external environment 0.916 0.947 0.857 4.1478 .64365 .06535 dialogue 0.817 0.881 0.655 4.1005 .47001 .04772 participative decision-making 0.814 0.914 0.841 4.1718 .66686 .06771 1.000 1.000 1.000 3.0722 1.13878 .11563 1.000 1.000 1.000 3.7938 1.07953 .10961 0.868 0.884 0.525 3.3879 .73098 .07422 0.783 0.902 0.822 3.0515 1.03954 .10555 1.000 1.000 1.000 3.3196 1.02618 .10419 0.822 0.883 0.656 3.3938 1.27654 .12961 npca 0.979 0.983 0.905 3.8823 .88759 .06690 1.000 1.000 1.000 3.9811 .31212 .02353 ict 0.938 0.9389 0.720 3.3365 .86555 .08788 olc 0.791 0.8428 0.5172 4.3170 .29751 .03021 a-f d ec-f en-f e h&m-f i npca npv p-d p-f r t-f 1.000 d 0.049 0.809 0.552 0.074 0.907 0.615 0.058 0.595 1.000 e 0.101 0.045 0.068 0.87 1.000 0.634 0.080 0.741 0741 0.048 0.810 i 0.004 0.772 0.132 0171 0.108 0.094 0.926 npca 0.018 0.584 0.013 0.081 0.423 0.098 0.511 0.951 0.050 0144 0.016 0.104 0.057 0.039 0.039 0.645 1.000 p-d 0.014 0.394 0.069 0.035 0.365 0.086 0.210 0.780 0.682 0.917 0.555 0.016 0.695 0.631 0.068 0.667 0.085 0.029 0.008 0.090 1.000 r 0.089 0.305 0.061 0.040 0.720 0.107 0.408 0.638 0.308 0.434 0.007 0.841 0.725 0.035 0.784 0.735 0.082 0.760 0.080 0.001 0.002 0.006 0.712 0.016 0.725 e = experimentation; r = risk-taking; i = interaction with external environment; d = dialogue; p-d= participative decision54 also been conducted by bi et al. (2013) and tamilmani et al. (2020). validity is estimated when the distinctive and unique values of the individual meacriminant validity of the constructs and according to gefen, straub, and boudreau be greater than the inter-construct correlation. table 2 ascertains that all the studied constructs satisfy the discriminant validity criterion. similar test has also been conducted by panda and rath (2016) to examine the discriminant validity of constructs. 5.2 and reliability of the measurement sections, it is time to examine the structural part of the model. in this section, the most common criterion for measuring the link between constructs in the model (structural part) is the sigif the t-value exceeds 1.96, it indicates the sigond criterion for measuring the structural 2 and panjakajornsak (2018) and wang et al. (2022), 2 is a criterion used to connect the measurement part and the structural part of model and shows the effect that an exogenous variable has on an endogenous variable. 0.19, 0.33 and 0.67 are introduced as the values for weak, medium and strong values of 2. the third criterion is 2. this criterion determines the predictive power of the model and if it is equal to or greater than 0.15, it indicates the appropriate predictive power of the independent variable. is at the appropriate level. 5.3 how well the researcher’s model reproduces the actual phenomenon presented in the data (kang and ahn, 2021). wetzels et al. (2009) have introduced three values of 0.01, 0.25 and 0.36 as weak, medium and strong values for 1. similar test has also been conducted by kim et al. (2005); schermelleh-engel et al. 1 2 and 2 latent constructs r2 q2 t-statistics experimentation 0.452 0.222 risk-taking 0.439 0.283 interaction with external environment 0.709 0.616 dialogue 0.761 0.50 participative decision-making 0.364 0.188 0.625 0.619 0.586 0.566 0.912 0.453 0.740 0.598 0.667 0.644 0.796 0.430 npca 0.640 0.465 0.496 0.308 ict olc 0.589 0.415 ict --> olc 3.028 olc --> npca 13.320 3.087 ict --> npca 3.110 2.010 2 and 2 55 5.4 hypothesis testing results the current study has used the sem approach to test the formulated hypotheses ( et al., 2015), where the results are derived on has also been considered by al-refaie (2015), eriksson (2017) and guzman (2022) to test their studied hypotheses. the present research has both direct and indirect effects similar to t-value for ict to olc is 3.028 which is higher than the critical t-value of 1.96. this nication technology on organizational learning nizational learning capacity due to changes in information and communication technology 3. this means that 42.1% of changes in organizational learning capacity is due to changes in information and communication technology. there is a similar analysis and interpretation for other hypotheses, which is presented in the conclusion section. 6. discussion at information and communication age, phenomenal development of communication and information technology changes the world (nazemi et al., 2005; shahzad et al., 2020; niu, jayaram, 2020). this technology by enhancing the information exchange process and cost reduction has been presented as inducement competition and growth in every human activand teo, 2013; arvanitis and loukis, 2009). the exploration on how to manage organizational resources and capabilities to sustain competitive advantages remains the intriguing unit of research of strategic management ). it is especially through for information and communication technologies industry where technologies developing with astonishing speed and where the life cycles of cutting-edge products are becoming shorter and shorter, and brand-new by others ( idly changing economic landscape, coupled with transformational advances in information and communication technologies, presents many challenges to managers of large and small enterprises alike ( in personal application to political and economic activities because it is multifunctional solution in personal and local applications to satisfy various needs (castelz, 2001). granroos (2000) indicates that ict can cause organizational interaction promotion, cost reduction of management and social interaction promotion of an organization so pay attention to ict and evaluate its level is fundamental and very important. knowledge changes makes new zations so organizations must change continuously. but do organizations know suitable resources for maximizing the innovation? researchers pay attention to factors which develop organizational innovation and introduce organizational learning as core instrument for making innovation, economic growth, organization survivability and also factor for employees’ productivity and organizational performance improvement (arango et al., 2007; hypotheses path t-value p-value test results information and communication technology affects organizational learning capability 0.421 3.028 supported organizational learning capability affects new product competitive advantage 0.800 13.320 supported organizational learning capability affects new product vision 0.309 3.087 supported information and communication technology affects new product competitive advantage 0.261 3.110 supported information and communication technology affects new product vision 0.186 2.010 supported 56 cegarra-navarro et al., 2020). in past, fundamental building of organizations was workforce and capital but nowadays organizations which learn and be innovative and service-oriented are successful. relatively, resources for controlling an organization was outside but in present new resources which are intangible are inside. intangible resources create knowledge and organizational learning is basic method for knowledge creation. organizational learning is is performance improvement and competitive advantage obtainability, retain ability and improvement. saban introduce organizational learning as important and critical component for innovation that has been developed through nization can improve innovation behavior, management must analyze common learning in organization (petrra et al., 2002). in fact, organization learning is important strategy for creating competitive advantage in organizations because competent employees are valuable resources for organizations (saru, 2007). also, organizational learning can help organizations achieve their performance goals and vision (goh, 2003). 7. conclusion information and communication technology (ict) actively promotes development of emerging industries in the global market and structural change, since it catalyzes the creation of some new markets and disappearance of others (li, lee, and kong, 2019). typically, has become a hot topic in the world economy and level investment in ict increased the perforinclude p2p, online banking, e-wallets. that is to say, ict has penetrated the traditional logical activities, transforming and upgrading internetand technology-based structure. the ict industry is an enabler and a driver of economic development and growth, it is imperative to gain knowledge on the functioning of ict in other industries at different levels (li, lee, and kong, 2019). organizational learning capability is considered as factors and managerial and organizational characteristics which facilitate organizational learning process and permit it to learn. also ict affects on olc and is higher than the critical value of 1.96 which to changes in ict and is equal to 0.421. this means that 42.1% of changes in olc is due to changes ict or in other words, ict determines 0.309, olc on npca are 13.320 and 0.800. all communication technology, in addition to having capability, can directly and indirectly affect the competitive advantage of the new product cant role in determining the level of each these variables. references abell, m. 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(2022). identifying changes in resources using a causality-based indicator framework, convergent cross-mapping, and structural equation modeling. environmental and sustainability indicators, 14, 1–11. page 4 editors note vol 11 no 1 editor’s note vol 11, no 1 (2021) the internet is leading the world towards forms of totalitarianism: how to fix the problem it is difficult to imagine intelligence studies as separate from information technology as we enter the third decade of the 21st century. the current issue of jisib bears witness to this integration with a strong focus on big data applications. hardly anyone today would or could do without the internet, but the project that started with us government financing in the 1960s, with packet switching, and in the 1970s with arpanet and saw commercial light in the 1990s is helping countries turn into totalitarian systems where totalitarianism is defined by a high degree of control over public and private life. public life is influenced by hacking, troll factories, fake news/propaganda, and interference in elections. private life is influenced by massive surveillance. to borrow the title of the book by zuboff (2019) we now live in “the age of surveillance capitalism”. business intelligence systems lie at the heart of this transformation, but so do artificial intelligence and robotics. and the trend is global. in the west the suppressors are mostly private monopolies (e.g. google, facebook), while in the east it is primarily the government that is snooping (e.g. china’s social credit system). face recognition is likely to become as popular in the west as it is in the east. it is also easily forgotten that no city was better surveilled than london, which started to build its cctv technology in the 1960s. the system is now being updated with facial recognition, just like the one we are criticizing the chinese for having. some forms of surveillance may also lead to great advances in our societies, like access to government forms and statements electronically and a non-anonymous central bank digital currency (cbdc), which promises to reduce corruption and tax fraud, and could be used for easy distribution of universal basic income (ubi) . fintech promises to be highly disruptive. we are moving into an orwellian world of surveillance more or less voluntarily, often applauding it. “i have nothing to hide” the young man says, but then he later becomes a minister and starts to worry about the traces he has left on keyboards. the five eyes intelligence alliance, or any other major service, can pull out extensive analyses of behavior and personality on most of us now as we continue to exchange our personal data for access to searches and social media, but also subscription-based services. most chinese think that the social credit system is a good thing. this is for much of the same reason: they believe it will not be used against them and think that they will do well. we all tend to be overoptimistic about our abilities and opportunities. it’s not before we fail that the full implications of the system are felt: lack of access, credit, housing, and no more preferential treatments. the result threatens to worsen the lack of social mobility and increase the growing conflict between the super-rich and those hundreds of millions who risk slipping from the middle class to being counted among the poor, many of whom live in the western world. the truth is another essential part of our civilization that we are now tampering with. on the internet, few users can tell facts from lies, but we think we can. most of those who grew up only with the internet never really learned how to think critically. the old library of physical books was the best guarantee that lessons learned from history would be transferred to future generations without anyone mingling. for that same reason, books were also seen as real threats to tyrants and have been censured and burned. the last time that happened in the west on a large scale was in nazi germany, but it is happening again now in subtler forms as amazon and other giants act as arbiter and refuse books with certain content based on value judgements. a world which relies all too much on the internet should recall that the information there can be switched off in a second. old books are often not even accessible, having been exchanged for online solutions. the situation in the brave new social sciences is much the same, everyone is running after the latest articles without ever questioning if the same ideas have been published before (difficult to know now). thus, much academic literature suffers, becoming a tedious process of repetitions under new brands. in a society where everyone is a writer, no one really reads or has much of importance to say at the end. journal of intelligence studies in business vol. 11, no 1 (2021) p. 4-5 open access: freely available at: https://ojs.hh.se/ 5 how do we solve these problems? step one on the internet is serious encryption as to make data private. step two is to give all personal data back to the users, that is, to take it away from the private companies and then indirectly away from the security services. that will eliminate the “free” business model and lead to more subscription-based products instead. step three is to break up the monopolies, and before that to tax them properly. step four is to return to books that have stood the test of time (real peer-reviewed) whether online or offline. (the learning process is probably only half as good on the screen). we need to go from a culture of skimming data back to reading and discussing it. technology and management practices should be a part of that solution. otherwise it looks like we will continue down the road that leads to totalitarianism. the internet right now is making shopping easier, but most people are becoming less aware of realities, less smart, less critical. only a small part of the population is able to use it to their advantage for understanding the world around them. it would be great to see more articles develop ideas and products for how we as societies can go in this direction. when looking at the articles in this issue we are reminded that intelligence studies is no longer an anglo-saxon body of literature but has become truly international. the first article entitled “interpreting, analyzing and distributing information: a big data framework for competitive intelligence” is by erlaine binotto et al. it presents a big data intelligence framework. the second article entitled “competitive intelligence and absorptive capacity for enhancing innovation performance of smes” by abdeslam hassani and elaine mosconi suggests a way in which competitive intelligence enhances innovation performance for smes. the third article entitled “a framework for big data integration within the strategic management process based on a balanced scorecards methodology” by mouhib alnoukari shows how to integrate big data into the strategic management process using a balanced scorecards methodology. the fourth article entitled “competitive intelligence approach for developing an e-tourism strategy post covid-19” by franky tulungen et al. shows a strategy for how to boost tourism after the covid19 pandemic by developing e-tourism based on a competitive intelligence approach. the fifth article entitled “la veille stratégique entre l'efficacité décisionnelle et l’optimisation de la gouvernance: etude restreinte dans les organismes publics tunisiens” by mostapha tayeb ben amor and fatma chichti (in french, abstract in english) suggests an intelligence framework for the public sector. the study is based on interviews with public sector organizations in tunisia. the last article entitled “integrating science and technology metrics into a competitive technology intelligence methodology” by marisela rodriguez-salvador and pedro f. castillo-valdez presents a new framework for competitive technology intelligence (cti) providing a broader scope to science and technology metrics where quantitative tools such as patentometrics and scientometrics are used. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. i wish i could say that the covid-19 pandemic is soon over, but unfortunately it still has a grip on our societies. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief zuboff, s. (2019). the age of surveillance capitalism: the fight for a human future at the new frontier of power: barack obama's books of 2019. profile books. copyright © 2021 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 53–64 open access: freely available at: http://jisib.com/ the role of competitive intelligence in improving performance through organizational learning, a case study start-ups in algeria zighed rahma laboratory ecofima, university 20 août 1955, skikda, algeria, e-mail: r.zighed@univ-skikda.dz, https://orcid.org/0009-0007-5957-5713. mekimah sabri1 laboratory ecofima, university 20 août 1955, skikda, algeria, e-mail: s.mekimah@univ-skikda.dz, https://orcid.org/0000-0002-7701-7500. received 8 march 2023 accepted 23 march 2023 abstract the study aims at identifying the role of competitive intelligence in improving company performance through organizational learning in start-ups, relied on a descriptiveanalytical approach with the use of a questionnaire to collect data, which was distributed to a random sample of 255 start-ups in algeria. the structural equation modelling was also used through the smart pls 4 program to test the study's hypotheses. the study concluded that there is a weak indirect role between competitive intelligence and the performance through organizational learning expressed in a correlation coefficient estimated at 23.1%, while the direct role was greater with a correlation coefficient of 61.6%.this is due to the fact that the mediator variable does not play its active role in strengthening the relationship between competitive intelligence and the start-ups performance despite this impact, start-ups in algeria does not effectively carry out research to obtain available opportunities in the market. keywords: competitor intelligence, market intelligence, organizational learning, start-ups, the performance 1. introduction: business companies today face a range of difficulties regardless of their size or nature of work, as the resulting risks from unexpected changes in the environment are due to its successive changes, which in turn have an impact on the performance which requires experiment and practice methods and approaches that enable them to survive and compete in the market, including competitive intelligence. among these methods is competitive intelligence, which in turn is a process that includes gathering analysing and communicating information about the environment to help in strategic decision-making (dish man & calf, 2008, p. 767).as it refers to the behaviour used by  corresponding author both companies and nations to enhance competitiveness through better use of information for a company to effectively benefit from competitive intelligence efforts and operations (moloi & iyamu, 2015, p. 3), there must be a proper organizational awareness and a competitive culture(saayman & al, 2008, p. 383). despite the fact that competitive intelligence serves as a highly important tool for the company’s strategy, represented in the planning, management, and official exploration of the marketing strategy model for the company (safarnia, 2011, p. 2) . its purpose was to analyse information about competitors’ activities, trends in a specific sector, and the market in general, in order to guide the 54 company in achieving its goals and objectives (artur, 2020, p. 2) . in order to ensure sustainability and continuity, companies work on improving their performance to reach high levels and have a competitive advantage. this trend has led to the emergence of human resources as a strategic supplier and a key element for creativity, learning, and technology creation. this is reflected through competitive intelligence and its role in improving organizational performance, as it has the ability to effectively produce goods and services that meet market demand (quality, term, and growth) and contributes to the economic system's movement (lorino, 1991, p. 56) . performance is a positive attribute that companies can achieve for a certain period of time, resulting in positive outcomes compared to others. performance in companies is subject to the measurement and evaluation process which helps the company ensure that all departments perform their various tasks with the highest possible efficiency. it also determines the outcomes that need to be achieved and the evaluation that is carried out independently by the relevant authority (fermon & grandjean, 2015, p. 1). performance management should be properly administered as it is a system that sets goals and connects individual goals with organizational ones by defining the objectives and expectations towards each individual, followed by providing incentives that align with their performance (lorraine dori ponu & zubair, 2015, p. 2) . this study aims at achieving objectives related to clarifying the different concepts that pertain to competitive intelligence and organizational learning, the performance of the company, and to identify if the start-ups in algeria have orientations and procedures aimed at developing the role of competitive intelligence in improving the institution’s performance through organizational learning. the study derives its importance from the role that competitive intelligence plays in improving the performance of start-ups in algeria through organizational learning. the significance of the study also lies in the fact that it deals with a recent topic in the field of scientific research in algeria and the scarcity of studies and research related to it, as it is one of the first studies that applies competitive intelligence in start-ups in algeria. therefore, we look forward that it will be a reference for specialized scientific studies and a practical guide for start-ups . the descriptive and analytical approach was adopted, by defining the variables of the study both theoretically represented by the variables of competitive intelligence and organizational learning, and performance of the company. in terms of the practical aspect, data was collected through a questionnaire designed and distributed to a sample of start-ups in algeria. to process and test the study's hypotheses, structural equation modelling was used through the smart pls 4 program. 2. literatures review: in this element, we will delve into the concepts related to competitive intelligence, organizational learning, and performance. 2.1. competitive intelligence: competitive intelligence is providing companies with the tools to make informed decisions. it is enabling companies to keep ahead of the competition and industry trends (maune, mobile applications adoption and use in strategic competitive intelligence: a structural equation modelling approach, 2022, p. 65), competitive intelligence is defined are considered a crucial tool for the company’s strategy represented in the formal planning, management and exploration process of its marketing strategy model (safarnia, 2011, p. 2), where the latter includes the optimal use of public sources for developing data related to the competitive and market environment (maune, 2014, p. 61) . competitive intelligence is also considered as behaviour used by companies and countries alike as a means to improve competitiveness through the best use of information (moloi & iyamu, 2015, p. 3). besides, the importance of competitive intelligence lies in shaping strategic marketing decisions and building for companies aimed towards the market, given its fundamental role in central marketing decisions and the company, with the latter focusing on monitoring the competitive environment to provide actionable 55 intelligence to enhance the company’s competitiveness (macinnis & al, 2002, p. 179) . competitor’s intelligence aims to assess the risks and opportunities in a competitive environment before they become apparent, this process is called early signal analysis, being a highly specialized activity where it has become necessary to design tools and means that can assist analysts in competitor intelligence in the process of collecting analyzing benefiting from knowledge and coming up with strategies effective work (lipika & al, 2011, p. 2). additionally, competitive intelligence also aims to analyze information about competitor activities and trends in a specific sector and the market in general, in order to guide the institution in achieving its goals and objectives (artur, 2020, p. 2) . market intelligence is the set of means that enable managers to be constantly aware of developments in the market environment (kotler & autres, 2006, p. 84). it is a strategy that links a company’s activities, resources and capabilities to its external environment with the goal of maximizing current and future performance and converting current goals into more meaningful and achievable ones from both functional and operational perspectives (johnson & scholes, 1993, p. 20) . the latter affects the planning process both in the long and short run, and adds value to the company’s strategic decisionmaking as well (lackman & al, 2000, p. 6). additionally, market intelligence studies the relationship between intelligence acquired through the internet, value creation, and variables such as customer relationships, innovation, productivity, and the efficiency of these connections (rahchamani & all, 2019, p. 58) . market intelligence performs a set of core functions that support strategic marketing information. it aims to fulfil the marketing goals of a company by determining the information needs of the intended strategic marketing objectives and conducting research to gather and deliver that information, processed appropriately for management, as well as executive managers who require intelligent data to develop and implement related marketing strategies. furthermore, market intelligence has the role of identifying business operations and techniques represented in the on-going information search, which contributes to improving the quality of strategic marketing programs. finally, the role of predicting the future is for intelligence to be more effective when it can act proactively, in other words, anticipating future events (лена, 2019, p. 3). 2.2. organizational learning: organizational learning is considered as a collective phenomenon for acquiring and forming competencies that can be more or less profound or sustainable. it leads to a change in the way situations are managed or in the situations themselves (bounfo, 1998, p. 182) .organizational learning is also a means through which individuals in companies continuously discover how they shape the reality they work in and how they can change it (peter & al, 1994, p. 59) . companies are considered large repository of knowledge, as their success depends on converting implicit knowledge into an explicit one, which is shared among the company’s members (marshall & al, 2004, p. 16). organizational learning is a multi-level process in which individuals acquire knowledge through work and thinking together, and it is also a process of improving practices through better understanding, developing vision, knowledge, and connecting past and future practices and activities (hillary, 2018, p. 3) . organizational learning is composed of a set of elements that may come about through partnerships and alliances, as it generates a large accumulation of knowledge. through this, the value and importance of the company increases, paralleling its assets, innovations, employee loyalty and customer satisfaction (stephen, 2000, p. 8). additionally, learning companies are distinctive in that they are leadershiporiented, either transformational or transactional. as transactional leadership is encountered in such a way which helps leaders understand the appropriate way to achieve desired goals. as for transformational leadership, it is a new type in which it motivates employees to work together for the long term (jeery & ann, 56 1999, p. 19). the more the scope of learning companies expands, the stronger the culture it creates, which leads to increased learning and is reflected in the results and development of the companies (raanan & al, 2007, p. 66) . 2.3. the performance: the subject of performance is considered to be of great importance in managing companies, considering its ability to ensure the sustainability and achievement of balance between the satisfaction of stakeholders and employees (drucker, 1999, p. 73). the performance represents the values and principles prevailing in the organizations internal work environment, which regulate work strategies, ideas and visions that help develop the organization and ensure its continuity (mbaindin, 2022), it is also considered as the ability to produce goods and services effectively in response to market demand (quality, deadline, growth), allowing for a surplus to move the economic system (lorino, 1991, p. 56). performance consists of three main elements, represented by efficiency, effectiveness, and potency. efficiency refers to the relationship between the resources allocated and the results achieved, while effectiveness refers to the level of goal attainment. as for potency, it is the degree to which a companies able to reach its goals and achieve them. therefore, performance is considered as a concept that reflects both the goals and the necessary means to achieve them (brosquet, 1989, p. 1). furthermore, all companies should measure the effectiveness of their activities and the results of their work, because the information obtained will lead them towards achieving their goals and thus improving their performance. therefore, a company that cannot measure its performance cannot monitor it, if it is so, it cannot manage it, and as a result, it will not be able to make sound decisions performance measurement is important because it helps the company to ensure that all departments are performing their various tasks with the highest possible efficiency (lingle & schiermann, 1996, p. 56). it also provides a benchmark for evaluating the performance outcomes, as well as an independent evaluation by the relevant authority. it measures the level of achievement (fermon & grandjean, 2015, p. 1) . performance management is a system that involves setting performance goals, defining measures, evaluating performance and providing feedback. this allows for the identification of training needs and the development of performance, as well as determining the reward system (solkova andrea & gabriela, 2013, p. 20). as it links individual goals with organizational ones by clarifying expectations for each individual and then offering rewards that are aligned with their performance (lorraine dori ponu & zubair, 2015, p. 2). the performance process in the company is subjected to the evaluation process, as the latter plays an important role by looking at the reasons and also concerned with the goals and ways to achieve them. it is a broader process as it considers the causes, also concerned with the goals and ways to achieve them (lauras, 2004, p. 112). 2.4. research questions: through this study, we will address the role of competitive intelligence in improving the performance of start-ups in algeria through organizational learning. however, this study differs from previous ones in that it takes into account a mediator variable represented by organizational learning, unlike other studies, it dealt with each variable separately, and it also focuses on start-ups in algeria. on this basis, the following problematic was raised: what is the role of competitive intelligence in improving the performance of start-ups in algeria through organizational learning? as a preliminary answer to the problematic, the following main hypothesis was adopted: there is a strong positive correlation with statistical significance at a 0.05 level of competitive intelligence in improving the performance of start-ups in algeria through organizational learning. 3. data and method: in order to test the hypotheses of the study and to reach results about the role of competitive intelligence in improving the 57 performance of the company through organizational learning, start-ups in algeria were studied as a case study . 3.1. study population and sample: the study population was made up of all 756 start-ups in algeria. a simple random sample was selected using the equation of steven thompson, with a size of 255 startups. 231 start-ups that were suitable for analysis were retrieved, resulting in a response rate of90.58% (thompson, 2012, p. 51) . 3.2. analysis and presentation of the study tool: in order to test the relationships between the variables of the study and to build a standard model while ensuring its validity, a questionnaire was designed which included (20) questions divided into three axes. the first one is concerned with competitive intelligence with questions ranging from 01 to 08. the second deals with organizational learning from 09 to 12, while the third is about organizational performance from 12 to 20. the variable representation statements of the study model that combines the latent and measured variables should be represented in order to test the biases .e. the extent to which the questions are able to express and measure the real variable, it was found that there are statements that do not achieve the required minimum of 70%, and this can be clarified through the following table: table 1. examine the question ramifications of the modified default form saturation coefficient paragraphes latent variables 0,857 m1 competitor intelligence competitive intelligence 0,861 m2 0,598 m3 0,762 m4 0,872 ma1 market intelligence 0,812 ma2 0,705 ma3 0,849 ma4 0,579 o1 organizational learning 0,558 o2 0,841 o3 0,879 o4 0,795 k1 efficiency company performance 0,744 k2 0,794 k3 0,751 k4 0,117 f1 effectiveness 0,881 f2 0,937 f3 0,686 f4 source: prepared by researchers using smart pls 4 from table 1, it can be seen that there are indicators less than 70% in the dependent variable "performance of the company f1", and this variable has been previously removed. however, despite the fact that there are indicators that do not comply with the 58 condition, they are not less than 40%, but they were kept in the model because they increase the composite reliability values or the average variance, as the following figure shows the adjusted study model after the mentioned indicators are removed. figure 1. the modified model 3.3. reliability evaluation: by measuring the reliability of the study tool, the alpha cronbach index was relied on and reinforced with the composite reliability index cr, and the results were as shown in the table below : table 2. the value of the alpha cronbach and the rho indicator vehicle reliability indicator rho alpha cronbach variants 0,857 0,798 0,774 competitor intelligence competitive intelligence 0,895 0,838 0,826 market intelligence 0,814 0,869 0,725 organizational learning 0,854 0,777 0,774 efficiency company performance 0,878 0,845 0,792 effectiveness source: prepared by researchers using smart pls 4 as seen from the previous table 2, all of the alpha cronbach’s coefficients are greater than 0.7, and the rho values are also high and exceed 0.70. this makes it possible to rely on the proposed questionnaire, and the cr index is greater than 0.7 in all dimensions. therefore, it can be said that the study tool is characterized by reliability. 3.4. measure of convergent validity: it is determined that the model has convergent validity if the accepted ave value is greater than or equal to 0.50, meaning that the model explains more than half of the variance in its indicators. the following table shows average variance extracted ave: table 3. the asymptotic validity measure of the model extracted average variance variants 0,604 competitor intelligence competitive intelligence 0,659 market intelligence 59 0,532 organizational learning 0,595 efficiency company performance 0,709 effectiveness source: prepared by researchers using smart pls 4 from the table 3, we note that all ave values are accepted from a statistical standpoint because they are greater than 0.50. thus, it can be determined that the model has convergent validity. 3.5. the r2 determination coefficient test: in this stage, the values of the determination coefficient that relates to the overall impact of the factors, (the independent variables dependent on the dependent variables through the mediator ones), are calculated. the following table shows the results of the determination coefficient: table 4. the coefficient of determination r2 adjusted2r 2r variants 0,774 0,776 company performance 0,457 0,460 organizational learning 0,434 0,437 effectiveness 0,813 0,814 efficiency 0,919 0,920 market intelligence 0,915 0,916 competitor intelligence source: prepared by researchers using smart pls 4 according to the table 4, it is noted that all coefficients are positive and statistically acceptable, where competitive intelligence explains 0.46 of the organizational learning, which is a mediator interpretation. however, competitive intelligence and organizational learning together explain 0.72 of the company performance, which is a large interpretation. it is similar to the modified coefficient of determination, where its results are close to the results of the coefficient of determination, to indicate the predictive quality of the model. 3.6. evaluating model validity: after confirming the validity of the measurement model, we move on to evaluating the validity of the previously determined building model. this is by calculating the conformity quality index using the gof. the calculation is done using the following formula: gof= √𝐴𝑉𝐸̅̅ ̅̅ ̅̅ × 𝑅2̅̅̅̅ 𝐺𝑂𝐹 = √0.619 × 0.720 𝐺𝑂𝐹 = 0.667 therefore, with a gof of 0.66, which is greater than 0.36, the model is characterized by high quality . 3.7. results analysis: the significance of the paths is confirmed by relying on the bootstrapping technique by generating 500 partial samples. the results were as shown in the following figure: 60 figure 2.statistical significance of thpaths of the structural model. 3.8. paths analysis: the following table illustrates the results obtained from the analysis of the relationship paths between the model variables. table 5. the results of the structural model trajectories analysis p-value std. dev t-value paths value paths 0,000 0,064 10,272 0,648 company performance ; effectiveness 0,000 0,018 51,520 0,908 company performance ; efficiency 0,000 0,043 7,496 0,340 organizational learning ; company performance 0,000 0,041 15,006 0,616 competitive intelligence ; company performance 0,000 0,034 19,796 0,679 competitive intelligence ; organizational learning 0,000 0,006 154,049 0,959 competitive intelligence ; market intelligence source: prepared by researchers using smart pls 4 the previous table 5; indicates that all the model coefficient paths have statistical significance at a level less than 0.05, which indicates the presence of a relationship between the model structural variables, meaning : there is a statistically significant positive relationship between competitive intelligence and organizational learning. there is a statistically significant positive relationship between organizational learning and the company’s performance. there is a statistically significant relationship between competitive intelligence and company’s performance. 3.9. hypothesis testing: the sub-hypotheses and the main hypothesis will be tested in order to determine the impact of competitive intelligence on the performance of start-ups in algeria through organizational learning. -first hypothesis test: there is a statistically significant relationship at a level of 0.05 between 61 competitive intelligence and organizational learning in start-ups in algeria. table 6. the results of the first hypothesis. p value value t std. dev beta paths 0,000 19,796 0,034 0,679 competitive intelligence ; organizational learning source: prepared by researchers using smart pls 4 according to the table 6, the correlation coefficient between the variables is 0.679, which indicates a positive correlation that aggregates the variables and is characterized by being a mediator relationship. furthermore, we notice that this correlation is statistically significant at the level of 0.000 which is less than 0.05. thus, we reject the null hypothesis and accept the alternative hypothesis which states that: there is a statistically significant relationship at a level of 0.05 between competitive intelligence and organizational learning in start-ups in algeria. -second hypothesis test: there is a statistically significant relationship at a level of 0.05 between organizational learning and performance of start-ups in algeria. table 7.the results of the second hypothesis p value value t std. dev beta paths 0,000 7,946 0,043 0,340 organizational learning ; company performance source: prepared by researchers using smart pls 4 from the table 7, we note that the correlation coefficient between the variables is 0.340, indicating a positive weak relationship that is characterized by a weak relationship between the variables. additionally, this correlation is statistically significant at a significance level of 0.000 which is less than 0.05. thus, we reject the null hypothesis and accept the alternative hypothesis which states that there is a statistically significant relationship at a level of 0.05 between organizational learning and performance of start-ups in algeria. -third hypothesis test: there is a statistically significant relationship at the 0.05 level of significance between competitive intelligence and the performance of start-ups in algeria. table 8. the results of the third hypothesis p value value t std. dev beta paths 0,000 15,006 0,041 0,616 competitive intelligence ; company performance source: prepared by researchers using smart pls 4 62 from the table 8, we note that the correlation coefficient between the variables is 0.616, indicating a positive and strong relationship between the variables. this correlation is statistically significant at a level of 0.000 which is less than 0.05. therefore, we reject the null hypothesis and accept the alternative hypothesis which states: there is a statistically significant relationship at the 0.05 level of significance between competitive intelligence and the performance of start-ups in algeria. -the main hypothesis test: there is a strong positive correlation with statistical significance at a level of 0.05 between competitive intelligence and performance of start-up in algeria through organizational learning. table 9. the results of the main hypothesis test. value t p value beta std. dev paths 7,218 0,000 0,231 0.032 competitive intelligence; organizational learning; company performance. source: prepared by researchers using smart pls 4 from the table 9, we notice that the correlation coefficient between the variables is 0.231, indicating a positive correlation that combines the variables together, and which is characterized by a weak relationship. we also note that this correlation is statistically significant at a level of 0.000, which is less than 0.05. therefore, we reject the null hypothesis and accept the alternative hypothesis which states that: there is a statistically significant role at a level of 0.05 for competitive intelligence in improving the performance of start-up in algeria through organizational learning. 4. results: the study reached a set of results related to competitive intelligence and its role in improving the performance of start-ups in algeria through organizational learning. it was concluded that competitive intelligence is part of the strategic information management process, which is necessary for the company’s strategies, as it assists to understand the methods and strategies used by competitors to gain and sustain a competitive advantage, and that organizational learning is the main driving force for improving organizational performance. it was also concluded that there is a relationship between competitive intelligence and the company’s performance with an average degree estimated at 61.6%, despite this impact, start-ups in algeria do not effectively carry out research to obtain available opportunities in the market. this direct relationship between competitive intelligence and the performance of start-ups was better than the indirect relationship through organizational learning as a mediator variable, which was weak, estimated at 23.1%. this is due to the fact that the mediator variable does not play its active role in strengthening the relationship between competitive intelligence and the start-ups performance. through a review of the results and the correlational relationships, it was concluded that the reason for the weakness of the impact is due to the fact that start-ups in algeria do not work on updating their programs for developing their employees' skills and providing training and education programs on the one hand, and on the other hand, they do not do a good job in analyzing their competitors and early detection of risks and opportunities available to them. 5. conclusion: competitive intelligence is considered one of the most significant systematic operations that work to improve the performance of a company through organizational learning. it is a solid foundation in the field of making strategic decisions and determining the priorities of the company intelligence requirements to lead the path of competitive intelligence in terms of collecting, analyzing and distributing information. it aims to 63 determine the purpose and new sources of competitive advantage identify strengths and weaknesses of competitors and their reactions, as well as to identify the priorities of agreement on research and development activities. based on previous results, we recommend that start-ups in algeria prioritize competitive intelligence as a necessary means of making strategic decisions in the company, which helps improve its performance. they should also give more consideration to organizational learning, as it is the process through which the company aims to improve its overall capabilities, develop itself, activate its relationships with its environment, adapt to its internal and external variables, and mobilize its employees to be more attentive in following and acquiring knowledge for the purpose of development and excellence. besides, it is also essential to conduct on-going and continuous improvement processes for competitive intelligence, which assists achieve a competitive advantage. additionally, startups in algeria should also pay more attention to organizational learning in order to achieve its expected role in improving the relationship between competitive intelligence and 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(2019). marketing intelligence as a tool for strategic enterprise management, doi:10.37200/ijpr/v24i8/pr281089. international journal of psychosocial rehabilitation, vol 24 (n 8) o p i n i o n s e c t i o n 30 integration of business intelligence and knowledge management – a literature review najibeh abbasi rostami 1 1 isfahan university, iran email: najibeh.abbasi@yahoo.com received september 27, accepted october 26 2014 abstract: in today’s world data are so numerous that technology is needed to cope with this knowledge. business intelligence (bi) is a process that involves sorting all the collected information and select those that are relevant. bi provides critical insights that help organizations make right decisions. knowledge management (km) is a key approach to solving current problems. km can be defined as a systematic process of finding, selecting, organizing, distilling and presenting information in a way that improves an employee's comprehension in a specific area of interest. bi and km play an important role in improving the qualitative and quantitative value of information available for decision making. km and bi can also benefit from each other. it seems that integration of bi and km can help organizations achieve wider benefits. integration of bi and km will not only help to promote and enhance knowledge for better decision making, but also improve an organization’s performance. therefore it is imperative for organizations to have both bi and km as an integrated system to get full value from both. this paper is a literature review which shows the importance of bi and km integration through a series of models. keywords: business intelligence, knowledge management, integration, literature review available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 2 (2014) 30-40 https://ojs.hh.se/ o p i n i o n s e c t i o n 31 1.0 introduction the environment in which firms operate is growing in complexity. since the 1900’s nearly three billion people have become players in the global stage, overcoming cultural, religious, ethnic, and political barriers to market entry. in addition to globalization, other environmental factors that are pressuring businesses to perform at high levels include: customer demand, government regulations, market conditions, and competition. to meet the performance challenge, companies require considerable volumes of timely, relevant, high quality data, information, and knowledge (kimpel and morris, 2013). in most larger firms, there is a vast aggregation of documents and data, including business documents, forms, data bases, spreadsheets, e-mail, news and press articles, technical journals and reports, contracts, and web documents. knowledge and content management applications and technologies are used to search, organize and extract value from these information sources and are the focus of significant research and development activities (herschel and jones, 2005). for example, the international data corporation (idc) reported that digital data growth was up by 48 percent in 2012, with 90 percent of information being unstructured. as a result of this type of data complexity, many businesses are now challenged to understand and analyse the wide range of information involved. however, as many business users lack access to the information they need, many tend to make decisions based on instinctive knowledge that can result in loss of productivity, reduced agility in the marketplace, and flawed decision-making (boonsiritomachai et al., 2014). therefore business intelligence systems allow organizations to access, analyze, and share information and knowledge, which in turn helps to track, understand, target and manage their business in order to improve enterprise performance (panian,2008). in today’s highly competitive and increasingly uncertain world, the quality and timeliness of an organization’s “business intelligence” (bi) can mean not only the difference between profit and loss, but also even the difference between survival and bankruptcy (ranjan, 2008). bi is a broad category of applications and technologies of gathering, accessing, and analyzing a large amount of data for the organization to make effective business decisions. bi is primarily used to improve the timeliness and quality of information, and enable managers better understand the position of their firm as in comparison to competitors. bi applications and technologies help companies to analyze changing trends in market share; changes in customer behavior and spending patterns; customers' preferences; company capabilities; and market conditions. it is used to help analysts and managers determine which adjustments are most likely to respond to changing trends. it has emerged as a concept for analyzing collected data with the purpose to help decision making units get a better comprehensive knowledge of an organization’s operations, and thereby make better business decisions (khan & quadri, 2012). in parallel with the development of paradigmatic knowledge economy, which emphasizes the role of knowledge in creating economic goods, grows the importance of knowledge management. managing business information allows the use of remaining data, its collecting and converting into usable information. managing the knowledge, through implementing various concepts, and using modern business intelligence tools, are necessary to gain a competitive advantage and survival in the markets. integrating business intelligence and knowledge management in new software applications designated not only to store highly structured data and exploit it in real time but also to interpret the results and communicate them to decision factors provides real technological support for strategic management. integrating business intelligence and knowledge management in order to respond to the challenges the modern enterprise has to deal with represents not only a “new trend” in it, but a necessity in the emerging knowledge based economy (albescu et al., 2008). with respect to the increasing importance of the use of bi and km, and the importance integrating business intelligence and knowledge management in knowledge based economy, it seems that integration bi and km can be determined as one of the key success factors in modern business. therefore, this article will address the importance of integration of bi and km as key for successful organizations. the article is structured as follows: section 2 provides definitions of bi and km. in section 3, similarities and distinction between bi and km are presented. section 4 discusses bi and km benefits for the organization. section 5 presents integration of km and bi with benefits, and the last section gives a brief summary of the article. 2.0 literature review 2.1 defining business intelligence understanding of business intelligence often differs by its content’s focus as well as on several related terms used for referring to business intelligence (including competitive intelligence, competitor intelligence, strategic intelligence etc.) (jaklic et al., 2009). o p i n i o n s e c t i o n 32 business intelligence is a natural outgrowth of a series of previous systems designed to support decision making. the emergence of the data warehouse as a repository, the advances in data cleansing that lead to a single truth, the greater capabilities of hardware and software, and the boom of internet technologies that provided the prevalent user interface all combine to create a richer business intelligence environment than was available previously. bi pulls information from many other systems. figure 1 depicts some of the information systems that are used by bi (negash, 2004). figure 1: bi relation to other information systems. where: olap = on-line data processing, crm=customer relationship management, dss= decision support systems, gis = geographic information systems bi is a set of business information and business analyses within the context of key business processes that lead to decisions and actions. in particular, bi means leveraging information assets within key business processes to achieve improved business performance (williams & williams, 2007). bi systems combine data gathering, data storage, and knowledge management with analytical tools to present complex internal and competitive information to planners and decision makers (al-shubiri, 2012). business intelligence has been defined as solutions applying information technologies to retrieve heterogeneous and distributed resources in order to interpret, categorize, and integrate them, and then to formulate any potentially usable knowledge by employing analysis mechanisms (vine, 2000). bi is the way and method of improving business performance by providing powerful assistance to executive decision maker which enables them to have actionable information at hand. bi tools are viewed as technology that enhances the efficiency of business operation by providing an increased value to the enterprise information and hence the way this information is utilized (cui et al., 2007). business intelligence is not a single entity; it is decomposed into business information. crosspollination of the value drivers identifies three major components to business intelligence within a business enterprise: (1) relationship intelligence. understanding of how the interactions between knowledge workers influence the organizational performance. (2) competence intelligence. understanding of how the abilities/proficiency of knowledge workers influences organizational performance. (3) structure intelligence. understanding of how an organization’s infrastructure environment influences organizational performance (green, 2007). wixom and watson (2010) define bi as: “a broad category of technologies, applications, and processes for gathering, storing, accessing, and analyzing data to help its users to make better decisions.” (p. 14). turban, et al. (2002: 460) define bi as a computer-based decision analysis usually done online by managers and staff. it includes forecasting, analysing alternatives and evaluating risk and performance. bi is a systematic process, by which knowledge needed for an organisation to compete effectively, is created, captured, shared and leveraged (foo et al., 2007). davenport (2006) defines bi as a term which: “encompasses a wide array of processes and software to collect, analyze, and disseminate data, all in the interest of better decision-making.” (pp. 106-107). the key to bi is to capture and share such knowledge. bi is often confused with it systems and processes. unlike information, knowledge resides in the experiences of people in different contexts. the aim of bi in an organisation is to work within business processes that create, and transfer knowledge throughout the organisation. if knowledge is created and transferred via human experiences then these business processes must encompass an understanding of how people learn business intelligence olap data mining dss/ eis knowledge management data warehouse gis crm marketing visualization o p i n i o n s e c t i o n 33 and transfer their knowledge (sharma and djiaw, 2011). 2.2 knowledge management definition knowledge management refers to a systematic and organizational specific framework to capture, acquire, organize, and communicate both tacit and explicit knowledge of employees so that other employees may utilize them to be more effective and productive in their work and maximize the organization’s knowledge (davenport et al., 1998). knowledge management (km) is not always about technology, but also about understanding how the people work, brainstorming, identify groups of people who work together and how they can share and learn from each other and in the end the organization learning about their workers experience and about the leadership the organization. (muhammad et al., 2014). based on actual experiences of the leading global km case studies, the components for km can be broadly categorized into three classes people, processes, and technology (figure 2). while all three are critical to build a learning organisation and get business results from km, a majority of organisations worldwide implementing km have found it relatively easier to put technology and processes in place, whereas the "people" component has posed greater challenges (bhojaraju, 2005). figure 2: components of knowledge management when analysing these dimensions, it appears clear that knowledge management in an organization is facilitated by the coordination among the three important elements: • people – who create individual and collective knowledge by learning, knowledge sharing, problem solving, integrating knowledge with corporate culture, in order to finally launch better and better products and services. • processes – which should be regularly updated with currently available information and knowledge, and improved adequately. • technologies, and in particular information technologies – which should be developed in line with market demands, in reply to competitors’ activities and based on a company’s resources. (olszak and ziemba,2010). km is a process of knowledge creation, validation, presentation, distribution, and application (bhatt,2001). km is achieving organizational goals through the strategy-driven motivation and facilitation of knowledge workers to develop, enhance and use their capability to interpret data and information (by using available sources of information, experience, skills, culture, character, personality, feelings, etc.) through a process of giving meaning to these data and information (beijerse, 1999). 3.0 the similarities and differences between bi and km enterprises have been investing in technology in an effort to manage the information glut and glean knowledge that can be leveraged for a competitive edge. two technologies in particular have shown good return on investment in some application of research and development. the technologies are business intelligence and knowledge management (cody et al, 2002). knowledge management and business intelligence systems have been around for a long time. km systems are people centric. people create, share, disseminate, use and apply knowledge. although bi includes various tools and technologies, the most decisions and actions are taken and implemented by people. although people play crucial role in both the systems, the distinguishing fact is: in km systems people use knowledge from various knowledge sources and apply them to address the problems knowledge management people process technology o p i n i o n s e c t i o n 34 while in bi systems the insights and decisions are mostly data driven (see figure 3) (sonar, 2011). figure 3 : people centric bi and km business intelligence (bi) and knowledge management (km) are the main tools to achieve the organizational tool by providing the environment which users receive, desire and find reliable as timely information or knowledge. the organizations need both bi and knowledge management (km) as an integrated system to get value from explicit and implicit knowledge (khan & quadri, 2012). bi exploits the advantage of huge repositories of data present with and outside the organization. it extracts valuable information/knowledge from various sources of data (khan & quadri, 2012). similar to bi, km improves the use of information and knowledge available to the organization (sun and chen, 2008). however, km is distinct from bi in many aspects. according to a survey by otr consultancy, 60 percent of consultants did not understand the difference between the two. (herschel and jones, 2005). main differences between bi and km have been well described in the table 1. table 1. difference between bi and km (rao and kumar, 2011). bi km sources internal and external structured data sources. data about suppliers, employees and customers etc. expert employees, communities of interests / practices, organization, market & competitors structured/ unstructured data sources. it source systems, etl ,dw,olap, meta data, data mining ,statistical analysis reporting and user interface document management, web content management, enterprise knowledge portal , work flow, collaboration and e-learning business process converts data into information & then into knowledge that finally meets needs of enduser. knowledge sharing, knowledge extraction, knowledge communication, knowledge application, and knowledge innovation. deals with explicit knowledge, which is extracted from operational data. kpi, process optimization, predict from internal and external data. it deals with explicit as well as tacit knowledge. informal, formal, synergic and operational knowledge. objective identifies trends and patterns in structured data for developing new business strategies. utilizes the massive data to discover the knowledge to provide competitive advantage. captures, stores, organizes, and distributes organizational knowledge and resources. it deals with the unstructured knowledge and tacit knowledge of the employees. depends it depends on km to receive feedback/experience from end-users and then to modify the solution, if required. depends on bi techniques to implement in an efficient way and explicit knowledge generated by bi. structured data sources unstructured knowledge sources bi tools km tools data driven insights knowledge driven insights people o p i n i o n s e c t i o n 35 4. bi and km benefits for the organization 4.1 benefits of bi in the last decade, bi has evolved as one of the critical applications in organizations to provide useful insight, support decision-making, and drive organizational performance (on, 2006). there are, of course, many other definitions of the benefits of business intelligence. carver and ritacco (2006, p. 6), for instance, divide them into four groups: (1) lowering costs; (2) increasing revenue; (3) improving customer satisfaction; and (4) improving communication within the company. similarly, atre & moss (2003, p. 39) categorize the benefits of business intelligence as: (1) an increase in revenue; (2) an increase in profit; (3) improved customer satisfaction; (4) a reduction of costs; and (5) an increase in market share. in the survey, kpmg identify several expected bi outcomes. they are:  better decision making;  better customer handling;  faster response to key business issues;  improved employee skills;  improved productivity;  increased profits;  sharing best practices;  reduced costs;  increased market share;  creation of new business opportunities; and  improved new product development. 4.2 benefits of km km can help organizations to provide better service, enhance quality product, reduce cost and respond faster to their customers (mcadam and mccreedy, 2000). efficient knowledge management has a positive effect on organisational performance (drucker, 1994). the knowledge management process aims to support innovation and encourage the free flow of ideas through the company. it helps increasing revenues and reducing costs. the knowledge management process increases the value of the company and its competitiveness as a whole, because it increases the efficiency and effectiveness, the relationship of all resources and innovation (tisen et al., 2006, p. 47). the importance of knowledge management and its link with business performance have been recognised: companies need to spend relevant management efforts towards this direction (canzano and grimaldi, 2012). the benefits of using km in the organizations are:  helps drive strategy  solves problems quickly  diffuses best practices  improves knowledge embedded in products and services  cross-fertilizes ideas and increases opportunities for innovation.  enables organizations to stay ahead of the competition better.  builds organizational memory (dalkir, 2005, p. 20). 5.0 integration bi and km 5.1 relationship between bi and km business intelligence plays a central role in knowledge management (white, 2005). business intelligence is a form of knowledge. the techniques used in knowledge management for generating and transferring knowledge (alshubiri, 2012). bi is seen as an integral part of a larger km effort. the effectiveness of bi integrated with km effort will help not only to promote and enhance knowledge for better decision making, but also improve an organisation’s performance. according to wang and wang (2008), there should be interactions between knowledge workers through bi techniques and business decision makers for knowledge sharing and improvement to happen in an organisation. the provision of quality information is the key to gaining competitive advantages. better information leads to better strategies, tactics, and a more efficient decisionmaking process ( schwartz and teeni, 2011, p.73). herschel (2008) argued that bi activities should lead to knowledge improvement. in other words, “the effectiveness of bi should measure based on how well it promotes and enhances knowledge, how well it improves the mental model(s) and understanding of the decision maker(s), and how well it improves decision making and, hence, firm performance. business intelligence should therefore be viewed as an integral part of km”. some researchers see the relationship differently. they argue that km and its processes are helping hand of bi and make it more pervasive in organizations (zarghamifard and behboudi, 2012). haimila (2001) also sees km as the ‘‘helping hand of bi’’. he cites the use of bi by law enforcement agencies as being a way to maximize their use of collected data, enabling them to make faster and better-informed decisions because they can drill down into data to see trends, o p i n i o n s e c t i o n 36 statistics and match characteristics of related crimes (herschel and jones, 2005). harold m. campbell created a business intelligence model through knowledge management in his paper “the role of organizational knowledge management strategies in the quest for business intelligence.” there are three strategic value propositions which are included in the above model which the organization may use. these are: 1) the need to manage their staff member as assets, who add meaning to information; 2) the need to set up structures that allow staff members to gather and distribute information, but most importantly to convert that information into bottom-line income; 3) the need to be in touch with, and responsive to, the needs of the customers of the organizations; they are the best, and final, arbiters of an organizations' actions. these value propositions are encapsulated in a model for creating bi through km (shrivastava and lanjewar, 2012). it can be argued that there exists an interaction effect between km activities and bi efforts. for example, as malhotra notes, artificial intelligence and expert systems are intended to help deliver the “right information to the right people at the right time.” but, this can only happen if the right information and the right person to use or apply it, and the right circumstance and appropriate time are known in advance. detection of non-routine and unstructured change depends on the sense-making capabilities of knowledge workers for correcting and validating the computational logic of the business and the data it processes. further complicating this issue is the realization that the same assemblage of data may evoke different responses from different people at different times or in different contexts ( herschel and jones, 2005). 5.2 bi/km or km/bi? integrated bi and km provide a robust system with the capability of process-driven decision making. the processes are stored in process model base and their flexibility and reuse help enterprises improve the speed and effectiveness of business operations (lee, 2000). bi and km must be integrated in order to promote organisational learning and effective decision making (cook & cook, 2000). campbell discussed km, components of km, bi and integration of bi and km. there have been several models of integration of bi and km reported in the literature. at the conceptual level, malhotra (2004) has proposed general models of integration of km and bi for routine structured information processing and nonroutine unstructured sense making. white (2005) provides a flowchart model that articulates the use of bi in the km context for decision making. the flowchart model illustrates the involvement of collaboration and interaction between the knowledge workers for socialization. (wang and wang, 2008). adirekpullap (2008) evaluated a framework of business intelligence systems and then explore the development integration framework of the bi and km process, so called bikm framework. you (2010) discusses how km and data mining can become more valuable for real time bi. also, km tools can provide a repository for organizing these reports among other relevant information and for collaborative business intelligence (cbi) (stavrianos and henderson, 2006). km practices make bi more pervasive throughout the organization (vesset and mcdonough, 2009). cheng and peng analyze bi and km, and explain their pros and cons followed by proposing a framework named the kmbi framework that integrates km and bi. the kmbi is built on three layers: data integration, function integration and presentation integration. km and bi have different features and the integration of both can maximize organizational efficiency and provide the best services to the customers (shehzad and ahmed khan, 2013). 5.3 stages in integrating km and bi integration is an ambiguous term that has many interpretations in different domains. for example, in strategy, it means “coordination of activities and management of dependencies between them”. in production and logistics, it is “coordinated management of information, material flows, plant operations and logistics through a common sets of principles, strategies, policies and performance metrics”. the dictionary also provides multiple definitions for integration, for example “the act of combining or adding parts to make a unified whole”. in the domain of information technology, integration is often associated with different perspectives (kahkonen and smolander, 2013). there are three levels of integration between bi and km: (1) presentation level integration provides a horizontal integration with a joint user interface. (2) data level integration provides the content of km systems for bi processes by storing the related metadata into data warehouse. (3) system level integration provides distribution and re-utilization of bi analysis models by a knowledge management system (rao and kumar,2011). km and bi a distinct but interrelated terms of common foundation, mutual effects, complementarities, and synergy ( zarghamifard and behboudi, 2012). stages of integrating km and bi have been described in 4 steps (figur 4). o p i n i o n s e c t i o n 37 according to the american heritage dictionary of the english language, synergy is defined as the interaction of two or more agents or forces so that their combined effect is greater than the sum of their individual effects or cooperative interaction among groups, especially among the acquired subsidiaries or merged parts of a corporation, that creates an enhanced combined effect (taib et al., 2008). as shown in the figur 4, integrating bi and km process generate synergy. therefore, it is expected that the effects produced by combining the km and bi functions will be greater than the sum of their individual effects. this synergy can be important to create and sustain competitive advantages that will lead the organizations to compete strategically in the k-economy. 5.4 integration bi and km benefits for the organization integrating business intelligence and knowledge management in order to respond to the challenges the modern enterprise has to deal with represents not only a “new trend” in it, but a necessity (albescu et al., 2008). km and bi have different features and the integration of both can maximize organizational efficiency and provide the best services to the customers (cheng and cheng, 2011). the benefits of integrating of bi with km are to 1) ensure a real support in deploying successful business across the organization by smoothly managing multicultural teams of employees in providing highest quality products and global services to multicultural customers, 2) end-user preference and experience can be included in bi implementation, and 3) provide better understanding on business context, interpretation results and training to the end-user (rao and kumar, 2011). integrating bi and km provides real technological support for strategic management (albescu et al., 2008). this integration will not only facilitate the capturing and coding of knowledge but also enhances the retrieval and sharing of knowledge across the organization to gain strategic advantage and also to sustain it in competitive market (khan and quadri, 2012). see also the topic of integrating knowledge management with business intelligence processes for enhanced organizational learning (shehzad and ahmed khan, 2013). bikm is the new term that represents the integration and can be determined as one of the key success factors in modern business. integration of bi and km will provide an harmonious tool for enterprise to exploit valuable information and knowledge and gain sustainable competitive advantage (adirekpullap, 2008). o p i n i o n s e c t i o n 38 conclusion rapid developments of techniques and technologies have driven the needs for the application of new knowledge in workplaces. in modern businesses, increasing standards, automation, and technologies have led to vast amounts of data becoming available. this explosive growth has generated an even more urgent need for techniques and tools that can assist us convert this data into useful information and knowledge which can meet customer requirements. in today's world of complex and dynamic, more knowledge-based companies than ever are in need of having knowledge management and business intelligence. in this article we discussed bi and km benefits. business intelligence can bring critical capabilities to an organization. business intelligence systems to allow organizations to access, analyze, and share information and knowledge. also, km improves the use of information and knowledge available to the organization. therefore, it can conveniently be assumed that bi and km play an important role in improving the qualitative and quantitative value of information available for decision making. as we discussed, km and bi can benefit from each other. business intelligence has an important role to play in knowledge management projects. business intelligence techniques are used in knowledge management for generating and transferring knowledge. there exists an interaction effect between km activities and bi efforts, which is discussed in greater detail in other articles. we can conclude that proper integration of bi & km can help organization to get wide benefits. it includes maximize organizational efficiency, enhanced organizational learning and improvement organization performance. we have also discussed the stages in integrating km and bi. both km and bi are deeply influenced by the culture of the organization, especially leadership, groups and opinion leaders, as well as organizational. with successful integration between knowledge management and business intelligence, every company can ensure its viability and outpace its competitors. if an organization aims to develop competitive advantage from information that it has collected then it is best to implement an integrated bi and km strategy. however, the success of each firm depends largely on its human factor. since culture is a km critical success factor and is largely expressed through tacit behavior, we can examine issues that culture can have on bi and km integration efforts. although using integration of bi and km has many benefits and advantages for organizations, studies show that business intelligence projects without due attention to necessary conditions presented here is inefficient. if factors affecting integration of bi and km of business are identified and understood, better integration strategies can be designed. references adirekpullap. t. 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autocorrelation in asset returns. the wealth dynamics for each agent group is analysed throughout trading period. agents with a higher time complexity trading strategy outperform those with strategy keywords: 1. introduction the world bank statistics reveal that the market capitalisation of all listed companies on stock exchanges in the world reaches a total of 94 trillion us dollars in 2020.1 there have broad range of studies aiming to explain dynamics of asset prices and model this comthe capital market theory for asset pricing assumption were the most common approaches used. these approaches assume that prices are tions have been challenged by both empirical therefore, alternative approaches have been introduced, kahneman and tversky (1979) proposed the prospect theory as a part of irrationally assess gain and losses asymmetrically. cont (2001) also present a set of stylbe explained by these traditional approaches. in this sense, agent-based models (abms) are introduced as a “paradigm shift” with more realistic assumptions as boundedly rational agents with heterogenous expectations. abms offer as emergent behaviour of system as result of interaction among system entities. therefore, 55 abms draw a wide attention and jean-claude trichet, the former ecb president, writes that “we need to deal better with heterogeneity across agents and the interaction among those heterogeneous agents”.4 an abm is a simulation to model a system consisting of interacting agents. agents can have static or adaptive rules to initiate their interactions with other agents and environment. it has great importance in terms of providing bottom-up understanding of systems. model the interactions among market entities and agents can also apply range of sophisticated learning capabilities especially when continuous adaptation exists.5 spective, traditional models fall short to explain the behaviour of market through extreme situ6,7 since there is no such classical approach to capture behaviour of crashing markets. in this sense, abms can capture such extreme moves when built with necessary components and optimal parameter calibrations. simulating stock markets has been growing market mechanism, wealth dynamics and price dynamics.9,10,11,12 the seminal paper of the santa 13 14,15,16 these models are differing in the way they set the market microstructure, agents trading strategies, network among agents and intelligence level in agents. a review of abms and found in the literature.9,17,18,19 the main studrequires a proper design and four main design elements are needed: market mechanism, trading strategies, traded assets and trader types. the built model is subject to be validated by measures of modelled market. the validation is the key part of abms since it ensures the appropriateness of the simulation cial market model is measured by the ability of reproducing stylized facts observed in the real market.3 another approach for validation is to use modelled market parameters.20,21,22 llacay and peffer (2018) use face validation differing from the mainstream. the stylized facts in erature and they are relation23 24,25 3 there is no simulation model can reproduce all known facts due to increasing complexity of model, hence models are kept simple in compliance to ockham’s razor principle which asserts to use minimal entity for explanations. the trading strategies agents employ play simulation model.17 these strategies can range from zero-intelligent agents26 to very intelligent agents compared to earlier studies.27 in a recent study, llacay and peffer (2018) used agents with realistic trading strategies that takes historical price into account. the method used to take trade action mainly relies on future price forecast which can be any method, for example, evolutionary techniques such as works. agents can also employ social learning method where agents observe other traders and change their strategy accordingly.9,28 this may lead a herding behaviour in the marthe herding behaviour as a reason for bubbles considering main components of agentmethods are main agent diversifying component in the model. in this sense, considering existing studies, there are a few studies that takes realistic agent trading strategies since the earlier studies mainly employ agents with zero-intelligent and agents using fundamental value and genetic algorithms. in this study, we more realistic technical and fundamental trading strategies as well as machine learning approaches. the methods our agents use have been studied in the literature for price preautoregressive integrated moving average (arima) and nelson et al. (2017) used long short-term memory (lstm) as predicting method. on the other hand, llacay and peffer (2018) applied some realistic technical tradthe most of prediction methods use historical data and do back testing to measure the sucmethod interaction with market environment, and this assumes no price impact in the market. considering this fact, we equipped our agents with realistic trading strategies and let them to interact with all market entities. with this, the agent’s market effect is considered, and the model provides an insight into wealth dynamics of interacting agents. the model pro56 market hyper-parameters such as price tick size. we extend the gasm model by adding interacting intelligent agents and analyse market dynamics and wealth dynamics. we aim to make four main contributions to the agent(1) reproduction and validation of the gasm strategies which are commonly used by practitioners (3) we analyse wealth dynamics of agent types hence, the effect of intelligence level on noise traders in the market. the rest of the paper is structured as follow: section 2 presents our simulation model. in section 4, simulation results are given. concludes the study. 2. proposed model lar microstructure with gasm model, for a detailed description of the model structure.40 the herding behaviour phenomena is modelled different from gasm model. agents form cluster is activated with a given probability that all agents belong to the cluster are either seller or buyer. 2.1 trader types on behalf of another parties. traders vary in perceiving the market, they therefore employ different strategies for trading. at this point, the market theories come into account and help traders to see different beliefs about these complex systems. there are several studies prices cannot predict the future prices while brock et al. (1992) and kwon and kish (2002) evidence that technical trading rules can beat to this, statistical methods such as arima30 and lstm31 are used to predict future stock price for trading. in this sense, an environment erogeneity of traders in real market. the literature in testing trading methods usually take a strategy as a baseline and do back testing to compare performances. therefore, agent-based not possible to mimic the entire complex real market dynamics. market is populated with six types of agents who are named as the method they are equipped with: noise, moving average convergence divergence (macd), relative strength index (rsi), bollinger bands, arima and lstm. agents will be named with the method they the amount of assets (cash) to be traded is random fraction of assets(cash) and the limit price is a draw from a interval that is attached to historical volatility. agents rely on their signal function when taking trading decision. have a great importance in keeping the market working since they act as a catalyser in the market and supply volume for intelligent traders.8,35 is considered as a momentum indicator that gives signal of overbought or oversold. the method is developed by wilder (1978) and the rsi value range from 0 to 100 and the rsi value is regarded as overbought if it is above 70 while it is oversold when it is below 30. is a technical trader tool developed by gerald appel in late 1970s. it is mainly based on exponential moving average (ema) which is a type of moving average that takes the more recent data points the greater weight. is a technical trader tool developed by john bollinger in 1980s. it is volatility measure indicator that relies on the past price of asset and its volatility. the agents using arma(p, q) forecast with arma model is computed recursively. the arima model use integrated data by differencing the raw data to meet the time series stationary. the arima traders checks stationarity of stock price and do differencing till obtain a stationary series. the traders estimate arima models with different lags to p and q the model with minimum akaike information criterion (aic). the forecast price values are predicted and that is fed into a decision-making process. is recurrent neural netschmidhuber (1997). it is a machine learning method with deep networks and differs from feedforward neural networks with feedback connections since it can process sequences of data. the lstm is widely used in predicting stock price movement and outperform baseline approaches.31,39 the lstm traders use simulation initialisation period stock price return 57 to predict following 5-periods return so post orders accordingly. 3. market initialisation at the beginning of simulation, the stock price p0 is set to be $100. the wealth is equally distributed among agents, each get 1000 stock (inventory) and $100000 cash. the hyperparameters for market is set before simulation run as in table 1. there are total of 550 agent population of which 500 noise traders and 10 for each of rsi, macd, bollinger, arima and lstm traders. the tick size for asset price is one cent. marchesi et al. (2003) extended the gasm model by populating the market with four different agents. like this study, the most of agents are noise traders that enables the order matching mechanism working. the simulation time steps refer a trading day and simulation is consist of 5040 days which is approximately 20-year trading period since a year has average agents are in a partially observable environment since they only can access asset price. agent types use technical trading indicators, statistical model for time series, and a machine learning, deep learning. all intelligent agents they rely on signals for the forecast period. the stock market is closed form since there is the total wealth of agent agent at time step can be calculated as = + , where and are the cash amount and assets of agent at time step and pt asset price. wise. the wealth of a trader changes throughout simulation as a result of their interactions. the actions within market environment are based on the strategy trader employ to take buy or sell action. building these strategies rely on the parameters that emulate realistic trading strategies, which is given in table 2. market initial parameters. market parameters value description n 550 total number of agents t 5240 simulation time steps pac 0.001 probability that agents create a cluster pca 0.002 probability that cluster is activated bp 0.5 buy probability of noise traders smu 1.01 mean of sell limit orders ssk 4.5 sell sigma k bmu 1.01 mean of buy limit orders bsk 4.5 buy sigma k agent population [500, 10, 10, 10, 10, 10] [noise, rsi, macd, bollinger, arima, lstm] 58 agent initial parameters. agent type parameters values description noise [p ] [0,5] buy probability rsi r1 ] [14, 30, 70] periods of rsi, buy signal threshold, sell signal threshold macd m1 m2 m3 [12, 26, 9, 2/(n+1) ema(p), ema(p), ema(macd) periods and smoothing constant bollinger [ b] [20, 2] periods and constant k arima [p, d, q] [ [1], [0,1], [1] ] p, d, q are lag order of ar, degree of differencing and ma window size, respectively. p, q take an integer value 1 and 2, depending on model selection aic criteria. d is mainly 0 or 1. lstm optimiser, epochs, learningrate] [20, “adam”, 50, 1, 0.005] input and output layers. “adam” is an optimiser for training deep neural networks. epochs is the number of learning algorithm works through the training set. learningrate is the step size function. 2. simulation model and results in this section, the extended gasm model is simulated, and the result of the experiments to trade in the market for a given initialisation period hence, initial stock price is generated. different traders who are called “intelligent” agents since those agents predict future price move. the market behaviour emerges under agent interactions. the simulation is run with 500 noise traders and 10 intelligent traders for each method. since the amount of asset to trade is a random friction of agent’s wealth, having 10 agents for each method will decrease the effect of randomness on average. several simulations with same parameters were run and all give similar outputs. therefore, results here are a representative simulation model for those series the model keeps the gasm main structure, however, some parameters are tuned after several experiments and intelligent agents are added to the market. the population share of traders in the market are determined with experiments. a market with more than 10% of intelligent agent population leads stock stock market simulation loop structure. 59 price jumps and halt in price formation process. the decision-making process is two part which are trading decision and the amount to trade. the amount to trade is random fraction sion depends on the method agents use, trading signal functions is summarised in table 3. it shows the tuning options on parameters for agent trading methods hence, mostly used realistic trading parameters are used to condition realistic trading strategies. 2.1 price, return and volume analysis approaches have assumption that stock returns than normal distribution.3 in addition to this acteristics that are well documented in warner and brown (1985). therefore, the price and other emergent features of simulated market agent decision estimation window and decision making. traders estimation period (day(s)) forecast period (day(s)) buy rule (if …) sell rule (if …) noise rsi 14 1 rsi rsi macd 9, 12, 26 1 bollinger bands 20 1 sma sma arima t lstm t market outputs over simulation time. upper left panel: asset price. upper right panel: asset price log return. lower left panel: asset price log return density distribution. lower right panel : traded volume. 60 are supposed to exhibit these characteristics alongside stylized facts. the price, return and volume outputs are of price is expressed as returns in the rest of this paper. asset price and return related descriptive statistics. statistics price returns mean 81.98 0.000 standard deviation 6.58 0.0091 minimum 65.12 -0.0702 maximum 101.80 0.0754 skewness -0.33 -0.5172 kurtosis 2.09 9.5849 augmented dickey-0.6579 -87.2366 descriptives of price returns are in line with real world stock return features which has zero mean and have heavy-tailed distribution. the distribution is leptokurtic and left skewed with 11.65 kurtosis and -0.769 skewness measure. the price is not-stationary at lation parameters are tuned for different combinations of market and agent parameters. the most striking result is that increasing population of intelligent agents halts price formation so the market. 2.2 validation market model is measured with the number of stylized facts the simulation model is capable to reproduce. the validity of our built model cial market features. as a seminal work, cont (2001) documented a list of stylized facts for markets have reproduce some these stylized facts but not all of them, so do ours. in addition to all market microstructure parameters, there are also six different types of agents interacting which increase the complexity of the stock market. the validation process is conducted for each fact given in cont (2001). return autocorrelations it is empirically showed that autocorrelation time scales could be exception.3 there would be a price to be exploited otherwise, and this function (acf) values for simulation generated asset price returns indicates that there is a staafterwards. this is more like intraday small the slow decay behaviour in absolute return autocorrelation function is another real marfeature that is measured by squared returns return related autocorrelations. left panel: return autocorrelation function. right panel: return partial autocorrelation function. 61 with ljung-box q-test. the test results show that there is an autocorrelation in squared return with test values [critical values] of 1960.22 [11.07], 2155.86 [18.31] and 2176.27 [24.99] for lag 5,10 and 15, respectively. this is a sign of long dependence of volatile market conditions so the conditional volatility behaviour. volume/return corelations it is expected to asset return has negative correlation with volume, however the simulation output short fall to meet this feature since the calculated correlation is = 0,03. another as negative correlation between return and change in volatility. the simulation output was able to reproduce a weak with . the validity of our model with stylized facts is summarised on table 5. testing all stylized facts given in cont (2001) for asset price and volume outputs from simulation show that the model can replicate real market features and they are summarized in table 5. 2.3 wealth analysis the literature in testing trading strategy methods relies on back testing mostly where the agent is assumed to have no market impact on market dynamics since they interact with market participants. this study aims to create a stock market testbed where agent interaction is considered, hence variety of sensitivity analysis can be applied. satisfying some real market stylized facts, the agent-based model is capable of generate real market features. therefore, the market is populated with different types of partial autocorrelation function. list of stylized facts for asset returns that is used for simulation model validations. stylized fact testing does our model meet? absence of return autocorrelations autocorrelation plot partially slow decay of autocorrelation in absolute returns autocorrelation plot squared return autocorrelation plot aggregational gaussianity skewness and kurtosis no corelation no leverage effect corelation partially 62 agents who compete to increase their wealth at the end of trading period. one of the question this study aims to answer is if computationally intelligent agents can beat the overall market. in the light of this with the signal they receive. the rules agent use to trade were summarised in table 3. based on these rules, agents entered market and start to trade. the average wealth of agent the agent named lstm, which is a deep learning method, outperforms other agents by far. lstm method is the most complicated and computationally costly method among others. computation power can be considered as intelligence level in an interacting agent market. therefore, it can be concluded that the more computational power the higher return. the number of days agents take long, and short positions is summarised in table 5. average number long and short positions over trading period. traders long positions short positions noise 2269 2266 rsi 120 131 macd 368 369 bollinger 125 126 arima 127 4400 lstm 2531 1811 two agent group rsi and bollinger are reluctant to take position since there is no up-down pattern in price long run. arima and lstm trade most of time since they take position based on their future price move predicagent types, agent wealth differs statistically of agent type pairs was tested at 1%, except noise-macd agent pairs, the rest of 14 pairs has different wealth over the trading period. a boxplot for each agent group is created that although all agents belong to the same group use the same trading method, they differ in the amount to trade at each trading decision. therefore, randomness in amount to trade decision give advantage to some traders. in this sense, each group has at least ten members and distribution checked at initial and homogenous. to measure this, the gini coefinequality in wealth that ranges from 0 to 100. increase in it is a sign of inequality in wealth distribution. at the beginning of simulation all agents were endowed with same amount of small inequalities occur during trading period average wealth of agent types in cash throughout trading period. 63 type agents were kept, and it remains stable at is a measure of wealth inequality, the outliers 3. discussion and conclusion the study aims to gain a better understanding of trader interaction in stock markets and reproduce real market price features. approach is employed to serve the purpose of this study since it takes agents’ market impact into account. the model was able to reproduce real market “stylized facts”, thus it is eligible to were able to equip agents with realistic trading into rivalry of different intelligence level in agents and supporting evidence to dominance of computationally powerful agents. it is evident that agent using deep learning approach get the highest return among others with the highest time complexity method. with agent groups using no trading strategy, rsi, macd, bollinger, arima and lstm methods. catalyser effect of noise traders is tested as the increase in population of 64 intelligent agents halts market and that is ligence in agents helps market to move and provide liquidity to the market. are also in line with back testing on real data, siami-namini et al. (2018) compares performance of arima and lstm methods where the lstm trader outperforms. this is also can be taken as validity measure whereas llacay and peffer (2018) use also face validation and sensitivity analysis to validate their market model extended with realistic trading strategies. our results are consistent with the previous work of raberto et al. (2001) and marchesi et al. (2003) since it reproduces its results. although it is challenging to represent commodel can still reproduce most of price dynamics.43 components is built and validity of empirical tic trading strategies compete alongside agent interactions in our bottom-up market model. the emergent behaviour of the market is a result of agent interactions which is hardly let agents to interact at micro level and analyse the behaviour of market dynamics under different parameter combinations. this can also be considered in a game theorical view since competence of different strategies resulted in price equilibria. considering these aspects, help us to better understand market dynamics even in a competing strategies environment. there are potential limitations of study that heterogeneity in agents is more diverse in real markets such as informed and uninformed although our model mimic real market price features, fundamental value of an asset is the key for major investors and could be added as one trader type. a more powerful computation can ease time complexity of simulation when agents with complex trading strategy is considered such as deep learning method. market parameters, different combination of parameters can be applied when modelling interest in high-frequency trading and limit order book modelling44, therefore there are variety of direction to apply machine learning tools for future research. references 1. market capitalization of listed domestic companies. 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(pp. 653–660). 36. wilder jw. new concepts in technical trading systems. 1978. term memory. dicting stock prices using lstm. ket: microstructure and simulations. lecture notes in economics and mathematical 41. brown, s. j., warner, j. b. using daily stock returns: the case of event studies. journal 42. siami-namini, s., tavakoli, n., namin, a. s. a com parison of arima and lstm in forecasting time series. 17th ieee international conference on machine learning and applicanancial complexity. . get real: realism metrics for robust limit order book market simulations. in methodology of integration for competitive technical intelligence with blue ocean strategy: application to an exotic fruit marisela rodríguez salvador* and manuel alejandro bautista reyes** *instituto tecnológico y de estudios superiores de monterrey (itesm) campus monterrey, eugenio garza sada 2501, monterrey, mexico marisrod@itesm.mx **exa-tec campus monterrey reyestec@gmail.com received 10 march 2011; received in revised form 22 november 2011; accepted 28 december 2011 abstract: this article presents a new methodology that integrates competitive technical intelligence with blue ocean strategy. we explore new business niches taking advantage of the synergy that both areas offer, developing a model based on cyclic interactions through a process developed in two stages: understanding opportunity that arise from idea formulation to decision making and strategic development. the validity of our approach (first stage) was observed in the evaluation of an exotic fruit, anacardium occidentale, in the south of the state of veracruz, mexico with the support of the university itesm, campus monterrey. we identified critical factors for success, opportunities and threats. results confirm the attractiveness of this crop. keywords: competitive technical intelligence, blue ocean strategy, anacardium occidentale 1. introduction with an area of 1,964,375 km², mexico is a country located in the southern part of north america, with a varied territorial geography: arid, mountainous, coastal and desert. its population is approximately 112,336,538 inhabitants (inegi 2010) and its economy is based substantially on the traditional industry, high-tech industry, and agriculture (cia 2011). in mexico, one of the main industrial areas is located in the northern part of the country, in monterrey, nuevo leon. in this city the main campus of the instituto tecnológico y de estudios superiores de monterrey (itesm) is located, which is one of the most important private academic institutions in latin america. the institute has since its beginning developed strong relations with the industry resulting available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 29-39 mailto:reyestec@gmail.com https://ojs.hh.se/ 30 in broad training and consulting services (noriega and rodríguez 2010, itesm 2011). since 2001 a unit of competitive technical intelligence is established on the monterrey campus headquarters (center of quality and manufacturing). its purpose is to promote academic and research activities within this field and assist companies in the identification of opportunities and drawbacks for improvement in innovation processes (noriega and rodríguez 2010, 30-39). in 2010, a master degree student in the quality and manufacturing program asked for support in developing his master's thesis with a project to evaluate the potential niche of an agricultural product from the southern part of mexico. the purpose was to develop a model to evaluate the feasibility of production of an exotic fruit, applying both methodologies: competitive technical intelligence and blue ocean strategy. the final aim was to help improve the competitiveness of a group of farmers of the olmeca region in veracruz. 2. competitive technical intelligence and blue ocean strategy the competitive intelligence field in the anglo saxon world has its origins around the 1600’s in england when sir francis bacon recognized that scientific knowledge is the engine that generates technological change and environmental evolution. the importance of collection and assimilation of sources of technological information was established in the 1800’s, as industries of textile, steel and others evolved. however, it wasn’t until the 1900’s that the field of competitive intelligence was recognized as a profession (ashton and klavans 1997). in 1986 the society of competitive intelligence professionals (scip) was established in the usa. scip is a nonprofit global organization whose purpose it is to promote the field and develop professional knowledge in order for organizations to be more competitive. competitive intelligence refers to a systematic and ethical process for collecting, analyzing and managing external information that could have an impact on the plans, decisions and operations of a company. it is an analytical process that transforms disperses data from competitors, industry and market to apply knowledge in strategic areas related to capabilities, intentions, performance, and position of competitors (scip 2011). whereas the term ‘competitive intelligence’ refers to the process that involves the handling of general information about the external competitive atmosphere of the business, competitive technical intelligence (cti) is also concerned with the associated scientific and technological events of research, development and innovation processes; technological acquisition policies, joint venture, portfolios of r&d, etc. (escorsa and rodriguez 1997, 835). competitive technical intelligence pursues three main objectives: 1. timely awareness of technological events that could improve or harm the organization’s performance. 2. identification of new products/processes, and collaboration prospects to create or improve business. 3. comprehension of scientific and technological events or trends related to the competitive environment, which identifies innovative opportunities (porter 1991). the primary role of cti is anticipation (early warning), a key factor in the business world today. companies that apply this methodology successfully can hope to make decisions with more certainty and can stay ahead of future changes in the environment (comai and tena 2006, 113-136). competitive technical intelligence systems have been a decisive factor of success for companies like: l’oreal, master lock, nestlé, american airlines, oracle, hasbro, 3m, hacer, kellog co. north america, nutra sweet, procter & gamble, johnson & johnson, hewlet packard, southern bell, texas instruments, ford motor credit and rockwell automative design. increased sales are one of the most important benefits that an organization can achieve. a study realized by price waterhouse coopers in 2002 concluded that companies considering awareness of environmental changes had a sales growth of 14.2%, against 11.8% from those who didn’t (scip 2009). from the mid-1990s there has been a substantial increase in research, literature, symposia, training and consulting in cti and related areas. in first world countries the value of cti activities are well recognized for growth and competitiveness (grisaleña and unai 2008, 26-31). in developing countries, like in latin america, there is still much to be done in this area (price 2000). cti provides a methodology interesting to latin american organizations, in particular when they can obtain support from academic institutions that can guide them in this process, taking advantage of resources available in the institution. as chan and mauborgne (2004a, 8) established, there has been an accelerated commoditization of products and 31 services, increased price wars, and shrinking profit margins around the world the last years. this is the result of increased global competition. for major product and service categories, brands are becoming more similar, and as they become more similar people increasingly make selections based on price. in overcrowded industries, differentiating brands becomes a harder strategy to implement in both economic upturns and downturns. this is why strategies that focus on the prospect of entering into an untargeted market and attracting a wider array of customers, who are not currently the target of heavy competition from other competing brands, are needed. one answer to this problem can be a blue ocean strategy deployment, creating and capturing new demand with the aim of adding value in businesses not seen or thought of before. the idea of blue ocean strategy was the result of a decade-long study of 150 strategic moves spanning over more than 30 industries and 100 years (1880-2000) (bos 2011). the name blue ocean derives comes from the idea of imagining the market universe formed by two types of oceans: a red ocean and a blue ocean. a red ocean refers to a market that is already known (competition is heavy, companies are already established). a red ocean means staying in a competitive environment where demand of products and services has defined boundaries and the competence are known by the companies involved. a blue ocean refers to a market space that hasn´t yet been explored and that could constitute a business opportunity. the blue ocean shape is set to overcome competitors and gain greater market shares (chan and mauborgne, 2005). the purpose of a blue ocean strategy is restructuring current market boundaries or creating an entirely new market, where competition rules are not yet set and high profits could be obtained. in this kind of scenario, competence is more or less irrelevant at the moment due to the fact that competition does not exist. products and service standardization is low and business growth is promising (chan and mauborgne 2005). a blue ocean strategy enables the opening of new markets, discovering new demands and consequently achieving economic benefits that allow a clear differentiation from competitors. as chan and mauborgne (2004b, 101-116) note, the strategy comes up from the result of limit expansion of the existent industries, applying a different logic strategy called ¨value innovation ¨. value innovation is the cornerstone of blue ocean strategy due to the fact that it requires simultaneous pursuit of differentiation and low cost. it is a new way of thinking, an execution of a strategy to set aside the competition and break the tradeoff between value and cost. value could be achieved by eliminating or reducing the variables on which a company competes. the value for clients increases by searching for and creating elements that companies have not offered before. chan and mauborgne, (2005) note that the real challenge is not only to be compared with competitors offering more for less; this kind of strategy could increase sales for a period, but will hardly lead to the opening of a new market. conversely, they suggest a redirection of the strategy, where alternative products are considered focusing directly on the customer, not only on the competitors. the final objective is to build strong barriers against imitation through innovation. some of the companies that have successfully implemented the blue ocean strategy include cirque du soleil, casella wines (australian wines), netjets (airlines), curves (a texan company specialized in women exercise programs), novo nordisk (a danish company that produces insulin among other products), nabi (hungarian bus company), cemex, starbucks, dell, and the home depot. these companies have obtained interesting competitive advantages generating a value differentiation by offering differentiated products/services, establishing high barriers against imitation (druehl and schmidt 2008, 44-60). in this context, we suggest that a systematic monitoring of the environment through competitive technical intelligence can lead to knowledge of key competence factors needed in a blue ocean strategy in terms of product, service and/or delivery. 32 we applied this strategy to the fruit anacardium occidentale. while the combination of six sigma and blue ocean strategy has been studied before (meyer 2010), no studies to our knowledge are published where competitive technical intelligence and blue ocean is integrated to evaluate agricultural products. chan and mauborgne (2005) propose several analytical tools to help in this effort: a six-way scheme, a strategic profile and a four action scheme. the combination of these tools could balance the risk factors in the formulation and execution of the strategy for the final concept implementation. for the purpose of this article, the last two tools are applied. 3. the case study mexican agriculture represents 4% of the country´s gdp; only 11% of mexican territory is arable and the agriculture is concentrated in products, such as corn and beans (u.s. department of state 2010). unfortunately, the agricultural development has suffered important constraints in the last years; this is the case for veracruz; a state located in the southern part of the country with an area of 71.820 km². veracruz borders with the gulf of mexico and has an extended coastline of 745 km. mexico, particularly in the southern area, has appropriate conditions for the production and marketing of many different agricultural products with high level standards. some barriers, however, exist. while veracruz shares are 4.8% of all domestic agricultural market, ranking sixth at national level in the category (inegi2011). the state has hardly increased its area harvested (inegi 2009), but have very attractive conditions for farmers, including large land area, excellent location, agro-climatic diversity and wide availability of natural resources, especially water. for many years, food production based on short crops periods have been of particular significance for companies in the area (sedarp 2010). veracruz has a large territory which is divided into 212 cities, grouped in 10 administrative areas, as can be seen in figure 1. figure 1: administrative areas that integrate veracruz state (source: inegi 2010) we will focus our attention on the district with the highest food production potential: the olmeca region, which is located in southern veracruz. this zone has an area of 17,863 km² and is composed of more than 20 municipalities, as shown in figure 2. 33 figure 2: olmeca zone (source: inegi 2010) even though it is one of the most attractive regions, this advantage has not been sufficiently capitalized upon. in most cases, farmers compete with traditional products (where markets are nearly saturated and the return on investment is poor) and they do not normally look for other options. the recommendation is that farmers should focus their efforts on searching for high value alternatives, for example by exploring non-traditional crops or exotic species that would give them a unique differentiation (conagua 2005). in this respect, we apply competitive technical intelligence as a method to explore new opportunities combined with blue ocean strategy. 34 4. integration approach based on the competitive technical intelligence methodology proposed by escorsa y rodríguez (1997, 835) and the blue ocean strategy of chan and mauborgne (2004), a synergic model was designed, as shown in figure 3. figure 3: model of competitive technical intelligence with blue ocean strategy the objective was to identify and analyze business opportunities in markets that have not been previously explored, such as the case of exotic fruit in our example. this model is based on cyclic interactions through a process divided in two stages: 1) understanding opportunities and 2) strategic development. in the subsequent paragraphs, we present a brief explanation of the development of each stage, including insights obtained from the implementation of the methodology proposed in the model above. 5. the methodology even though the model includes both understanding the opportunity and strategic development, for the purpose of this study, we decided of practical reasons to develop only the first part. with this perspective, we hope to show those interested (individuals, companies, associations) new ways to discover business opportunities applying innovative methodologies. the second phase was not developed due to time and space restrictions; it would have been necessary to select a company, establishing utility, 35 price, implementation cost and strategy. it will instead be suggested for future research. 5.1 understanding the opportunity in this phase, the bases of the innovation project is established by employing four activities, starting with idea formulation and establishment of objectives. according to otto and wood (2001, 83-110) the idea of how to drive the project forward should be clearly defined; this includes development of vision and market analysis, including detection of hidden client needs. in our case the project involved the exploration of a non-traditional crop: the anacardium occidentale fruit, shown in figure 4. figure 4: anacardium occidentale next, competitive and technical intelligence was applied to perform the environment analysis. concerning the project, a thorough review of primary and secondary information was completed over a period of six months. information sources were selected based on content, actuality, legality, and cost efficiency. access to the digital library resources of itesm campus monterrey was crucial. a primary research was conducted in veracruz. for this purpose, one municipality of the olmeca region was selected (name is confidential). this municipality had more opportunities to grow and develop new business. 10 of the most important farmers of the region were interviewed in terms of their possible interest in the project as well as availability of resources (economic, facilities and basic capabilities needed). once the information was gathered, the processing and analysis could start. it is important to emphasize that these activities should focus on getting an actionable final result, which signifies an added value for the decision-making process. in this respect, analysis of the factors that could determine the exit potential of the product (in our case, efficiency in yields and market attractiveness) was the main focus of attention. the analysis indicated that anacardium occidentale is appropriate for exploitation. its crop yields are attractive; for example, in favorable conditions it is possible to harvest approximately 1.4 ton/ha starting from the second year sown. the analysis determined that up to 28 ton/ha of production could be obtained after the 5th year sown. concerning the other key factor, the product has a high market value; its commercial value could reach $221,760 mxp or 16,234 usd (bank of mexico, 36 2011) per hectare with a cost to the producer of $7,920 mxp or 580 usd per ton. continuing with the methodology proposed, an initial analysis of commercial feasibility was performed; possible success or failure of the project determined considering potential attributes for market commercialization. the results of this task helped to create a better strategy for the subsequent correct conceptualization of the product in the market. we also found that the product has a high attractive potential in terms of yield production, price per ton, and commercial value, in relation to other existing crops in veracruz (figure 5). it is also possible to commercialize different products from it. cashew nut is the main product of anacardium, which is widely consumed as a snack and for the elaboration of pastries. fresh and dried nuts total an annual worldwide demand of about 750,000 ton. unfortunately, there are no regional statistics on demand in mexico. there are no statistics concerning exploitation of the other parts of the plant either. this is one of the barriers that the project had to face: the scarcity of detailed information about the fruit. however, after a primary investigation with food engineers, biochemical engineers, farmers, companies and potential clients, we found interesting insights concerning the potential diversity of the plant. leaves and flowers can be used for the elaboration of teas and essential oils; seeds for the elaboration of stabilizers, margarines, condiments and ingredients for health treatments (mainly ulcers and scars). the fruit peel can be an ingredient in salads, juices, candies, cosmetic products and treatments for respiratory and gastrointestinal diseases. figure 5: comparative economic evaluation according to bank of mexico september 2011 the subsequent stage of the proposed approach concerns the strategic profile. this task creates a frame of reference where the key attributes of the project can be identified as the basis that the company will use to define the next competitive strategies. for this, critical factors for success need to be determined considering competitors, performance and events in the environment. regarding the project, this stage was conducted to identify the variables relative to the crops conditions and performance in terms of production, capacity of industrial diversification, total estimated market value and comparative economic evaluation crop yield (ton/ ha) price per ton (usd) commercial value ($usd/ha) papaya 39.28 204.00 8,009.00 orange 12.82 140.00 1,791.00 sugarcane 65.27 21.00 1,392.00 corn 2.15 176.00 379.00 anacardium occidentale 28 580.00 16,234.00 maracuyá 8.16 588.00 4,779.00 pitahaya 5.28 398.00 2,094.00 dominical banana 15.3 132.00 2,016.00 guanábana 7.46 212.00 1,573.00 vanilla 2.5 1,533.00 3,816.00 robusta coffee 1.68 2,647.00 4,427.50 pepper 3.08 391.00 1,200.00 macadamia 3.88 682.00 2,646.00 ginger 13 147.00 1903.00 anthurium 6.67 159.00 1,055.00 palm oil 20 53.00 1,054.00 37 potential net benefit. this information provided a clearer visualization of the critical success factors that would distinguish anacardium occidental from the rest of the crops in veracruz. due to the strategic value of this information, it is not possible to reveal all insights obtained here, but we can show some details in the next step, the four actions scheme (figure 6). this activity defines the factors that should be created, increased, reduced or eliminated in order to gain competitiveness. figure 6: four actions scheme as shown in figure 6, the following actions were determined for the project: 1) reducing time of crops, 2) creating different products (food, cosmetics and health treatment), 3) increasing net benefit to consumer as well as increasing crop production, and 4) eliminating pests and scraps. as we have mentioned before, the most important attribute of the plant is its diversification capacity to develop into different natural products. in order to follow the four actions scheme, several elements are necessary, for example: farmers should have specialized technical assistance, access to economic resources and equipment needed to manufacture different kinds of products. the analysis showed that production could start with small quantities, with a small investment and a better distribution of the resources that are already accessible to farmers. we saw that sometimes resources are focused on traditional crops, where utilities are minimal. while as information was validated and checked for accuracy in previous stages, it is important to make an extra revision before the diffusion of the results, including verification of data interpretation with key people involved in the project. once final results are determined, they should be disseminated in terms of appropriate content, format and time according to the needs of the client. with reference to this project, results were analyzed by potential investors. as a result, some farmers with a strong interest in the production and commercialization of anacardium and its products were identified. decision making is the last stage of the first phase: understanding opportunities from the methodology. it consists of the final decision by the company of whether to proceed with the next phase of the project or not: strategic development. the methodology is developed in form of a cycle, implying that interactions are important between all 38 and for all of the steps. moreover, the results obtained at the end of the phase understanding opportunity can be used for other projects in the identification of other possible opportunities to investigate. 6. conclusions the model proposed based on the integration of competitive and technical intelligence with blue ocean strategy (figure 3) provides a new perspective for the identification of new businesses to explore. in our case, support from a major academic institution is essential for exploiting new market niches in regions which lack the resources. this is the case of agriculture in the southern region of veracruz, mexico. the proposed approach represents an interesting opportunity, since many mexican companies are preoccupied with their day-to-day competitive problems in already established markets. awareness concerning the importance of future prevision and management of innovation are areas which are lacking. a common cause of this is insufficient resources (economic, human, methodological, etc.). while companies interested in investing in new approaches, such as the one proposed here, are easier to find in more developed industries, the agricultural sector has traditionally been far behind. however, given the excellent natural resources present in the regions studied, this was an excellent opportunity to consider. from a general point of view, with the application of the proposed methodology, the following benefits were identified: • identification of critical factors for success: high diversification capacity, adequate regional weather, extensive crop surface, high yield production and possibility of scraps exploitation • identification of opportunities and threats, as well as favorable or unfavorable factors that can significantly affect the business • estimation of the feasibility of a business idea taking into account the market potential and the availability of resources. for future research, the application of the second stage in our plan is recommended: strategic development, to develop a desirable concept for a particular product, considering aspects such as: uses (in this project, this includes food, cosmetics and medicinal products), performance, presentation, design and production. in order to accomplish this task the following stages should be developed: determination of the utility generated to the client (for example from the sales process, product delivery, complements offered, etc.), definition of a price strategy policy, fixation of a minimum cost (analysis of alternatives to reduce costs involved in the principal operations of the business), establishment of a product adoption strategy and analysis of the organizational structure. further stages will define the concept implementation activity, which represents the final characteristics definition before launching a new product. finally, this project opened for other opportunities to expand activities in the competitive technical intelligence (cti) domain. when the methodology becomes more available new advantages may emerge in other areas. companies in development can have access to highly trained personnel from academic institutions. these institutions provide broad information resources and new approaches for uncovering business opportunities. proof of this was revealed through the anacardium occidental project. references ashton, b., and klavans, a. 1997. in keeping abreast of science and technology, technical intelligence for business. columbus, ohio: battelle press. bank of mexico 2011. dollar exchange. retrieved september 2011. available online url: http://www.banxico.org.mx/portal-mercadocambiario/index.html bos 2011. about blue ocean strategy. available online 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at: https://ojs.hh.se/ pp. 38–53 the effect of marketing intelligence adoption of banks listed in the egyptian stock exchange shereen aly abstract. the purpose of this study is to examine the effect of marketing intelligence (mi) stock exchange. a statistical analysis was carried based on data collected, using a questionnaire 12 central banks adopting mi and listed in the egyptian stock exchange were measured during the period (2012–2021). then, statistical analysis was conducted based on data collected using the egyptian stock exchange. keywords. return on assets (roa) 1. introduction the egyptian banking sector is one of the huge service sectors that contribute to egypt’s economic growth, creating around a third of sector operates in a fast changing environment characterized with highly competitive market. moreover, the competitive pressure intensively increased due to the penetration of foreign and private banks to the egyptian market. and thangaraja, 2016, p. 756). intensifying competition forced banks operating in egypt to offer more technologically – based services in order to better serve their customers including automated teller machines (atms), plastic cards, mobile banking, internet banking, and electronic fund bagga, 2020, p. 5, ismaeel and alzubi, 2020, et al., 2014, p. 84). therefore, the banks operating in egypt are required to adapt to that highly competitive market and respond to these rapid changes in the marketplace. in the light of severe competition between banks operating in the egyptian market, the adoption of mi within banks was absolutely necessary, in order to be able to respond to the market pressures and compete with larger majority of banks operating in egypt have adopted mi. this study focuses on 12 central banks adopting mi and listed in the egyptian stock exchange. mi adoption was the key to success for those 12 banks listed in the egyptian stock exchange, in terms of managing their marketing activities, as well as analyzing large amount of marketing information gathered about their customers, competitors, and 39 banks to predict their customers’ needs and interests, know their competitors, and analyze the internal and external marketing environment to determine their strengths, weaknesses, 2020, p. 1236). essential tool used by banks’ management to of those 12 banks listed in the egyptian stock exchange and make decisions related to their analysis allows banks’ management to anaprovides them with a deep understanding on to evaluate their banks’ performance. (san and often called ratio analysis. (lipunga, 2014, of those 12 banks adopting mi and listed in on equity (roe) and return on assets (roa). 2. theoretical framework (mi) of them include: “marketing intelligence is the process of collecting daily information about important developments in the marketing environment that help managers to set, adjust, and update marketing plans”. and thangaraja (2016) added that “marketing intelligence is the continuous and systematic collection and analysis of everyday information about any changes occurring in the company’s marketing environment including competitors, attitudes, or buying behavior for the purpose of helping managers to better understand what is happening in the market and the available market opportunities. this in turn will help managers to make effective and accurate decican be viewed as a continuing and interacting structure of people, equipment, and procedures that are responsible for gathering, sorting, analyzing, and distributing pertinent, timely, and accurate information that help decision makers to improve their marketing planning, intelligence refers to the information, primarily quantitative in nature, that organizations gather through direct interaction and dialogue with market participants including customers, competitors, suppliers, sales force, social media, blogs, internet, or any combination of these in order to produce actionable insights for decision makers”. to scan, monitor, analyze, and evaluate marketing information gathered from all accessible points (internal and external marketing environment, marketing research, and market developments) in order to counteract on competitors’ actions and prevailing market conditions for improving the company’s competitive advantage and overall performance through enhanced and intelligent decision making”. 2.2 main dimensions of mi adoption sions or variables that constitute the adoption of mi. competitor intelligence customer intelligence product intelligence technology intelligence marketing environment intelligence marketing intelligence (mi) main dimensions of mi. 2.2.1 competitor intelligence: is the process of collecting and analyzing information about competitors, their trends, strategies, and future plans. this helps an organization to form a clear picture of the competitive environment where it works in, as well as helps it competitor intelligence is based on the ethical gathering of different types of information 40 including government records that are openly 2.2.2. customer intelligence: is the process of gathering and analyzing information about customers’ buying behavior, intentions, preferences, motivations, concerns, beliefs, and perceptions. this helps an organization to create will be able to produce the products that satisfy customers’ needs, as well as meet their expeclymperopoulos and chaniotakis, 2005, p. 485). 2.2.3 product intelligence: is the process of collecting and analyzing information about an organization’s products as well as about those of competitors. this provides an organization’s management team with deep insights about product development and innovation activities. product intelligence enables an organization to make individual product decisions including decisions about product attributes such as product quality, price, design, features, labeling, packaging, as well as after – sale services. ozturk et al., 2012, p. 231). 2.2.4 technology intelligence: is the process of identifying and analyzing the technological opportunities and threats that may affect an organization’s development. this helps an organization to understand what is going on in the surrounding world of technology, and adopt the technologies that help an organization to gain the most competitive advantage. the good technology intelligence provides an organization with a solid knowledge and support for planning and creating its own innovation path. 2013, p. 35, ozturk et al., 2012, p. 331). 2.2.5 marketing environment intelligence: mi goes beyond gathering information related to competitors and customers. it extends to gather information about the external marketing environment of an organization. the marketing environment intelligence aims at identifying the opportunities as well as the threats an organization faces in the external marketing environment. mi works to take advantage of the available opportunities and overcome the threats as well as try to turn them into investment opportunities. due to global competition and the complexity of surpredict the events surrounding the organization. mi reduces the environmental uncertainty through continuous monitoring of events that help to receive signals about any changes in the environment. this in turn leads to excellence and competitive advantage. (ismaeel p. 231). 2.3 importance of mi adoption ing intelligence within any organization stems from its crucial role in performing the following functions: mi gathers daily information on all developments in the marketing environment which help managers to design and modmi is an important tool for gathering relevant information that help marketing managers to improve decision making under different conditions including certainty, uncertainty, and p. 25). mi is a future – oriented activity that helps managers in predicting and planning for the future reactions of competitors. this enables managers to overcome threats and avoid risks of competitors early, as well as exploit available opportunities in the marketreduce the astonishments and the employees’ inability against environmental changes, as well as minimizes the company’s exposure to environmental risks and danger. (al-weshah, marketing managers to identify the organization’s target market, and provides insights 41 about both current and potential customers who are predisposed to buy the organization’s products/services. this will guide organizations in directing their marketing activities to the right target market. moreover, mi helps to analyze consumer buying behavior. thus, an organization can produce the products that only satisfy and meet consumers’ needs and wants. p. 1005). mi helps marketing managers to create long-term relationships with customers, manage customer relationships, which results in increasing customers’ satisfaction, loyalty, retention, and positive word of mouth. (carson of mi is vital in shaping an organization’s competitive advantage. mi helps an organization to compete with other organizations, by providing it with relevant information about its competitors. this helps an organization to expect it competitors’ reactions and be able to plan for the next strategic moves. (carson et al., 2014, p. 27). mi contributes to improving an organizations performance due to its effect on enhanced market share. (ismaeel and alzubi, p. 2). mi plays an important role in encouraging innovation and creativity. the emergence of creative ideas from using mi helps an organization to produce new products and enter new markets. this results in improving an organization’s competitive position. thereby, it can survive and grow in competitive markets helps an organization to analyze the marketing environment. this in turn enables marketing managers to identify the organization’s strengths, weaknesses, opportunities, and threats (swot analysis). also, mi helps in formulating the market penetration strategy, as well as market segmentation and market development strategies. (maria et al., 2020, et al., 2012, p. 228). the banking sector is the most important segp. 649). moreover, banks play a crucial role in the economic resource allocation of countries by chanelling funds from depositors to investors continuously. they offer all important services including providing deposits and loan facilities for personal and corporate customers, making credit and liquidity available under different market conditions, and providing access to the nations payment systems. added that the health of the nation’s economy is closely and positively related to the soundness of its banking system. a highly developed banking sector plays an important role in promoting the whole country’s economic growth. cial performance of banks reward the shareholders for their investment and stimulates additional investment which will bring further economic growth. on the other hand, poor performance of banks may lead to their which will have negative consequences on ecothe soundness of the banks depends greatly cates into either the strength or the weakness is one of the essential conditions for maintaining the stability of banking system, this study the different performance measures of the banks which can be analyzed. (akbas, 2012, p. 104). a bank in generating earnings. (lipunga, 2014, of banks contributes to the economic development of the entire nation by providing additional employment and tax revenues to the gov42 to the income of investors by having a higher dividend, and thereby improve the standard of a number of previous studies argued that there found to be the most generally used methods. and accounting information, which in turn provides managers a deep understanding of mance. this study as well as previous studies indicators: return on equity (roe) and return on assets (roa). roe and roa are the most 3. methodology and data 3.1 hypotheses development this study examines the effect of mi adoption banks adopting mi and listed in the egyptian stock exchange. the following section presents the development of the main hypothesis based on the relationship between mi adoption and mi and listed in the egyptian stock exchange. help the bank’s management in the decision making process of the bank’s operations, as well as maintaining providing the management with concrete and jolevski, 2017, p. 7). in particular, the value of for any changes that may occur in the bank’s p. 231). based on the above discussion, the following main hypothesis is proposed: (a) return on equity (roe): there are varindicators. this study focuses on using two them includes return on equity (roe). the following section presents the development of roe = net income average total equity return on equity is considered as an importroe is calculated as dividing net income (or this indicator is most often shown in percentper dollar of book equity capital. roe shows erable, as it implies that the management is and generating revenues to shareholders. thus, is the bank. this indicates into a more powerper unit of the invested capital. (asqar, 2022, 2015, p. 51). based on the above discussion, (b) return on assets (roa): a second alterbanks is return on assets (roa). the following section presents the development of the second sub-hypothesis: roa = net income average total assets 43 banks. it is used as a main indicator of the bank assets. this indicator is most often shown in percentage. it indicates into the returns genagement in converting bank’s assets into net able is the bank, and vice versa. roa is the best roa is not distorted by high equity multipliers. roa is also a proxy measure used to determine the bank’s ability to generate income a bank utilizes its total assets to achieve high ity from the perspective of shareholders, i.e. lipunga, 2014, p. 41). based on the above discussion, the second sub-hypothesis is proposed as follows: 3.2 measures on one hand, a questionnaire tool was used to measure the research independent variable which includes the mi adoption in 12 central banks adopting mi and listed in the egyptian stock exchange. the questionnaire was directed to people working within the information operationalization of the independent variables of mi. variable operational measure references mi adoption dichotomous variable indicating • customers evaluate the extent to which mi adoption helped the banks in predicting customers’ behaviors & directions, analyzing customers’ buying behavior, as well as determining customers’ needs, interests and preferences. maria et al., (2020), rao (2020), (2020), noviyanti et al. (2020), allymperopoulos and chaniotakis (2005). • product or service assess the extent to which mi adoption contributed to providing the banks with information about the current as well as the new banking services that can be provided to customers. shailza et al. (2020), kumar (2020), kant (2020), azeez (2020), inha dnd bohlin (2018), ade et al. (2017), igbaekemen (2014), ozturk et al. (2012). • analyzing the marketing environment the extent to which mi adoption helped the banks in analyzing the marketing environment in order to identify its strengths, determine its weaknesses, exploit the available opportunities, and overcome competitors’ threats. (2019), inha and bohlin (2018), ozturk et al. (2012). • competitive risks the extent to which mi adoption helped the banks in avoiding the risks of competitors, as well as analyzing any potential risks in the market. • information technology the extent to which mi adoption helped the banks in adopting the most advanced information technologies in the marketplace, which in turn contributed to gaining a competitive advantage in technology. shailza (2020), kamau and njugungo et al. (2012). 44 technology (it) department in those 12 banks. the questionnaire consists of questions with scale. in this study, all variables of mi adoption were developed based on an extensive literabeen concluded that mi adoption consists of service, analyzing the marketing environment, competitive risks, and information technology. consequently, the independent variables included in the present study have been adopted from measurements used in previous mi studies. operationalization of the study variables is summarized in table 1. the questionnaire was originally prepared in english and then translated into arabic. on the other hand, the research dependent variable which central banks was also measured. this study indicators: return on equity (roe) and return on assets (roa). the roe and roa were calthe adoption of mi (2012–2016) were compared after the adoption of mi (2017–2021) in each banks can be observed. this study extracts which include annual reports on the income statements and the balance sheets of those 12 cial statements of those 12 banks were drawn from egypt for information dissemination (egid), found in cairo, egypt. 3.3 the sample and response rate tiality of banks, the 12 central banks listed in the egyptian stock exchange are numbered from 1 to 12 instead of mentioning their names. the main concern of the present study is targeting the it people working within the information technology (it) department due to their great knowledge of mi adoption. there are nearly 40 people working within the it department in each of those 12 banks. based on the research population which consists of 480 people, the research sample size consists of 224 people which represent the minimum sample size. the simple random sampling technique was the most suitable one for this research. the questionnaire was distributed to 320 people working within the information technology (it) department in the 12 central banks adopting mi and listed in the egyptian stock exchange. 80 questionnaires were excluded and removed from the sample for being largely incomplete, and only 240 out of 320 were collected. the remaining 240 usable question75%, which was considered highly reasonable with regard to mi adoption studies. 4. data analysis and results 4.1 validity and reliability to measure the validity and reliability of the constructs of the questionnaire instrument, exhaustive literature review was carried out to identify the constructs and items that were used in the previous studies related to mi adoption. secondly, a wide range of items were selected included in the present study. thirdly, an initial version of the questionnaire was prepared in english, and then translated into arabic. directing the questionnaire to 25 it staff working in different banks operating in egypt. relaying on their comments and recommendations, some questions and items was deleted improve the clarity and relevance of the quesability of the questionnaire, cronbach’s was computed to evaluate the internal consistency pendent variable used in the present study. the results presented in table 2 indicate that ability of questions, as it ranges between 0.526 and 0.657, with p-value < 0.001. therefore, cronbach’s alpha p-value customers 0.526 <0.001 product/service 0.608 <0.001 analyzing the marketing environment 0.612 <0.001 competitive risks 0.645 <0.001 information technology 0.657 <0.001 45 4.2 descriptive statistics of the independent variables the independent variable of the study is repproduct, analyzing the marketing environment, competitive risks, and information technology. as shown in table 3, the mean values of all variables are ranged between 3.67 and 4.89, indicating that the respondents tend to agree or strongly agree to most of the statements that measure these variables. table 3 reveals that the variable with the highest agreement and minimum variation (s.d. = 0.12) is the information technology. while the variable with the least agreement and maximum variation (s.d. = 0.35) is the competitive risks. besides, a comparison was conducted between the 12 central banks listed in the egyptian stock exchange, in order to determine the differences among the 12 banks in each bank. the comparison is based on the 5 uct/service, analyzing the marketing environment, competitive risks, and information technology. the results of comparison are sumthe results indicate that all the 12 central cates that those banks have adopted the mi in 9, 2 and 10 respectively come later, which indicates that those banks have adopted the mi cient way. table 4 also reveals the differences between the 5 main variables of mi adoption for each bank. in general, the information technology variable (97.85%) the most important variable in the mi adoption, followed by product/service (90.60%), followed by customers (87.70%), followed by analyzing the marketing descriptive statistics of the independent variables. variable n minimum maximum mean std. deviation customers 214 3.70 4.80 4.3766 0.24034 product/service 214 4.20 5.00 4.5234 0.14410 analyzing the marketing environment 214 3.73 4.73 4.2260 0.19415 competitive risks 214 3.00 4.83 3.6721 0.35434 information technology 214 4.60 5.00 4.8925 0.12349 comparison among 12 banks based on the 5 variables of mi. mi variables bank number customers product or service analyzing the marketing environment competitive risks information technology total 1 83.47% 88.84% 85.26% 79.65% 96.84% 86.81% 2 85.64% 90.18% 85.45% 75.15% 95.45% 86.38% 3 84.90% 90.60% 87.64% 78.67% 97.80% 87.92% 4 87.22% 89.56% 85.56% 75.37% 98.00% 87.14% 5 86.90% 91.80% 84.64% 72.50% 97.60% 86.69% 6 89.05% 91.24% 79.65% 70.79% 97.14% 85.58% 7 88.82% 90.82% 84.17% 68.63% 99.76% 86.44% 8 89.44% 90.22% 82.93% 79.44% 97.33% 87.87% 9 88.96% 90.56% 85.82% 67.47% 99.20% 86.40% 10 88.91% 90.18% 83.80% 68.33% 100.00% 86.25% 11 90.20% 90.60% 87.00% 71.33% 97.20% 87.27% 12 88.78% 92.67% 86.36% 69.26% 97.78% 86.97% total 87.70% 90.60% 84.86% 72.89% 97.85% 86.78% 46 tive risks (72.89%). the results in table 4 have concluded that: based on the information techhas the ability to use information technology (95.45%). while, based on product/service variproduct/service is provided by bank 1 (88.84%). is the best bank in avoiding the competitive bank. a comparison between the 12 central banks adopting mi and listed in the egyptian stock exchange is illustrated in a bar chart, as the differences among those 12 banks in terms 4.3 descriptive statistics of the dependent variable the dependent variable of the study represents adopting mi and listed in the egyptian stock exchange. this study focuses on using 2 mea(roe) and return on assets (roa). as shown in before after roe roa roe roa mean 0.015983 0.1538 0.030067 0.2889 median 0.0155 0.156 0.03 0.2835 maximum 0.028 0.221 0.047 0.399 minimum 0.007 0.049 0.016 0.185 std. dev 0.006108 0.034597 0.006257 0.058848 38.2156 22.4948 20.81019 20.36968 skewness 0.216123 -0.498 0.073132 0.001873 kurtosis 1.770913 3.370287 3.032453 2.040236 jarque-bera 4.243727 2.822827 0.056116 2.302901 probability 0.119808 0.243798 0.972332 0.316178 mi% bank the percentage of mi adoption 47 table 5, the results indicate that all dependent variables whether before or after the adoption of mi, reveal small data distraction due to their whereby the standard deviation of this variation is less than the mean. table 5 also shows tor (roe) that was 0.015983 before mi adoption. while, after mi adoption, the mean values of roe raised to 0.030067, with a percentage of increase equals to 88%. similarly, the mean valwas 0.1538 before mi adoption, and raised to 0.2889 after mi adoption, with a percentage of increase equals to 88% as well. moreover, the mean values of roe and roa are very close to median values, which indicate that the distribution of these variables is symmetrical. in addition to skewness values which the minimum and maximum values of roe and roa are positive values, which indicate that all ratios, whether before or after mi adopthe results in table 5 indicate that all jarquebera statistical values are less than the tabumeans that all dependent variables follow normal distribution. this result is in compliance with the sig values (p-value > 5%). plots were conducted, and reveal that all data points are near or on the straight reference line, indicating that both roe and roa are normally distributed. moreover, the effect of mi adoption on roe and roa of 12 central banks adopting mi and listed in the egyptian show the effect of mi on roa. the roe and before the adoption of mi (2012–2016) were period after the adoption of mi (2017–2021). ing mi, and its effect was clearly observed on enhancing the roe and roa of the 12 banks after adopting the mi. the effect of mi adoption on roe. the effect of mi adoption on roa. 48 4.4 correlation analysis the correlation analysis of the variables of the study was conducted using pearson correlaand roa). the results of the correlation analysis are summarized in table 6. the results in between roe and mi adoption, since the value p-value < 0.001, and the strong positive correlation ranges between (0.7 and 1). table 6 a strong positive correlation between roa and mi adoption, since the value of pearson correlavariable mi pearson correlation p-value roe 0.816 < 0.001 roa 0.754 < 0.001 4.5 regression analysis this study aims to examine the effect of mi cators (roe and roa) of 12 central banks adopting mi and listed in the egyptian stock exchange. therefore, the simple linear regression model was used to test the two research sub-hypotheses. the independent variable (mi) will be expressed as dummy variable that takes the value 0 before the adoption, and takes the value 1 after the adoption. the following simple linear models were estimated as follows: 120. j = 1, 2, …, 10 120. j = 1, 2, …, 10 where roeij: denotes the ith observed value of roe within bank j. roaij: denotes the ith observed value of roa within bank j. miij: denotes the ith observed value of mi within bank j. reg.1 and reg.2 respectively. reg.1 and reg.2 respectively 4.5.1 the analysis of reg. 1 the main aim of the present study is to examine the effect of mi adoption on enhancing the return on equity (roe) of 12 central banks adopting mi and listed in the egyptian summarized in table 7. as shown in table 7, the roe of 12 banks adopting mi and listed in is 234.998 with p-value < 0.001. also, based on the value of adjusted r2 (0.663), this indicates model sum of squares df mean square f p-value regression 0.548 1 0.548 234.998 < 0.001 residual 0.275 118 0.002 total 0.823 119 r2 = 0.666 adjusted r2 = 0.663 std. error t p-value durbin watson dwlower limit upper limit constant 0.154 0.006 24.680 < 0.001 0.141 0.166 1.817 mi 0.135 0.009 15.330 < 0.001 0.118 0.153 49 that mi could infer 66.3% from the total variation of roe. in order to estimate the parameters of reg. 1, the ordinary least square estimation method (ols) was used, which is a parametric estimation method. table 8 summarizes table 8 indicate that there is a positive relation between mi and roe, and any change in the independent variable (mi) from 0 to 1 will lead to an increase of 0.135 in the predicted value of the roe. moreover, there is banks adopting mi and listed in the egyptian stock exchange, since (t-statistic = 15.33) with watson (1.817) indicates that there is no serial autocorrelation problem, as the value is near to 2. 4.5.2 the analysis of reg. 2 similarly, the same analysis of the previous sub-section was conducted in order to examine the effect of mi adoption on enhancing the return on assets (roa) of the 12 central banks adopting mi and listed in the egyptian marized in table 9. as illustrated in table 9, the roa of 12 central banks adopting mi and listed in the egyptian stock exchange, since, also, based on the value of adjusted r2 (0.565), this indicates that mi could infer 56.6% from the total variation of roa. table 10 summarizes the regression coefthere is a positive relation between mi and roa, and any change in the independent variable (mi) from 0 to 1 will lead to an increase of 0.014 in the predicted value of the roa. roa of 12 central banks adopting mi and listed in the egyptian stock exchange, since (t-statistic = 12.476) with p-value < 0.001 and conthe value of durbin watson (1.901) indicates that there is no serial autocorrelation problem, as the value is near to 2. according to all previous statistical analysis results, it can be concluded that the main hypothesis is rejected. 5. discussion the present study contributes to the existing literature of mi adoption and its effect 12 central banks adopting mi and listed in explores a new domain (egypt), and thereby of mi has emerged as a modern marketing system in most of banks operating in egypt. in this context, the present study aims to examine the effect of mi adoption on enhancing the profitability indicators of 12 central banks adopting mi and listed in the egyptian stock exchange. the results of the study indicated a strong positive relationship between mi adoption and model sum of squares df mean square f p-value regression 0.006 1 0.006 155.657 <0.001 residual 0.005 118 0.000 total 0.010 119 r2 = 0.569 adjusted r2 = 0.565 std.error t p-value durbin watson dwlower limit upper limit constant 0.061 0.001 20.024 <0.001 0.014 0.018 1.901 mi 0.014 0.001 12.476 <0.001 0.012 0.016 based on the above discussion, the second sub-hypothesis is rejected. 50 banks. moreover, the study provided empirical of those 12 banks. according to these results, central banks. as a result, the second sub-hyet al., 2013). despite the 12 central banks had adopted the mi, there were some differences of adopting the mi. a detailed analysis of the results revealed that the information technology variable was found to be the most variof those 12 central banks. this result supports et al., 2012. the following variable to enhancing banks was product/service. this was asserted by a great body of literature review (e.g.: shailza indicators of those 12 central banks was the customers variable. this result is in line with sevability indicators of the 12 central banks was analyzing the marketing environment. this supports the research results of other previous the 12 central banks was the competitive risks. this results was consistent with previous studit can be concluded that there are some banks others. as a result, the 12 central banks were the results indicated that bank 3, 8, 11, and bank 12, 1, 5, 7, 9, 2 and 10 respectively come cient way. 6. conclusion currently, the egyptian banking sector witnesses severe competitive pressure within the vast majority of banks are urged to adopt mi due its effect on improving operational itive advantage, increasing sales revenues, ing growth and survival in the marketplace. study through examining the effect of mi adopof 12 central banks adopting mi and listed in the egyptian stock exchange. the results roa) of those banks. this result is largely in ies related to mi adoption in different countries and contexts. this study contributes to both regarding knowledge, little research work has been carried out regarding mi adoption in the service sector and particularly within cerning mi adoption within the banks listed in the egyptian stock exchange. as for practice, marketing managers need to move theory into practice and gain better understanding of mi adoption process. in this context, the study provides guidelines for marketing managers to 51 that constitute and support the adoption of mi within any sector. these include: customers, product or service, analyzing the marketing environment, competitive risks, and information technology. 7. limitations and implications for future research the research on which this study is based, like much social science research, is affected by sevself – reports, which may produce bias. second, this study has been conducted in one country (egypt). moreover, the study focuses on one service sector (banking sector: only 12 central banks listed in the egyptian stock exchange). third, the present study aims to examine the effect of mi adoption on enhancing only 2 ings, future researches need to be carried out on many other dimensions such as bank performance including sales revenues, market share, and competitive advantage. successful mi adoption, marketing managers need to understand the main requirements of adopting mi. the following managerial implicommitment, support, and belief in the importance of adopting mi within banks. second, using the latest up-to-date information technology which is considered to be the backbone of mi adoption. third, mi adoption requires conducting effective training programs for all bank members especially it staff, on a regular in order to encourage and motivate the talent members for their devoted efforts. sixth, building cross-functional team-works that are highly skilled, experienced, competent, 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(2011), “application of business intelligence in the banking industry”, management information systems, vol. 6, no. 4, pp. 23–30. ing intelligence: antecedents and consequences”, 3rd internationl conference on innovative computing and communication, (icicc), pp. 1–9. performance: reviewing the mediating impact of customer relationships, customer satisfaction and customer loyalty”, indian journal of economics and business, vol. 18, no. 2, pp. 555–570. 59 o p i n i o n s e c t i o n the intelligence worker as a knowledge activist – an alternative view on intelligence by the use of burke’s pentad magnus hoppe mälardalen university school of business, society and engineering (est) p.o. box 883, 721 23 västerås, sweden magnus.hoppe@mdh.se received march 3 2013, accepted march 26 2013 abstract: as society and business is becoming more complex, the creation and management of knowledge attracts more attention. for intelligence research it offers an alternative perspective on the art and science of intelligence that challenges a previous dominance of strategy and decision-making theories. the article is based on semi-structured interviews with intelligence personnel in four different multinational companies. through the use of burke’s pentad this article gives an account of important challenges encountered by intelligence personnel in modern business organizations due to an increasing dependence on different knowledge processes. these challenges are summarized in four central tasks for knowledge activists; that is to initiate and focus knowledge creation, to reduce the time and cost needed for knowledge creation, to leverage knowledge creation initiatives throughout the corporation and to guide knowledge creation by the instigation of complementary reference points. by engaging in these types of activities intelligence workers are able to stage and influence different sorts of analytical conversations, where the insights from these conversations as reformed knowledge govern an evolving strategy in dispersed circumstances. thus, intelligence workers fulfil their purpose, which in this perspective can be viewed as creating better business in whatever process they engage in. keywords: knowledge activism, knowledge creation, knowledge management, organizational learning, organizational change, analytical conversation, complexity, burke’s pentad, competitive intelligence, organized intelligence work. available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2013) 59-68 mailto:magnus.hoppe@mdh.se https://ojs.hh.se/ 60 1. introduction technological and social changes make business environments less stable by the year, blurring our preconceived ideas of what constitutes an industry (bettis and hitt 1995). as early as 1965 emery and trist stated, ”a main problem in the study of organizational change is that the environmental contexts in which organizations exist are themselves changing at an increasing rate, and towards increasing complexity” (ibid, 24). since then the complexity of industries and their environments has come to interest an increasing number of academics (andersson 1999), who address questions of how to manoeuvre fragmented companies in a complex society. as well as these visible signs of industrial renewal, there are also more subtle changes in organizational processes and the way organizations function. many companies have turned to more knowledge intensive production, which has affected both core competencies and business design. thus management of different knowledge processes has become particularly important. this development challenges the idea of a central core controlling the organization like a machine. instead ideas have been launched where control can be executed through influencing the mind-set of organizational members (miller 1999). as røvik (2000) puts it: "leadership is increasingly a matter of coordination through mental manipulation as opposed to control of physical movements” (ibid, 279, author’s translation). strategic coordination through formal decisions is thus not enough, challenging traditional ideas of the mission and purpose of competitive intelligence, even though these ideas are still central in contemporary descriptions of intelligence (e.g. mcgonagle and vella 2012). knowledge, and a not unproblematic relationship to knowledge management, has interested intelligence theorists since the 1990’s at least (tuomi 1999). more recently intelligence theory has also come to acknowledge complexity as an issue for intelligence professionals and theory. gay (2012) points out that the new business circumstances that follow complexity ought to have effect on how to organize and implement intelligence. lópez et al. (2012) suggests that contextualisation of best practices in supply chain knowledge might counteract the strain that complexity puts on organizations. whereas el haddadi et al. (2011) argues that what used to be strategically planned now (due to increased complexity), to a greater extent, is limited to a strategic response, thus challenging ideas of proactivity. instead, the strategic response must connect to widespread knowledge renewal activities that enable the company to innovate. in line with this reasoning knowledge creation processes (oubrich 2011) has come to interest intelligence researchers along with organizational learning (steiner and ploder 2011) as well as a still vital interest in knowledge management (lópez et al. 2012, rothberg and erickson 2012). tuomi (1999) as well as ghannay and mamlouk (2012) argue that ci could be viewed as a subset of knowledge management, thus definitely changing the locus of intelligence from decision support to knowledge support. on the other hand there are arguments that even though the world changes, the need for good decision support is still a vital task for intelligence professionals (mcgonagle and vella 2012). nan bulger (2013), executive director of scip, emphasizes this view: “whether you are a practitioner, an academic, or a consultant focused on a myriad of business operational disciplines, the need for applied methods to garner and use intelligence in decision support remains.” taking a decisional view, we can conclude that the increasing complexity is a real challenge for companies’ decision makers, not only at the top level, but throughout entire organizations. an increasing number of strategic decisions are now made outside the control of top management, a phenomenon that was also noted by emery and trist in 1965 (cf. eisenhardt 1989). for companies, the current situation makes new demands on internal services and functions that can help various decision makers and others to not only make informed decisions but also coordinate the decisions and actions taken with the rest of the organization; organizational entities that help leadership to coordinate organizational action. in knowledge based companies this demand expands the managerial dimension of a firm to other people and processes, so that the knowledge developed and applied is informed and coordinated. these types of assignments are now given to intelligence services and intelligence personnel inside business organizations; with their tradition of monitoring and analysing the environment they display the necessary competence. but it doesn’t end there. as intelligence is getting more dispersed, intelligence personnel encounter new intelligence needs and dilemmas, thus creating new opportunities for novel research. so far, the knowledge perspective has not been the pinnacle of intelligence research. instead the field is dominated by research objectives aiming at delivering practical advice for the practitioner, cf. rothberg and erickson 2012, solberg søilen 2005). this is partly due to the strong influence from consultants in the formative phases of the intelligence field in the 1980’s and onwards. the market for research favoured easily digested concept literature (jackson 2001) with authors like benjamin gilad (1988, 1996, 2003, 2006) and leonard fuld (1995, 2006). 61 the traditional writing was usually done in a managerial tradition (cf. furusten 1999), where analytical methods for strategic decision making are given emphasis, carrying with them a traditional hierarchical view of how organizations function (cf. mcgonagle and vella 2012). this tradition has favoured a view on strategy as design where managers are in control of the organization (mintzberg et al. 1998), overshadowing other views on strategy and organization. the dominance of this perspective is also due to a strong influence from military intelligence traditions (e.g. meyer 1987, wilensky 1967). what’s also noticeable is that the emergence of the intelligence field coincided with theoretical ideas of strategy planning, especially made popular by michael porter in the 1980s. porters (1980, 1985) value chain analysis respectively five forces model still attract attention today as it indirectly calls for internal and external intelligence. in this theoretical tradition analysis of the business environment is judged to be the core competence of management as it enables managers to create strategy and design the organization by informed decisions about a specific market position to aim for and defend. accordingly managers also need analysis support, upholding a perspective that emphasises the intelligence practitioners’ analytical skills and downplaying other aspects of the work. the increasing complexity in both business design and society has thus far not led to a major reformation of this dominant view of intelligence. as stated, there are emergent research initiatives that could introduced alternative descriptions of intelligence, uncovering important dimensions and aspects that will help form an intelligence science. especially knowledge management and knowledge creation are deemed promising for this advancement (cf. rothberg and erickson 2012). in line with this reasoning we provide here an exploration of questions and problems that could be fruitful areas for new research on intelligence, especially considering knowledge aspects. this leads me to phrase the purpose of this article as follows: to give an account of important challenges encountered by intelligence personnel in modern business organizations due to an increasing dependence on different knowledge processes. 2. method and materials the empirical material consists of a total of 18 semi-structured and transcribed interviews, mainly with intelligence professionals (but also in one case [case 1] people in the surrounding organization) spanning four different large multinational companies (all referred to by pseudonyms c1-c4 in this article). all companies studied were very well experienced in the organization and use of intelligence, and had a back log of organized intelligence work since the 1990s or even longer. c1 (case 1) is a global pharmaceutical company, and interviews were conducted at their country headquarters. c2 (case 2) is a global electronic company, and interviews were also conducted at their country headquarters. c3 (case 3) is a global packaging company, and interviews were conducted at the country headquarters. c4 (case 4) is a subsidiary of a european chemical company with a global market, interviews were conducted at the headquarters of the country subsidiary. complimentary research material was gathered e.g. through emails and company websites, as well as through discussions with various intelligence professionals at conferences and other gatherings. the analytical constructs presented in this article are developed inductively, and made visible through the transcription and coding process of the material as well as the intellectual process of making sense of the material at hand. burke’s pentad (burke and gusfield 1989) was used as an organizing tool for the sense-making part, where the pentad was adapted to suit the specific circumstances of this paper. the drama-metaphor emanating from burke is used to make some of the points under discussion stand out. the empirical material is presented in aggregated form. the paper begins with an explorative section, presenting the initial findings. these findings are used in the later section to build a discussion around the challenges now facing intelligence personnel, thus addressing the stated purpose of this article. 3. results from the data at hand, several aspects of intelligence emerge as interesting candidates to meet the stated purpose. in the sections below i will elaborate on five themes based on burke’s pentad, where purpose, scene, agent, and agency are presented under results but the actual act is the theme for the discussion. the paper ends by raising questions about the type of play we are witnessing and the challenges this creates for the actors, which in this case equals intelligence personnel. the themes presented are of course intertwined, and aspects of each theme can be found under different headings. 3.1 purpose: intelligence in order to create better business the interviewees described their work as mainly consisting of gathering, analyzing and disseminating information in order to support decision-making in general. the interviewees still used the term decision support while describing their work, even though the decisions to be made were not that well defined or were not clear-cut decisions. if we limited ourselves to the self-descriptions of the interviewees we would most likely come pretty close to 62 traditional ideas of strategy making and ideals of informed decisions. even though this self-description of intelligence and decision support was more or less generic, there were other aspects of their work that transcended this quite limited sphere of activity. the missions guiding the work were not focused on decisions. instead they were about supporting a special part of the company or a specific process. an analyst at c2 pointed out that their mission functioned as a good guideline for what to do and what to strive for; phrasing the mission as follows "our mission is to support the sales force with competitive knowledge and arguments in order to win the deal, and do profitable business." with missions like the one cited intelligence practitioners were encouraged to try different methods and techniques to expand their scope of work, e.g. to create and stage war stories that forced those involved to reflect and act in simulated business situations (cf. oubrich 2011). except for financial and moral considerations, the interviewees did not mention any real limitations to the scope of their work. in this respect the decision-making selfreference did not constitute an obstacle to expanding their field of practice. decision support therefore appears to be an important idea for defining the intelligence identity, but the missions given guide the practice, and these missions are, to put it simply, about creating better business. 3.2 scene: dispersed intelligence intelligence had more than one place (scene) in each of the researched organizations. it was dispersed around the organizations and could be found e.g. in the central core, subsidiaries and connected to designated project teams. intelligence units mostly worked independently of one another, serving their specific part of the organization. the c1 unit concentrated on promoting marketing issues and filling information and analytical gaps in different project teams. the c2 unit concentrated on supporting key account managers who would give c2 the upper hand in future deals. the c3 unit concentrated on identifying and making use of new ideas and technology in support of the r&d part of the organization. the c4 unit, located in a subsidiary, concentrated on handling strategic issues arising from all over the organization in an effort to help almost anyone who was in need. the context and the mission descriptions differed, but regardless of the particular context (scene) all interviewees classified themselves as intelligence practitioners. there was collaboration between intelligence units at each investigated company, e.g. for buying information or skill training, but the collaboration was a result of common interests more than a coordination effort designed by a central intelligence manager. whereas most collaboration was within the boundaries of each organization, the unit at c4 collaborated with units at other subsidiaries and at headquarters (cf. steiner and ploder 2011). even though the intelligence workers interviewed worked in dispersed circumstances, their stories contained passages that made it clear that the top levels of the investigated organizations had their own designated intelligence services. however, these intelligence units assigned to top management worked independently from the others, answering to the local needs expressed and experienced in the interfaces developed between supporters and those supported. one exception to this was occasional strategic overviews and projects where crossfunctional teams of intelligence personnel were formed, working together towards common goals for a limited time. in these specific situations hierarchical order emerged as important in defining the work to be done. this however was the exception to the rule. thus, intelligence in this study appears to be locally organized, and close to those designated to benefit from the service. intelligence also plays out more as a loosely coupled network of distinct units and less as a hierarchically organized and coherent support structure for a central core. rothberg and erickson (2012) state that this type of independent and distributed intelligence is a sign of a more mature intelligence organization that over the years has been able to develop more effective processes. it is also a type of intelligence more common in high-value knowledge industries, which in the citation under the previous heading also is visible in the informant’s choice of words. he does not simply use “competitive intelligence” but instead “competitive knowledge and arguments”, referring to something else than just decision support. together with complementary descriptions of how intelligence is used to enhance a specific knowledge need, one is inclined to say that when the intelligence organization matures, it is moving away from the tight leash of decision support defined by the hierarchical system, towards a position where intelligence functions as knowledge support is defined by the parties involved. 3.3 agent: serving the willing traditionally, intelligence is described as a function that works on the demands from the decisionmakers they are to serve. there is a clear distinction between those who experience and express an informational need and those who act to satisfy this need. in the common visualization of the intelligence process below (figure 1) the planning task is the prerogative of decision makers and the three other tasks are the responsibility of the intelligence unit (cf. mcgonagle and vella 2012). 63 figure 1: the intelligence cycle (traditional) conceptually the model is quite correct. unfortunately it describes the intelligence process on a simplified organizational level and not on a complex individual level. with the model the organization appears to be a coherent whole with a common mind, where the brain controls the limbs. this description has its roots in ideas emanating from taylorism and fayolism, with clear functional divisions between employees, which in a complex knowledge economy stand out as quite obsolete. today it’s more common to view organization as a network of loose connections between individuals, where the individuals are limited to a most personal quest of making sense of the world no matter what official function they uphold (hamrefors 1999). turning to the data at hand, and as mentioned earlier, there was no clear distinction between those who did the planning and those who did the fieldwork. instead the division appeared to be nonexistent as both intelligence personnel and intelligence users cooperated to complete the tasks they identified. thus, we have the combining of efforts of understanding and refining the question and making sense of the world. occasionally there were clear-cut assignments, but most of the time the experienced and expressed need was something that evolved through discussion between the parties involved (cf. treverton 2004). i would like to stress here that the active party was usually not the information user/decision maker, but rather the intelligence worker. interviewees frequently revisited the fact that they had to market their services internally to their intended users. it was also common that intelligence personnel went on road trips to different countries, invited themselves to meetings, and laid out plans how to reach certain people internally who they felt had something to gain through their work (but also in some cases were believed to be in possession of valuable information/knowledge that could be put to use elsewhere in the organization). in conclusion, we find that intelligence work is not so much passively awaiting requests from designated end-users than actively influencing parties in the organization that will help the intelligence workers reach important goals targeted by them in their quest of fulfilling their mission of creating better business. therefore intelligence workers are limited to serve those who are willing. the role of the agent can also be said to shift depending on purpose, scene and how the agency has developed, but nonthe less the interviewees classified themselves as intelligence practitioners. 3.4 agency: analytical conversations describing their work, the interviewees favoured stories involving actions like scouting, informing, providing a second opinion, and working as internal consultants. however none of these descriptions stands out as well as analyzing, a verb used frequently throughout the interviews. scrutinizing the data, one can also conclude that most of the time the interviewees’ work (and thus analysis) was focused on issues other than those directly connected to decision-making. instead, much of their work and the artefacts produced were for wider purposes. routine tasks included organizing and participating in discussions, updating standard analysis of particular market sectors, checking and making sense of rumours, and keeping files and profiles on competitors. so, if decision support is not enough to define intelligence and many other activities are being performed in order to fulfil the overarching goal of creating better business, are there other and possibly better ways to understand intelligence? i believe there are. here i suggest that instead of paying too much attention to the intelligence workers’ selfplanning / direction dissemination information retrieval / collection analysis 64 descriptions and the specific artefacts being produced, we should consider both what happens around these artefacts and around the practitioners themselves. taking this leap of mind brings us to a another perspective that focuses on the interaction among organizational members, where different intelligence artefacts and intelligence initiatives can be viewed as created reference points for continuous reflection and action in order to build better business (cf. argyris and schön 1995). by continuous interaction as well as the creation and maintenance of intelligence artefacts intelligence personnel influence what’s being discussed inside the organization. henceforth they are turning organizational attention towards certain aspects and away from others, and when organizational members’ ideas and experiences are affected we can also say that their knowledge has been manipulated. as noted above intelligence literature favours a description of intelligence as a service working on the command of decision makers, preferably defined through the use of models like the one shown in figure 1. in this model analysis is the third step in the process of developing raw information into intelligence (principally as intelligence artefacts). when the analytical step is completed the constructed intelligence is ready to be disseminated to the decision maker, hopefully fulfilling the information need that triggered the intelligence process in the first place. turning to the cases, this description is to some extent true, where e.g. at c1 different people and projects turned to their designated intelligence service with requests for intelligence (especially frequent in areas where they lacked necessary expertise or when they experienced time restraints). in these cases the intelligence personnel were also adding value by giving voice to facts and perspectives not present in the requesters frame of reference. nevertheless, even in these specific cases most of the intelligence workers were active in both defining the request as such and in building a common idea of how to perform the quest, depending on the insights that were gained in the process. those who expressed this intelligence need were mostly also involved in fulfilling it throughout the process. there was not just initiation and delivery; there was continuous dialogue throughout a sensemaking process where both parties (and others) performed tasks that helped solve the identified intelligence / knowledge need (cf. treverton 2004). a technical scout at c3 expressed that an important part of his job was to stage interesting discussions and processes so that a rough idea could develop into something useful for the company. different people from both inside and outside the company took part in these analytical discussions as the idea evolved, formalizing itself into an action plan with the objective of making the company more viable, e.g. through a better process, product or service. the responsibility and organizational home of the idea (and thus the discussion) also changed during the process through mutual adaptation. the technical scout’s actions were congruent with his overall organizational mission of creating better business, and were not limited to a clearly defined place in an organizational chart or a sequence in a model for intelligence creation. another example of how analytical discussions emerged as the core process for intelligence workers was given by an analyst at c2. he expressed that different analytical models of course came in handy in order to create all sorts of templates and texts, but as he pointed out, this was not the end goal. instead he emphasized that the most important outcome of using a model was the discussion that it triggered. in these examples we see that an organization is in fact a place for organizing, and that organizing is an on-going matter between organizational members, especially synchronized through speech and other communicative tools. formalities like organizational charts, work descriptions and even standard intelligence artefacts are just tools that help us keep some sort of order in the organization (or at least give the impression that order exists, cf. brunsson 2002, 2006, røvik 2000). however all these things, though useful for understanding an organization, do not reveal the true organization. instead, the organization is always an act of becoming, where those with the position and ability to influence play an important role. the intelligence services, as described in my study, can in this perspective be regarded as specific organizational entities with a mission to influence those knowledge structures that guide behavior in designated business processes. this is quite the opposite to a more traditional view on intelligence services as passive producers of intelligence artifacts. the problem with the latter position is that it limits the role of the intelligence worker to that of a bystander, with no interest of his or her own, not participating in the organizational power games, and working on the whims of others. as my study show, this description unnecessarily limits our understanding of how intelligence affects organizational behavior. the knowledge perspective is in this case better as it opens up for complementary views and ideas of how intelligence can support different business processes. this is to a large extent done by facilitating and even staging analytical discussions that intelligence personnel think will be fruitful for themselves (fulfilling their mission) and other participants. the use of analysis thus resembles the use of scenarios, which kees van der heijden (2005) describes as the art of strategic conversation. the scenarios and the analytical artifact fulfill the same purpose as they force us to 65 communicate and build common ideas of what’s important inside and outside the company. intelligence thus complements long-term strategic conversation fueled by scenarios with a more shortterm analytical conversation fueled by the supply of complementary reference points. by doing this, intelligence also helps the organization to create new knowledge in order to fulfill the mission of the company. 4. discussion: act! so what is the act? what do we see in the scene where the intelligence workers operate? i see a different kind of play to that most authors in the field traditionally chose to present. to begin the discussion i will present four different aspects (table 1) of how intelligence work appears in my study in relation to how it has traditionally been described. building on the ideas of burke, i have also constructed a drama metaphor to make each aspect clearer. change in appearance as descriptive text change in appearance as drama-metaphor the intelligence mission has changed from being a passive information service working on the command of high-ranking decision makers to an active internal agent for better business. intelligence workers are not reading from a script, they are improvising around a specific topic. hierarchical position does not determine where intelligence is to be found. instead the deployment of intelligence comes from dispersed needs displayed in each unique subpart of an organization. intelligence workers have now left the dramatic institute in favour of being a travelling theatrical company. intelligence work moves away from the creation of intelligence artefacts to the creation of analytical conversations and the advocacy of distinct reference points in these conversations. the distinction between actors and audience dissolves to the extent that together they define the play as they speak. intelligence is personalized in two dimensions, firstly the analyst comes forth as an individual agent with a personal network, and secondly the intelligence produced is adapted to the individuals and the specific situation at hand. at least compared to older plays involving the whole ensemble, intelligence is becoming more personal. table 1: summary of how intelligence appears in my study in relation to the traditional view, presented both as a descriptive text and as a drama-metaphor. with reference to the results presented above and these four points one can conclude that intelligence of today deals less with formal decisions and more with both formal and informal analytical conversations. this change of focus also moves the subject of intelligence away from decision making towards the field of knowledge creation (cf. oubrich 2011). it is hard to distinguish whether this has to do with real changes in the practice of intelligence or if these changes can be traced back to a more paradigmatic change in society. perhaps we have just learned to both see and speak about aspects of intelligence that were already present earlier when we didn't have the perspective and words needed to describe them. one could also object that the data used is skewed and/or that the intelligence presented above is culturally dependent where scandinavian intelligence practice always has been more democratically organized and less formal. nevertheless, we can at least say that the practice of intelligence described above fits well into the knowledge discourse that has developed alongside changes in industrial logics and increasing complexity in recent decades. it also seems that intelligence has a role to play in today's knowledge based industries, supporting more balanced and profitable knowledge constructs, thereby contributing to developing more viable businesses. even if it is just a scandinavian model for intelligence, it is still something to reflect on when considering how we should organize intelligence in a more knowledge intense world with blurred industrial borders. working so closely with information and analysis one might have suspected that intelligence practitioners would also use the term knowledge in defining the purpose of their work. the word knowledge was employed on and off (cf. the citation above), 66 but in an everyday fashion where knowledge appears synonymous with aggregated or analysed information. the intelligence workers did not call their work knowledge management (cf. pirttimäki 2007), market analysis or anything along those lines. instead they used the english term intelligence most of the time (even though the interviews where held in another tongue), but that should not hinder us from seeing them as highly active in influencing the knowledge used inside the organization, or even the knowledge defining the organization as such. changing the locus of the intelligence subject from decision support to knowledge support and knowledge creation will also open the field for other intelligence descriptions, where in the examples given we can interpret the intelligence worker as a knowledge activist, here described by von krogh et al. (1997, 475): ”the knowledge activist is someone, some group or department that takes on particular responsibility for energizing and coordinating knowledge creation efforts throughout the corporation. we believe that such activism will have three purposes, the first of which is to initiate and focus knowledge creation, the second to reduce the time and cost needed for knowledge creation, and the third to leverage knowledge creation initiatives throughout the corporation. knowledge activism can reside in a particular department or with a particular person, but it can also be situated in already existing departments and functions, or it can be taken up as a special assignment by individuals or departments.” important in this quote is the central concept of knowledge creation, which indirectly implies a development of, or change in knowledge as a result of knowledge activism. what von krogh et al. misses out on in the citation above is that knowledge creation also need to be guided in a certain direction and enhanced through the instigation of complementary reference points. intelligence services can do just that, which also makes intelligence personnel most suitable for taking on a role of knowledge activists. building on this it is even more obvious that intelligence workers do participate in the on-going power struggle inside the organization that define the ideas that guide organizational actions. another way of phrasing this, with reference to røvik (2000, 279), is to emphasise that intelligence is about mental manipulation and thus constitutes a vital leadership tool for those in a position to influence the missions given. perhaps, as nonaka points out (e.g. nonaka and takeuchi 1995, nonaka et al. 2000, nonaka et al. 2006), western thinking has paid too much emphasis on knowledge as a physical product, an intelligence artifact (as apparent in traditional intelligence literature), and has neglected the immaterial aspects of knowledge as personal and collective insights. this could at least explain the dominant view on intelligence as decision support still present in today’s discussions and literature. 5. conclusion this article shows that there are complementary ways of understanding the role of intelligence in organizations. intelligence workers are already engaged in the creation and management of strategic knowledge, which is done in parallel to supporting informed and outspoken decisions. this is mainly done by initiating and upholding analytical conversations in dispersed circumstances, answering to local needs for better knowledge. by doing this they fulfill their purpose of creating better business, where the end result appears more prominent than the analytical artifacts produced in pursuit of this goal. with this description, intelligence workers stand out as designated knowledge activists, or if you like knowledge intelligence activist, with four main responsibilities. * to initiate and focus on knowledge creation, * to reduce the 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krogh, georg, nonaka, ikujiro, and ichijo, kazuo. 1997. develop knowledge activists! european management journal, vol. 15, no. 5, pp. 475-483. journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 76–89 open access: freely available at: http://jisib.com/ narrowing the marketing capabilities gap alamir louro brazil federal university of espirito santo alamirlouro@gmail.com received 2 may 2023 accepted 16 may 2023 abstract purpose: in marketing discipline, there is considerable interest in understanding the relationship between diverse approaches of market knowledge learning and organizational performance, and recently, how analytics and emerging revolutionary technologies are changing this relationship. to fully apprehend this relationship it is first necessary to uncover the role of marketing capabilities, the management mechanism that boosts organizational performance using market knowledge. design/methodology/approach: a new construct that embraces analytics and adaptive capabilities approach (aac) was developed to increase our comprehension of marketing capabilities mechanism using structural equation modeling and regressions. findings: the model has shown an indirect-only effect of aac using static marketing capabilities as a mediator narrowing the marketing capabilities gap and avoiding any tautological capabilities pitfalls. research limitations: a deeper endogeneity test could be executed related to adaptive market approach as well it was an original preoccupation concerned to dynamics capabilities. practical implications: it enabled managers to understand what aac are. additionally the results suggest precaution for headhunter because aac needs pre-existing marketing capabilities. social implications: it provides to managers a useful tool to assess their organizations regarding analytics in marketing realm, what makes it possible to compare with rivals and to predict the investments. originality/value: it lies in to appraise the marketing capabilities management mechanism and a step by step scale developed for aac in different industries in brazil. keywords: analytics adaptive capabilities. scale development. marketing capabilities gap 1. introduction according to the literature review of barrales-molina, martínez-lópez, and gázquez-abad (2014) and pereira & bamel (2021), marketing discipline increases attention in emerging revolutionary technologies of the recent data-driven decision-making scenario, in particular using the capabilities literature. to fully understand the learning and the outputs of market knowledge, it is first necessary to uncover the role of marketing capabilities and its management mechanism that allows the relationship between the new opportunities of market learning and organizational performance to exist. the utilization of big data, mobile connectivity, e(m)-commerce, and the internet of things (iot) has led to the emergence of revolutionary technologies that provide interactive and voluminous market 77 information. this information is used as input to advanced analytical methods, transforming both structured and unstructured internal and external data into valuable market knowledge (wedel & kannan, 2016). these new opportunities for learning are at the forefront of recent and complex performance-driven debates surrounding emerging technologies and analytics (chuang & lin, 2017; wamba et al., 2017; donthu et al., 2021; ahmed et al., 2022). revolutionary technologies have significantly improved the power of analytics, which has paved the way for the emergence of adaptive business models such as experimental spin-offs, startups for industry foresight (kiron, prentice, & ferguson, 2014), joint ventures, external networks, and collaborative strategies (barrales-molina, martínez-lópez, & gázquez-abad, 2014). however, there is a significant literature gap in measuring the construct that represents learning capabilities related to analytics, which are used in conjunction with the adaptive approach explained in day (2011). to address this gap, a scale for analytics adaptive capabilities (aac) has been proposed and tested as an antecedent variable to organizational performance (op). however, the relationship between aac and op only exists with the mediation mechanism of marketing capabilities. also according to barrales-molina, martínez-lópez, and gázquez-abad (2014) and pereira & bamel (2021), the integration of various marketing resources, capabilities, and processes into a common framework is hindered by the wide range of options available. this plethora of capabilities, often without clear construct content delimitation and scale validation, has led to conflicting and misleading findings regarding the nature and contributions of analytics for marketing. while tautological research may sometimes yield positive results, it can also lead to pitfalls, such as testing correlations between similar dynamic capability scales. the present work has aimed to avoid such pitfalls by testing a new scale derived from adaptive capabilities (day, 2011), which is an advancement related to dynamic capability. day (2011) differentiates between static marketing capabilities, which are stable capabilities, and dynamic marketing capabilities, which are capabilities that can be reconfigured and augmented, or as capabilities to pursue new opportunities. in addition to the challenges related to capabilities, a multitude of recent empirical studies in marketing and information systems have utilized various constructs related to analytics. these constructs include terms such as business analytics, business intelligence & analytics (bi&a), customer relationship management (crm) analytics, social media analytics, and big data analytics (chuang & lin, 2017; côrte-real, oliveira, & ruivo, 2017; trainor, andzulis, rapp, & agnihotri, 2014; wamba et al., 2017). it is important to recognize the potential pitfalls that may arise from an overemphasis on capabilities and analytics without adequate theory development. such tautological pitfalls can occur when concepts are overused and applied without proper consideration for their underlying theoretical foundations. the most prominent contribution of the present work is to uncover static marketing capabilities mechanism between aac and organizational performance. the step by step scale development of aac and the association between this new construct to organizational performance was tested using structured equation modeling (sem) with partial least square (pls) and ordinary least square (ols) with spss process macro. in the next sections, we discuss some concepts and assumptions and after we propose the model and the new scale, and tested them. synthetically, the paper showed an indirect only-mediation of marketing capabilities and discuss how to narrow the marketing capabilities gap. literature review and theoretical development the concept of absorptive capability (acap) is commonly used in traditional marketing and strategy literature to describe the overall learning process. this approach employs exploitative and explorative market orientation or responsive and proactive market orientation (barrales 78 molina, martínez-lópez, and gázquez-abad, 2014; ozdemir, kandemir, & eng, 2017). while this literature is prominent, it falls short in addressing the role of analytics and relies heavily on traditional marketing methods and approaches (wedel & kannan, 2016), thus failing to close the marketing capabilities gap (day, 2011). to solve the lack of an aac scale and test the mediation role of marketing capabilities we developed a new scale using the mackenzie, podsakoff, and podsakoff (2011) validity framework have ten steps that were followed here and are outlined using the notation: (validity framework step x). we followed this framework and used other scale quality tests. day (2011, 2014) criticize the current resource-based view literature, and even the current dynamic capabilities literature, as less dynamic theories than the market demands, suggesting the existence of the adaptive capabilities. directed by the point of view of day (2011, 2014) the present work advocate that aac explore market opportunities. aac reflect the (aiq) analytical information quality, and a (te) team exploits it with specific expertise (analytical, technology, and business) improved by (mkl) market knowledge learning. in summary, to develop a conceptual definition of the construct (validity framework step 1), aac can be classified as an adaptive capability that uses analytics. of course, this definition is based on two others, adaptive capability, and analytics, defined in the present theoretical review. using mackenzie, podsakoff, and podsakoff (2011) suggestions (validity framework step 1), organizations are the aac entity and the aac general property are the capabilities of these organizations to use sophisticated data technology approach to boost a market openness in a continuously experimental behavior, forging partnerships, vigilantly for deep market insights. aac is multidimensional, and its stability is across cases, where cases are, for example, projects of marketing, data science, r&d, or product/brand innovations. in terms of dimensionality, aac consists of three reflective first-order constructs. while information quality is a well-known and measured construct (gorla, somers, & wong, 2010; wieder & ossimitz, 2015), it is important to note that emerging technologies handle data in novel ways, leading to an increase in analytical information quality. market data is no longer limited to information systems within databases but includes web and social media data, different types of data that are merged into data lakes or warehouses, and independent datasets such as texts, videos, and denormalized spreadsheets that are prepared for data science applications. the process of data engineering and cleansing gives rise to another type of data, which in turn leads to another type of information quality, which we refer to as analytical information quality (provost & fawcett, 2013). teams with special expertise perform analytics. updated quantitative studies provide empirical evidence that confirms the positive role developed by innovation teams (barrales-molina, martínez-lópez, & gázquez-abad, 2014, sincorá, oliveira, zanquetto-filho, & ladeira, 2018). another example is a quantitative work executed with chinese senior executives that identified exchange and integration of team knowledge, and by its turn, this improves the organizational financial performance because of new product development (tseng & lee, 2014). analytics can help in the market knowledge learning (barrales-molina, martínez-lópez, & gázquez-abad, 2014; pereira & bamel, 2021). weaven et al. (2021) and davenport (2006) exemplifies the market knowledge learning by saying that the organizations may spend many years accumulating data from different approaches before having enough information to analyze a marketing campaign in a trusting and efficient way. this market knowledge is all information that the organization has about the customer and his needs in different situations and various moments, past, present and future (cooke & zubcsek, 2017). aac has a construct that responds to market accelerating velocity and complexity with a more outside-in and exploratory learning capability. this first-order construct is based on absorptive capability (acap) with the improvement of vigilant, experimental and, market openness of day (2011). 79 the first-order constructs do not have a causal relationship with aac; instead, they represent the dimensions of the second-order construct. another crucial point for defining the construct is the reflective/formative issue. it is essential to understand that whether a construct is reflective or formative is not inherent but a matter of definition (mackenzie, podsakoff, & podsakoff, 2011). the three dimensions of aac represent its manifestations. for instance, learning a new statistical method like clustering can enhance the team's expertise, which in turn can improve market knowledge learning and analytical information quality. as part of the first step in the validity framework, which involves defining the construct, it is important to differentiate aac from other constructs in the field of marketing capabilities (mackenzie, podsakoff, & podsakoff, 2011). figure 01 summarizes the position of aac in relation to team expertise, which is utilized during the reconfiguration process of acap, and then passes through static marketing capabilities such as resource/capabilities related to customer lifecycle assessment, loyalty or churn programs, pricing, segmentation, and personalization. theoretical model and hypotheses development market knowledge is a crucial point of connection between the constructs discussed in this paper. the source of this knowledge can be diverse, ranging from crm systems and social media to new technologies like iot and big data. however, the way of learning remains the same, that is, by using quantitative evidence (davenport, 2006). this evidence is then used to launch adaptive business models, such as experimental spin-offs, industry foresight, and collaborative network strategies. the theoretical model is presented in figure 01, and hypotheses are introduced in the following section. figure 01 – theoretical model source: prepared by the authors the information system literature has extensively used the concept of capabilities to explain the learning process (popovič, hackney, coelho, & jaklič, 2012; teo, nishant, & koh, 2016; wang & byrd, 2017), but these approaches have not explicitly focused on the market knowledge learning process, which is crucial for changing/reconfiguring organizational strategies (barrales-molina, martínezlópez, & gázquez-abad, 2014). therefore, the unique contribution of the present work lies in the utilization of market knowledge through aac. some digital marketing technologies facilitate large-scale field experiments that produce market knowledge and become powerful tools for eliciting the causal effects of marketing actions (wedel & kannan, 2016). examples are a/b tests and recommendation systems. the former started with changes in site colors for best sales, and nowadays they apply machine learning to test small details for full automated super individualized market-mix. by it turn, recommendation systems can interact directly with stock management or other marketing capabilities like loyalty programs and customer relationship management (crm) building super segmentation approaches. complementary capabilities, idiosyncratic business needs, and organizational procedures\routines should be integrated by teams of technologists and scientists that leads with complex and 80 sophisticated technological knowledge (cohen & levinthal, 1990). this seminal work about market information learning, before the discussions about analytics and big data boom (ciampi et al., 2021), gives us a clue that technologies uphold the market knowledge impacting other marketing capabilities like pricing, segmentation, and personalization. from this discussion and the assumption about the capabilities tautological pitfall, the first hypothesis raises. h1. aac has a direct positive effect on static marketing capabilities. marketing literature is concerned about the relationship between marketing and performance constructs using capabilities (morgan, 2012; kozlenkova, samaha, & palmatier, 2014) but few works measure day’s named "static marketing capabilities" improvement in organizational performance (op). op is measured subjectively. we assume the marketing capabilities importance for performance, and the following hypothesis is declared to uncover the literature term avoidance: h2. static marketing capabilities have a direct positive effect on organizational performance. analytics can improve marketing capabilities/resources like customer lifecycle assessment, loyalty or churn programs, pricing, segmentation, and personalization (germann, lilien, fiedler, & kraus, 2014; wedel & kannan, 2016). however, these capabilities/resources need to have its preexisting procedures/routines to aac make possible disruptions or become adaptive business models like experimental spin-offs, industry foresight or collaborative network strategies. extant literature argument that crm systems are enablers for marketing capabilities (wang, hu, & hu, 2013; barrales-molina, martínez-lópez, & gázquez-abad, 2014; chatterjee, chaudhuri, & vrontis, 2022) which indicates the dependence of some technological capabilities to other sorts of capabilities. additionally, the technology effectiveness, its output, is enabled by preexisting capabilities (boulding, staelin, ehret, & johnston, 2005; ferreira & coelho, 2020). finally, some technology capabilities constructs about analytics are assumed to have a direct effect on performance (wamba et al., 2017; ferreira & coelho, 2020). on the other hand, adaptive capabilities constructs have no direct effect (morgan, zou, vorhies, & katsikeas, 2003). the results show a mixed behavior, and there is hardly clear evidence for a positive impact. in brief, aac as a kind of technological adaptive capability depends on preexisting marketing capabilities to improve performance, and this is the reason to test the mediation and expect a not significant direct relationship to performance. thus, we assume that aac translates organizational performance just thru marketing capabilities. from this discussion, and using the zhao, lynch, and chen (2010) terminology about mediation, we formulate our third and central hypothesis: h3. static marketing capabilities have an indirect-only mediating role between the aac and organizational performance the last hypothesis assumed the terminology of zhao, lynch, and chen (2010) that detail three possibilities regard to mediation, (i) complementary mediation, there are direct and indirect effects and both point at the same direction. (ii) competitive mediation, there are direct and indirect effects, and they point in opposite directions. (iii) indirect-only mediation, there is only the indirect effects. methodology a survey was executed to test the hypotheses (validity framework step 5) with brazilian users of linkedin using a google docs form. it was sent after mining professionals employed (at least one year) and from the following profiles: marketing manager/ analyst, product/ brand manager/ analyst, marketing research manager/ analyst, r&d manager/ analyst, top management, it manager/ analyst, innovation manager/ analyst, data analyst/ scientist, other management positions. the survey was conducted from december 2017 to march 2018, and garnered a total of 250 records for the purposes of scale validation and item purification, without any additional treatments (mackenzie, podsakoff, & podsakoff, 2011). from this larger sample, a heuristic holdout sample of 200 was selected 81 for use in step 6 of the analysis. finally, a subsample of 195 respondents was used to validate the final model, after excluding those with it profiles. the aac construct described earlier is new, and can´t be confused with the existing constructs related to analytics which usually deal with greater technological detail (rapp, trainor, & agnihotri, 2010; wamba et al., 2017). table 01 defines the dimensions of the three first-order aac constructs and how to operationalize the multi-industry questionnaire. in the validity framework, step 2 involves generating items for the aac construct. these items are all new but were adapted from the literature review. the formal specification of the measurement model, without any formative indicators, is presented in table 01 as part of the validity framework in step 4. the table 01 adaptation (i) was a change in the items that deal with data improvements due to a crm implementation, so the new items address any data improvements. by it turn, the adaptation (ii) was necessary because the original scale did not encompass the davenport (2006) concept of quantitative evidence in decision-making. this author explains this characteristic as a background for competing on analytics. additionally, in the three questions of the original work of chuang and lin (2013) emphasis was given to the use of quantitative sources of information. regarding the team expertise, no other questionnaire tested concepts of quantitative evidence, market immersion, and experimentation, key parts of analytics and day(2011) concepts. this idiosyncrasy came from the aac contextualization as an adaptive capability discussed in the theoretical section. the adaptation (iii) was necessary because projects can be done by teams especially formed for this purpose, at a strategic level of top management or even as a specific management initiative like marketing research, or innovation, it, r&d, or product/brand management. the original scale assumes it team only (kim, shin, & kwon, 2012). table 01 aac defining the first-order constructs defining the constructs source of the indicators analytical information quality – refers to the quality of analytical information outputs (i) adaptation from chuang and lin(2013) scale team expertise– represents the professional abilities of the project team that are fundamental to perform tasks. (ex: skills or knowledge) of three different dimensions. dimension analytical expertisefor holsapple, lee-post, and pakath (2014) is about to give high priority to the resolution and recognition of problems based on quantitative evidence. this expertise has others characteristics like data-driven learning, and experimentation (day, 2011). dimension technological expertise represents the professional abilities of the project team (ex: skills or knowledge) that are considered fundamental to perform tasks related to programming languages, data engineering, and cleansing, etc. to improve analytical information quality and learn market knowledge business expertise represents the professional abilities of the project team (ex: skills or knowledge) to perform tasks related to internal and external business understanding, and related to the capacity to collaborate inter and intra-organizations, all task driven by market immersion and openness looking for industry foresight, customer insights or collaborative networks (day, 2011). (ii) dimension analytical expertise–new scale inspired in popovič and others (2012) and day (2011) (iii.a) dimension technological expertise– new scale inspired by kim, shin, and kwon (2012) (iii.b) dimension expertise in business–new scale inspired by kim, shin, and kwon (2012) and day (2011) market knowledge learning the ability of the team to recognize the value of new external knowledge, assimilate and apply that knowledge (cohen & levinthal, 1990). these authors argue that the ability for assessing and using external information is, in most part, adaptation from pavlou and sawy, (2013) and pavlou and sawy, (2010) scales and influenced by day (2011) 82 directed by the level of previous knowledge, what is related to analytical information quality. source: prepared by the authors the references for the other constructs are all based on established works in marketing. the concept of static marketing capabilities focuses on marketing competencies (conant, mokwa, & varadarajan, 1990) and employs a multiindustry scale adapted from song, di benedetto, and nason (2007). in addition, organizational performance uses a scale reproduced from jaworski and kohli (1993) as it is challenging to obtain objective performance data in a cross-industry survey. thus, this study measures performance subjectively. categorical data for multi-group analyses was based on organizational size and respondents' profile. the nonparametric equivalence analysis technique, partial least square multi-group analysis (plsmga), was used. this technique is considered an original extension of henseler's (2009) mga method. despite hypothesis delimitation, control variables such as organizational size and respondents' profile were tested. the mga results differentiated it and non-it respondents. aside organizational size and respondents profile, the work used only seven-point likert scales, ranging from "totally disagree" (1) to "totally agree" (7). to test differences between early and late responders a pls-mga was used too, with no significant differences found. another precaution was to assess common method bias using harman’s single-factor test (podsakoff, mackenzie, lee, & podsakoff, 2003). there is no missing data. according to checked non-normality, the empirical test of theoretical hypotheses was made using structural equation modeling (sem) on smartpls software (version 3.2.4). results analysis the univariate skewness and kurtosis, with values of 14 from 31 likert variables are out of interval from -1 to 1, indicate nonnormality for the original sample, what was confirmed after executing the shapiro-wilks and kolmogorov-smirnov tests rejecting the hypothesis of normality for all 31 variables (hair, black, babin, anderson, & tatham, 2009). the scale purification and refinement (validity framework step 6) resulted in the exclusion of two questions, as seen in appendix i, due to cross-loadings tests. to gather data from new sample (validity framework step 7) a holdout with only 200 first registers of the original sample, we called as heuristic subsample, was used with no big difference (mackenzie, podsakoff, & podsakoff, 2011). the holdout was used only to confirm refinement of step 6. some multi-group analyses was performed using organizational size and profile information. using a data-driven approach, the smartpls suggested the following groups for size: (a) less than 10 employees, with 48 registers, (b) more than 1000 employees, with 52 registers, and (c) the middle, with 150 registers. the plsmga and the permutation algorithm were performed using the combination of these three size groups and two groups of profile resulting in p-values bigger than 0.05, i.e., rejecting the hypothesis of group differences about organizational size. however, for profiles assessment, the pls-mga shows differences from it, 55 registers, and non-it respondents, 195 registers (final sample), then just non-it respondents were used as the final subsample (mackenzie, podsakoff, & podsakoff, 2011) for model tests. using the validation/final subsample with micom process (henseler, ringle, & sarstedt, 2016), we confirmed the possibility of pooling the data of the other profiles. step 1, configural invariance assessment ensure that both setup and algorithm parameters of the measurement and the structural model are identical; we did no additional data treatment for each group, and algorithm settings are the same. for step 2 (compositional invariance) and 3 (composites’ equality of mean values and variances across groups) we used the permutation algorithm with 5000 permutations confirming no significance and then measure invariance. the aac construct has the biggest number of variables, 19 after the deletion of 2 items. therefore, preliminary would be 190 83 respondents using the rule of thumb of 10 times (hair, hult, ringle, & sarstedt, 2017). another conservative way, making a statistical power test in 95%, and assuming an f square of 15%, the software gpower determines, for a significance of 1%, the size of the sample as 170 respondents. the gpower statistical test chosen is one that tries to maximize the multiple regressions r square adding new predictors to the solution, f² (faul et al., 2007). we used 4 predictors, including 2 control variables. model tests the pls algorithm was executed with the default values following the guidelines of hair et al. (2017). all constructs have at least three variables and are reflective according to the content definition, or a priori specification. the hierarchical components are treated using repeated indicators approach (hair et al., 2017), and the results of the measurement model regarding the validity and reliability show cronbach's alpha and composite reliability greater than 0.7 and ave, greater than 0.5. measured for the first-order and second-order aac construct (mackenzie, podsakoff, & podsakoff, 2011). the external loads of convergent validity are greater than 0.7 (validity framework step 6). still on the measurement model was analyzed discriminant validity using the fornell-larcker criterion, according to which the square root of the ave must be greater than the other constructs loads. after exclusion of two items, the cross-loading test showed no problem, confirming the validity at construct level (validity framework step 6). both tests were executed for multidimensional constructs of aac (validity framework step 8). the structural model collinearity was evaluated using the vif indicator, using less than 5 as a parameter, with the highest result being 4,097 (hair et al., 2017). after, the coefficients are evaluated using the bootstrapping procedure with 5000 subsamples with the option "no sigh changes" (validity framework step 6). the coefficients are not significant (p-value <0.05) only for the statistical test of the relationship between aac and organizational performance indicating an indirect-only mediation of static marketing capabilities (h3). for a more in-depth analysis (see table 02 and figure 02), the macro process of spss confirmed the h3, indirect-only effect for mediation, (a) and (b) <0.001 and (c´) not significant, and gave more information using ordinary least squares (ols) regression analysis with the latent scores outputted from smartpls. we used the procedures and parameters of hayes (2013), and the results of the bootstrap with 10000 resample are summarized in table 02 with results for r2, f statistics (degree of freedom 1 and 2) and p-values. it also includes unstandardized regression coefficients of direct paths (a, b, and c’), and the indirect path ab with significance level for bias-corrected 95% confidence intervals, and standard error(se). table 02 process ols mediation results consequent antecedent m(static marketing capabilities) y(performance) coeff. se p coeff. se p x(aac) a .7325 .0640 <.001 c' .0532 .0859 ns m(static marketing capabilities) - - -b .7084 .0865 <.001 constant i1 .0 .0494 1 i2 .0 .0484 1 r2 = 0.536 p<.001 f(1,193) = 130,8382 r2 = 0. 3273 p<.001 f(2,192) = 90,5057 source: prepared by the authors the first two hypothesis was confirmed (see figure 02, left side), and they gave responses to extant literature and introduced aac as an antecedent of the realm of marketing capabilities. about the main test, mediation (see figure 02, right side), the indirect effect (ab) resulted in a value of .5189 using both the normal theory test and the bootstrap confidence interval (hayes, 2013). as h3 is the main test, to improve the robustness of 84 the indirect effect value, another test procedure was executed using a simulationbased method, monte carlo using the mcmed macro (hayes, 2013). mcmed showed the same value with confidence intervals ranging from .3734 and .6811 (preacher & selig, 2012), i.e., not passing thru zero. figure 02: smartpls algorithm and process spss outcomes source: prepared by the authors thus h3 was confirmed, no direct significant effect, using sem and ols indicating an indirect-only mediation between aac and organizational performance, what agree with part of literature that we assumed as correct, what has a definite impact for practice and academics. the mediation effect is most important as higher is the indirect-effect value, not the inexistence of direct-effect (zhao, lynch, & chen 2010), and have to be analyzed together with the size of the effect f², which evaluates if any omitted constructs generate substantive impact on the endogenous constructs. this caveat is necessary to avoid the epiphenomenal association, that means a mediator correlated with another omitted construct (hayes, 2013), but f2 results deny this association as we will see. the indirect-effect has a value of .5189, but it is a scale bound then it is dependent on the constructs metrics, and the measurement metrics in our model are not inherently meaningful because they are responses to rating scales aggregated over multiple questions (hayes, 2013) and standardized by smartpls. thus we used the r-squared mediation effect size (rsq_med from process) that resulted in .3260, confidence intervals ranging from .1969 and .4546, meaning that aac explains 32.6% of organizational performance valiance in our final sample, that has total effect larger than the indirect effect and they have the same sign, following the restriction of hayes (2013) for r-sq_med effect size index. back to the smartpls, the f² effect shown that aac on static marketing capabilities and static marketing capabilities on organizational performance are large, bigger than 0.35 (hair et al., 2017), meaning the contribution of the exogenous construct for the r2 of the endogenous construct. we also evaluated the coefficient of determination that measures the model predictive power. the result was 0.523 for static marketing capabilities and 0.547 for organizational performance, with adjusted values of 0.521 and 0.543 respectively, which is considered both moderate (hair et al., 2017). the predictive relevance is evaluated using the blindfolding algorithm with default configuration, omission distance equal to seven, resulting in a q² that represents great relevance 0.377 (organizational performance) and near to great 0.318 (static marketing capabilities), with 0.35 as parameters (hair et al., 2017) using crossvalidated redundancy (validity framework step 9). to finish the validity framework steps 6 and 9, with standardized root mean square residual (srmr) fit parameter as less than 0.08 (hair et al., 2017), was found a good fit of 0.064. in summary, the analysis of sem carried out in smartpls, and ols in 85 process resulted in the confirmation of all three hypothesis. discussions the hypothesis h1 confirmed the importance of teams of technologists and scientists that leads with complex and sophisticated knowledge impacting in marketing capabilities (cohen & levinthal, 1990; ciampi et al., 2021) with a moderated r square. by it turn, the hypothesis h2 confirmed the marketing capabilities literature (morgan, 2012; kozlenkova, samaha, & palmatier, 2014) and gives the possibility of using the term "static marketing capabilities". additionally, h2 also resulted in a moderated r square for organizational performance. the parsimonious model empowers the moderated r2. the hypothesis h3 showed that aac is dependent on static marketing capabilities. this result gives to aac the same enabler behavior of technological capabilities regarding preexisting marketing capabilities to improve performance (barrales-molina, martínez-lópez, & gázquez-abad, 2014; pereira & bamel, 2021). these tests expand the knowledge of managers and academics. in particular to both profiles that take for granted the importance of analytics and think about it naively. conclusions the present paper helps to explain organizations that continually feel and act upon the emerging technological trends using a market knowledge with the adaptive approach. the paper shows that to improve organizational performance using aac it is needed static marketing capabilities. thus, analytics can boost traditional methods of customer lifecycle assessment, loyalty or churn programs, pricing, segmentation, personalization, which by its turns, can launch adaptive business models like experimental spin-offs, startups for industry foresight, they can promote joint ventures or external networks and collaborative strategies. the results show findings both from academic and practice point of views. the academic relevance is to show how aac acts through static marketing capabilities to become a critical and predictive element for organizational performance. thus, the results of the research contributed to clarify the way in which the construct operates, additionally the paper escape from traps linked to tautological dynamic capabilities research. regarding the managerial context, this research effort enabled managers to understand what the analytics adaptive capabilities are, as well as the static marketing capabilities that need to be developed and articulated by work teams involved in marketing activities. the expertise of these teams are used to recognize the value of new market knowledge through the use of technologies, assimilating them and applying them to new adaptive business models. thus, aac is a rare, valuable and adaptable capability to the market demands. the paper provides to managers a useful 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(2010). reconsidering baron and kenny: myths and truths about mediation analysis. journal of consumer research, 37(august), 197–206. https://doi.org/10.1086/651257 journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 4–5 open access: freely available at: http://jisib.com/ editor’s note vol 13. no. 1 (2023) unveiling the value of competitive intelligence: coordinated communication and added value recently, a lot of attention has been paid to several aspects of ci, which influence the decision-making of organizations and the acquisition of competitive advantages. organizations must leverage data, artificial intelligence (ai), and social capital to enhance their competitive intelligence processes. social media data, ai and machine learning, big data analytics, dynamic capabilities, and intraorganizational social capital all play significant roles in driving strategic decisionmaking and improving customer experiences. by integrating these elements effectively, organizations can gain valuable insights, mitigate risks, and stay ahead of the competition. organizations can enhance their dynamic capabilities by integrating social media analytics into their competitive intelligence practices, particularly in the stages of information collection and analysis. this integration positively influences the various stages of competitive intelligence (wu, q. et all., 2023). organizations also expect higher added value and looking for sources of this value in relation to competitive intelligence. this value could be shared between different departments and coordinated by corporate communication. (ding, j.-l. & shi, b., 2021). in this issue, the authors explore internal aspects of organizations and propose models that integrate existing knowledge. these models aim to assist organizations in establishing, assessing, and enhancing their ci practices and theories, ultimately resulting in improved organizational performance. there are practical implications for various organizations, including academic entities. existing solutions are designed to help businesses deal with unforeseen events by gathering and transforming data into understandable information. while major companies have adopted big data analytics systems, the adoption and effects of business intelligence tools in universities and organizations are not well understood. therefore, researchers are investigating how business intelligence tools specifically impact decision-making and performance in public universities. furthermore, there has been a growing recognition of the importance of startups in driving economic growth and innovation. governments, private organizations, and academic institutions around the world have initiated various programs and initiatives to support startups, facilitate their establishment, and harness their potential for generating a significant impact on national economies. these initiatives aim to provide startups with the necessary resources, knowledge, and networks to thrive in competitive markets. the overarching goal is to create an environment conducive to entrepreneurial success and encourage the growth of startup ecosystems. within this context, competitive intelligence has emerged as a valuable tool for startups to improve their company performance and gain a competitive edge. researchers have conducted studies highlighting the role of competitive intelligence in improving company performance through organizational learning. 5 finally, there are numerous possibilities for enhancing the applicability of existing tools to address current problems. the use of analytical and adaptive technologies can provide organizations with comprehensive tools and techniques. i would like to express my gratitude to all contributors to this issue. references ding, j.-l., shi, b. (2021) analysis and modeling of enterprise competitive intelligence based on social media user comments. entrepreneurship research journal, 11(2), pp. 47-69. wu, q., yan, d., umair, m. (2023). assessing the role of competitive intelligence and practices of dynamic capabilities in business accommodation of smes. economic analysis and policy, 77, pp. 1103-1114. on behalf of the editorial board, sincerely yours, prof. dr. andrejs cekuls university of latvia, latvia article_sidhom_lambert__siie2011_v5f_en__ss information design for “weak signal” detection and processing in economic intelligence: a case study on health resources sahbi sidhom * and philippe lambert * * * loria/kiwi & nancy université, 4 rue ravinelle, 54000 nancy, france sahbi.sidhom@loria.fr ** vinalor, nancy université, 4 rue ravinelle, 54000 nancy, france philippe.lambert@vinalor.fr received 20 february 2011; received in revised form 22 november 2011; accepted 25 december 2011 abstract: the topics of this research cover all phases of “information design” applied to detect and profit from weak signals in economic intelligence (ei) or business intelligence (bi). the field of the information design (id) applies to the process of translating complex, unorganized or unstructured data into valuable and meaningful information. id practice requires an interdisciplinary approach, which combines skills in graphic design (writing, analysis processing and editing) , human performances technology and human factors. applied in the context of information system, it allows end-users to easily detect implicit topics known as “weak signals” (ws). in our approach to implement the id, the processes cover the development of a knowledge management (km) process in the context of ei. a case study concerning information monitoring health resources is presented using id processes to outline weak signals. both french and american bibliographic d a t ab a s e s were applied to make the connection to multilingual concepts in the health watch process. keyword: economic intelligence, business intelligence, information design, weak signals available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 40-48 mailto:sidhom@loria.fr mailto:lambert@vinalor.fr https://ojs.hh.se/ 41 1. introduction on november 2 6 t h . (2010), the uni ver si t y o f califo r nia officially launched its laboratory project on “information design” (id). the project aims to develop knowledge exchange between different actors through applications for new media platforms such as ipads in networks or iphone technology. beyond the innovative aspect of this project, we note that the id is the projection of an important “prospective approach” in the anglo-saxon research world. this point is reinforced by the comparison of the scientific literature on the issue. since the 70s, research teams have specialized on the connections’ between the graphical representation of information and its interpretation. one of the representation techniques that have been developed is “spatial” information across neuron networks. especially in france, this approach has been somewhat vulgarized at first as in the example of mind-maps a nd mind mapping in education research. in recent years, this research focus has been applied to data mining u si n g d ata from the web (web mining). it helps to develop new knowledge from large text themes. this technique is increasingly interested in leaders who have the responsibility to detect topics that can have been missed in a linear reading. in the field of ei studies, the implicit properties on analysis take on the name “weak signals” (ws) (the explicit properties are “strong signals”).the detection of ws allows the user to take better account of the environment in a dynamic sense and t o b u i l d foresight (“to prepare today for tomorrow”). however, the connection between id and ws detection requires the development of a complex methodological process. this is the topic of this paper. the first part of the paper defines the meaning of weak signals and processes through a strategic approach. the second part presents the logic in id processes that tends to present varied graph data sets while facilitating the appropriation of “semantic” properties. the last part is matched to a case study on “strategic” health watch for which we use mapping and the visualizing of information. the study was able to detect a n u m b e r o f weak signals on scientific and technical information with the assistance of id. 2. mapping information for detecting weak signals (ws) anticipating strategic failures is one of the most common issues in ei studies. market volatility, uncertainties about property p r i c e s and economic change are signals that announce future crisis and breaks from crisis. these breaks may be opportunities or threats in a changing world of economics where the faculty of anticipation becomes a powerful strategic advantage for companies. in 1970, ansoff discussed the concept of ws in his first paper on the subject, entitled “managing strategic surprise by response t o w e a k s i g n a l s ” (ansoff, 1975). he considers the w s as corollary of organizational factors in the company, especially due to environmental turbulence a s compared to the formulation of corporate strategy. in a following paper he specified the nature of ws, by defining it as “a warning (external or internal), events and developments that are still too incomplete to allow for an accurate estimate of their impact and/or to determine a full adapted response” (ansoff, 1985). in what follows, we s e t o u t t o determine the theoretical framework and application of ws. 2.1 theoretical framework: weak signals (ws) any company can engage in a strategic process. the specificity of the ws lies also in its potentiality. if one considers the famous s-curve, w h i c h describes the four phases of the product’s life (birth, growth, maturity and decline), we can imagine that ws is a precursor of a new trend upstream of the cycle. hence, the importance of ws detection in a logic of competitiveness. the term “signal” is ambiguous. if one refers to the definition in the treasury of the french language (atilf) for the word “signal” we f ind: [in french] ”signe convenu par lequel quelq’un donne une information un avertissement á quelqu’un le moment de faire quelque chose”. ansoff's: [in english]: a sign by “proactive” value: to capture ws by the decision-maker via the channel of intuition (i.e. spontaneous knowledge of the environment) to cause a request for additional information (i.e. explicit formulations) from these signals. another contribution to the question of weak s i g n a l s was made by coffman who has worked on various aspects of the problem. for him, a ws is defined as (coffman, 1997): an idea that affects the way we trade and the environment in which we work; a novelty and a surprise in terms of receiving signals, a noise and other signals, sometimes difficult to detect among noise and other signals, an opportunity or a threat to the organization, often mad e f u n of b y the "knowledge h o l d e r s ” or experts, w e a k signal with a substantial period of time before it matures and becomes a strong signal, therefore, this signal represents an opportunity to learn, grow and evolve. coffman ( 1 9 97 ) also said that the ws could be of three types: supra-perceptual signal, perceptible s ig n a l but not recognized by our mental models, and recognized signal by our mental models and by which our change in behavior. in f r a n c e , h. lesca (2001) propose s a list of characteristics that define a ws, w h i c h 42 is close to that of ansoff. a signal can be classified as ws if it is fragmentary, embedded in a mass of useless information (or noise), an apparent weak and ambiguous meanings, could not be seen, an apparent low usability, and low "palpability". in synthesis of these definitions and presentations, we can consider that a weak signal is characterized by: a temporal discontinuity of its discovery, but also by the fact that it causes a shift (or breaking) in the facts found by the receiver to arouse/create measurable interest in the future. the researchers found, in the notion of breaking or the “discontinuity”, the reason for the information flow and design that someone provides information, a warning to someone; someone tells i t ’ s the time to do something. precisely the opposite that constitutes the “weak signal” in a strategic watch process. the transmitter of the information detected as ws do not expect the risk that competitors become aware of the potentially innovative nature of the information given. the adjective term “weak” is also a sematic problem. the “weakness” of the signal is opposite to the potential of information designated b y this t e r m . t h e ter m “weak signal” is defined by “a high potential for new innovations”. due to this we propose to transform the term “sign” above as in “weak signal” to “latent warning sign” (lws) for designated information in a strategic context. 2.2 application framework: knowledge discovery for nearly a decade, several teams of researchers across the atlantic have focused on the subject of information design (id). the concept, however, remained forgotten in france until recently. visualizing information has g r e a t p o t e n t i a l advantages. eppler and burkhard (2007) gives six main reasons for why it is important to give priority to this area: it motivates the receiver, presents new perspectives, develops memory, encourages the learning process, captures the attention of the receiver, and allows structuring and coordinating of communication. many definitions present id as an art, the art to direct information to create meaning. graphic productions goes together with significant creativity, with formatted, colorful, animated and multiform information. in addition to the purely aesthetic s i d e o f this approach, id contains intrinsically a new way of thinking about information and could be summarized as karabeg (2002) did in “a new approach to information”: he explains what id is by p r o p o s i n g t h e i m a g e o f a b u s equipped with “candle flags” (atilf, 2010). the bus represents a “modern culture” while the candles symbolize “traditional” information. we observe what the author means by this incongruence (dysfunction). however it can be surpassed by the use of id. moreover, “modern culture” is producing and consuming information on a lar ge -scale. i d through the development o f information technologies can act as a remedy to the problem of chronic “infobesity”. on this epistemological id, more technique is being added, p r o p o s e d b y men like j o t h a m fry (2004) in h i s t h e s i s e n t i t l e d “computational information design”. the issue of work is to propose a methodology for data visualization and offer a comprehensive set of graphical representations to give sense to implicit relations between connective data. j o t h a m fry (2004) presents a classic seven step process for id to ensure the transition from data to knowledge, acquire: acquisition of data from any medium, parse or split; cutting to provide a structure of the data and order, filter: filtering to select only relevant data, m i n e : the sear c h w h e r e y o u p l a c e the d a t a into a mathematical context, show: representation where it is determined, t h a t a simple representation of data can take, refine: refining to change the simple representation to more and advanced visual renderings, and interact: interaction by adding methods for manipulating data through visualization. besides the purely aesthetic s i d e o f information (or infographic), id is at the crossroads of several fields of scientific applications. this includes the fields of visualization techniques to computer graphics for greater knowledge. w e also s e e the impact i d h a s in psychology and semiotics. this d e v e l o p m e n t is to perfect the cognitive and physiological theories of visual perception and cultural factors that come into account in the process of information visualization. ultimately, id enables the end-user, usually an expert whose skills enable him to interpret the data represented as graphs, to generate links between data and knowledge. this knowledge discovery is not the ultimate goal of the logic of id. on the contrary, the new application aims to refocus the attention of the user to historical data previously unnoticed. as a result, a new watch cycle will begin on data previously “unnoticed”. in this case study, the aim is to illustrate the relation of id and knowledge data discovery (kdd). the “latent warning sign” (lws) is here a key component of this new application by t h e emergence of thematic relations that may improve the strategic watch process. 3. t h e case study: the health heterogeneous resources – project « cronisanté » during the conference siie’2010, there was a study about reflections on “chronic diseases 43 management (project 2007)”, by the high council of public health (hcsp) with inistcnrs i n fr ance , t o estab lish a n “information s y s t e m for decision support” powered by a strategic watch process on the health resources (lambert & sidhom, 2010). the hcsp was trying to identify how european health systems manage the problem of “chronic diseases”. the approach to the problem is based on the wisp model (i.e. watcher information and search problem) developed by p. kislin (2007). this model is the extension of a watch approach to describe the information needs and help the user (decision-maker and user) to formulate needs. in the context of this work, the formulation of needs has been directed towards the bibliographic references obtained after consulting a business database (cf. iii.d). the strategic issue of this work, for the user, is to formalize the declarative rules, by: <<issue>>: = if we do not act on the <object> and knowing the state of the <signal>, the n the risk is the expected <hypothesis>. where: issue is defined by an object of the environment, on which it is possible to act. a signal pro mpts t he decision-maker t o trigger the problem, an hypothesis, w h i c h i s t h e r i s k , a s , expected consequences, if left unchecked. the approach in view of the application is to better target the information needs of the project sponsor, the hcsp. to achieve this we translate the strategic issue in a series of dimensions related to the problem with a set of indicators on t h e information retrieval (ir) process. one can easily imagine, given the multidisciplinary nature of the working group and the specific interests of each expert, that the heterogeneity of the subject fields represent a problem in the collected information and for analysis. 3.1 health resources: semantic heterogeneity “too much infor mation kills information” ha s become the favorite expression of responsible users at the time of information o v e r flow . the ability to q uickly extract relevant information, while providing added value, creates more robustness to any surveillance process. the concept of added value will here be understood as the annotation process to facilitate access to relevant information for the user (sidhom, 2008). indexing and reindexing by users (i.e. social tags, folksonomies, etc.) are in the list of tools for this process. furthermore, the quantity of information, the heterogeneity of resources and information itself are a problem well known to designers of information systems. schematically, we speak of a dual heterogeneity that is both semantic and syntactic. example of this is the syntax for the heterogeneity of data storage formats (pdf, doc, xml, etc.), query languages and more generally across protocol data structure. the semantic heterogeneity is the differences between the interpretations of the real world inducing several terminology uses for the same reality (ontology, synonymy, etc.) (goh, bressan, madnick and siegel, 1999). later, we will return to this problem by relying on examples from the bibliographic databases. the added value gained from the system use two aspects. the first is the addition of keywords or comments (i.e. social tags) by the user to information resources. this allows customization of information regarding documentary resources. these anno tatio ns can feed up the index in a system to improve the return rate for ir. the second aspect concerns the “information design” process (ansoff, 1975). several studies i n t h e medical sector have shown that visual information influenced the decision-making both in a strategic situation (i.e. care policies) and a therapeutic condition (i.e. alternatives to hospitalization) (elting, martin, cantor and rubenstein, 1999), (wyatt. 1999). this logic has not only to refine the conceptual goal in the system but also to support the iterative process: – information needs – ir – new conceptual indicators (proposing). this process can come from techniq ues o f knowledge management (km) and mind mapping. 3.2 from nlp to information visualization sidhom (2002) has developed a morpho syntactic analysis platform for automatic indexing and information retrieval (simbad). it is composed of an indexing kernel (i.e. indexing process) that uses the noun phrases (np) as descriptor in nl structures (i.e. to extract concepts) in text documents (and opens to multimedia associated to text descriptions). we use the definition of a noun phrase (np) as defined by le guern (1989) to place a lexicon word in the discourse of universe, de facto, this word i s ejected i n extensional logic, and gives to np a repository status, as a reality segment associated with it. in our context, the np appears to be the bearer of a “semantic load”, which makes it relevant and a central element to bibliographic information analysis. around this semantic we search guides for our analysis on the actual corpus. thus, grammar of np recognition has three logic levels: 1°/ intentional level (or natural language properties), is represented by the level n. words are considered free predicates o r as simple (i.e. the noun properties) or as complex (i.e. the noun properties modified by other units: 44 adjectival units a’ (i.e. a’ a|adv+a|a+rel, etc.), expansional preposition ep (i.e. ep prep+n’, etc.), etc. 2°/ intermediate level (or taking into account the universe of discourses), it is represented by the level n’. it i s the transition from the intentional to the extensional levels. words are considered free predicates with a set construction of closed predicates to denote objects in the world (i.e. n’ n+sp|n+a’|…|n) 3°/ extensional level (or the np and its complexity), it is represented by the level n’’. it is the close operation using a quantifier that selects a specific element in the class n of nominal. these are the existing objects in the world, referred objects or mind-constructed objects. in this work, the morpho-syntactic grammar of the np has been rewritten for nooj in two levels: firstly, the work was to reformat linguistic resources (dictionaries and grammars) resources in our possession. during a second time we developed the finite state transducer of the noun phrase. labels existing dictionaries have been harmonized to match the syntactic graph of np (fig. 1-2). figure 1: syntactic graph of simple np in nooj figure 2: embedded syntactic graph of complex np in nooj the graph provides numbered phrases identifying the fitting relations in syntagmatic level results (lambert and sidhom, 2010). in the logical use of the semantic concepts (i.e. np and its properties) from the bibliographic records, the results on output graphs must be operated by an end-user. this gives the end user access to pure information, leaving him free to evolve in the concepts from a document process: visualizing information spaces fed by heterogeneous data sources. this is a support of an economic intelligence process and for a information design system (lesca, kriaa-medhoffer and casagrande, 2009), for the “chronisanté” project. in particular, in information surveillance activities, the process is a major vector for the emergence of significant associations after phases of collection, processing and analysis in a large mass of data and information. several solutions to information mapping software are available. the tool we used is software under gnu general public license (gpl3) called gephi (http://gephi.org). it allows the visualization of complex networks. 3.3 corpus study and indicator valorizations as part of our core construction, w e m a i n l y searched bibliographic databases via the multiapplication “webspir”, a tool that was replaced at th e start of 2009 by the platform “ovidsp” (http://www.ovid.com) with features near equivalent but more robust for users. three databases were selected for the constitution of bibliographic our entities: <pascal 2 > <psyinfo 3 > and <medline 4 >. the choice to use these three sources on health information is justified by our aim to cover as fully as possible the thematic management on chronic diseases. the basic advantage of pascal database is that it presents european references and includes records from the databases in public health (bdsp). the medline database is centered on u.s. publications, such as psycinfo, but with a broader theme in the social sciences. in synthesis and contrary to this logic which requires complete topics, our search equations were developed to deliver results to the widest possible extent: first, to cover all the sub themes on "chronic disease" and, second, to identify new sub-themes which we had not originally thought of. the browsing on the three databases reported: 2097 references to pascal, 6110 references to medline, and 2177 references to psycinfo. we subsequently refined our search to select only those published between 2001 and 2009 in french. the result consists of 397 references and 303 references in the duplication pass. these entities then will be the first synthesis of our work. the results of the ir process indicate that "chronic disease" is a new concept in france, because of the singularity of the model in the french health system. a second approach has motivated a second job on the database “pubmed” as previously mentioned. the completion of the “chronisanté” project as a “decision support system” (dss) or siad in french, was faced with a semantic problem: the rendering of the term "chronic disease" i s as a concept purely anglohttp://gephi.org/ http://www.ovid.com/ 45 saxon, which brings a series of problems in a multilingual and “translation terminology”. in fact, the completeness of the study involves a search process on multilingual literature to define the best concept and study consisting of what intersects. it is in this logic that the base “pubmed” was viewed with a search for the term “chronic disease” in the title of the records. the result is 13,222 records. these had parallel entities in t h e english language with relation to the initial multi-base. 4. connections to latent warning (or weak signals) in the id process applying automatic analysis (nooj) on our data entities (ie. as the id process in phases 1 acquire 2 parse), the complex graph of np reported 1374 concepts (ie. as the id phase 3 filter) including the smallest concepts (ie. the lemma n) to simple or complex concepts np (ie. levels n' + n''). the advantage of this approach is to present to users the primary concepts (i.e. as the id phase 4 mine) in information resources but also secondary concepts (i.e. the id phase 5 representation) that the user does not necessarily think of i n h i s r e s ea r c h o f i n d i ca to r s : the translation p hase o f a decision problem into an ir problem in the ei context. in this case, considering the concept of “patient” is t h e central tour theme. in practice, we tend to establish our search for indicators in a passive acceptation with concepts: “patient monitoring [(fr) suivi du patient]”, “patient care [(fr) prise en charge du patient]”, “patient education [(fr) éducation du patient]”, etc. but not in an active acceptation, as “patient involvement [(fr) implication du patient]”, “active participation of patient [(fr) participation active du patient]”, etc. (i.e. as the id phases 6 refine in iteration). the research of nps in the titles of references highlighted ideas that apparently have no close relation with our themes, but which nevertheless appear several times in different references. in this case, on the theme of “cannabis consumption” it puts a link for “long term illnesses”. given these observations, we took for advantages of select matches, the longest in the np. this corresponds to the fitting relation: the concept o f fitting in (x y), x the longest and most informative np; the concept fitted (zw), z the shortest and the least accurate np. the richness of meaning that emerge, allows the identification of informational collection with relevant, complex and hierarchical concepts (np). these characteristics may go unnoticed in the linear analysis of an entity. thus, the process of the bibliographic entity records on the platform nooj showed satisfactory results based on the np and its semantic properties (i.e. the relations of tree (t: y x and x z, fitting (f: x y w) and belongs (b: n x / xy)) (sidhom, 2002). pascal: produced by inist-cnrs, pascal is an international and multidisciplinary database that identifies literature in science, technology and medicine. psycinfo i s t h e database of the american psychological association (apa) and provides access to journal articles (many are full text), book chapters and books, research reports and theses and dissertations in psychology and related fields (medicine, nursing, sociology, etc.), from the 19 th century to today. medline is a bibliographic database produced by the national library of medicine (nlm-usa). it covers all biomedical fields: biochemistry, biology, clinical medicine, economics, ethics, dentistry, pharmacology, psychiatry, public health, toxicology, veterinary medicine. figure 3: semantic networks based on bibliographic records: nucleus a n d satellite connections. concerning t h e visualization o f information (i.e. as the id phase 7 interacts in iteration), we tested the application with gephi fruchterman-rheingold algorithm (card, mackinlay and shneiderman, 1999) on the results of extraction with nooj. this algorithm of multi-scale force can calculate the force between two nodes and map complex networks. by its use, there is much emerging nucleus surrounded by satellite subsystems that can be considered non central themes to the theme target. according to the analysis of information needs, the user can focus attention on these satellites nodes to be considered as “latent warning signs” themes (weak signals i n e i ) and give them special attention (fig. 3). by nooj parsing, we present the gr ap h results of the np extraction in the french entity (fig. 4). 46 figure 4: visualization of nap semantic networks based on the analysis of the semantic network, we observe that the center of the graph (central nucleus) consists of terms related to the decisionmaking analysis: work that we completed in the process of ei. thus, for the analyzed entity, it reprsents terms such as “coverage, care [fr: prise en charge]” or “chronic diseases [fr: maladies chroniques]”, new terms like: (“hepatitis c”, “cardiopathy”, “asthma”, etc.). we notice the relation that exists between nodes that represent the semantic connections between terms (fig. 5). the usefulness of such a “visual structure” document for a user, an expert or a decisionmaker, is considerable. it allows presenting an interactive document likely to bring new knowledge. in such a semantic logic, it allows to better understand the complex dimensions present when concerned with the surveillance or ei process. figure 5: the np core (central nucleus) and themes. the visualization of named entities in the data can also be positioned relative to the documentary logic. the graph makes it possible to show relations between concepts (np) and document references (fig. 6). said differently, we can see which resources concentrated more concepts and which ones that is potentially relevant. figure 6: connection between np and information resources. the atomic structure for the nucleus concept, “coverage, care [fr: prise en charge]” is linked to the bibliographic references. we also note the secondary concepts like: “management of asthma [fr: prise en charge de l’asthme]”, “chronic asthma [fr: asthme chronique] ” and other concepts which appear in the peripheral area of the semantic network. this process was applied to the second data entity in english, with the same logic: the extraction of nps based on graphs modeling (silberztein, 2005). four hundred and twentynine mapped terms are returned. they are linked with their document resources. this approach requires of users a “proactive approach” through the research (mining) graphs proposed in order to detected new knowledge. in the logic presented here, it may refine the concepts from another cultural sphere. in application, the activation of a term (t) allows us to view notice records (n1. ni) in connection with subjects (s1. sm) and associated keywords (k1. kj). the scenarios for identifying and refining may be multiple: as an example, from record (ni) to keywords (k1. kj) or vice-versa. the possibility to link the node "notice” to the source document by hyperlink feature allows the user to have access to the document environment in terms of interest with any subject. 5. discussion and conclusion the experience shows that the techniques we used require automation to achieve a state of performance, robustness and an acceptable level of efficiency. the “information design” (ansoff, 1995) process defined as the “art and science of preparing information so it can be used by humans with efficiency and effectiveness.” in the id 47 process, we evaluated our study areas by the use of the following aspects: “graph(s)”, “semantic network (s)”, “project (s)” and “connection(s)”, to translate them into clear, immediate and appropriate information for users. in our study, the user is often the observer, the analyst or expert and the decision-maker. for us, useful information is not the increase of information quantity, but on the contrary, the reduction of it by relevant information clusters to facilitate its reading and appropriation ( lesca, kriia-medhaffer and casagrande, 2009). this has been discussed and treated throughout this paper explicitly as the application o f i d processes in the context of o u r “chronic diseases” study (project “chronisanté”). for the “surveillance” process, w e f o u n d t h a t the information visualized extracted from the concepts of nps is useful to actors in a strategic project in numerous aspects. at first, information visualization facilitates document indexing and content of information systems (is), information retrieval (ir) systems or decision support systems (dss). as an example, for a bibliographic record or document to be analyzed, to extract noun phrases in the content w e m a y convert them into tags. this solution allows any user of the document to present the key concepts in the information database (lesca, kriiamedhaffer and casagrande, 2009). this may again encourage a new logic of “reindexing b y users”: the user-tags are automatically stored; the user will add subjective, objective and creative tags, to give added-value (harboui, ghenima and sidhom, 2009). second, the visualization of a semantic network (based on nps concepts and properties) enables the production of new knowledge. viewed no des in a semantic network can indeed be analyzed in a working group o r tea m to identify new topics related to business intelligence as convergence and divergence of represented subjects (i.e. decisionmaking needs). this is, to use the “humbert lesca” logic; heuristic processes allow a collective creation of meaning (lesca, kriia-medhaffer and casagrande, 2009). at third, in the surveillance, information and documentation p rocesses, the visualization logic and the id process can bring out potentially relevant data. on this point, it should refine results by a statistical analysis: the use of bibliometric indicators (salton, wong and yang, 1975) as the tf-idf (term frequency inverse document frequency). for “economic intelligence”, we see that the usefulness of the id process goes beyond a simple and literal translation of ir indicators (i.e. the translation phase of a decision problem into an ir problem). for complex and “multilingual” semantic search, we can take the conceptual differences between terms, like: “chronic disease” or “chronic disease management” and “management of chronic diseases”. thus, we can show, by semantic visualizing of these concepts, the connections with the processed information (parsing, analysis and needs information). also, we can establish multilevel intersections between information concepts and common or different “morphemes” to get shared meanings. finally, on a technical level, the problem of heterogeneous information resources can be minimized with the addition of annotations and/or linguistic processing. nlp tools (as nooj or others) will enable the processing of multi-format sources, and for nontextual documents (multimedia), analysis can be made on the annotations associated with the documents: developing a semantic homogenization, b y counterbalancing the syntactic heterogeneity. references atilf – cnrs. 2010. université nancy 2, le trésor de la langue française, http://atilf.atilf.fr/dendien/scripts/tlfiv5/advan ced.exe? 8;s=66859215; [visited date: nov. 20, 2010]. h. i. ansoff. 1975. “managing s t r a t e g i c s ur p r i se by response to weak signals”. california management review, vol. 18, no. 2, pp. 21–33. h. i. ansoff. 1985. “strategic response in turbulent environments”. handbook of business strategy. s. card, j. mackinlay, and b . shneiderman (eds). 1999. readings in information visualization: using vision to 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11 no 2 editor’s note vol 11, no 2 (2021) intelligence studies as an alternative approach to the study of economics i am sitting at home looking through two thick books used in business education a hundred years ago and wondering how they are outdated. they are full of detailed knowledge about markets, products, production, and legal issue between countries. today everything is lifted to a more abstract level and many parts have become their proper disciplines. how successful has this change been when it comes to understanding business and economics? the study of economics, but even business and management today, are too far removed from the reality they are trying to describe. to study economics has instead ironically become a guaranteed way not to understand much about real economics; for example, how money is created and is distributed through private banks or how the gold market works. instead scholars know econometrics, or they adhere to some group with a favorite journal. as we know, far earlier than adam smith, for example with marco polo, at the heart of economics lies the notion of competitive advantage. in the thick books i am sifting through that notion is never lost. it’s all about understanding markets to find an opportunity or a niche. intelligence studies suggests that the way to become competitive is to learn about the world by focusing on cultures, history, geography, people of influence, markets, resources and knowledge. there is a strong relationship of causation between the survival of companies and that of a nation state, as the latter can be seen as the sum of the former. if we take one more step, the notion of competitive advantage has always been related to the study of geopolitics, realpolitik and today what we understand by geoeconomics. it is also closer to the german and english tradition of political economy, seeing that it is counterproductive for any attempt to understand societies to separate politics from economics, or from psychology for that matter. they are all parts of the same social system, as luhmann argues. try to take out any part and your miss the picture. the study of culture today is part of anthropology or sociology; thus, business students seldom learn much about it. the geography they are supposed to have learned in high school (but few do). the same for history. so, it is becoming clear that too many bits and pieces are missing in our education for us to be able to draw valuable conclusions about how to make money on a grand scale. when austrian economists wanted to take out history from economics there was a serious battle in european universities (“methodenstreit”). those arguing for removing history and ever more specialization won, in part because germany had lost wwii and the new superpower wanted to set its own rules, even in the study of people and society. the separation between micro and macroeconomics is now close to complete. and, what else is “marketing” but a subset of geography? students today study “marketing” instead of actual markets, in lagos or mumbai, assuming that all are more or less the same and that the models that university professors and consultants make up are universal. “entrepreneurship” is studied like an exciting new fruit, not as an ancient game of willpower, sweat and tears. do these studies really help young men and women become entrepreneurs? i doubt it. in the meantime, companies in the western world are being surpassed by their asian competitors, whose employees often do not have a business education. for as long as the western world was doing well economically, no one really questioned the subjects, models and theories presented at business school. it was assumed there was some sort of correlation, i guess, even though most successful entrepreneurs had a natural science background or no diploma at all. now things are different. a good way to start is by going back to the main question of competitive advantage. it’s there that intelligence studies are, defining methods for how to understand markets and events as they unfold before us. jisib has always tried to reflect this shift by publishing articles on markets, industries, different countries, new technologies, and especially software that shows how companies can become competitive. how to obtain a competitive advantage is still about gathering intelligence. what happened this week with the coup-d’état in guinea when president of guinea alpha condé was captured by the country's armed forces? no one at business school can tell you because they don’t study that. it shows the irrelevance of most modern social science. if we really want to understand economics, we should study what happens in the world’s many markets journal of intelligence studies in business vol. 11, no 2 (2021) p. 4-5 open access: freely available at: https://ojs.hh.se/ 5 and countries. in that sense intelligence studies is a better replacement for the study of economics in its current form. maune’s article “intention to use mobile applications in competitive intelligence: an extended conceptual framework” use utaut2 constructs to show how ci mobile applications can be used effectively. nuortimo and härkönen’s article “the first wave impact of the covid-19 pandemic on the nasdaq helsinki stock exchange: weak signal detection with managerial implications” argues that covid-19 was not a black swan event and use a social media firestorm scale to argue why. tulungen et al.’s article “competitive intelligence application: the case of geothermal power plant development in rural tompaso, north sulawesi, indonesia” presents a case for how ci is used in a power plant development project in indonesia. kula and naktiyok’s article ”strategic thinking and competitive intelligence: comparative research in the automotive and communication industries” is derived from a phd dissertation and shows how strategic thinking and competitive intelligence can be related. finally, poblano-ojinaga’s article “competitive intelligence as factor of the innovation capability in mexican companies: a structural equations modeling approach,” uses a structural equation modeling methodology to evaluate the relationships between competitive intelligence and innovation capability of mexican companies. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. again, i wish i could say that the covid-19 pandemic is soon over, but unfortunately it still seems to have a grip on our lives. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2021 jisib, halmstad university. all rights reserved. 30 comparative study of competitive intelligence practices between two retail banks in brazil and south africa a.s.a. du toit department of information science, university of pretoria, south africa e-mail: adeline.dutoit@up.ac.za received march 12, accepted 20 july 2013 abstract: using competitive intelligence (ci) can help developing countries to increase their competitiveness. this paper compares the ci activities between two retail banks in brazil and south africa. an e-mail survey in a sample of 2550 employees in a retail bank in brazil and 847 employees in a retail bank in south africa was carried out in which ci practices were measured. respondents in both countries were not very effective to conduct effective ci analysis. respondents from brazil consider information on operational risks as the most important while for south african respondents the most important information was on changing regulatory requirements. although there is a culture of competitiveness in both organizations, it is recommended that if they want to compete effectively in the global economy, they should create ci awareness by organizing ci training sessions for employees. keywords: competitive intelligence, brazil, south africa, banking sector introduction with the increased volatility of the business environment, companies rely on early detection of environmental changes so that they may respond with appropriate counter measures. since countries and companies require time to adapt to the changing environment they should have the ability to anticipate changes and imagine the consequences of alternative responses to those changes. competitive intelligence (ci) is a strategic tool to facilitate the identification of potential opportunities and threats. because ci improves decision-making, it helps a company to meet or exceed its objectives and business goals. according to waheeduzzaman (2002: 13) the ultimate goal of competitiveness is to improve the standard of living or real income of the citizens of a country. since companies actually compete in the global economy, many authors are of the opinion that when studying competitiveness, the focus should be on companies. the economic success of a country depends on its capacity to apply activities which create a competitive advantage, its ability to create an available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2013) 30-39 mailto:adeline.dutoit@up.ac.za https://ojs.hh.se/ 31 environment of transformation and progress, and its capacity to innovate (canongia, 2006: 58). ci has long been recognised as a strategic management tool that could enhance competitiveness. this perception of ci as a strategic tool is not exclusive to developed countries. ci is expected to play a key developmental role in developing countries as well. the need to enhance companies’ and by extension, countries’ competitiveness has grown rapidly. ci is essential, and will increasingly be a challenge in the years to come, especially for emerging economies (canongia, 2006: 59). problem investigated little research has been done on the application of ci in developing countries (dou, n.d.; dou, dou & manullang, 2005; du toit, 2003: 112) and the purpose of this paper is to compare the current situation with regard to ci processes between two retail banks in brazil and south africa. ci is always influenced by country-specific environmental factors and a questionnaire survey was conducted to compare ci activities in the two organisations. research questions: • why is ci important for organisations in developing countries? • what is the level of importance attached to ci in the two organisations? • what information on the external environment is important for the organisations to get a competitive advantage? • what ci techniques do the organisations use to analyse information? competitive intelligence de pelsmacker, muller, viviers, saayman, cuyvers, and jegers (2005: 606) stated that “ci is actionable recommendations arising from a systematic process involving planning, gathering, analysing and disseminating information on the external environment for opportunities, or developments that have the potential to affect a company’s or country’s competitive situation”. calof and skinner’s (1999: 24) view is closely related; they state that “at its most basic description, intelligence is analysed information”. ci is also defined as “the transformation of raw information regarding the competitive external environment into intelligence to support business decisions” (hughes, 2005: 5). “competitive intelligence focuses predominantly on qualitative research based on a well-developed process and relying also on a human source network” (fouche, 2006: 18). these definitions revealed ci to be a tool that transforms information into actionable intelligence that, if used in strategic decisionmaking, could enhance an organisation’s competitiveness. for the purpose of this research, ci will be defined as an ongoing, systematic evaluation of the external environment for opportunities, threats and developments that could have an impact on the organisation and influence proactive decision-making. ci is the process of developing actionable foresight regarding competitive dynamics and non-market factors that can be used to enhance competitive advantage. ci is concerned with the techniques used to select and filter information from a variety of sources, to interpret and analyse it, to communicate it to the right people and to use it effectively (xu, liao, li & song, 2011:745). competitive dynamics refers to the evolution of a company’s industry and the moves and countermoves of competitors, suppliers, customers, alliance partners and potential competitors (shih, liu. & hsu, 2010:2885). nonmarket factors such as government regulation, tariffs and the culture of a country impact competitive dynamics but are not suppliers of products or services to the industry (prescot, 1999:40). ci uses legally and ethically public sources to assess the strengths and weaknesses of a company’s competitors. ci in developing countries ci management is a well-established function in organisations in developed countries, because managers realise that if they do not monitor the actions and activities of their competitors, their strategic plans will fail. however, organisations in developing countries continue to be surprised by undesirable changes in the environment and it appears that the advances in managing intelligence are as yet largely unknown in these countries (nasri, 2011:58). kahaner (1996:61) states that ci has become the 'latest weapon in the world war of economics', in which many emerging economies view ci as a way to win economic wars against larger, more industrialised countries. by using their wits instead of weapons, these countries are able to 32 turn raw information into usable intelligence to further their economic status (calof & smith, 2010: 38). according to calof and skinner (1999:30) a country will under-perform without an appropriate ci infrastructure and he quotes prescott and gibbons by stating that “the key question is not whether governments should play a role in a company’s ci efforts but what should be the purposes and methods used by government.” countries such as france, sweden, japan and canada have recognized the value of government and industry working jointly in the development of an intelligence culture (calof & skinner, 1999: 24). hawkins (2004:42) and nasri (2011:53) emphasise that companies in developing countries should use formal processes of collecting, analysing and disseminating intelligence to successfully compete in the global economy. the new paradigm in development economics is based on self-analysis, self-reliance and selfrenewal, which would seem to necessitate a development-orientated intelligence policy in a country. currently most developing countries are weakly integrated with the global economy. for organisations to compete globally they are facing many challenges since consumers use the internet to compare products and prices and they need to stay ahead of their competitors (huggins, 2010:640). if this situation is to change, major infrastructural investment in information systems and services, as well as technical training, is required. utilising ci will enable organisations in developing countries to gain a greater market share and to compete successfully against international competitors (pellissier & kruger, 2011). ci in brazil the focus of this paper is the comparison between ci practices of a brazilian and a south african retail bank. substantial political changes in brazil since 1990 have led to greater information exchange and the brazilian society has been evolving into a knowledge society dealing with political changes, globalisation, new technologies, hyper competition and new global competitors, such as china (davis, 2007:1). brazil is among the world’s fastest-growing economies and the 9th largest economy in the world (datamonitor, 2012). like south africa is seen as the gateway to africa, brazil is the gateway to south america (libis, 2005:237). brazil offers limited infrastructure to businesses and has limited energy resources but the government is trying to establish a positive business environment that stimulates business growth (libis, 2005:239). prior to 1995 the oppressive government was a barrier to information sharing among businesses and brazil does not have a ci culture (libis, 2005:241) but ci plays an increasing important role in brazil. large firms and international companies with head offices outside brazil apply ci practices. a country’s environment supports or threatens economic growth through its policies. a country like brazil manages its competitive environment by relying on assets (land, people and natural resources) but is not necessarily competitive (garelli, 2003). the brazilian government and brazilian companies have realised competing in a global economy requires a strong vision of what exists outside the country’s borders. as a result, ci is becoming more accepted both as a profession and as an important business function. ci was introduced in brazil in the mid 1990s as an initiative of the national institute of technology. a ci interest group, the competitive intelligence society of brazil (abraic) was established and is sponsored by the government and industry. the growing market for ci created the development of consulting activities. various ci tools were developed (for example a national database of science competencies) (dou). ci in south africa the business environment is highly complex in south africa because of factors such as the country’s unique history, diversity, geography, political and institutional landscape. companies tend to be less dynamic and more resistant to change, compared to companies in developed countries. south africa faces new socioeconomic challenges and research capacity needs to be developed in the context of the global economy. before 1994 south africa was isolated from the rest of the world as a result of the apartheid regime and this inhibited competitiveness (viviers & muller, 2004: 54). the use of ci before 1994 has mostly negative connotations since south african intelligence activities were mostly pursued by state institutions. within a short period of time after the democratic elections in south africa in april 1994, the international market opened up. many industries were deregulated and privatised and 33 there was a large construction boom due to the 2010 soccer world cup. to survive many south african companies needed to extensively globalise their business activities to exploit country differences and worldwide markets. this prompted companies to become more sensitive to external environments which includes monitoring political/legal, economic, technological, sociocultural and industry forces such as competitors, customers and suppliers. currently south africa as a net exporter of strategic minerals and the ‘gateway’ to africa has an internal environment ideally suited to the use of ci by companies to gain the competitive edge in a developing domestic economy and a challenging external environment. ci is therefore enjoying increased prominence in south africa. south africa’s lack of global competitiveness, according to various competitiveness indices (blanke, 2007; imd, 2012: 704), has over the past few years become a contentious issue with the main focus on the inability of the country to escape its competitiveness trap. competitiveness concerns factors such as skills, higher education and training, efficient markets, the ability to harness the benefits of existing technologies and business sophistication (blanke, 2007). one of the most prominent indices include the imd’s (imd, 2012:713) world competitiveness yearbook, which analyses and ranks the ability of nations to create and maintain an environment that sustains the competitiveness of enterprises. countries that consistently rank high in these indices are the us, switzerland, denmark, sweden, germany, finland and singapore (blanke, 2007). common denominators of these leading countries are quality education and high spending on research and development (blanke, 2007). in contrast to leading competitors, south africa not only fails to improve its competitive position but its competitiveness is actually deteriorating. although ci is a relatively new concept in south africa, the competitive environment of south african companies is vast, competitors are numerous and technological advances staggering. with the recognition that competitive challenges and risks will increase significantly in the future, there is an increasing need to monitor the competitive landscape continuously to remain competitive. most companies recognise the need to improve the quality and integration of their ci, but may seem unsure of how to adopt more effective, integrated and systematic approaches to ci. multinational companies in south africa face unique challenges as far as ci are concerned (viviers, muller & du toit, 2005:246). many multinational corporations have their african head offices in south africa and have to provide strategic level intelligence to their boards of directors concerning their african operations (odendaal, 2004:48). research by viviers, saayman, calof and muller (2002:30) found that the largest companies in south africa have adopted ci in a comprehensive manner, including designing and setting up structures and appointing a dedicated ci staff. these are, however, few and limited to the largest companies in south africa or local subsidiaries of multinationals based elsewhere. research by du toit (2003:118) found that only 26% of manufacturing organisations have ci units, but that 76% of the organisations have a ci system. an interesting observation about the ci practices of south african companies is that the more companies rely on exports and interaction with the international market, the more they are inclined to adopt ci and the greater their understanding of the role and benefits of ci as a strategic business tool (viviers & muller, 2004). empirical survey of ci practices research methodology in spite of an increasing interest in ci in both countries, the state of ci in brazil and south africa remains fragmented for decision makers who need reliable information to deploy innovative policies for economic development. the banking market in brazil is dynamic and competitive despite involvement of the state with foreign banks gaining more presence. modernisation of the financial system in 1988 has led to the creation of multipurpose banks and foreign participation in the commercial banking system (datamonitor, 2012). brazil has the largest financial system in south america and the banking industry is diversified and competitive. the 200 public and private commercial banks have adopted international best practices (datamonitor, 2012). the top ten retail banks in brazil are abn amro, banco do brasil, bradesco, hsbc, itaú cef, safra, santander, 34 unibanco and votorantim (datamonitor, 2012). since 1990 the south african banking industry has gone through substantial changes. new bank legislation has been introduced and foreign banks have entered the domestic market (heppes & du toit, 2009: 60). south african retail banks operate in a very dynamic and complex competitive environment and the five major banking groups (absa, firstrand, investec, nedbank and standard) control 89.4 per cent of total banking assets in south africa. about 200 public and private commercial banks have adopted international best practices (datamonitor, 2012). the question is to what extent these differences in economic structure in general and banking activities in particular will have an impact on ci practices in retail bank activities in brazil and south africa. the purpose of the empirical survey was to investigate the current situation with regard to ci practices in a retail bank in brazil and a retail bank in south africa. the research question guided the design of the research in terms of what data were needed to answer the question, where the data were, how data were to be collected and how they were to be analysed. the study follows a quantitative research methodology. employees in the two retail banks were asked about their practices of competitive intelligence. the measuring instrument was a questionnaire which was compiled which was compiled to cover the theoretical constructs of competitive intelligence. the questionnaire was divided into three sections. section a focused on biographical data, section b on the competitive environment and section c on ci practices. the questionnaire used in this study is based on three questionnaires used in other empirical ci surveys (heppes & du toit (2009: 4866), pellissier and kruger (2011) and du toit and strauss (2010: 17-32)). of the sample frame of 110 000 employees in brazil and 31 000 employees in south africa a total of 2550 employees in brazil and 847 employees in south africa were randomly drawn by computer from the two retail bank’s employee databases to form the sample of this study. the questionnaire was e-mailed to the whole sample with a cover letter explaining the purpose of the research and its legitimacy. the data collection took place over a period of two months and during this period, several reminders were sent to the participants on a weekly basis. of the sample of 2550 employees in brazil, 615 employees (24.1%) returned completed questionnaires and of the sample of 847 employees in south africa, 346 respondents (40.85%) returned completed questionnaires. the credibility of the research was measured by the cronbach alpha coefficient and an overall coefficient of 78, 5 per cent was calculated for the results obtained. this is considered to be in the range of scores considered as being reliable. findings biographical data in brazil the gender of the respondents was mostly female (54%) while in south africa the majority of the respondents were male (69.5%). the length of employment differs between the two countries since the majority of the respondents in brazil (58%) have been employed by their current employer ten years or more while .the majority of the respondents in south africa (47.5%) have worked for their current employer for less than five years. in brazil 61.1% (376) of the respondents were on top management level with 38.9% (239) on middle management level while in south africa 68.8% (238) of the respondents were on top management level with 31.2% (108) on middle management level. this implies that more concern for ci in the south african organisation lies with top management. strategy to manage competitive environment in trying to establish whether there was a strategy in place to manage the competitive environment, 94,1% (579) of the respondents in brazil and 89% (308) of the respondents in south africa answered in the affirmative. it is interesting to note that 64% (394) of respondents in brazil and 70% (242) of respondents in south africa indicated that ci was always a key-component of company strategy and is used as input to the organisation’s annual strategic plan. this means that both organisations are competitor oriented and understand the significance of having a strategy in place to deal with competition. such a strategy may encourage innovation and alliance with customers, which 35 would lead to a competitive advantage. prescot (1999: 50) and calof and smith (2010: 37) concur with the above and affirms that having a strategy in place would have a positive impact on the strategic direction of an organisation. competitive situation according to table 1 both organisations appear to be in control of changes in the business environment with respondents in brazil coping slightly better with changes. table 1. coping with changes in business environment brazil south africa frequency percentage frequency percentage above average (i.e. they cope very well 299 48.6 143 41.2 average (i.e. they cope) 316 51.4 203 58.8 total 616 100 346 100 this correlates with kahaner (1996:93) who stated that organisations that are alert of changes in the environment will be least surprised and negatively affected when there are changes in their business environment. in assessing the perceived level of competition 64% (394) of the respondents in brazil and 59.8% (207) of the respondents in south africa are of the opinion that it is very intense while 36% (221) of the respondents in brazil and 40.2% (139) of the respondents in south africa believe that competition is intense. none of the respondents claimed that competition is not intense. information needs respondents were requested to indicate the frequency in which they require information on key elements of the competitive environment in which banks operate (see table 2). the actual number of responses is shown in brackets below the percentage value. table 2. information needs brazil south africa daily weekly monthly never daily weekly monthly never changing accounting/tax requirements 8% (49) 58% (356) 17% (105) 17% (105) 6% (21) 26 % (90) 44% (152) 2 4% (83) changing legal/regulatory requirements 2% (12) 18% (111) 45% (277) 3 5% (216) 9% (31) 34% (118) 57% (197) 0 % (0) local competitors 25% (154) 58% (356) 17% (105) 0 % (0) 3 1% (107) 42 % (145) 27% (94) 0% (0) foreign competitors 17% (105) 33% (203) 50% (307) 0% (0) 21% (73) 35% (121) 44% (152) 0% (0) interest rates 33% (203) 8% (49) 59% (363) 0% (0) 32% (111) 25% (87) 43% (148) 0% (0) inflation 17% (105) 0% (0) 83% (510) 0% (0) 10% (35) 14% (48) 76% (263) 0% (0) technological innovation 17% (105) 25% (154) 50% (307) 8% (49) 8% (28) 17% (59) 72% (249) 3% (10) leadership development 8% (49) 0% (0) 33% (203) 59% (363) 3% (10) 19% (66) 57% (197) 21% (73) 36 skills availability 8% (49) 17% (105) 75% (461) 0% (0) 12% (42) 24% (83) 64% (221) 0% (0) operational risks e.g. industry fraud 28% (172) 31% (191) 41% (252) 0% (0) 5% (17) 7% (24) 73% (253) 15% (52) on average respondents in both countries required updates to all listed classes of information on a monthly basis. information types for which updates were required less frequently were those with a longer term implications for the organisation, while those information types for which updates were required more frequently were those which require response from the organisation as/when they occur. the south african bank requires information on changing regulatory requirements more frequently than their brazilian colleagues while information on operational risks is required more frequently in brazil. this supports the finding by pellissier and kruger (2011) that south african organisations are cognisant of new government information legislation that impacts their organisation. information on skills development is important for both organisations. ci analytical techniques used a set of five questions sought to establish the techniques used to analyse information by the two organisations. according to figure 1 the three most popular techniques used by the respondents are swot analysis, competitor analysis and industry analysis. surprisingly best practices and scenario analysis are seldom used. a swot analysis is an important technique for both organisations since it may provide a comparison between the organisation and their competitors. overall, there appears to be a lack of the used of sophisticated techniques such as scenario analysis and best practices by both organisations. the brazilian organisation mostly used swot analysis while the most popular technique used by the south african organisation is industry analysis. this correlates with the finding by viviers et al. (2002:36) that south african organisations spend too much time collecting information and too little time on adding value to information by analysing it. figure 1. ci analysis techniques used 37 conclusion and recommendations using data from a ci survey sent to a retail bank in brazil and a retail bank in south africa the author has tried to establish whether there are significant differences between ci activities in retail banks in these two countries. to a certain extent the ci practices of the brazilian and south african retail banks are highly comparable. both organisations are competitor oriented and understand the significance of having a strategy in place to deal with competition while both seldom use sophisticated analysis techniques to analyse the information. within both retail banks there are definite elements of ci and therefore the proposal is to develop the existing capabilities further in accordance with best practices. however, there are some remarkable and significant differences. the length of employment differs and more respondents in south africa are on top management level. respondents in the bank in brazil cope slightly better with changes in the external environment. information on the changing regulatory environment is more important for the south african organisation with information on operational risks more important for the brazilian organisation. an obvious limitation of the study is that it utilised a sample of employees in one company in brazil and one company in south africa. the findings therefore cannot be generalised beyond the sample that took part in the survey. more comprehensive research is still needed to clarify all the underlying dimensions of ci to enhance understanding of these issues. this is an exploratory study aimed at determining the application of competitive intelligence in two retail banks in brazil and south africa. these limitations leave scope for further empirical research. as brazil and south africa become more integrated into the global economy it stands to reason that the global economy will have more of an impact on the countries’ economy. to this end it has become more crucial to monitor global events and trends and it is very important for both organisations to develop an integrated ci culture. ci analyses not just the environment but competitors and markets as well. therefore understanding the direction that competitors are moving to in the future is key to be able to counteract them timeously for both organisations. keeping abreast of domestic and international market trends and their potential impact on the organisation is vital. trend tracking needs to monitor the impact of not only product changes but also organisational changes such as future mergers and dissolutions. it is also recommended that both organisations should enhance a ci culture by creating ci awareness among employees and provide ci training sessions for new employees. it is concluded that the purpose of ci is to collect information about competitors to provide benchmarks, avoid surprises and identify opportunities. the case for ci to play a role in developing countries is strong, but not much literature is available on the application of ci in these countries. as discussed in this article, the two retail banks in brazil and south africa are already carrying out ci practices and the importance as well as the recognition of ci as a strategic instrument will inevitably increase in these two countries in the coming decade. in the light of the importance of ci in developing countries the hope is expressed that companies in brazil and south africa will realise that ci is not only a system to improve the decision making in companies and regions but that it is an important lever to facilitate the industrial development and innovation in developing countries. in both organisations the opportunity exists to take the current ci capabilities from predominantly defensive (avoiding surprises) and passive intelligence (benchmarking) to offensive intelligence with a primary goal of identifying opportunities. areas for future research in both organisations should focus on a stakeholder analysis to determine the key intelligence users. critical success factors for ci need to be identified. this includes issues such as senior management involvement, a focus on what is important to the organisations, the maintenance of ethical standards and the development of expertise in analysis and communication. list of references blanke, j. 2007. assessing africa's competitiveness in a global context. available 38 http://www.members.weforum.org/pdf./gcr/afri ca/1.1pdf : 1-26. 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(2020) on the relationship between competitive intelligence and innovation. journal of intelligence studies in business. 10 (2) 32-43. article url: https://ojs.hh.se/index.php/jisib/article/view/569 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index on the relationship between competitive intelligence and innovation jonathan calofa,b* and nisha sewdassc atelfer school of management, university of ottawa, canada; bnorth-west university, south africa; cdepartment of business management, university of south africa, south africa; *calof@telfer.uottawa.ca journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 2,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10, no. 2, 2020 thinking methods as a lever to develop collective intelligence ursula teubert pp. 6-12 big data analytics and international market selection: an exploratory study jonathan calof and wilma viviers pp. 13-25 atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzes, riccardo bonazzi and pp. 26-31 francesco maria cimmino on the relationship between competitive intelligence and innovation jonathan calof and nisha sewdass pp. 32-43 intelligent information extraction from scholarly document databases fernando vegas fernandez pp. 44-61 on the relationship between competitive intelligence and innovation jonathan calof a,b* and nisha swedassc atelfer school of management, university of ottawa, canada; bnorth-west university, south africa; cdepartment of business management, university of south africa, south africa *corresponding author: calof@telfer.uottawa.ca received 15 february 2020 accepted 4 april 2020 abstract innovation research suggests customer, competitor and market knowledge are important requirements for innovation. researchers in competitive intelligence (ci) have proposed that there should be a relationship between ci and innovation. yet despite both fields recognising the need for ci and related areas for innovation in their theories, there have not been many empirical studies that look at ci and innovation and those few studies that do exist have limited focus and have only looked at a small subset of ci variables (for example collection sources). the aim of this study is to examine if there is a relationship between ci and innovation. this was done by surveying strategic and competitive intelligence professional (scip) members and those attending scip events, and asking them about their intelligence practices and how innovative their company was. ninety-five questions were asked about ci structure and organization, intelligence focus, information sources used, analytical techniques used, communication methods, and the management of the intelligence efforts. of the 95 competitive intelligence measures used in this study, 56 (59%) were significantly correlated with the study’s measure of innovation. the measures within the ci organizational elements and ci management categories had the highest percentage of measures significantly correlated with innovation (90% and 89%). four of the ci measures had statistically significant correlations above .300. these included the extent to which business decisions in the organization were better facilitated/supported as a result of intelligence efforts (.355), the number of performance measures used in assessing ci’s performance (.322) and decision depth (.313), which is a measure of the number of decisions that utilized ci. as a study of this nature measuring the relationship between ci and innovation has not been conducted previously, the findings can be beneficial to organisations using innovation to succeed in the competitive environment. keywords competitive intelligence, competitive intelligence practices, environmental change, innovation 1. introduction innovation according to researchers within both the competitive intelligence and innovation fields requires an understanding of the competitive environment (christensen et al. 2015, paap and katz 2004, dogan 2017). this competitive environment is one that has been “rapidly changing where new competitors are entering the marketplace, and where current competitors are offering new products” (nasri 2012, 25). for organisations to survive in this environment, they need to be effective and proactive in identifying and responding to the opportunities, challenges, risks and journal of intelligence studies in business vol. 10, no. 2 (2020) pp. 32-43 open access: freely available at: https://ojs.hh.se/ 33 limitations posed by the external environments that they operate in. thus, innovation requires anticipatory capabilities through approaches such as competitive intelligence. while there is a plethora of research on innovation, very little of it looks at the link between competitive intelligence (ci) and innovation. further, as will be shown in this paper, the few studies that do look at ci focus only on selected aspects of ci and their link with ci (for example information collected), or on one dimension of intelligence practices (such as competitive technical intelligence). there has not been a study of the influence of each construct of the ci cycle with that of innovation. this includes the extent of formal intelligence structures, planning of ci projects, collection of information used for intelligence, analytical techniques used, communication of ci information, evaluation or management of ci. this paper takes a comprehensive view of ci including ninety-five ci variables and examines the relationship between these variables and innovation from ci practitioners. 2. literature review 2.1 competitive intelligence the ci professional association (scip) defines ci as “a necessary, ethical business discipline and/ or skillset for decision making based on understanding the competitive environment in order to drive to competitive advantage in a marketplace. any organization that has employees gathering information or developing insights on the external environment (competitors, external environment, customers, suppliers, technology, etc.) in order to make decisions is practicing some form of ci. ci validates decision making by introducing a disciplined system not only to gather information, but also to do analysis and disseminate findings about the external environment tailored with the intent to drive competitive advantage for their organization" (www.scip.org). as this definition is one that is provided by the scip and it encompasses the integrated nature of ci, it aligns well with the current study and will therefore be adopted as the definition of ci. this definition is consistent with the research by du toit (2015, 15) who provided a definition based on meta-analysis of 338 articles about ci between 1994 and 2014. the article defined ci as “a process or practice that produces and disseminates actionable intelligence by planning, ethically and legally collecting, processing and analyzing information from and about the internal and external or competitive environment in order to help decision-makers in decisionmaking and to provide a competitive advantage to the enterprise”. when assessing ci practice, researchers start with this and similar definitions and then survey practitioners regarding the extent to which they are conducting activities in a manner consistent with this definition. this includes asking questions about how the organization plans their intelligence activities, collects information (how they do it, what information), how it is analysed, communicated and how the intelligence process is managed (see fehringer et al 2006, calof et al. 2018). m-brain’s market intelligence framework and benchmarking tool assesses ci activities by looking at the scope of ci activities, stakeholder management, process, digitalization, deliverables, tools, organization, management & leadership and culture (m-brain 2020). the ci field in examining intelligence practice looks at how intelligence projects are run (the intelligence process) and how the intelligence process is managed. this is a broad holistic view of intelligence and the one adopted in this study. 2.2 innovation and competitive intelligence innovation is a very popular research topic, and much has been written about it. a search on abi-inform proquest on 24 april 2020 on peer reviewed publications with “innovation” as a subject found 45,561 articles. within this large stream of peer-reviewed articles on innovation, those that focus on ci or market insight and innovation are relatively small. a search for the terms “innovation and competitive intelligence” in the subject field yielded only 29 articles. expanding the search to include areas related to intelligence such as market insight and also environmental scanning did not increase results by much. while there are many articles where the terms competitive intelligence and innovation appear, these are not the focus of the paper (which is why subject matter was used). we changed the search to be “competitive intelligence” and innovation with the limitation being that it had to appear anywhere besides the full text as this would provide a second level of importance. this increased the total number of documents found to 76 articles, again not a lot. thus, it appears 34 that despite the growing popularity of innovation research, little of it has focused directly on ci and innovation. an additional search was conducted on google scholar using the terms “competitive intelligence and innovation” specifically looking for research conducted in the last two decades (2010-2020) and this revealed 103 articles. while there were some overlaps in the articles already found on abi-inform proquest, some more recent publications were identified from the 103 articles and used for the literature review. the articles that were found in this literature search fell into two broad categories: 1) research done by ci researchers who used constructs and theories from ci to examine the extent to which ci could help innovation and 2) research done by innovation researchers that focused more on innovation theory and constructs but would then look at how ci and ci related topics could improve innovation. table 1 provides a sample of the literature reviewed and information about these studies including the aspect of ci studied and how innovation was defined. brief details of the methods used for the studies are also reflected in the table including whether the study was empirical or theoretical. all 20 studies found in both the subject matter searches were found to be suitable for this study and are summarized. a few observations emerge from table 1 that necessitate this kind of study: 1) half the studies are theoretical and not empirical, thus there have not been many empirical studies done. 2) those studies that were empirical focused the ci portion of their study on only a subset of the organizations’ ci activities. this will be described in more detail below. 3) there is no consistency in how innovation measurement or performance is being conceptualized. for example, cerny (2016) looks at innovation management and dogan (2017) looks at strategic innovation. perhaps the most frequently occurring innovation construct in table 1 is around market leading innovation as embodied in duan et al. (2020) with new product development, lee and lee (2017) with business opportunity, tahmasebifard (2018) with market performance, and tainev and bailetti (2008) with innovation performance. several researchers have proposed that there should be a relationship between ci and innovation but for the most part these have been theoretical studies (e.g. vargas et al. 2017, mihaela, sabin and raluca 2017, veugelers, bury and viaene, 2010). those studies that have been empirical in nature have tended to limit their focus on the impact of ci on innovation using only a small subset of ci practice variables. for example, tanev and bailetti (2008) only looked at the kinds of information gathered and their relationship to innovation. poblano-ojinaga et al. (2019, 62) looked at the basic collecting and analysing information, predicting market movements and technology changes into consideration when determining the relationship between ci and innovation capabilities. in total this study had only a handful of questions about ci. furthermore, the authors acknowledged that their findings reflected a lack of sufficient statistical evidence to prove their hypotheses that ci influences innovation capability and ci influences intellectual capital. hence the current study is essential and timely to respond to the findings of poblano-ojinaga et al. (2019, 65). in summary, there are not a lot of papers focusing on ci and innovation. half of those that we found are theoretical and the empirical studies only looked at a limited number of ci variables. 3. methodology the objective of this study is to examine if there is a relationship between ci and innovation. this was done by asking ci practitioners how effectively they felt their organization coped with changes in the business environment with innovation related selection options and correlating this response with ci. 3.1 the competitive intelligence measurement a survey was developed by the study authors. the survey was revised based on the one used in 2006 by fehringer, hohhof and johnson (2006) and modified to reflect research on ci practice conducted since that time and reported either in the academic literature or the professional literature and discussions with ci practitioners and academics. the revised questionnaire was then sent to five leading ci academics and practitioners for comment and validation. the revised survey was pre-tested on scip members and revised again based on their feedback. table 1 literature on ci and innovation concepts and measures. method: e = empirical, t = theoretical. author/date ci constructs innovation constructs method measures used cerny (2016) competitive technical intelligence innovation management e collection, analysis dogan (2017) strategic intelligence basic elements of strategic innovation t culture, structure, systems and processes duan, cao, & edwards, (2020) business analytics, environmental scanning, data-driven culture new product development and meaningfulness e business analytics directly improves environmental scanning which in turn helps to enhance a company's innovation eidizadeh, salehzadeh, & ali, (2017) business intelligence organisational innovation e collecting, processing, knowledge sharing (dissemination) lee & lee (2017) competitor intelligence business opportunity t data collection, analysis mihaela, sabin & raluca (2017) competitive intelligence innovation strategy t collect, compile, analysis, communicate nemutanzhela & iyamu (2011) competitive intelligence information systems (is) innovation e collection, dissemination of information awareness norling et al. (2000) competitive technical intelligence (planning, collecting, analysing and dissemination) innovation process t intelligence resources used to seek out technology opportunities. paap and katz (2004:13) anticipating change and drivers of technology disruptive innovation t managing disruptive technologies by detecting new technology and customer needs paap (2007) competitive technical intelligence innovation new product positioning t planning; collection, assessment (evaluation) poblano-ojinaga, lópez, gómez, & torres-arguelles (2019) competitive intelligence innovation capabilities, ip, early warning e collection, analysis of information spinolaa, bezerrab, & gregolina, (2008) competitive intelligence technological innovation e identification of needs, planning, collection, analysis, dissemination and evaluation. tahmasebifard, (2018) competitive intelligence, market intelligence, competitor intelligence, technological intelligence market performance e general ci activities tarek et al. (2016) competitive intelligence, business intelligence mediation and moderation effects of innovation e collection, analysis and processing, sharing and dissemination, and memorizing of strategic information tanev & bailetti (2008) competitive intelligence innovation performance e information collection vargas, perez & franco (2017) ci practice disruptive innovation t ci can be an important aid to managers of established organizations on predicting and acting in the face of disruptive innovations. veugelers, bury and viaene (2010) technology intelligence disruptive innovation t planning, collection, analysis, reporting watts et al. (1998) competitive technical intelligence technological innovation t r & d profile, supporting technologies, gap analysis zhang et al. (2015) competitive technical intelligence technology road mapping t r&d, existing and potential collaborations in technology development, technological trajectories zhang et al. (2016) technical intelligence technological forecasting e data collection, analysis based on the fehringer et al. (2006) survey, literature review, discussions, expert review and pre-test, the final survey had 95 questions that looked at various aspects of ci practice that are reported in this paper. ten questions were asked about ci organization (such as structure, formal processes, employee involvement in ci). six questions were asked about the amount of time spent in each phase of the intelligence process. twenty-five 36 questions were asked about intelligence planning and focus activities. seventeen questions were asked about the sources of information used for ci. thirteen questions were asked on analytical techniques used. ten questions were asked about the methods used to communicate intelligence and fourteen questions about how ci was evaluated. further details on the design and delivery of the survey is elaborated on in calof, arcos and sewdass (2018, 663). 3.2 measuring innovation we adopt a measure of innovation that is based on how the organization copes with changes in the environment. the question posed was “in your opinion, how well does your organization cope with changes in the business environment?” respondents could select from four options which ranged from “we are the leaders in innovation – we drive the change” to “we do not cope well – below average” in using this approach, we follow the conceptualization of innovation as espoused by leading innovation writers who advocate that innovation is about responding to factors within the business environment. for example, one of the best-selling innovation books is “innovation: the five disciplines for creating what customers want” (carlson and wilmot 2006). clayton christensen developed a theory of disruptive innovation which he introduced in 1995, which has as its key tenants challenging existing competitors by improving products and services in a way that exceed the needs of some segments of the market (customers) with competitors either underestimating the threat of the new technology or being slow to respond (christensen, raynor and mcdonald 2015). thus, much of the innovation literature does suggest that innovation is about leading the market (being disruptive). by asking the respondent how they respond to changes in the environment and if in fact they lead/drive the change would therefore be a conceptualization of christensen’s disruption innovation and carlson and wilmot’s five disciplines. we recognize that while this measure of innovation is consistent with the theory in the innovation, the field does have far more measures such as patents filed and sales from new products and in most of the innovation studies multiple measures are used, but for this study how well respondents cope with changes in their business environment with one of the options being that they lead the change (innovation) can be viewed as a suitable measure of innovation. however future studies should use more complex measures that are more consistent with the innovation field. the final survey which contained the 95 ci dimension questions and the one innovation question was then sent to scip members and also distributed at scip events (chapter meetings and conference). with the help of scip, 420 surveys were returned of which 248 had details of all elements of their ci activities while the remainder had only partial details (defined as between 25% and 75% of the questionnaire filled in). 4. study results how innovative were the respondents? four hundred and twenty replied to the study’s innovation measure. ten percent replied that they drove change within their industry and that they were leaders in innovation; 31% were above average in dealing with industry change; 46% were average and coped with environmental changes, while 13% responded that their companies were below average. the range in responses to the innovation question, coupled with the large number of responses, provides a rich base of information to examine the elements of intelligence associated with the study’s operationalization of ci. for this study, we correlated 95 measures of ci with the innovation measure. of these, 56 (59%) were significantly correlated with the study’s measure of innovation (table 2). the measures within the ci organizational elements and ci management categories had the highest percentage of measures significantly correlated with innovation (90% and 89%). four of the ci measures had statistically significant correlations above .300. these were the extent to which business decisions in the organization were better facilitated/supported as a result of intelligence efforts (.355), the number of performance measures used in assessing ci’s performance (.322) and decision depth (.313), which is a measure of the number of decisions that utilized ci. not having any ci performance measures had a -.301 correlation with innovation. thus, at the onset it appears that those ci functions that were more integrated into the organization’s decision making with clear performance measures were associated with organizations that were more innovative. the remainder of this section provides details on the study results for the 95 measures. 37 table 2 summary of study results. m/q = number of measures per questions asked; stat sig = number statistically significant; % sig = percent significant. correlations between: m/q stat. sig. % sig. ci organizational elements and innovation 10 9 90% time spent in each phase of the intelligence process and innovation 6 3 50% ci planning and focus and innovation 25 19 76% sources of information used for ci and innovation 17 3 18% analytical techniques used for ci and innovation 13 6 46% methods used for communications of ci and innovation 10 4 40% how ci is evaluated and managed and innovation 14 12 86% total 95 56 59% table 3 (a)the relationship between having a ci unit and innovation. below avg. = innovation: below average (of a total 25); avg = innovation: average (of a total 118); above avg. = innovation: above average/leads (of a total 105); (b) a.sig= asymptotic significance (2-sided); a. 1 cells (16.7%) have expected count less than 5. the minimum expected count is 2.92. (c) ase = asymptotic standard error (not assuming the null hypothesis); t app = approximate t (using the asymptotic standard error assuming the null hypothesis); sig app = approximate significance (based on normal approximation). (a) below avg. avg. above avg. we have a ci unit (219) 19 101 99 we don’t have a ci unit (29) 6 17 6 (b) value df a.sig pearson chi-square 8.143a 2 .017 likelihood ratio 8.095 2 .017 linear-by-linear association 8.101 1 .004 n of valid cases 248 (c) value ase t app. sig app interval by interval pearson's r .181 .063 2.888 .004 ordinal by ordinal spearman correlation .179 .060 2.847 .005 n of valid cases 248 4.1 ci organizational variables and innovation the survey explored many dimensions of ci organization and structure. as mentioned in the overview, those organizations that responded that they had a ci function that informed decisions were more innovate. there were however nine additional measures of ci organization used. the study asked questions about several elements of the ci organization starting with if they have an intelligence unit. table 3 presents the correlational information, and associated tables. with a significant positive correlation of .181, it was evident that having a ci unit was positively associated with innovation. in looking further at the crosstabs, which were also statistically significant, innovation appears to be associated with having an intelligence unit. of the firms that said they either were above average or lead the industry, 94% had an intelligence unit. questions were also asked about the structure of the ci function and its role within the organization. the correlation between the 10 ci organization questions and innovation are provided in table 4. table 4 association between intelligence organizational variables and innovation. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). ci organizational variables correlation with innovation business decisions are facilitated/supported as a result of ci .355** full time ci resources .136* formal ci strategy .145* formal ci procedures .153* ci ethical guidelines .111 manager with ci responsibilities .185** employees know about ci .222** employees participate in ci .271** years that the ci function been in existence .170** do you have a ci function .181** respondents were asked about whether their organization had a formal ci strategy, specific ci ethical guidelines and a manager with ci responsibilities. these are measures of ci formality and in all cases were positively associated with innovation. part of ci formality is the extent to which it informs management decision (integration into the 38 senior management of the organization) and the extent to which employees are aware of the function and participate in its activities. all correlations between these measures and innovation were positive and statistically significant, with its role in informing decisions at .355 and employees participating in it at .271 having the highest correlations to innovation in this category. integrating all employees in an organization’s intelligence effort has long been acknowledged as something that enhances ci performance (calof, santilli and richards 2018). it is also associated with innovation in the open innovation literature (veugelers, bury and viaene 2010). 4.2 4ci process dimensions and innovation as mentioned in the literature review section, intelligence is developed, not collected. thus, the ci literature focused on intelligence as an outcome of what is termed the wheel of intelligence, which involves planning, collection, analysis, communication and various management activities. in the study, respondents were asked what percent of intelligence time was taken in each of these activities (the total had to add up to 100%). table 5 provides the correlation of the time spent in each phase of the intelligence process with innovation. three out of the six correlations were significant. management of ci measures (managing the project and evaluating the intelligence project) were significantly and positively correlated with innovation while collection was negatively correlated with innovation. this latter result would appear to indicate that spending more time collecting information as part of the ci project leads to lower innovation. ci theorists have consistently stated that intelligence involves a lot more than just collection and that in fact past studies have put collection time around 25% of total intelligence activity (see calof et al 2018). 4.3 ci planning/focus and innovation three sets of questions looked at the focus of the organization’s intelligence efforts. this is a key dimension of planning: business decisions supported by ci, temporal orientation of the intelligence projects (how forward-looking they were) and ci deliverables. in addition, there was a question about formal planning for trade show intelligence. table 6 provides the correlations between these three sets of planning questions and the study’s innovation measure. 4.3.1 business decisions supported by ci respondents were given eight decisions and asked to assess the extent to which ci supported these decisions. all eight were significantly correlated with innovation. decision depth (a composite measure of the eight decision areas supported by ci) had the one of the highest significant correlations in the entire study (.313) with research/technology development being the most strongly correlated decision with innovation, followed by customer profiles (.256). table 5 process dimensionthe wheel of intelligence. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). ci process dimension correlation with innovation % ci time spent planning your intelligence project 0.122 % ci time spent collecting the information -.134* % ci time spent in analysis (piecing together collected data and analyzing) -0.031 % ci time spent communicating the intelligence (formatting intelligence deliverables, reports, writing the reports) -0.064 % ci time spent managing the project including meeting with clients .149* % ci time spent evaluating the intelligence project .146* 4.3.2 temporal orientation of ci projects respondents were asked to break down the percentage of intelligence projects undertaken by how forward-looking they were. four categories were provided: less than one year, one to five years, five to ten years and over ten years. the total percentage for the four categories had to add up to 100%. of the four, two had significant correlations with innovation: temporal orientations of over ten years with a .199 correlation and under one year with a negative correlation of -.149. this suggests that shorter temporal orientations are negatively associated with innovation and longer-term orientations associated with higher levels of innovation. 39 table 6 planning and focus dimensions and innovation. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). ci planning and focus questions correlation with innovation decision depth .313** ci supports research or technology development .268** ci supports market entry decisions .247** ci supports reputation management/ communication/ public relations .243** ci supports regulatory or legal .209** ci supports mergers & acquisitions, due diligence or jointventure assessment .177** ci supports sales or business development .158* ci supports corporate or business strategy decisions .148* ci supports product development .137* ci temporal focus percent more than 10 years .199** ci temporal focus percent less than 1 year -.149* ci temporal focus percent 6 10 years 0.119 ci temporal focus percent 1 5 years 0.074 competitive intelligence product depth .284** customer profiles .256** supplier profiles .250** technology assessments .231** early warning alert .215** executive profiles .199** political analysis .155* competitive benchmarking 0.106 economic analysis 0.098 market/industry report/analysis 0.039 company profiles 0.031 trade show intelligence plan done .215** 4.3.3 competitive intelligence products or deliverables respondents were given a list of ten different ci products/deliverables and asked to assess the frequency each was done using a four-point likert scale (from never to frequently). six of these were significantly correlated with innovation. customer profiles, supplier profiles, technology profiles and early warning alerts were the most strongly correlated with innovation, with correlations above .20. these results collectively appear to indicate that innovation is more correlated with an intelligence focus that covers more areas of their external environment, is focused longer term and in which technology, customers and suppliers are focused on. finally, in terms of formal planning within ci activities, there was a significant and positive correlation between doing a trade show intelligence plan and innovation (.215). what is interesting about this result is the information collection question (discussed in the next section) which did not yield a statistically significant correlation with innovation, although having a trade show intelligence plan did. this suggests that planning for collection activities may be more linked to innovation than the collection activities themselves. this is consistent with the view in intelligence that focus and planning are important. 4.4 ci collection and innovation in the survey, participants were given a list of seventeen sources of information and asked to evaluate the importance of each to their organizations ci efforts. of all areas in the study, collection sources yielded the fewest statistically significant correlations with innovation (table 7). of the 17 sources, only three were statistically significant. only use of social media in general and twitter, blogs and wikis had positive correlations with innovation. in general, the kinds of information used beyond social media did not appear to have an association with innovation. table 7 information sources used innovation. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). information sources use correlation with innovation publications (print/online) -0.073 internet websites (free) 0.006 commercial databases (fee) -0.005 social media .198** internal databases 0.072 company employees 0.089 customers 0.088 suppliers 0.088 industry experts 0.102 government employees 0.059 association employees 0.089 linkedin used for ci 0.068 facebook used for ci 0.108 twitter used for ci .165** blogs / wiki used for ci .228** wiki 0.137 trade show/conference importance for ci 0.090 4.5 ci analysis and innovation those surveyed were asked if they used analytical techniques in their ci activities. in total, 84% responded that they did. there was 40 no significant correlation between using analytical approaches and innovation. the correlation was extremely low and not statistically significant (.088, table 8). however, taken individually, several of the analytical techniques were correlated with innovation: business analytics, benchmarking, technology forecasting, scenario analysis, financial analysis and customer segmentation analysis were all positively correlated with innovation. this would suggest that it is not doing the analysis that is associated with being innovative but the kind of analysis you are doing. for example, several of these techniques are associated with technology-oriented analysis (benchmarking, technology forecasting, and scenario analysis). technology oriented intelligence topics as mentioned earlier had higher correlations with innovation and those intelligence topics that are more forward-looking temporally (which are associated with technology) are also more positively associated with performance. from the planning and analysis sections it appears that focusing on technology and customers and being more forward-looking is more associated with innovation. table 8 analysis and innovation. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). analysis question correlation with innovation does your organization use analytical methods or models to generate ci? 0.088 business analytics for competitive intelligence .288** benchmarking (best practices) .160* technology forecasting .156* scenario analysis .148* financial analysis and valuation .132* customer segmentation analysis .128* swot analysis 0.097 indications and warning analysis 0.087 competitor analysis 0.077 industry analysis 0.043 patent analysis -0.031 competitive positioning analysis -0.098 4.6 ci communications and innovation the survey asked about the use of nine different communication methods for intelligence findings (there was also an “others” category) and a composite score called communications depth. only four of these had a statistically significant correlation with innovation with the highest being warning alerts at .205 (table 9). this is consistent with the literature where duan, cao and edwards (2020) also found early warning alerts useful for identifying new product development and their meaningfulness, and lee and lee (2017) who used patent and trademark data as early warning about competitors’ technology development. other studies also alluded to the use of early warning alerts to assist them in managing disruptive innovation (veugelers, bury and viaene, 2010; paap and katz 2004). table 9 communications and innovation. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). communications question correlation with innovation communications depth .184** warning alerts .205** presentations / staff briefings .164** teleconference .155* central database 0.117 printed alerts or reports 0.072 company intranet 0.045 personal delivery 0.044 newsletters 0.025 e-mails -0.024 4.7 ci management/evaluation and performance respondents were given 13 ci evaluation/performance measures and asked which ones were used by their organization. a composite total number of performance measures was calculated by adding up all measures used for a fourteenth measure. of the fourteen measures, twelve had statistically significant correlations with innovation (table 10). use of multiple measures had the strongest correlation with innovation, while not having any performance measures had a strong negative association with innovation (0.308). this was one the four largest correlation in the study and would suggest that 41 it is important to have some effectiveness measures of ci activities for innovation. consistent with the results reported in this paper, those measures associated with the longer term, customers and technology were the ones most associated with innovations such as new products or services, strategies enhanced and customer satisfaction. table 10 ci management/evaluation and innovation. *correlation is significant at the 0.05 level (2-tailed). **correlation is significant at the 0.01 level (2-tailed). ci performance measure used correlation with innovation total number of performance measures .322** we have no effectiveness or value measures -.308** new products or services .244** strategies enhanced .222** customer satisfaction .213** profit increases .213** ci productivity output .202** new or increased revenue .175** decisions made supported .160* cost savings or avoidance .153* return on ci investment .151* financial goals met .140* time savings 0.095 5. conclusions and areas for future research this study found a significant relationship between 59% of the study’s ci variables and innovation with the strongest correlations being in ci organization variables, ci management variables, ci focus and planning variables and innovation. using a more comprehensive measurement of ci (95 variables) that looks at the many areas of intelligence enables the field to better understand not just whether ci is related to innovation but specifically what aspects of ci are related to it. for example, when the question is asked “do you do formal analysis?”, the relationship between that and ci is not significant, but the type of techniques used are significantly related to innovation. breaking down planning and focus into different foci, different products and different temporal orientations similarly provides insights for innovation. for example, the study noted that temporal orientations of less than one year were negatively correlated with innovation while orientations on projects of longer than 10 years were positively correlated with innovation. this does not mean that organizations should not have short term intelligence topics, but it does mean that they need to spend time in longer-term intelligence projects as well. in summary, the approach taken in this study has found significant relationships between various ci process and structure variables and innovation and provided insights into what elements of the ci process and structure are most 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(2020) big data analytics and international market selection: an exploratory study. journal of intelligence studies in business. 10 (2) 13-25. article url: https://ojs.hh.se/index.php/jisib/article/view/567 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index big data analytics and international market selection: an exploratory study jonathan calofa,b* and wilma viviersb atelfer school of management, university of ottawa, canada; bnorth-west university, south africa *calof@telfer.uottawa.ca journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 2,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10, no. 2, 2020 thinking methods as a lever to develop collective intelligence ursula teubert pp. 6-12 big data analytics and international market selection: an exploratory study jonathan calof and wilma viviers pp. 13-25 atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzes, riccardo bonazzi and pp. 26-31 francesco maria cimmino on the relationship between competitive intelligence and innovation jonathan calof and nisha sewdass pp. 32-43 intelligent information extraction from scholarly document databases fernando vegas fernandez pp. 44-61 big data analytics and international market selection: an exploratory study jonathan calof a,b* and wilma viviersb atelfer school of management, university of ottawa, canada; bnorth-west university, south africa *corresponding author: calof@telfer.uottawa.ca received 15 february 2020 accepted 4 april 2020 abstract a great deal of information is available on international trade flows and potential markets. yet many exporters do not know how to identify, with adequate precision, those markets that hold the greatest potential. even if they have access to relevant information, the sheer volume of information often makes the analytical process complex, time-consuming and costly. an additional challenge is that many exporters lack an appropriate decision-making methodology, which would enable them to adopt a systematic approach to choosing foreign markets. in this regard, big-data analytics can play a valuable role. this paper reports on the first two phases of a study aimed at exploring the impact of big-data analytics on international market selection decisions. the specific big-data analytics system used in the study was the trade-dsm (decision support model) which, by screening large quantities of market information obtained from a range of sources identifies optimal product‒market combinations for a country, industry sector or company. interviews conducted with trade-dsm users as well as decision-makers found that big-data analytics (using the trade-dsm model) did impact international market-decision. a case study reported on in this paper noted that trade-dsm was a very important information source used for making the company’s international market selection decision. other interviewees reported that trade-dsm identified countries (that were eventually selected) that the decision-makers had not previously considered. the degree of acceptance of the trade-dsm results appeared to be influenced by trade-dsm user factors (for example their relationship with the decision-maker and knowledge of the organization), decision-maker factors (for example their experience and knowledge making international market selection decisions) and organizational factors (for example senior managements’ commitment to big data and analytics). drawing on the insights gained in the study, we developed a multi-phase, big-data analytics model for international market selection. keywords analytics, big data, export decision-making, international market selection 1. introduction choosing an international market is an important decision. there is a plethora of information from numerous sources and dozens of analytical models available to help people make the international market selection decision. while there has been much research conducted on international market selection, weaknesses (as described below) are evident in studies that look at the application of big-data analytics in the evaluation and selection of markets. this paper reports on a preliminary study conducted to start addressing this void in the journal of intelligence studies in business vol. 10, no. 2 (2020) pp. 13-25 open access: freely available at: https://ojs.hh.se/ 14 literature. the paper discusses the results of the first two phases of the study, which involved interviewing users of an international market selection big-data analytics system, called the trade-dsm. also interviewed were decision-makers who have used the tradedsm output. the paper identifies a link between the application of the trade-dsm and international market selection, and proposes a big-data analytics and international market selection model based on the information gathered from the interviews. in addition, the paper presents a case study to illustrate the proposed big-data analytics model. 2. literature review: international market selection as a big-data analytics challenge one of the most efficient ways of enhancing firms’, and consequently countries’, growth is by stimulating exports. increased exports directly and positively impact job creation, poverty alleviation and economic development, and help to promote sustainable and balanced economic growth in a country or region (czinkota and ronkainen 1998; steenkamp et al. 2012; los et al. 2015). in the executive opinion survey of the world economic forum’s global enabling trade report (2016), respondents were asked to select the five (out of a possible 12) most problematic factors affecting their ability to export more efficiently and effectively, ranking them from 1 (most problematic) to 5 (least problematic). the factor that most executives said was the most problematic and therefore the most important was the identification of potential markets and buyers of goods (wef 2016). in the literature, the problems associated with the identification of potential markets tend to fall into two categories: the lack of information and the lack of an appropriate decision-making methodology. while there is a plethora of information on international markets (see, for example, https://globaledge.msu.edu/), exporters ‒ and in particular, early-stage exporters ‒ do not know how and where to find the necessary international market information. this lack of knowledge of where to find information on possible export markets has often been cited by exporters (and scholars) as one of the most challenging export barriers to overcome when firms wish to enter new international markets and/or expand their current export operations (johanson and vahlne 1977; reid 1981; wiedersheim-paul et al. 1987; katsikeas and morgan 1994; leonidou 2004). souchon et al. (2015) emphasise the importance of export market orientation as the key differentiator between successful and less successful exporting firms. research points to the importance of international market selection being scientifically determined, and not the result of hearsay or causal analysis, if firms are to generate sustainable returns (cameron et al. 2017; calof and lane 1988). at the exporter level, the challenge is to determine which markets offer realistic opportunities in terms of products and markets (wef 2016). at the macro level, governments and policymakers need to introduce export assistance programmes or information services that focus on the intelligence needs of exporters (calof 1997). these needs relate to determining the best markets for their countries and companies and being assisted in accessing them, for example, through governments’ negotiations of trade agreements and the formulation of appropriate policies and related measures (kühn and viviers 2012; cuyvers et al. 2012b, lederman et al. 2006, 2016; cameron et al. 2017). given the growing importance and expansion of international business over the years, it is not surprising that there has been a corresponding increase in the amount of information available to help in the selection of export markets. websites such as global edge insights (globaledge.msu.edu), the federation of international trade associations (www.fita.org/webindex.html) and gapminder (www.gapminder.org) provide access to many sources of information that assist international market selection. gapminder, for example, has well over 100 variables that can be used to select export markets. the information for these variables is drawn from numerous statistical agencies, governments and consulting firms around the world. the challenge, therefore, for exporters and policymakers is how to harness and correctly interpret the huge volumes of information that lack structure and coherence and, moreover, are constantly being revised and embellished (cameron et al. 2017). although all firms require information on which to make informed business decisions, in the case of exporters the importance of acquiring the correct information is even greater because of the complexities of the international business 15 environment and the export process itself (souchon and diamantopolous 2000; kühn and viviers 2012). it is not just the amount of international market selection information that has exploded over the years. the number of analytical models and theories for selecting international markets has increased as well. the speed at which scientific research is accelerating, accompanied by the sheer volume of information, is making it very difficult for even the most knowledgeable expert to keep up with developments in their own industries (hughes 2017). ozturk et al. (2015) examined the international market selection literature finding dozens of such models. they compared many of the different models and then summarised the criteria that were used in these studies. they divided the criteria into six broad categories: i. demographic environment, including for example population, age and gender segments, income distribution, market size, infrastructure, geographical/physical distance, market similarity and human resources. ii. political environment, including for example political climate/stability, country risk and corruption. iii. economic environment, including for example economic stability, market growth/development, economic/market intensity, market consumption/middle class, economic freedom, long-term market potential, trade agreements, trade barriers, investment incentives, tax advantages and financial risk factors. iv. socio-cultural environment, including for example cultural distance, psychic distance, language distance, education level and literacy rate. v. sector/product-specific indicators, including for example competitive landscape, customer receptiveness, demand potential and personal values of consumers. vi. firm-specific indicators, including for example strategic orientation of the firm, network relationships, firm entry barriers, motivations for growth and reputation. based on a comprehensive review of many international market selection studies, ozturk et al. (2015) proposed a foreign market opportunity assessment (fmoa) model which used country responsiveness, growth potential and aggregate market measures. czinkota and ronkainen (2012) proposed a multi-level process model for international market selection involving: i. preliminary screening: this involves doing an initial assessment using typical criteria such as market size, market growth rate, fit between customer preferences and the product, and competitive intensity. ii. identification/in-depth screening: this involves doing an assessment of industry attractiveness and doing forecasts of costs and revenues related to short-listed countries. iii. final selection: this involves arriving at the choice of market that best matches the company’s objectives and leverages available resources in the most effective way. there are many more models available for choosing international markets. the green and allaway shift-share model, papadopulous et al.’s trade-off model, the international trade centre’s (itc) multi-criteria method, the gravity model, the product space network methodology, canada’s trade opportunity matrix and the trade-dsm are but a few (steenkamp et al. 2012). cameron et al. (2017: 140) made reference to this growing number of models and frameworks as follows: “in determining such opportunities, consideration needs to be given to aspects demonstrated by e.g. gravity modelling (the so-called work horse of international trade), such as geographic distance, cost of logistics, market demand characteristics such as size, trends and growth; tariff and non-tariff barriers; competition; comparative advantage; revealed trade advantage; and local production capabilities; to name but a few. all of these aspects carry with them the real world implication of masses of information and data that need to be considered by policy and business decisionmakers, placing this challenge firmly into the realm of so-called big data.” 16 kabir and carayannis (2013) also noted this by writing that many firms understand that there is more knowledge to be gained and more insights to be extracted from available big data. therefore, exporters and governments need practical ways of overcoming this big-data challenge ‒ particularly the analytical challenge of identifying the most promising export opportunities (markets and products) from the substantial mass of information that is available. cameron et al. (2017: 140) put this squarely in the big-data analytics arena, stating: “what countries therefore need is a practical way of tackling the ‘big data’ challenge in international market selection, i.e. efficiently identifying the most promising export opportunities at a given point in time from the confusing mass of information that is constantly spilling into the public domain in the form of data sets, research findings, industry and government analyses, and general commentaries.” 3. methodology 3.1 selection of the trade-dsm system there are a few big-data analytics packages designed to help with international market selection decisions. for this, the trade-dsm was selected as it was specifically designed for international market selection purposes and has been widely used (cuyvers et al. 2012b). for example, since 1995, the trade-dsm has been applied in various countries, including belgium, thailand, rwanda, the czech republic, greece, thailand and the usa (at state level – louisiana), in addition to south africa (cameron and viviers 2017; oluwade 2018; jansen van rensburg et al. 2019). it has also received favourable reviews from the international trade centre (itc 2017) as well as the wto (see steenkamp et al. 2016). the trade-dsm methodology was initially developed to find the product‒market combinations with the best prospects of export success for a single country, and was primarily aimed at export promotion organisations (see cuyvers et al. 1995). since 1995, the tradedsm methodology has been further developed to provide a view of all the potential product‒ market combinations that national and provincial governments, industry associations, sector groups and exporters are interested in analysing for the purpose of strategic decisionmaking. the trade-dsm system evaluates global trade data from many sources using built-in analytical programmes that assess trade flows between countries. the system allows users to focus on trade flows of specific products, which are identifiable by detailed, 6-digit international tariff codes. furthermore, the system provides for the application of various filters to identify those opportunities with the highest product export potential. these filters include macroeconomic environment, operational environment and political risk, size and growth of markets, competition in the market, accessibility of a market, maturity of a market, and the ability or capacity of the home market to supply the export goods (see figure 1) (cuyvers et al. 2012a; trade advisory 2020). the international trade data supporting the trade-dsm comes from several different sources, such as un comtrade, cepii baci databases, the credendo credit insurance figure 1 illustrative overview of the trade-dsm methodology. from cameron and viviers (2015), adapted from jeannet and hennessey (1988: 139). 17 group, the international monetary fund (imf), the international trade centre (itc), the world bank, the united nations, shipping companies, googlemaps, searates.com and worldfreightrates.com, as well as various country reports and studies. there are approximately 6.3 billion data points in the trade-dsm system (cameron et al. 2017). “the trade-dsm methodology has the ability to reduce vast quantities of data to manageable proportions. it is particularly valuable to those in government and the business sector who are tasked with formulating export growth and diversification strategies but who find the traditional tasks associated with ‘big data’ – i.e. high-volume and sophisticated data collection, processing and analysis – to be unfeasible from a technical or skill perspective.” (cameron et al. 2017: 140). 3.2 study methodology the research was designed to be carried out in three phases: phase 1 would cover the exploration of the concept, phase 2 would cover the preliminary interviews and phase 3 would cover in-depth case studies. this paper reports on the results of phase 1 and phase 2 as well as providing one short case study. 3.2.1 phase 1: exploration of the concept: october 2019 in phase 1, interviews were conducted with individuals familiar with the trade-dsm to identify if there was any evidence that the bigdata analytics system was used to assist decision-making and to determine if a preliminary model could be developed. based on these interviews, an interview guide, survey and preliminary model were developed. the interview guide and survey were based on similar types discussed in the competitive intelligence literature (calof et al. 2017; fehringer et al. 2006). 3.2.2 phase 2: preliminary interviews with users: january 2020 in phase 2, interviews were held with selected users of the trade-dsm and decision-makers who had used the report from the trade-dsm (the systems output). to ensure that those interviewed represented active trade-dsm users, the researchers identified (using a variety of sources) the most active tradedsm users. those identified who were available when the research was conducted (january 2020) were interviewed. the individuals selected and interviewed came from: i. firms: packaging, steel, funeral supplies, beverages, industrial adhesive, infection and hygiene control products; ii. an industry association: south african pork producers organisation (sappo); iii. provincial trade promotion organisations who had used the trade-dsm to help figure 2 the emerging big-data analytics model for international market selection. 18 their respective provinces’ exporters: trade & investment kwazulu-natal (tikzn), cape town & western cape tourism, trade & investment (wesgro); iv. a national government department: department of agriculture, forestry and fisheries (daff). 3.2.3 phase 3: in-depth case studies: 2021 in phase 3, in-depth case studies will be developed from interviews with some of the users of the trade-dsm. the objective of these interviews will be to validate the model developed in phase 2 and to obtain more details on the use of the big-data analytics system and how the results are integrated into decisionmaking. 4. results all of the phase 1 and most of the phase 2 interviews yielded direct evidence of the trade-dsm having had an impact on international market selection decisions. in this section, we propose a model based on the interviews. the results section ends with a short case study from one of the trade-dsm projects that incorporates both the results from the interview and survey given to the decisionmaker. in the first part of the results section, we describe the emerging model of international market selection emanating from the phase 1 and phase 2 interviews (figure 2 presents the model). we provide some observations on the multidimensionality of two of the model elements (decision-maker and trade-dsm user), followed by a write-up from one of the interviews to demonstrate the proposed model. 4.1 from decision-making need to trade-dsm report the decision-making model starts with a decision-maker who is looking to choose one or more international market(s). thereafter, it can move through multiple pathways en route to the development of the trade-dsm report (big-data analytics output). we observed five pathways in our phase 1 and phase 2 interviews: i. the decision-maker engages in a preprocessing activity such as preliminary market research and then through interaction with a trade-dsm user receives a trade-dsm report. ii. the decision-maker goes directly to a trade-dsm user and requests a report without having done any pre-processing. iii. the decision-maker, having received the trade-dsm report, asks for another report using different variables. iv. the trade-dsm user proactively develops a trade-dsm report for the decision-maker without being asked. v. the trade-dsm user or decisionmaker shows the trade-dsm report to one of their stakeholders who in turn requests their own report from the trade-dsm user. regarding pre-processing activities, those interviewed frequently mentioned that their organisation had already commenced the international market selection process. they had gathered information and in some cases had already conducted supporting analysis prior to the production of the trade-dsm report. for example, one user talked about having a heat map done on opportunities in africa for their sector by using credit card data. 4.2 from trade-dsm report to decision from the production of the trade-dsm report (big-data analytics output) to an international market selection decision by the decision-maker, we observed two pathways: i. the trade-dsm report moving directly towards the decision. ii. the trade-dsm report being further processed by the organisation through a combination of additional data gathering, discussion and analytical processes, after which the decisionmaker makes the decision. regarding post-processing activities, some of those interviewed mentioned that they used the trade-dsm report either as a starting point in their international market selection process or as a mid-point (having done some pre-processing). they then gathered additional information using processes such as stakeholder consultations, expert panels, country visits and attendance at international trade shows to validate and provide additional depth to the information. many of those interviewed also talked about having further 19 discussions within their organisation. in those cases, the trade-dsm served as one of the inputs in their international market selection decision. this concept of broad information gathering from multiple sources was also found in other recent studies (søilen 2019; calof et al. 2017: calof et al. 2015). no-one who was interviewed said that the trade-dsm report (big-data analytics output) was the sole input in making the international market selection decision. because of this, the research team developed a questionnaire designed to identify the inputs used to make the international market selection decision, together with the importance of each input. 4.3 from decision to implementation and action in the phase 1 and phase 2 interviews, many commented on the organisational factors influencing whether the decisions emanating from the trade-dsm ‘process’ and report were accepted and implemented. interviewees told us how individuals in their organisation reacted to the trade-dsm report and the eventual implementation or rejection of the trade-dsm recommendation. in one interview, we were told that senior management welcomed the report as they “want to make fact-based decisions”. we were also told about organisational support in that senior management was already highly supportive of the trade-dsm. this kind of orientation towards fact-based decisions and big-data analytics has been reported in past studies (kabir and carayannis 2013; gnizy 2018). in another interview, we were told that while management was open to the tradedsm findings, the organisation lacked the resources to implement the report’s recommendations. persaud and schillo (2017), in a report that synthesised past research on big data and analytics, wrote extensively about organisational or management impediments and the requirements for integrating the results of big-data analytics. 4.4 recap of trade-dsm participants from the model and discussion above, several trade-dsm participant categories were identified: decision-maker: an individual who works for an organisation that has an international market decision-making need and requests and/or receives a trade-dsm report (big-data analytics output) as part of their decisionmaking process. trade-dsm user: a person trained in the use of the trade-dsm system. in our study, users were individuals who produced the reports based on an understanding of the international market selection decision that the organisation needed to make. the researchers noted three types of trade-dsm user: 1. the in-house trade-dsm user. for example, tikzn-trained trade-dsm users produced reports to help tikzn select priority markets. 2. the outsourced trade-dsm user (consultant model). an example was a steel company (the specific case will be described in section 5) that requested and received a trade-dsm report from a consultant from trade advisory (a consultancy specialising in the application of the trade-dsm). 3. the in-house trade-dsm user combined with an outsourced user (mixed approach). this approach was sometimes used where an organisation had in-house user capability but also outsourced to a trade-dsm consultant. we saw this, for example, in daff (a national government department). stakeholders: in the daff and industry association interviews, we learned that as part of their decision-making process, the individuals in question engaged in a variety of discussions with industry stakeholders and used the trade-dsm report as part of these discussions. the industry stakeholders whom we interviewed said that the report also became part of their decision-making process. in some cases, the stakeholder requested a separate trade-dsm report focused on their specific product(s) and hs code(s). senior management: in some of the interviews, the decision-maker who had requested and/or received the trade-dsm report said that while they were able to make a recommendation, the final decision would be made by a more senior individual in their organisation. for example, in one of the organisations (a packaging company), the recommendation had to be discussed with the managing director. 20 4.5 multidimensionality of the decision-maker and the tradedsm user the interviewers made several observations that demonstrated how multidimensional the various elements of the model are. we discuss multidimensionality in terms of both decisionmaker and trade-dsm attributes below. 4.5.1 the decision-maker in one of the interviews, the decision-maker told us that the report was neither valuable to them nor used in their decision-making process. the reason the decision-maker gave was that the report did not include the key information that they needed to make an international market selection decision. we asked the decision-maker what information they needed. upon being told what their requirements were, we told them that the trade-dsm could indeed provide such information. the decision-maker’s response was: “i am going to ask the [trade-dsm] user to produce a report for me with that information.” this was in contrast to another decision-maker who had requested several trade-dsm reports in the past and not only specified to the trade-dsm user what analysis was required but also told us that he knew the model’s strengths and weaknesses. we refer to this here because it illustrates the extent to which the decision-maker understood how the trade-dsm could help satisfy their decision-making needs. these examples highlight different levels of trade-dsm literacy. the first decision-maker described above had a low level of trade-dsm literacy and neither understood how to instruct the trade-dsm user to produce the report they needed nor understood what was contained in the report. the second decision-maker had a high level of trade-dsm literacy and knew how to use the big-data analytics system. similar phenomena are evident in the intelligence and foresight field where you hear reference being made to foresight literacy and intelligence literacy (see calof et al. 2012; bisson and tang tong 2018). in one of the interviews, the decision-maker talked about all the steps he had taken in making the international market selection decision. this individual described how the trade-dsm report had helped to narrow down the international markets and, by conducting interviews with people in the market and attending a trade show, they were then able to arrive at a final decision. the decision-maker named all the different variables that had gone into the decision. this was in contrast to two other decision-makers whom we interviewed ‒ one did not even open the trade-dsm report and had yet to make a final decision and the other referred to the report as overwhelming: “i did not know what i was looking at.” what differentiated the former and the latter decision-makers? it was their grasp of the international market selection process and their experience in selecting optimal markets. we refer to this as decision-maker international market selection experience and knowledge. the international business literature also notes that the extent of international experience will impact decisionmaking processes (for more on this, see the research conducted on theories surrounding different stages of internationalisation). 4.5.2 the trade-dsm user we interviewed several of the trade-dsm users and reviewed many of their tradedsm reports. we noted that some of the users’ reports were longer and more comprehensive than others, with additional information having been integrated into the results. interestingly, some of the users said that they were using the reports in a number of different ways, over and above helping decision-makers choose international markets. for example, one user told us that the trade-dsm had been used to prepare the decision-maker for an upcoming trade show. we refer to this as trade-dsm user expertise, which we speculate may also have a link to an individual’s knowledge and past experience of big-data analytics systems. we also noted the extent to which the user knew and understood the decision-maker. this became evident in one of the interviews where the decision-maker in question commented that the trade-dsm report prepared by a user was not useful. when we asked why, the response was that although the report offered valuable insight into the best markets for the company around the world, the company’s rights to market and sell the product were limited to africa. therefore, only african countries should have been assessed and ranked in the trade-dsm report. we call this user knowledge of the decision-maker and their organisation. a second dimension of the user‒ decision-maker interface became evident in another interview where the decision-maker 21 commented that while the trade-dsm report was lengthy (which would normally make them decide to ignore it), they nevertheless read the whole document as they trusted the tradedsm user to give them something useful. we term this the decision-maker‒user relationship. 5. applying the trade-dsm: a case study the following case illustrates the use of the trade-dsm model by a steel producer to select international markets. in describing the case, we refer to the proposed model. the trade-dsm decision-maker was the export manager at a steel-producing company in africa, which already exported to various african markets but wanted to extend its footprint on the continent. the export manager had been tasked with deciding which additional african markets to select for his company. when attending a social engagement, he met up with a friend (relationship) who was very knowledgeable about and experienced in the use of the trade-dsm. his friend told him about the trade-dsm system and how it could be used to help him with his decision. the export manager wanted to know more and requested a demonstration of the tradedsm system. the friend scheduled a meeting with the export manager and his managing director to discuss the trade-dsm methodology. after providing an overview of the company and its plans to diversify and expand its export reach into more african countries, the export manager and managing director requested a trade-dsm report, which would identify export opportunities for three of the company’s products. the decisionmaker (the export manager) was very experienced when it came to international market selection, was highly technical and, at that point, very knowledgeable about the trade-dsm. the managing director was at the time very committed to big-data analytics and in fact wanted to make decisions based on big data. in terms of the model developed (see figure 2), the user had already done some pretrade-dsm research aimed at selecting new markets in africa. this pre-processing phase had resulted in fourteen countries being chosen for export expansion consideration. tradedsm identified seven of these countries, and the company decided to do further processing on five of these. this was achieved through visits to each of these countries, where several interviews were conducted with customers, suppliers and other entities. three countries were selected and the company successfully entered each one. further informationgathering took place, including talking to existing customers, company employees, industry experts and expert panels, and industry consultations. in the survey, the decision-maker rated the trade-dsm as being very important to making the decision and stated that “the trade-dsm did indicate one or two interesting countries in the results as a) being lower than what we would have expected for some countries and b) being surprisingly higher than what we expected in some other countries.” to summarise, the company was an experienced exporter to a number of african countries and the decision-maker had therefore selected and entered international markets before (experienced). the user had extensive knowledge of the trade-dsm and a strong relationship with the decision-maker, and preprocessing had been done. the trade-dsm report was further processed on the basis of inputs obtained from in-market visits and interviews and the decision-maker then forwarded the recommendations to his managing director (organisation). the managing director was also committed to the trade-dsm and the use of big data (attitude) and the company had the resources to implement the international market selection decision. 6. conclusions and areas for future research the objective of this paper was to see if big-data analytics impacted international business decisions. several of the decision-makers interviewed during phase 1 and phase 2 of the study stated that the trade-dsm was used to help select international markets, thereby showing a link between big data and analytics and international market selection. based on the interviews, a preliminary model was developed (see figure 2), showing multiple pathways in which big data was used in the international market decision-making process. the model will be examined further and if necessary refined during phase 3 of the study. in our interviews, we noted that the trade-dsm report was not the only input for the international market selection decision but one of several factors (albeit in the case study a 22 very important one). the interviews identified both pre-processing and post-processing phases involving the trade-dsm report, which led to a final decision being made. organisational factors, such as management attitudes towards big data, impacted the extent to which the trade-dsm report was accepted and used. during the interviews, we also noted several qualities and attributes of the decisionmaker and the trade-dsm user that appeared to influence the extent to which bigdata analytics were used in the international market selection decision-making process. the observations emanating from the interviews do validate a linkage between bigdata analytics and international decisions, and serve to offer some depth to various aspects of the emerging model. the case study that was discussed provided confirmation of the emerging model. however, given the small number of interviews conducted to date, future research should collect more data to validate and deepen these preliminary observations. surveying more users of the trade-dsm system will provide statistical validation of the relationship and possibly also the attributes and mind-sets of both the trade-dsm user and trade-dsm decision-maker that we have noted in this study. in addition, more in-depth case studies should be developed. the case study reported on in this paper was based on two 30-minute interviews and a few follow-up emails with the decision-maker. since the objective is to ultimately fully understand the impact of bigdata analytics on the international decisionmaking process, future research should provide for all trade-dsm participants to be interviewed, as identified in section 4.4, i.e. the decision-maker, the trade-dsm user, senior management and, where relevant, other stakeholders. this will provide additional insights and validations. finally, from the observations arrived at following the limited number of interviews conducted, we suggest that a more rigorous study be carried out, both to validate the preliminary model findings and to develop a deeper understanding of each element: a. trade-dsm user study: we have speculated, based on the interviews, that the quality of the analytics (trade-dsm report) was related to the user’s tradedsm experience and knowledge, their experience of big-data analytics in general, their relationship with the decision-maker, and their knowledge of the decision-maker and their organisation. a future study should investigate these aspects and assess their impact on the quality of the analytics produced. a positive relationship would help in the development of appropriate training programmes for trade-dsm users. b. trade-dsm decision-maker study: we have speculated, based on the interviews, that the quality of the analytics (trade-dsm report) and its usefulness in the decision-making process are related to decision-maker trade-dsm literacy and the decision-maker’s knowledge and experience of international market selection decision-making. a future study should look at these aspects and assess their impact. c. trade-dsm processing focused study: we observed both pre-processing and post-processing activities. these should be explored in more detail. specifically, what analytical techniques are used? what additional information is gathered? what role does each piece play in the process? we have reported on this in the case study, but more research is needed to create a better understanding of how big-data analytics results are processed and their relative importance for the overall decision-making process. if performance measures are used in the study (effectiveness or quality of the final recommendation), then process variables can be linked to performance. this type of research could provide insight into how big-data analytics can be effectively combined with preand post-processing. d. study on the organisational factors impacting trade-dsm report implementation: we heard that organisational factors such as management attitudes towards big data and analytics impacted the organisation’s willingness to accept and integrate the trade-dsm report. we also heard that organisational factors such as resources impacted the ability to implement trade-dsm-based recommendations. a future study should look at how organisational factors impact the big-data analytics process (the emerging model). e. study on different kinds of decisionmakers’ use of the trade-dsm: a future study should explore the use of the 23 trade-dsm from the perspectives of government, sector associations, trade promotion organisations and companies. we noted during the interviews that each group had a different perspective and a different set of decisions influencing the application of the same big-data analytics system. f. study on the different kinds of decisions supported by the tradedsm: the objective of the study was to look at how big-data analytics (trade-dsm) impacted international market selection decisions. the trade-dsm was specifically designed for this purpose. however, we noted in the interviews that the trade-dsm was also used to inform other decisions. for example, we saw it used to help companies prepare for trade shows, to help companies determine what products to export (and how to classify them) and to support hs-code reclassification requests. 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knowledge management processes; organizational performance; industrial sector 1. introduction knowledge management is one of the tools that contribute to increasing speed and improving khan et al., 2021). as knowledge is a major robust source of funding within institutions (clavercortés et al., 2007), so companies and institutions must pursuit of having knowledge in 2019). knowledge management constitutes a set of interrelated and connected procedure that work within the organization in order later used in the best way for the interest of the organization and the different administraalghail et al., 2021). schmitz et al., (2014) believes that, knowledge management has taken a great deal of interest and has become an important part within any company’s production operations to business scope, knowledge management has been considered as a distinctive mark for the most effective institutions from a strategic point of view (areed at al., 2021). the dynamic environment within the institutions provides 21 its employees with support and motivate them to be more productive and active (al shraah et al., 2021). given the importance of knowledge management, many researchers have analyzed it from different points of view. schmitz et al. (2014) delved into the study of the impact of knowledge management with its various aspects and relationship with the organization allameh & management on corporate sustainability and the successful key for the companies is providing support and attention to their employees (anwar & abdullah, 2021; shanker et al., 2017). the commitment of senior management and staff discipline is very important 2018). senior management facilitates a culture of learning and knowledge management in the organization (george et al., 2019). serrat (2017) argues that knowledge-oriented leadership is the most important part because it can lead the company towards excellence and development. entrepreneurship orientation is considered one of the basic and successful methods in knowledge management and organization, and ing the level of companies and their employees achievement. (tajeddini et al., 2020; corrêa neurial orientation are available in the literature. entrepreneurial orientation executives are crafting strategies in the hopes of doing something new and exploiting opportunities that other organizations cannot exploit. (wales et al., 2019; arzubiaga et al., 2018). the entrepreneurial orientation organizes plans, ideas and workers within the company for the sake of the company itself as well as the customers. (genc et al., 2019; jiang et al., 2018). this paper includes three sections; it begins with a review of the current literature on knowledge management processes, organizational performance, and entrepreneurial orientation, and conclusion, as it will add a contribution to industrial companies from the perspective of the capabilities of knowledge management and zational management, and increasing the company’s entrepreneurial orientation. 2. literature review 2.2 knowledge management entrepreneurial orientation refers to the organization’s adoption of the concepts of initiative and innovation, and risk tolerance, as a strategic approach based on experimenting with innovative ideas and diversity in the use of modern management strategies (mckenny et al., 2018). thus, the entrepreneurial orientation leads organizational performance towards excellence (monteiro et al., 2019). the entreciency with business requirements and adapt et al., 2019)the rapid changes and transformations witnessed in recent years in all areas surrounding business organizations at the ecocal, legal and cultural levels have exacerbated the intensity of competition between the industrial organizations (wales et al., 2020).whereas entrepreneurial orientation helps industrial establishments to implement entrepreneurial 2018). the entrepreneurial orientation is divided into six elements (identifying opportuity, and vision (alshanty & emeagwali, 2019). knowledge is the essential organizational tury, which can achieve a sustainable competitive advantage in the long term. many studies have focused on the importance of knowledge management (webb, 2017). knowledge management processes have become one of the international trends of entrepreneurship, as knowledge management forms part of the organization’s assets that lead it towards better performance, through obtaining, storing, sharing, and processing information in order to enhance its strategy, and providing the necessary information so that members of the organization make the right decisions (abubakar et al., 2019). to achieve better corporate performance, entrepreneurs need to use knowledge management to improve the quality of their deciknowledge management is also dynamic and multidimensional, covering most aspects of corporate knowledge activities, including knowledge creation, knowledge accumulation and knowledge exchange (anwar & ghafoor, 2017). 22 as the various administrative processes that a company devote to the production, distribution and use of knowledge to enhance organizational performance through knowledge acquisition, sharing and application (durst & explicit and implicit forms, documenting and sharing it with all stakeholders in the company, and applying it in a way that guarantees the organization’s advancement and progress (abualoush et al., 2018). knowledge management is one of the most important requirements that any company or institution needs to ensure its progress and its development in light of the tremendous technological progress witnessed by the business sector in the current era (ali & anwar, 2021). where companies, especially industrial ones, are interested in investing in the knowledge management projects and applying them to achieve success and continuity in the labor market (al-ahbabi et al., 2017). as companies have become more interested in knowledge management, as a result of the huge developments and changes on the one hand, and the increasing intensity of competition, and the multiplicity of requirements and needs of the customers on the other hand (barley et al., 2018). knowledge management has become the focus of companies’ attention through their reliance on information and knowledge and their use in designing and developing services (othman et al., 2019), and technologies in order to renew their methods of providing compared to their competitors from other companies (bolisani & bratianu, 2017). knowledge management helps the industrial sector to take decisions at all administrative levels within the company, which leads to increase better competitiveness (gopinath, 2021). it also helps to increase the stock of knowledge owned by the company, which leads to enhancing the capabilities of employpositively on their performance (gacanin, 2019). the knowledge management also contributes to identifying and understanding all the knowledge available in the company, which facilitates the process of investing it in an optimal manner and building a future vision based on it. knowledge management also helps to consolidate the concept of knowledge culture within the minds of all employees, by encouraging behaviors of discovery and sharing of knowledge (abdi et al., 2018). 2.3 organizational performance organizational performance is one of the most important foundations upon which organizations and companies are built, and organizational performance expresses the features of the organization that distinguish it from other companies and organizations in the labor market (al khajeh, 2018). organizational performance represents the values and principles prevailing in the organization’s internal work environment, which regulate work strategies, ideas and visions that help develop the organization and ensure its continuity (schneider et al., 2018). organizational performance also helps to develop the capabilities of all employees in the organization, increases their loyalty, and enhances interdependence among them. successful organizational performance gives the organization a competitive advantage that helps attract both customers and qualtive staff to make decisions that will develop the organization and increase its productivity. organizational performance is a major component of the components and foundations of modern organizations, as it is seen as one of the entrances to change, improvement and development (khalid et al., 2019). formance helps in revealing the extent of the organization’s ability to confront environmental determinants and identify the organization’s goals and resources (mbaidin, 2021). cial and human resources and invests them in a way that makes it able to achieve its goals (alghamdi, 2018). the organizational performance is the sum of all the operations carried out by the organization and all the strategies and plans it follows in order to increase its competitiveness in the labor market (al khajeh, 2018). cesses, appropriate allocation of human, mateeffective management capable of developing clear, understandable and well-known strategies for employees (abubakar et al., 2019). organizational performance can also be 23 cial, human resources, and the exploitation of these resources in a way that gives it the ability to achieve the desired goals or that it seeks to achieve (muthuveloo et al., 2017). the effective performance of the organization is achieved through its ability to manage its internal capabilities, which gives it the ability to adapt to the surrounding environmental changes in order to innovate and renew in a way that meets the changing needs of customers and achieves its goals and objectives (andrew, 2017). where organizational performance helps to develop human capital, productivity, and liquidity ratio (anwar & abdullah, 2021). the importance of organizational perforthe organization, without which the organization business, and urging all employees of the organization to invent new marketing and creative methods that contribute to the development or discovery of new products or entering new markets (george et al., 2019). organizational performance also helps to increase administrative productivity rates and administrative capabilities towards achieving outstanding performance (wanasida et al., 2021). 3. research methodology 3.1 the research method in order to analyse the mediating effect of entrepreneurial orientation on the impact of knowledge management processes on successful organizational performance at industrial sector in jordan the quantitative approach quantitative approach is concerned with the gathering and examination of information in numeric shape from the chosen sample. 3.2 the research hypothesis the hypotheses can be presented as follows: first hypothesis (h01). there is no impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance and its variables (performance of employees, commitment maceutical industry companies in jordan. second hypothesis (h02). there is no impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the entrepreneurial orientation knowledge management organizational performance entrepreneurial orientation knowledge acquisition knowledge storage knowledge sharing commitment to quality standards performance of employees in no va tiv en es s r is kt ak in g pr oa ct iv ity knowledge application 2.4 conceptual framework 24 and its variables (innovativeness, proactivity, cal industry companies in jordan. third hypothesis (h03). there is no impact of entrepreneurial orientation and its variables (innovativeness, proactivity, and risk-taking) on the organizational performance and its variables (performance of employees, commitment to quality standards) companies in jordan. forth hypothesis (h04). there is no impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance and its variables (performance of employees, commitment to quality standards) in the presence of entrepreneurial orientation as a medical industry companies in jordan 3.3 the research instrument the tool contains (36) items which the questionnaire was distributed by hand. questionnaire contains (4) demographic variables and (36) items represent study variables. 3.4 data analysis and interpretation to examine the mediating effect of entrepreneurial orientation on the impact of knowledge management processes on successful organizational performance at industrial sector in jordan. statistical package for social sciences (spss) in processing the following statistical techniques and tests in data analysis: 1. reliability test 3. descriptive statistical techniques 4. multiple regression 5. structural equational model (sem) demographic characteristics for the study sample. sample groupsdemographic per centagefrequency 80.2321male gender 19.879 100%400total 75.0300bachelor’s degree academic level 20.281master’s degree 4.819doctorate degree 100.0%400total 2.39less than 1 year years of experience 2.391–3 years 14.3570–5 years 81.1325more than 5 years 100.0%400total 37.5150administration job position 62.5250employee 100.0%400total fieldfield number independent variables: knowledge management 0.841knowledge acquisition 0.909knowledge storage 0.824knowledge sharing 0.784knowledge application dependent variable: organizational performance 0.859commitment to quality standards 0.742performance of employees mediating variable: entrepreneurial orientation 0.838innovativeness 0.856proactivity 0.873risk-taking the stability of the results for this study. 25 3.5 study sample the study population consisted of all senior and middle administrations and employees in the pharmaceutical industry companies in jordan. the study sample consisted of (150) senior and middle administrations, and (250) employees. the study sample was selected the tables below: 3.6 validity and reliability of the instruments after preparing the questionnaire in its initial form, it was presented to a group of experts specialized in business administration in jordanian universities, and they were asked to express their opinion on the appropriateness of the paragraphs of the tool and the subject of the study, and to ensure the linguistic formulation of the test questions, and the clarity of the test instructions. based on the opinions of the experts, some amendments were made, and some vocabulary was checked. after taking the opinions of experts, the questionnaire the questionnaire had an appropriate degree of apparent honesty. to reach a degree of reliability of the test, the researcher used reliability test for the instruments of measurement the reliability of a measure highlights the stability of consistency with which the instrument is measuring of a measure, in order to compare if the students achieve stability. 3.7 study results first hypothesis (h01). there is no impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance and its variables (performance of employees, commitment maceutical industry companies in jordan. to test this hypothesis, the researcher uses the multiple regression analysis. as shown in table (3). impact of knowledge management and its variables on the organizational performance in pharmaceutical industry companies in than (0.05). the value of r is the square root of r-squared and is the correlation between the observed and predicted values of dependetermination r2 (0.424) thus, about 42.4% of the variation in organizational performance explained by knowledge management and its variables in pharmaceutical industry compa(72.785) of the organizational performance in pharmaceutical industry companies in jordan will be caused from for knowledge management specially (knowledge sharing and knowledge application). second hypothesis (h02). there is no impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the entrepreneurial orientation and its variables (innovativeness, proactivity, cal industry companies in jordan. to test this hypothesis, the researcher uses the multiple regression analysis. as shown in table (3). table (3) demonstrate that there is significant impact of knowledge management and its variables on the entrepreneurial orientation in pharmaceutical industry companies in than (0.05). the value of r is the square root multiple regression test to check the direct effect knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance in pharmaceutical industry companies in jordan. sig*tcalculatesig*df f calculate(r 2)(r)dependent variable .0701.815.098knowledge acquisition 0.000 4 72.7850.4240.651organizational performance .541.612.049knowledge storage395 .0033.009.233knowledge sharing 399 .0008.832.857knowledge application 26 of r-squared and is the correlation between the observed and predicted values of dependetermination r2 (0.407) consequently, about 40.7% of the variation in entrepreneurial orientation explained by knowledge management and its variables in pharmaceutical industry companies in jordan. restriction parameter tion in pharmaceutical industry companies in jordan will be caused from for knowledge management specially (knowledge application). third hypothesis (h03). there is no impact of entrepreneurial orientation and its variables (innovativeness, proactivity, and risk-taking) on the organizational performance and its variables (performance of employees, commitment to quality standards) companies in jordan. to test this hypothesis, the researcher uses the multiple regression analysis. as shown in table (5). impact of entrepreneurial orientation and its variables on the organizational performance in pharmaceutical industry companies in jorthan (0.05). the value of r is the square root of r-squared and is the correlation between the observed and predicted values of dependetermination r2 (0.879) therefore, about 87.9% of the variation in organizational performance explained by entrepreneurial orientation and its variables in pharmaceutical industry companies in jordan. restriction tional performance in pharmaceutical industry companies in jordan will be caused from for entrepreneurial orientation specially (innovativeness and proactivity). forth hypothesis (h04). there is no impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance and its variables (performance of employees, commitment to quality standards) in the presence of entrepreneurial orientation as a medical industry companies in jordan the model is built in amos and the graph is shown below, and estimates of the standardized parameters are shown in the graph. the boxes represent the observed variables and the circles for the error terms. amos refers to the correlation structure between associated error conditions. this can improve the overall model synthesis. played below. please note the chi-square test the root mean square error of approximathe saturated model. (rmsea) is 0.550, it indi multiple regression test to check the direct effect knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the entrepreneurial orientation in pharmaceutical industry companies in jordan. sig*tcalculatesig*df f calculate(r 2)(r)dependent variable .2751.094.060knowledge acquisition 0.000 4 67.8160.4070.638entrepreneurial orientation .323.989.080knowledge storage395 .453.751.059knowledge sharing 399 .0008.859.867knowledge application multiple regression test to check the direct effect entrepreneurial orientation and its variables (innovativeness, proactivity, and risk-taking) on the organizational performance in pharmaceutical industry companies in jordan. sig*tcalculatesig*df f calculate(r 2)(r)dependent variable .0007.934.404innovativeness 0.000 3 955.6220.8790.937organizational performance .0008.950.587proactivity396 .1351.496.061risk-taking399 27 the model accounts for you what proportion of the variance in the sample variance covariance matrix. this should exceed (0.7) for a good in this model. which represent also strength of the model. (75.9%). 4. discussion in this study, part of the industry sectors in jordan was being examined to show how the impact of knowledge management processes on the internal organizational proceof knowledge management processes on structural equation model. structural equation model to check the impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance and its variables (performance of employees, commitment to quality standards) in the presence of entrepreneurial orientation as a mediating hypothesis chi2 gfi cfi rmsea impact of knowledge management and its variables (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) on the organizational performance in the presence of entrepreneurial orientation as in jordan. 811.864 0.759 0.792 0.258 independent variable dependent variable estimate s.e. c.r. p (sig) knowledge acquisition entrepreneurial orientation .060 .043 1.385 .166 knowledge storage entrepreneurial orientation -.046 .020 -2.254 .024 knowledge sharing entrepreneurial orientation .103 .034 3.017 .003 knowledge application entrepreneurial orientation .867 .057 15.231 entrepreneurial orientation organizational performance 0.699 0.018 41.959 knowledge acquisition organizational performance .059 .050 1.165 .244 knowledge storage organizational performance .005 .023 .206 .837 knowledge sharing organizational performance .119 .025 4.841 knowledge application organizational performance .182 .024 7.584 28 improving organizational performance, which showed a positive relationship with statistical shows that knowledge management is a key factor in improving job performance and standards. the result is compatible with the work of koohang et al., (2017) and abualoush et al., (2018). this result shows that knowledge management in all its aspects and operations works its competitive capabilities by focusing on one of the main axes within it, which is the employees by supporting them and increasing their the role of skill, creative thinking and innovation must be activated among employees in terms of the pharmaceutical industry and the marketing of these medicines in order to obtain better results and seize more opportunities. (nwankpa et al., 2021). the second hypothesis indicates that knowledge management positively affects the entrepreneurial orientation. this is supported because the value of t is (1.094). based knowledge management and entrepreneurial orientation. this is consistent with the work of de guimaraes et al. (2018) and alshanty & emeagwali (2019), who also found that knowledge management positively affects entrepreneurial orientation. the workers’ possession of experience is one of the important reasons for development and prosperity. this happens because of training employees to keep up with developments and what is new in the world of knowledge management, as well as increasing their cultural and cognitive sources will contribute to providing the company and production with creative and modern ideas. (iqbal, 2021) thus, they will take advantage of good opportunities and raise the level of the company. the result is also in line with weerakoon et al. (2020), who suggest that there is a direct relationship between the experience of employees and the high level of competitive advantage of the company by providing the market with distinctive products the third hypothesis studies the impact of entrepreneurial orientation on the development of organizational performance. which cant correlation between the entrepreneurial orientation and its dimensions on organizational performance in pharmaceutical companies in jordan. this positive relationship was in addition, the integration of organizational performance and entrepreneurship improves one of the foundations of the success of companies is sensing the needs of customers and studying the feedback in order to achieve a competitive standard between companies in attracting customers through an entrepreneurial orientation. in addition, companies must follow up the internal organization in terms of employees and performance level, as well as the external organization that is based on customers and dealing with them. employees also should be passionate because it is a motive for creativity and achievement and helps them to integrate within the company’s environment and thus deal with customers within entrepreneurial-oriented behaviors. the fourth hypothesis suggested that the en trepreneurial orientation mediates the relationship between knowledge management and organizational performance. mediation mediation effect. the results showed that the entrepreneurial orientation positively mediates the relationship between knowledge management and organizational performance. pharmaceutical companies can merge knowledge management with entrepreneurial orientation, which further will support the organized planning within the company. by having more knowledge, skill and experience to employees and supporting entrepreneurship will as well as the growth and improvement of employee performance, and all of this will give the company an advantage. (latif et al., 2020). this result is consistent with those of monteiro et al. (2019), abubakar et al. (2019). implications of the study the effect of both entrepreneurial orientation and knowledge management on the organizational performance of pharmaceutical companies in jordan. although the concept of knowledge management (wach et al., 2018; abbas & kumari, 2021) the four procedures in knowledge management which are (knowledge acquisition, knowledge storage, knowledge sharing, knowledge application) work together performance and work within the company, which will contribute to its development and distinction. moreover, the current studies show that the entrepreneurial orientation is 29 one of the reasons for the success of organizational performance, as it enhances quality criterions and raises the productive capacity the results indicate that the success of pharmaceutical companies is based on the amount of quantitative cognitive experience that employees possess and how it been applied. second, two parts–commitment to quality standards, and employee performance—and an empirical impact assessment between the two perspectives–due to the complexity of the organizational performance of pharmaceutical companies. thus, there is a direct link or relationship that depends on the high performance of the employees and in return also the increase in the quality standards to be achieved neurship and knowledge management are interested in this research as well as anyone else who can read it. companies should keep up and continue to search for new ways and mechanisms for knowledge management (raudeliuniene et al., 2020), to improve the organizational and functional performance (sahibzada et al., 2020). to activate and operational levels to acquire transfer and apply knowledge. 2. the second step: an approcial and information resources, in the presence of an effective administration capable of clearly setting strategies for all. 3. the third step: taking into account the obstacles that prevent knowledge management in innovation. 4. the fourth step: developing practices and decision-making processes to enter new markets, discovering opportunities available in the market, and adopting new ideas within taking into account the possibilities that arise from the interactions of the last steps. 5. conclusion knowledge management is one of the ways to raise the level of job performance and support the entrepreneurial orientation of companies. there are many studies explain that knowledge management methods and processes support employees’ experiences and skills, and thus affect the extent of their motivation. as a result, it can be said that the application of knowledge management processes in pharmaceutical companies will increase production capacity while raising the value of quality, gaining positive recommendation from customers as well strengthening the entrepreneurial orientation. by referring to the company’s goal, customers, entrepreneurial orientation can modify and innovate according to the feedback obtained from them and thus gain more customers and management aims to provide employees with the experience and skills necessary to be able to meet the needs of customers in a better and more distinctive way than other companies in the market. the enforcement of the entrepreneurial approach causes companies to innovate new businesses that ultimately will form the active elements. proposed model of the moderating effect of entrepreneurial orientation on the impact of knowledge management processes on successful organizational performance. step one step tow step three step four step five establishing a broad scientific base based on scientific research allocation of human, material, financial and information resources taking into account the obstacles that prevent knowledge management in inno ation developing practices and decisionmaking processes to enter new markets assessing risks 30 references abbas, j., & kumari, k. 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indian journal of economics and business, 20(2), 281–298. https://doi.org/ 10.5281/zenodo.5409342 issn: 2001-015x v o l 4 , n o 1 ( 2 0 1 4 ) c o n t e n t s marisela rodriguez , alejandro palacios and dante cortez technical intelligence approach: determining patent trends in open die forging pp. 5-15 o p i n i o n s e c t i o n victor cavaller analysis of knowledge transference processes in first mission activities of universities: portfolios as proposal of analytical tool for competitive intelligence functions pp. 16-25 luc quoniam and charles-victor boutet competitive intelligence cycle in the light of web 2.0 tools pp. 26-35 julyeta p.a runtuwene, audy aldrin kenap and verry ronny palilingan the development of north sulawesi through competitive intelligence pp. 36-42 abdelkader baaziz and luc quoniam contribution to reduce risks related to strategic decisions in new uncertain competitive environments: the case of algerian state-owned firms pp. 43-57 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: prof. dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2014 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india associate professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain associate professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, hedin intelligence & strategy consultancy, sweden javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/22') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/23') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/8') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/9') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/10') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/12') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, may 28 2014 e d i t o r i a l n o t e v o l 4 , n o 1 ( 2 0 1 4 ) on may 3 rd 2014 jisib received an email saying it has been accepted to be indexed by scopus elsevier. thus a vital goal for the journal has been achieved. the scopus acceptance will automatically allow us to enter a number of other indexes used by different nations for their individual rankings, which we again expect will increase the number and quality of submissions. the next goal of the journal is to be accepted to reuter’s isi web of knowledge. experience with other journals however show that this may take some time, also after official criteria are fulfilled as isi are looking at the number of times the applicant has been cited by their existing journals. there is no reliable way to keep track of this figure from our side as reuter’s do not say how many citations are required. instead we will file and application during the year and keep at it with regular intervals. open source journals are highly appreciated by users and we are convinced that they are here to stay. in this issue of jisib we have admitted a large number of opinion pieces. opinion pieces are important to allow for a broader perspective of the field in terms of policies, adaptions of ci in foreign countries and general interest in the form of debates. it also shows the normative qualities that are present in any social science discipline. in the first article marisela rodriguez , alejandro palacios and dante cortez show how ci can help define a business opportunity or threats to the open die forging industry. they show how the methodology can be combined with other types of analysis (market analysis, porter five forces, etc.) to enrich and make the process of strategic decision-making more precise. victor cavaller shows the correlation between knowledge translation (kt) and ci in the perspective of university students. cavallar concludes with a classification of analytical parameters for learning and teaching. luc quoniam and charles-victor boutet reflects on how the ci cycle changes with web 2.0. the article by julyeta p.a runtuwene, audy aldrin kenap and verry ronny palilingan shows a case of how ci is implemented in the region of north sulawesi, indonesia. the article by abdelkader baaziz and luc quoniam discuss the situation of algerian state-owned firms and come up with a conceptual model of how bi, ci and km are related in a decision making framework. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 43–52 open access: freely available at: http://jisib.com/ the role of business intelligence tools in the decision making process and performance tamara maaitah northern boarder university, jordan tamara_shahemnashmi@yahoo.com received 22 february 2023 accepted 28 march 2023 abstract in the current turbulent business markets, the way companies address and tackle unexpected events is reflective of its success. different varieties of technological tools have been created to assist in overcoming unpredictable and unexpected events in businesses that cold impact them, and one such tool is the business intelligent. such systems assist in gathering data concerning business operations and environments transforming information into something that can be easily understood. major firms have adopted big data analytic systems but this does not hold true for most universities and organizations literature has yet to present the way business intelligence tools affect businesses of different types. therefore, in this study, the impact of business intelligence tools on the decision-making and performance of public universities in jordan is investigated. this qualitative study was conducted on 200 members in 10 chosen universities. based on the interview results, bi tools deployed in the universities assist in facilitating timely decisionmaking, enhances efficiency of performance and meets client’s needs suitably, leading to employee satisfaction. keywords: business intelligence tools, competitive advantage, customer satisfaction, employee satisfaction and universities. jel classification: m15 1. introduction there are two fundamental meanings to business intelligence (bi) based on its relationship with the term, ‘intelligence’. the first less often used meaning is the capacity of human intelligence used in business activities or affairs. in other words, business intelligence as a new field of investigation of the application of the human cognitive faculties and ai technologies to decisionmaking and management support for resolving business issues. the second meaning is related to intelligence as valuable information where value is in terms of currency and relevance – it refers to expert information, knowledge and technologies used in managing businesses. under this meaning, business intelligence is a general category of applications and technologies used for collecting, accessing, and analyzing data to assist in decision-makers to make informed decisions. moreover, business intelligence is a term that indicates the ownership of comprehensive knowledge of the entire factors affecting business and thus, firms need to known about these factors (e.g., customers, rivals, business partners, economic surrounding and internal operations) for effective and informed quality business decisions. moreover, a distinct business intelligence field referred to as competitive intelligence is focused only on the external competitive surroundings of the firm. the firm collects information regarding the competitors’ actions and makes decisions on its basis. no serious attempt has been made to gather internal information. however, in current business organizations, because of automation, technological development and increasing standards, vast amounts of data are being generated, and data warehouse technologies have been developed for data storage. such warehouse 44 technologies include improved extract, transform, load (etl) and enterprise application integration tools enabling timely data collection. similarly, olap reporting technologies enabled the faster reports generation which carries out data analysis. on the whole, business intelligence has become an art of going through vast data amounts, extracting what is important, and transforming it into knowledge that is useful for decision-making. therefore, in this paper, the author examines the bi concept, its components, emergence, benefits, and the factors that influence it, technology requirements, bi design and implementation, cultural imperatives and different bi techniques. the paper would contribute to the understanding of the basic concepts of bi. 2. business intelligence business intelligence is the process of obtaining vast data mounts, analyzing them and presenting them in the form of quality reports that contain a summarized version of the data essence based on business actions, allowing management to make daily business decisions (abusweilem & abualoush, 2019). according to (alyan, 2022), bi is a method of enhancing the performance of business through the provision of robust assistance to decisionmaking, enabling access to actionable information. essentially, bi tools are technology that facilitates efficient business operations through the provision of increased value to information for effective use. bi, based on alzghoul et al. (2022) refers to the process of gathering, treating and diffusing information to reduce uncertainty in decision-making. other researchers described it as a business management term that describes applications and technologies functioning together to collect, access and analyze data concerning the business for informed decisions. moreover, arefin et al. (2022) described one of the fundamental characteristics of bi tool as its ability to gather data from a source that is heterogeneous and through the use of advanced analytical methods, the demands of users can be met. bi technology was classified by bach et al. (2018) based on the information delivery method, namely reporting, statistical analysis, ad-hoc analysis and predictive analysis and the gartner group brought up the bi concept and defined it as, a set of methodologies and technologies (j2ee, dotnet, web services, xml, data warehouse, olap, data mining, representation technologies, among others, to enhance the effectiveness of enterprise operations, and support decision-making for competitive advantages. in the current times, bi is no longer a new technology but rather it is considered as an integrated solution for firms that focus on their requirement as a key factor driving technology innovation. thus, the way key business issues are identified and addressed is the major challenge of bi applications to achieve valuable impact on business. bi was stated to include effective data warehouse and reactive element that oversees the time critical operations, enabling tactical and operational decision-makers to modify their actions based on the strategy of the company božič, k., & dimovski, 2019). another definition came from chen & lin (2021), who described bi as the result of in-depth analysis of detailed business data, with the inclusion of database and application technologies and practices of analysis. the authors further extended the definition of to include technical tools that cover knowledge management, decision support systems, enterprise resource planning and data mining. other authors included several software for extraction, transformation and loading (etl) data warehousing, database query and reporting under bi (gauzelin & bentz, 2017) as well as multidimensional/online analytical processing (olap) data analysis, data mining and visualization. 3. business intelligence tools the following are tools of bi: olap (on-line analytical processing) – this is the way business users can go through data through the use of sophisticated tools that enable dimensional navigation (e.g., time and hierarchies). olap provides multidimensional, summarized business data and is utilized for the purpose of reporting, analysis, business modeling or 45 planning optimization. olap has methods and tools that are useful in working with data warehouses or data marts created for state-of-the-art enterprise intelligence systems. the systems are essentially used to process questions directed towards trends determination and critical factors analysis. reporting software produces the aggregated data views to maintain an informed management concerning their business status. bi tools used for storing and analyzing data like data mining and data warehouses, decision support systems and forecasting, document warehouses and document management, mapping, information visualization, and knowledge management. this also includes dash boarding, geographic information systems, management information systems, trend analysis, software as a service (saas), advanced analytics, and forecasting/predictive analytics, which leverages statistical analysis methods for the prediction of accurate facts measurements. corporate performance management (portals, scorecards dashboards) – under this category, a container exists for the pieces to plug into in order to create an aggregate story; for instance, a balanced scorecard displays portlets for financial metrics coupled with universal learning and growth metrics. in this regard, real time bi enables the real time distribution of metrics using email, messaging systems and interactive displays. data warehouse and data marts – this is an important bi component, which is subject and oriented and integrated. it supports the physical data propagation through the several enterprise records integration, cleansing, aggregation and query tasks. often times it contains the operational data, which is referred to as updateable set of integrated data used for the wide tactical decision-making in the enterprise. it constitutes live data and not snapshots with minimal history retained. data sources data may be sourced from historical data, operational data, external data, market research firms, online data or information from an existing data warehouse. also, the data sources may take the form of relational databases or data structure supporting the existing business applications, and they may also exist in various platforms and can possess structured information (e.g., tables, spreadsheets) or unstructured ones (e.g., plaintext files, pictures and multimedia information). moving on to data mart, it is referred to as a collection of subject areas that are organized to support decisions that are made by specific departments, with every department, having their separate data mart. marketing data mart is similar to other data marts but it should be noted that individual departments do have their own hardware, software, data and programs that comprise the data mart and each interpret their data mart’s structure that meets specific needs. moreover, data marts are like data warehouses in that they store operational data that is useful for strategizing based on past trends and experiences analysis. the major difference is that the data mart is developed based on distinct, pre-defined needs for a specific grouping and configuration of chosen data – which is why there can be several data marts within a business enterprise. it can support a specific function, process or unit in the business organization and it is a collection of subject areas organized to support decisions of a specific department concerning its needs. bi tools have been extensively accepted as the new middleware between transactional applications and decision support applications, thereby decoupling systems focused on facilitating business transactions efficiency from those focused-on business decisions support efficiency. bi is capable of decision support, online analytical processing, statistical analysis, forecasting and data mining. 4. issues in bi: experts different views of bi experts in data warehousing consider bi as a supplementary system that is still a novelty. they view it as a technology platform that supports decision-making and it appears that data mining experts also view it as a set of advanced decision support system coupled with data mining methods and algorithms applications. in the viewpoint of statisticians, bi is a forecasting 46 analysis-based tool that has several dimensions. it has been mentioned time and time again that the key to bi system success is the consolidation of data from various different enterprise operational systems into an enterprise data warehouse but in the case of universities, a full-fledged enterprise data warehouse is still a rarity because of the effort scope required towards the consolidation of the whole enterprise data. according to daradkeh et al. (2022), because of the newly emerging highly dynamic business environment, only enterprises that are competitive will be successful in sustaining their market status. with regards to universities, they can only stand out if they leverage information on their market place, customers and operations to grab business opportunities. in this regard, the right information needs to be analyzed and several commonly used surveys like gartner, forrester and international data center indicated that majority of the firms all over the world are inclined towards investing in bi, with the top major investments poured into enterprise resource planning (erp) and customer relationship management (crm) in the past decade because due to the information gathered by the systems most of them achieve competitive advantage. the main objective of any corporate entity is to aim for the right access to information at the right time and thus firms need to facilitate information analysis and application to make timely decisions for their operations and processes. this may be exemplified by the marking of seasonal merchandise or provision of specific customer recommendations, where the firms have to access information as fast as they can and through the implementation of smarter business processes like business intelligence tools, such processes may influence the firm’s bottom line and value of returns. 5. future of business intelligence in the rapidly evolving business world, consumers demand efficient and timely services and to remain competitive, it is crucial for firms to meet or exceed the consumers’ demands or expectations. firms need to largely depend on bi systems to be able to lead trends and future events. bi users have been demanding real time bi or the next best thing, specifically to use in their frontline operations, expecting to obtain up to date information in a way that is similar to monitoring stock quotes online. in other words, weekly/monthly analysis is no longer sufficient and in the near future, businesses will become dependent on real time business information in the same way that they obtain information by just clicking on the internet. the near future also sees businesses to expect democratized information whereby university users will be enabled to see information on their specific segment in light of performance. the future demands bi tools to increase to match the increase in the expectations of consumers. therefore, it is crucial for businesses to increase the pace of services to remain relevant. 6. reasons for adopting business intelligence in the context of universities, bi facilitates accurate and informed decisions and hence, it can function as a tool of competitive advantage – this is particularly true for firms that extrapolate information from indicators in their surroundings, based on which they can accurately predict future trends and economic conditions. after gathering bi effectively and proactively used, decisions can be made for their benefit, with the ultimate aim being to improve the timeliness and quality of information generated. this is akin to having a lead on a race with the clear road ahead. bi reveals the firm’s position compared to its rivals, customer behavior changes and patterns of spending, firm capabilities, market conditions, future trends, demographic and economic information, and social, regulatory and political environment. 7. research method this qualitative descriptive study used semistructured interviews with members of the universities for data collection regarding bit issues (grublješič et al., 2019) and the emerging themes deciphered from the interviews were highlighted. two hundred 47 (200) research participants were recruited from public jordanian universities staff the semi-structured interview (refer to appendix i and ii) comprised of questions concerning bit aspects and the participants were queried on each of them after which the answers were coded and analyzed and the emerging themes listed (refer to table 1). table 1. a summary of universities academic staff responses on several parts of bi tools no% yes% business intelligence tools aspects tested through interviews 65 50 placement of business intelligence tools 80 20 usage of business intelligence tools at all universities levels 60 40 difficulty of the business intelligence tools deployed 80 30 obtainability of expert staffs for accomplish business intelligence tools 10 90 business intelligence tools support in decision making 10 99 different influences of business intelligence tools different than helping in decision making 5 95 awareness on maintenance of the practice of business intelligence tools 8. research results on the basis of the obtained results, the summarized responses of the respondents concerning several bi system aspects and the perceptions of universities academic staff are displayed in table 1 and table 2. no% yes% business intelligence tools aspects tested through junior employee interviews 90 20 practice of at the universities 90 30 familiarity with bit 35 75 bit influence on employee production and presentation 30 70 bit impact on firm performance 20 90 opinions on continuation of bit use 9. analysis the themes that emerged from the interview responses were regarding bit deployment and use among universities from the perception of junior employees and managers. 9.1. bit deployment and usage majority of the universities have not deployed bit and among the 50 top management employees who were part of the interviews, only 45% acknowledged their universities implementation of bit. the junior employees were generally unsure as to their universities have implemented bit or not, and only 15% were of the consensus of bit use. from the managers, 19% indicated the use of bi throughout the levels of universities, indicating the deployment and use of bit has not yet proliferated throughout all the employees. the results are consistent with (vallurupalli, & bose,2018) result which showed that small businesses have not completely embraced bit. the authors proceeded to explain that the costly bit are the reasons for their economic unfeasibility for universities and this makes them unattractive to such institutions. universities are often on a tight budget and are thus convinced that bit investments would be a waste of resources. the second barrier to universities adoption of bit is the lack of it systems in the institutions as noted wahua & ahlijah (2020). it appears that small business entities lack sufficient computer equipment for hosting bit (yiu & cheng, 2021; tripathi etal., 2020). generally speaking, computer equipment’s are capital intensive and universities just do not have enough budget to invest them being cost-saving institutions and thus, this limits their opportunities to adopt bit. according to yeboah-boateng and tripathi et al., (2020) universities lack the right installation capabilities and they are 48 not inclined towards business functions online as this may compromise security. in cloud-based services, business intelligence functions are sometimes hosted online and thus, owing to the universities lack of trust in online processes, they prefer not to adopt bit. 9.2. bit complexity and availability of bi maintenance personnel another theme that arose from the interviews is the lack of available skilled bi maintenance personnel and bit complexity. based on the results, majority of the managers (61%) are of the consensus that bit implementation would be full of complexity and 39% stated that they only have basic bit in their firms. moreover, regardless of the confirmation of the majority of respondents that universities have deployed complex bit, the results indicated that personnel needed to maintain the systems are lacking. the results showed that only 25% of the managers agreed to the capable handling of their skilled employees of bit, and the managers’ responses are aligned with those of the employees in that 20% of the latter possess bit knowledge. therefore, universities who had enough skilled employees been the ones who embraced complex bit. in a related study, huang et al., (2022) described complexity as the level to which an innovation is viewed as difficult to understand or use. in this regard, complexity remains one of the barriers to innovation/technology adoption as less complex technologies are more likely to be adopted compared to complex technologies, which is why in the former, high adoption rate was noted (jaklič et al., 2018). bit complexity stems from the mathematical functions that are useful for predicting a specific phenomenon to resolve an issue. skills in it are crucial for bit use (jaradat et al, 2022). the interviews revealed that majority of the employees do not have sufficient knowledge on bit and this could have been affected by their lack of it skills. added to the it skills are the mathematical skills which are needed for bit adoption and use. universities lack the resources and personnel for bit management – they have limited resources that may prevent them from adopting bit (jayakrishnan et al., 2018). furthermore, universities have high rate of failure in attracting qualified personnel for bit management as they do not have the resources to pay them. 9.3. impact of bit on universities performance the third theme noted in the interviews is the impact of bit on the institutions of higher learning as based on the results, 89% of the interviewed managers contended that bit facilitate decision-making in their institutions. for instance, one of the managers admitted, “our company, though categorized as a university has deployed bit, which provide real-time data”. information from bit is essential for a lot of processes, like the registration of low number of sales which was later attributed by the system to the expensive price of the product. this information is real-time stemming from market intelligence, enabling the companies to resolve the product price, and ultimately enhance sales”. this admission shows that bit is capable of providing technological tools that facilitate decision-making based on accurate data. essentially, owing to the high uncertainty in market trends and the competitiveness, valuable information is difficult to come by and in this regard, bit enable business efficiency as they generate timely information for decision-making. aside from generating such information, bit also provides data quality in that information is free from error and highly analyzed, ready for the leaders to interpret the results. bit is thus significant as it enables firms to identify changing trends and emerging threats to resolve them before they can do any damage. according to one of the respondents, “in our company, we rely on business intelligence solely for market scanning. the interview results are consistent with khan., (2022), who contended that a firm needs constant provision of information regarding consumer behavior and changing preferences and this is provided by bit in a timely manner so that informed decisions 49 can be made (masa’deh et al., 2021). apparently, bit is crucial for assisting leaders of companies to take timely decisions and front-line employees and executives to make informed decisions. bit include historical data and combine it with real-time data as needed by the business leaders, empowering them to make quick decisions with confidence as the provided information is valid and reliable. the system generates information based on the past while at the same time considering the present situation, and incorporating expected changes (torres et al., 2018). they extract factual data from a vast amount of unstructured data and transform it into meaningful and actionable reports, which is important for making informed decisions in the universities. businesses largely depend on bit to source reliable data for their decisions and aside from reliable information, bit also has several other benefits. the interview results showed that almost all of the interviewed managers (95%) were of the consensus that bit provides several benefits aside from timely decision making. for instance, one of them contributed that, “bi is not just amount timely decisionmaking as it helps businesses in many other ways, like providing vital information used to mitigate errors in production, enabling the company to achieve efficiency in operations”. notably, one of the benefits of bit that were mentioned by the managers is the increased efficiency and productivity of the universities. this is consistent with melo & machado (2019), who stated that informed strategic decisions obtained from bit are important in enhancing efficiency in operations and productivity in business. in this line of argument, bit is capable of analyzing emails and chats between customers and the company to determine customer characteristics and demands, paving the way form higher strategic plans to address such needs through enhanced operations for competitive advantage and goal achievement. from the interview results, the interviewees perceived that bit provides information that is important and accurate directed towards enhancing the company’s efficiency and productivity. bit was also mentioned to affect return on investments (roi) and similar to this, wieder nithya & kiruthika, r. (2021) revealed that bi paves the way for businesses to mitigate costs, increase revenues and profit margins and it impacts roi by offering a cost-effective method of collecting business information. businesses used to channel vast amounts of cash to conduct market research to obtain information how to increase their efficiency but currently, bi provides cost and timesaving strategy of gathering the same if not more information. hence, financial resources that were used to carry out market research can be directed towards other functions that need it. the roi is also affected by bit as they enhance the productivity of employees (nuseir et al., 2021). as for the interviewed employees, majority of them (70%) were in agreement that bi fosters their work performance and productivity, and in turn, enhance the overall company performance. one junior employee stated, “our company has made use of bit as a norm in all operations. at the onset, after the system’s implementation, we thought that it was a way for the leaders to control use but eventually we were convinced that the system noted each employee’s productivity, which is a vital owing to the need to support and empower those who are low-performing. the report may also be used by managers and supervisors to find the right strategy to motivate low-performing employees to enhance their performance and thus, i find bit to be crucial to both performance and productivity”. it is notable that bit assists in the productivity and performance enhancement of employees and they assist leaders in how to encourage and motivate such performance (rahardja & harahap, 2019). motivating employees is a must if the company is to meet their satisfaction and obtain their loyalty. 10. perceptions of university members on the use of bit it is evident from the results that managers and junior employees alike in the universities hold positive views on bit use, with 96% of managers convinced of the need for continued usage. this held true for 85% of the employees who were also convinced of its usefulness and the need for ongoing use. 50 such responses may be related to the bit provided benefits. regardless of the company size, bit provides enhanced and timely strategic decision-making, meets customer satisfaction and motivates the work force (rahman, 2021). these benefits are coupled with enhanced performance of the universities. 11. conclusion the study findings evidenced the extensive effects of bit on the university’s operations. bit brings about decision-making of management through the provision of data that is timely, quality and accurate, considering the past, present and future events, thereby enabling leaders to reached informed decisions. added to this, bit deployment in universities goes beyond decision-making resolution but also enhancing employees’ performance, customer satisfaction and firm functions and processes. they promote and maintain efficient operations to meet customer needs and present reports on the individual performance of employees in order to support and motivate them. on the whole, bit impact enhances the performance of companies, which is a result that is consistent with that found in universities in sweden, and thus, it can be argued that there appears to be universal behavior among universities. finally, bit enhancement of universities performance can be used as a bit outcome indicator – one of the top challenges that businesses generally face. bit is important for monitoring universities performance richards et al., 2019), with performance generally determined through the comparison between goals and outcomes. bit performance among universities calls for focusing on several dimensions (i.e., financial, operational and overall effectiveness), which need to be determined through subjective and objective means (saleem & ilkhanizadeh, 2021; siripipatthanakul & phayaphrom, 2021). there is thus a need to conduct a holistic determination of the overall impact and outcome in universities ranging from financial performance, to employee satisfaction, and customer satisfaction. author contribution business intelligence (bi) is the decisionmaking serving structure,therefore, bi aids kind improved choices, and it has developed prevalent in numerous administrations, it is significant to illustration bi’s rule concluded dmps and to display how the paraphernalia used in bi enable the dmp. “higher teaching organizations global are working nowadays in a actual active and multifaceted situation” as a outcome, universities that are within advanced teaching are vulnerable for rivalry is thoughtful. additionally, developed teaching is additional part that will theoretically influence large statistics study therefore, the request and usage of big data in advanced instructive organizations might consequence in improved excellence teaching for scholars and a better involvement for the university members. this study the first study in my country explain the role of bi tools in the decisions making process at the public universities. references abusweilem, m., & abualoush, s. 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(2021). the impact of business intelligence systems on profitability and risks of firms. international journal of production research, 59(13), 3951-3974 5 exploring competitive intelligence practices of french local public agricultural organisations christophe bisson 1 1 kadir has university, istanbul, turkey email: cbisson@khas.edu.tr received july 15, accepted october 25 2014 abstract: modern agriculture has increased the need for information when making strategic decisions for farmers since they must be more entrepreneurial to survive. this paper investigates the levels of competitive intelligence practices in a french regional chamber of agriculture and its four departmental chambers of agriculture to examine the ability of these public organisations to keep fulfilling one of their missions which is to provide the necessary information and knowledge to farmers. thus, this study proposes a behavioural and operational typology of competitive intelligence practice. both types of organisations demonstrate that they are not well adapted to support the entrepreneurial farmers on this issue. the findings of this study and the diagnosis of the competitive intelligence practices applied to the typology could be of help to increase their and other public agricultural structures performance levels. furthermore, the platform has the potential to inspire the public sector through subsequent adaptations. keywords: competitive intelligence, entrepreneurial farmer, local public organisations, modern agriculture, behaviours, typology, france 1.0 introduction agriculture is facing profound shifts (vesala and vesala, 2010; woods, 2008) under the pressure of global trade agreements, climate change, the changing balance of the global energy economy (blaney, 2006), increasing world populations available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 2 (2014) 5-29 https://ojs.hh.se/ 6 (pollock, 2007) and the debts of developed countries which have reached a threshold, radically altering the ability of the state to intervene (bisson et al., 2012). these conditions have triggered frequent revisions of agricultural policies (stanford-billington and cannon, 2010). consequently, although agriculture used to be strongly subsidised in developed countries, “in recent decades, these policies have been substantially modified, from the multiple reforms of the common agricultural policy (cap) in the european union and the various farm bills in the united states to the full removal of agricultural subsidies in new zealand” (latruffe, et al., 2013, p.10). under such conditions, farmers in these countries need new strategies, new sources of revenues such as tourism and “also by adding value to farm products via processing and direct marketing” (vesala and vesala, 2010, p.22). hence, a greater degree of multi functionality is expected in the agricultural sector (morgan et al., 2010) and a different strategic direction is required (european commission, 2007), increasing the necessity for strategic planning (franks, 2006). about the cap, seuneke et al. (2013) stress that “the new eu regulations designed to stimulate more sustainable agriculture and the increasing use of expensive external inputs increased farming costs, while ongoing globalisation has led to decreased returns on agricultural products” (p. 208). thus, ‘the squeeze on agriculture’ (ploeg and roep, 2003) compels economies of scale to reach a viable size and farmers need increasingly to be able to compete in the global market. in addition, the new cap which will go into effect in 2015 is founded on a new paradigm (carpon et al., 2013) as it will (among other things) no longer stipulate quotas for several products (e.g. milk) and should eventually end others (e.g. sugar in 2017). therefore, farmers, regardless of whether they do non-agricultural activities (e.g. tourism) or purely conventional production-oriented farming, are facing similar difficulties as other businesses, and are being obliged to become more entrepreneurial (alsos et al., 2011; morgan et al., 2010; seuneke et al., 2013; vesala and vesala, 2010). much of the research done on farmers’ entrepreneurial skills was linked to the european research project ‘entrepreneurial skills of farmers’ (esof). seuneke et al. (2013) depict the three essential entrepreneurial skills identified by the esof project: a) recognising and realising business opportunities; b) developing and evaluating a business strategy; c) networking and utilising contacts (wolf and schoorlemmer, 2007). thus, the first two skills mentioned above require a lot of information since they deal with strategic formulations (david, 2013), underlining that information becomes vital for farmers like for other companies to build the right strategy and make adequate decisions (bisson et al., 2012). to cope with this highly competitive and changing environment (schoemaker, 2002; stead and stead, 2013), private and public entities need to integrate competitive intelligence (ci) methodologies and tools (larivet and brouard, 2010; wright, 2011; yap et al., 2012). there are numerous conceptualisations of ci, and it has been variously defined as competitive and technological intelligence, business intelligence, environmental scanning, competitor intelligence and even industrial espionage in the literature (bisson, 2013; sewdass, 2012). ci is defined by rouach and santi (2001) as the “art of collecting, processing and storing information to be made available to people at all levels of the firm to help shape its future and protect it against current competitive threats: it should be legal and respect codes of ethics; it involves a transfer of knowledge from the environment to the organisation within established rules” (p. 553). yet, the scope of ci goes beyond entities nowadays as new forms of territorial governance must include tools and methods of ci to optimise the creation of knowledge and intelligence. this is defined as territorial ci (françois, 2008; moinet, 2009). thus, innovative organisations must be constructed to allow for networking between the various economic actors and to be able to best share this information to improve the competitiveness of the territory (bouabdallah and tholonat, 2006). although it is deemed important that public entities engage in ci (massmann and quoniam, 2010), very little has been written about ci for public service or non-profit organisations (caronfaisan and lesca, 2010; sewdass, 2012) or for the agricultural field. concerning the relationship between government, intelligence and society, france was the first country in the world to publicly make such examination (dedijer, 1994). local state institutions are considered as critical in rural areas as they are “delineating the ‘problems’ which that economy faces and in defining attendant policy solutions” (pemberton and goodwin, 2010, p. 278). located in every department and region, french chambers of agriculture are public organisations: a) regional chambers of agriculture 7 (rcas) aim to support farmers in their installation projects or development by providing assistance on technical, economic, administrative and personnel issues to enable them to succeed in their professional and personal lives. rcas coordinate and plan agricultural regional development, coordinate departmental chambers, represent and discuss with the regional council and regional state services; b) departmental chambers of agriculture (dca) must disseminate information, support and train farmers (chambers of agriculture, 2013). in spite of the fact that ample research has been undertaken regarding entrepreneurial skills in agriculture, and that the importance of the french public sector as an information provider for farmers was stated to be a vital component for building a robust strategy and make the right competitive decisions, no research has been done regarding the level of ci practice in the public agricultural sector. aiming to contribute to and fill a scientific gap in the literature, this paper examines the ci level of french public chambers of agriculture in one region, investigating their ability to provide information and knowledge for competitive and strategic purposes as a support for farmers to become more entrepreneurial and to survive in a modern agriculture (seuneke et al., 2013). the research question which leads this study is: are the competitive intelligence practices of the french local public agricultural sector congruent with the growing needs for information of farmers in facing environmental, social, and economic issues? thus, through this lens, are french local public agricultural organisations adapted or not to the entrepreneurial mutation of agriculture? to undertake such a diagnosis, this paper proposes a behavioural and operational typology of ci practices applied to a french regional chamber of agriculture (rca) and its four departmental chambers of agriculture (dca) (it was requested that the name of the french region be kept confidential.). as emphasized by seuneke et al., (2013) “small-business entrepreneurship literature provides many useful concepts and frameworks helpful to our future work on entrepreneurship in agriculture” (p. 217), and their call in line with alsos et al. (2011) for more research applying frameworks from small businesses, the model used in this study is inspired by a model applied to smes (wright et al., 2012). the remainder of this paper is organised as follows. the theoretical background is discussed in terms of why ci ought to be developed in the public sector, the weight of french agriculture for the french economy and the existing ci practices in agriculture. the following section describes the sampling procedures, data collection method and analytical approach. lastly, the findings are discussed and this survey concludes with an examination of the implications while proposing some possible avenues for further research. 2.0 review of the literature why does the public sector need ci? more than ever before, the public sector must collaborate with the private sector to improve competitiveness and face fierce global competition (andersen et al., 1994; fuglie and schimmelpfennig, 2000) as “governments have a role in fostering competitive industries but it is an indirect one” (smith, 2012, p. 17). for that reason, the flow of information and means of analysing it are vital (herbaux, 2004). moreover, sewdass (2012) posits that “public service organisations need to perform types of strategic planning activities similar to their private-sector counterparts” (p. 1) which requires competitive intelligence function (wagner, 2003). thus, ci can improve the efficacy of the strategic planning process of public service departments in the collection of the information necessary to support decisions (horne and parks 2004). moreover, ci “can and does provide external background and fundamental perspectives that can complement the traditional inward focus that public services usually have […] and assist the decision makers in the public sector in making more informed decisions concerning the improvement of the quality of services offered to citizens” (sewdass, 2012, p. 3). nowadays, public organisations are facing “a series of external challenges, such as declining trust and increasing pressures for accountability, wicked policy problems that cut across organisational boundaries and require intersectoral collaboration, tightening budgetary constraints, new internetbased technologies, and the polarization of politics and ideologies” (holzer and yang, 2013, p. 1). under such conditions, the public sector becomes more like traditional profit-making organisations and so ci can benefit these organisations in a way 8 similar to private sector organisations (horne and parks, 2004). it is strongly believed that local authorities can improve performance by adopting values and practices imported from the private sector (clark, 2003). moreover, local public organisations have a critical role as demonstrated by the eu programme in rural areas named ‘leader’ which is based on the fact that having local decision-making processes provides better coordination mechanisms (ray, 2000; shucksmith, 2000). as regards to france, the way that the state is ubiquitous in ci affairs is unique (dou, 2004; massmann and quoniam, 2010), and it makes it possible to support the co-creation of strategies of innovation and development between the state, territories and entities (carayon, 2003). furthermore, territory as a project has been defined in france by the inter-ministerial delegation for regional planning and regional attractiveness (1999) as an organisation to be built with information by linking public and private actors engaged in a dynamic of projects in a territory. the weight of agriculture for the french economy in 2011, agriculture represented 1.84% of the french gdp with 32.8 billion euro and 3.3% of the workforce (agreste, 2014). the main productions are: cereals (11.8 billion euro), wine (10.9 billion euro), milk (9.2 billion euro), cattle (7 billion euro), poultry (4.6 billion euro) and pigs (3.2 billion euro). agriculture is the base of the agrifood sector (momagri, 2012) which represents 2.3% of the workforce (the second most important french industrial sector based on the number of workers after the mechanical industry) and 1.68% of the gdp with 30.1 billion euro (agreste, 2014). furthermore, agriculture indirectly creates jobs through service, tourism, administration, equipment and commerce. thus, nearly 5 million of jobs, i.e. 18% of the french workforce, are dependent on agriculture (momagri, 2012). france is the largest producer and second largest exporter (after germany) of agricultural products in the eu, and the eighth largest producer and fourth largest exporter in the world. however, in 1995, france was the sixth largest producer and second largest exporter in the world (momagri, 2012). therefore, its competitive position is decreasing due to the slow disappearance of the cap and internal factors (momagri, 2012). in 2011, france produced 70 billion euro of agricultural products, germany 52 billion, italy 48 billion, and spain 41 billion (agreste, 2014). however, in terms of agrifood germany is first in eu with 161 billion euro and france second with 159 (ibid.). concerning the trade balance, the agricultural and agrifood sectors are one of the few french economic sectors with a positive balance. indeed, it is the second highest surplus after transport (i.e. sales from airbus) with more than 11 billion euro of trade surplus which represent more than 13% in value of french exports (momagri, 2012). in 2011, france primarily exported wine and alcohols, cereals and milk and milk products, while its main imports were meat, fish and fruits (agreste, 2014). its main clients were germany, belgium, italy, great-britain, spain, netherland and the usa, while its principle suppliers were the netherlands, spain, belgium, germany, italy, great britain and brazil. however, this surplus is constantly decreasing. in germany, agriculture represents only 1% of the gdp and the government supports agriculture only to keep it competitive and maintain exports, not to maintain existing jobs (lemaitre, 2012). moreover, while france increased its exports by 10 billion euro since 2000, germany has increased it by 25 billion euro. thus, the surplus of the trade balance (second after aeronautics) has been cut in half compared to 1998 (agreste, 2014). agricultural prices are highly volatile. prices can vary for a single product in the same year by 100%. therefore, in france, farmers’ income can vary by over one third from one year to the next (momagri, 2012). this phenomenon is reinforced by increasing economic uncertainty. furthermore, there are no regulating stocks. a mere 1% or 2% discrepancy between supply and demand can generate a variation of 50% to 100 % (momagri, 2012). like many other economic sectors (e.g. the pharmaceutical sector), the trend has been to increase the size of farms to acquire economies of scale. yet, this phenomenon has been notable accelerated by the new cap (girard, 2013). for that reason, there are 21% less farms compared to 2003, as 19% of farms exploit 58% of the useful agricultural surface (agreste, 2014). a close relation between agricultural power and political power exists as demonstrated by the fact that the main agricultural producers are all 9 members of the g20 and four of them (china, usa, france and russia) are members of the united nations security council (momagri 2012). hence, since france can export a massive amount of agricultural products, its political power on the international scene is bolstered. however, due to the characteristics of agriculture, it cannot be relocated to other countries like industry. thus, it can be argued that agriculture is the foundation of french economic power. furthermore, due to the increase in the global population, agriculture has potential growth with a 70% increase expected in 2050 (momagri, 2012). table 1. different types of scanning carried out by french agricultural organisations (based on the work of laurent (2012) to which was added strategic scanning. nevertheless, the debts of states including the u.s.a. and the european union (eu) will cause major changes in public policies, foremost among which are agricultural policies (e.g. the new cap in 2015). in such a context, french agriculture will undergo various changes and could optimize its competitive intelligence practices to address these challenges. competitive intelligence in agriculture a rich body of literature exists about ci practices in the service and industry sectors (day and schoemaker, 2005; dou, 2004; smith et al., 2010). however, only a few articles have been written about ci and scanning for agriculture such as in china (peng cui and li, 2011), japan (nagai et al., 2009), india (gupta, 2012), columbia (domínguez local source(s) national source(s) internatio nal source(s) territorial scanning dca dca, rca, paca paca, institutes technical, legal and competitiv e scanning dca, rca rca, paca, institutes paca, institutes technologi cal scanning rca, institutes rca, inra, institutes inra, institutes scientific scanning rca, inra, institutes inra, institutes inra, institutes strategic scanning inra (animal health departme nt) inra (animal health departme nt) inra (animal health department ) 10 et al., 2009), france (bisson et al., 2012) and denmark (grunert et al., 1996). this is surprising since agriculture needs, just like other sectors, information about various topics such as competition, markets, and technologies to judge the implications of feasible alternatives in the decision making process (aharoni et al., 2010; hammondet al., 2006; kroll and forsman, 2010). furthermore, agriculture and its actors form an important pillar of territorial intelligence and ci activities should be developed to ensure better governance (herbaux, 2004). guesnier (2004) has pointed out the correlation between territorial governance and economic performance, and in this way ci activities should lead to better territorial economic results. a lack of information, for example, on price or technology lowers the price of farmers’ yields (momagri, 2012). moreover, ghadiyali et al. (2011) contend that intelligence for agriculture makes it possible “to avoid guess work […], to improve performance […], to know about the customer […] and to know about competitors’ markets and enhance profitability” (p. 314). in france, agricultural entities such as dca, rca, the permanent assembly of chambers of agriculture (paca) which is the national network of chambers of agriculture, considered as the “official” agricultural development and extension agencies (goulet, 2013), institut national de recherche agricole (inra) and agricultural technical institutes practice different types of scanning (see table 1). renard (2010) underlines that ci practices are emerging in french chambers of agriculture. however, an important base for ci exists in these as their libraries constitute a network allowing them to share tools and professional know-how (dutkiewickz, 2004). as regards inra, a strategic scanning system has been launched at the animal health department (fauré, 2010) and can be construed as the most advanced system it has developed. this was triggered by the sanitary crises that occurred in previous years (e.g. mad cow disease). moreover, other advanced projects were undertaken by multon et al., (2003) who used bibliometrics to analyse the locations of scientific collaborations at inra. falize and faure (2010) noted about the ci culture at inra that (translated from french ) “scanning to support projects and decision makers is not natural in our structure. the ci culture is underdeveloped […]. the ci concepts and vocabulary seem to be more suitable to the industrial world and cause reluctance among researchers […] nevertheless, scientific and documentary scanning, more individually based, is intrinsic to the work of researchers and this is well developed, but not structured from a collective point of view” (p. 4) . 3.0 methods sample and procedure this study was conducted at a french regional chamber of agriculture and the four departmental chambers of agriculture linked to it. in 2010, the french region where the study was carried out represented 4.3% of the french gdp and 5.2% of the french population. 2.2% of the regional gdp was from agriculture and this represented 3.5% of the labour force, which is slightly higher than the french average. the agrifood business was significant, with 2.7% of its workers and 2% of its gdp derived from this sector (national institute for statistics and economic studies, 2013). this survey is based on the model developed by wright et al., (2012), a behavioural and operational typology of competitive intelligence practice applied to smes and construed as robust (ross, 2012; gaspareniene et al., 2013; smith, 2012). this model is based on six strands which are attitude, gathering, use and location (drawing on the model created by wright et al. 2002), technology support (identified as the degree of investments made to assist with gathering competitive information), and it support (i.e. the type of systems used to manage the flow of competitive information). this paper aims to create a behavioural and operational typology of ci practices of the french public agricultural sector, and therefore a constructivist/transformative approach was adopted. although one could argue that the data collected provides ‘provisional knowledge,’ the results pinpoint the ci practices of the french public agricultural sector and can be replicated with similar structures in france, in the eu and the rest of the world. for this study, the questionnaire used by wright et al. (2012) was adapted to the context of the french public agricultural sector and all the strands were changed into diagnostic questions leading to a ci typology verdict for the rca and dcas. thus, the model and its questionnaire were tested through http://link.springer.com/search?facet-author=%22klaus+g.+grunert%22 11 collaboration with top management and ci specialists from the rca and each dca. this helped avoid issues arising from lack of clearness and potential misinterpretation. for example, a new question was added to investigate who the targeted persons were for the collection of strategic information and to understand the concepts of service toward companies and society, and other questions related to competitors were deleted. furthermore, some terms were replaced by others such as ‘employee’ by ‘collaborators’ and ‘firm’ by ‘organisation’. a self-declared position statement was included at the end of the questionnaire to confirm or contradict answers given within each category. this helped to reveal any inconsistencies in a typology verdict based on the allocations of answers to individual questions and the position statement. the top management of the rca and dcas identified the targeted collaborators for that survey and two types of jobs were not selected as they were deemed to be not concerned with ci. thus, only six job categories were considered through eight of the official journals of french agriculture (see appendix 1). indeed, the first two classes were ‘logistics and maintenance’ and ‘secretary, assistance and accountancy’. in addition, the class ‘management’ was divided into two categories to merge ‘technical head and head of service’ as lower class management and ‘vice director and director’ as upper class management. so, seven classes were considered for this survey. qualtrics (www.qualtrics.com) was used to develop the online survey and collect the responses from the 38 collaborators selected at the rca and 248 at dcas. the message which accompanied the questionnaire mentioned that the results would be anonymous to guarantee freedom of expression. it is important to note that the directors did not take part in the survey (the chambers of agriculture believed they should be observers of the survey) and only vice directors answered the questionnaire. thus, by aggregating the number of people from dcas and the rca, 153 people completed the survey and 286 participated in the study. the structure of the questionnaire and its model of analysis can thus be considered to be robust. it is worth noting that the percentage of persons who participated is higher for the rca than the dcas. yet, all the rca collaborators who started the questionnaire finished it, showing a greater interest in the survey (see table 2). table 2. response rates for each stage of the survey typology strand section heading rca dcas number of respondents % number of respondents % gathering intelligence gathering strategies n = 25 100 n = 152 100% attitude attitude toward ci n = 25 100 n = 138 90.8% technology support technology support used for ci n = 25 100 n = 133 87.5% it systems it systems used to manage ci n = 25 100 n = 133 87.5% use use of ci in the decision making process n = 25 100 n = 133 87.5% location location for intelligence gathering in the structure n = 25 100 n = 132 86.8% identification job title and type of dca n = 25 100 n=128 84.2% http://www.qualtrics.com/ 12 moreover, it should be pointed out that at the rca nobody provides consultancy or technical support and at dcas there are no it positions (see table 3). table 3. response rates per type of job. type of job rca dcas number of persons % number of persons % technician n = 0 0 n = 28 21.9 consultant n = 0 0 n = 41 32 surveys, rd n = 10 40 n = 36 28.1 it n = 3 12 n = 0 0 information/communication/library n = 3 12 n = 2 1.6 technical head. head of service n = 7 28 n = 19 14.8 director. vice-director n = 2 8 n = 2 1.6 total n = 25 100 n = 128 100 4.0 analytical approach based on previous research and the results obtained from the pilot survey and consequent improvements, a set of descriptors was made (see appendix 2). thus, the findings from the survey were applied to this behavioural and operational typology of ci which allowed for verdicts regarding their levels of gathering, attitude, use, location, it systems and technology support. the categories in italics are the optimal ones which could lead the public organisations to better ci practices. furthermore, since this study aims to investigate the ci levels of two different public structures of the french agricultural sector, i.e. the rca and dca, and of seven different classes of workers, cluster analysis was chosen as an exploratory tool (kaufman & rousseeuw, 2005). once the diagnostic of their ci practices is established, it could trigger improvements in terms of benefits for the farmers and the entire society. results and discussion the answers obtained for the behavioural and attitude descriptors are indicated below for each of the six strands, and this is followed by a discussion of the implications of these results. in the first question, the respondents were asked about the persons who were their main targets for the gathering of strategic information in the investigation of whether or not a relation exists between the targeted persons and the level of gathering. it was found that the main concern for all dcas and the rca was for farmers (see table 4). however, in comparison with dcas, the collection of information at the rca targets elected officials more than farmers at the rca. this reveals two aspects: there is a greater political dimension at rcas compared to dcas, and dcas have a core mission of ‘services for farmers’. only dca 4 displayed similar results (see the percentages in table 4) as the rca. 13 table 4. people targeted for the collection of strategic information at the rca and dcas. farmers elected officials internal for the service no difference main target dca 1 15 (65.2%) 2 (8.7%) 4 (17.4%) 2 (8.7%) farmers dca 2 20 (69%) 2 (6.9%) 5 (17.2%) 2 (6.9%) farmers dca 3 36 (73.5%) 3 (6.1%) 10 (20.4%) 0 farmers dca 4 13 (48.1%) 4 (14.8%) 6 (22.2%) 4 (14.8%) farmers rca 10 (40%) 6 (24%) 6 (24%) 3 (12%) farmers total 94 (61.4%) 17 (11.1%) 31 (20.3%) 11 (7.2%) n=153 as regards the people targeted for the collection of strategic information by type of jobs at the dcas (see table 5), they logically all have farmers as their main target, except the librarians (who also target equally ’internally’) and the top management (who also target equally ’elected officials’). table 5. people targeted for the collection of strategic information by type of job at dcas. type of job farmers elected officials internally no difference main target technician 22 (78.6%) 0 5 (17.9%) 1 (5%) farmers consultant 30 (73.2%) 2 (4.9%) 6 (14.6%) 3 (7.3%) farmers surveys, rd 21 (58.3%) 5 (13.9%) 7 (19.4%) 3 (8.3%) farmers information/ communication/ library 1 (50%) 0 1 (50%) 0 farmers or internally technical head. head of service 9 (47.4%) 3 (15.8%) 6 (31.6%) 1 (5.3%) farmers director. vice director 1 (50%) 1(50%) 0 0 farmers or elected officials total 84 (65.6%) 11 (8.6%) 25 (19.5%) 8 (6.3%) n=128 at the rca, the results are similar (see table 6). a slight difference can be seen compared to dcas as regards the vice directors as their target is ‘elected officials.’ similarly, librarians have as their main target ‘farmers’. it should be noted that, in this group we find both ‘communicating’ persons and ‘librarians’ who may therefore have different perceptions of their targets. 14 table 6. people targeted for the collection of strategic information, by type of job at the rca type of job farmers elected officials internally no difference main target surveys, rd 4 (40%) 2 (20%) 3 (30%) 1 (10%) farmers it 0 0 2 (66.7%) 1 (33.3%) internally information/ communication/ library 2(66.7%) 0 1 (33.3%) 0 farmers technical head. head of service 4 (57.1%) 2 (28.6%) 0 1 (14.3%) farmers director. vice director 0 2 (100%) 0 0 elected officials total 10 (40%) 6 (24%) 6(24%) 3 (12%) 25 information gathering this section covers the types of information gathered, the sources of information used, how much strategic information is provided to the organisation, how staff are prepared to collect strategic information, the expected financial performance of their efforts regarding ci and the financial support given to ci activities. 605 responses were received from dcas about the types of information collected, and by far the most frequent type of information collected regarded the products and/or services in the market/area of intervention (74.3%), followed by four subjects i.e. laws (55.3%), articles and scientific publications (52.6%), economy (50%), and customers/users (48%). other selected types of information were much lower, i.e. political, social, financial, iso standards, industrial processes and patents. therefore, the type of information collected is limited, which is surprising for such a broad sector as agriculture. at the rca, nearly 100 responses were obtained regarding this question, and the top five types of information were: products and/or services in the market/area of intervention (80%), customers/users (72%), economy (52%), articles and scientific publications (48%) and law (44%). in this particular, the results are very similar to those of dcas and the range of the types of information collected is also limited to a ‘comfort zone’. concerning the sources of information used at dcas, the primary sources used were experts from the competence networks (78.9%), followed by websites (68.4%), then magasines in the industry /sector (59.2%), respondents’ own knowledge (59.2%) and national newspapers (50%). thus, the organisation essentially uses free and/or cheap sources. these are local or national sources but rarely international. at the rca, websites were the most used sources (76%), then ’their own knowledge’ (68%), and ’experts from competence networks’ (64%). thus, the organisation also uses mainly free and/or cheap sources. dcas use slightly more human sources than the rca as they tap more into the competence network. to the question ‘how much strategic information does your organisation obtain from you’, 48% of collaborators answered a low level or none, 35% a moderate amount and only 7% a high 15 amount. this reveals the lack of participation among collaborators and involvement in the decision making process at dcas. the same situation was found at the rca, as only 16% of employees responded ‘a large amount of information’ and 36% ’do not know’. it seems that strategic information is provided with moderation in these organisations. the gathering of informal information is not frequent and rarely formalised at dcas as demonstrated by 51% of persons who were occasionally prepared/trained before going to public events and 24% never (the rca had similar results). therefore, reporting does not seem to be formalised. the organisation thus deprives itself of a very interesting source, the cost of which would be minimal. to the question about financial support for the monitoring of the strategic environment, responses at dcas reveal minimal support. at the rca, responses were disparate but generally this support seems to be minimal (32% ‘do not know,’ 20% ‘no funds’ and 16% ‘somewhat adequate’). in the light of these results, the general verdict is that the gathering of information falls into the category ’basic gatherer’ at dcas and the rca. taking into account the responses to the question about the targets of the gathering of strategic information from collaborators, generally, regardless of who is the target, the level of gathering is ‘basic gatherer’ but there are more employees in the category who are ‘hunters’ if the target is ’farmers,’ followed by ‘internally for services’ and then ‘elected officials’ (see table 7 for dcas for the rca). table 7. targeted persons for the collection of strategic information dcas rca basic gathering (g1) gathering ‘hunter’ (g2) gathering level g1/ g2 basic gathering (g1) gathering ‘hunter’ (g2) gathering level g1/ g2 farmers 62 40 g1 1.5 6 4 g1 1.5 elected officials 8 4 g1 2 5 1 g1 5 internally for services 18 10 g1 1.8 5 1 g1 5 no difference 5 5 g1 1.6 2 1 g1 2 total 93 59 152 1.6 18 7 25 2.6 attitude concerning the rhythm at which dcas collect information on technologies and markets, the most frequently selected answer is the same for both ‘irregularly, when available’. this reinforces the previous conclusion concerning the gathering of information. only 12% reported that their organisation has a written procedure and a dedicated ci system. the situation is comparable at the rca, as the most frequent response was ‘irregularly, when available’. only 12% underlined that their organisation has a written procedure and a dedicated ci system. moreover, 25% of respondents at dcas and 20% at the rca answered ‘i do not know’ which emphasizes a lack of participation in the decision making process and a top down organisational process. at dcas, to the question, ‘does the organisation audit staff knowledge regarding its 16 strategic environment to determine what report they possess’, 56% answered ’never’ which strongly indicates an ‘overall attitude of immunity’ which is staggering as they need to provide services for farmers (e.g. consultancy). at the rca, to the question, ‘what kind of support does the ci activity get from the management?’ 40% responded ‘just about enough for immediate needs’ which is the most common response. this places the rca in the ‘ad hoc attitude’ category which is somewhat better compared to dcas. notwithstanding, the organisation does not try to anticipate and is far from engaging in collective gathering and analysis of information leading to collective intelligence. technological support this section discusses the types of tools used to support the gathering of information. at dcas, the most utilised tools are web sites (97%) and search engines such as google (96.2%). following that, 24.8% of people used specialised websites e.g. espacenet (see www.espacenet.net). eight persons reported that they had access to other tools such as the paca databases. these results were confirmed by the self-declared position statement (at the end of the questionnaire and used to either confirm or contradict answers given within each category), where 91.4% of people responded that they are utilising ‘free common web tools, such as google to search for information’. therefore, dcas fall into the category ‘simple technological support’. at the rca, from a total of 73 selections across 10 possible answers, the most frequently used tools were websites (25) and google (25). only one person reported that they used specialised databases (e.g. dun and bradstreet) and four reported using specialised websites such as espacenet. this was confirmed by the self-declared position statement, where 88% of people responded that they utilise ‘free common web tools, such as google to search for information’. this places the rca in the category ‘simple technological support’. information systems this section aims to evaluate the level of information systems used by the organisation to manage strategic information. to this question, 60.2% at dcas stated ‘we rely on our memory and the willingness of the staff to share what they are learning’. the second most common answer was (21.1%) ‘the organisation has developed its own internal information system which is unique to the organisation and its needs’. thus, some people have certainly developed their databases and excel spreadsheets; they may use macros to analyse and store their strategic information. so, dcas are in the category ‘missing information system’. at the rca, 48% reported that they do not know. this again reveals the lack of visibility and participation in the decision making process. 24% declared that they do not use any systems to manage strategic information. 20% claimed they use standard systems. to the selfdeclared position statement, 52% answered ‘we rely on our memory and the willingness of the staff to share what they are learning’. this positions the rca in the category ‘missing information system’. therefore, both dcas and the rca are organised like silos in which collaborators organise their work as they can. furthermore, the redundancies of work must be frequent and the processes of these structures are far from being optimised. use the most common answer from staff at dcas is that ‘there is no established process for the use of ci’ (49.6%), followed far behind by ‘shortterm decisions’ (23.3%), and ‘operations are done on a daily basis. as soon as we receive information, we act’ (21.1%) and ‘long-term decisions’ (18.8%). dcas can be classified as ‘joneses users’. at the rca, the most common answer was that ‘there is no established process for the use of ci’ (48%), followed by almost an equal number of ‘decisions for the long term’ (32%) and ‘shortterm decisions’ (28%). yet, 48% (the most frequent answer) of people responded to the self-declared position statement ‘we move forward with the data we obtain, but we often do it too quickly’. hence, the rca falls into the ‘knee-jerk user’ category, which is slightly better than dca. location it was essential to know whether respondents deemed that a place dedicated to ci would be beneficial. 59.8% of respondents 17 at dcas indicated they knew to whom to provide information. the most frequent responses about the ‘service which is responsible for the gathering of strategic information’ were ‘all services have this responsibility’ (34.8%) followed by ‘no service has responsibility for it’ (31.8%) and ‘library’ (27.3%). these answers highlight the informal and disorganised nature of ci at dcas. yet, 36.4% of respondents agreed that a unit specialised in intelligence is essential but not always necessary. furthermore, only 14.4% of people replied negatively to the question; the responses generally emphasize that people are aware of the needs and improvements that should be done. 78.8% of respondents underlined that they did not have a unit dedicated to monitoring their strategic environment, and 9.1% replied ‘yes’ (they most often mentioned the library as being in charge of these functions). thus, the conclusion is that the location is ’ad hoc’ as regards the use of ci at dcas. regarding the rca, 68% of respondents indicated that they knew to whom to provide information; this is surprising with respect to the previous answer, as 68% replied that the process was not formalised. the most frequent responses about the ‘service which is responsible for the gathering of strategic information’ were: the library (56%), ’all services have this responsibility’ (44%) and then the planning service (20 %). it seems that the library works for and with only some people about ci. yet, 48% of respondents agreed that a unit specialised in intelligence is important but not always essential. surprisingly, 52% of respondents said they had a specialised intelligence unit and 44% ’no.’ we can interpret this with the lack of visibility, communication, participation and organisation of the ci process at the rca. thus, the conclusion is that the location is ’designated’ for the use of ci at the rca. cluster analysis of dca and the rca concerning the six themes of the typology studied, i.e. gathering, attitude, technology support, information system, use and location, the practices of dcas are homogeneous and at the lowest levels of the reference grid model. only dca 3 demonstrates a better attitude regarding strategic information (see table 8). the rca shows slightly better practices compared to dcas through their attitude and use, and there is a designated location for ci. for the detailed results by dca, see appendix 3. table 8. behavioural and operational typology of ci practices at dcas and the rca (g= gathering; a=attitude; ts= technology support; is= information system; u= use; l= location). g a ts is u l dca 1 g1 a1 ts1 is1 u1 l1 dca 2 g1 a1 ts1 is1 u1 l1 dca 3 g1 a2 ts1 is1 u1 l1 dca 4 g1 a1 ts1 is1 u1 l1 rca g1 a2 ts1 is1 u2 l2 cluster analysis for the different types of job table 9 summarises the results by types of job. overall, levels of dcas’ practices are at the lowest levels of the reference grid of the model but some jobs have better practices on given strands. therein, technicians are the only ones to reach level 2 for the gathering, which can be explained by their having numerous topics to work on. concerning this attitude, unsurprisingly librarians as information professionals have the best level, followed by vice-directors, 18 and department heads and technicians. as for the level of the information system (is) of the organisation in terms of the management of strategic information, librarians have access to higher levels of is, followed by vice directors. hence, such is exists and is used only by a few people. still, the top management (director and vice-director) prefer paper as they certainly have difficulties quitting their old habits. for the details of the cluster analysis for the different types of jobs, see appendices 4 and 5. at the rca, the level of practices is generally slightly better than those of dcas but some jobs stand out (see table 9). thus, for gathering, librarians are the only ones to be at the level of ‘hunter.’ regarding the attitude, it is reassuring that management positions have a higher level even though it is limited to ad hoc practices. while most collaborators do not use any is to manage their strategic information, librarians and it staff have access to very good levels of tools which are unique to them. this demonstrates yet again the very low levels of collective intelligence of such entities. although most employees are classified as ‘impulsive users’, some are more effective, including people in management. table 9. behavioural and operational typology of ci practice by type of job at dcas and the rca. dcas rca g a ts is u l g a ts is u l technician g2 a1 ts1 is1 u1 l1 consultant g1 a1 ts1 is1 u1 l1 surveys, rd g1 a1 ts1 is1 u1 l1 g1 a1 ts1 is1 u2 l2 it g1 a1 ts1 is6 u2 l2 information/ communication /library g1 a3 ts1 is3 u1 l1 g2 a1 ts1 is6 u3 l2 technical head. head of service g1 a2 ts1 is1 u1 l1 g1 a2 ts1 is1 u3 l2 director. vice-director g1 a2 ts1 is2 u1 l1 g1 a2 ts1 is1 u2 or u4 l2 cluster analysis for the type of structure, type of job, the targeted person of the collection of strategic information and the level of gathering this cluster analysis confirms the previous conclusion regarding a higher level of collection of information if the targeted person is a farmer (see appendix 6). however, a collaborator at dca4 from the ‘technical head/ head of service’ category who targets elected people for his/her collection of strategic information is at the level of ‘hunter.’ one can explain this either by the fact that this collaborator (only one head of service at dca4) has a special interest in that matter or the elected 19 persons in that dca are particularly demanding regarding strategic information. 5.0 conclusion this paper investigated the ci level of french public chambers of agriculture in one region to examine their ability to provide information and knowledge for competitive and strategic purposes, as a support for farmers to become more entrepreneurial. while the ci practices of dcas are at the lowest levels of the reference grid of the model (only dca 3 attained a2), rca practices are slightly better. dcas practices are anchored in the past and do not tackle the upheaval in the agricultural sector. compared to dcas, the rca demonstrates to some extent better attitudes, use and has a designated location for ci. however, its practices are ad hoc, its sources and tools are limited, and it is organised like a hive in which collaborators and departments work as though in silos. in such a context, redundant work might be frequent, and the feedback on the service satisfaction is certainly informal and un-optimised as well. thus, the existing system is ineffective, inefficient and the organisation is far from having attained collective intelligence. in both the rca and dcas, the ci organisation is informal and top-down, and the number of collaborators involved in the decision making process is very limited as demonstrated by the limited access of only a few to is to manage strategic information. yet, even though a few collaborators demonstrated higher ci practices (e.g. librarians and top management), most of them are at the lowest levels. hence, the findings of this study demonstrate that both dcas and the rca are not well adapted to satisfy the current needs for information and knowledge by farmers which is one of their missions. the diagnostics of ci practice applied to the typology provide a useful model which could inspire all dcas and rcas in france to improve their ci practices. this has the potential to help them improve their performance to better support french agriculture which is vital for the french economy, and this would be useful in dealing with the deep changes expected in the short and medium term (e.g. rapid emergence of new competitors, amendment or withdrawal of agricultural subsidies, rapid technological advances, and climate change). in the same way, organisations which are similar to dcas or rcas in the eu and the rest of the world could use this model as a platform to increase the quality of their services delivered to clients and users while also benefitting society. furthermore, this study demonstrates that ci models and practices can be implemented in the public sector just as in the private sector. obviously, it would require some adaptation, and the changes encountered by the private sector as the result of various phenomena (e.g. globalisation, fast improvements of icts) also have impacts on the public sector; ci is thus necessary to address these challenges. further work it would be quite interesting to utilise this behavioural and operational typology of ci practices in the public agricultural sector in other countries and especially in the eu. indeed, it could be the initial point of an ambitious eu program with an objective to adapt agriculture to the new constraints (e.g. rapid increases in the public debt, changes made to the cap and an increase in competition) of today’s agriculture. moreover, agriculture constitutes a strategic and vital sector for the eu, just as in france, as the ‘eu goes neck and neck with the us as the leading agricultural exporter’ (european commission, 2012, p. 1). moreover, since this model can be construed as an inspiring template to improve ci performance, one aspect that could be further explored is the qualitative and quantitative analysis of the outcomes triggered when one structure reaches different levels of each strand of the model. 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(2021) competitive intelligence approach for developing an e-tourism strategy post covid-19. journal of intelligence studies in business. 11 (1) 48-56. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 1 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive intelligence approach for developing an e-tourism strategy post covid-19 franky tulungena, johan reimon batmetanb*, trudi komansilanb, and sondy kumajasc adepartment of agribusiness, universitas kristen indonesia tomohon, indonesia; bdepartment of information technology and communication, universitas negeri manado, indonesia; cdepartment of information engineering, universitas negeri manado, indonesia; * john.reimon@unima.ac.id journal of intelligence studies in business please scroll down for article competitive intelligence approach for developing an etourism strategy post covid-19 franky tulungena, johan reimon batmetanb*, trudi komansilanb, and sondy kumajasc adepartment of agribusiness, universitas kristen indonesia tomohon, indonesia; bdepartment of information technology and communication, universitas negeri manado, indonesia; cdepartment of information engineering, universitas negeri manado, indonesia. *corresponding author: john.reimon@unima.ac.id received 18 march 2021 accepted 29 march 2021 abstract the covid-19 pandemic has brought many fundamental changes in running a tourism business. many countries need to reformulate their post-19 strategy so that the tourism sector will revive. this study aims to formulate a strategy for developing e-tourism by utilizing information technology. the method used is a competitive intelligence approach. this research takes samples from tourist destinations in indonesia. the results of this study indicate that the right strategy can encourage the tourism industry to grow back in the post-covid-19 period. the resulting strategy is based on campaign, content, community, cooperation, and competitiveness. these five basic strategies are implemented with an e-tourism model and a simple management pattern utilizing information technology. the results of this research can have implications for the formulation of e-tourism policies and produce recommendations for policymakers. keywords competitive intelligence, e-tourism, post covid-19 1. introduction the covid-19 pandemic, which is still endemic, has forced the world to adapt to limited circumstances. this limitation can be seen from the closure of access and exit to countries with high rates of transmission. this majorly impacts countries with a lot of tourism potential, but decreasing foreign tourist arrivals. measures to overcome the covid-19 pandemic have been carried out by vaccination in several tourist destination countries. however, the level of tourist visits has not increased significantly. this can be seen from the world tourism organization report (unwto) which states that there has been a decrease of 74% in tourism globally. this decline occurred in all regions, including asia pacific (84%), middle east and africa (75%), europe (70%), and even the americas (69%) (calderwood & soshkin, 2019). a specific example was in portugal, where during 2019 tourism contributed 8.7% of gdp with an increase of 7.9% compared to the previous year, but in march 2020 it experienced a decline of 50% and even stopped completely since may 2020 (camarinha et al., 2021). this also occurred in many european countries which are world tourist destinations (salehnia et al., 2020). this decreasing condition has various complex derivative problems such as decreased occupancy rates for hotel rooms, fewer bookings of travel tickets to tourist destinations, selling less merchandise, and increases in unemployment due to layoffs in the tourism business. this has a systematic impact and is very influential on the level of welfare. although vaccination has been carried journal of intelligence studies in business vol. 11, no. 1 (2021) pp. 48-56 open access: freely available at: https://ojs.hh.se/ 49 out in tourist destination countries, it has not shown a significant increase in the level of tourist visits. in addition, in several tourist objects, there have been strict applications of health protocols, but this has not been able to encourage an increase in the number of tourists expected. the application of this health protocol actually increases the operational costs of a tourist attraction. thus, it can be seen that the covid-19 pandemic has had a systematic impact on the tourism industry. solutions to overcome these problems include integrating it and business processes to address challenges in the tourism industry as a result of covid-19 (munas & arun, 2021). it and tourism integration that produces smart tourism with products such as ar (augmented reality) and vr (virtual reality) services are believed to be a solution to the challenges of tourism during the covid-19 pandemic (lee et al., 2020). in addition, another solution to this problem could be the use of a combination of service-oriented architecture (soa) and artificial intelligence (ai), which can be created by sonia, an integrated tourism system (qomariyah et al., 2020). there is also a model that relies on inbound marketing strategies, for example, the costa del sol planning & tourism board can produce a list of loyal and interested customers to come to their tourist attractions (sánchezteba et al., 2020). there is also a solution that includes creating a framework for building tourism industry resilience consisting of a government response, technological innovation, local interests, and customer and employee confidence. this framework is believed to be able to create a resilient tourism industry in the world of the global economy (sharma et al., 2021). these solutions have drawbacks when applied to a tourism industry that does not have an adequate business strategy. this study will discuss how to build a post-covid-19 tourism development strategy that has competitiveness based on information technology. this strategy is built using a competitive intelligence approach. this study aims to produce a strategy for developing e-tourism post-covid-19. this strategy is produced with a competitive intelligence approach, using the variables of destination, community, promotion, and competitiveness by considering the strengths, weaknesses, opportunities available, and challenges that can threaten the sustainability of the tourism industry. 2. method this study uses a competitive intelligence approach. this approach can be seen in figure 1. figure 1 describes the competitive intelligence approach in the form of a cycle which can be called the competitive intelligence cycle. the steps in this cycle can be explained in the following steps. 2.1 collection strategy the collection strategy utilizes a literature study. this helps to develop a strategy and formulate an implementation model that will be outlined below. this study is complemented by observations on the implementation of tourism, which were sampled in the city of manado during the pandemic, late 2019 to mid2021. as a medium-sized city, manado tourism has boomed with an increase of 1000% in foreign tourists. the city of manado is growing in tourism because it has beautiful landscapes that spoil the eyes. the condition of tourism in manado, which had just begun to be commercialized, fell due to the pandemic. tourist attractions closed and a prohibition on foreign and domestic visits was implemented. 2.2 information gathering the analysis was carried out based on information obtained from formal and informal information. formal information was obtained from journals on google scholar, elsevier, springerlink, researchgate, and ieee concerning e-tourism and competitive intelligence. the study also used tourism publications from the city of manado. informal information was drawn from direct observations at tourist destinations, and from travelers, cultural communities, and msmes related to tourism with manado city. figure 1 competitive intelligence cycle. 50 2.3 evaluation and analysis the evaluation that was done went through validity and reliability testing and is deemed worthy of being analyzed in the next stage. this is to get intelligence so that it can be a basis for developing an e-tourism strategy in the post-covid-19 era. 2.4 presentation the presentation was done by analyzing strength, weakness, opportunity, and threats with existing conditions so that we can get a strong opportunity strategy, a strategy of weakness opportunity, a strategy of strength threats, and strategies of weakness threats. its application is also described in the workflow for the tourist life cycle and suppliers' processes. using a mind map, the strategies obtained when implemented in e-tourism are also mapped. 3. result and discussion the results of this study describe the strategy for developing e-tourism. building a strategy begins by analyzing internal conditions (strengths and weaknesses) and external conditions (opportunities and threats). this internal condition is needed to find an appropriate strategy by utilizing existing strengths so that it can be superior in absolute and comparative terms while identifying weaknesses so that a strategy can be formulated to reduce losses that will arise. analysis of external conditions is very useful for mapping opportunities that can be exploited so that they can achieve strong competitiveness by paying attention to emerging threats. mapping threats is very important to analyze the tourism industry. internal and external conditions are shown in table 1. table 1 explains that the internal factors in the form of high government support, the abundance of human resources as a driving force, policies and laws made to support tourism, and various tourism destinations are the strength of e-tourism. on the other hand, tourism management and lack of professionalism, coordination, and synchronization between related agencies, financial support and high use of ict financing, and local tourist culture are still threats to the development of e-tourism. however, the opportunities created by the increasingly widespread use of the internet, the increasing trend of e-tourism, global programs that encourage the development of etourism, and the increasingly high growth of social media are supporting external factors. threats arising from the ongoing covid-19 pandemic, economic recession, competition for tourism between countries and even between regions, the uneven distribution of internet infrastructure, and the stability of security in tourist destination areas are external factors that need to be considered as well. these factors are used as the basis for formulating a development strategy for post-covid-19 etourism. the development strategy for post-covid19 e-tourism can be formulated based on the identification of internal and external factors. for this identification, the following strategies are developed. table 1 identification of strength, weakness, opportunity, threats in e-tourism. internal factors external factors strength weakness opportunity threats e-tourism helps make promotion more global government support for tourism is high human resources in large quantity supporting policies and laws for tourism tourist destinations in the form of natural potential and high cultural diversity poor management, especially e-tourism high cost of using ict mastery level the level of mastery and professionalism in implementing etourism is still low coordination, integration, and synchronization between agencies in carrying out promotions through etourism have not yet been implemented e-readiness that hasn't materialized yet low financial support the culture of local tourists who are still not aware of the sustainability of a tourist destination management of a tourist destination that does not yet have hygienic standards, especially in the face of a pandemic the increasing trend of tourism development the development of ict technology to support etourism is getting better the growing number of internet users e-tourism in indonesia is increasingly showing its stretch some programs can be processed globally into support, especially in the application of e-tourism the growth of social media increases tourism promotion with photo and video content from users increasing competition in world tourism internet network limitations inflation and global recession stability and security of tourist destination areas digital e-tourism security. the ongoing covid-19 pandemic so – strategy • develop a brand that is based on local wisdom uniquely and attractively, so that it is easily recognized and easily associated as a characteristic of manado city tourism. • build a strong image of a tourist destination thereby increasing attractiveness. building this image is done by offering tourist attractions that can stimulate the arrival of foreign tourists. in building this image, all tourism actors from upstream to downstream will collaborate to actively establish communication to develop the image that has been developed. • build synergy of e-tourism networks between tourism websites and communities. st – strategy • sustainable global promotion while building synergies between tourist destinations and surrounding areas. in this case, manado city, which is the provincial capital as a hub, can increase or promote tourist destinations in other regencies/cities in north sulawesi province. • support from the government that encourages communities to build and support tourism activities in the city of manado. this community is based on local wisdom, such as religious celebrations which are used as annual events, and tourist attractions organized by the government and supported by manado city residents, such as e.g., thanksgiving. • enforce law enforcement for lawbreakers who infiltrate internet sites. • conducting comparative studies with other tourist areas to increase the competitiveness of tourism in the city of manado. • ensure the implementation of vaccinations primarily for tourism actors from upstream to downstream to be carried out carefully. wo – strategy • encouraging and strengthening local tourism (community-based tourism, cbt) so that people can attract investors and use the internet as a promotional medium (e-cbt). • collaborate with academic practitioners to increase e-readiness and enhance local tourism culture using various instruments such as village funds, village funds, csr funds, and community service. • implementing standardization of management of tourism destination areas, especially regarding the implementation of hygienic levels that must be maintained. wt – strategy • empowering the community with the development of cbt, to generate competitive local products to be promoted via the internet. • achieve a common vision, especially at the culture and tourism office as a bridge with other agencies, to increase the competitiveness and professionalism of tourism, especially e-tourism in manado city. • ensure that the health protocol is still implemented by deploying a covid-19 task force to continue to advise and warn all tourism actors to comply with existing regulations until covid-19 cases around the world become zero. 3.1 strategy e-tourism (5c) the strategies that have been formulated can be developed for derivative strategies that are implemented in e-tourism, focusing on the 5cs. in figure 2 it can be seen that the resulting strategy can be in line with utilizing suppliers' processes. this shows that the 5c strategy can encourage demand, namely customers (users of tourism services) to grow so that they can move service providers to increase the supply of goods and services to ensure the best service is available. the 5c strategy can be described in the following. 3.1.1 campaign / promotion the campaign plays an important role in the promotion of a tourism destination, this involves branding tourist spots in order to strengthen the image for tourists who are interested in visiting the area. this can be done through various media to build brand awareness to help improve the destination's image globally. it is suggested to advertise on 52 the internet on well-known websites that have links to e-tourism sites that they wish to develop. when this attracts visitors to a tourism website, it can increase the number of hits on the developed site. increasing the number of hits will help search engine optimization (seo) so that the site will appear among the top in search keywords on the internet. the ranking obtained in search engines will be improved because the search engine search method will rank the sites that are referred to the most alongside the most relevant keywords desired by users. 3.1.2 content content includes interactive and informative tourism destination information. with informative content, tourists who want to know a tourist destination can easily find out which places they want to visit. you can also update information on the online encyclopedia site so that users who want to find information about these keywords can be helped by their explanations there. regular updates on the website further enhance the existing content. e-community base tourism (e-cbt) can also be added here. community lifestyles, local wisdom, promotion of local products belonging to the surrounding community, and handicrafts from small and medium enterprises owned by the community can be promoted through this tourism website. this existing content comprehensively raises all the potential that can be the main key to increasing local tourism. interactively the use of 360 video technology, virtual reality, and augmented reality can also be raised in content to sell a tourist destination. after all these things are discussed, the health protocol should still be applied regularly, in the form of interesting videos and infographics. 3.1.3 community community can be built through blogs, social media, e-cbt, forums, or social travel sites. maintaining these sites can be done by providing comments with various additional information or other things that can raise the image of a destination area. regular publishing of an e-newsletter can provide additional information about a tourist spot. word of mouth with the help of social media sites, blogs, vlogs, and podcasts will provide additional positive information that will increase the attractiveness of tourist areas. meanwhile, developing e-cbt can develop local cultural events, such as festival activities that have taken root in local communities. 3.1.4 cooperation it is important to establish cooperative relationships with external tourism service providers, such as travel agents, hotels, resorts, dive operators, transportation, local governments and tourist destinations, and telecommunications operators (cellular or internet service providers). universities can also provide various sources or activities that can support tourism, such as seminars or activities related to tourism. local governments can work together to build figure 2 implementing an e-tourism strategy in the tourist life cycle and suppliers’ processes. 53 destination packages that have the same theme or different themes but are geographically close to each other. the cooperation should establish intense communication and interaction with health facilities in the area. this can help stop a pandemic and keep a tourism site hygienic. this is important to do because in this pandemic, many people are more aware of the implementation of health procedures. 3.1.5 competitiveness for competitiveness, it is key to know and understand the market by implementing various strategies obtained by benchmarking extensively with other tourism sites, or with annual reports of various tourist destinations in other countries. the state of the tourism market, especially e-tourism, can also be known by periodical reports from the united nations worlds tourism organization (unwto) website or the official websites of other organizations. through this benchmarking, knowledge can be obtained to increase the competitiveness of the quality of local tourism products. this competitiveness can also be enhanced by industrial cooperation with universities to build or develop tourism products through joint research. the results of this research analysis will be input for decision makers, especially for marketing tourism products via the internet to make them more competitive. 3.2 development the development of an e-tourism strategy that has been formulated with content development is filled in interactively and informatively. this is done interactively with the use of technology and informative by utilizing information about e-tourism, especially regarding information on local tourism destinations. the idea of postcovid-19 tourism content is better if a tourism organization has entered the new age of communication with its users, which is more flexible, complex, and is no longer entangled with existing bureaucracies (camarinha et al., 2021). digital tourism content must also be supported by an adequate education process so that it can achieve optimum results (çınar, 2020). tourism content is very important to build while adhering to post covid-19 rules according to regulations set by local authorities and the covid-19 pandemic guidelines (islam, 2021). this is important to ensure visitors have adequate knowledge when visiting a tourist destination. content must be built using available information technology in a friendly manner so that smart technology-based content is produced (hamid et al., 2021) which makes visitors have a satisfying experience when visiting tourist destinations (stankov & gretzel, 2020). smart tourism must be built on strong knowledge by paying attention to the development of science from the results of previous research (shafiee et al., 2019). to be able to run this smart technology, it is very figure 3 mind map strategy e-tourism. 54 important to have workers who have sufficient technological skills to run various e-tourism technologies used in the tourism industry (carlisle et al., 2021). smart technology can also be used to build smart ways of choosing tourist destinations (ivars-baidal et al., 2021) (lee et al., 2020) by building measurement indicators precisely and quickly so that a new habit is built in planning tourism for potential visitors. this method can of course be done if smart tourism is built based on information technology which is used in smart e-tourism. it is necessary to establish clear boundaries (stankov & gretzel, 2021) to accurately explain the role of humans and the role of technology in presenting an e-tourism model that builds a comprehensive and strong tourism experience. communities in the development of etourism have an inseparable role. community is a tourism product based on local culture, has its local wisdom, is unique, and is interesting to become a tourist object that is different from destinations in other parts of the world. community-based ideas must pay attention to culture which is the fastest growing segment of the tourism industry (vena-oya et al., 2021). it is very important to build a community that pays attention to cultural symbols so that it does not conflict with local wisdom in the tourist destination area (vinodan & meera, 2020). the e-tourism development strategy can have a positive impact by taking into account the growing trends in society, which have changed the process in the tourism industry (okwemba & nambiro, 2020). the tourism industry is expected to be more flexible in building business models, and provide faster change management so that it can adapt to ongoing trends. through the e-tourism strategy that was developed previously, it can be a necessary driver, especially after covid19. it is very important to transform the postcovid-19 tourism business model so that a formula is found to answer the challenges of post-covid tourism (gretzel et al., 2020). this can be answered with the results of this research which suggest a strategy for dealing with the post-covid-19 situation. the management model that existed before covid-19 needs to be rearranged contextually according to post-covid needs without leaving the basic principles of tourism industry management (elida mahriani, purwanti dyah pramanik, 2020). various strategies have been put forward, it is very important to also pay attention to the competitiveness of the available tourism industry and put forward various ways to improve the competitiveness of the industry (grančay, 2020). on the other hand, in a covid-19 pandemic situation, many countries close their borders to foreign arrivals it will cause the flow of tourists from abroad to stop. then, the way to adjust the tourism industry is to take advantage of domestic tourism (local tourists) (woyo, 2021). an adequate strategy is needed to bring in domestic tourists. the strategy built into this research can be a good solution to overcome it. various strategies that have been produced need to calculate the business value so that it can produce measurable economic value so that it can generate economic returns, especially in the tourism sector. this calculation is to see the extent to which the tourism industry is competitive from a business point of view (michael et al., 2019). the strategy in this research has implications for tourism management based on intelligent information technology e-tourism, which is implemented in various tourist destinations based on this 5c strategy. 4. conclusion the study concludes that the competitive intelligence approach can produce a development strategy for post-covid-19 etourism. this is done by mapping the strengths and weaknesses in detail and identifying opportunities and threats in detail. then a strategy is built that can be implemented easily in the post covid-19 period. these strategies are in the form of campaigns, content, community, cooperation and competitiveness. the implication is that it can encourage an e-tourism-based industry to develop in the post-covid-19 period. 5. references calderwood, l. u., & soshkin, m. 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(2020) an examination of the organizational impact of business intelligence and big data based on management theory. journal of intelligence studies in business. 10 (3) 24-37. article url: https://ojs.hh.se/index.php/jisib/article/view/587 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukaria,* asyrian private university, syria *mouhib.alnoukari@spu.edu.sy journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 3,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10,no.32020 opinion: a project management approach to competitive intelligence miguel-ángel garcía-madurga and miguel-ángel esteban-navarro pp. 8-23 an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukari pp. 24-37 the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry stefan zwerenz pp. 38-62 the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyen and nguyen phong nguyen pp. 63-79 financial intelligence: financial statement fraud in indonesia muhammad ikbal, irwansyah irwansyah, ardi paminto, yana ulfah and dio caisar darma pp. 80-95 an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukaria,* asyrian private university, syria *corresponding author: mouhib.alnoukari@spu.edu.sy received 2 june 2020 accepted 26 october 2020 abstract big data and big data analytics have been considered to be a disruptive technology that will rebuild business intelligence. the purpose of this study is to enrich the literature on the organizational impact of business intelligence and big data based on management theory. while the majority of the organizational theories have had research dedicated to enhance the understanding of the impact of business intelligence and big data on organizational performance and decision-making, the research lacks scholarly work capable of identifying the other main organizational outcomes. to achieve this goal, a semi-systematic literature review was carried out to find all studies related to the research topic. then, an analysis was conducted to understand the use of the organizational theory in accordance with business intelligence and big data. finally, a grouping was developed to assign each organizational theory the related impact. the main findings of this work, after examining thirty-three related organizational theories, was that there are other important organizational impacts including innovation, agility, adoption, and supply-chain support. keywords big data, big data analytics, business intelligence, management theory, organizational theory 1. introduction with the data explosion from clicks, sensors, and technological innovations, new fields have become more and more in need, especially in the field of big data (bd; mazzei, & noble, 2020). every person is currently considered a “data generator” and organizations become “information processors” (mazzei, & noble, 2020). most of the scholars agree on the fact that bd enables organizations to create entirely new innovative products, and new business models. they also agree on the fact that bd helps achieving competitive advantages (holmlund, van vaerenbergh, ciuchita, ravald, sarantopoulos, villarroel-ordenes, & zaki, 2020; sadovskyi, engel, heininger, böhm, & krcmar, 2014). bd still represents, for a large number of companies, a tool that can enhance their reporting and monitoring capabilities (bischof, gabriel, rabel, & wilfinger, 2016). for a limited number of companies, bd represents an opportunity to create innovative business models (mazzei, & noble, 2020). in the latter case, bd can be integrated within the company’s structure, processes, infrastructure, technologies and strategy (bischof, gabriel, rabel, & wilfinger, 2016). scholars argue that there is a close relationship between bd, business intelligence (bi), and big data analytics (bda) because bi provides the methodological and technological capabilities for data analysis (e.g. llave, 2018; sun, zou, & strang, 2015). bi supports a firm’s decision-making with valuable data, information, and knowledge (alnoukari & journal of intelligence studies in business vol. 10, no. 3 (2020) pp. 24-37 open access: freely available at: https://ojs.hh.se/ 25 hanano, 2017), hence bda can be seen as a part of bi (sun, zou, & strang, 2015). in addition, both bi and bda share some common tools supporting the decision-making process. both bi and bda are common in emphasizing valuable data, information, and knowledge and both involve interactive visualization for data exploration and discovery. bi is currently based on four technology pillars: cloud, mobile, big data, and social technologies, which are also supported effectively by bda as a service and technology (passlick, lebek, & breitner, 2017; sun, zou, & strang, 2015). from the data viewpoint, knowledge discovery is the core of bda and bi systems (sun, zou, & strang, 2015). jin & kim (2018) consider bi’s “raw data” to have been expanded into “big data” due to the advanced technology capability. therefore, it is logical to consider that bi, bd, and bda are not independent concepts. consequently, it is beneficial to integrate all of them into an integrated dss, incorporating all processes from data gathering to data analytics and insights to decision making (calof & viviers, 2020; jin, & kim, 2018). however, analytical models based on single data sources may provide limited insights that consequently lead to biased business decisions. using multiple and heterogeneous data sources can provide a holistic view of the business and result in better decision-making (fan, lau, & zhao, 2015). fan et al. (2015) conclude that big data and its applications on bi have great potential in generating business impacts. according to braganza et al. (2017), bi and bd are more than technology, and to be fully effective, they should be incorporated into corporate strategy (calof, richards, & santilli, 2017). many current researches highlight the need to tackle the strategic incorporation of bi and bd technological development, and the link between bi, bd and sm theories (mikalef, pappas, giannakos, krogstie, lekakos, 2016). wang et al. (2018) address the lack of understanding of the strategic implications of bd by examining the historical development, architectural design, and components functionalities of bd analytics. organizational theory (ot) provides the basis to understand and define all of an organization’s activities, processes, and environments (sarkis, zhu, & lai, 2011). while bd technologies have been developed rapidly, academic research on the use of ot to explain bd impact on the organizational level is still in its infancy. recent researches have started to highlight organizational-level outcomes after applying big data initiatives (braganza, brooks, nepelski, ali, & moro, 2017; côrtereal, oliveira, & ruivo, 2019; mikalef, pappas, krogstie, & pavlou, 2020; wang, kung, & byrd, 2018). fiorini et al. (2018) argue that certain organizational theories support the findings about the implications of big data in an organizational context. therefore, considering the importance of ot to better understand the implications of bi and bd in an organizational context, the lack of an all-encompassing view of the bi and bd organizational impact based on ot, and the emerging role of bi and bd as tools for organizational innovation and transformation, this study will consider the following research question that guides this work: how can ots be used to provide an all-encompassing view of the bi and bd organizational impact? thus, in light of this, the main goal of this study is to analyze recent literature on ot related to the bi and bd domains, and to find the main organizational impacts of bi and bd based on ot. to achieve this goal, a semi-systematic literature review was carried out to find all studies that relate ot with bi and bd domains. then, an analysis was required to understand the core use of each ot in accordance with bi and bd domains. finally, a grouping was conducted to assign each ot its related impact. this work is inspired by recent related studies tackling ot with bd including walls & barnard (2020), fiorini et al. (2018), hazen et al. (2016), and erevelles et al. (2016). the remainder of this paper is organized as follows. the next section presets the research method. section 3 looks at the theoretical background of bd and ot. section 4 presents the core work of this study by analyzing the application of ot on bi and bd, then identifying the list of all related ots, and then groups the resulting ots according to the bi and bd organizational impact. section 5 discusses the study’s findings and provides discussions about the results. the last section explains the study’s outcomes as well as the conclusions drawn from the findings, the study implications and limitations, and finally the suggested future research directions. 2. research method inspired by sarkis et al. (2011) and fiorini et al. (2018), this study revises literature on bi and bd, and highlights how management 26 theory can be applied to enhance bi and bd research. the research method adopted was a semi-systematic literature review, as this approach is suitable for emerging topics such as bi and bd. the main purpose of a semisystematic literature review is to provide an overview of the research area. the research questions can be broad, the research strategy may or may not be systematic, and the analysis and evaluation can be quantitative or qualitative (snyder, 2019). this study uses this approach to classify the literature on the use of ots with bi and bd domains, to understand this topic in a comprehensive perspective, and to highlight the research gaps on this topic. the three steps of our literature review are presented in figure 1. the first step was the definition of the research question as presented in section 1. based on the research question, the search and selection of articles was conducted based on the recent findings from fiorini et al. (2018), which cover the literature till 2018, and the recent studies that have been published till 2020. the search for recent studies was carried out on the scopus database. the final number of selected articles after a full reading was 65 articles that are closely related to the research question. these articles identify 33 ots based on their application on bi and bd domains. the second step was to conduct an in-depth reading and analysis of the papers to identify the contributions and the gaps for future research. all 65 articles were analyzed in detail according to how they have applied management theories to underpin the research. the third and last step was to find the common organizational-level bi and bd impacts, and group the listed ots accordingly. 3. theoretical background 3.1 big data there is big hype around bd (al-qirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019). bd is becoming an attractive field for scholars, practitioners, and policymakers around the world. however, bd is currently still in the preliminary stages. therefore, bd is still complex due to its infancy as a field, and the limited understanding of what bd means for organizations. bd is more than a technology (braganza, brooks, nepelski, ali, and moro, 2017), and to be fully effective, it should be incorporated into organizational strategy (mazzei, & noble, 2017). moreover, bd affects organizational culture (gupta, & george, 2016); it converts firms to become data and evidence-based organizations (braganza, brooks, nepelski, ali, and moro, 2017). according to al-qirim et al. (2019), the convergence of iot with bd and cloud computing has taken organizations to the next level of value creation. moving from 3 vs into 5 vs, and finally 7 vs, our work adopts the updated definition of fosso wamba et al. (2015) of bd as “a holistic approach to manage, process and analyze the 7 vs (i.e., volume, variety, velocity, veracity, value, valence, and variability) in order to create actionable insights for sustained value delivery, measuring performance, establishing competitive advantages, and becoming a source of innovation.” this work argues that bd initiatives provide value at several stages: knowledge, organizational performance, organizational agility and flexibility, value creation, innovation, competitive advantage, and decision-making. 3.2 organizational theory according to sarkis et al. (2011) and fiorini et al. (2018), defining and identifying ots is not a simple task. sarkis et al. (2011) defines ot as “a management insight that can help explain or describe organizational behaviors, designs, or structures”. this definition is adopted for the purpose of this study. sarkis et al. (2011) argue that ot provides the ability to understand organizational activities, processes, and environments. figure 1 steps for this study’s semi-systematic literature review. 27 4. application of organizational theories on business intelligence and big data domains 4.1 organizational theories supporting business intelligence and big data for the development of this theoretical study, bibliographical research was conducted, since it contributes to reflexive thinking that allows us to find new facts and relations. with this effort, we bridge and extend the research on ot supporting bi and bd conducted by fiorini et al. (2018) and hazen et al. (2016), with the recent research in the field conducted by walls & barnard (2020) and erevelles et al. (2016). this study identifies thirty-three ots based on their application on bi and bd domains. the following paragraphs provide an ordered list of these ots, with a general description of each theory, and a list of bi and bd related studies: 1. absorptive capability theory is the ability to recognize the value of new and external information, and use it for future commercial use (walls & barnard, 2020). absorptive capacity can be a source of innovativeness, as it can be seen as a specific type of dynamic capability (wang, kung, & byrd, 2018). bi and bd related studies include braganza, brooks, nepelski, ali, and moro, 2017, walls & barnard, 2020, and wang, kung, & byrd, 2018. 2. actor-network theory considers organizations to be networks of heterogeneous actors. the theory addresses how these actors and organizations are constructed from the “bits and pieces out of which they are constructed” (hazen, skipper, ezell, & boone, 2016). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, and hazen, skipper, ezell, & boone, 2016. 3. agency theory explains how to control the relationships in which one ‘principal’ delegates work to another, the ‘agent’ (sarkis, zhu, & lai, 2011). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, nocker & sena, 2019, sarkis, zhu, & lai, 2011, and waller & fawcett, 2013. 4. contingency theory addresses the effect of the environment’s uncertainties on organizations (dubey, gunasekaran, & childe, 2018). bi and bd related studies include dubey, gunasekaran, & childe, 2018, fiorini, seles, jabbour, mariano, jabbour, 2018, gupta, & george, 2016, and waller & fawcett, 2013. 5. decomposed theory of planned behavior states that the behavioral intention is an antecedent of behavior and is determined by attitude, subjective norms and perceived behavioral control. in order to better understand the relationships between belief structures and the antecedents of intention, beliefs (attitude, subjective norms and perceived behavioral control) are decomposed into multidimensional constructs (esteves & curto, 2013). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, and esteves & curto, 2013. 6. diffusion of innovation theory provides an understanding about the innovation diffusion process, and how and why new ideas and technologies are spread (sarkis, zhu, & lai, 2011). ahmad et al. (2016) examined how the innovative traits of bd can influence its successful implementation. even more, it offers valuable insights into the characteristics of bi that influence its successful adoption. bi and bd related studies include ahmad, ahmad, & hashim, 2016, fiorini, seles, jabbour, mariano, jabbour, 2018, sarkis, zhu, & lai, 2011, and soon, lee, & boursier, 2016. 7. dynamic capabilities view refers to the firm’s abilities to maintain and adapt its internal resources to environment changes to maintain sustainability of competitive advantages (alnoukari & hanano, 2017). it refers to the capability of acquiring new ways of competitive advantage. it also involves continuous search, innovation and adaptation of firm resources and capabilities to uncover and tape new sources of competitive advantages (alnoukari & hanano, 2017). bi and bd related studies include alnoukari & hanano, 2017, braganza, brooks, nepelski, ali, & moro, 2017, chen, preston, & swink, 2015, côrte-real, oliveira, & ruivo, 2017, dubey, gunasekaran, & childe, 2018, erevelles, fukawa, swayne 2016, fiorini, seles, jabbour, mariano, jabbour, 2018, mikalef, krogstie, wetering, pappas, & giannakos, 2018, mikalef, pappas, giannakos, krogstie, & lekakos, 2016, fosso wamba, gunasekaran, akter, ren, ji-fan., dubey, & childe, 2017, gupta, & george, 2016, hazen, skipper, ezell, & boone, 2016, lin & kunnathur, 2019, nocker & sena, 28 2019, prescott, 2014, rialti, zollo, ferraris, & alon, 2019, shams, & solima, 2019, shan, luo, zhou, & wei, 2018, and walls & barnard, 2020. 8. ecological modernization describes a technology-based and innovation-oriented approach to environmental policy and politics (sarkis, zhu, & lai, 2011). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, hazen, skipper, ezell, & boone, 2016, and sarkis, zhu, & lai, 2011. 9. evolutionary perspective focuses on innovation, learning and competitive advantages (du, huang, yeung, & jian, 2016). bi and bd related studies include du, huang, yeung, & jian, 2016, and fiorini, seles, jabbour, mariano, jabbour, 2018. 10. expectancy theory considers that individuals’ performance is in accordance with rewards or inducements (fiorini, seles, jabbour, mariano, jabbour, 2018). bi and bd related studies include chang, hsu, & wu, 2015, and fiorini, seles, jabbour, mariano, jabbour, 2018. 11. game theory applies analytical tools to predict, explain and prescribe what players with various degrees of rationality will do in specific situations (liu, shao, gao, hu, li, & zhou, 2017). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, fu & zhu, 2017, liu, shao, gao, hu, li, & zhou, 2017, and liu & yi, 2017. 12. goal contagion theory explains how individuals automatically adopt and pursue a goal of another person’s behavior (aarts, gollwitzer, & hassin, 2004). bi and bd related studies include aarts, gollwitzer, & hassin, 2004, fiorini, seles, jabbour, mariano, jabbour, 2018, and lee, li, shin, & kwon, 2016. 13. ignorance based view relies on the fact that “what we don’t know (i.e. ignorance) is actually more than what we know (i.e knowledge).” in other words, ignorance enables knowledge (erevelles, fukawa, swayne 2016). bi and bd related studies include erevelles, fukawa, swayne 2016. 14. information systems participation theory explains what parameters used for designing systems involve users’ participation (silva, 2015). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018 and silva, 2015. 15. institutional theory explains the pressure effects from external environments on an organization’s adoptions of certain practices and actions (fiorini, seles, jabbour, mariano, jabbour, 2018). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, hazen, skipper, ezell, & boone, 2016, kwon, lee, & shin, 2014, and waller & fawcett, 2013. 16. knowledge management theory defines the process of using the value generated by intellectual capital transfer, where this value can be viewed as knowledge creation, acquisition, and sharing (alnoukari, alhawasli, alnafea, & zamreek, 2012). bi and bd related studies include braganza, brooks, nepelski, ali, and moro, 2017, du, huang, yeung, & jian, 2016, and fiorini, seles, jabbour, mariano, jabbour, 2018. 17. knowledge-based view states that knowledge and related intangibles are sources to competitive advantages (gupta, & george, 2016; herden, 2020). bi and bd related studies include côrte-real, oliveira, & ruivo, 2017, erickson & rothberg, 2017, fiorini, seles, jabbour, mariano, jabbour, 2018, hazen, skipper, ezell, & boone, 2016, herden, 2020, and gupta, & george, 2016. 18. market-based view is a traditional approach to strategic management. according to this approach, an organization gains competitive advantages according to its industry attractiveness, and its relative positioning against competitors. industry attractiveness is expressed by porter’s five competitive forces (porter, 1980). bi and bd related studies include bischof, gabriel, rabel, & wilfinger, 2016. 19. normalization process theory refers to the social processes through which new ideas and technologies are embedded within the working process. this theory fits well with macro approaches to innovation (shin, 2016). bi and bd related studies include shin, 2016. 20. organizational information processing view states that effective utilization of data requires an appropriate, context-specific composition of information processing mechanisms (fiorini, seles, jabbour, mariano, jabbour, 2018). bi and bda are considered important information processing mechanisms for organizations. they can reduce uncertainty and equivocality in the decision-making process (kowalczyk & buxmann, 2014). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, hazen, boone, ezell, & jonesfarmer, 2014, and kowalczyk & buxmann, 2014. 29 21. practice based view focuses on practices that can create specific and actionable advice for practitioners while explaining firm behavior and the influence on organizational performance (bromiley & rau, 2014). bi and bd related studies include wang, kung, wang, & cegielski, 2018. 22. resource based theory considers that resources are valuable, rare, inimitable, and non-substitutable; they are the main pillars of competitive advantages (alnoukari, 2009). bi and bd related studies include akter & fosso wamba, 2016, akter, fosso wamba, gunasekaran, dubey, & childe, 2016, barbosa, vicente, ladeira, & oliveira, 2018, braganza, brooks, nepelski, ali, and moro, 2017, cheah & wang, 2017, du, huang, yeung, & jian, 2016, erevelles, fukawa, swayne 2016, fiorini, seles, jabbour, mariano, jabbour, 2018, fosso wamba, gunasekaran, akter, ren, ji-fan., dubey, & childe, 2017, gupta, & george, 2016, hazen, skipper, ezell, & boone, 2016, mazzei, & noble, 2020, mikalef, krogstie, wetering, pappas, & giannakos, 2018, mikalef, pappas, giannakos, krogstie, lekakos, 2016, nocker & sena, 2019, shan, luo, zhou, & wei, 2018, suoniemi, meyer-waarden, & munzel, 2017, waller & fawcett, 2013, and walls & barnard, 2020. 23. resource dependence theory states that organizations attempt to reduce others’ power over them, often simultaneously trying to increase their own power over others (sarkis, zhu, & lai, 2011). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, hazen, skipper, ezell, & boone, 2016, prasad, zakaria, & altay, 2016, sarkis, zhu, & lai, 2011, and waller & fawcett, 2013. 24. service-dominant logic explains value co-creation between firms and customers. the theory considers service as the core component for economic exchange (xie, wu, xiao, & hu, 2016). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, and xie, wu, xiao, & hu, 2016. 25. social capital theory provides the base for social networks; it premise is that the network provides value to its members by allowing them access to the network’s social resources (hazen, skipper, ezell, & boone, 2016). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, and hazen, skipper, ezell, & boone, 2016. 26. social comparison theory focuses on self-assessment by comparing individuals’ own opinions and abilities with others (lee, li, shin, & kwon, 2016). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, and lee, li, shin, & kwon, 2016. 27. social exchange theory assumes the existence of relatively long-term relationships of interest based on intrinsic and extrinsic benefits (chang, hsu, & wu, 2015). it explains the motivational factors that lead managers to adopt bd solutions. beneficial factors such as organizational rewards, reputation, and reciprocity encourage managers use bi effectively for bd solutions (chang, hsu, & wu, 2015). bi and bd related studies include chang, hsu, & wu, 2015, and fiorini, seles, jabbour, mariano, jabbour, 2018. 28. sociomaterialism theory presents a balanced view by interlinking and enacting management, technology and human (akter, fosso wamba, gunasekaran, dubey, & childe, 2016). bi and bd related studies include akter & fosso wamba, 2016, akter, fosso wamba, gunasekaran, dubey, & childe, 2016, and fiorini, seles, jabbour, mariano, jabbour, 2018. 29. stakeholder theory suggests that companies produce externalities that affect both internal and external stakeholders (wilburn, & wilburn, 2016). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, sarkis, zhu, & lai, 2011, and wilburn, & wilburn, 2016. 30. systems theory states that organizations interact with their environment, thus, evolve constantly (hazen, boone, ezell, & jones-farmer, 2014). bi and bd related studies include fiorini, seles, jabbour, mariano, jabbour, 2018, and hazen, boone, ezell, & jones-farmer, 2014. 31. technological, organizational, and environmental framework states that the firm’s three elements (technological, organizational and environmental) have the ability to impact organizational innovation (chen, preston, & swink, 2015). bi and bd related studies include chen, preston, & swink, 2015, and fiorini, seles, jabbour, mariano, jabbour, 2018). 32. technology acceptance model explains how to encourage users to accept and utilize new technology (soon, lee, & boursier, 2016). bi and bd related studies include fiorini, 30 seles, jabbour, mariano, jabbour, 2018, liu, dedehayir, & katzy, 2015, and soon, lee, & boursier, 2016. 33. transaction cost economics considers the efforts and costs required to complete the activity between buyer and seller (sarkis, zhu, & lai, 2011). bi and bd related studies include akter & fosso wamba, 2016, fiorini, seles, jabbour, mariano, jabbour, 2018, hazen, boone, ezell, & jones-farmer, 2014, sarkis, zhu, & lai, 2011, and waller & fawcett, 2013. 4.2 analysis of the organizational impact of business intelligence and big data according to the organizational theories as listed in the previous section, 65 studies were conducted to investigate the role of ot in an understanding of bi and bd organizational impact. the next step of this work was to perform in-depth reading and analysis of the papers, discover the common organizationallevel bi and bd impact, and group the listed ot accordingly. this work analysis discovers six common bi and bd organizational impacts: performance, adoption, supply chain support, innovation, decision-making support, and agility. as value creation and competitive advantage are sources for improving organizational performance, they are all grouped under organizational performance. the following sub-sections provide the results of the literature analysis in order to highlight each of the previous bi and bd impacts, with all the related ots. 4.2.1 performance according to the literature analysis, most of the organizational theories were investigated to explain the effect of bi and bd on business performance (sixteen organizational theories). dubey et al. (2018) argue that dynamic capabilities view explains how bi and bd initiatives can be considered as a source of competitive advantage that improves organizational performance. similarly, du et al. (2016) argue that evolutionary perspective provides the framework to check how bd can affect organizational performance, and they further argue that knowledge management theory can explain how bd affects service innovation and a firm's performance (du, huang, yeung, & jian, 2016). in their interesting study, erevelles et al. (2016) suggested that an ignorance-based view coupled with inductive reasoning might lead to the discovery of hidden pattern, and future prediction, hence leading to enhance organizational performance. knowledge-based view explains how bi and bd can be considered a source of competitive advantage, thus enhances a firm's performance (fiorini, seles, jabbour, mariano, jabbour, 2018; herden, 2020). furthermore, they observed that organizational information processing view considers bda as important information processing mechanisms for organizations (fiorini, seles, jabbour, mariano, jabbour, 2018). moreover, they found that resource-based theory explains how bd can promote better performance and innovation (fiorini, seles, jabbour, mariano, jabbour, 2018). however, from external perspectives, bischof et al. (2016) observed that market-based view investigates the strategic relevance of bd, which results competitive advantages gain, hence improved strategic positioning in the market. waller & fawcett (2013) observed that resource dependence theory could explain how bda may increase a firm's performance. furthermore, according to service-dominant logic, bd provides enhanced organizational performance by collecting customer data, improving communication with customers, and adapting to environment changes effectively (xie, wu, xiao, & hu, 2016). hazen et al. (2016) argue that social capital theory, in a supply chain context, explains the positive effects of interactions among members on value and norms acceptance, and enhances knowledge sharing, hence improving performance. furthermore, they argue that systems theory investigates the impact of bd on supply chain performance through the measurement and control of data quality (hazen, boone, ezell, & jones-farmer, 2014). in their study, akter et al. (2016) argue that sociomaterialism theory presents a balanced view of bda capabilities by interlinking and enacting management, technology, and people to support a firm's performance. whereas, akter & fosso wamba (2016) noted that transaction cost economics explains how to use bi and bda for e-commerce transactions, and enhance organizational performance by improving market transaction cost efficiency, managerial transaction cost efficiency and time cost efficiency. in their recent research, wang et al. (2018) observed that practice-based view investigates how to facilitate the implementation of bd to 31 contribute to business value, hence improving a firm's performance. 4.2.2 adoption according to the literature analysis, a good number of organizational theories were applied to foster bi and bd adoption (twelve ot). decomposed theory of planned behavior helps to predict the intention to adopt bd (esteves & curto, 2013). similarly, lee et al. (2016) noted that social comparison theory explains an organization's intention to adopt bd. fiorini et al. (2018) argue that diffusion of innovation theory helps to understand the process for bi and bd adoption. they further argue that expectancy theory helps to understand how to accept and adopt bi and bd (fiorini, seles, jabbour, mariano, jabbour, 2018). additionally, they argue that goal contagion theory explains the intention to adopt innovative information technology such as bd with limited it knowledge (fiorini, seles, jabbour, mariano, jabbour, 2018). in the same vein, silva (2015) found that information systems participation theory provides the grounds for successful bd adoption and implementation. in this context, liu et al. (2015) argue that the technology acceptance model investigates the key factors influencing bd adoption. hazen et al. (2016) noted that institutional theory explains how external pressures affect the decision to adopt bd for a sustainable supply chain. in the same context, they found that resource dependence theory helps explaining the adoption of bd in supply chain management (hazen, skipper, ezell, & boone, 2016). in the same vein, shin (2016) found that normalization process theory helps analyzing how to adopt bd in organizations, and supply chains. xie et al. (2016) argue that service-dominant logic can explain the effects of adopting bd by cocreating value with customers. chang et al. (2015) observed that social exchange theory states the behavioral factors that lead managers to adopt bd. 4.2.3 supply chain according to the literature analysis, 12 organizational theories were used to examine the effect of bd on the supply chain. hazen et al. (2016) argue that actornetwork theory can be used to examine the impact of bd on supply chain sustainability, as the theory provides the framework to describe the effect of changing a network (e.g. supply chain) on its actors. furthermore, they argue that agency theory can be used to analyze bd impact on relationships in a supply chain context (hazen, skipper, ezell, & boone, 2016). they further argue that ecological modernization describes how bd can support supply chains (hazen, skipper, ezell, & boone, 2016). hazen et al. (2016) highlight that institutional theory can explain how external pressures affect the decision to adopt bd for a sustainable supply chain. they further argue that a knowledge-based view highlights the importance of data quality for predictive bda in supply chain management (hazen, skipper, ezell, & boone, 2016; herden, 2020). in the same vein, they argue that resource dependence theory can explain the adoption of bd in supply chain management (hazen, skipper, ezell, & boone, 2016). like the previous theories, they tested social capital theory in the supply chain context, and found it can explain the positive effects of interactions among members on value and norms acceptance, and enhance knowledge sharing, hence improving performance (hazen, skipper, ezell, & boone, 2016). finally, they investigated systems theory, and argued that it can provide an understanding of the impact of bd on supply chain performance through the measurement and control of data quality (hazen, boone, ezell, & jones-farmer, 2014). waller & fawcett (2013) argue that contingency theory can be applied to explain how bd can help a supply chain to adapt to environmental changes. whereas, shin (2016) found that normalization process theory can help analyzing how to adopt bd in organizations, and supply chains. fiorini et al. (2018) argue that game theory can be used to find the pricing for a green supply chain. they further argue that resource-based theory can explain the impact of bd on supply chains (fiorini, seles, jabbour, mariano, jabbour, 2018). 4.2.4 innovation four organizational theories were applied to examine the effect of bd on innovation: absorptive capacity, evolutionary perspective, knowledge management theory, and resourcebased theory. wang et al. (2018) argue that absorptive capacity can be a source of innovation, as it can be seen as a specific type of dynamic capability. whereas, du et al. (2016) argue that evolutionary perspective provides the framework to check how bi and bd can affect service innovation performance. similarly, 32 they found that knowledge management theory can explain how bi and bd affects service innovation and a firm's performance (du, huang, yeung, & jian, 2016). fiorini et al. (2018) argue that resourcebased theory explains how bd can promote better performance and innovation. 4.2.5 decision making four organizational theories were applied to examine the effect of bd on the decisionmaking process: game theory, organizational information processing view, stakeholder theory, and transaction cost economics. according to liu et al. (2017), game theory can be used to enhance the decision-making process. hazen et al. (2016) argue that an organizational information processing view can help in assessing the use of bi and bd to reduce uncertainty in the decision-making process. they further argue that transaction cost economics provides the decision makers with the factors for evaluating "make versus buy" decisions concerning bi and bd initiatives (hazen, skipper, ezell, & boone, 2016). wilburn & wilburn (2016) noted that stakeholder theory can explain how bda can be used to better satisfy stakeholder expectations, and improve the decision-making process in regards to the organization's stakeholders. 4.2.6 agility according to the literature analysis, three organizational theories were used to examine the effect of bd on organizational agility to environment changes. these theories are: contingency theory, dynamic capabilities view, and service-dominant logic. waller & fawcett (2013) argue that contingency theory can be applied to explain how bd can help organizations to adapt to environmental changes. similarly, braganza et al. (2017) argue that dynamic capabilities view states that bi and bd can help organizations to adapt to environment changes. servicedominant logic also explains how bd can support an organization’s adaption to environmental changes effectively (xie, wu, xiao, & hu, 2016). 5. findings and discussion in the course of this study, we have found and analyzed most of the recent literature on the topic of ot applications on bd. several findings were made over the course of this research. according to the literature analysis, both dynamic capability view and resource based theory are the most dominant ots that have been used to investigate bi and bd issues (about twenty related papers). resource based theory was acknowledged as one of the most powerful theories that describes, combines and predicts organizational relationships (gupta, & george, 2016). unlike most of the ots, resource-based theory is the only one that considers origination as a set of dissimilar resources, and by combining them the firm can achieve a competitive advantage (gupta, & george, 2016). according to braganza et al. (2017), this theory proposed that resources are tangible resources including data, technology and other basics resources (e.g., time and investment), human resources including managerial and technical skills (shan, luo, zhou, & wei, 2018), and intangible resources including data-driven culture and the intensity of organizational learning. however, suoniemi et al. (2017) found that according to the empirical analysis results, bd analytics skills are the most critical domain of bi and bd resources. hence, they confirm the concerns raised by scholars that a lack of talented people can be the greatest impediment to a bi and bd initiative’s success (nocker & sena, 2019). conversely, braganza et al. (2017) argue that resource-based theory assumptions are not valid for bd and may not be able to explain the management of resources in bd initiatives. data, the core resource in bi and bd, is not rare. data may be sourced from many external providers, and can be accessed and used by everyone. the same arguments can be applied for physical resources such as hardware and servers. people with bi and bd skills are hard to find. often, they are hired from outside the organization, and this may not be employed by the organization and therefor may not be utilized in this theory sense of the word. braganza et al. (2017) confirm that not all aspects of bi and bd meet the theory requirements. dynamic capability view is the organization’s ability to update and reconfigure by responding to changes in the external environment to develop sustainable competitive advantages (erevelles, fukawa, swayne 2016). according to dubey et al. (2018), dynamic capability view was raised due to the resource-based theory failure on providing explanations on the way the resources can 33 provide competitive advantages to the firm. dynamic capability view is able to provide the explanation in a changing environment by arguing that the combination, transformation, and renewal of a firm’s resources are the base for competitive advantages (dubey, gunasekaran, & childe, 2018). similarly, fosso, wamba et al. (2017) argue that bda can be considered a dynamic capability that results from the organization’s ability to reconfigure resources. to highlight more findings, table 1 provides insight into the bi and bd organizational impact with the related ots. according to table 1, organizational performance was the most common bd outcome explained by ots (fifteen theories). this result agrees with bi and bd literature that considers bi and bd initiatives the source of competitive advantage, which improve organizational performance (e.g. walls & barnard, 2020; lin & kunnathur, 2019; nocker & sena, 2019). bi and bd adoption was investigated by many ots (twelve theories; table 1). most of the related ots help to understand how to accept and understand bi and bd adoption (e.g. ahmad, ahmad, & hashim, 2016; soon, lee, & boursier, 2016; esteves & curto, 2013; hazen, skipper, ezell, & boone, 2016). interestingly, supply chain sustainability was also highly connected to many ots (12; table 1), at the same level as bi and bd adoption. most of the related ots are used to examine the impact of bd on supply chain sustainability (e.g. hazen, skipper, ezell, & boone, 2016; shin, 2016; waller & fawcett, 2013). four ots investigated innovation. these theories explain how bi and bd can promote innovation (du, huang, yeung, & jian, 2016; fiorini, seles, jabbour, mariano, jabbour, 2018; wang, kung, & byrd, 2018). four ots investigated decision-making. these theories explain how bi and bd can be used to enhance the decision-making process (liu, shao, gao, hu, li, & zhou, 2017; hazen, skipper, ezell, & boone, 2016; wilburn, & wilburn, 2016). three ots investigated agility. these theories can be applied to explain how bi and bd can help organizations to adapt to environmental changes (braganza, brooks, nepelski, ali, & moro, 2017; waller & fawcett, 2013; xie, wu, xiao, & hu, 2016). finally, we should note that some ots have more than one impact on bi and bd domains table 1 grouping ot according to bi and bd organizational impact. bi and bd impact ot performance dynamic capability view evolutionary perspective ignorance based view knowledge-based view knowledge management theory organizational information processing view resource dependence theory resource based theory service-dominant logic social capital theory sociomaterialism theory systems theory transaction cost economics practice based view market-based view adoption decomposed theory of planned behavior diffusion of innovation theory expectancy theory goal contagion theory information systems participation theory institutional theory normalization process theory resource dependence theory service-dominant logic social comparison theory social exchange theory technology acceptance model supply chain actor-network theory agency theory contengency theory ecological modernization game theory institutional theory knowledge-based view normalization process theory resource dependence theory resource based theory social capital theory systems theory innovation absorptive capability theory evolutionary perspective knowledge management theory resource based theory decision making game theory organizational information processing view stakeholder theory transaction cost economics agility contengency theory dynamic capability view service-dominant logic (table 1). for example, contingency theory impacts the supply chain and agility, game theory impacts the supply chain and decisionmaking, evolutionary perspective impacts innovation and performance, resource-based 34 theory impacts the supply chain, innovation and performance, and dynamic capability view impacts performance and agility. 6. conclusion and directions for future research this work was conducted to identity the organizational impact of bi and bd based on ots. recently, researchers argue that adopting bi and bd solutions enhances organizational performance and the decision-making process. the purpose of this work was to examine all other organizational impact when adopting bi and bd solutions. this goal was achieved by conducting a semi-systematic literature review to find all studies that relate ots with bi and bd. then, an analysis was done to understand the use of the ot in accordance with bi and bd. finally, a grouping was conducted to assign each ot with its bi and bd related impacts. this work concludes, from the extensive review carried out, that ot supports studies on bi and bd. the study demonstrates that even with the considerable number of ots that impact bi and bd, they all share the same main characteristics in the bi and bd context: they help understanding bi and bd impact on organizational performance, adoption, support supply chain sustainability and management, innovation, decision-making support, and agility. this study demonstrates an uneven distribution of ots use with bi and bd. although two dominant theories were investigated, resource-based theory and dynamic capability view, there is a need for more research on other important modern theories such as game theory, sociomaterialism theory, goal contagion theory, information systems participation theory, normalization process theory, and service-dominant logic. this study highlights that ots have different impact attentions on bi and bd. organizational performance, bi and bd adoption and supply chain sustainability have the highest attention. the work suggests the need for future studies to focus more on other important directions including innovation, decision-making, and agility. in term of implication, this work aims to list all up-to-date theories that have been used to support the use and development of bi and bd. although most of the literature focuses more on the linkage between bd and ots, bd and bda can still be seen as a part of bi (sun, zou, & strang, 2015). hence, the results can be applied for bi accordingly. exploring how the knowledge of bi and bd has used ots helps to create innovative insights for theoretically original research in bi, bd and bda and their impact on a firm’s performance, innovation, adoption, agility, decision-making, and supplychain support. in term of limitations, this work has some limitations regarding its scope. the articles analyzed were mainly carried out from recent empirical studies including fiorini et al (2018), and hazen et al. (2016), and the recent researches in the field, which does not gather all the latest research in the field. to conclude, we have outlined some avenues for future research in the area of bi and bd. we propose some opportunities for future studies in this promising research area. future studies could focus on organizational behavior and structure in accordance with bi and bd implementation. technological research of bi and bd dominates organizational culture studies, especially data-driven, organizational learning and knowledge sharing within bi and bd domains. future studies could focus on bi and bd organizational culture. 7. references aarts, h., gollwitzer, p. m., & hassin, r. r. (2004). goal contagion: perceiving is for pursuing. journal of personality and social psychology, 87(1), 23–57. ahmad, a., ahmad, r., & hashim, k. f. 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(2016). value co-creation between firms and customers: the role of big data-based cooperative assets. information & management, 53(8), 1034– 1048. page 4 editors note vol 10 no 2 editor’s note vol 10, no 2 (2020) the impasse of competitive intelligence today is not a failure. a special issue for papers at the ici 2020 conference intelligence studies started as strategy, the “art of troop leader; office of general, command, generalship", both in europe (in greece as stratēgia, but first of all much later with carl von clausewitz’ book “on war”, 1832 ) and in china much earlier with the seven military classics (jiang ziya, the methods of the sima, sun tzu, wu qi, wei liaozi, the three strategies of huang shigong and the questions and replies between tang taizong and li weigong). the entities studied then were nation states. later, corporations often became just as powerful as states and their leaders demanded similar strategic thinking. many of the ideas came initially from geopolitics as developed in the 19th century, and later with the spread of multinational companies at the end of the 20th century, with geoeconomics. what is unique for intelligence studies is the focus on information— not primarily geography or natural resources— as a source for competitive advantage. ideas of strategy and information developed into social intelligence with stevan dedijer in the 1960s and became the title of a course he gave at the university of lund in the 1970s. in the us this direction came to be known as business intelligence. at a fast pace we then saw the introduction of corporate intelligence, strategic intelligence and competitive intelligence. inspired by the writings of mikael porter on strategy, as related to the notion of competitive advantage the field of competitive intelligence, a considerable body of articles and books were written in the 1980s and 1990s. this was primarily in the us, but interest spread to europe and other parts of the world, much due to the advocacy of the society of competitive intelligence professionals (scip). in france there was a parallel development with “intelligence économique”, “veille” and “guerre économique”, in germany with “wettbewerbserkundung” and in sweden with “omvärldsanalys,” just to give some examples. on the technological side, things were changing even faster, not only with computers but also software. oracle corporation landed a big contract with the cia and showed how data analysis could be done efficiently. from then on, the software side of the development gained most of the interest from companies. business intelligence was sometimes treated as enterprise resource planning (erp), customer relations management (crm) and supply chain management (scm). competitive intelligence was associated primarily with the management side of things as we entered the new millennium. market intelligence became a more popular term during the first decade, knowledge management developed into its own field, financial intelligence became a specialty linked to the detection of fraud and crime primarily in banks, and during the last decade we have seen a renewed interest for planning, in the form of future studies, or futurology and foresight, but also environmental scanning. with the development of big data, data mining and artificial intelligence there is now a strong interest in collective intelligence, which is about how to make better decisions together. collective intelligence and foresight were the main topics of the ici 2020 conference. all articles published in this issue are from presentations at that conference. the common denominator for the theoretical development described above is the information age, which is about one’s ability to analyze large amounts of data with the help of computers. what is driving the development is first of all technical innovations in computer science (both hardware and software), while the management side is more concerned with questions about implementation and use. management disciplines that did not follow up on new technical developments but defined themselves separately or independently from these transformations have become irrelevant. survival as a discipline is all about being relevant. it’s the journey of all theory, and of all sciences to go from “funeral to funeral” to borrow an often-used phrase: ideas are developed and tested against reality. adjustments are made and new ideas developed based on the critic. it’s the way we create knowledge and achieve progress. it’s never a straight line but can be seen as a large number of trials and solutions to problems that change in shape, a process that never promises to be done, but is ever-changing, journal of intelligence studies in business vol. 10, no 2 (2020) p. 4-5 open access: freely available at: https://ojs.hh.se/ 5 much like the human evolution we are a part of. this is also the development of the discipline of intelligence studies and on a more basic level of market research, which is about how to gather information and data, to gain a competitive advantage. today intelligence studies and technology live in a true symbiosis, just like the disciplines of marketing and digital marketing. this means that it is no longer meaningful to study management practices alone while ignoring developments in hardware and software. the competitive intelligence (ci) field is one such discipline to the extent that we can say that ci now is a chapter in the history of management thought, dated to around 1980-2010, equivalent to a generation. it is not so that it will disappear, but more likely phased out. some of the methods developed under its direction will continue to be used in other discipline. most of the ideas labeled as ci were never exclusive to ci in the first place, but borrowed from other disciplines. they were also copied in other disciplines, which is common practice in all management disciplines. looking at everything that has been done under the ci label the legacy of ci is considerable. new directions will appear that better fit current business practices. many of these will seem similar in content to previous contributions, but there will also be elements that are new. to be sure new suggestions are not mere buzzwords we have to ask critical questions like: how is this discipline defined and how is it different from existing disciplines? it is the meaning that should interest us, not the labels we put on them. unlike consultants, academics and researchers have a real obligation to bring clarity and order in the myriad ideas. the articles in this issue are no exception. they are on collective intelligence, decision making, big data, knowledge management and above all about the software used to facilitate these processes. the first article by teubert is entitled “thinking methods as a lever to develop collective intelligence”. it presents a methodology and framework for the use of thinking methods as a lever to develop collective intelligence. the article by calof and sewdass is entitled “on the relationship between competitive intelligence and innovation”. the authors found that of the 95 competitive intelligence measures used in the study 59% were significantly correlated with the study’s measure of innovation. the third article is entitled “atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making” and is written by grèzes, bonazzi, and cimmino. the research project shows how companies can constantly adapt to their environment, how they can integrate a learning process in relation to what is happening and become a "learning company". the next article by calof and viviers entitled “big data analytics and international market selection: an exploratory study” develops a multi-phase, big-data analytics model for how companies can perform international market selection. the last article by vegas fernandez entitled “intelligent information extraction from scholarly document databases” presents a method that takes advantage of free desktop tools that are commonplace to perform systematic literature review, to retrieve, filter, and organize results, and to extract information to transform it into knowledge. the conceptual basis is a semantics-oriented concept definition and a relative importance index to measure concept relevance in the literature studied. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. have a safe summer! on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2020 jisib, halmstad university. all rights reserved. to cite this article: degerstedt, l. (2015) social competitive intelligence: sociotechnical themes and values for the networking organization. journal of intelligence studies in business. vol 5, no 3. pages 5-34. article url: https://ojs.hh.se/index.php/jisib/article/view/135 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index social competitive intelligence: socio-technical themes and values for the networking organization lars degerstedta adepartment of media technology, sodertörn university, sweden; lars.degerstedt@sh.se journal of intelligence studies in business please scroll down for article social competitive intelligence: socio-technical themes and values for the networking organization lars degerstedt department of media technology, södertörn university, sweden; lars.degerstedt@sh.se received 27 august 2015; accepted 5 december 2015 abstract this article introduces the notion of social competitive intelligence, meaning competitive intelligence (ci) for the networking organization. a novel socio-technical framework called the social ci framework (scif) is presented, intended for analysis and design of social ci processes, methods and tools. by using a socio-technical perspective, both social and technical aspects are considered together in scif. the framework is founded on a theory related to enterprise 2.0 and wikinomics, and is intended to be used to study social ci using principles such as openness, participation, sharing and co-creation. the presented results are based on a literature review and an exploratory study with interviews of ci experts from swedish organizations. scif explicitly distinguishes between task-oriented models and collaboration models, and models of different socio-technical perspectives. moreover, scif uses the mechanisms of socio-technical themes and a socio-technical value map that relate the theoretical and empirical characteristics with the scif modeling method. keywords community, competitive advantage, competitive intelligence, computersupported collaborative work, enterprise 2.0, information systems, knowledge management, networking organization, social computing, social learning, social media, social networking, social organization, socio-technical systems, strategic management, wikinomics 1. introduction a major trend in the world today is the increasing competition in global and digitalized markets where the speed of change and innovation is becoming faster than ever before. the development is fueled by developments in information technology (it) and is likely to continue for a long time. in order for organizations to keep up with the rapid change, a systematic approach to understand the surrounding world is needed. an existing solution is called competitive intelligence (ci), which is a systematic process whereby an organization (division, unit or 1 the term competitive in ci can be traced back to the economic notion of competitive advantage, see e.g. porter (2008) and barney & hesterly (2012). the notion of competitiveness is used within the context of ci to emphasize that the intelligence is related to any aspect of the surrounding competitive environment with strategic significance, cf. sharp (2009). in swedish, the two terms “omvärldsbevakning” (monitoring) and “omvärldsanalys” (analysis) person) gathers, analyzes, and transforms information into actionable intelligence, see e.g. murphy (2005) and sharp (2009). the objective of ci is to understand how the surrounding competitive environment1 will impact an organization – by monitoring events, actors, trends, research breakthroughs, and so forth – in order to be able to make relevant strategic decisions. furthermore, in a situation with continuous innovation and change, organizations are relying more and more on informal social networking structures and individual decision making as a means to increase rapid response are often used instead of ci. the swedish terms are slightly more general than ci since the term “omvärld” means “surrounding world” and refers to any aspect of the surrounding world that has strategic significance (which makes sense in particular for non-commercial organizations such as public authorities). for this article, ci is used as an english synonym for “omvärldsbevakning” and “omvärldsanalys” which follows swedish practice. journal of intelligence studies in business vol. 5, no. 3 (2015) pp. 5-34 open access: freely available at: https://ojs.hh.se/ 6 and agile creativity within the enterprise. these (socially) networking organizations2 often rely on the use of social technology with features from web 2.0 as an important part of their collaborative networking platform. a major promise of using networking for work is the use of mass-collaboration, i.e. increased participation and collaborative possibilities that allows people to influence and take advantage of other people's knowledge in new and flexible ways (tapscott & williams 2008; bradley & mcdonald 2011). the underlying question of the presented research is how mass-collaboration and social networking can be utilized for ci, and vice versa how ci should be adapted for the (socially) networking organization. a new term called social ci will be used to refer to any ci process, method or tool that is adapted for the networking organization3. social ci relies on notions of enterprise 2.0 and wikinomics, using systemic principles such as openness, participation, individual freedom, democracy, self-organization, sharing and co-creation (mcafee 2006; tapscott & williams 2008; malone 2004; li & bernoff 2011; bradley & mcdonald 2011). from the viewpoint of social ci, the ci process is viewed as a (unique) form of knowledge work (nonaka & takeychi 1995; davenport 2005; liebowitz 2012) that combines: a) an information-gathering and analytical methodology for strategic decision support, cf. porter (1980); murphy (2005); sharp (2009); b) a social community-based learning process, cf. wenger (2000); brandi & elkjaer (2009); c) integration with and decision support of the networking organization, cf. cross & parker (2004); tapscott (2009); gray (2012); d) use of social it that supports collaboration and networking for analytical work, cf. mcaffe (2009); li & bernoff (2011); crumlish & malone (2009); wodtke & govella (2009). 2 the term (socially) networking organization is used as an umbrella term for organizational use of work models that rely on informal and self-organizing social networks, instead of relying mainly on more formalized roles and work units. networking work models can be physical, virtual (based on social technology), or a combination of both. in practice, virtual solutions are often a necessary component of the network and mean the adjustment of work processes by using the emerging web 2.0 technologies in the enterprise. there are various related terms, e.g. (virtual) social networking, mass collaboration, enterprise 2.0, social business and the social organization (cross & in the article a socio-technical framework called the social ci framework (scif) is introduced, intended to be used as a conceptual foundation for analysis and design of social ci. by using a socio-technical perspective, both social and technical aspects are considered together with the scif. the presented results are based on a literature survey and an exploratory study with in-depth semi-structured interviews of nine ci experts from swedish organizations that work either in firms that supplies ci services or deliver expert ci knowledge in relation to teaching and research. from these findings the scif has been deduced, which consists of four parts that will be discussed in the remainder of the report: a) a theoretical foundation of social ci with a selection of relevant theory, based on a literature review. a theorybased perspective denoted peoplemedia-people strategy is introduced. see section 2. b) socio-technical themes that cluster relevant socio-technical design requirements for social ci, which have been extracted from identified tendencies in the ci field according to the interviewed experts. see section 3. c) a socio-technical value map that is a form of pattern language for properties that reflect the underlying characteristics and gains of social ci, from selected studies of the literature review. see section 5. d) a socio-technical modeling method is outlined where the other parts of the framework are used together for practical analysis and design of social ci. see section 6. the current study is based mainly on the expertise in the supplier organizations and existing theory rather than the customer organizations using ci. the customer organizations using ci will be the object of study in forthcoming studies, which will parker 2004; traudt & vancil 2011; bradley & mcdonald 2011; mcafee 2006; tapscott & williams 2008; li & bernoff 2011)). 3 the related term social intelligence has been used in a report from mckinsey (harrysson et al. 2012). the main emphasis in this work concerns how the character of the information flows changes due to the use of social networking media, which seems to complement the findings reported in this article. social media intelligence is perhaps a better term for this, which is an overlapping notion with social ci, but they are not identical since ci emphasizes the strategic character of the collected intelligence. 7 further compliment the findings of the proposed framework. the presented scif is to the best knowledge of the author a novel approach. in previous work, von krogh (2012) and haefliger et al. (2011) discuss how social software challenges strategic thinking by introducing more open and distributed ways of working with strategy, e.g. in connection with the notion of open innovation (chesbrough & appleyard 2007). haefliger et al. (2011) introduce a framework for research on social software and strategy based on three domains: strategy, technology and community. in contrast, the categories of the theoretical foundation of social ci are more specific and emphasize a socio-technical perspective. by introducing the notion of social ci, the term “social” is preferred ahead of a concept such as community, since it is important to distinguish explicitly between the individual behavior and the communal structure. razmerita et al. (2014) identifies how social networking media support both personal and collective knowledge management, which is related to the sociotechnical perspective of social ci. alternative research frameworks related to social ci can be found in a) the work by pawlowski et al. (2014), where sub-fields are distinguished based on research method; and (b) in the work by quoniam (2011), where competitive intelligence 2.0 is introduced as an umbrella term for various developments in the competitive intelligence field in relation to web 2.0 and social technology. in relation to the choice to use a sociotechnical approach for social ci, a taxonomy of approaches is presented by earl (2001) that makes distinctions between technocratic, economic and behavioral approaches to knowledge management. handzic (2011) studies empirically how social and technological factors advance in public administrative organization, using a sociotechnical approach. von krogh (2012) outlines a research agenda for strategic thinking, knowledge management and social technology in the form of six research questions. these questions are useful guidelines for future research related to social ci. in particular, two of the questions (4.5 and 4.6) deal with how the use of social technology will influence the competitive advantage of the firm and how it will affect the firm's boundaries (and thus indirectly the business model). there are also a number of results in favor of a socio-technical approach to be able to utilize social technology in a strategic process, see e.g. (denyer et al. 2011; leonardi & barley 2010; roblek et al. 2013; holtzblatt et al. 2013; saldanha & krishnan 2012; turban et al. 2011). simply inserting social technology into a process, in general or into a strategic process in particular, will not in itself change the work flow to become more open, social or participatory, cf. denyer et al. (2011). vuori has shown that the emergence of social media affects how knowledge sharing is done within ci processes (vuori 2011). her findings have also identified motivational factors and barriers related to willingness to share competitive knowledge, identifying obstacles and possibilities. from the perspective of social ci, sharing is one important aspect among several others, such as openness and peering. cross et al. (2006) investigated how social networking analysis can be used to improve the productiveness of the collaborations and the generated value with communities of practice. these techniques seem useful also in the context of social ci. kolfschoten et al. (2010) offers a method for collaboration engineering using socio-technical design patterns called thinklets. the thinklets approach seems like a promising complementary approach for the collaborative aspects of social ci, see e.g. azadegan et al. (2013). a related framework with an aim similar to the scif has been proposed recently by jin & bouthillier (2013). their proposal seems to be the closest of existing results that have been found for the scif. they emphasize the connection between collaboration and information sharing and access, which seems somewhat related to the work by vuori (2011) on knowledge sharing for ci. four general research questions are pointed out by jin & bouthillier (2013), and activity theory (at) is identified as the appropriate research method, which is one way to describe actions in sociotechnical systems, cf. mcmichael (1999). this means that the discussion of at in their context also seems relevant for the scif. based on at, jin & bouthillier (2013) introduce a model with four nodes that looks similar to the socio-technical perspectives of the scif (structure, behavior and technology). a fourth node holds a model of the ci cycle. in contrast, however, the scif contains six models, separating task and collaboration for each of the socio-technical perspectives. 8 2. theoretical foundation of social competitive intelligence the field of social ci consists of a combination of competences from, at least, five knowledge areas. an overview of the knowledge areas is shown in figure 1. the knowledge areas have been ordered in layers, where the lower layers are of a more general character and the upper layers are more specific to social ci. in the remainder of this section these five knowledge areas are presented in more detail. 2.1 socio-technical analysis and design on a fundamental level, the proposed scif is a framework for social ci that supports sociotechnical analysis and design of methods, services and tools (denoted as layer 1 of the theoretical foundation in figure 1). the sociotechnical viewpoint is important, since the use of it in social ci should always be done in alignment with the whole process, which 4 in the article, the term information is understood as data that is contextualized, categorized, calculated and condensed, where the altogether is a more complex type of requirement than technical or user interaction requirements. in the scif, the ci work process is seen as a particular form of socio-technical system (sts) where "social and technical aspects integrate into a higher level system with emergent properties", (whitworth 2009, page 4). in other words, an sts is a social system built on top of a technological base, where the technology is an essential integral part of the habitat for the human actors. in the context of ci, the technology is primarily it through which the human actors can discover, aggregate, refine, present and distribute information4. the systemic level of analysis of an sts is by definition communal, where focus is placed on how humans interact, which in turn determines the interaction between humans and technology (coiera 2007). therefore, the perspective on it within social ci will mainly be that it is a mediator of information between humans. context gives the data its meaning and purpose (davenport & prusak 2000). figure 1. areas that form the theoretical foundation for social ci and the scif. 9 brown & duguid (2000) calls for a process of socializing technology that is useful in the context of the scif. the term social it (also sometimes referred to as social technology) is a term used for the scif to denote it that is an appropriate mediator of information within the context of an sts and where humans are seen with the full complexity of social beings. finally, using the notion of an sts, the ci work process flow can be analyzed as an information system (is), or alternatively a work system (alter 2008). that is, the ci work process is seen as a system consisting of people, tools and information, with the purpose to collect, process and use information about the surrounding world. the is of ci work can be seen as a particular perspective on the sts in which the perspective is information-centric, which is relevant since ci is centered around the handling of information and its mediation that is meaningful for the organization. presents a conceptual model for sociotechnical analysis of ci processes that identifies three mutually interdependent perspectives: structure (s), behavior (b) and technology (t). the model, referred to as the sbt perspectives model, can be seen as a slight generalization of the information systems research model which uses the perspectives people, organizations, technology (hevner et al. 2004, figure 2, p. 78). another related notion is the multiple perspective model, cf. mitroff & lindstone (1993, e.g. table 6.1). it is important to note that the (social) structure consists of social networks where humans are individuals each with complex unique (social) behavior. collective structure between humans emerges as a consequence of their interactions and relations together. behavior and structure form a dual human aspect which is mutually 5 in this article, the term knowledge is understood as “a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new interdependent with technology, forming the duality of the sts. it may also be practical to divide the perspectives further, but such distinction is not needed at this point for social ci. for example, technology can be further divided into technology for the individual and the collective, see e.g. davenport (2005). another possible refinement is to focus explicitly on information and information processing in the technology component, see e.g. jin & bouthillier (2013). the presented research and the scif follow the scientific methodology of design science that seeks to "extend the boundaries of human and organizational capabilities by creating new and innovative artifacts" (hevner et al. 2004; herbert 1978; hevner & chatterjee 2010). thus, the purpose of the scif is not that of behavioral science to "explain or predict human or organizational behavior" – instead the focus is primarily intended as a basis for analysis and design of useful work methods, services and tools for social ci. 2.2 characteristics of knowledge work according to many researchers, including drucker, we have in recent decades entered a new era where knowledge5 has become the new basic economic resource that creates value (drucker 1993). organizations are relying more and more on systematic knowledge creation and learning as a key asset for continuous innovation (nonaka & takeychi 1995). the increased importance of knowledge and learning can be seen, for example, during the last twenty years in the rapid growth of new knowledge-centric academic disciplines such as the fields of knowledge management and organizational learning where "knowledge is applied to knowledge" (drucker 1993, p. 40), see e.g. easterby-smith et (2011); north & kumta (2014). characteristic for knowledge work is that it is less structured than administrative and production work (davenport 2005, p. 15). its exploratory nature means that knowledge work typically has inputs and outputs which are less well defined, and information is less targeted. instead the main purpose of knowledge work is rather to make sense of an unclear situation, interpret conflicting aspects and increase general understanding of the experiences and information.” (davenport & prusak 2000). moreover, the term knowledge work is defined as “work with the primary purpose to create, distribute or apply knowledge” (davenport 2005, p. 10). figure 2 the socio-technical sbt perspectives model. the perspectives structure, behavior and technology are mutually dependent in socio-technical analysis and design. 10 phenomena at hand (brown & duguid 2000). davenport (2005) points out the following basic principles of knowledge work: knowledge workers like autonomy; detailed step-by-step processes are less valuable; knowledge workers usually have good reasons for doing what they do; commitment matters; and, knowledge workers value their knowledge; they do not share it easily. an implication of this is, according to davenport, that knowledge workers cannot be "managed" in the traditional way. according to drucker (1993, p. 51) the organization of knowledge work is a destabilizer, an organization that is built for change – and continuous innovation. drucker claims that the knowledge-based organization must have three practices that are fueled by systematic knowledge creation: continuous improvement, ability to exploit earlier successes, and systematic innovation. however, as davenport (2005) points out, not all knowledge work is equal, and it makes sense to place efforts of improvement and interventions to work that are most expensive first. davenport uses two dimensions to distinguish the level of complexity of the knowledge work: judgment and collaboration, which is illustrated in figure 3. from this viewpoint, the knowledge work that should be focused on the most is work combining advanced forms of judgment and collaboration. this clearly motivates why a socio-technical methodology is valuable for social ci, which combines strategic judgment and a collaborative work model in such an advanced way. davenport (2005, p. 66-67) also describes the collaboration worker as "the most difficult to address in traditional process terms". similar to expert workers, collaboration workers prefer to work with high level guidelines only, and it is difficult to structure the format of their work. instilling some form of customer-orientation or a sense of urgency, are suggestions of intervention approaches (rather than detailed process flow charts) given by davenport. moreover, as pointed out by davenport, it is still unusual that work of this category is fully mediated and structured by a computer. this is also a motivation for the scif – to contribute with new and better tools for the collaborative knowledge workers of social ci. davenport points out two forms of it-tools for the collaborative work: knowledge repositories and collaborative aids. however, he emphasizes that such tools must be used voluntarily. the more unstructured and collaborative the work is, the harder it is to foresee and thus build knowledge repositories in advance that support the current situation. instead information is typically sought in multiple ways and using multiple channels. instead, the collaborative workers need time and support to seek and share knowledge from various different sources and repositories (davenport 2005, p. 91). 2.3 the networking work model a combination of the internet, cheap computers, web-based software, open-source projects such as linux or apache and publicly available information sources such as wikipedia are mixing together to dramatically reduce the transaction costs of doing work beyond the traditional hierarchical organizational structures. the new tools have made new ways of collaborating possible. malone (2004) discusses how general developments in it and communication technology have drastically lowered the cost of communication which has profound implications on how we can organize work. new more decentralized work models, utilizing a higher information sharing density, have become realistic choices. one important gain of a more decentralized work model is that larger groups of people can be directly involved in decision-making that matters to them, with the gain of increased individual freedom (malone 2004). from the perspective of the organization a main advantage is increased connectedness between workers and the surrounding world, cf. gray (2012). in particular, the increased connectedness between the organization and the surrounding world has become crucial since today's markets often follow a servicedominant logic where the generated value-inuse is sensitive to the customer's situation or preference (vargo & lusch 2004). using new social technology, people have developed new behaviors and new skills. the figure 3 categorization of knowledge work using the two dimensions: complexity of task and interdependence. 11 society is thereby being transformed into new forms of social spaces and structures where people are connected and collaborate in new ways and on a massive scale (tapscott & williams 2008). according to tapscott & williams (2008), the business logic in this new digital economy follows the laws of “wikinomics”, which are based on four powerful principles of mass collaboration: openness, peering, sharing and acting globally. internet and social technology are in this sense generalpurpose technologies and applying the principles of wikinomics are potentially enablers of complementary innovations and growth, cf. brynjolfsson & hitt (2000). the decentralization of work implies a shift in focus for management, from models based on command-and-control to models based on coordinate-and-cultivate (malone 2004). on a principal level decentralization can be seen as a shift in the perspective from push to pull (siegel 2009; anderson 2004; hagel iii et al. 2010). in a highly connected situation with an abundance of information, the basic work operations must by necessity be that of "pull" – by information customization ("only to the right persons") and goal-directed ("only at the right time"), cf. shirky (2008). moreover, to be able to exploit the power of information abundance is to take advantage of the capability to keep massive amounts of information for specific situations, a phenomenon sometimes called the long tail ("scarce usage") of information, cf. anderson (2004). customization, goal-directedness and scarce usage are all variants of the operative work mode of pull. in the push-model (i.e. the command-and-control model), the basic metaphor is an information-processing machine. in its simplest form this becomes sequential phase-based filter architecture, a hierarchy, or a combination of these two models. in contrast, from the perspective of pull (i.e. the coordinate-and-cultivate model) the basic metaphor becomes an organism, cf. gray (2012). in its simplest form the organism can be seen as a network, which is living, dynamic, learning and adapting. the different work models are illustrated in figure 4. viewing the organization from the perspective of pull consequently also means a shift of focus to people rather than artifacts, such as documents and it-systems, in the models. in other words, the management models of the decentralized organization naturally become people-centered rather than artifact-centered, with a focus on co-creative ecosystems instead of product-centric producer-consumer chains (vargo & lusch 2008). decentralized knowledge-creating organizations can naturally be described in the form of social networks, i.e. network structures that take into account the full complexity of human nature. social networks facilitate analysis of knowledge-creation as a process where individuals and productivity are primarily driven by intrinsic motivators such as autonomy, mastery and purpose (pink 2009) and social rewards (cross & parker 2004), rather than driven by extrinsic or formal rules. in other words, from the perspective of pull, the focus should be placed primarily on the informal, or social, aspects of the organization of work. the development of new social networking technologies related to the internet, web 2.0 and social media make dramatically more figure 4 illustrations of the work models of command-and-control vs. coordinate-and-cultivate. 12 decentralized ways of working possible and desirable. these new technologies have created new great possibilities for how to organize work, and the choices made will have great impact on professional life. malone (2004) emphasizes the importance that decisions are not only economically sound but also consistent with deep human values in general. for example, the new social networking technology makes it possible to realize many of the promises of decentralization such as selforganization, self-management, individual empowerment, social emergence, democracy, participation, people-centeredness and so forth. however, to be able to utilize such new possibilities in the context of social ci, a sociotechnical perspective and work method seems both natural and necessary. the new social networking technology that is being developed within an organizational context has been jointly referred to as emergent social software platforms (essps) by mcafee (2006a). an organization that uses essps to pursue its goals is called enterprise 2.0. however, although enterprise 2.0 is defined in terms of its enabling technology the new phenomenon is actually a socio-technical phenomenon, which also involves new solutions for organizational and management levels in order to become useful. such new uses of social networking media in organizations enable the use of mass collaboration (bradley & mcdonald 2011; li & bernoff 2011). by mass collaboration, it is possible to form collaborative communities where large and more diverse groups of people can pursue a mutual purpose that creates value, for example by increased levels of transparency and participation. in this type of social organization, work is organized using collaborative communities that allow everyone along the value chain to create value together in new more decentralized ways (bradley & mcdonald 2011). 2.4 social learning community nonaka & takeychi (1995, p. 6), propose that success in a knowledge-creating company comes from understanding and utilizing the dynamic nature of the knowledge conversion process between tacit and explicit knowledge – “from outside to inside and back outside again in the form of new products, services or systems.” the main dimensions of such 6 seci stands for the conversions: socialization; externalization; combination; internalization. dynamics of knowledge conversion are the conversions between, on the one hand, tacit to explicit knowledge, and on the other hand the conversion of knowledge between the individual and the collective, creating the now well-known seci model6. brown & duguid (2000) also emphasize the importance of not oversimplifying the notion of information as an artifact or explicit coding that can be understood without understanding the full complexity of the social context. they point out that if it is not used in a proper way it can easily lead to solutions with less collaborative support for the individual, making their role more difficult, stressful and ineffective. brown & duguid (2000) conclude that although a welldefined overall view of organizational processes can be important, it cannot replace the importance of support for the informal and collaborative practice of the people who work in the processes and bring them to life, and this is especially true for knowledge-intensive work. hence, when designing new socio-technical solutions, the informal aspects of work practice, sociability and collective knowledge exchange are important factors that must be encountered and emphasized according to their analysis. according to the social learning theory of wenger (1998), people are social beings that construct their understanding from participation in practice within a group or organization, see e.g. wenger (1998, p. 4). in this sense, social learning cannot be avoided but is a ubiquitous part of everyday life and work. it takes place not only inside the minds of individuals but is also processes of participation and interaction. learning therefore becomes a relational activity in a social context, not simply an individual process of thought. the locus of social learning is the patterns of participation of the members of a group or organization, where the learning takes place (brandi & elkjaer 2009). wenger (1998) makes a useful distinction between participation and reification to describe the process of social learning in a community of practice, see figure 5 for details. a distinction related to push versus pull has also been made within the field of knowledge management where two schools of thought have been identified: the codification strategy (people-to-document) and the personalization strategy (people-to-people) (hansen et al. 13 1999). originally, these two strategies were placed as opposites and historically organizations have tended to favor one at the expense of the other (hansen et al. 1999). however, as argued by wegner using the terms participation and reification these two aspects are actually co-dependent, but care must be taken regarding exactly what should be codified and not (wenger 1998, pp. 264-265). moreover, wenger views "learning as the engine of practice" where communities of practice come together through learning in an open, emergent and informal process that negotiates its own meaning and identity, see wenger (1998, p. 96). from a social constructive point of view, knowledge thus becomes synonymous with the active process of knowing (brandi & elkjaer 2009). the active social knowledge can be said to leave and use codification footprints in media, e.g. articles, digital conversations and webinars used to cocreate, educate and generate social activity. however, social learning as a complete process of knowing can only be understood by focusing on human actors and social aspects of the sociotechnical system. 2.5 the strategic decision making process and the role of competitive analysis in a situation where competition on markets has become more open with continuous change, strategic thinking has become more important than ever before. understanding the forces that shape business competition is the first step towards deciding on a strategy (porter 2008). strategic decisions typically occur in elusive open-ended business situations with choices that are hard to define precisely (nutt & wilson 2010). to understand a problem of strategic nature normally requires an extensive interpretative analysis to gain understanding before generating a solution. there rarely exists one best solution, but several solutions which are typically trade-offs with different priorities. it is also usually difficult to predict how competitors and markets will evolve. strategic solutions are therefore typically at a high level, still full with ambiguity and uncertainty, even after systematic strategic analysis, cf. barney & hesterly (2012). the benefit of a strategic decision also typically comes with considerable risk. to handle this complexity, a systematic strategic process is needed. figure 6 illustrates a principal strategic management process in the form of a phase-based process, adapted from barney & hesterly (2012). by conducting an external analysis of the surrounding world, a firm identifies threats and opportunities in its competitive environment. the external analysis relates the external world with the mission and objectives of the firm, which together with an internal analysis results in decision basis for the strategic choice phase. the systematic process of research and assessment about external factors that could endanger or enhance a company's revenues and profits is also known as competitive intelligence, see e.g. murphy (2005); kahaner (1997); sharp (2009). in spite of the name, ci is not limited to competitor benchmarking but focuses on any external factor that can affect the ability of a firm. the ci professional gathers relevant information, turning raw data into actionable intelligence, where its significance and value comes from figure 5 participation and reification – two dual aspects of social learning in a community of practice. participation denotes the active process of social experience for members of a community of practice. reification denotes the process of producing artefacts. figure 6 a systematic strategic management process. 14 the results of the action taken. contributing to firm-wide ci is of course something that is relevant for any knowledge worker. however for ci to become efficient there is normally also a need for an individual or a group with the specific responsibility of ci and coordination of ci activities within the organization (murphy 2005). traditionally, two models with a focus on "command-and-control" for ci processes have been used: positioning ci as a functional unit and a phase-based process model for the ci-process, as illustrated in figure 7; see e.g. murphy (2005); bose (2008)7. the ci work process can be seen as a particular form of knowledge community, or community of practice. however, the process has a number of specific characteristics such as: a) a collection of well-defined objectives: the ci process should always work towards a collection of well-defined objectives in the form of analysis for strategic decision support. this contrasts the general notion of community of practice, where the overall and open-ended aim is to strengthen the competence of its members. in particular, this means that ci focuses on creating so-called actionable knowledge, i.e. b) knowledge that becomes a strategic resource, see e.g. drucker (1993, p. 42); carter (2014); (barney & hesterly 2012); hedin et al. (2011, pp. 49-61); sharp (2009, pp. 17-18). 7 the phases in the phase-based intelligence cycle exist in many variations around a similar theme. in the figure the phases originate from kahaner (1997) as a simple illustrative example of the c) a well-defined research process: ci consists of a research process with a number of well-defined steps or phases, each of which with tools and methods that support them. the ci research methods and tools are related to and build on those of other analytical research processes such as business administration, information science, media studies and general academic research. however, the methods and tools of ci have a specific focus on delivering strategic support; see e.g. håkansson & nelke (2015); hedin et al. (2011); murphy (2005); hamrefors (1999); bose (2008). d) analytic techniques for determining competitiveness: the techniques for competitive analysis come from general research in strategic management and competitive advantage (e.g. porter (1980); krogerus & tschäppeler (2008); barney & hesterly (2012)) but have also been further developed in ci literature (e.g. sharp (2009); murphy (2005); håkansson & nelke (2015)). the purpose of these techniques is to support how raw data and information can be turned into intelligence (i.e. actionable knowledge). e) a nuanced understanding of different types of information seeking, information behavior and information quality: ci centers on information – gathering, interpreting, analyzing and reporting. the end result of the ci process is some form of well-founded principles of a phase-based model only. for a more recent, but related phase-based process model for ci, see e.g. pellissier & nenzhelele (2013). figure 7 two models of command-and-control for ci. 15 analysis or recommendation that will be used as decision-support. ci relies on the rich tradition of media analysis from communication studies and information science when analyzing sources and content, see e.g. murphy (2005); håkansson & nelke (2015); case (2012). 2.6 theoretical implications for social ci the introduction of organization models that rely on social technology creates new opportunities for how ci work processes can be designed and integrated in the enterprise. however, for this to be possible new knowledge about this new role of ci in enterprise 2.0 and the kind of tools and services are needed. it is also clear that there are best practices that ci in enterprise 2.0 must learn from to be successful, cf. li & bernoff (2011); bradley & mcdonald (2011). on a conceptual level, the study of social ci and the scif contributes with knowledge about how to apply the ideas of enterprise 2.0 and essps in networking organizations. solutions based on the scif should be based on the five knowledge areas presented above and also synthesize new solutions by combining insights from them. as a first step, a new conceptual strategy called the peoplemedia-people8 strategy, which constitutes a human-centered and socio-technical viewpoint 8 the notion of media is used here in its most general sense and can be everything from face-to-face and signs on a wall, to webinars, on the social ci process, is introduced here and illustrated in figure 8. the new strategy generalizes and subsumes the two perspectives of personalization (peopleto-people) and codification (people-todocument) perspectives, which were discussed previously in section 2.3. in the people-media-people strategy the two (partial) viewpoints people-to-people and people-to-document are seen to complement each other with a focus on the dynamic transformational character of knowledge and media, in a way similar to nonaka & takeychi (1995); liebowitz (2012, p. 1). the two levels of the new strategy can be analyzed further using the dual notions of participation and reification, from the theory of communities of practice (wenger 1998). the proposed strategy suggests using a network approach to organize the ci process in an open and participatory fashion, based on the theory of network organization (discussed above in section 2.2). the network approach relies to a larger extent on emergent strategies and strategic experiments, which mean that ci professionals and other contributors are needed in various positions in connection with the social ci work process. for this to be possible, an approach such as the people-media-people strategy is required, which contrasts the traditional view, where strategic choices have been seen as the exclusive responsibility of senior executives. in an open strategy process, value for the firm is also to a larger extent created by internet searches, knowledge bases and smart phone apps, cf. mcluhan (1964). figure 8 the people-media-people strategy, which is a part of the theoretical foundation of the scif. 16 external resources not owned by the firm in question, such as co-creating customers, innovation communities and surrounding business ecosystems (chesbrough & appleyard 2007). in such an open context, the role of social ci is also naturally seen as a more open social knowledge creating process, or a form of learning community, based on theories of social learning (discussed in section 2.3). for tools and techniques of the technical media level, these are naturally based on a combination of enterprise 2.0 (mcaffe 2009) and existing tools specialized for ci, which are a necessary core of any ci process. this new hybrid must avoid making tools for experts only. moreover, the tools should focus on the collaboration worker (davenport, 2005). successful examples exist within social technology that social ci can learn from, for example the wikipedia community that also has proved to be competitive with its traditional alternative encyclopedia britannica (jemielniak 2014; giles 2005). 3. tendencies in the area of competative intelligence the expert interviews have been performed in an exploratory semi-structured way with the intent to let different experts freely express what they believe are the main issues of ci as we entered the age of social networking and social it. the questions were open-ended and discussed challenges and possibilities of ci in general, and the networking organization and social ci were not emphasized by the interviewer. the data material has here been structured in terms of eight tendencies of ci, as shown in figure 9. the tendencies have been identified after the interviews, as a way to organize similar remarks in the material. in the remainder of this section, we will summarize the views of the experts for each tendency. 3.1 tendency 1: changing business models for ci one theme discussed by several experts was how the business situation for the ci industry is changing, similar to how the business models of the media industry in general are changing. one observation was that in the past, there has been a close relationship between "regular" news media and ci, where public news has been one of the primary sources for the ci companies. traditionally, these sources had a content-oriented business model based on "paid content" (often a mixture of paid content and advertising), which has also been discussed by e.g. (wirtz et al. 2010). one expert commented that such changes have ripple effects along the value-chain leading to how ci services are delivered and what are suitable business models. several interviewed ci experts pointed out that it is not possible to know exactly what will be working business models and market structures for ci companies in the future, but what was considered certain was that they will change in some way. a recurring theme in the interviews was also a concern with how new competition from “general internet services” with a strong endconsumer orientation, such as google and facebook would affect the ci industry. (no expert offered a more exact description of what exactly the competing industries were here, and perhaps the situation is somewhat blurred at present.) the “general internet services” were pointed out to have features and functionalities that are partly overlapping with those services from the ci industry, as well as those of traditional media. in contrast to traditional media, the “general internet services” have business models that can be said to be context-oriented rather than contentoriented, i.e. their primary value lies in structuring and accessing information that already exists, rather than creating new content (see e.g. wirtz et al. (2010)), which is similar to how many ci firms operate as well. one observation was that the ci industry, therefore, needs to look more at how to connect and refine knowledge generated from general internet services instead of traditional media. one of the experts emphasized how this also means that the ci industry may inherit the uncertainty that surrounds the rapidly evolving business models of internet-oriented information services that often lack a clear focus and are highly sensitive to change even figure 9 eight tendencies of the area of ci identified in the expert interviews. 17 for larger companies. another expert noted that since ci services are relatively expensive services they need to add substantial value "on top" of the internet-oriented information services to be able to motivate their value for their customers. for example, new ci services could add value by offering different mixtures of more extensive service solutions, adding more analytica l power, offering more advanced forms of filtering of information or by making the collaborative and social dimensions of the tools more advanced. several experts observed that on the one hand the market need for advanced information services has increased, but on the other hand so has the competition, where different kinds of services compete on a new internet-based global market, including actors such as google and facebook. the challenge in this new situation is how to reach out and connect to the new users and customers on this market. the ci providers must find ways to explain to their future customers what added value their solutions give and how they are intended to use their products, on this new market, was another observation. a related discussion with some of the experts was seen in the fact that on this global market many different notions exist and it can be hard to understand the differences for the non-expert, such as the notions of competitive intelligence, business intelligence, knowledge management and market intelligence and so forth. it was also pointed out that when users of the intelligence services are no longer “ci specialists”, it is crucial that they are simple to use and it is easy to understand the benefits. 3.2 tendency 2: ci in networking organizations several of the interviewed ci experts noted that the need for handling information flows is infinitely large today due to the increased availability of information (which is similar to the view taken in e.g. manyika et al. (2011)). this development was observed to be driven by a combination of increased market-orientation and technological innovation that offer both opportunities and challenges for the ci services. one expert observed that traditionally the ci analysts have often worked as single selfgoverned experts or in a small group of specialists. they worked exclusively with ci sources and other related database and newsbased services for expert usage. typically, they have either delivered tailored analysis for management decision-support, or competence support for the whole firm in the forms of information portals or pamphlets. the question is how that work role will change in the networked organization. when the company is no longer divided into clear-cut functions but works more in interdisciplinary teams, then the ci services for that environment must also become more general-purpose to fit that situation. at the same time, it was noted that the worker in a decentralized knowledgeintensive organization is accustomed to manage large flows of information. moreover, it was noted that information about the surrounding business environment of an organization is useful in many different places, roles and situations in the organization. today, it seems that competitive intelligence as a specialist profession is mostly self-taught, at least in sweden, according to one of the experts. there are some minor courses or education, but the initiatives lack a larger clear professional context and clear academic identity. according to the expert, this reflects the fact that ci is largely a work behavior that all professionals should have in a knowledge-intensive organization. the ci industry and earlier ci scholars made the distinction between spontaneous and organized ci, cf. hamrefors (1999). the point made by several ci service providers has been that they focus on organized ci only. this seems to contradict the fact that most companies focus on spontaneous, "self-taught" ci according to one expert. it was suggested that perhaps the distinction between spontaneous vs. organized ci needs to be revisited, in the light of the networked organization, and, thus, any tool or service that is strictly specialized in nature will not fully fit the new needs. at the same time, according to several of the interviewed experts, the use of networked work methods is still distant for many larger organizations today. well-established larger industrial enterprises have close ties between their traditional way of working and their core business idea. for these organizations, it seems unclear how they can become networked without challenging their core business values at the same time, as was noted by two of the interviewed experts. interestingly, it was also pointed out in the interviews that contracts with major it enterprise service-providers were thought to be an impeding factor in the transformation to networks. this goes against the idea that it in general is a progressive force in the context of organizational development. 18 in this case, it seems that the internetcentered information providers are considered progressive, but traditional enterprise it providers are considered impeding. an interesting question here is what more “progressive” alternatives of ci services would look like, if this is true. can ci solutions and services be a key driving force of growth and innovation that transforms the way organizations work as well? another discussion centered on how to help large companies that have realized that they are "stuck" in an industrial way of working, and provides ci solutions, perhaps in combination with other organizational development solutions, that would help these companies transform into more networked ways of working. ci solutions are typically a mixture of automatic tools and the services of human ci analysts. several of the interviewed ci experts noted how increased automation was a driving force that "pushed" the human experts towards more advanced forms of analysis work. according to some of the interviewed experts, it is unclear exactly what will be the professional role of the ci analyst of the future, depending on which way the technological development goes. for example, will automatic text summarization become good enough so there is little need for humans to intervene at all, or will automatic tools only be used to empower the ci analyst when interpreting and analyzing a text? in other words, the understanding of how the boundaries between technology and human experts work will develop into an important part of the competence of the ci professional. in that sense, the ci professional needs to understand the socio-technical nature of ci, together with content creation and communication. 3.3 tendency 3: ci networking the details of the ci process can vary and external experts may not always have insight into them, according to several of the interviewed experts. however, the ci process was described by several of the interviewees as a chain of information refinement steps where the initial step is usually starting from public sources, such as daily press and trade journals. intermediate steps are typically done in specialized ci service organizations that aggregate and refine information relevant for different industries or sectors. the final steps are taken within the user-organization that will also use the final information. one of the observations was that larger userorganizations often have their own specialized analysts that further aggregate and refine the information. the final analysis, that turns knowledge into action, is typically done by the end-receivers of the information in the business processes. another observation was that the ci analysis chain is mainly motivated by efficiency, but another important factor is to guarantee high quality. an interviewed expert noted that when the automatic information seeking tools become more powerful the ci analysis chain will be affected in several ways. one suggestion was that the chain may be shortened, where some intermediate steps in the chain can be skipped. for example, the need for internal expert analysts in the user-organization may not always be needed anymore. instead, information may go more directly from external sources to an end-receiver in the core business process, the interviewed expert noted. similarly, studies in social networks of research and development also suggest that the role of a single "gatekeeper" is transformed into a network of specialists (whelan et al. 2013). one interviewed expert noted that the role of the ci analyst may have to evolve when automatic solutions become more advanced. one suggested adjustment on the human side of ci is to improve the quality of the analysis by adding more insight into it. for this to be possible the analyst must broaden or deepen the analysis somehow. the interviewed expert suggested that the ci analyst must become more of a domain expert as well. another suggested alternative was to increase the complexity of the analysis and for example look at more variables and larger data sets. a third suggested alternative by an interviewed expert was to use more advanced forms of collaboration during analysis, in order to make the analysis richer and more multidisciplinary. at some point, migrating to a networked work model is probably the way to handle the increasing complexity of the analysis work, which is also what is indicated in whelan et al. (2013). 3.4 tendency 4: quality assurance of ci content one way to add value to the ci process is to work with information quality (eppler 2006) in order to systematically raise the level of insight in the analysis and also make the level explicit to the receiving party. this type of work seems 19 to be at an early phase, at least in sweden, according to one interviewed expert. content analysis of ci is analysis of texts and other media, which is related to methodology from social sciences and humanities. however, the quality of ci should be determined based on its quality for business analysis purposes, similar to business intelligence (bi). for bi it is natural to use the notion of data quality systems since data is normally numerical, where the quality measures can be easily automated. ci is different from bi since it deals mainly with text and media, i.e. with so-called "unstructured" information, or information in free form. it deals with information, in the sense that it is a contextual, coherent message of "potential knowledge" (eppler 2006, p 22). but even though the content is in free form and its interpretation requires human thought, the analysis includes both qualitative and quantitative approaches, similar to other kinds of methods for media analysis and media evaluation. one of the interviewed experts raised an open-ended question about how exactly this kind of quality assurance should be done, and how it could be communicated in a transparent and understandable way to the receiving party (that may not be a specialized ci analyst). it can also be noted here that to use more rigid quality management systems in the domain of ci and knowledge management "is a dangerous undertaking" due to the unpredictability of knowledge work (eppler 2006, p. 13). 3.5 tendency 5: integration of ci content the typical knowledge worker that uses ci has many information processing systems they work with. to define and redefine the position and role of a ci service in such an environment is an important question, according to several interviewed experts. for the user of information, it is important to understand the basic function, or added value, of the ci service and how can it be connected with other streams of information. the needs and requirements for tools that can handle information integration is highly dependent on the level of it sophistication in the organization. today this level can vary substantially depending on industry and the kind of organizational model that is used. however, several of the interviewed experts pointed out that these issues of integration of services are needed and important. in particular, there is a demand for ci services to be able to connect to generalpurpose information systems in the enterprise, such as intranets and microsoft sharepoint. even though this is possible on a technical level, the solution is often not satisfactory. the general-purpose platforms often lack important functionality that is required to really take advantage of ci content, such as advanced search functions and metadata filtering mechanisms. information integration has increased in importance for a more networked organization, cf. grey (2012). the division in a more decentralized organization is more selforganized, continuously changing and informal. therefore, there is no way of knowing in advance who will need what information. however, the usages of social media services are still also poorly integrated in many organizations today, according to several of the interviewed experts. there was a belief of these interviewees that the integration will continue, but the exact way is still unclear. one tested alternative has been to introduce social enterprise software with similar functionality found online, but that has not worked well according to several experts. on the other hand, if employees start groups on external services, such as facebook, the information becomes even more scattered for the organization, which was another observed problem. 3.6 tendency 6: ci beyond enterprise 2.0 the basic principles of web 2 and social media are not really enough anymore, according to several interviewed experts. something beyond the vision of enterprise 2.0 (mcafee 2006) is needed, but exactly what was not clear to them. early attempts of enterprise 2.0 that simply introduced social software in organizations have not worked well in the experiences of these experts, which is supported also by e.g. li & bernoff (2011); bradley & mcdonald (2011). the problem is not new, earlier attempts with so-called groupware as well as earlier attempts of knowledge management systems show even more problems in their approach (koch 2008; levy 2009). it seems that solutions from enterprise 2.0 solve some of the problems of earlier methods, but perhaps not all. there seems to be a gap between technical feasibility and the social requirements that may simply be too large for certain organizations (ackerman 2000). 20 organizations are on different levels of maturity with regards to both ci and the usage of advanced social technology, according to several interviewed experts. it seems that some organizations may be advanced in one of two ways, either in their usage of ci analysis in their work (cf. hedin et al. (2011)), or in their use of social technology (cf. li & bernoff (2011)). however, it still seems uncommon that an organization is advanced in both ways at the same time, at least from the experience of some of the interviewed experts. this indicates that ways to combine advanced ci methods and enterprise 2.0 is still an open question. another phenomenon that was noted by the interviewed experts was that organizations that are not so technically advanced are in a similar situation today that, for example, telecommunication companies were in the 1990s. but the difference is that the technological tools they require are more mature today, whereas the tools in the 1990s were tailored by the organizations themselves. to guide these organizations forward, more support is needed on the technical side and the solutions must be made simpler and more attractive. on the one hand, the clients cannot be assumed to be that visionary concerning technological choices, here they need finished solutions. on the other hand, these same organizations may be mature when it comes to knowledge work and ci competence, either organized or spontaneous, compared to the technologically advanced industries. 3.7 tendency 7: human experience of ci services and tools the fact that ci services and tools simply "function well" does not give it a competitive edge anymore, according to several of the interviewed experts. the basic technological problem is in a sense solved according to the experts, and most providers build their solutions on these solutions. what is still not solved is how to design the experience for ci, cf. forlizzi & battarbee (2004). attention is a scarce resource for ci professionals today, as one interviewed expert pointed out. the way to require minimal effort is to have an experience design that gives instant and non-intrusive access to information in a way that is attractive. in a similar way, the value a ci service gives to an organization must be quickly understandable, for it to get any attention at all in the first place. it is a daunting task to make productivity tools such as ci tools that demonstrates direct value. tools that give the organization as a whole value, rather than the individual, can have values that are not instant but pay off in the long run. typical long term assets can lead to a better reuse of knowledge, better collaboration, better use of experts in the organization and so forth. however, neither of these organizational assets are "instant" in nature. it will be crucial to bridge this and make these values explicit somehow, according to one interviewed expert. the expected experience of the users of ci services is often influenced by their usage of consumer services such as google and facebook, according to several of the interviewed experts. an observation was that this places the bar fairly high for experience design of specialized ci tools such as knowledge portals. in general, for all knowledge work, this is problematic because it is expensive and solutions risk being specific for a particular organization, cf. (davenport 2005). furthermore, it can be hard to get permission to study ci processes at all, due to their often sensitive strategic nature according to some of the experts. users also need to understand that the consumer services online and tools within an organization have different purposes and functionality, something that is not obvious to the non-technical user. organizational systems also have a hard time keeping up with updates of systems and hardware in the same way as the individual consumer. this limits the technical possibilities in using cutting-edge technology such as the latest graphical code libraries for web browsers, according to some of the interviewed experts. younger people also tend to come with new behavior and are less patient with poor design experience, according to several of the interviewed experts. no matter what the order from the superior has been, they tend to use their own consumer services to solve problems instantly instead of using the organizational solutions. exactly what this change stands for and its universality is a question for debate, but in practice it seems to be a problem that needs to be dealt with somehow. on a positive note, the same interviewed experts said that they learn a lot from looking at how younger people use technology, both in companies and in their private lives. in that sense, the consumer market seems to lead the way when it comes to experience design, and productivity tools follow, whereas at an earlier stage when the focus was on technical issues, the roles 21 were reversed. this seems to fundamentally change the situation for the development of specialized tools such as for the ci industry. 3.8 tendency 8: more ci information and more natural formats the amount of information that the ci professional needs to handle seems to continue to increase, according to several interviewed experts. in general, this increase of information is "unstructured" in the sense that it comes from many different sources, formats and has different types of content. however, from a human and social perspective it is rather that the new formats are more natural, a perspective we prefer (ackerman 2000). this naturalness is of particular importance in relation to collaborative work, as pointed out by kock (2004). today, many organizations have to use substantial effort to handle the increase of information volumes (manyika et al. 2011). for the ci professional, increased text volumes means less time to spend on each information item, on average. so, there is an increasing need for succinct material in "small chunks", according to one interviewed expert. another way is to rely more on advanced forms of metadata or other structures that classify and filter material for the ci professional. a general question is how the value of information can be improved on the level of the individual, as one interviewed expert noted. this relates to questions of how to avoid information overload (eppler & mengis 2003). the increase of information is also a consequence of increase digitalization in general, cf. castells (2010). this means that more information is easily accessible as a basis for decisions. the goal of ci is to understand the surrounding world of the organization as much as possible. with more information available in digital form, it should be possible to further increase the level of predictive accuracy in the ci analysis. due to the amount of information, new solutions will definitely have to rely on advanced forms of automatic data analysis combined with expertise in data science (davenport 2014). 4. extracting socio-technical themes for social ci the tendencies identified above can (and should) be used as a basis for any further development of social ci. to make the expert knowledge more manageable, the tendencies are viewed here as a general discussion about socio-technical design requirements concerning the ci work process, which is viewed as an sts. as pointed out by whitworth (2009), requirements can exist on several levels. in the context of social ci, the chosen level for requirements is the socio-technical level using the sbt perspectives model, according to the discussion in section 2.1. moreover, since the tendencies are fairly general, they are not so easily seen as design requirements as they are discussed above. therefore, in order to extract the most relevant parts and make the data material more succinct, six so-called socio-technical themes have been deduced and selected from the data material, two for each perspective in the sbt perspectives model, as illustrated in figure 10. each theme constitutes a cluster of relevant socio-technical design requirements within the context of social ci. the identified sociotechnical themes can be described and motivated as follows: a) network coordination: using a ci network means that we deliberately minimize hierarchical control. however, a key to successful mass collaboration is still to have an effective coordination of the network, see e.g. bradley & mcdonald (2011). therefore, network coordination is critical for the social ci approach. in particular, the style of coordination of a ci network must balance the need to work in a selfmanaged style, with the demands on the ci work process to deliver results in accordance with its given tasks. b) collaborative analysis: collaborative analysis is a way to both speed up the analysis part of the ci work process but also obtain results on levels not possible using solitary ci experts. collaborative analysis may include using techniques such as brainstorms, seminars, work figure 10 socio-technical themes structured using the sbt perspectives model. 22 sessions, feedback, peer-reviewing and so forth. moreover, when the topic covered is getting more complex, mixing expert capacities of a multidisciplinary team can potentially generate insights on a higher level than single discipline teams can achieve. c) creative thinking: the reason why social learning and community-based techniques are so useful for more advanced forms of knowledge work is because they support creative thinking. however, for this to work the individual must also be motivated and prepared to focus on creative thinking. there are various techniques that could be used here. common to them is the fact that they do emphasize divergent and lateral thinking, as well as using means other than those that are strictly intellectual such as beliefs, values, emotions and narratives. in ci this is useful when we want to make original contributions in all aspects of ci such as making interpretations, drawing consequences, or arriving at a novel analysis. d) visual communication: visual techniques are one of the main tools to communicate complex information and transfer holistic awareness of a nonlinear situation. this theme emphasizes education and facilitation so people in the ci community can communicate visually with each other. it is important both to be able to create messages visually and to receive and understand visual presentations of information and social data. e) engagement: a key to creating a wellfunctioning ci network is to create a social and technical platform that engages people for them to join and contribute. the voluntary character of the networking work style puts demands on making the ci platforms attractive, easy-to-use and to include instant intrinsic and extrinsic reward systems. f) complex information: to be able to handle increasingly more complex 9 a more detailed discussion of the notion of value is outside the scope of this article. however, we refer to a good discussion about value-in-use and co-created value in the context of service-dominant logic (vargo & lusch 2004) and the importance of human value in the context of decentralized work (malone 2004, pp. 170-182). whitworth information is and will continue to be an important aspect of the ci work process. the increase in complexity comes in various forms: the amount of available data is increasing ("big data"), the available data is unstructured ("noise"), the covered topics are becoming more advanced, the topics are changing more rapidly, and world changes are becoming harder to foresee, making the "unknown unknowns" more important to look for. moreover, the media format of information is no longer restricted to numbers or text only, but comes also in the forms of photos, movies and sound and other formats closer to real life. the themes are derived from the tendencies identified in the expert interviews. hence, these themes are not the only possibilities, and it is expected that others can be added as well. in particular, when customer organizations using ci are studied in more detail, new themes will most likely occur. however, the notion of socio-technical requirement themes is likely to be useful there as well. 5. socio-technical values of social competitive intelligence the socio-technical themes are support for which areas of functionality the socio-technical design should focus on, based on the empirical experiences of the experts. however, the theoretical foundation of social ci points to other, more general, related aspects that social ci needs to be considered as well. in order to facilitate using theoretical results in sociotechnical analysis and design, a coherent format is called socio-technical values9. these values contain value propositions intended to capture basic human needs and systemic benefits mainly from a utility perspective. the socio-technical values are typically related to needs (or desires) on a social level, useful for both socio-technical analysis and design. three areas of study have been selected as the basis for extraction of the socio-technical values of social ci, with one study for each of the perspectives of the sbt perspectives model. the three selected areas of study are collective intelligence, the networking individual and (2009) uses the notion of socio-technical performance requirements in the wosp system, but makes no explicit reference to the notion of human values. another perspective on human value in relation to computing are questions of moral and ethics, which are not (so much) in focus for social ci at this point (friedman et al. 2008). 23 social it, which is illustrated in figure 11. the remainder of this section briefly recaptures the relevant parts of the theories and formulate a map of socio-technical values for social ci. for a more detailed description of the areas see the appendix. collective intelligence. loosely organized groups can work together in surprisingly effective ways when given suitable networked support. this phenomenon can be described in terms of collective intelligence10. malone et al. (2010) have identified a relatively small set of building blocks, or genes that are combined and recombined to support collective intelligence. similarly, bradley & mcdonald (2011) have investigated the new way of working that comes with the use of some form of social technology in the organization. bradley & mcdonald (2011, figure 4-1, pp. 41-42) introduce a collection of characteristics where collective intelligence (they use the term community collaboration) will be most beneficial to use. the socio-technical values of social ci for the structure perspective use a combination of the genomes and genes of malone et al. (2010) and the characteristics for community collaboration by bradley & mcdonald (2011). the networking individual. tapscott (2009) (and others), have studied the net generation born between 1977 and 1997 that have "grown up digital" and found that they have distinctly new behaviors where social technology is an important factor (tapscott 2009; palfrey & gasser 2008). these new behaviors can actually be seen more or less with most people today, so we will use tapscott's result as an indicator of a more general change in behavior triggered by the fact that social technology has become a general purpose technology. of course, one should also be careful not to oversimplify the complexity of new behavior 10 collective intelligence is closely related to the notions of mass collaboration (tapscott & williams 2008), enterprise 2.0 (mcafee 2006b) or crowd sourcing (doan et al. 2011). we prefer the term (jones et al. 2010) but there are some interesting indicators of how the ci process should be adapted to follow the new behaviors related to social technology. tapscott has described these new behaviors in terms of eight new norms, which summarize behaviors that are different compared to earlier generations. these eight norms have been selected for the socio-technical values of the behavior of social ci. social it. it seems that computing reinvents itself approximately once each decade, following technological development. at each stage the complexity of the system seems to push the level of analysis upwards. according to whitworth (2009), the latest stage is a move from the level of human-computer interaction to the social computing level, in other words, to the level of the socio-technical systems, and thus social it. one way to approach socio-technical design and social it is to understand it in the form of architectural patterns of social spaces (wodtke & govella 2009). patterns are systematic ways to describe problems or needs that occur over and over again, followed by a general solution to such situations (alexander et al. 1977). in particular, wenger (1998, pp. 225-240, figure 10.3) describes how identity and belonging are important aspects of learning. the sociotechnical values of the technology perspective have been extracted from a patterns catalog for social interfaces (crumlish & malone 2009) combined with the principles of the learning architecture from wenger (1998). 5.1 extracting a socio-technical value map for social ci socio-technical values are intended to be used to capture specific needs or wanted benefits of individuals or the community. similar to the socio-technical themes, the values capture clusters of possible requirements of an sts. one way to look at socio-technical values is in the form of relevant and generic patterns of sts properties, similar to how the notion of (design) patterns for design solutions (alexander et al. 1977). the socio-technical values reported in the surveyed literature have, in fact, all evolved in an emergent fashion similar to the emergence of (design) patterns. moreover, the socio-technical values form a kind of “language” that becomes a common ground for the socio-technical systems in collective intelligence, since it focuses explicitly on the notion of "intelligence" that comes from various forms of collaboration, emergent or planned. figure 11 the three areas of study for socio-technical values related to the sbt perspectives model. 24 general, and social ci in particular. here, such a language is called a socio-technical value map11. a socio-technical value map for social ci has been extracted from the selected studies discussed previously in this section and is shown in figure 12. the collection of sociotechnical values in the map are divided using the sbt perspectives model. in general, sociotechnical values can be any kind of relevant characteristic of the studied system within its three dimensions, some are useful as a basis for specific socio-technical requirements while others are more holistic in nature. the sociotechnical value map is intended to be used to systematically understand the underlying properties and forces that generate the sociotechnical systems. the specific values have been discussed in relation to the selected studies above, and hence will not be discussed further here. 6. modeling method for social competitive intelligence generally, conceptual modeling helps to structure requirements in order to reduce complexity and thereby make them easier to understand, discuss and realize. the requirements and models of a system must follow the level of analysis of the modeled system. on the socio-technical level, added requirements on the social (i.e. communal) level must be handled well (whitworth 2009). six socio-technical models are suggested for social ci, as illustrated in figure 13. 11 the corresponding notion for patterns is a pattern language (alexander et al. 1977). malone et al. (2010) uses the notions of genes the modeling structure has been deduced from the theoretical foundation of social ci and insights from the expert interviews, and can be described and motivated as follows: a) community model: besides being a task-driven work process, the ci network is also a collaborative community that must be coordinated and cultivated in terms of meetings, interactions and relations. various contributions exist for how to manage a community, for details see e.g. bradley & mcdonald (2011); li & bernoff (2011); bacon (2012). a community model should at a minimum contain a purpose statement, a purpose road map and schedules for coordination and community activities. b) process model: the ci network has a specific task-related purpose. in this sense, the ci network can also be seen as a form of loosely organized work process, but the purpose and the result of the ci work process must be carefully and clearly stated. this means that a well-defined ci-process must be defined that facilitates, makes the results predictable and assures quality in a suitable way. c) role model: for people in the ci network, community roles can be identified, both formal and informal. a basic categorization of online community roles is: moderators and mediators, professionals, general participants, provocateurs, and lurkers (preece, 2000). in the context of social ci this could, for example, be: ci coordinators, ci professionals, and genomes for collective intelligence, but we prefer a less metaphorical notion in the context of social ci. figure 12 a socio-technical value map for social ci. the values are sorted using the bst perspectives and the selected areas of study. within each perspective they have been further organized in groups (the bold face headings in the values column). figure 13 six socio-technical models for social ci related to the sbt perspectives. 25 participants, external experts and information users. furthermore, a ci community as an enterprise is normally connected physically as well as a virtually. d) work phase model: the ci work process consists of a series of steps that are often referred to as the intelligence cycle. a typical series of phases are: plan and prioritize, capture, manage, analyze and communicate and follow-up. exactly how these phases are implemented depends on the purpose of the ci operations, such as if they are ad hoc studies, regular processes or continuous (specific or unspecific) scanning, see e.g. håkansson & nelke (2015). for social ci, they will probably often be composed in partially new ways. e) social features model: the social features model is a model over what kind of social functionality should be supported by the technological tools and platforms. this can, for example, consist of information architecture patterns for social spaces. it is important to note that this model is only indirectly related to the task model. instead the main focus here is on how to support users as social beings. that is, social features are various mechanisms that support meeting, interaction and relations between people in the community. f) information model: an information model is required for social ci and describes what kind of information formats, flows, sources and metadata the process uses. there are many variations but the information model can, for example, include a world model (e.g. actors, topics, events and trends), a content-related model (e.g. authors, source and content classifications), social data (e.g. rating and comments), a source list, links and reference mappings, personalization rules and a controlled vocabulary. the proposed modeling method of social ci is that these models are used in combination with insights and analysis based on the sociotechnical themes and the socio-technical value map. a suggested basic work method for modeling of a ci sts is: 1. select and study how socio-technical themes apply to the sts. 2. create socio-technical models for the sts, with a focus on selected themes. 3. refine the socio-technical models until they agree with the corresponding socio-technical values. 4. (optional design stage) create prototypes or live implementations of the sts based on/integrated with the models. evaluate the relevance of the socio-technical models of the sts. update, refine and reiterate steps 1-4 until the evaluation is satisfactory, or until requirements change. the modeling method can be used either for analysis only, or for analysis and design (using the optional design step 4). an illustration of the modeling method of the scif is shown in figure 14. the modeling method is intended to be used in various ways as a conceptual tool for analysis and design of ci stss, where relevant parts of the framework can be used as needed. the relation between models and design prototypes can be more or less integrated, where prototypes and artifacts can be seen as a part of the model or not. there can also be a close relationship between the behavior and structural model in practice. however, it is important to separate the two social aspects in some way, similar to how the perspectives are separated in a social network analysis for good reasons, cf. cross et al. (2006). a strength of the method is the close sociotechnical connection between, on the one hand, the models, and, on the other, the theoretical and empirical findings. thereby, the sociotechnical values and requirements naturally become a point of focus for the whole analysis and design process. in this way the modeling is kept “on target” and focuses on aspects that are relevant from a socio-technical perspective. furthermore, the scif is a conceptual toolkit that leaves maximal flexibility which allows for adaption and tailored usage, which is important on the socio-technical level to handle vagueness and complexity of requirements. 7. conclusions in this article, a new notion called social ci has been introduced. social ci identifies a new knowledge and research area around methods 26 and tools for competitive intelligence in the networking organization. during this investigation it has become clear how the purpose of social ci is to facilitate what davenport (2005) calls collaborative knowledge work in the realm of strategic management. four bodies of work converge in synthesis with social ci: a) established methods from the area of competitive analysis and strategic decision making; b) knowledge and know-how concerning collaborative knowledge work in general; c) use of collective intelligence to increase the level of performance; d) use of social technology as a key enabler for collective intelligence. from a theoretical perspective, further studies of social ci can be motivated by the fact that collaborative knowledge work, herein understood as collective intelligence, is the most advanced form of knowledge work, and thus potentially will deliver the most sophisticated results. an important assumption is that social technology is the enabling technical platform needed to achieve such intelligence in a systematic and replicable way. the selection of interviewed experts in the presented work has focused on the viewpoint of the suppliers of ci. two separate interview studies have also been performed with focus on the ci analyst in various domains and organizations that will be presented elsewhere. a third possible group of expertise is professionals with experience in knowledge networks, communities of practice and use of social technology in the enterprise, that would complement the results found here. the intention of the socio-technical themes is that they can be used to adapt the basic framework figure 14 illustration of the modeling method of the scif. the picture shows how each bst perspective has one collaboration model (c) and one task model (t). each perspective also has a collection of socio-technical values (shown in detail on the sociotechnical value map). the socio-technical themes are also related to different perspectives (illustrated by the color code and position in the figure). 27 depending on new insights from further interviews and other experiences. moreover, the semi-structured interview technique also has its built-in limitations. another interesting way to proceed is to use creative workshops to further design and develop new work methods for social ci. the presented scif is to the best knowledge of the author a novel approach, where the closest alternative is a framework proposed recently by jin & bouthillier (2013). as discussed above, there are various details that differ but there are several points where sharing of results should be possible in forthcoming work, such as the use of activity theory by jin & bouthillier (2013) versus the use of a socio-technical viewpoint in the scif. a major strength of the proposed scif is that the field of social ci is placed in a coherent conceptual frame at the socio-technical level of analysis, thus making the issues at hand more manageable. another strength of the scif modeling method is that it explicitly distinguishes between task-oriented models and collaboration models, which relates social ci to the dual view of knowledge work by davenport (2005). in subsequent work, the scif will be used as a platform for development of methods and tools for social ci. finally, a motivation for the presented work has been to create a conceptual platform for forthcoming work within the area of social ci. the scif fulfills this objective in a way that is on the one hand flexible enough to be used in various settings, and on the other hand sufficiently concrete to support further practical work with methods and tools for social ci. 8. references ackerman, m.s., 2000. the intellectual challenge of cscw : the gap between social requirements and technical feasibility. human–computer interaction, 15(2-3), pp.179–203. alexander, c. et al., 1977. a pattern language: towns, buildings, construction, oxford university press. alter, s., 2008. defining information systems as work systems: implications for the is field. european journal of information systems, 17(5), pp. 448–469. anderson, c., 2004. the long tail. wired magazine, october. 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wirtz, b.w., schilke, o. & ullrich, s., 2010. strategic development of business models: implications of the web 2.0 for creating value on the internet. long range planning, 43(23), pp.272–290. wodtke, c. & govella, a., 2009. information architecture: blueprints for the web 2nd ed., new riders. 9. appendix this appendix contains an overview of the selected areas used for the socio-technical values map of social ci in section 5.1 9.1 collective intelligence the socio-technical values of social ci for the structure perspective uses a combination of the genomes and genes of malone et al. (2010) and the characteristics for community collaboration by bradley & mcdonald (2011). this section contains an overview of these two sources. malone et al. (2010) have identified a relatively small set of building blocks, called genes, which are combined and recombined to support collective intelligence. the genes are organized as answers to four questions, called genomes: a) what. the first question to answer is what is being done? two genes are identified: create and decide. the create gene is used when the actors in the collective intelligence system should generate something new. the decide gene is used for the evaluation and selection of generated alternatives. 31 typically, a complete genome needs both a create part and a decision part. b) who. malone et al. (2010) make a distinction between activities done by a crowd or a hierarchy. the crowd gene is preferred in situations where many people have resources and skills needed, or you cannot tell in advance who has these resources and skills. a major gain when using a crowd is that you can tap into a larger number of independent competences as a collective resource. c) why. there are three identified genes for why people participate in a collective intelligence system: money, love or glory. financial gain (the money gene) can be in the form of direct payment, or increased likelihood of future earnings. intrinsic enjoyment, socializing or feelings of contribution to a bigger cause are examples of the love gene. recognition from peers or others is the third gene called glory. d) how. in collective intelligence systems hierarchies are still used, but the novel part is their use of crowds. a main determinant for the work is whether members can make their contributions and decisions independently or not. four genes of how crowds perform using the create or decision genes are identified: collection, collaboration, individual decision and group decision. the collection gene occurs when members contribute independently. the collaboration gene occurs when members work together to create something that cannot be divided into independent parts in the social organization community collaboration will work best when the following characteristics are met (bradley & mcdonald 2011, figure 4-1): a) broad observation. community collaboration is appropriate when larger groups of people can contribute with different complementary pieces of knowledge in a work process. a gain with this approach is that it gives broader understanding of the studied phenomenon and is more likely to find innovative solutions. community observation tends not to lead to the same depth of analysis as work done by recognized experts and these should be seen as complementary ways of working. b) independence. the work method in community collaboration should be structured so that participants can work and contribute independently of each other. it is typically done in a more free-form where people can choose freely when, how and what they contribute. the participants should also be able to enter and leave the process freely. however, from an organizational point of view it is important that the community is kept connected to the organization. c) complementary information. community collaboration is socially adaptive and emergent in nature. it is typically focused around some focal point, such as a "shared interest, an idea, a concept, an opinion, a product design, a political position, a common experience, or a medical condition" (bradley & mcdonald 2011). the contributions naturally will be of a complementary nature that cannot be predicted in advance. d) open information. a community builds on the fact that contributions can be freely shared. if contributions are of a sensitive nature, a community approach will not work very well. in a community, the contributions that will be put forward will typically gravitate towards information that people have self-interest in sharing. e) collective wisdom. a strength of a community is that the wisdom of people with expertise and experience can easily be put forward when it is needed. using a transparent work process means that everybody can put forward their views at any particular point. f) direct. community collaboration is good at getting contributions directly from those who are affected. g) diversity. in a community that is typically multidisciplinary, it is often hard and not even desirable to find consensus on most questions. instead community collaboration embraces the fact that there are different opinions. h) innovation. the broad emergent and diversified approach taken in 32 community collaboration may lead to innovative idea generation. when people come together from different backgrounds on a common theme, new associations and ideas will naturally come to light. 9.2 the networking individual tapscott (2009) has described new behaviors related to social technology and wikinomics in terms of eight new norms, which summarize behaviors found in the net generation that are different compared to earlier generations. these eight norms are used here as indicators of a general change in behavior, suitable as a basis for the socio-technical values in the behavior perspective of social ci. the eight new norms of the networking individual can be described briefly as follows: a) norm 1: freedom. the networking individual revels in freedom – freedom in what she consumes in what she learns, in her relation to work and career, when to be social and with whom, and in how she selects her sources of information. she expects to be able to choose when and where to work. often she prefers to integrate social and work life, and uses technology as a way to avoid traditional office space and hours. b) norm 2: customization. for the networking individual it is essential that the product or service has the potential to be personalized, even if she will not use that functionality in the end. personalization has more to do with experience than with functionality. she prefers media services similar to the internet itself, where they can consume content when they want to, such as youtube, rather than traditional television channels. for the networking individual, it gadgets have also become fashion accessories. c) norm 3: scrutiny. the networking individual is accustomed to dealing with different levels of uncertainty of information. she has developed a new sensibility of how to tell fact from fiction and has a high level of awareness about the world. the networking individual uses digital technology to find out about the world, rather than traditional media. she "trusts but verifies" – facts are double– checked also when they come from traditional authorities such as teachers, doctors, politicians or journalists. as a consumer, she always searches for information thoroughly before she consumes, and she trusts few claims from companies or services at face value. she is aware of known facts and demands that companies and services become more transparent. d) norm 4: integrity. the networking individual cares about integrity-based values such as: being honest, considerate, tolerant, transparent and fulfilling commitments. she wants societal institutions to behave honestly, considerately, accountably and openly. the new behaviors are perhaps in part self-centered, but in part it is only a new way to approach everyday life. the networking individual often has little problem with illegal ways to obtain information products, which she may motivate with the claim that she has payed indirectly in some other way. e) norm 5: collaboration. the networking individual collaborates whenever it is possible. for the networking individual it is natural to use virtual meeting places for informal chat and contacts at work, instead of the coffee machine. she likes to collaborate online both for pleasure and efficiency. as a consumer, she is willing to collaborate with the producing organizations to develop better goods and services. at work, the networking individual wants to feel that her opinion counts. the networking individual mass collaborates in many aspects of her life. the collaborative work style is informal and often goes beyond the borders of traditional team work. f) norm 6: entertainment. for the networking individual work should be fun. thus, if an organization wants to attract the networking individual, they should make the work intrinsically satisfying. the new digital infrastructure built around the internet also intertwines professional support and amusement. the historically strict border between private and professional consumption is 33 not felt by the networking individual. she has no problem with blurring of roles, which can be seen as the next step after what has been called consumerization of it (gens et al. 2011; harris et al. 2012). g) norm 7: speed. the networking individual expects quick responses from everyone, everywhere, at any time by default. they expect humans to react at a speed similar to automatic services such as search engines. if a peer does not respond quickly they get annoyed and worried that something is wrong or that they are ignored. e-mail is often used for dialog with organizations, but in close relations instant messaging may be preferred to get quick responses. the networking individual typically prefers continual feedback from employers. h) norm 8: innovation. the networking individual is accustomed to and appreciates continuous innovation. she wants to have the latest version of a product or service whether it is to improve service quality, or simply for social status and self-image. in the workplace this means they prefer work processes that encourage creative collaboration. the networking individual is impatient with bureaucracy; instead she wants the work environment to be leading edge, dynamic, creative and efficient. 9.3 social it the socio-technical values of the technology perspective have been extracted from a patterns catalog for social interfaces (crumlish & malone 2009) combined with the principles of the learning architecture from wenger (1998). in the following list, groups of patterns for social interfaces are listed extracted from crumlish & malone (2009): a) engagement. working with social it is similar to planning and hosting any other social event. you need to think about how to invite people, create an interesting mix and keep the interest alive. it is important to identify and engage the early adopters and use them to spread the word and help development. b) identity. social it is concerned with people – who they are, how to know them, what they contribute with. when people use social it they want to present themselves and make personal collections. they also want to be able to connect to other social sites and interconnect with other social networks. c) presence. it is critical that social it is perceived as a space that is inviting and "full of life", which will attract people to spend time there. in a digital environment, presence can be defined as various ways of "leaving footprints in the digital sand" (wodtke & govella 2009). d) reputation. people who take part in social structures expect to develop social reputation and learn about the social status of others. however, the design of support structures for inventiveness must include a delicate balance between making success and thus also failure explicit. e) gathering. collecting is a basic human need. this behavior can be exploited as a driving force of social it, such as saving, favorites, tagging and displaying. collecting gives people a tool to organize and make sense of their experiences. in a social space, where the basic structure is highly dynamic, gathering becomes a central functionality to introduce a level of order. f) sharing. social it should always support sharing so that people can access information from one another. this can be used both for informal, private sharing and for more systematic public "word of mouth" that markets new ideas in a viral way. g) broadcasting. people in digital social spaces often want some form of individual arena that they can use to broadcast ideas to larger audiences in a natural way. h) feedback. feedback is a simple and effective way to engage people in a community. having an opinion is an important first step in how to engage people in a community. i) communication. there are many different modes of communication, one 34 to-one, one-to-a-few, one-to-many, and many-to-many. for social it, these modes should be used in a wellbalanced mix. j) collaboration. support of collaboration is an important feature of social it. there are many different modes of collaboration that can be supported in different ways, for example formal vs informal, small vs large groups, temporary vs long term relations, and so forth. k) keeping up. in a social space where it is easy to share and broadcast it is also important to support how to follow and keep up with new events. l) relationships. the possibility to see and connect with other people is an integral part of a social experience. not all acquaintances are equal, some have strong ties, and some have weak ties. social it should support different modes of relationships, for different situations and needs. m) community management. a community needs rules and norms that guide them in how to behave. in social settings norms are more important than rules. to enforce them, community management must be visible for, and actively participating in, the community. n) local connection. people are social beings that like to meet face-to-face. social it is most effective when combined with real life events, locations and contacts. wenger (1998) describes how identity and belonging are important aspects of learning. for a learning architecture to support identity formation in a social learning system three modes of belonging should be met (wenger 1998, figure 10.3): a) engagement: achieving a sense of belonging by active involvement in processes of negotiation of meaning. this can include shared histories of learning, relationships, interactions and practices. b) imagination: achieving a sense of belonging by creation of images of the world and seeing connections by extrapolating from experience. this can include images of possibilities, images of the world, images of the past and the future, and images of the community. c) alignment: achieving a sense of belonging by coordination of energy and activities in order to fit into broader structures and joint contributions. this can include discourses, coordinated efforts and energy, finding common ground and creating boundaries. vol5no3 article1 coverpage vol5no3 article1 vol11no1paper6 to cite this article: rodriguez-salvador, m. & castillo-valdez, p.f. (2021) integrating science and technology metrics into a competitive technology intelligence methodology. journal of intelligence studies in business. 11 (1) 69-77. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 1 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index integrating science and technology metrics into a competitive technology intelligence methodology marisela rodriguez-salvadora,* and pedro f. castillovaldeza atecnologico de monterrey, av. eugenio garza sada 2501, col. tecnológico, monterrey, n.l. c.p. 64849, méxico; *marisrod@tec.mx journal of intelligence studies in business please scroll down for article integrating science and technology metrics into a competitive technology intelligence methodology marisela rodriguez-salvadora,* and pedro f. castillo-valdeza atecnologico de monterrey, av. eugenio garza sada 2501, col. tecnológico, monterrey, n.l. c.p. 64849, méxico *corresponding author: marisrod@tec.mx received 27 october 2020 accepted 29 march 2021 abstract for years, the appropriate interpretation and application of metrics have enabled scientists to assess science and technology dynamics. consequently, diverse disciplines have emerged, such as bibliometrics, scientometrics and patentometrics, offering important theoretical and methodological contributions. however, the current accelerated technological advances require researchers to implement a superior approach to detect continuous changes in the external environment identifying opportunities and vulnerabilities to strengthen the decision-making process regarding r&d and innovation. in this context, competitive technology intelligence (cti) offers a strategic approach based on a continuous cycle where information is transformed into an actionable result. this research provides a broader scope to science and technology metrics, incorporating them into a cti global methodology of eight steps. metrics add value throughout the entire cti process, from project planning to decision-making stages, having the most significant role in the information analysis stage, mainly to process information from sources such as scientific documents, patents, and social networks. particularly, this approach considers recent studies in cti in which quantitative tools such as patentometrics and scientometrics were successfully used. this proposal can be applied to predict upcoming technologies, movements of competitors, disrupting activities, market changes, and future trends. accordingly, this research adds value to the assessment of science and technology dynamics, aiming to improve the decision-making process of r&d and innovation. keywords competitive intelligence, competitive technology intelligence, patentometrics, science and technology metrics, scientometrics 1. introduction in a global world, technological advances embody new opportunities to be assessed by organizations. good decision-making requires correctly identifying the technologies to implement, the products to develop and the standards to use. the new forms of collecting, storing, transforming, and processing data have made the information more accessible than ever. information about the external environment enables leaders to manage their businesses more effectively; however, information is not enough. an adequate assessment of science and technology is fundamental to impact present and future r&d and innovation decisions; therefore, building metrics is essential to obtain accurate results. to facilitate science and technology understanding, diverse disciplines based on metrics analysis have emerged, including scientometrics, patentometrics, and altmetrics. they offer fundamental theoretical and methodological journal of intelligence studies in business vol. 11, no. 1 (2021) pp. 69-77 open access: freely available at: https://ojs.hh.se/ 70 contributions involving the use of traditional and non-traditional metrics. scientometrics is a discipline based on mathematical methods to quantify scientific research literature to reveal the process of scientific development (qiu et al. 2017). it enables researchers to identify the actors and processes involved in scientific activities, such as authors, research groups, institutions, countries, and their scientific production, to determine the structure, relationships, and research dynamics (michán l. 2013). scientometrics deals with scientific information analysis mainly from scientific documents; on the other hand, patentometrics focuses on the analysis of patents. patents protect inventions developed by companies, institutions, or individuals, and can be interpreted as indicators of invention, and it is possible to create scientific and technological scenarios of countries, industries, and research institutes by analyzing them. unlike scientific literature, patents have a legal framework that supports them, and the information they contain has a uniform structure, allowing the easy extraction of the information desired. economic indicators have also been associated with patents, addressing connections between technology and trade. while traditional metrics focus on the data mining of scientific and technological outputs (e.g., scientific papers, patents), nontraditional metrics–also known as alternative metrics or altmetrics (priem et al. 2012)–are oriented to measure scholarly activities on social networks, blogs, newspaper articles, and web sites, among others (european union 2017). the consolidation between traditional and non-traditional metrics offers a complementary view to evaluate the dynamism of science and technology, which requires more than one single metric approach (staudt et al. 2018). although metrics analyze different aspects of science and technology, they are not enough to continuously monitor the external environment to support strategic r&d and innovation decision-making. by systematically analyzing the external environment, organizations can increase their advantages (luu, 2015), identify movements of competitors (rothberg and erickson 2017), and detect opportunities for growth (zeid 2014), which represents a crucial factor to survive under the current and future industry global competition (shaitura et al. 2018). in this context, cti adds fundamental value since it involves a continuous process based on collecting and analyzing external information transformed into a strategic result (dou et al. 2019) to anticipate changes in the market and to identify relevant opportunities, supporting the decision-making process for innovation (du toit 2015, rodriguez-salvador and lopezmartinez 2000). based on studies that apply cti for science and technology assessment, a global methodology that incorporates metrics into a cti process is proposed. first, a description of the general context of cti is presented, then recent cti studies are identified, and finally, a cti methodology is proposed revealing the incorporation of metrics. 2. competitive technology intelligence r&d fosters knowledge aiming to provide answers to questions from different fields. for this activity to be enhanced, it is necessary to transform information into intelligence and provide conditions to facilitate a continuous flow of knowledge (amidon rogers, 1996). therefore, it is crucial to analyze external data in a timely and proper way to develop business insights and become more competitive (rodriguez-salvador 2006, zeid 2014). competitive intelligence emerges as an approach to support strategic decision-making. while fitzpatrick and burke (2003) define competitive intelligence as a process to collect and analyze external information to increase the advantages and position of an organization, dou et al. (2019) define it as the ability of an organization to understand its environment effectively and drive strategies accordingly. this ability is sustained by the process of collection, analysis, and dissemination of actionable knowledge. when competitive intelligence is applied to science and technology research, the term cti arises. cti pursues timely awareness of scientific and technological events to stay ahead, identifying collaboration prospects, technology knowledge landscapes, and in general, valuable findings to improve r&d and innovation processes (rodriguez-salvador et al. 2002). achieving this involves a methodology which in general starts with a planning stage aligned to the main objectives of the study, continuing with the identification of information sources, aiming to identify the best alternatives to collect the most relevant information on science and technology from different sources, such as experts in the field, 71 documents, patents, and social networks. the next step consists of information collection, where the main goal is not to get the most significant amount of information but to get the most meaningful information possible. this information is processed and prepared for further analysis, where different techniques can be applied (e.g., scientometrics, patentometrics, road-mapping). dissemination and decision-making comprised the last stages. 3. cti methodology to understand the impacts of metrics on scientific and technological research, an indepth analysis of studies that examine metrics and apply cti for science and technology assessment was conducted. wilsdon et al. (2015) explored the effects of the growing use of metrics to evaluate research, proposing their responsible application and establishing that an appropriate research assessment should include elements such as robustness, transparency, reflexivity, humility, and diversity. staudt et al. (2018) proposed a set of textand citation-based metrics to identify high-impact and transformative works. these metrics are categorized into seven types: radical-generative, radical-destructive, risky, multidisciplinary, wide impact, growing impact, and impact (overall). based on an analysis of the accuracy of 39 metrics, bollen et al. (2009) showed that a multi-dimensional view is required to measure the impact of scientific research effectively. finally, cronin and sugimoto (2014) emphasized that the web leads to new tools to assess scholar productivity, revealing behaviors and impact that were previously invisible, such as number of mentions, acknowledgments, endorsements, number of downloads, recommendations, blog posts, tweets, and a variety of other metrics that can be utilized. table 1 recent studies using quantitative tools under an intelligence approach. title year authors journal analysis of the knowledge landscape of 3d bioprinting in latin america 2019 marisela rodriguez-salvador, diego villarreal-garza, mario moisés alvarez, grissel trujillode santiago international journal of bioprinting data analytics for better informed technology & engineering management. 2019 alan l. porter ieee engineering management review discovering new 3d bioprinting applications: analyzing the case of optical tissue phantoms. 2019 luis hernandez-quintanar, marisela rodriguez-salvador international journal of bioprinting additive manufacturing in healthcare. 2018 marisela rodriguez-salvador, leonardo a. garcia-garcia foresight and sti governance additive manufacturing knowledge incursion on orthopaedic devices: the case of hand orthoses 2018 leonardo a. garcia-garcia, marisela rodriguez-salvador proceedings of the 3rd international conference on progress in additive manufacturing (pro-am 2018), singapore an assessment of technology forecasting: revisiting earlier analyses on dyesensitized solar cells (dsscs). 2018 ying huang, alan l. porter, yi zhang, xiangpeng lian, ying guo technological forecasting and social change competition-driven figures of merit in technology roadmap planning. 2018 ksenia smirnova, alessandro golkar, rob vingerhoeds 2018 ieee international systems engineering symposium (isse) revealing emerging science and technology research for dentistry applications of 3d bioprinting. 2018 marisela rodriguez-salvador, laura ruiz-cantu international journal of bioprinting uncovering 3d bioprinting research trends: a keyword network mapping analysis 2018 leonardo a. garcia-garcia, marisela rodriguez-salvador international journal of bioprinting scientometric and patentometric analyses to determine the knowledge landscape in innovative technologies: the case of 3d bioprinting. 2017 marisela rodriguez-salvador, rosa maria rio-belver, gaizka garechana-anacabe plos one technology roadmapping for competitive technical intelligence 2016 yi zhang, douglas k.r. robinson, alan l. porter, donghua zhu, guangquan zhang, jie lu technological forecasting and social change topic analysis and forecasting for science, technology and innovation: methodology and a case study focusing on big data research. 2016 yi zhang, guangquan zhang, hongshu chen, alan porter, donghua zhu, jie lu technological forecasting and social change. despite the profuse research on metrics, few studies have explored metrics under a strategic view. recent investigations incorporate scientometrics, patentometrics, and other quantitative tools into a cti approach using data mining to make science and technology assessment more comprehensible, but they mainly address the analysis of secondary information, such as scientific documents and patents. as an example, table 1 shows some recent efforts ranging from the analysis of specific fields to those focused on analytic tools. in the first group are new 3d bioprinting applications: optical tissue phantoms, emerging dentistry applications of 3d bioprinting, additive manufacturing for hand orthoses, technology forecasting on dyesensitized solar cells (dsscs), competitiondriven figures of merit (automotive industry), 3d bioprinting in latin america, keyword network mapping analysis on 3d bioprinting research, knowledge landscape of 3d bioprinting and forecasting on big data research. in these studies, scientific and technological trends were identified by analyzing documents and patents, including data mining of some of their elements, such as titles, keywords, authors, and affiliations. this revealed the dynamics of intellectual outputs in terms of metrics such as number, evolution, and impact of publications and/or patents by authors, journals, institutions, countries, and areas. on the other hand, table 1 also exhibits tools to facilitate analysis tasks, particularly data analytics for technology and engineering management and technology road-mapping for competitive technical intelligence where metrics combine qualitative and quantitative data and external actors are participating. approaches from porter (2019), rodriguezsalvador and ruiz-cantu (2019), hernandezquintanar and rodriguez-salvador (2019), huang et al. (2018), garcia-garcia and rodriguez-salvador (2018a), rodriguezsalvador et al. (2017), and zhang et al. (2016) were considered to develop a new cti methodology where, unlike current studies, 1) primary and secondary information are considered, 2) quantitative and qualitative metrics are applied and 3) experts participate. this cti eight-step methodology comprises interdependent phases, receiving continuous feedback. 1. project planning. the main activities and scope of the cti project are established, as well as participants, roles, resources, and internal policies. metrics, in this stage, can be established according to specific key performance indicators depending on the objectives to accomplish. 2. identification of data sources. this represents the input for further analysis. in this stage, metrics can facilitate the selection of the best information sources. there are two basic types of data sources: primary and secondary. the former is based on the insight of experts, where metrics contribute to identifying experts for feedback purposes, determining their presence in a field in terms of indicators such as the number of paper citations, the number of patents, the ranking of publications, areas of specialization, and network collaborations through affiliation analysis. commonly, secondary sources include scientific and technical documents, as shown in the studies in table 1; however, this approach also incorporates strategic information such as industry and market reports. additionally, social networks, which are rapidly evolving, are considered. in this case, metrics can help identify the quality of sources in terms of features such as their completeness, impact, and prestige. 3. search strategy design. establishing a plan and a strategy to retrieve information is essential. this activity should be aligned to the study focus as well as to the characteristics of the specific data sources previously identified. tools like delphi studies, focus-groups, and interviews may be considered, each one with specific metrics. for secondary information, particularly from the internet and databases, it is essential to identify the most relevant terms to feed searching queries. for this aim, an in-depth literature review should be executed, not only from scientific publications, technical reports, and patents but also from industry and market reports, among others. moreover, different queries should be designed to maximize the efficiency of further data collection. 4. data collection. this focuses on the previous primary and secondary sources identified. database management systems would be required to access and manipulate large sets of information. this stage also 73 includes normalization and preparation of the information to be processed and analyzed in the following step. 5. information analysis. while traditional studies are typically focused on only on solving the questions “what?” and “how?” and on the analysis of scientific and technological documents, this stage aims to answer fundamental questions such as “what?” (to develop, incorporate, cancel, allocate), “how?” (human and material resources), “when?”, “where?”, “why?”, “with whom?” and involves industry and market reports in combination with expert views. scientific literature can be evaluated using metrics such as the number of publications, the growth rate of publications, impact factor of journals, the number of citations, author affiliation, collaboration networks, countriesand institutions-predominance, and areas of specialization by journal, author, institution or country. on the other hand, patents can be analyzed based on metrics such as patent production, patent categorization according to the international patent classification (ipc), ipc distribution of inventors, assignees and/or countries, the number of patent families (pfs), patent distribution of assignees and patent legal status (assigned, granted or inactive). to analyze social networks and websites alternative metrics can be incorporated, considering statistics comprising the number of mentions, number of downloads of the documents, and social network interactions. for scientific papers and patents, specialized software, data mining, and algorithms for text mining can be used to apply co-occurrence analysis, and keyword or term clustering to determine behaviors by the output of authors, countries, institutions, journals, and areas. industry and market reports can be analyzed in terms of well-known metrics such as market share, competitiveness level, consumer behavior, and distribution rate. 6. feedback from experts. recommendations from experts constitute a great asset. compared with other studies where expert participation is scarce or does not exist, this research suggests their participation across the entire cti process. in this case, metrics can be established to get an expert evaluation of results obtained, particularly for the analysis stage. interviews and questionnaires throughout the entire cti process are suggested. experts can also participate in delphi studies and focus groups. 7. validation and delivery of final results. it is crucial to zoom in to examine the accuracy of results obtained; validation should be developed from the initial to the final stages of the methodology. this stage represents the last verification to make final adjustments as needed. results are then consolidated and prepared for their delivery through a report that can be communicated to the decision-maker and other stakeholders. this report should be aligned to the objectives previously established, adding value to the decision-making process. it is suggested that the content displays quantitative results; for example, figures that show the evolution of the industry, market, technology, product or process, emerging areas, readiness level, its performance, the predominance of areas, and position by authors, countries, companies, collaboration networks, market share, economic feasibility and distribution. additionally, it is suggested to include qualitative results such as scenarios for industry, market, technology, product, or process. furthermore, metrics can help to systematically monitor research activities at international, national, regional, and industry levels. it is also fundamental that this report considers user preferences in terms of several aspects such as presentation style, content, and delivery time. 8. decision making. this step represents the execution of results obtained, where decisions are taken by the people in charge of r&d and innovation. the result obtained previously is transformed into a specific action, and it is an input to decide what should be monitored constantly, which is also a differentiator of other approaches. it is imperative to stimulate debate and discussion, looking for competitive advantages. 4. discussion the methodology proposed in this paper promotes the integration of metrics through a cti eight-step process. like those of table 1, current studies are mainly focused on a statistical analysis of secondary information, 74 principally through data mining of scientific and patent information applying techniques such as scientometrics and patentometrics. a gap still exists in the application of metrics under a strategic perspective, such as that of cti, where primary and secondary information can be combined, and quantitative and qualitative metrics are integrated with the insight of experts. such insight is required to support and validate metrics to ensure the production of reliable outcomes. figure 1 illustrates how metrics could be integrated into the cti methodology previously presented, where the principal contribution is for four steps. the second step is to identify the best information sources. the fifth step is where metrics acquire the most critical role of the cti process, being possible to reveal strategic elements for r&d and innovation as early warnings, technologyand market-lifecycles, potential collaborators, technology impact and so on. the sixth step is where the insight of experts can help to refine results and broaden the scope of the study. and the seventh step involves validation and the elaboration of an executive report, integrating the most relevant insights. through this cti global methodology, we aim to fill the gap regarding the current use of metrics. this can be an essential guideline for assessing science and technology evolution supporting strategic planning for r&d and innovation initiatives in technology-based organizations. leaders should set new directions toward strategic changes to achieve competitive advantages (verlander 2012). this effort may represent an important alternative to give a better overview of science and technology, giving the possibility of detecting opportunities and threats on time to gain competitive advantages through r&d and innovation. 5. conclusions in a globalized world where competition is becoming more complex, professionals should adapt, change, and develop competitive advantages by assessing the evolution of science and technology research. metrics analysis represents a strong contribution for the research activities to be more figure 1 competitive technology intelligence (cti) eight-step methodology incorporating metrics. 75 understandable. however, they do not offer a complete solution to anticipate and detect continuous changes in the external environment as cti does. while current research focuses mainly on analyzing secondary information through quantitative metrics, this proposal goes further by considering 1) primary and secondary information, 2) quantitative and qualitative metrics, and 3) insight of experts into a cti eight-step methodology, with an emphasis on the stages of identification of data sources, information analysis, feedback from experts, and validation and delivery of final results. the proposed methodology can be applied to disclose the dynamics of an industry, market, and a scientific and technological field, predicting new technologies, movements of competitors, disrupting activities, market changes, and future trends. moreover, this approach can enable the early detection of scientific and technological opportunities or threats by monitoring the competitive environment continuously and supporting the strategic planning of r&d and innovation. finally, it is relevant to state that the implementation of this global approach requires identifying specific metrics to incorporate according to the objectives to pursue, the industry, and the project context. furthermore, novel metrics and automation processes to interpret information are continuously emerging. consequently, it is crucial to keep abreast and include them in future research. acknowledgments the authors acknowledge the institutional funding received from tecnologico de monterrey, and the national council of science and technology (conacyt) through a doctoral scholarship. conflict of interest the authors declare that they do not have any conflicts of interest. 6. references 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(2020) the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use. journal of intelligence studies in business. 10 (3) 63-79. article url: https://ojs.hh.se/index.php/jisib/article/view/589 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyena,* and nguyen phong nguyena auniversity of economics ho chi minh city, ho chi minh city, vietnam *baoquyen@ueh.edu.vn journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 3,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10,no.32020 opinion: a project management approach to competitive intelligence miguel-ángel garcía-madurga and miguel-ángel esteban-navarro pp. 8-23 an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukari pp. 24-37 the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry stefan zwerenz pp. 38-62 the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyen and nguyen phong nguyen pp. 63-79 financial intelligence: financial statement fraud in indonesia muhammad ikbal, irwansyah irwansyah, ardi paminto, yana ulfah and dio caisar darma pp. 80-95 the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyena,* and nguyen phong nguyena auniversity of economics ho chi minh city, ho chi minh city, vietnam *corresponding author: baoquyen@ueh.edu.vn received 13 august 2020 accepted 26 october 2020 abstract in the past decades, enterprise resource planning (erp) systems have become increasingly automated, particularly for routine management accounting tasks. however, there has been little research investigating the accounting benefits of adopting erp systems. this study investigates the role of perceived accounting benefits in erp success. drawing on juran’s principle of ‘fitness for use,’ this study establishes a framework that captures how perceived accounting benefits influence effective system use, which, in turn, enhances enterprise success. using partial least squares – structural equation modelling (pls-sem) with survey data collected from 120 enterprises in vietnam that have implemented erp, our findings provide strong support for the predicted positive effect of perceived accounting benefits on enterprise success, and for the hypothesis that this relationship is fully mediated by effective system use. this study is novel for two reasons. first, it is one of the first attempts to provide empirical evidence that effective system use and enterprise success are valuable outcomes of accounting benefits perceived to be gained from the use of erp systems. second, it discovers and demonstrates that effective system use is the most appropriate system-use concept in the present enterprise systems-related context, a topic that remains under discussion in the literature. keywords effective system use, enterprise resource planning, enterprise success, fitness for use, perceived accounting benefits 1. introduction an enterprise resource planning (erp) system refers to commercial software that automates and integrates many or most of a firm’s business processes. this type of system allows access to integrated data across the entire enterprise in real-time (davenport, 1998). thus, an erp system is expected to increase firm productivity via processes standardisation, improve decision-making ability via information integration throughout the entire enterprise, enhance cooperation between organisational entities by connecting them smoothly, and, most importantly, maintain competitive advantage once these benefits are realised (davenport, 1998). these expected benefits serve to explain the increasing popularity of firm adoption of erp systems. for example, fortune 500 companies trust erp systems, and in relation to the present study, large-sized organisations in vietnam have been increasingly adopting erp systems. however, some firms have faced difficulties achieving the benefits they expected from adopting an erp system. therefore, as journal of intelligence studies in business vol. 10, no. 3 (2020) pp. 63-79 open access: freely available at: https://ojs.hh.se/ 64 suggested by markus and tanis (2000), it is of great interest to researchers and managers to discover whether investing in an erp system will pay off. several organisational-level econometric studies have found that, on average, investment in erp systems does indeed create benefits (anderson, banker, & ravindran, 2003; hitt, wu, & zhou, 2002). however, such benefits vary among enterprises, and even among accounting modules (nicolaou, 2004). kanellou and spathis (2013) review the literature related to the benefits of implementing erp systems and conclude that erp implementation has a considerable effect on the accounting departments of firms. thus, managers must ask the following questions: what are the accounting-related benefits perceived from implementing an erp system? is it possible that these benefits can support organisations to implement erp systems effectively? how do perceived erp accounting benefits affect the success of the erp system itself? it is important to address these questions. kanellou and spathis (2013) provide the only study to investigate these questions. however, their study has several limitations. first, the outcome of perceived accounting benefits is conceptualised as user satisfaction, which is not an appropriate measure of erp system success. to address this issue, this study adopts effective use and erp success to measure the success of erp systems. second, while kanellou and spathis’s (2013) analysis unit is the firm, their study is conducted at the operational level (the informants are accountants) rather than at the organisational level (in which case the informants would typically be managers such as accounting professionals working as chief accountants or controllers). to address this limitation, this study is conducted at the organisational level. measuring the success of erp systems at the organisational level allows for information to be aggregated at higher levels, enabling success to be evaluated at the industry, regional, national and global level. therefore, the present study is expected to provide greater insight into the role of perceived accounting benefits in the success of erp systems. as stated, the present study aims to examine the effect of the perceived accounting benefits gained by the effective adoption of erp on system success. the study draws on juran’s principle of fitness for use to establish a framework for the effect of perceived accounting benefits on effective system use, and how this effect enhances enterprise success. the findings of this study will be of value to any companies considering including their accounting techniques and operations in an erp system. further, the results of this study will provide guidance and motivation for organisations that have implemented erp systems but are in trouble. the remainder of this paper is organised as follows. section 2 begins with a review of the previous research, and then presents the research model and hypotheses. section 3 justifies and describes the methodology employed for the study. section 4 reports and analyses the results of the study. section 5 concludes by presenting the theoretical and practical implications of the study, the study limitations, and suggestions for future research. 2. literature review, research model and hypotheses 2.1 perceived accounting benefits (pab) from the erp system and pab outcomes several studies have investigated the technical, managerial and economic advantages of erp implementation. for example, rouhani and mehri (2016) show that erp implementation benefits (e.g., decisional empowerment, improved interaction with customers, improved decision-making process, increased flexibility in information generation, and improved information flow among departments) have a positive impact on the level of readiness in business intelligence readiness. if erp is integrated with business intelligence, it can provide additional value to organisations (søilen & hasslinger, 2012). under a business intelligence platform, data collected by erp can be stored in a data warehouse and then further analysed and exploited for problem-solving and value enhancements (langlois & chauvel, 2017). however, the evaluation of the accounting benefits generated by an erp system remains inadequate and unsystematic. this section reviews studies that focus on the interaction between accounting and erp systems to gain an understanding of the perceived accounting benefits derived from erp. spathis and constantinides (2004) find the following three most important motives leading business organisations to decide to adopt an erp system rather than retain their traditional information system: increased 65 demand for real-time information, information generation for decision making, and need to integrate applications throughout the entire enterprise. these authors also explore several positive changes related to accounting applications arising from erp implementation, such as flexibility in information generation, increased integration of accounting applications, improved quality of reports and statements of accounts, improved decisions based on timely and reliable accounting information, and reduction of time for closure of annual accounts. some studies have provided an in-depth analysis of the accounting benefits arising from improving the quality of an erp system’s output. for example, velcu (2007) and colmenares (2009) identify that erp implementation allows reports and statements of accounts to be provided more accurately. brazel and dang (2008) state that erp appearance reduces reporting lags. olhager and selldin (2003) explain that erp implementation also increases the availability of information, the integration of business procedures and functions, and the quality of information. spathis (2006) and colmenares (2009) find that an additional accounting benefit perceived to be gained from the use of erp systems is connected to decision-making ability. specifically, it was found that erp supports enhancements to the decision-making process in a business organisation (spathis, 2006) and erp implementation is usually followed by improvements to the decision-making process and enterprise integration (colmenares, 2009). in addition, gattiker and goodhue (2004) and chang (2006) find that other accounting benefits arising from erp implementation are eliminating chores associated with report writing and data entry. gattiker and goodhue (2004) find specifically that an erp system results in an increase in coordination within the enterprise, and chang (2006) finds that an erp system connects traditional business functions such as finance, production, warehousing and sales into a single integrated system based on a shared database. other studies have noted how the accounting process and the accountant’s role are affected by the implementation of an erp system. for example, booth, matolcsy, and wieder (2000) examine the extent to which the application of an erp system can lead to the adoption of new accounting practices. booth et al. (2000) demonstrate that the entire erp system constitutes sources of data for new accounting practices, and thus can support these practices powerfully. more specifically, rom and rohde (2006) find that an erp system not only provides considerable assistance in the collection of data but also increases the organisational breadth of management accounting. this finding is confirmed by järvenpää (2007), who notes that an erp system leads to new management accounting being adopted. thus, accountants obtain several advantages from erp implementation because they are able to conduct routine activities more effectively, handle large databases more quickly, and report in a faster and more flexible manner. several studies have found that the accountant's role considerably changes when the erp system is implemented. granlund and malmi (2002) find that the most important benefit of erp implementation in relation to accounting is the improvements made in the mass processing of documents. this improvement in efficiency allows management accountants to spend more time focusing on analysis and business support processes rather than on designing and generating appropriate reports. these findings are consistent with scapens and jazayeri (2003), who find that the implementation of erp systems has shifted the work of management accountants from a traditional role focused on accounting activities to a more interpretative role focused on analysis, information evaluation and decision making. to reflect this shift, accountants are considered ‘consultants’ and ‘analysts’ rather than ‘bookkeepers.’ hyvönen, järvinen, and pellinen (2008) present the development of a management accounting control system, and suggest that information technology (it) accounting solutions in general compel accountants not only to examine the logic of the solution but also to invent ways of combining accounting and management rationalities. similarly, newman and westrup (2005) employ case studies and a survey to demonstrate empirically that the relationship between accountants and technologies (e.g., erps) has become increasingly intertwined. indeed, newman and westrup (2005) argue that the development of erp results in reshaping the management accountant’s role, and that this redefinition of the management accountant’s role then has a positive effect on erp. more recently, grabski, leech, and schmidt (2011) also acknowledged the change in the role of 66 management accountants during the process in which firms learn how to use erp systems and obtain considerable value from these systems (grabski et al., 2011). it is clear that erp systems affect accounting processes and the role of accountants. o'leary (2004) analyses and measures ‘erp system benefits’ and tests whether these benefits vary across different industries, and then classifies a list of these benefits into tangible and intangible. some benefits relate to accounting functions such as inventory reduction, close financial cycle reduction, personnel reduction, management improvements, it cost reduction, on-time delivery, information/visibility, integration, flexibility, better decisions, financial controls and new reports/reporting capability. in an attempt to conceptualise and operationalise ‘erp benefits’, shang and seddon (2002) proposed a comprehensive framework for assessing the benefits derived from erp systems. their framework groups erp benefits according to five dimensions: operation, management, strategy, it infrastructure and organisation. similarly, but more narrowly, esteves and dwivedi (2009) develop a benefits-realisation road map for erp usage focusing only on small and mediumsized enterprises. the analyses show that the dimensions of erp benefits realisation are interconnected, and that managers should perceive this connection as a continuum cycle during the erp post-implementation period to maximise erp benefits. the accounting benefits gained through erp use identified by esteves and dwivedi (2009) that are quite similar to those of shang and seddon (2002) are cycle time reduction, cost reduction, quality improvement, improved decision making, support of organisational changes, increase in it infrastructure capability and increase in business flexibility. more relevant to the present study, spathis (2006), spathis and ananiadis (2005) and kanellou and spathis (2011) focus on developing a measurement of erp accounting benefits. the analyses of spathis (2006) are based on shang and seddon’s (2002) erp benefits classification. thus, spathis’s (2006) perceived accounting benefits from erp are classified into organisational benefits, operational benefits, managerial benefits and it benefits. spathis (2006) hypothesises that perceived accounting benefits can be explained by the following variables: the number of reasons for enterprise resource implementation, the number of enterprise resource modules, enterprise resource cost as a percentage of sales and the company’s total assets. according to spathis’s (2006) survey findings, the most important accounting benefits in the erp environment are increased flexibility in information generation, increased integration of applications, improved quality of reports and statements of accounts, improved decisions based on timely and reliable accounting information and reduction of time for closure of annual accounts. these results are consistent with those of spathis and ananiadis (2005) and kanellou and spathis (2011). the literature confirms the benefits of erp through the examination of the effect of erp systems on an organisation’s financial performance. however, the present study is most interested in the direct effect of erp systems on the accounting process, a topic that remains to be explicitly examined. most of the research noted above explains only what accounting-related benefits are or how accountants are affected in an erp environment. only four articles have investigated and developed a scale of the accounting benefits attained from erp systems (i.e., kanellou and spathis (2013), spathis (2006), spathis and ananiadis (2005), spathis and constantinides (2004)). as presented in table 1, only the scale of kanellou and spathis (2013) is adequately validated by testing the relationship between perceived accounting benefits and user satisfaction. however, user satisfaction is only a part of system success, not a scale for measuring system success because a user being satisfied with an erp system does not ensure that the erp system leads to enterprise success. 2.2 system use in the original delone and mclean information systems (d&m is) success model, systems use is referred to as the ‘recipient consumption of the output of an information system’ (delone & mclean, 1992, p. 66). however, an information system is constantly changing. enterprise systems adopted in business organisations nowadays are more mandatory than voluntary, thus, conceptualisation of the original system use in the d&m is success model seems likely to be inappropriate. in an excellent literature review, delone and mclean (2016) detail the development of information systems literature focusing on 67 systems use. however, they focus only on the context of adoption. deng, doll, and truong (2004) list three available system contexts: training, adoption (sometimes understood as technology acceptance) and ongoing, which are often referred to as the ‘pre-implementation’, ‘implementation’ and ‘post-implementation’ stages, respectively (chang, gable, smythe, & timbrell, 2000). delone and mclean (2016) do not consider systems use in the training and ongoing contexts at all despite training being ‘one of the most important activities of the preimplementation stage of any information system’ (deng et al., 2004) and, more importantly, ongoing referring to the duration of the success of the erp system, which is partly captured by the use construct (delone & mclean, 1992, 2016) and occurs to a great extent (sternad, gradisar, & bobek, 2011). previous research on the erp lifecycle phases (chang et al., 2000; markus & tanis, 2000; ross & vitale, 2000) finds that training belongs to the erp pre-implementation stage—which includes the erp design, chartering and project stages—and ongoing belongs to the erp post-implementation stage—which includes the erp stabilisation, continuous improvement and transformation stages, or the erp onward and upward stage, as in chang et al. (2000), ross and vitale (2000), and markus and tanis (2000), respectively. based on a highly insightful statement by deng et al. (2004) about the differences between the training and ongoing use contexts, delone and mclean’s (2016) comprehensive review of system use, and the literature review presented here, this study summarises and analyses the differences in system use in different use contexts, which correspond to the pre-implementation, implementation and postimplementation stages. it must be remembered that systems used in the training, adoption and ongoing contexts are similar in relation to the aspect that it usage always faces possible challenges in relation to technique, technology and human factors. nevertheless, the three contexts differ in their goals, time horizons, knowledge domains, identification of solutions to problems, practice environments, requirements for user behaviours, nature of appropriate support, and characteristics of related information systems. these differences reflect the dynamic and complex nature of system use and become a prerequisite for selecting an appropriate conceptualisation of ‘system’ that can be used in the present study’s focus on the erp postimplementation stage. the context is often implicit rather than explicit, which means that using an inappropriate system-use construct is likely to affect research findings. therefore, we claim that the meaningful conceptualisation and operationalisation of system use must consider the characteristics of the information system (mandatory or voluntary), the users employing the information system, the task performed with the information system, and most importantly, the system context in which the information system occurs (i.e. training, adoption or ongoing). the present study also emphasises that once the ongoing use is formed, it can be acceptable to employ it as the system used in the adoption context because there are no great differences in the use characteristics of the adoption and ongoing contexts. the limitation of this approach is that users’ perceptions of ongoing use in the adoption context are perhaps different from what they are in the ongoing context because it takes time for a user to be familiar with a new system. given these criteria for selecting a meaningful and appropriate system-use construct, this study chose effective system use (doll & torkzadeh, 1998) to represent erp adoption and ongoing use. when users become more sophisticated, they may be expected to accomplish their tasks more efficiently and effectively. thus, following doll and torkzadeh (1998) and deng et al. (2004), in the present study, the concept of ‘use’ refers to how effectively an erp system is used for fundamental organisational functions such as problem solving, decision making, work integration, and work planning. 2.3 erp system success there are limited studies that have concentrated on measuring the success of an erp system (mukti & rawani, 2016). therefore, on the grounds that an erp system is a type of information system, the present study reviews all popular measurements of the success of information systems and erp systems in the literature. a review of the success of information systems shows there are many definitions of success as it relates to information systems. thus, there is no formal definition of the phenomenon of information systems success. each kind of stakeholder has a different definition of the success of an information 68 system in an organisation (grover, seung ryul, & segars, 1996; ifinedo, 2011). for example, from the perspective of the system developer, the information system’s success is achieved when the information systems project is completed on time, under budget, and functions correctly. for customers or users, an information system is successful if it improves user performance and satisfaction (guimaraes & igbaria, 1997). from the organisational perspective, an information system’s success is measured by its contribution to the company’s profits or competitive advantage. in addition, the success of an information system also depends on the type of system to be evaluated (seddon, staples, patnayakuni, & bowtell, 1999). despite the value of these definitions of the success of an information system, this study focuses on delone and mclean’s (1992) conceptualisation of measuring information systems success because this conceptualisation provides a schema for categorising the measures of information systems success (ifinedo, 2011) and their framework has been widely used to assess the effectiveness or success of information systems at the organisational level (petter, delone, & mclean, 2008). accordingly, effectiveness constitutes the ‘extent to which an information system actually contributes to achieving organisational goals’ (thong & yap, 1996, p. 252). therefore, this study defines erp success as referring to whether the adoption of an erp system has improved effectiveness in the implemented enterprises. notably, by this definition, erp success does not refer to success in relation to erp technical installation or erp technical implementation, which are measured by factors such as cost overruns, project management metrics and time estimates (hong & kim, 2002; markus & tanis, 2000). 2.4 research model and hypotheses under a completely different approach, the framework of the present research is developed based on the principle of fitness for use concerning product and service quality, as defined by juran (1988). we argue that a prerequisite for using an erp system effectively is the quality of the erp system. there are two reasons for this. first, the quality of an erp system determines how the system can be used. second, if the quality of the erp system is reduced, there will be a low level of success in most cases (kronbichler, ostermann, & staudinger, 2010). thus, the successful adoption of an erp system must consider the quality of the erp system. this is why the principle of fitness for use is applied in this study. in information systems literature, this principle is commonly adopted to examine data and data quality (laudon, 1986; redman, 1995; strong, lee, & wang, 1997; vermeer, 2000; wang & strong, 1996). similarly, the present study adopts this principle to clarify the system and system-related qualities. the enterprise system (i.e., erp system) and other goods have distinct differences. first, an enterprise system is created through acquiring or self-designing, while organisations can produce products or services by themselves. second, a product or service can be exhausted through use, but an enterprise system is not depleted through use. that is, the elements of an erp system can be exploited simultaneously by multiple users and continue to be available for employment in a different context by subsequent users. these characteristics of an erp system are significant when considering the principle of fitness for use. the principle of fitness for use involves developing a shortlist of inputs that companies, organisations, and individuals can use to determine the fitness for the use of a product or service. juran and godfrey (1999) and juran (1988) provide the following questions for consideration: • who are the users of the product or service? (who) • what are the economic resources of both the producer and the user? (what) • how will the product or service be used? (how) • what are the users’ specific determinants of a product or service’s fitness for use? (economic benefits) • what is the possibility and/or probability of the product or service endangering humans? (privacy and security) the present study does not consider the safety aspect of adopting an erp system, thus it applies four of the above five queries to explain the appearances of, and connections among, all the constructs including pab, system use and erp success in the proposed framework. accordingly, this study defines who, what, how and the economic benefits of and erp system as follows: 69 • who = the accounting professionals in this study; these professionals are expected to be the most knowledgeable and effective users of the erp system • what = the perceived accounting benefits are the economic resources of both the producer and the user of the enterprise system • how = effective use, which refers to how the system is used • economic benefits = the erp system’s success is a specific determinant of the system’s fitness for use. following the principle of fitness for use (juran and godfrey (1999), this study assumes that based on the perceived accounting benefit (‘what’), accounting professionals (‘who’) will effectively exploit an erp system (‘how’) to achieve the system effectiveness (‘economic benefits’) that accounting experts expect when using an erp system. accordingly, perceived accounting benefits are the antecedents of erp system use and erp system success is the outcome of erp system use. hence, the hypotheses are proposed: h1. perceived accounting benefits have a positive influence on use. h2. use has a positive influence on erp system success. h3. perceived accounting benefits have a positive influence on erp system success. h4. effective system use mediates the relationship between perceived accounting benefits and erp system success. the research model and corresponding hypothesis are shown in figure 1. 3. research method 3.1 sampling and data collection this present study was conducted in vietnam, and features a data set of 120 firms. the sample is restricted to organisations that have adopted an erp system for at least one year because the research focuses on the implementation and post-implementation stages. the core aim of this study is to investigate perceived accounting benefits, thus the respondents are experienced accounting employees. however, this study is conducted at the organisational level, which means that each respondent represents one company. therefore, the most suitable informants are chief financial officers and chief accountants. unfortunately, given that there are few enterprises in vietnam that have implemented erp (a very low percentage of the total enterprises operating in vietnam), accessing potential respondents is extremely difficult. thus, the study identifies acceptable alternatives such as internal controllers, internal auditors and management accountants who have accounting experience related to erp and a general understanding of the operations of the entire enterprise. in addition, according to shang and seddon (2002), it takes two to three years for users to become familiar with a new enterprise system and extract the maximum benefits from that system. thus, the informants in this study are chief financial officers, chief accountants, internal controllers, internal auditors, and management accountants who have worked in organisations that have been using an erp system for at least one year and have at least two years of work experience in their current position. the sampling frame includes 5,110 email addresses of the potential informants (who figure 1 research model and hypothesis. 70 have all the above characteristics) from the personal linkedin social network of the authors of this study. the original survey items in english were translated into vietnamese and back-translated following brislin’s (1970) translation process. the official vietnamese version of the survey questionnaire was circulated to potential informants via surveymonkey, an online survey administration tool. we emailed the 5,110 potential respondents (with several follow-up emails) over two-and-ahalf months, and received a total of 569 responses. after eliminating 177 organisations that had not adopted an erp system, 78 responses from respondents whose employment position did not meet the inclusion criteria, 50 responses from respondents who did not have sufficient work experience, 102 incomplete responses, 26 responses whose response duration was too short (less than 10 minutes), and 16 outliers, the final sample consists of 120 valid responses. the profile of the responding organisations is presented in table 1. the details of erp systems adopted in organisations in vietnam are summarised in table 5. the sample enterprises utilise different erp packages (most use either sap or oracle). all sample enterprises had erp software installed and implemented for at least one year. table 1 demographic characteristics of surveyed companies. frequency % type of ownership 100% foreign-owned enterprises 23 19.2 state-owned enterprises (≥51% government capital) 22 18.3 private enterprises/limited enterprises 54 45 joint venture with foreign partners 14 11.7 joint venture with domestic partners 7 5.8 total 120 100.0 type of industry sector manufacturing 72 60.0 commercial 44 36.7 services 42 35.0 total 120 100.0 type of industry bank, insurance, investment 2 1.7 chemical and pharmaceuticals 3 2.5 dairy, food and meat products 28 23.3 electrical and electronics 7 5.8 medical and healthcare 8 6.8 information technology 10 8.3 manufacturing 12 10.0 retail/wholesale/distribution 25 20.8 telecommunications 3 2.5 transportation, logistics and courier 7 5.8 construction 6 5.0 others (e.g., beverages, fashion, design, fast-moving consumer goods) 9 7.5 total 120 100.0 company size (paid-in capital) in vnd billion <10 3 2.5 10–50 6 5.0 >50–100 11 9.2 >100–200 12 10.0 >200–500 14 11.7 >500–1000 22 18.3 >1000 52 43.3 total 120 100.0 company size (number of employees) ≤50 8 6.7 51–200 13 10.8 201–500 29 24.2 501–1000 23 19.2 1001–5000 32 26.7 5001–10000 9 7.5 >10000 6 5.0 total 120 100.0 71 table 2 demographic characteristics of the erp system. frequency % type of erp software oracle 20 16.7 sap 43 35.8 xman (erp) 2 1.7 salesup erp 2 1.7 navision 3 2.5 microsoft dynamic 4 3.3 lemon 3 2.5 fast (erp) 3 2.5 others (e.g., amis–misa, bamboo, bravo, bross, maconomy, mmis, peoplesoft, perp) 40 33.3 total 120 100.0 years erp has been implemented and used in the current company <1 year 0 0.0 1–2 years 21 17.5 >2–4 years 16 13.3 >4–6 years 37 30.8 >6–8 years 13 10.8 >8 years 33 27.5 total 120 100.0 the demographic characteristics of the informants are shown in table 3. most informants have a bachelor’s degree, 52.5% are female and 47.5% male. most are aged between 25 and 34 years. they have an average of 6.5 years of work experience, and an average of approximately 2.7 years of experience using the erp system in their current position. moreover, the informants report using the erp system frequently (5.4 of a 7-point likert scale). 3.2 measurement scales all research constructs included in this study have multi-item scales derived from the relevant literature. each item in the survey employs a 7-point likert scale (1 = strongly disagree, 7 = strongly agree). all instruments have been tested and defined in related research (deng et al., 2004; gable et al., 2003; kanellou & spathis, 2013) as reflectivereflective constructs. perceived accounting benefits (pab as a construct) are measured using the scales from kanellou and spathis (2013). this construct includes five dimensions: it accounting benefit (5 items); operational accounting benefit—time (4 items); organisational accounting benefit (5 items); managerial accounting benefit (3 items); operational accounting benefit-cost (1 item). the scale for effective system use includes 11 items from deng et al. (2004), which were adapted from doll and torkzadeh (1998). in deng et al. (2004), these 11 items are partially aggregated into four unlabelled congeneric indicators. erp system success, according to sedera and gable (2004), is a second-order construct measured by four first-order components: information quality (5 items), system quality (8 items), individual impacts (4 items), and organisational impacts (8 items). it is tested and defined as a reflective-reflective construct (sedera & gable, 2004). to ensure the content validity of the measurement scales in the research context of vietnam, before collecting data, we conduct a preliminary measurement assessment through an expert panel composed of three academics who are knowledgeable about erp and two managers: one internal controller and one expert that has experience in successfully implementing numerous erp projects in large enterprises. the preliminary measurement assessment confirms the high consensus of the expert panel on the ability of the selected scales to measure the research concepts in the model. next, the questionnaire is piloted with three accounting experts in enterprises that have adopted an erp system, after which some minor adjustments are made to the survey to ensure the questions are worded clearly and concisely, and are easy for the informants to understand. to ensure that the structure of the scale sets is consistent with the surveyed data collected in vietnam, this study conducts exploratory factor analysis (efa) to determine the appropriate structure of the variables without reducing the number of items employed to capture the concepts under investigation. in 72 doing so, this study employs principal axis factoring with promax rotation and a minimum eigenvalue of 1 (hendrickson & white, 1964) for data analysis. the exploratory factor analysis results determine that of the three scales, the erp success construct is immediately acceptable, while the others need to be refined. pab is a second-order construct with two factors extracted from 13 items (the remaining items are eliminated). effective system use is also a second-order construct with two factors extracted from eight items (the remaining items are eliminated). 4. data analysis, results and discussions all instruments in this research model are second-order constructs. partial least squares (pls) allows the conceptualisation of higherorder factors through the repeated use of manifest variables (tenenhaus, amato, & esposito vinzi, 2004). a higher-order factor can thus be created by specifying a latent variable, which represents all the manifest variables of the underlying lower-order factors. the study uses the pls approach because of the limited table 3 demographic characteristics of informants. frequency % min max mean position in the firm (job title) chief finance officer 15 12.5 chief accountant 39 32.5 internal controller 45 37.5 internal auditor 15 12.5 management accountant 6 5.0 total 120 100.0 position in the organisation’s hierarchy top management position 27 22.5 mid-level personnel 51 42.5 senior staff 39 32.5 staff 3 2.5 total 120 100.0 gender female 63 52.5 male 57 47.5 total 120 100.0 education background college degree 0 0.0 university (bachelor’s) degree 101 84.2 university (master’s) degree 19 15.8 total 120 100.0 age <25 3 2.5 25–34 66 55.0 35–44 51 42.5 >44 0 00.0 total 120 100.0 experience years in the current position 1 20 6.5 years using erp at the current position 1 5 2.7 the extent of erp system use (i.e., the degree to which informants agree with the following statements according to a 7-point likert scale ranging from 1 “strongly disagree” to 7 “strongly agree”) 'we use the erp system for many hours per day at work.' 1 7 5.2 'we use the erp system for many times per day at work.' 1 7 5.5 'overall, we use erp a lot.' 1 7 5.4 intention to continue the use of erp system (i.e., the degree to which informants agree with the following statements according to a 7-likert scale ranging from 1 strongly disagree to 7 strongly agree) 'we intend to continue using the erp in our job.' 3 7 6.2 'we intend to use more functions of the erp.' 3 7 6.1 'we intend to continue using the erp to process more tasks' 2 7 6.2 'we intend to suggest that our company should continue to use the current erp system.' 1 7 5.9 73 table 4 internal consistency, indicator reliability and convergent validity analyses of the first-order measurement model. first-order factor indicator loadinga composite reliabilityb avec pab_oganizational pab11 0.84 0.94 0.65 pab12 0.89 pab13 0.87 pab14 0.78 pab15 0.83 pab16 0.80 pab17 0.76 pab18 0.64 pab_operational pab6 0.95 0.95 0.86 pab7 0.96 pab8 0.95 pab9 0.93 pab10 0.86 use_work use5 0.91 0.93 0.77 use6 0.81 use8 0.92 use11 0.87 use_decision use1 0.79 0.90 0.69 use3 0.85 use4 0.88 use7 0.81 iq iq1 0.75 0.93 0.68 iq2 0.79 iq3 0.86 iq4 0.90 iq5 0.81 iq6 0.84 sq sq5 0.77 0.89 0.56 sq6 0.79 sq8 0.70 sq2 0.71 sq1 0.76 sq7 0.77 ap ap1 0.90 0.94 0.80 ap2 0.89 ap3 0.92 ap4 0.87 op op1 0.78 0.94 0.64 op2 0.85 op3 0.80 op4 0.75 op5 0.81 op6 0.81 op7 0.82 op8 0.78 valid sample size and the desire to analyse the second-order constructs. data are analysed in two stages through pls using smart pls software (hair, sarstedt, hopkins, & kuppelwieser, 2014). 4.1 assessment of the measurement model measurement instruments are assessed based on reliability, convergent validity and discriminant validity. construct reliability measures the stability and consistency of the scale, and is evaluated through internal consistency reliability and indicator reliability (hair et al., 2014). composite reliability measures the internal consistency reliability of the scale. tables 7 and 8 demonstrate that all the reflective first-order factors and secondorder factors have composite reliability that is over the cut-off value of 0.7, as suggested by hair et al. (2014). however, some of the factors have quite a high value; for example, pab_operational (0.95), pab (0.96) and erp success (0.95). these figures are considered sufficiently close to 0.95 (hair et al., 2014). hence, they are possibly acceptable. indicator reliability is assessed through outer loadings. table 4 demonstrates that the 74 outer loadings of all but one (i.e., except item pab18) of the observed first-order factors of all constructs range between 0.70 and 0.96, which is higher than the cut-off value of 0.70 (hair et al., 2014). the loading of indicator pab18 falls only slightly below 0.70 (0.64). we decide to retain this indicator for two reasons. first, we attempt to delete pab18, and then re-estimate the internal consistency and convergent validity of the first-order factor ‘pab_operational’. the results show that deleting pab18 leads only to an extremely slight increase in composite reliability and average variance extracted. second, and more importantly, pab18 expresses the item ‘the erp enables a reduction in the number of personnel in the accounting department’, which is indispensable because it explains the benefit of operational cost reduction that an organisation experiences when adopting an erp system. this item has also been used in different scales measuring perceived accounting benefits in previous studies (kanellou & spathis, 2013; shang & seddon, 2002; spathis & ananiadis, 2005). almost all of the average variance extracted values of all the first-order factors and secondorder factors are acceptable because they are higher than 0.50 (fornell & larcker, 1981). only erp success (0.44) (see table 5) was less than 0.50. erp success is a second-order factor, and its composite reliability is higher than 0.60. therefore, its convergent validity is adequate (fornell & larcker, 1981). in addition, the variance inflation factor values for each relationship between variables in the proposed model range between 1.00 and 1.81, which is well below the cut-off value of 5.0 (hair et al., 2014), indicating no issues of multicollinearity in this study. we evaluate the discriminant validity of the measurements following the procedure proposed by fornell and larcker (1981). table 6 demonstrates that the square roots of average variance extracted of all first-order factors range between 0.75 and 0.93, which is well above the corresponding correlations between these variables, thus indicating the discriminant validity of the measurements. 4.2 assessment of the structural model to test the proposed model and hypotheses, we evaluate the strength and significance of individual paths concerning the predictive relevance of these individual paths in the proposed model. the indices employed to evaluate the predictive relevance of individual paths are reported in table 7. these indices are calculated based on 5,000 bootstrapping samplings. the results of testing the direct relationships are presented in table 7. our hypotheses offer adequate explanatory power because the r2 values for all the predicted variables, effective system use (0.45) and erp success (0.67), are far greater than the recommended level of 0.10. specifically, this study finds positive direct effects of pab on use ( > 0.67, p < 0.001), of use on erp success ( > 0.14, p < 0.05) and of pab on erp success ( > 0.72, p < 0.001). thus, h1, h2 and h3 are strongly supported. table 5 internal consistency and convergent validity of the second-order measurement model. second-order factor first-order factor composite reliabilityb avea pab pab_ogranizational 0.96 0.63 pab_operational use use_work 0.92 0.60 use_decision erp success iq, sq, ap, op 0.95 0.44 table 6 discriminant validity (fornell–lacker criterion). note: the diagonal shows the square root of the average variance extracted of the latent variables and indicates the highest in any column and row ap iq op pab_ operational pab_ organizational sq use_decision use_work ap 0.89 iq 0.49 0.83 op 0.63 0.48 0.80 pab_operational 0.54 0.63 0.47 0.93 pab_organizational 0.61 0.69 0.67 0.73 0.80 sq 0.45 0.76 0.46 0.60 0.66 0.75 use_decision 0.56 0.52 0.49 0.53 0.70 0.45 0.83 use_work 0.47 0.39 0.39 0.42 0.56 0.40 0.64 0.88 β β β 75 table 7 direct relationships for hypotheses testing (using pls bootstrapping). h relationship std beta std error t-value hypothesis testing result 95% ci ll 95% ci ul h1 pab -> use 0.67 0.06 11.51*** accepted 0.57 0.76 h2 use -> erp success 0.14 0.07 1.94* accepted 0.03 0.25 h3 pab -> erp success 0.72 0.07 11.05*** accepted 0.61 0.82 notes: ***p < 0.001, p < 0.05; r 2 (use = 0.447, erp success = 0.673) table 8 results of direct, indirect and total effects (using consistent pls bootstrapping). h relationship std beta std error [t-value]^ hypothesis testing result 95% ci ll 95% ci ul h3 pab -> erp success 0.72 0.07 11.05*** accepted 0.61 0.82 h4 pab -> use -> erp success 0.08 0.01 1.22 accepted −0.02 0.18 total 0.85 0.04 21.69*** 0.78 0.91 notes: ***p < 0.001, *p < 0.05; r2 (use = 0.447, erp success = 0.673) in addition, this study utilises a procedure for mediation analysis using partial least squares – structural equation modelling (plssem) as proposed by nitzl (2016) to test further the mediating role of use on the relationship between pab and erp success. accordingly, consistent pls bootstrapping is employed to calculate the related indices. table 8 affirms that use fully mediates the relationship between pab and erp success. thus, h4 is supported. 5. conclusion 5.1 theoretical implications based on the significance of the statistical tests in the previous section, the proposed model and all of its hypotheses were accepted. these results have some important theoretical implications. first, based on previous studies relating to the accounting benefits perceived to be gained from the use of erp systems (kanellou & spathis, 2013; spathis, 2006; spathis & ananiadis, 2005; spathis & constantinides, 2004), this study discovers new outcomes of perceived accounting benefits. that is, the study provides further empirical evidence of the effects of perceived accounting benefits on erp use as well as on erp success. second, the findings from this study provide evidence to support juran’s principle of fitness for use by examining the critical role of accounting experts in enhancing erp success. accordingly, based on the perceived accounting benefit (i.e. ‘what’ is available as a benefit of the system), accounting professionals (i.e. ‘who’ uses the system) effectively exploit erp systems (i.e. ‘how’ the system is used) to achieve system effectiveness (i.e. ‘economic benefits’ of the system). third, this study adds to the limited research on the implementation and post-implementation stages of erp systems. specifically, it considers the effectiveness of erp system use rather than only the extent of erp system use. 5.2 managerial implications besides the theoretical implications, this study guides firms that use erp systems on how to design and implement an erp system to enhance system effectiveness. in addition, the results of our study can assist accounting experts to assess better the accounting benefits that an erp system may offer. hypothesis 1 testing result indicates that organisations should achieve a higher level of system use effectiveness by enhancing the perceived accounting benefits of erp via appropriate training and communication mechanisms. moreover, erp consultants should be able to guide companies that are interested in including their accounting processes in an erp system more efficiently. in addition, the hypothesis 2 testing results should be of interest and value to practitioners, who can adopt actions related to accounting techniques and procedures to improve effective erp system use, which in turn, enhances erp system success. finally, the results of testing hypotheses 3 and 4 imply that organisations should recognise that effective system use can be a connecting device to translate people’s 76 perceptions of accounting benefits into erp success. 5.3 limitations and future research our findings should be considered in light of several study limitations. first, our sample includes 120 respondents, 17.5% of which are enterprises that are in the stage of erp implementation and 82.5% of which are in the stage of erp post-implantation. the perceived accounting benefits may change in different stages of the erp lifecycle, which may influence its effects on erp system success. future studies may consider investigating whether a difference exists between the stages of erp implementation and erp postimplementation to provide a more comprehensive evaluation of the phenomena investigated here. second, because of time and budget constraints, the study adopted measurement scales that were originally developed in the context of developed countries. thus, the scales may not truly reflect the nature of the study’s constructs in the context of vietnam, which is a developing country. this means that the results of the present study may have been affected by potential measurement bias. this problem could have been mitigated if the scales had been more extensively augmented by additional explored items and tested qualitatively before the field survey. 6. references anderson, m. c., banker, r. d., & ravindran, s. 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(1996). beyond accuracy: what data quality means to data consumers. journal of management information systems, 12(4), 5-33. https://doi.org/10.1080/07421222.1996.115180 99 37 a risk and benefits behavioral model to assess intentions to adopt big data josé esteves 1 and josé curto 2 1 e business school, spain 2 uoc, spain email: jose.esteves@ie.edu jcurtod@uoc.edu received october 17, accepted 21 december 2013 abstract: everyday a constant stream of data is generated as a result of social interactions, internet of things, e‐ commerce and other business processes. this vast amount of data should be collected, stored, transformed, monitored and analyzed in a relatively brief period of time. reason behind is data may contain the answer to business insights and new ideas fostering competitiveness and innovation. big data technologies/methodologies have emerged as the solution to this need. however, being a relatively new trend there is still much that remains unknown. this study, based on a risk and benefits perspective, uses the theory of planned behavior to develop a model that predicts the intention to adopt big data technologies. keywords: big data, perceived benefits, risks, decomposed theory planned behavior, adoption introduction understanding the adoption of information technology (it) innovations continues to be a challenge for information systems (is) researchers (venkatesh, 2006). every aspect of society, including business and culture, is currently in the midst of a technology‐based phenomenon. advances in digital sensors, communications, mobile networks, storage, processing and cloud computing have given rise to huge collections of data, capturing valuable information to business, science, governments, and society (bryant et al. 2008, firestone 2010). by 2020, more than 2.7 zettabytes of data will be created annually reaching 35 zettabytes (idc 2011) this will call into question the ability of firms to analyze information. traditional decision‐making systems are incapable of adequately resolving this problem. therefore, companies are starting to roll out their own big data initiatives and building massive database systems to drive significant new growth in their business operations (manyika et al., 2011). although the concept of big data exists since 2001 when the meta group analyst doug laney (laney 2001) defined data growth challenges and opportunities as being three‐dimensional, i.e. increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources), only in the last two years big data has become one of the it industry’s hottest topics. in the press literature, big data is characterized as the new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high velocity capture, discovery and/or analysis (woo et al. 2011). available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2013) 37-46 mailto:jose.esteves@ie.edu mailto:jcurtod@uoc.edu https://ojs.hh.se/ 38 the big data market is expanding rapidly since many firms are expending significant resources on related projects, or are planning to. according to idc (2012), this market is expected to grow from $3.2 billion in 2010 to $16.9 billion in 2015 based on the premise that these technologies will improve operational efficiency and drive innovation. software vendors such as ibm, oracle, microsoft, emc or sap, are already providing big data services as a source of competitive advantage for their customers. big data systems are being implemented in multiple industries, including commerce, science, and society (bryant et al. 2008), but many companies still are not interested in this new trend. a big data survey conducted in june 2012 by idc found that 47% of 502 companies across different industries think that they do not need big data technologies and 25.8% of them do not see the value it can generate for their companies. simon (2010) provides a sobering statistic: three out of five big data projects do not meet expectations in terms of cost and performance. the major implementation costs are incurred during the integration of big data into the existing it framework. also, given the high level of sophistication required for big data projects (mckinsey 2011), there are some fears related to the implementation playing against adoption. all together, these facts lead to the conclusion that the market is at an early stage of adoption, hence only early adopters are betting on these new technologies. overall, big data represents a disruption in decision‐making by enabling business processes to be effectively based on information. nonetheless, the main challenge at this point is not the deployment of the technology, but rather the transformation of the culture, processes, and people within organizations. the overall purpose of this study is to explore the impact of big data technologies perceived risks and benefits in the intention to adopt them. since behavioral intention may not be reflected in actual use, this paper also examined the relationship between intended and actual use. theoretical background the academic literature on big data is still scarce. recent articles published focus more on the software, algorithms and hardware needed for big data, especially in techniques such as hadoop, while the adoption decision issues remain unattended. the initial definition of big data was composed of three‐dimensional characteristics (known as the 3vs model): volume, variety and velocity. volume refers to the need for intensive and complex processing of data subsets that actually contain information of value for an organization. variety refers to the combination of different types of data from different sources. the attribute of variety therefore alludes to the fact that data can come from inside or outside the organization, and may also be structured, semi‐structured, or unstructured. finally velocity, not all of the data in an organization has the same urgency of analysis. there is a full range of velocities: from data that can be batch processed (as in the case of data warehousing) to data that must be processed in real time (when continuous data streams need to be analyzed). the key to understanding speed in big data is to clearly identify the informational requirements of the processes and business users. in 2012, gartner updated its definition as follows: "big data are high‐volume, high‐velocity, and/or high‐variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization." (laney 2012). perceived benefits of big data there is a fourth characteristic for big data: value. in the context of big data, value refers to: (1) the cost of the technology, which has dropped to allow more companies to undertake this type of projects, and (2) the benefits generated by the use of big data (cost reduction, operational efficiency, and business improvements and new revenue streams). like any other new technologies, big data comes with benefits and drawbacks. table 1 presents a list of several key benefits and risks developed by mckinsey global institute (2011). benefits risks creating transparency by making data accessible to relevant stakeholders in a timely manner improve operational efficiency (cost, revenue and risk) use data and experiments to expose variability and raise performance segment populations to customize the way your systems treat people use automated algorithms to replace and support human decision making innovate with new business models, products, and services sector‐specific business value creation data quality talent scarcity (lack of data scientists) privacy and security concerns big data integration capabilities decision‐making organizational maturity level table 1: perception of benefits for big data 39 decomposed theory of planned behavior decomposed theory of planned behavior (dtpb) was raised by taylor and todd in 1995. dtpb is an extension of the theory of planned behavior (tpb) developed by ajzen (1988, 1991). tpb encompasses three constructs, the attitude toward the behavior, subjective norm, and perception of behavioral control – that when combined form behavioral intention. intention is then assumed to be the immediate antecedent of behavior (ajzen 2002). table 2 presents brief descriptions of the constructs used in tpb. h14. perceived behavioral control has a positive effect on actual adoption of big data. h15. intention to adopt big data has a positive effect on actual adoption of big data. antecedents of big data adoption intention based on dtpb, in our research model big data adoption intention is jointly determined by the individual’s big data attitude, subjective norms, and perceived behavioural control. thus we hypothesize: construct definition behavioral intention refers to individual’s intention to perform a behavior and is a function of attitude, subjective norm and perceived behavioral control attitude refers to individual’s positive or negative evaluation of the behavior (ajzen, 1988) subjective norm refers to individual’s “perception of social pressure to perform or not to perform the behavior” (ajzen, 1988, p.132) perceived behavioral control refers to the “perceived ease or difficulty of performing the behavior and reflects past experience as well as anticipated impediments and obstacles” (ajzen, 1988, p.132) table 2: definitions of predictors of behavior in the theory of planned behavior (tpb) taylor and todd (1995) also specified that, based on the diffusion of innovation theory, the attitudinal belief has three salient characteristics that influence adoption; relative advantage, complexity and compatibility (rogers, 1983). relative advantage refers to the degree to which an innovation provides benefits superseding those of its precursor. this may incorporate factors such as economic benefits, image, enhancement, convenience and satisfaction (rogers 1983). complexity represents the degree to which an innovation is perceived to be difficult to understand, learn or operate (rogers, 1983). the complexity construct is extremely similar, although it is conceived in the opposite direction as ‘‘perceived ease of use’’ (technology acceptance model, davis 1989). innovative technologies that are perceived to be easier to use and less complex have a higher possibility of acceptance and use by potential users. thus, complexity would be expected to have negative relationship to attitude. complexity (and its corollary, ease of use) has been found to be an important factor in the technology adoption decision (davis et al. 1989). theoretical model and research hypotheses synthesizing the theoretical background, we propose the following model (see figure 1) based on dtpb for understanding factors influencing big data adoption. antecedents of big data adoption based on dtpb, the adoption adopt big data will be determined by intention to adopt big data and perceived behavioral control. as a consequence, we hypothesize: 40 figure 1: the proposed research model and research hypotheses h11. attitude towards big data has a positive effect on intention to adopt big data. h12. subjective norm has a positive effect on intention to adopt big data. h12.1. media has a positive effect on intention to adopt big data. h12.2. social influence has a positive effect on intention to adopt big data. h13. perceived behavioral control has a positive effect on intention to adopt big data. antecedents of attitude big data requires of technologies that process and analyze large amounts of heterogeneous data within the right scope of time. these technologies includes a/b testing, association rule learning, classification, cluster analysis, crowdsourcing, data fusion and integration, ensemble learning, genetic algorithms, machine learning, natural language processing, neural networks, pattern recognition, predictive modeling, regression, sentiment analysis, signal processing, supervised and unsupervised learning, simulation, time series analysis and visualization, massively parallel‐processing (mpp) databases, search‐based applications, data‐mining grids, distributed file systems, distributed databases, cloud computing platforms, the internet, and scalable storage systems. depending on the degree of knowledge of these technologies, an organization may consider that big data is more or less easy to use. it is reasonable to infer that the perceived ease of use positively influence the company’s perceived usefulness and intention to adopt big data. therefore, we hypothesize that: h7. perceived ease of use has a positive effect on attitude towards big data. perceived usefulness is defined as the degree to which a person believes that adopting big data would enhance his or her job performance (davis 1989). therefore, we hypothesize that: h6. perceived usefulness has a positive effect on attitude towards big data also, as previously discussed, there are three main reasons to big data adoption, namely: volume, variety and velocity. thus we hypothesize: h1. volume has a positive effect on perceived usefulness towards big data h2. variety has a positive effect on perceived usefulness towards big data h3. velocity has a positive effect on perceived usefulness towards big data. as discussed in section 2.1, big data generates many potential benefits for companies such as cost control, revenue generation, risk control, decision‐ making improving, etc. therefore, it is reasonable to infer that big data technologies perceived benefits positively influence the company’s attitude and intention to adopt big data. 41 h5. perceived benefits have a positive effect on attitude towards big data. similarly, it is reasonable to infer that the perceived risks of big data negatively influence the company’s attitude and intention to adopt big data. among them: talent scarcity, organization maturity, big data internal capabilities and data quality. h4. perceived risk has a negative effect on attitude towards big data. compatibility is the degree to which the innovation fits with the potential adopter’s existing values, previous experience and current needs (rogers, 1983). tornatzky and klein (1982) found that an innovation is more likely to be adopted when it is compatible with the job responsibilities and value system of the individual. therefore, it may be expected that compatibility has a positive influence on big data adoption. the existence of information systems such as e‐commerce platforms, enterprise resource planning (erp), business intelligence (bi), customer relationship management (crm) or product lifecycle management (plm), external sources of information and the need to make decision near real‐time are factors that generate big data situations. it is reasonable to infer that compatibility has a positive influence on attitude towards big data. hence, we hypothesize: h8. compatibility has a positive effect on attitude towards big data. antecedents of perceived behavioral control according to ajzen (1988), perceived behavioral control reflects beliefs regarding access to the resources and opportunities needed to perform behavior, or alternatively, to the internal and external factors that may impede performance of the behavior. this notion encompasses the component of “facilitating conditions” (triandis 1980) and self‐efficacy (bandura 1982). in this research, we define perceived behavioral control as the degree to which external and internal factors influence, knowledge‐seeking behavior in an ekr. thus, we hypothesize: h9. self‐efficacy has a positive effect on perceived behavioral control to adopt big data. h10. facilitating conditions have a positive effect on perceived behavioral control to adopt big data. research methodology data for this study was collected using an online survey questionnaire. the participants in the survey were managers involved in big data adoption decision and usage such as cios, marketing directors, and business analytics managers. based on the list of the top 100 spanish companies firms, we contacted the users through email and/or linkedin. the questionnaire has two parts. the first considers demographic information with control variables such as the job role of the participant, size of the company, and existence of a data mining data center. the second part considers the theoretical model. the measurement items in the questionnaire were developed for the decision variables of attitude, perceived behavioral control, intention to adopt, and actual adoption by adapting the measures proposed and validated by azjen (2002) to fit the big data context. the total number of answers was 53. table 3 reports the demographic breakdown of the research sample. 42 variable sub‐category number (n=53) % business sector services 15 28.3 public sector 11 20.75 manufacturing 2 3.77 education 2 3.77 health/pharmaceutical 3 5.66 banking/finance 7 13.21 other 13 24.53 functional technology 27 50.94 area marketing/sales 7 13.21 operations 4 7.55 finance 3 5.66 top management 3 5.66 other 8 15.09 annual >10 million euros 13 24.53 revenue 10 to 50 million euros 5 9.43 >50 million euros 35 66.04 table 3: research sample demographics a sem technique was used to examine the relationships among the constructs. the partial least squares (pls) approach was chosen for its capability to accommodate small‐sized samples (chin 1998). further, pls recognizes two components of a causal model: the measurement and the structural model. additionally, pls is especially suitable for exploratory research focusing on explaining variance. given the aforementioned pls seemed particularly relevant for this exploratory study – one that is limited by sample size. construct reliability and validity table 4 shows the factor loadings, cronbach’s alphas (a), average variance extracted (ave), and r 2 values. all cronbach’s alphas exceeded the recommended minimum value of 0.7 with the exception of perceived risks variable and, all of the observed construct reliabilities (c.r.) were higher than 0.8 (fornell and lacker 1981) with the exception of perceived risks variable. all construct loadings were found to be significant at greater than the recommended p‐value of 0.05 (gefen and straub 2005) and typically exceeded the recommended threshold value of 0.707 (barclay et al. 1995) with the exception of perceived risk, perceived benefits and behavioral intention that were inferior in some constructs. average variance extracted (ave) was found to account for a minimum of 50 percent of the variance in each construct and the square root of ave for each construct was much larger than the construct’s correlation with every other construct (barclay et al. 1995; gefen and straub 2005). measurement items loaded on their respective constructs at a value of at least 0.1 greater than their loading on other constructs (barclay et al. 1995; gefen and straub 2005) and all items loaded higher on their intended construct than on any other construct. hence, it was concluded that the construct measurement items were consistent and exhibited a substantial degree of convergent and discriminant validity. 43 factor item loadings ave cronbach composite reliability r2 att att1 att2 att3 0.972 0.976 0.970 0.946 0.712 0.981 0.407 aa ‐ ‐ 1.000 1.000 1.000 0.568 pb pb1 0.838 0.475 0.812 0.859 ‐ pb2 0.524 pb3 0.653 pb4 0.459 pb5 0.609 pb6 0.848 pb7 0.790 bi bi1 bi2 bi3 0.975 0.976 0.660 0.952 0.95 0.975 0.476 com c1 c2 0.833 0.918 0.769 0.707 0.869 ‐ mi mi1 mi2 mi3 0.889 0.896 0.868 0.782 0.862 0.915 pbc pbc1 pbc2 0.859 0.898 0.772 0.706 0.871 0.706 peou peou1 peou2 peou3 0.897 0.936 0.972 0.875 0.933 0.954 ‐ pu pu1 0.861 0.789 0.933 0.949 0.283 pu2 0.926 pu3 0.897 pu4 0.931 pu5 0.823 pr pr1 0.632 0.286 0.30 0.194 ‐ pr2 0.010 pr3 0.790 pr4 0.122 pr5 ‐0.627 se se1 se2 se3 0.827 0.965 0.950 0.84 0.904 0.94 ‐ si si1 si2 si3 0.954 0.935 0.840 0.83 0.896 0.936 ‐ fc fc1 fc2 0.912 0.911 0.83 0.797 0.908 ‐ vlcty vlc1 vlc2 0.756 0.885 0.68 0.535 0.807 ‐ vlm vlm1 vlm2 0.895 0.751 0.68 0.548 0.8101 ‐ vrt vrt1 1.000 1.000 1.000 1.000 ‐ table 4: convergent, discriminant validity and reliability of measurements path analysis smartpls (version 2.0.m3) (ringle et al. 2005) was used to evaluate the statistical significance and relative salience of the research hypotheses. results of model testing indicated that the constructs included in the research model accounted for approximately 47.6 percent of the variance in the intention to adopt big data and 56.8 percent of the variance in actual use of big data (figure 2). chin (1998) notes that path coefficient values between 0.20 and 0.30 are adequate for meaningful interpretations. thus, in particular, the results provided support for the significance of eleven research hypotheses. r 2 values, which indicate the predictive power of the model, ranged from 0.28 to 0.7, indicating that the fit of the research model was acceptable. 44 figure 2: main study path model results discussion adding to previous literature on big data, the first contribution of this study is the recognition that volume and velocity are the key aspects in big data adoption and they have a significant impact in the intention to adopt these technologies. although, variety seems not having still such effect, it is expected to become an important factor in determining adoption. the logic behind is that the more heterogeneous and unstructured the data is, the higher the barriers to capture and analyze data. what is clear is as corporate systems are built into database management systems (dmbs), companies perceive volume and velocity as more urgent matters than variety. also, companies have traditionally focused more on numerical and structured data rather than working with different types of data. however, with the increasingly diversity of data, being able to manage that aspect will play a key part in companies´ data strategy. even though the traditional definition of perceived usefulness does not have an impact on the attitude toward big data, our model shows that perceived benefits have a significant impact on behavior. thus, in the subsequent/confirmatory study we plan to use perceived benefits as the construct that replaces perceived usefulness. regarding perceived risks, the exploratory results suggest that perceived risks variable and measurements need to be re‐defined. construct loadings are not statistically relevant, so we need to adjust the constructs definition. hence, the definition of the potential big data risks needs to be reviewed and perhaps extended with more risks. however, the results lead to the belief that perceived risks might have a moderate effect on the attitude towards big data adoption. finally, our results suggest that media and press news about big data have a stronger impact on the decision to adopt big data than social influences (friends and/or colleagues suggestion to adopt big data). therefore the results indicate that specific opportunities as well as challenges exist in big data technologies adoption. considerations and future work this research‐in‐progress contributes to the existing body of knowledge on big data by developing a theoretical model to explore and predict the intention to adopt big data technology. by extending the theory of planned behavior with the concepts of perceived benefits, risks and 45 perceived usefulness of big data, we seek to understand the adoption of big data. overall, our exploratory results suggest that the proposed model is a first 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(2011). big data‐big challenges. econtent, vol. 34, no. 9, pp 21. http://www.gartner.com/resid%3d2057415 http://www.smartpls.de/ journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 6–29 open access: freely available at: http://jisib.com/ competitive intelligence maturity models: systematic review, unified model and implementation frameworks luis madureira* nova information management school, portugal lmadureira@novaims.unl.pt aleš popovič school of economics and business, university of ljubljana, ljubljana, slovenia ales.popovic@neoma-bs.fr mauro castelli nova information management school, portugal; school of economics and business, university of ljubljana, slovenia mcastelli@novaims.unl.pt received 4 february 2023 accepted 22 march 2023 abstract competitive intelligence (ci) is vital for sustaining the performance of organisations in an increasingly volatile, uncertain, complex, and ambiguous (vuca) world. however, the impact of ci on performance is proportional to its maturity level. the article aims to review and integrate the existing literature on competitive intelligence maturity models (cimms) to provide a go-to framework for setting up, assessing, and developing ci. the cimms were sourced from scholarly databases, registers, the social web, and using backwards and forward searches. all the cimms respecting the characterisation criteria were included in the study. a scientific and empirically validated definition of ci guided the integration and synthesis of the fourteen selected cimms. the primary outcome is a proposed unified cimm (ucimm) covering all the ci dimensions and aspects in tandem with the respective implementation guidance frameworks. the proposed ucimm and implementation frameworks effectuate the guidance needed to set up, assess, and develop the ci practice and theory and, ultimately, the performance of organisations. keywords: maturity model; maturity levels; framework; ci function; ci system; implementation roadmap; ci practice; organizational performance 1. introduction ci is “the process and forward-looking practices used in producing knowledge on the competitive environment to improve organisational performance” (madureira et al., 2021a, 2021b). the maturity of the ci practice is positively correlated with being a learning organisation (senge, 2006). a learning organisation addresses future decision * corresponding author making proactively, effectively, and efficiently. within the contingency theory (fiedler, 1964; vroom & yetton, 1973), organisations use decision-making to achieve a strategic fit with their competitive environment (duncan & weiss, 1979). the better the decision-making, the greater the fit and the organisational performance (eisenhardt, 1989). therefore, ci maturity is both an antecedent and a proxy for organisational performance. mailto:lmadureira@novaims.unl.pt mailto:ales.popovic@neoma-bs.fr mailto:mcastelli@novaims.unl.pt 7 in the current zeitgeist of a vuca world with an exponentially increasing speed of change (bennett & lemoine, 2014), obtaining and maintaining the strategic fit to sustain top performance is the ultimate challenge. ci is thus vital to navigating highly challenging environments, remaining competitive (harkleroad, 1998; hedin, 2005; vedder & guynes, 2001), and ensuring the superior performance of organisations (yap et al., 2018, 2013; yap & rashid, 2011). the problem arises in maintaining a ci maturity level that allows organisations to deal with change. kahaner (1997) has long identified the critical change drivers as the increasing business pace, information overload, more aggressive and global competition, geopolitical changes, and rapid technological change. nassim taleb (2007) provided further insight into their volatility and unpredictability. recent academic and business research corroborates and reinforces the severity of the impact on both organisations and the ci practice (heppes & du toit, 2009; calof et al., 2017; mbrain et al., 2019; klue & scip, 2021; aci & gilad, 2022; crayon & scip, 2022). as a result, ci evolves up to the average maturity level (hedin et al., 2014; heppes & du toit, 2009; m-brain et al., 2019). organisations must be able to address these impacts in setting up, assessing, adapting, and developing the ci maturity level to obtain top performance. therefore, the cimm, consisting of several archetypal levels of achievement across the different dimensions and aspects, is a critical assessment and guidance tool supporting the ci practice evolutionary path. previous literature consists of tens of cimms. the development approaches for these models range from identifying best practices (apqc et al., 2004; calof, 1998; j. p. herring & leavitt, 2011; marceau & sawka, 1999) to assessing cutting-edge ci functions (cif), programs (cip), or systems (cis) (heppes & du toit, 2009). academic investigations (calof, 1998; oubrich et al., 2018), executive opinion (marceau & sawka, 1999), practitioners’ self-assessments (comai & prescott, 2007), and ci experts’ professional judgment vendor-sponsored studies (m-brain et al., 2019) have been the formats of choice in evaluating the professional status and developmental progress of the ci practice. benchmarking versus an independently established model (hedin et al., 2014) and case studies are the most frequently used methods (j. p. herring & leavitt, 2011). however, ci dimensions and descriptors, as well as the maturity levels used, vary considerably. most importantly, mms are not exhaustive regarding the ci dimensions and aspects. as a result, given the broad range of existing cimms, it is incredibly challenging to compare and identify the relevant model to use for improving practice or scientific research. furthermore, no cimm fully aligns with the conceptual definition of ci, its longitudinal evolution over time, or its full array of dimensions and aspects. these difficulties profoundly impact the scientific development of the ci practice, especially in smaller and less mature organisations. thus, researching a unified scientific cimm (ucimm) is extremely important for effective practical guidance to address the conflicting interests of academics, executives, practitioners, and vendors. this study aims to fill this gap by performing a systematic literature review – using an explicit, systematic method for identifying, analysing, integrating, and synthesising the findings of prior research – contributing to the conceptualisation of cimm research. this conceptualisation will allow for integrating relevant descriptors across all dimensions and levels of maturity into a holistic goto ucimm. the expected empirical contributions from such a unified model are the significant improvement of decision-making quality and the consequent business performance, the implementation guidance for the effectuation of the ci practice or function, and the increased productivity of ci professionals. furthermore, the grounding of this theory development exercise in sound theoretical and empirical evidence will highlight critical gaps and paths to exploit while dismissing outdated, irrelevant and duplicate research (webster & watson, 2002). our systematic review based on scientific, commercial and grey literature is expected to deliver on this objective. the following section details the systematic literature review procedure according to the prisma statement (page, mckenzie, et al., 2021). results will then be critically analysed and discussed, and a ucimm will be proposed in the sections that follow. finally, we conclude with implications and recommendations for application and further research avenues for this topic and the ci field. 2. literature review to identify and characterise the relevant cimms published in the last three decades, we conducted the systematic review as outlined in table 1: 8 table 1. overview of the literature review based on prisma, cooper and webster & watson guidance (cooper, 1988; page, moher, et al., 2021; webster & watson, 2002) item description scope focus on cimms as research outcomes and practices or applications from all types of literature. however, only cimms that meet the mm characterisation are within scope (cf. section 3.2). goals identify, synthesise, and integrate existing cimms into a unified holistic cimm (ucimm) to support the development of a common linguistic framework covering all ci dimensions per the 5ps (madureira et al., 2021a). perspective espousal of position in demonstrating the value of integrating existing cimms with the 5ps of ci. coverage exhaustive as it intends to be “comprehensive in the presentation of works relevant to the topic” (cimms). organisation historical in combination with cimms content analysis (cooper, 1988). audience ci scholars, ci practitioners, ci vendors, business executives, policymakers time frame cimms literature published after 1980. conceptualisation ci, mm, cimm (cf. section 2). search strategy combination and proximity of the search terms “maturity model” and “competitive intelligence” to ensure the exhaustiveness as mentioned above. sources database (db), registers, ci journals (i.e., cir and jisib), and social web as we expect to find cimms from practitioner and commercial sources. procedure data was collected, analysed, synthesised and integrated by a single author to avoid reviewer bias for approximately one year between january and december 2022. db search: google scholar, sciencedirect (scopus), ab/inform (proquest), jstor, emerald publishing, ebsco (business source ultimate). specific ci journals: competitive intelligence review. registry search: scip.org (strategic and competitive intelligence professionals). social web search: use google search to identify leading practitioner and commercial literature [i.e., ci vendors (services and technology/software) cimms]. these sources cover journals, books, conference proceedings, and practitioner sources (brocke et al., 2009). backwards and forward search: reviewing the citations found in articles from the first step; “to identify articles citing the key articles identified in the previous steps" (webster & watson, 2002). all steps: examine at least titles, abstracts, and introductions in order to evaluate only relevant sources (brocke et al., 2009). outcome the anticipated outcome is an identification of the main cimms, their dimensions, and their aspects. we followed the guidance of cooper (1988) to “combine organisations, […] by addressing works historically within a given conceptual framework.” the chosen framework is the 5ps (dimensions and descriptors) from the ci unified view and modular definition (madureira et al., 2021a). to the best of our knowledge, still “no classification system for cimms exists to date.” therefore, for the content analysis of the mms, we use a concept-centric approach based on so-called concept matrices (webster & watson, 2002). 2.1. definition of key variables and study boundaries 2.1.1. competitive intelligence until recently, the definition of ci was not consensual and changed over time, as the previous five universal definitions demonstrate (bartes, 2014; breakspear, 2013; brody, 2008; marcial, 2018; pellissier & nenzhelele, 2013). however, madureira et al. (2021a) developed a unified view and modular definition, the only empirically validated one (madureira et al., 2021b). furthermore, this definition provides the 5ps – the core defining dimensions and respective descriptors – which may be used as a proxy for assessing the comprehensiveness of a cimm. as such, we will use this working definition alongside its visual abstract as the guide for comparing and integrating the different cimms analysed in the literature review. 9 2.1.2. maturity models maturity is “the state, fact, or period of being mature” (oxford english dictionary, 2022a). as such, it implies the existence of an evolutionary process to achieve the desired end-state. a model is a simplified representation of reality used as an example to follow or imitate (oxford english dictionary, 2022b). a maturity model (mm) details the evolution levels (also known as stages or phases) of maturity across several structuring dimensions and their respective aspects. levels have differentiating descriptors providing the purpose and detailed characterisation of each level. dimensions are areas of capability that structure the object of the model. each dimension is subsequently structured into several aspects (also known as elements, activities, or measures) for each level (bruin et al., 2005; fraser et al., 2002). mms serve as guide rails to the set-up and development path to achieve the targeted maturity level (fraser et al., 2002). lahrmann & marx (2010) characterised mms as shown in figure 1. figure 1. fundamental characterisation of mms (lahrmann & marx, 2010, tbl. 1) in this regard, we will base our study on a few considerations. first, de bruin et al. (2005) guidance suggests that dimensions should be exhaustive and distinct. second, mms have single or multiple dimensions but can also be hierarchical. hierarchical mms are more complex and require a formal architecture of measures (lahrmann & marx, 2010). third, staged mm models require compliance with all the dimensions (fraser et al., 2002), the specified goals and critical practices to reach the aimed level. fourth, although we acknowledge the different mm audiences, this paper aims to provide industry-agnostic maturity recommendations. finally, the maturity level assessment can be qualitative using descriptions or quantitative using likert-like scales (fraser et al., 2002). 2.1.3. competitive intelligence maturity model ci maturity relates to the process of thoroughly developing its practice across all dimensions for each level of the model. this maturity can be computed in levels (staged model) or configurations (continuous model). considering the previous subsections, the cimm guides both the effectuation, the maturity assessment, and the improvement of the ci practice. thus, ci maturity indicates the level of development for each of the 5ps (dimensions) and respective descriptors for a predefined audience, organisation, industry, or country. notable, cimms allow economic agents to assess, understand, and improve their performance. finally, given that ci is multidisciplinary, the cimm is a broader-scoped umbrella maturity model. as such, this study considers only cimms, not business intelligence, market intelligence, data management, social intelligence, or capability maturity models (cmms), as those would be specific and not representative of the overall ci concept. 3. the cimms state of the art 3.1. literature search results the search focused on six scholarly databases (db), one register (scip.org), one specific journal (competitive intelligence review), the social web, and citation searching (i.e., snowballing). we screened all the results except for google scholar and google search, where we stopped at the saturation point, i.e., no more showing of 10 relevant or duplicate cimms. we successfully retrieved all the 38 records sought and screened for relevant cimms matching the scope (cf. table 1) and mm characterisation (cf. figure 1). snowballing – backward and forward search – allows us to identify five additional records. scholarly dbs and registers allowed us to elite eight reports while other methods identified six further. the outcome was fourteen reports included in this study (figure 2). figure 2. prisma 2020 flow diagram used for the systematic review (page, moher, et al., 2021) 3.2. overview of the selected cimms the overview goes beyond the criteria from section 2-1 by adding supporting scientific or empirical evidence and the motive supporting the development of the cimm (table 2). we included a further detailed characterisation in annex 2. a cimm is developed every year and a half in the defined 1980-2022 timeframe denoting the longitudinal importance of the topic. the cimms have 4,1 levels (computed for staged maturity principle) and 6,4 dimensions on average. they are primarily qualitative, based on case studies or surveys, and focused on assessing and improving the ci function or programmes. only one cimm (m-brain et al., 2019) is motivated by increasing the performance of organisations, which is the ultimate purpose of ci (madureira et al., 2021a, 2021b). table 2. detailed characterisation of included cimms (developed by the authors) (authors, year) citation name of the cimm dimensions maturity principle number of audiences assessment approach study / report motivation (calof, 1998) competitive intelligence quotient (ciq) multidimensional: 4 continuous to maturity (wcci) multiple qualitative report economic policy (marceau & sawka, 1999) world-class ci program in telecoms (wccip-t) multidimensional: 5 continuous single (telecom) qualitative study of telecoms practices ci program development framework (prescott, 1999) action-oriented ci program (aocip) multidimensional: 5 + 5 staged: 4 multiple: proposal management professionals focus qualitative report based on apqc 1997 best practices study improve ci effectiveness 11 (west, 2001) ci stages of development (cisod) multidimensional: 4 staged: 3 multiple: european focus qualitative report ci usage development (apqc et al., 2004) fiich model (fiich) multidimensional: 5 + 21 staged: 4 multiple qualitative study of ci best practices guide ci efforts leveraging empirical best practices (j. p. herring & leavitt, 2011) ci maturity matrix (cimmx) multidimensional: 5 staged: 5 multiple qualitative case study implement and develop ci best practices (comai & prescott, 2007) world class ci (wcci) hierarchical: 9 + 48 continuous: 1-5 multiple mixed. mostly quantitative study identify the dimensions, level and drivers for wcci (singh et al., 2008) roadmap for enduring ci success (recis) multidimensional: 11 staged: 4 multiple. additional focus on pharma qualitative study based on worldwide ci survey ensure ci success (heppes & du toit, 2009) ci function maturity level (cifml) multidimensional: 8 staged: 3 single (banking) qualitative case study establish the cif maturity level within a south african retail bank (j. p. herring & leavitt, 2011) world-class ci program roadmap (wccipr) multidimensional: 4 staged: 3 multiple qualitative report show cif evolution and promote organisational learning (hedin et al., 2014) world class mi roadmap (wcmir) multidimensional: 6 staged: 5 multiple mixed. mostly quantitative report based on own global survey guide the development of the ci function (oubrich et al., 2018) competitive intelligence maturity model (cimm-m) multidimensional: 6 staged: 3 multiple. focused on morocco. mixed. mostly quantitative report based on own local survey identify the purpose and propose a cimm to assess morocco ci practices (m-brain et al., 2019) m-brain worldclass intelligence framework (wcif) multidimensional: 9 staged: 5 multiple mixed. mostly quantitative report based on own global survey help organisations improve business performance (alvares et al., 2020) organisational intelligence maturity model (oimm) hierarchical: 2 + 17 staged: 6 multiple qualitative report understand, implement, improve, benchmark or selfassess im, km, or ci models. 3.3. cimms benchmark vis-à-vis the ci 5ps and descriptors we analysed and compared the content of the selected cimms vis-a-vis the dimensions (5ps) and descriptors of the ci unified view and modular definition scientifically validated by madureira et al. (2021a, 2021b). as such, the visual abstract of the paper (madureira et al., 2021a) provided a standardised meta-model (lahrmann & marx, 2010) for content analysis (conceptualisation, codebook creation, coding, refinement, and reliability check), guaranteeing the scientific rigour of the classification process (neuendorf, 2019). furthermore, the webster & watson (2002) conceptual-centric approach allows for the comparison between the cimm’s meta-model (dimensions and aspects) and the 5ps (purpose, purview, practices, process, and product) and underlying descriptors – table 3. in its preparation, we paid particular attention to three potential issues. first, synonymy – different names for the same dimension/aspect. second, polysemy – same name but meaning different dimensions/aspects. last, homonymy – similar names suggesting similar dimension/aspect but effectively meaning different dimensions/aspects. additionally, we needed to make several assumptions: • the tools and techniques can refer to the process or the product dimensions – e.g., analysis of competing hypothesis (ach) can either refer to the technique used in the process of analysis or the product of such analysis, the ci deliverable; • that we correctly empathised with the meaning the author intended to convey from reading the original article; • that some cimm dimensions need to be split (hence appearing in two or more columns in table 3 below) for two reasons: 1) cimms included aspects that correspond 12 to different benchmarked dimensions (madureira et al., 2021a) – e.g., the ”strategic significance” dimension from comai & prescott (2007) has aspects of three of the 5ps, purpose (usage in strategy development), purview (focus on the strategic scope), and practices (ci is included in the corporate strategy statement); 2) they refer to various dimensions or aspects in different maturity levels. table 3. integration and benchmark of included cimms vis-à-vis the unified view and modular definition of ci (madureira et al., 2021a) (authors, year) citation name of the cimm ci dimensions and (aspects) model maturity levels purpose purview practices process product (calof, 1998) competitive intelligence quotient (ciq) activities (scope) style resources activities (reporting, sources) tools 1. infancy 2. maturity/world class (marceau & sawka, 1999) world-class ci program in telecoms (wccip-t) decision-support (opportunities) culture (early warning) process (interface, location) culture (info sharing) process (key activities, interface) decision-support (options) technology (storage) decision-support (portfolio, tools techniques) technology (infrastructure) world class (continuous) (prescott, 1999) actionoriented ci program (aocip) focus location & structure (personnel) ethics location & structure (network) projects products (tar) 1. gathering 2. industry & competitor analysis 3. strategic decision making 4. core capability (west, 2001) ci stages of development (cisod) applications (anticipation) organisation applications (curiosity) data collection ci systems 1. aware 2. sensitive 3. intelligent (apqc et al., 2004) fiich model (fiich) change (performance) focus (goals & objectives) implement institutionalise change (behaviour) hone change (process) 1. prestart-up 2. start-up 3. established 4. world class (j. p. herring & leavitt, 2011) ci maturity matrix (cimmx) processes (aligned) teams tools (training) processes (culture, ethics, legal) processes (gathering, cyclic) techniques (kits, sources, analytical) products tools (techniques, tools) 1. ad-hoc 2. emerging 3. defined 4. institutional 5. optimised (comai & prescott, 2007) world class ci (wcci) strategic significance ci in sbu (vision) project selection strategic significance human resources evolution governance culture process (protocol) resources (financial) projects process (subprocesses) ci in sbu (procedure, governance) ci in sbu (portfolio) resources (system, software) 1. not started 2. some progress 3. still a lot to do 4. nearly achieved 5. fully achieved (singh et al., 2008) roadmap for enduring ci success (recis) people analysis (capability) professionalism organisational structure roles & responsibilities awareness value perception processes research analysis (insight) technology 1. stick fetching 2. pilot 3. proficient 4. world class 13 (authors, year) citation name of the cimm ci dimensions and (aspects) model maturity levels purpose purview practices process product (heppes & du toit, 2009) ci function maturity level (cifml) relationship w/ management (strategy, early warning, opportunities) deliverables (strategy) relationship w/ management (csuite) staffing skills & training relationship w/ management (decision) capabilities analytical products sources of information info requirements deliverables 1. early stage 2. mid-level 3. world class (j. p. herring & leavitt, 2011) world-class ci program roadmap (wccipr) policies (mission, alignment) uses (strategic planning, strategy, benchmark) methods (early warning, threats) professional development policies (governance, mission) people users (training) methods (future studies) uses (long-range planning) processes (cci) procedures (kits) methods (subprocesses) users (networks) sources users & uses (products) methods (products, expert systems, software) processes (value added) 1. developmental 2. professionalisation 3. optimisation (hedin et al., 2014) world class mi roadmap (wcmir) scope (purpose) scope (macro, meso, user groups) organisation culture process tools (templates, techniques) deliverables tools (ci system) 1. firefighters 2. beginners 3. coordinator 4. directors 5. futurists (oubrich et al., 2018) competitive intelligence maturity model (cimm-m) impact relationship w/ management (functions) resources structure strategy & culture system analytical deliverables capabilities ci use relationship w/ management (actionable) 1. early stage 2. mid-level 3. world class (m-brain et al., 2019) m-brain world-class intelligence framework (wcif) leadership scope (strategic objectives, opportunities, early warning) scope (external environment) organisation culture management scope (forwardlooking) process stakeholders digitalization deliverables tools 1. informal 2. basic 3. intermediate 4. advanced 5. world class (alvares et al., 2020) organisational intelligence maturity model (oimm) org. learning (capability) org. capabilities org. memory (capability) spaces info. policy culture individual vision env. scanning (practice) env. scanning (process) storage, search, recovery sharing & reusage usability (use) org. memory (storage) security org learning (process) knowledge value knowledge and info processes intel. reports usability (system) technology 1. initial 2. intermediate 3. advanced cimms w/ dimension  11 5 14 14 12 average levels: 3,9 total benchmarked aspects: 33 dimension alignment % 78,6% 35,7% 100% 100% 85,7% aspects average alignment % 30,0% 11,9% 42,9% 33,8% 31,3% (madureira et al., 2021a) competitive intelligence unified and modular definition (adapted from visual abstract for benchmarking) performance decision (specific goals, competitive advantage, early warning) competitive environment external (macro, meso, micro) internal (org. functions) org. practices capabilities (individual, organisational, structure, policies, mindset, culture) orientation (time horizon) activities procedure (processes, characteristics) knowledge nature (augmented, machine, human) outcome (knowledge management, characteristics) 14 4. discussion of findings the following sub-sections detail the findings from the integration and benchmarking exercise from the previous section. we start at the dimensional level and then go deeper into the aspects. finally, we discuss the cimms, the implications of the findings, our recommendations for implementation and the limitations of the study. 4.1. dimensions level an evident gap in the results is that, as with any strategy (rumelt, 2012, 2022), the underlying reason for the ci efforts should be the starting consideration. however, despite the need for ci practitioners to start with the end in mind, the ci purpose dimension is the second least addressed in identified cimms. a second finding is that only five cimms include the ci purview dimension and aspects. the scope is critical for the ci practice as it defines the focus and conditions the effectiveness of the activities. it is impossible to develop intelligence for the entire ci scope. in an informationoverloaded world, ci professionals must trade off the amount of big data (laney, 2001) processed vis-à-vis the (lack of) computing power and the available headspace. the considerable stream of research on key intelligence topics (kits) is proof of the importance and guidance on this topic (j. herring, 2008; j. p. herring & leavitt, 2011). surprisingly, all cimms address ci practices despite being the least mentioned dimension in the 816 definitions used in developing the benchmarked definition (madureira et al., 2021a). the importance of the ci practices for the cimm is evident since it materialises the concept. the practices and process dimensions form the core of the ci model, reinforcing each other in implementing ci effectively. the ci function location in the organisational structure (calof, 1998; comai & prescott, 2007; j. p. herring & leavitt, 2011; marceau & sawka, 1999; singh et al., 2008), the policies (namely the importance of respecting the legal and ethical aspects (j. p. herring & leavitt, 2011; prescott, 1999), the capabilities of the organisation and the individual (alvares et al., 2020; comai & prescott, 2007; oubrich et al., 2018), the mindsets (apqc et al., 2004; calof, 1998; comai & prescott, 2007; west, 2001), and the culture of intelligence (alvares et al., 2020; hedin et al., 2014; m-brain et al., 2019; oubrich et al., 2018), are the most appointed key success factors in the cimms for the development and evolution of ci (adamala & cidrin, 2011; nasri & zarai, 2013; m-brain et al., 2019; marceau & sawka, 1999). there is no surprise, though, in the complete alignment between the cimms and the ci process dimension, given that it provides the blueprint for the ci activities performed and overall output. the lower level of alignment (85,7%) towards the ci product dimension is somehow more problematic given the importance the quality of ci has on decision-making, which in turn profoundly impacts the performance of organisations. 4.2. aspects level an in-depth analysis of the aspects (and subaspects) evidence a high synonymy, polysemy, and homonymy. navigating the meaning of the aspects across cimms is extremely difficult given its number, the diverse nomenclature used, and the longitudinal evolution of the ci construct (prescott, 1999). it is almost impossible to benchmark the maturity level between ci functions, programs, organisations, industries or countries using different cimms. therefore, there is a clear need for a unified reference model with standardised nomenclature of dimensions and aspects. another important finding is the different levels of the thoroughness of the cimms regarding the aspects. on average, for any given dimension, the cimms do not address half of the aspects of the unified view of ci. again, this reinforces the need for a holistic go-to cimm with a solid scientific base that executives and academics can rely upon in theory and praxis. 4.3. cimms a significant finding is that only one cimm covers the 5ps. this insight highlights the relevance of this study, addressing the research gap for a go-to cimm of reference 15 and delivering on the expected contributions. moreover, by benchmarking the best of theoretical and empirical cimm knowledge vis-a-vis a unified and scientifically validated definition of ci (madureira et al., 2021a, 2021b), we bring a solid foundation and scientific rigour to the ci practice, the broad-spectrum ci audiences, and the related disciplines. the findings also contribute to establishing ci science, as an integrated scientifically developed ucimm will make the practice more scientific, repeatable, and comparable between organisations and industries. on top, none of the literature from the included cimms refers to the order of implementation of the 5ps. nor are the criteria for dimension selection, exceptions for best practices, or findings from case studies and empirical surveys. the level of arbitrariness can be considerable and dependent on the scope – specific country, industry, or organisation under analysis. overall, the findings highlight the essential contributions of the study. firstly, all the dimensions and aspects included in the cimms fit within the ci unified view and modular definition (madureira et al., 2021a). nevertheless, there are still descriptors of the ci definition not addressed by aspects in any of the maturity models studied. consequently, integrating the missing aspects into a cimm will guarantee that professionals do not oversee any critical aspect and a sound grounding in ci theory. secondly, there is the need for a more manageable cimm. assessing more than five dimensions can be burdensome for practitioners in a more pragmatic business setting. conveying the results to the top management is also made more difficult as the number of dimensions increases. this miscommunication with top management can endanger the allocation of further needed resources for ci, endangering its development. as such, the hierarchical structuring of all the aspects into five dimensions seems to be a valuable empirical and theoretical contribution. therefore, given previous cimm shortcomings, we propose a unified cimm in the next section. 4.4. integration of cimms into a proposed ucim we used the capability maturity model integration (cmmi) developed by the software engineering institute at carnegie mellon university to integrate the cimms (isaca, 2022). this process and behavioural model, designed to improve the performance of organisations, share the exact purpose of ci (madureira et al., 2021b), hence our preferred choice. the model aims to combine multiple business maturity models into one framework, thus additionally addressing the challenge identified in section 4-3. a model is a tool for streamlining process improvement by developing measurable benchmarks and creating a structure for encouraging productive, efficient behaviour throughout the organisation, functions, and projects. therefore, it leverages the established standards for vetting vendors and suppliers, identifying and resolving process issues, and minimising risk while building a corporate culture that supports the new integrated model. in addition, the maturity and capability levels of an organisation provide a way to characterise its capability and performance. 4.4.1. maturity levels (ml) mls represent a staged path for the organisation to improve the performance and processes efforts based on predefined dimensions and aspects. within each ml, the dimensions and aspects also provide a path to performance improvement. each ml increments the previous by adding new functionality or increased rigour. the goal is to raise the maturity of the organisation to the highest ml. once reached, organisations should focus on maintenance and regular improvements, a learning organisation. the journey starts at ml0 – incomplete – where ci work may or may not get completed. ci goals are not established, and the processes are partly formed or do not meet the needs of the organisation. in ml1 – initial – ci processes are viewed as unpredictable and reactive. ci work gets completed, but it is often delayed or over budget. this is the worst level for an organisation facing an unpredictable environment that increases risk and inefficiency. in ml2 – managed – 16 organisations achieve the project management level. projects are planned, executed, measured, and assessed, but many issues remain unaddressed. in ml3 – defined – organisations are more proactive than reactive. a set of organisational policies and standards guide projects, programs, and portfolios. organisations know their shortcomings, how to overcome them and the objectives for improvement. in ml4 – measured – the organisation starts to measure and control the business, working off quantitative data to determine predictable processes aligned with stakeholder needs. the organisation manages risk with insight-driven process deficiencies. lastly, in ml5 – optimised – the organisation processes are stable, flexible, and agile. the learning organisation status is achieved with continuous improvement and responding to changes or other opportunities in an innovative and agile way. ml4 and ml5 are considered high maturity and stakeholder and customercentric. 4.4.2. capability levels (cl) cls are used to evaluate the ci process improvement and performance of the organisation. they bring structure to the process and performance improvement. each cl builds on the last, in the same fashion as mls, for appraising an organisation. the cls range from cl0 – incomplete – with inconsistent performance and incomplete approach to achieving the intent of ci. in cl1 – initial organisations address performance issues in specific activities, but there is not a complete ci practice in place. cl2 – managed – there is a complete set of procedures that result in ci practice improvement. finally, in cl3 – defined – the focus is on achieving project and organisational performance objectives with clear organisational standards for managing ci projects. 4.4.3. dimensions and aspects based on the finding from section 4-3 that some aspects are present but do not thoroughly cover all the relevant descriptors from madureira et al. (madureira et al., 2021a), we focused on adding the missing aspects to the ucimm. furthermore, given that the 5ps and their descriptors are empirically proven, the outcome is a hierarchical catalogue (cf. figure 3) of mutually exclusive ci maturity dimensions covering all aspects replicating the benchmarked visual abstract (madureira et al., 2021a). figure 3. ucimm hierarchical meta-model – dimensions, aspects, and sub-aspects (adapted by the authors) 4.4.4. the proposed ucimm the ucimm proposed comprises five levels of maturity, three levels of capability, five dimensions, eight aspects, and sixteen sub-aspects. the ucimm is multi-dimensional, hierarchical, staged, primarily qualitative and built on the integration of previous studies. 17 table 4. the ucimm (prepared by the authors building on madureira et al. unified view of ci (madureira et al., 2021a) name of the cimm ci dimensions and (aspects) model maturity levels purpose purview practices process product unified competitive intelligence maturity model (ucimm) performance decision (specific goals, competitive advantage, early warning) competitive environment external (macro, meso, micro) internal (org. functions) org. practices capabilities (individual, organisational, structure, policies, mindset, culture) orientation (time horizon) activities procedure (processes, characteristics) knowledge nature (augmented, machine, human) outcome (knowledge management, characteristics) proposed maturity levels 0. incomplete 1. initial 2. managed 3. defined 4. measured 5. optimised following, we propose four integrated graphical visualisations (figures 4-7) and their explanation to guide and help ci professionals implement the ucimm in practice. 4.4.5. ci purpose ci aims to create value by addressing its stakeholder needs in a unique and superior way vis-a-vis its competitors. as such, organisations must continuously make decisions to adapt to the evolving context and stakeholder needs and wants. stakeholder centricity is pivotal to guaranteeing that the value created is superior to the value provided by competitor organisations at any time. optimised ci organisations support specific strategic, tactical, and operational decisions, help develop competitive advantages and provide early warning to decisionmakers. thus, the critical constructs are adaptation, agility, and anticipation. figure 4. ci purpose (developed by the authors) 4.4.6. ci purview the scope of ci is the entire competitive environment (figure 5). it encompasses the macro forces (macro-environment – outer arrows), the market forces (meso-environment – dashed triangle), the industry forces (microenvironment – industry (porter, 2008)), and the internal environment (inside the organisation – players). therefore, given its wide dimension, aligning the scope addressed by the ci function with the purpose of the organisation is paramount. most notably matching the scope to the maturity level of the ci competencies. an eventual mismatch affects the quality of ci, leading to sub-standard decisions and ultimately jeopardising the overall performance. therefore, the ci practice must start small and increase the scope as its resources and competencies develop. i ti alue proposition, fferings capabilities c mpetit alue proposition , fferings capabilities t e e eeds, ants c te t macro , meso . micro environment 18 figure 5. ci purview (developed by the authors) 4.4.7. ci practices and process the core ci model results from integrating the ci practices and process dimensions. process-wise, learning organisations continuously adapt and improve their processes, tools, and techniques to support high-quality decision-making. the activities in the middle concentric circle (figure 6) are guided by the ci procedure and executed with project management proficiency. the ci practice (and performed activities) depends on soft and hard factors: the place it occupies in the organisational structure, the policies that guide its execution, the mindsets, and the intelligence culture. the time orientation also impacts ci activities. understanding the past is not enough; understanding the present may not be possible without considering the past, and anticipating the future is impossible without previous time horizons. organisations optimising ci are forward-looking, integrating the different time horizons synergically to create a new official future (wilkinson & kupers, 2013). in a nutshell, ci needs to be an established support activity within the value chain of the organisation. c ti (country, market , channel, physical, nline) i t (product ervice) p e ( rganisation competitors) c me (consumer, customer) p itic ec mic tec e i me t ci e planning, irection esearch tructure policies rgani ational culture capabilities mindset ata information processing information nalysis eedback, measurement nowledge protection intelligence communication torage present sage ecision making ata information ccess intelligence eeds its i s 19 figure 6. core ci model: practices and process (developed by the authors) 4.4.8. ci product the output of ci outcome is a set of artefacts (deliverables, systems, or projects) produced for a given purpose, within a specific scope, through a systematic process, and a defined set of practices. given the need for anticipation, organisations must act on quality intelligence – meaning the actionable insights will be verified true (converted into knowledge) or allow for creating an official future (wilkinson & kupers, 2013). despite knowledge being the desired output, if an organisation waits for the insights to be verified true (e.g., a merger between two competitors), it will lose its opportunity to influence the competitive outcome. as such, ci has no value if the decision-makers receive factual truths. they need actionable insights. moreover, the ci functions will derive learnings from using such intelligence and converting them into wisdom. the knowledge and wisdom of today are the data points of tomorrow, allowing ci practitioners to develop new higher-order intelligence. an increasingly important factor is the augmentation of artificial intelligence by ci professionals to guarantee reduced time to insight and overall timeliness of deliverables. therefore, the ci function must not limit itself to data science or information management and should leverage knowledge management to become a learning organisation (alvares et al., 2020). figure 7. ci product (developed by the authors) 4.5. limitations and future research we purposely limited the study to cimms and excluded models focusing on ci subdomains, such as business intelligence mms, artificial intelligence mms, or capability mms. the specific models can thus be integrated for a more thorough and granular assessment, guidelines, and evolutionary path. namely, aimms can be a fruitful and valuable research avenue, given the need for guidance in this newer field within ci. another research path is the empirical validation of the proposed model, the ucimm. to this end, developing a scientifically validated scale would be essential. 5. conclusion the study successfully addressed the need to develop a ucimm for effective practical guidance addressing the conflicting interests of academics, executives, practitioners, and vendors. this study adds to existing theory by synthesising the current cimms literature, serving as a future reference for all ci stakeholders. more prominently, it expands ci theory with the first ever integrated cimm based on a scientific and empirically validated definition of ci. furthermore, it contributes to practice by identifying gaps in existing cimms dimensions and aspects, providing a thorough and scientifically sound ucimm. the model allows practitioners to pinpoint and address the areas they need to improve. t ( ignals ymbols) i m ti (processed ata) i i t i i t e i t ( nderstanding) i te i e ce ( ctionable insight) e e ( erified true) i m (best ecision) e ecti e i e e m eme t i te cti e e c e ti i te i e ce i t e i p ce i 20 the accompanying frameworks support a better assessment, implementation, and development of the ci practice in organisations, navigating the adverse impacts of continuous change. higher quality ci – timely, actionable, accurate, relevant (tar) (prescott, 1999) – should result in better decision-making and improved performance of organisations. on becoming a reference model, the ucimm will save time while guiding the effectuation of ci construct and practice, functions, systems and programmes in surpassing the average and reaching the world-class optimised level of maturity. 6. declarations 6.1. author contributions conceptualisation, lm, ap, and mc; methodology, lm; formal analysis, lm; investigation, lm; resources, lm; data curation, lm; writing—original draft preparation, lm; writing—review and editing, lm, ap, and mc; visualisation, lm; supervision, ap, and mc; project administration, lm, ap, and mc; funding acquisition, ap and mc. all authors have read and agreed to the published version of the manuscript. 6.2. funding the authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this work was supported by the slovenian research agency (research core funding) [p5–0410]. this work was supported by national funds through fct (fundação para a ciência e a tecnologia), under the project uidb/04152/2020 centro de investigação em gestão de informação (magic)/nova ims. 6.3. conflicts of interest the authors declare that there is no conflict of interest regarding the publication of this manuscript. in addition, the ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, and redundancies have been completely observed by the authors. references aci, & gilad, b. 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(2013). strategic uncertainty and firm performance: the mediating role of competitive intelligence practices. journal of information & knowledge management, 12(04), 1350028-1–14. https://doi.org/10.1142/s0219649213500287 annexes annex 1: prisma checklist table 3. prisma 2020 checklist (page, mckenzie, et al., 2021) section and topic item # checklist item location where item is reported title title 1 identify the report as a systematic review. page 1, line 1 abstract abstract 2 see the prisma 2020 for abstracts checklist. page 1, lines 4-15 introduction rationale 3 describe the rationale for the review in the context of existing knowledge. page 1-2, lines 45-13 objectives 4 provide an explicit statement of the objective(s) or question(s) the review addresses. page 2, lines 14-23 methods eligibility criteria 5 specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses. page 2, line 32 table 1 information sources 6 specify all databases, registers, websites, organizations, reference lists and other sources searched or consulted to identify studies. specify the date when each source was last searched or consulted. page 2, line 32 table 1 search strategy 7 present the full search strategies for all databases, registers, and websites, including any filters and limits used. page 2, line 32 table 1 selection process 8 specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and, if applicable, details of automation tools used in the process. page 2, line 32 table 1 data collection process 9 specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and, if applicable, details of automation tools used in the process. page 2, line 32 table 1 data items 10a list and define all outcomes for which data were sought. specify whether all results that were compatible with each outcome domain in each study were sought (e.g., for all measures, time points, analyses), and if not, the methods used to decide which results to collect. page 5, line 6 table 2 10b list and define all other variables for which data were sought (e.g., participant and intervention characteristics, funding sources). describe any assumptions made about any missing or unclear information. page 5, line 6 table 2 24 section and topic item # checklist item location where item is reported study risk of bias assessment 11 specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process. page 2, line 32 table 1 effect measures 12 specify for each outcome the effect measure(s) (e.g., risk ratio, mean difference) used in the synthesis or presentation of results. page 6, line 27 table 3 synthesis methods 13a describe the processes used to decide which studies were eligible for each synthesis (e.g., tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)). pages 6, lines 2-26 13b describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions. page 6, lines 2-7 13c describe any methods used to tabulate or visually display results of individual studies and syntheses. page 6, lines 8-10 13d describe any methods used to synthesise results and provide a rationale for the choice(s). if meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used. page 6, lines 2-7 13e describe any methods used to explore possible causes of heterogeneity among study results (e.g., subgroup analysis, meta-regression). not applicable 13f describe any sensitivity analyses conducted to assess robustness of the synthesised results. not applicable reporting bias assessment 14 describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases). not applicable certainty assessment 15 describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome. page 6, lines 2-7 results study selection 16a describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram. page 4, lines 25-26 – figure 2 16b cite studies that might appear to meet the inclusion criteria, but which were excluded and explain why they were excluded. page 4, lines 25-26 – figure 2 study characteristics 17 cite each included study and present its characteristics. page 5, line 6 table 2 risk of bias in studies 18 present assessments of risk of bias for each included study. page 6, line 27 table 3 results of individual studies 19 for all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimates and its precision (e.g., confidence/credible interval), ideally using structured tables or plots. page 6, line 27 table 3 results of syntheses 20a for each synthesis, briefly summarise the characteristics and risk of bias among contributing studies. page 6, lines 10-26 20b present results of all statistical syntheses conducted. if meta-analysis was done, present for each the summary estimate and its precision (e.g., confidence/credible interval) and measures of statistical heterogeneity. if comparing groups, describe the direction of the effect. page 6, line 27 table 3 20c present results of all investigations of possible causes of heterogeneity among study results. not applicable 20d present results of all sensitivity analyses conducted to assess the robustness of the synthesised results. not applicable reporting biases 21 present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed. not applicable certainty of evidence 22 present assessments of certainty (or confidence) in the body of evidence for each outcome assessed. page 6, lines 10-26 discussion discussion 23a provide a general interpretation of the results in the context of other evidence. pages 8, lines 3-6 3b discuss any limitations of the evidence included in the review. pages 8, lines 7-16 23c discuss any limitations of the review processes used. page 6, lines 10-26; page 13, lines 13-19 23d discuss implications of the results for practice, policy, and future research. pages 8-13, lines 8-10 other information 25 section and topic item # checklist item location where item is reported registration and protocol 24a provide registration information for the review, including register name and registration number, or state that the review was not registered. not registered 24b indicate where the review protocol can be accessed, or state that a protocol was not prepared. not prepared 24c describe and explain any amendments to information provided at registration or in the protocol. not applicable support 25 describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review. page 19, lines 9-14 competing interests 26 declare any competing interests of review authors. page 14, lines 15-19 availability of data, code, and other materials 27 report which of the following are publicly available and where they can be found template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review. pages 14-17, lines 21-24 annex 2: cimms further detailed characterisation table 4. visualisation and description of included cimms (developed by the authors) citation cimm name visualisation description (calof, 1998) competitive intelligence quotient (ciq) ci is about skills development, process, and structural and cultural change. the ciq is the maturity level resulting from advancing style, activities, resources, and tools from infancy to maturity/world class ci (wcci). building a competitive organisation requires its leaders' clear commitment and involvement, usually taking at least five years of committed effort from senior management to create a wcci capability. a ci competencies list (from scip) is offered to support the development of the practice. (marceau & sawka, 1999) world-class ci program in telecoms (wccip-t) the model presents five development planes as prerequisites and critical success factors to achieving a world-class ci: corporate culture (conducive to information sharing); straightforward interface (relationship and location of the ci within the organisation); relevance and extent of the ci portfolio of services; decision-making support (throughout the company); technical infrastructure (aggregation, organisation, and diffusion ci). the audience is the telecom industry-leading global players, and critical stakeholders were the object of an interviews study for the development of the model. (prescott, 1999) action-oriented ci program (aocip) this model is based on the analysis of the evolution of ci to identify its key dimensions and levels. the dimensions and aspects (ten) are based on identified main attributes and the key decision areas from the decision-oriented approach to designing a ci program. the latter is based on the 1997 study on ci best practices from apqc. the main objective is to improve the effectiveness of ci while presenting a business case for proposal management professionals. the model adds additional value by identifying key defining events and issues in the evolution of ci. (west, 2001) ci stages of development (cisod) the model assumes that organisations move through three stages of ci evolution across four dimensions: data collection, applications, organisation, and ci systems. the model has three levels. first, competitor awareness key competitors are known, some knowledge exists, the organisation rarely uses data for decisionmaking, and there is no ci systems in place). second, competitorsensitive aware of competitive threats, relies exclusively on informal information flows, and there is still no structured intelligence program. third, competitor-intelligent organisation anticipate competitive actions and events, dedicates serious resources, and has a specific location with the structure and systems to support the ci function. the model aims to understand the drivers and support the development of ci in europe. the book offers further insight into the probability of using ci depending on the need for development capability and the ability to use it in practice. 26 citation cimm name visualisation description (apqc et al., 2004) fiich model (fiich) the development of a ci program (cip) proceeds through four stages: prestart-up, start-up, established, and world-class. each stage of development has an identifiable set of critical activities or indicators that allows a company to know its level and transition activities to the next stage of the ci program development. the model is based on the premise that cips can be characterised by their stage of development and that identified external and internal factors may cause reversals to earlier stages — if not the failure of the cip – must be examined. the model offers a methodology to evolve across dimensions into more advanced stages: focus (clear set of goals and objectives); implement (organisational culture); institutionalise (incorporate ci practices); change (modify processes, behaviours, and performance); hone (dynamic, evolving, continuously improving activity). this empirical study provides a comprehensive understanding of what it takes to have a successful ci functional unit. based on years of research of leading-edge organisations – supported by examples of best practices and tips from actual practitioners — it intends to guide readers in their own ci efforts. the study also aims to influence the academic community in researching the role of an intelligence function in decision-making theory. (j. p. herring & leavitt, 2011) ci maturity matrix (cimmx) the matrix is based on a six-month study of the core of the entire value chain processes to optimise the ci of the enterprise. a later benchmark in best practices determined that it was ineffective to continue to be ‘everything to all people.’ consequently, the group reassessed its ion and audience and focused primarily on providing ci to support enterprise-wide strategic decisions and research new market potential. as a result, the author developed the ci maturity matrix in early 2006 to serve as a roadmap to achieve a ci process that provided more value to the enterprise. the matrix is five stages per five dimensions description of best practices to develop mature ci practices. (comai & prescott, 2007) world class ci (wcci) the structure of the wcci model identified nine dimensions subdivided into 48 aspects. the authors prepared a statement describing what the judges believe to be a world-class performance for each dimension and its accompanying aspects. the modes were defined so that their statements apply regardless of how the cl function is organised in the strategic business unit (sbu). the authors defined "world-class" not as "the best that currently exists" but as "the ultimate best that might be achieved”. the nine dimensions are: 1) strategic significance (recognised importance of cl defining the scope and level of cl activities); 2) ci in the organisational structure (clear operational vision between ci & the sbu); 3) ci culture (organisational culture allows ci contribution to be maximised); 4) & 5) people and physical resources (necessary for ci effective functioning); 6) ci process (clearly defined and well established for gathering, validating, analysing, and storing ci); 7) ci project management (systems in place for selecting and prioritising ci projects); 8) management control (clear processes in place for top-level management control of cl operations); 9) evolution of the ci unit (clearly defined evolutionary strategy for how the cl vision is to be achieved). the measurement scale to identify the development level is 1) we have not started this yet. 2) we have made some progress but still have a long way to go; 3) we have achieved a lot but still have a lot to do. 4) we have nearly achieved this but still have some work to do; 5) we have fully achieved this. the study aims to answer four research questions: what are the dimensions? what are the main dimensions? what are the milestones and relationships between them? what are the best ways to achieve wcci? 27 citation cimm name visualisation description (singh et al., 2008) roadmap for enduring ci success (recis) the recis results from the evolution of two reports and a study to ensure the success of ci activities in an organisation. the selfdiagnostic framework (sdf) (singh & beurgschens, 2006) provides value by describing the current stage of your program’s development per attribute (dimension). the column with the most checks is where the organisation is in terms of ci development level (stage). this tool is a starting point to begin the analysis of the ci capabilities of an organisation by determining at which level it is and defining how it can be improved. the survey and white paper from fuld & singh (2007) explored the critical success factors of ci programs (cips) across the globe. using the exact eleven dimensions and “ our intelligence tages” from the , it developed a more scientific and more profound assessment of the state of the ci discipline. a roadmap emerged from the two-year study where 141 worldwide companies examined and assessed their intelligence efforts (fuld & singh, 2007). capability attributes are the key building blocks to developing a fully operational intelligence and competent ci function capability. the phases of development are the milestones for developing your function. the aim is to accelerate ci improvement as an individual, a team, or a function. note: this study was based on a self-assessment test submitted via a web survey. fuld & company did not interview or audit each respondent after submitting the survey. (heppes & du toit, 2009) ci function maturity level (cifml) heppes identified the typical evolution of a world-class ci capability typically as spanning three significant stages; 1) early-stage (providing facts and creating ci awareness | less than 1,5 years of operation); 2) mid-level capability (identifying trends and implications from gathered data, within an emerging partnership with ci users | operational between 1,5 3 years); 3) world-class (ci regarded as a key component of company strategy | more than three operating years). these stages evolve across seven dimensions: 1) ci function (cif) deliverables and capabilities; 2) analytical products; 3) relationship with management; 4) staffing of ci function; 5) ci skills; 6) sources of information. the overall aim is to establish the level of maturity of the ci function. this study focused on identifying the maturity level of ci for a south african retail bank. (j. p. herring & leavitt, 2011) world-class ci program roadmap (wccipr) the roadmap shows where the ci program (cip) is now, the vision of where the organisation wants it to be, and the steps needed to get there. the roadmap organises a cip in three-time stages: 1) developmental (first 1-2 years), 2) professionalisation (3-5 years), and 3) optimisation (6+ years). the developmental stage is critical to building a world-class professional program (wccip) from the onset. all dimensions must be identified and put in place over the first two years to develop a strong foundation. the professionalisation stage requires formidable effort to enhance the collection and analysis methods while advancing intelligence policies and procedures requires experienced intelligence expertise. once these essential functions and processes are established, the next set of tasks is to professionalise those operations and the individuals who produce and apply the intelligence. the optimisation stage is the final stage in becoming a wccip. the real challenge is to maintain the level of organisational performance for years afterwards. the scip-iri study found that the average age of worldclass programs was about eight years. the vertical axis contains the four functional dimensions that form the core of all ci programs: 1) users and uses; 2) people and their professional development; 3) sources and methods; 4) the policies, processes, and procedures that bring the program altogether and ensure it runs smoothly. following is a descriptive discussion of the twelve boxes on the herring-leavitt world-class ci program roadmap. the choice of a roadmap framework for the wcci model shows the evolution of the worldclass process over time and, most significantly, promotes organisational learning. 28 citation cimm name visualisation description (hedin et al., 2014) world class mi roadmap (wcmir) the world class market intelligence roadmap (wcmir) incorporates intelligence development into an evolutionary process. the authors identified five levels of growth from the start to the world-class level and six key success factors (ksf) that move the program through those growth levels. the role of the ci manager is different for each of the five levels of the intelligence evolution roadmap. the same applies to all six key success factors (ksf): the further the program advances through the various levels, the more sophisticated process it needs. combining the six ksfs with the five stages creates a 30-box matrix. each box describes a ksf relevant to each of the development steps. to grow the ci function, organisations need to implement the appropriate measures. reviewing the development roadmap, one can identify the present status and what is necessary to move ci up a level. the roadmap can also help determine the ci function’s future objectives. ver time, most ci functions should reach the intermediate level, where the basic intelligence processes are in place. however, several specific issues arise at that level and must be addressed before the organisation can move toward the advanced and world-class levels. the framework is based on research conducted during 20052008 with 700 companies, and their input has been used to verify the roadmap concept. in addition, many companies have empirically tested the concept. (oubrich et al., 2018) competitive intelligence maturity model (cimm-m) the maturity model proposed is based on a comprehensive review of recent literature. the objectives of this study are threefold: 1) determine the significant purposes of a cimm, 2) identify the ci dimensions and levels of maturity, and 3) evaluate moroccan ci practices. the conceptual framework articulates the ci dimensions and three maturity levels. the six ci dimensions are ci culture; ci deliverables; ci sourcing; ci cycle; ci investment in resources; ci users; and ci application). implementing these dimensions determines the position across three levels: early, mid, and worldclass. the model was tested through an empirical study conducted in the moroccan context. the results show that most moroccan companies are in the early stage of ci, using environment scanning in a not-so-intense competitive environment allowing for the absence of a ci structure. however, most of these moroccan companies are not able to cope with changes in the business environment as ci systems and processes are implemented on an irregular basis. (m-brain et al., 2019) m-brain worldclass intelligence framework (wcif) m-brain´s intelligence framework (m-bif) expands the hedin et al. wcmir to help organisations achieve three benefits: better and faster decisions, time and cost savings, and organisational learning and new ideas. this is achieved by a systematic strategic market and competitive intelligence operation. results are measured against and plotted on the matrix of nine key success factors of an intelligence organisation (ksf) against five increasing levels of ci professionalism. the m-bif framework distinguishes five maturity levels from level 1 beginners or “firefighters” to the most advanced evel 5, the “futurists” and orld class intelligence organisations. the supporting survey gives the international ci community a good picture of the global average and world-class intelligence functions. in addition, the results offer in-depth information about the size of intelligence teams, their place within the organisation, available budget, number of stakeholders and contributors to intelligence (for co-creation) and much more. in concrete terms, the survey results are used by many companies to benchmark, set aspirational goals and develop roadmaps with implementation plans. (alvares et al., 2020) organisational intelligence maturity model (oimm) the organisational intelligence maturity model (oimm) presents the condition of dependence between information management (im), knowledge management (km), and ci to demonstrate that im and km are associated with the ci maturity level. the results from exploratory qualitative research based on a literature review show that im is the foundation for km, which, in its turn, supports and enables ci. this confirms that the maturity level as a series of onedimensional linear stages is also applicable to the organisational intelligence expanded model. the result is a matrix of 2 categories and 17 dimensions across the three stages (im, km, and ci) and six 29 citation cimm name visualisation description levels (non-managed/individual, structuring/group, formative/integration, effective/creation, analytical/network, and proactive/full). the study aims to explain business development relative to the progression from im to km and ci maturity levels to understand, implement, improve, benchmark or self-assess im, km, or ci models. journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 65–75 open access: freely available at: http://jisib.com/ artificial intelligence and morality: a social responsibility anuradha kanade school of computer science anuradha3279@gmail.com dr. vishwanath karad mit world peace university, india sachin bhoite school of computer science sachin.bhoite@mitwpu.edu.in dr. vishwanath karad mit world peace university, india shantanu kanade india shantanukanade@gmail.com niraj jain united states jainn@uwp.edu received 12 march 2023 accepted 23 march 2023 abstract both the globe and technology are growing more quickly than ever. artificial intelligence's design and algorithm are being called into question as its deployment becomes more widespread, raising moral and ethical issues. we use artificial intelligence in a variety of industries to improve skill, service, and performance. hence, it has both proponents and opponents. ai uses a given collection of data to derive action or knowledge. there is therefore always a chance that it will contain some inaccurate information. since artificial intelligence is created by scientists and engineers, it will always present issues with accountability, responsibility, and system reliability. there is great potential for economic development, societal advancement, and improved human security and safety thanks to artificial intelligence. keywords: artificial intelligence, morality, ethics, intelligence, accountability, social responsibility 1. introduction we already have artificial intelligence (ai), and many of its applications are currently in the early stages of development. whether, if  corresponding author ever, other, far more sophisticated kinds of ai, such as superintelligence, will exist, is a matter of debate. many people believe that the development of superintelligence is inevitable; there are the typical 66 disagreements on when it will arrive as well as whether we should welcome it and why. in the discussions over whether we will ever construct ai that has awareness and that is sufficiently complex and in the correct ways to merit our moral concerns and protection, philosophical and technical disputes overlap. one of the burning subjects of the twentyfirst century is the ethical issues raised by artificial intelligence (ai). the use of robots in dangerous situations is one of the many alleged possible advantages of ai, which also includes operational enhancements such as a decrease in human error (for example, in medical diagnosis) (e.g., to secure a nuclear plant after an accident). ai also brings up a number of ethical issues, including grave safety and health problems, algorithmic unfairness, and the digital divide. artificial intelligence (ai) ethics is a discipline that has emerged in response to the growing concern over the potential consequences of ai. artificial intelligence can be used in a wide range of fields and in several contexts within a single field. in the field of medicine, artificial intelligence (ai) may play a role in computerised patient diagnosis or in algorithms that analyse massive amounts of data from hundreds or millions of patients to better understand the nature of disease and health. it might provide automated or online responses during patient consultations and even therapeutic sessions. ai may be used in robotic surgery help for difficult and sensitive procedures. it might be connected to mobile technology that informs individuals about their own illnesses or remote health monitoring. it might provide nursing and care along with robotic companions or aides. robots are being used to help autistic persons learn social skills. robotic dogs are being created to offer dementia patients companionship and mental stimulation. robotic limbs are being created, along with tools that will help people with locked-in syndrome and other illnesses interact. 1.2 ethics or morality the concept of ethics is difficult, nuanced, and confusing. the moral principles dictating a person’s, or a group of people's conduct can be referred to as ethics (nalini, 2019). in other words, ethics are a system of principles, standards, or laws that help individuals make moral decisions. ethics, in general, is the study of good and evil as well as the moral roles and responsibilities of people and groups. there have been more high-profile instances of harm brought on by either technology misuse (such as voter manipulation using psychometrics, surveillance using facial recognition, bulk data gathering without authorization, etc.) or technology design defects (e.g., bias in cases of recidivism, loan denial, and medical misdiagnosis, etc.). what characteristics ethical ai have? or anything in general that is ethical? practically speaking, being ethical entails abiding by and upholding moral principles and doing what is "the right thing to do," as well as not harming others. instead of addressing the issue of whether something is lawful, ethics address the issue of what is right and wrong. an artificial intelligence (ai) is said to be ethical when it is developed on moral principles and with the goal of enhancing society rather than just maximising financial gain. responsible ai refers to the development of ai that preserves the principles of equity, openness and explainability, human-centeredness, and privacy and security. in our opinion, the study of ai ethics is still in its infancy and is a subset of the larger area of digital ethics, which examines the moral questions raised by the development and use of cutting-edge technologies like blockchain, big data analytics, and ai. 2. literature review because ai's versatility and wide range of uses are one of its most noticeable features. it has been noted that a technological capability is hailed as ai until it is implemented, at which point, in the words of john mccarthy, the computer scientist who coined the phrase "artificial intelligence," claiming that "as soon as it works, no one calls it ai anymore" and that its definition is problematic. it might be difficult to distinguish what constitutes true ai from other types of technology. some ai systems are so deeply ingrained in modern technology that we hardly even notice them. 67 this also means that, in many instances, it is difficult or impossible to determine which ethical and other value dilemmas are brought by ai and other technology. ethics has a long history, which is a reflection of its enduring importance to human life, whereas ai has only recently experienced significant growth. yet during the past decade or two, the power and promise of ai have grown incredibly quickly. brings to light the critical necessity of addressing the numerous ethical challenges it raises. we might be living in a world in a few years when a large number of the decisions that affect our lives—from the financial markets to transportation, from health care to military operations—are either made by ai systems or heavily influenced by them. 2.1 concept of artificial intelligence in the presence of experts from many fields, john mccarthy (1970) discussed and introduced the phrase "artificial intelligence" at the summer workshop organised by the dartmouth summer research project in the year 1956. artificial intelligence is the study and application of science and engineering to the development of intelligent devices, particularly intelligent computer programmes (ai). mccarthy reportedly chose artificial intelligence because of its objectivity, that the machine can be constructed and used to replicate the attribute of intelligence which is specified clearly. the term ai is such a broad field, it cannot be defined by a single definition. according to blackman (2022), artificial intelligence is defined as "a computerized system that demonstrates behaviour that is usually assumed to require intelligence." 2.1.1. background of ai it is unknown who started working on artificial intelligence technology first, however, it is said that alan turing was the first as there is a record that states that he has deliver lectures on artificial technology in 1947 he was a mathematician by profession during world war ii selfmotivated people started voluntarily working on the artificial intelligence machines as mentioned by muller (2020) and additionally, turning is said to be the first to express his opinion as programming is more powerful than building machines. by the late 1950s, numerous researchers were relying on ai, and the majority of them were built on computer programming. christopher strachey made a significant step forward in 1951 when he created the first artificial intelligence software. although mathematician alan turing had previously published the most well-known work, "computer and machinery intelligence," a year prior, the naming ceremony for "artificial intelligence" was slated for 1956. he posed the query, "can machines think?," to everyone. he also put the techniques to the test as he put up the idea that computers may be trained to learn much like a young child. he wanted to know the solution to this problem. by developing the first artificial intelligence programme in 1951, christopher strachey accomplished a tremendous advancement. he created computer programmes for checkers games that are played on manchester's ferranti university's mark i computer. also, until 1952, they made a few little adjustments before speeding up the programme. they were finally able to show off the better game in the summer. the initial artificial intelligence software to operate in the us was a checkers program developed for the ibm 701 prototype in 1952. arthur samuel took over the essential elements of strachey's checker's program and considerably expanded it over the course of several years. in 1955, he developed features that enabled the software to absorb experience. samuel made his program better by incorporating tools for rote memorization and generalization. as a result, in 1962, the programme won one game against a previous connecticut checkers champion. a lower number of volunteers and more issues made the next years difficult for ai, but things began to improve at the beginning of the 1990s. the worldwide situation was becoming more discouraging, and artificial intelligence challenges were outpacing solutions. 2.2. why do ethical issues with ai keep popping up? 68 one of the most incredible and frequently made allegations is that ai poses a "existential threat" to humans. some claim that an ai may evolve vigorously and spontaneously, much like a cancer that is exponentially smart. we may start out with something simple, but intelligence evolves in ways that are out of our control, according to muller (2020). the struggle for survival will soon involve the entire human race why do so many people hold diametrically opposed opinions about the possible advantages and dangers of ai? hollywood is to blame, as is so often the case. we can take the example of films like the matrix into consideration. the ai in these drawings, however, is portrayed as intelligent, supremely powerful, and in control of either a military arsenal or invulnerable robots. yet, ai as we currently understand it is just a collection of complex computer algorithms. given the state of technology, the vast majority of clichés about ai consuming the world are therefore untrue. following are the main reasons that are causes for raise in the ethical issues. i. manipulative ai: the private sector had the chance to monetize user data properly, but instead decided against it. as a result, it is now the responsibility of the federal government to ensure that manipulative ai practices are stopped. the government learned from the creation of antitrust laws when it realized the risks associated with select businesses dominating and controlling markets. as a result, legislation was passed to promote free competition and safeguard consumers from predatory business activities. when it comes to ai-driven online data collection, the same needs to happen. information that will help them profile people was provided by facebook cambridge analytica (2022). numerous businesses will profit financially by using artificial intelligence to investigate user biases. the user may develop an addiction as a result of adopting artificial intelligence strategies. one might come across this use case in the gaming and gambling sector. another example is the current facebook analytica controversy from the 2016 us election, which used voter behavior as a lever to change the outcome. ii. privacy: ai technology must priorities respecting people's rights to privacy and information, and consumers must be given unequivocal assurances regarding the handling and security of their personally identifiable information. protecting their privacy. data about an individual should always be the main factor considered while gathering, analysing, exchanging, and interpreting data. by defining data access, ownership, and permission, it is done. research on privacy have typically concentrated on governmental organizations, but over time, the term privacy has been widened to cover any individual, group, or detective. i. c. education (2021) states that although technology has advanced and had a big impact over time, government rules have not changed much. because of this, new technologies like artificial intelligence are still open to abuse by powerful groups or individuals. the rate of digitization is accelerating faster than expected. today, every document and piece of personally identifiable information is digitized. every information gathered, whether knowingly or unknowingly, is accessible online. also, many sensors produce a variety of data on people. the potential for clever data collecting and analysis is increased by the application of artificial intelligence. a security-related agency or agent will then begin to monitor you as a result. as a result, agents share information in exchange for payments. pesapane, tantrige, et al. (2020) stated that the information they gathered in exchange for a free service was user information, which is extremely valuable when compared to their prices. for instance, facial recognition technology can be used to recognize a person from a collection of images or videos, allowing for the building of a digital profile of that individual. iii. lack of transparency: the "black box" designs, which hide the reasoning behind each ai decision, are a branch of the decisions made by artificial intelligence. it brings up the issue of machine-human trust. the fairness metric disappears, excluding people from the decision-making process. it raises the issue 69 of systemic prejudices. moreover, data is used by artificial intelligence systems. the truth of it is unknown. it merely predicts patterns based on previously discovered patterns. muller (2020) guarantees that adding quality data into decision-making processes will increase their quality, but there is still a long way to go until artificial intelligence is sufficiently sophisticated to distinguish between good and bad input. winikoff and sardelik (2021), for example, claimed that when apple debuted its new credit card, artificial intelligence was used to tack on interest to the user. women were charged a higher interest rate than men, which was seen as discriminatory. 2.3. necessity of morality or ethics in ai? in the above section, we have seen the causes for the rising of the ethical issues in the field of ai. in this section, one must understand the need of morality or ethics to be followed practicing ai. to include ethics into artificial intelligence, following issues must be resolved. 2.3.1. privacy: the users' psychological, emotional, intellectual, physical, and digital safety should be protected by maintaining information security, say the ai now institute (2022) and blackman (2022). in order to reduce security risks and boost user confidence in system outcomes, platforms incorporating ai-powered technologies need to be constantly guarded against potential attacks. 2.3.2. accountability: transparency is required for technical decisions to be held responsible. every choice should be explained to the parties concerned so they can understand why it was made. according to the ai now institute (2022) and blackman (2022), accountability enhances the likelihood that organizations or people will guarantee the successful implementation of artificial intelligence systems they design, develop, operate, or deploy over the course of their lifetime, in complete compliance with their obligations and applicable laws and guidelines, and will demonstrate this through their actions and suggestions. 2.3.3. freedom: the global level of living shouldn't be threatened by technology. it could harm freedom since individual can be tracked and profiled based on certain beliefs and actions. 2.3.4. since it is difficult to know how a model arrives at a certain result, the term "black box models" is widely used to characterize machine learning methodologies, particularly deep learning models. human-readable explanation of the machine's reasoning this level of transparency is required to build learners' trust in artificial intelligence systems and ensure that they can understand why a model comes to a particular result. 3. ai ethics what should ethical ai look like is one of many questions. the simplest definition of ethical ai is that it shouldn't harm people. yet, what harm? how are human rights implemented? before creating moral ai, these questions must be resolved. training in ethical sensitivity is required for moral decision-making. theoretically, ai should be able to recognize moral ambiguities. how can we make ethically conscious decisions if ai is capable of doing so? unfortunately, it's difficult to understand and put into practice. it necessitates consistent, continual work. nonetheless, recognizing the significance of creating ethical ai and beginning to work on it gradually are huge advancements. companies like accenture, microsoft, google, ibm and atomium-eismd are just a few that have begun developing ethical guidelines for the advancement of ai. the feat principles for the application of ai were published in november 2018 by the monetary authority of singapore (mas), amazon web services, and microsoft. fairness, ethics, accountability, and transparency are represented by these tenets. the framework for creating ethical ai is shown in fig. 1. this framework makes it possible to create and use ethical ai. to establish ethical standards for the conception, advancement, and use of ai, it is critical for academics, practitioners, and policymakers to work together. to ensure 70 ethical behavior, protective boundaries are needed with the frameworks and concepts. regulatory organizations must close a legal loophole in order to ensure the use and observance of such ethical principles. whether they are based on case law or carried out through responsibilities described by siau and wang (2020), these legal and regulatory tools will be crucial for the good governance of ai, which helps to implement and enforce ethics of ai to enable the establishment of ethical ai. figure 1. ai ethics: framework of building ethical ai (wang and siau, 2020) 71 4. organization working on ai morality despite the fact that privacy and data engineers and data scientists are not primarily concerned with ethical standards, certain associations have emerged to advance ethical behavior in the artificial intelligence field. some well-known ethical organizations focusing on ai ethics are listed below. 4.1. algorithmwatch: according to hagendorff (2020) and tags, algorithmwatch is a non-profit research and advocacy group devoted to monitoring, examining, and evaluating the effects of automated decision-making (adm) systems on people (2022). algorithmwatch's goal is to make sure that algorithmic systems are used to benefit all people, not just a small number of individuals. they start promoting algorithmic systems that defend democratic institutions and the rule of law, favoring autonomy over surveillance, civil rights over racial discrimination, independence over power in place of dictatorship, dynamism, justice, and equality in place of prejudice and partiality, and a sustainable way of life in place of an unethical way of life. 4.2. ai now institutes: the mission of the ai now institute (2022) is to conduct multidisciplinary research, engage the general public, and ensure that artificial intelligence systems may be applied in a range of social contexts. as per them, we must collaborate with those who will suffer the most from the use of ai to create standards and procedures. this will lessen harm and guide ethical ai deployment. the present research of this institute focuses on privileges and rights, employment and discrimination, and inclusivity and architecture. 4.3. darpa: the defense advanced research projects agency of the us department of defense (2022) encourages investigation into and creation of understandable ai. for more than 50 years, darpa has been a leader in the creation of ground-breaking technologies that have facilitated the deployed rule-based and statistical learning-based ai technologies. according to hagendorff (2020) and the center for human compatible artificial intelligence, the creation and application of "third wave" ai systems will allow computers to learn new information using generating circumstances and descriptive models. 4.4. chai: "center for human-compatible artificial intelligence", a group of universities and institutions working together, is committed to advancing trustworthy ai and technologies that have a clear positive impact. the goal of chai is to lay the conceptual and technical groundwork for a shift in ai research's emphasis towards systems that could be perceived as demonstrably helpful. a number of situations and ultimately, it appears that computers are becoming far more powerful than living things as a result of ongoing ai research. according to hagendorff (2020) and home nscai (2021), some of these solutions may have unwanted and possibly long-lasting effects for humans because the solutions produced by such systems are fundamentally unforeseen by humans. 4.5. nascai: an oversight committee named “national security commission on artificial intelligence", considers the means and methodologies to accelerate the advancement of ai, ml, and supporting technologies in order to fully address the needs of the united states' national security and defense. according to agarwal, gans, and goldfarb, section 1051 of the john s. mccain national defense authorization act established the national security commission on ai as a separate committee on august 13, 2018. (2016) 5. government’s overnment’s initiative for ethics in a normally, the government is responsible for ensuring that the ethics are upheld through the regulation of laws and the formulation of policies that take into account societies. the national government as well as the 72 international governments are making great efforts to develop the laws and regulations in light of the developing technology and its use cases. some non-governmental organizations are working side by side with the government to draught rules to ensure that ai is used ethically. the following are the actions made by various governmental organizations, according to herbert (2022). • the us government began developing an ai policy during the presidency of barack obama. their government published two reports on the impacts of ai. the white house designated the nist to work on the rules for the government's involvement in ai in a note the "american ai initiative" in 2019. • once more in 2020, the trump administration provided the draught of its "guidance for intelligence applications" policy. the strategy was primarily concerned with investing in the ai industry, with a project aimed at fostering confidence in ai software and addressing privacy concerns. • new york city passed legislation in december 2021 that forbids new york-based businesses from using ai techniques for personnel screening unless they first check the technology for bias. in january 2023, the law will take effect. employers must inform candidates if an ai tool is used to decide who to hire. • the provision for the act "right to explanation," that includes a set of legislation in the general data protection regulation act of european union proposed in 2018 that deals with ai and data protection. in other words, people have the right to ask for the information they possess and how it is used. 5.1. level of ethical ai figure 2. levels of ethical ai 73 the impact of various factors, including the professional behavior of developers and users, organizational governance of these individuals, and judicial oversight of both individuals and organizations, results in ethical ai. second, there are three basic stages to the ai lifecycle, each of which must be finished before the subsequent step can start. these phases are as follows: data management includes the following steps: i. data collection, ii. best security measures used to protect data, iii. data cleaning (including pre-processing and augmentation as necessary), and iv. data reporting an ai model is trained using a dataset, and its performance is then tested using test datasets, reported, and verified. stakeholder participation, user-centered design, and model deployment in the actual world are followed by updates, ongoing validation, supervision, and auditing. 6. discussion the direction in which we might lessen the harmful effects is also important. because artificial intelligence lacks the emotional intelligence necessary to assess societal impacts, political contexts, or cultural contexts, researchers from a variety of professions must examine distinct community complexes in order to reduce the possibility of biases in extraordinary scenarios. for instance, due to bias against race, google's photo recognition programme mistakenly identified black humans as gorillas. political and societal ramifications were also seen. we might need to revise our hypotheses since artificial intelligence is routine, just like it is in our everyday lives. we may create the structure for appropriate regulatory and a code-of-conduct that will supervise and control, transparency, liability, and responsibility by investigating and researching this topic. second, there is still another issue that needs our attention: how artificial intelligence makes decisions. artificial intelligence needs to be able to justify its choices in terms of moral principles. but the adaptive nature of artificial intelligence presents a challenge. it's possible that the programmer won't be able to predict every decision that artificial intelligence will make during testing and in the future. even while this might be the case, it might damage user confidence in the ai system. one vehicle that uses ai is the tesla model s. according to pizaro, figueroa, lopez, et al., it features a system called traffic-aware cruise control (tacc) that causes it to hit with a van parked on a european highway, injuring the van's owner (2022). the owner had faith in the ai software and anticipated that the automobile would stop, but it did not act as intended. from the outset, it would seem that artificial intelligence ethics is a science that reduces the likelihood of immoral outcomes in the artificial intelligence. yet, a closer examination shows that this intuition is incorrect. it's true that there are a few worries, either from ethicists themselves or from the effects of their involvement in ai groups. these risks are connected to psychological problems with limited ethicality in the ethicists themselves, problems with how people react to (or disregard) ethical principles and advice, the difficult professional role of ai ethicists, the ineffectiveness of ai ethics guidelines, or the potential negative effects of ethics audits for ai products. so, this comment is not intended to downplay the importance of ai ethics. instead, it seeks to enhance introspection and, thus, the discipline's efficacy. the comment also highlights how harder it is than it seems to put ai ethics into reality. it's possible for thoughtful ethical concerns to have unintended, unsuspected effects that, if judged independently, would be viewed as unethical. these undesirable results should be avoided in order to make ai ethics a discipline that can uphold its own standards. conclusions a recent technological development is artificial intelligence. it is widely used across many industries. in the end, it impacts human beings' principles, morality, and ethical ideals 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https://www.shrm.org/hrtoday/news/all-things-work/pages/regulations ahead-on-artificial-intelligence.aspx [accessed oct. 2022] http://www.darpa.mil/work-with-us/ai-next-campaign http://www.darpa.mil/work-with-us/ai-next-campaign http://www.nscai.gov/ http://www.shrm.org/hr-today/news/all-things-work/pages/regulationshttp://www.shrm.org/hr-today/news/all-things-work/pages/regulationshttp://www.shrm.org/hr-today/news/all-things-work/pages/regulationso p i n i o n s e c t i o n 62 ict lifecycle and its major role in the development of strategic intelligence francisco carlos paletta, nilson dias vieira junior cidade universitária, brazil e-mail: fpaletta@ipen.br, nilsondv@ipen.br received december 18 2012, accepted 6 august 2013 abstract: in this article, we focus on the role of information and communication technologies ict to create additional sources of competitive advantage that can help companies to prepare themselves for sustainable growth. first, we discuss the dynamics of icts and the ability to generate innovations with a direct impact on business. then we present the need for greater balance between goals of short and long term on it projects. in the third part, we discuss how these new technologies have helped to increase the productivity of information professionals as well as to enhance the decision-making process and the satisfaction of the end customer. to conclude, the main challenges that the technology-based companies will have to face in relation to the management of the lifecycle of their technology, is consolidation and simplification of their processes within their computing environments, aiming to increase productivity and develop agile environments that allow the organizations to meet the demands of managing digital information. keywords: competitive intelligence, information technology, innovation, it lifecycle introduction for many organizations, the increasing availability of technologies has shown an ambiguity in their management. the management and support of these complex and heterogeneous environments full of different pcs, desktops and laptops, mobile and wireless devices, printers, networks and applications have demonstrably proven difficult and expensive for the departments of information technology. according to oecd (2002), information and communication technologies (icts) play important and growing role in world economy, and companies, industries and governments are getting increasing benefits from their continuous investments in icts, as well as available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2013) 62-78 mailto:fpaletta@ipen.br mailto:nilsondv@ipen.br https://ojs.hh.se/ o p i n i o n s e c t i o n 63 from a wider use of the internet in a knowledgebased economy. icts have stimulated innovation in services, increased the efficiency of production and creation, and at the same time, facilitated the management of inventories and administrative costs. it was a catalyst of changes in companies, improving the organization of work, helping companies to reduce the cost of their routine transactions and streamlining their supply chains. so crucial, icts, especially when associated with the raise of the level of skills and organizational change, apparently seem to support the improvement of productivity within enterprises, both in new sectors and in traditional branches. such benefits have long term effects and will continue to develop, despite the difficulties and challenges with which companies are facing today. many new applications of information and communication technologies have a potential meaning and may have economic and social impacts, as well as a key role in the bonding and in the convergence of the various technologies. among these emerging technologies are the ubiquitous networks, which enable monitoring of people and objects as well as tracing, storing and processing of information in real time. applications such as radio frequency identification (rfid) and other technological sensors are being used in applications for commercial use. the technology of prevention and warning of natural disasters are becoming more important for reducing the impacts of disasters which result in large economic losses. the participatory web (web 2.0) is the active participation of users on the internet, creating contents, they adapt the internet and develop applications for a wide variety of fields. the digital content represents an important factor in the ict industry. technological innovation and demand of new consumers are leading to new forms of creation, distribution and access to digital content. the convergence in applications such as convergence of nanotechnology, biotechnology, neurotechnology, robotics and information technology, probably, will provide more opportunity and challenges for companies operating in the sector (oecd, 2006). based on this scenario, this article proposes to examine the critical factors that should be considered by technology-based companies in managing the lifecycle of their resources for information technology with a focus on organizational performance. information and communication technologies icts at the world summit on the information society (wsis) held in geneva in 2003, countries and regions were invited to develop tools to measure and monitor progress toward the "information society", including basic indicators of information and communication technology – ict. the summit marks the start of a geopolitical process led by the united nations and the international telecommunication union. therefore, a crucial period in terms of multilateral negotiations that might lead to a new level of global governance of digital networks, guided by the quality of the indicators of inclusion, digital access or connectivity (fapesp, 2004). digital convergence among telephony, internet and telecommunications (radio and tv) foresee changes of great magnitude and depth not only in behaviours and human institutional relations, but also in the patterns of connection among the infrastructures of all sectors of the economic social life. "these changes have as a determining factor the development of information communication technologies operated by means of interactive digital networks" (fapesp, 2004). in a search of measurement held by the united nations (un) in 2004, 179 countries received the questionnaire. in latin america and the caribbean, more than half of the twenty countries surveyed have no formal definition for ict; six countries implemented some sort of definition and there are developing one (un, 2005). according to the report, information technology (it) can be summarized as a set of all activities and solutions provided by computing resources and, with applications related to several areas. information technology is also commonly used to denote the set of non-human resources dedicated to storage, processing and communicating information as well as the mode of how these resources are organized in a system capable of executing a set of tasks. it is not limited to equipment (hardware), software (software) and data communications. there are technologies for the planning of computing, for the development of systems, for the support, for the software, for the processes of production and operation and for the support of hardware. the acronym it covers all activities developed in society by using the resources of computers. o p i n i o n s e c t i o n 64 living in the scenario of research and development of icts, the perception of the revolutionary character and a unique set of problems in the field of measurement, interpretation and, therefore, decision-making (fapesp, 2004). comparative statistics on access and use of ict are critical to the formulation of policies and strategies for the growth of ict, aiming at social inclusion and cohesion to monitor and assess the impact of ict on the economic and social development (un, 2005). ict indicators and e-commerce in the telecommunications industry voice remains the main driver of the telecommunications markets of member countries of the oecd, which yields millions of dollars. the mobile services make up 40% of all income from telecommunications in the region of the oecd, and subscribers to mobile services go beyond those from fixed network at a rate of three to one (3:1). at the same time, technologies such as voice over internet protocol (voip) make strong pressure on prices for voice services. broadband has become the dominant technology for internet access at the oecd; 60% of the 256 million of internet subscribers have broadband connection. providers of cable services often offer data and voice, while mobile service companies complement those offerings with packets of data and video, and traditional telecommunications providers offer similar multiple products on networks (oecd, 2007). a basic and practical form of referring to e-commerce is used by the internet management committee in brazil (cgi, 2007): "purchase or sale of goods or services by means of computer networks, based on internet protocols or other networks mediated by computers." the definition does not take into account the competitive advantages resulting from the combination of the participants of supply chains and value (the people involved in the flow of goods, services, money and necessary information to bring the products from raw materials to the hands of consumers). in that sense, e-commerce includes any business that takes place directly between business partners or customers through a combination of computing and communication technology (luciano, 2003 apud trepper, 2000). electronic commerce is causing intense changes in the organization of companies as well as in their relationship with customers, partners and suppliers, inaugurating a new era in world business. behind the simple and apparent change in the way of buying, there are changes in the economy, industry organization, legislation, jobs, forms of consumption, relationships and value creation (luciano, 2003). according to viotti and macedo (2003), in brazil, in 1999, the segment b2b (“business to business", or commercial transactions between companies) had a revenue of 50.4 billion dollars, against 30.1 billion segment of b2c (“business to consumer", or company with final consumer). nearly half of the people who have used the internet said that they have conducted searches in price of goods or services in the net (45%) in 2007, while only 16% reported to have finalized a purchase through the web. the data shows that the internet has consolidated itself as a tool for comparing costs and surveying the availability of goods and services, even if the process of finalizing the purchase of the product does not happen through it (cgi, 2007). according to the brazilian chamber of electronic commerce (2005), the revenue from ecommerce in brazil had nominal growth of 400% over the past five years. moreover, a survey commissioned by the board e.net shows that between 2003 and 2004, the value traded by ecommerce, among businesses and brazilian consumers, represented 4.22% of total trading done in brazil. figure 1, with e-commerce data from brazil (20012005), and figure 2 with data from world ecommerce (1999-2004), compare brazil's position in relation to the other countries surveyed. the industry in brazil should reach the mark of 2.8 billion reais in 2010, according to study conducted by forrester consulting (cecb, 2005). evaluating the data in graphs, it is possible to have a vision of the sums involved and of the status of e-commerce in brazil and in the world. o p i n i o n s e c t i o n 65 figure 1. e-commerce in brazil 2. e-commerce in the world (source: brazilian chamber of electronic commerce) internet and ict in brazil and in oecd the ict sector is one of the most dynamic in trade of goods and services in foreign direct investment focused on exports, mergers and acquisitions, particularly in telecommunications. in 2003, more than 14.4 million people were employed in the area of ict in oecd countries, or 5.5% of the workforce: five million in manufacturing and 9.5 million in services (oecd, 2006). the trade in ict has expanded rapidly in the 1990s, growing more than 20% in 2000. in 2001 there was a slowdown, and a decline in demand was heavy, with a strong recovery in 2003 and 2004. growth had remained steady in the same values in 2005 and, for 2006, it was expected to maintain the same rates in the production, with higher growth in some segments, especially in trade with developing countries like china (oecd, 2006). csillag and graeml (2005) sought to evaluate the intensity of use of the internet and other it tools; their impact on the processes and activities of companies between 2001 and 2004; and the intention of adopting the tools in the next three years. the sample comprised 665 companies from the database of the federation of industries of são paulo state, since the state accounts for 36.6% of the jobs of brazilian industrial sectors and 49.1% of the national industrial transformation value (itv). the results show that many tools adopted abroad are underused in brazil. although most companies have their own site, the use is basically as a window of products, without generation of revenue. electronic commerce, for example, is little explored, and conferences through the net and chat rooms are almost absent from the organizational environment, although they are promising tools for communication among professionals in the company, suppliers and customers. at least 20% of companies participating in the research of csillag and graeml believe that the internet and other technologies of information were responsible for considerable change in most of its processes and activities in the past three years. it was also verified that almost three quarters of large companies already try to obtain responses from customers through the site, and half use them to after-sales service. according csillag and graeml, this suggests that the industry is discovering that provide the best service for customers can be a powerful argument to differentiate the product from the competition and gain a competitive advantage. another positive point is the increased interest by e-procurement, corporate tool used for shopping on the internet. furthermore, the literature cited by the authors show that the dominance of institutional sites is not in itself a setback for e-commerce, as it might seem. according to them, institutional sites tend to be a test for commercially-aggressive sites, as well as the purchase of non-productive materials by the internet tends to be a test for the purchase of productive materials, which is more central to the business. the internet and the rapid expansion of mobile telephony have transformed the segment of communications equipment in one of those which had the fastest growth in ict since 1996, with exports from oecd countries having doubled between 1996 and 2000. the biggest exporters were korea, germany and the united states. it equipment form the largest market for ict, with one third of the total negotiated, and korea and 0 500 1000 1500 2000 2500 2001 2002 2003 2004 2005 r$ millions 0 100 200 300 400 500 600 1999 2000 2001 2002 2003 2004 b2c (u$ billions) o p i n i o n s e c t i o n 66 ireland are still the largest producers (oecd, 2006). in brazil, the liberalization of the ict market in the early 1990s had greater impact on the sector of information technology; changes in telecommunications happened later, with the general telecommunications law (viotti & macedo, 2003). table 1 shows, via "hosts", the growth of internet in brazil, whose index is high even when compared to developed countries. table 1. expansion of the internet in brazil and in the world (jan./1998 and jan./2008) maps of countries by number of hosts (isp's) jan./1998 jan./2008 1st united states* 20.623.995 1st united states* 302.884.146 2nd japan (.jp) 1.168.956 2nd japan (.jp) 36.803.719 3rd united kingdom (.uk) 987.733 3rd germany (.de) 20.659.105 4th germany (.de) 994.926 4th italy (.it) 16.730.591 5th canada (.ca) 839.141 5th france (.fr) 14.356.747 6th australia (.au) 665.403 6th china (.cn) 13.113.985 7th netherlands (.nl) 381.172 7th australia (.au) 10.707.139 8th finland (.fi) 450.044 8th netherlands (.nl) 10.540.083 9th france (.fr) 333.306 9th brazil (.br) 10.151.592 10th sweden (.se) 319.065 10th mexico (.mx) 10.071.370 11th italy (.it) 243.250 11th united kingdom (.uk) 7.727.550 12th norway (.no) 286.338 12th poland (pl) 7.134.976 13th spanish (.es) 168.913 13th taiwan (.tw) 5.121.607 14th switzerland (.ch) 114.816 14th canada (.ca) 4.717.308 15th denmark (.dk) 159.358 15th finland (.fi) 3.728.551 16th new zealand 169.264 16th belgium (.be) 3.618.495 17th korea (.kr) 121.932 17th russia (.ru) 3.577.635 o p i n i o n s e c t i o n 67 18th brazil (.br) 117.200 18th sweden (.se) 3.513.170 19th belgium (.be) 87.938 19th switzerland (.ch) 3.308.684 20th south africa (.za) 122.025 20th denmark (.dk) 3.256.134 * (.edu, .us, .mil, .org, .gov, .com, .net e .info). source: network wizards in 2007, the internet reached 17% of the total of brazilian homes, representing a growth of 3 percentage points over the previous year. broadband connections are already present in 50% of brazilian houses that have internet access, but 42% still connect to the network primarily by traditional modem access via dial. in 2006, dial access was predominant, with 49%, while broadband connections accounted for 40% of the types of home access. the growth of broadband in the period was, therefore, by 10 percentage points (cgi, 2007). risks and benefits of investment in it when it happens, the collapse in it projects takes two forms. the first pattern of failure is marked by a lack of consensus on objectives and lack of confidence in the it business of the company. managers are hesitant to invest in major projects in it, which results in lower budget for the area. in another standard, the it and the businesses of the company align themselves, and it spending remains stable, but the managers resists investing in something that is not intimately connected with the immediate needs of application in the business the infrastructure becomes obsolete, the common basis of data does not grow and the system becomes complex and fragile. since the collapse in it has been avoided and confidence restored, companies must remain vigilant. the alignment between it and business foundation is important and requires constant adjustment to keep it in the right direction. (westerman, 2007) the performance of the largest companies in ict in recent years shows broad recovery from the sharp decline and recession that began in 2000 and was until 2002. software, services and it equipment have been growing consistently, but the conditions were much more challenging for business of communications equipment. the corporations need to find a balance between the extreme of not innovate in any way and lost opportunities and only innovation and increase the risk and expense (fujitsu, 2002). the 250 largest companies in ict had revenue of three trillion dollars, nearly 570 billion more than in 2000, with average growth of 4% a year since then. the 250 largest firms employ 10 million people worldwide, with spending on r & d around 135 billion (6.3%) in 2005 (oecd, 2006). figure 3 shows the market share of each sector of ict in 2005. http://www.isc.org/ds o p i n i o n s e c t i o n 68 figure 3. revenue per sector from 250 largest companies in ict (2005). source: oecd, 2006 a 2003 survey of ibm business consulting services with 150 companies based in brazil with their internal customers show, among other things, the need for greater balance between goals of short and long term projects in the it (lozinsky, 2003). below are the findings of ibm study, together in six broad aspects. • strategic planning: the area should help with questions about the viability of corporate strategies and propose new solutions and alternatives, cannot do strategic planning without any support from it. • balance between short and long term: the pressure to reduce costs in the short term cannot eliminate r & d, under risk of the company failing to meet the challenges imposed by the competitive environment. it is up to individual abilities of each element of the value chain, without necessarily bearing all the costs and risks of these activities. • governance: it is necessary to professionalize and classify the decisionmaking processes and provide the commitment, setting priorities for investment, monitoring it contribution to business as well as the correct capture and allocation of the costs of the department to the areas which use them. • measuring of value: the area of it needs to demonstrate results that can be understood by managers, which requires assessment systems in structured financial metrics and non-financial, internal and external, to assess the past and the prospects for the future, quantifying the benefits not only the cost of the activity of it. • it relationship with users: it must find a new way of interacting with internal clients, capturing expectations and surpassing them. • sourcing: issues such as strengthening the relationship with a limited number of suppliers, standardization of items of equipment, renegotiation of supply contracts and review of procedures for the management of assets are rarely addressed in an appropriate manner in relation to it. they are not problems of managing it, but it management. for most who write and talk about governance and management of portfolio of investments in it, there was no such significant changes in these techniques to justify imagine problems that are distinct from those it equipaments 18% eletrônics and components 34% comunication equipments 6% it services 6% software 3% telecomunicationsserv ices 33% o p i n i o n s e c t i o n 69 originally discussed by them. people, relationships, communication, planning and control must always be in the foreground. scenarios of ict digital content has become a major driver of the ict industry. technological innovation and new consumer demand are leading to new and direct ways of addressing the creativity, new methods of distribution and improvement in access. research results, for example, are becoming more accessible, and digital content is invading various sectors, for applications that may be more significant than the others for entertainment (oecd, 2006). continuous improvements in technology, networking, software and hardware, including cellular and wireless service and protection of content and services, have made possible the development of advanced digital content. greater cooperation is a major challenge, since the production of digital content requires agreements between content developers, equipment manufacturers and distributors. this successful implementation requires efficient services and low cost in infrastructure and technologies to protect content. issues of compatibility and interoperability must also be resolved (oecd, 2006). significant number of companies wants to provide resources so that customers can track the progress of their orders through the internet (49.8%) over the next three years. that was one of the trends revealed when the study of csillag and graeml (2005) investigated the future intention towards the use of technology. the e-procurement (41.8%), the extranet to suppliers (41.1%) and customers (44.4%), crm (45.8%) and electronics recovery (41.2%) are areas where major changes are expected. in research by day and hubbard (2005), with 352 executives about the impact of the internet towards the ability of managing customer relationships, the reduction of costs in acquiring new customers was the most important variable for managers. however, the fact that customers can enlarge the field of action, compare prices quickly and eliminate transaction costs using the internet, does not mean that they will abandon their current supplier. only 3% of companies felt that a major factor threatening, while 14% saw it as an important opportunity. the possibility of reducing costs of customer service (self-service) was the second most important factor in the opinion of respondents, which reflects changes in the goals of crm projects that fail to seek an increase in revenue in order to contain costs. the responses to the 2005 oecd questionnaire (2006) about policy on information technology indicate that government policies are mainly aiming at: • the coordination and priority setting and general direction of policy in it and its contribution to wider goals of economic policy; • the promotion of innovation in the field of it; • the dissemination and use (with emphasis on electronic government egov); • jobs and expertise in ict; • digital content; • business environment for ict (with emphasis on intellectual property rights); • strengthening the infrastructure (particularly broadband). the term "broadband" is usually associated with internet connections for high-speed cable. however, in recent years, companies started offering mobile phone services in large-band cellular network. an oecd study of 2006 found nearly 30% of mobile carriers offering 3g data connection, of third-generation (oecd, 2007). the ability to leverage the potential of the technology is becoming increasingly critical to the success of organizations. the main tool to acquire this ability is to develop an effective organization of it, focusing on three key areas: • definition of an organizational structure appropriate to the services and technological environments of the company; • development of processes and skills to centralize critical functions; • model of governance structured to facilitate the alignment of service with responsibility for it personnel. o p i n i o n s e c t i o n 70 focus on it lifecycle management the consolidated management of the working environment of it requires that technology-based companies adopt a holistic approach directed to people, processes and technology throughout the computing environment. it also requires that organizations work with suppliers of it that can analyze their operational needs, assisting the implementation and ongoing management and support of the solutions implemented. according coex (2005), the basic challenges that organizations face in the computing environments include: reduction of costs – the environments for customer service are moving quickly to mobile search locations, virtual and global, culturally diverse, which are expensive to maintain and support. through the consolidation of hardware, applications and support processes within their working environments, organizations can manage and reduce it costs, while simultaneously improving the return on investment. increased productivity of professionals of information to achieve this goal, organizations are seeking ways to improve collaboration and teamwork by creating a work environment without borders, reliable and secure, providing the connection and access to information anytime and from anywhere. reducing the complexity of it the lack of standardization within the computing environment can increase the time and cost required to manage and support this environment. at the same time, as the computing environments become more complex, the level of knowledge and expertise needed to support them increases. the tools for managing the it lifecycle allow the standardization of the hardware platform; reducing redundant devices; simplifies and automates the computational processes; besides managing the support functions and building flexibility and stability that allow the creation of a dynamic management of digital information. the management of the it infrastructure becomes increasingly expensive and complex. studies indicate that more than 50% of all costs of it are allocated to configure, upgrade, migrate and manage resources (o'brien, 2002). according to silver (2003), the largest expense of ownership of it resources is not the initial purchase of hardware and software, but the complexity of implementing and maintaining these devices. to reduce these costs, organizations need to invest in management software systems to improve reliability and availability of hardware and software, through all phases of a resource lifecycle. figure 4 shows the main stages of it lifecycle management. o p i n i o n s e c t i o n 71 figure 4. it lifecycle management (source: altiris). when evaluating a tool for it lifecycle management, it is imperative to consider the following relevant features of the solution (silver, 2003): • management of the lifecycle of it assets via web; • identification and physical location of assets; • physical and logical setting hardware devices and software; • monitoring of the use of software and hardware; • management of maintenance contracts for hd (hardware) and sw (software); • increased productivity of users, it professionals and network devices; • resolution of problems ensuring the availability of resources and services; • diagnostics and real-time information for decision-making; • modular structure with flexible deployment; • integration via web with database and repositories of information; • technical support and training of the user. as stated by browm (2005), best practices for managing it should allow adequate treatment to the complexities associated with the management of it resources. the systems must be modular, allowing the definition of a technological structure compatible with the computing needs of the organization. resource management, mobile equipment and servers the increasing complexity of the technological assets has encouraged it managers to seek ways to improve efficiency in the operation to reduce costs, adhere to the regulatory aspects and meet the constant demands of organizations for a better response from the department of it. these factors have been a booster so that it managers seek efficient ways to take control of everything that exists in their network. according to rockart (1996), the eight requirements for an organization of it to achieve operational excellence and maximize their performance are: o p i n i o n s e c t i o n 72 1. getting strategic alignment of "two hands" between it and "operation" • to be an effective strategic alignment between it and business, it should occur in "two hands": the staff of it should have a greater understanding of the operation and, concomitantly, the company's executives must keep in mind the potential that it has to "leverage" or even change the business. 2. develop effective relationships between it and operation. • as the line managers are key users of it applications, there should be a close and continuous relationship between them and it staff, at each level of the organization. • successful priority systems and close relationship leads to a better understanding of the operation and a cyclical process of progress and successes. 3. deliver and deploy new systems. • big change in the process of developing systems. the internal development of transactional systems for greater outsourcing, integrating information focused on re-engineered processes. • users less tolerant about long delays in development, inflexible interfaces and over-budgets. • placing of high-level line managers in the leadership of the projects, increasing the responsibility of future users with the system. • external development and "packages" (for example, the "packages" erp enterprise resource planning): faster and less expensive alternative of deployment. • manage this process is very different than in the case of external development. 4. build and manage the infrastructure  need for an infrastructure (in terms of computers, telecommunications, software and data) that enables the provision and integration of information throughout the network and for the re-engineered processes. • important for a “globalized” operation. basic points for this infrastructure: 5. re-train (reskill) the it organization • need of it staff be re-trained in new ways and methods of development, such as client-server architecture, new languages and communication protocols. • training in skills and knowledge of the business itself, since it is increasingly important and ubiquitous in all organizations. how to promote this training is not consensus among businesses yet. 6. manage partnerships with suppliers  outsourcing: is the alternative to supply deficiencies of certain skills in it, especially those that are not core competencies or competitive differentials.  in addition to any economy, would allow high it directors to focus their attention where is strategic.  the implementation and administration of outsourcing demand skills that permit to distinguish when a strategic partnership is being done or simply a business transaction. 7. develop high-performance.  the area of high-performance it should: seek operational efficiency, either in development or in the internal outsourcing.  in the search for efficiency, often it follows trends in the area of manufacturing, such as tqm (add up to iso9000 for software development).  a concern in the area of it should be the time for development: information systems should be deployed as soon as possible (today, delays of two or three years are no longer acceptable), so they are not obstacles to the deal. 8. re-design and administer an it organization o p i n i o n s e c t i o n 73  the question "centralization vs. decentralization" culminated in the organization.  a central it organization to do the planning, allocation of resources and shopping with economy of scale, some autonomy for local businesses to seek their specific solutions.  with this structure, one can get the alignment with the business, economy of scale and integrity in systems architecture. figure 5 illustrates the modularity necessary for the development of the it infrastructure, necessary for the deployment of a solution for the management of assets. figure 5. management of resources, clients, mobile equipment and server. (source: altiris inc.) according to brown (2005), an integrated solution for the management of assets combines the disciplines of management resources and services of the digital company in a single architecture based on the web, repository and console, helping to unite various departments and processes. to actively manage the entire lifecycle of resources, the solution helps organizations to eliminate unnecessary costs for software and hardware, to proactively manage contracts with suppliers and align the resources of services with itil (information technology infrastructure library), to ensure optimization of it investments. the benefits include: • monitor the configuration, the implemented versions, the relationships and historical information of it resources; • monitor the use of software and hardware for relocation and negotiation of contracts; • ensure the availability of resources through the management of incidents and problems. the management of clients and mobile equipment allow administrators to implement, manage and troubleshoot systems from anywhere. the benefits include: • consolidated management of desktops, notebooks and handhelds; • implementation of the os (operating system) migration and personality of the pc with zero intervention; • comprehensive inventory of software and hardware with the generation of reports over the internet; • assessment of the vulnerabilities of the system with software distribution and patch management in real time; o p i n i o n s e c t i o n 74 • management states through the resources of auto correction and reversal of applications. the management of servers offers the functions of implementation, management and monitoring from a centralized console, reducing the total cost of infrastructure. the benefits include: • improve the reliability and stability of servers, minimizing downtime of the digital company and improving user satisfaction; • automate the management of it operations to respond quickly to changing needs of the digital company; • monitor the performance, restore the operation and minimize the security patches to ensure the continuity of the operation. it managers need to be increasingly involved in development, control and monitoring technology assets of their organizations. the constant pressure to keep the efficiency in it investments shows that it is priority to manage these assets in two ways: as a function of the it department as well as an integral part of the organization. it management should be focused on allowing them to obtain the full potential of technology, working in four main areas: alignment with the business and services, management of complexity, strategic outsourcing and capture of value (brown, 2005). the ability to leverage the potential of technology is becoming increasingly critical to the success of small and medium enterprises. the main tool to acquire this ability is to develop an effective it organization, focusing on three key areas: the definition of an organizational structure appropriated to the business and technological environments of the company, the development of processes and skills to centralize some critical tasks, and a model of governance structured to facilitate the alignment of those responsible for service with the team of it (brown, 2005). to support these organizational changes, it also needs a strong cultural change: the information technology needs to be perceived as a competitive lever and managers should feel responsible, together with it professionals, by incorporating the technology in the services strategy. the supports of high direction, as well as the recruitment of professionals with the appropriate profile, are essential elements for achieving the change (schwaber, 2007) figure 6 shows how information technology is involved with all operational procedures of the company and, increasingly, is affecting the ability to offer services influencing the efficiency, quality of customer service and innovative capacity. figure 6. it maximum potential (source: bain & company). developing the it organization and structuring its relationship with the areas of services is the main instrument to build skills in it. analyzing the organizational models of companies that stand out in the use of technology, we point out best the practices on three key aspects to an effective recovery of projects for it management of new projects it strategy aligned to the business it organization rationalization of the it architecture outsourcing of it and business processes negotiation of contracts o p i n i o n s e c t i o n 75 organization of it: defining the most appropriate organizational structure, functions and the critical competencies that should be centralized and governance for investments in technology (ramirez, 2003) conclusions to conduct, effectively, the lifecycle of assets in it is no longer an option, it is essential. regardless the type of asset, organizations need to understand, at least the minimum, of what was purchased, what is its value and where it is allocated. the solutions for managing the it lifecycle include a combination of policies, processes, technologies and resources to use, monitor, serve, manage and update the hardware and software assets effectively. the increase in the number of servers and pcs, the mobility trend reflected in a longer list of equipment (laptops, cell phones, pdas, among others), exponential growth of data centre, as well as the number of departments within a company, contribute to a greater complexity in the administration of it assets (coen, 2004). additionally, organizations suffer strong pressure to meet the needs as: • reduction of the total cost of ownership (tco) of assets through the optimization of procedures for the purchase, implementation, monitoring and administration; • to manage the relationships between people and assets, by simplifying the it workloads, human resources and finance departments; • to simplify the process of updating software; • to ensure good follow up and monitoring of licenses and other contractual arrangements; • accelerate the service and the support through proactive alerts, thus simplifying time and effort of it administration. the solution for managing it lifecycle is organized on three levels over a model of maturity, as the needs of computing resources (figure 4). o p i n i o n s e c t i o n 76 figure 7. maturity model (source: altiris) to manage the it assets with greater precision and integration, offers greater operational efficiency and greater control and simplification of computing resources (coen, 2004). aware of this need, the it managers need to align the company's digital strategies with the policies of deployment and use of information technology as essential considering the following items: • what are the challenges faced and the paths followed by the organizations? • what are the services offered to customers with the implementation of the practice of managing the it cycle? • how to manage purchasing decisions and processes of it assets? • how to develop predictive information and a real-time view of it assets to improve the level of service, security and the use thereof? • how to keep a consistency and control of costs at a deeper level of user / department? • in what degree is your organization and what steps should it follow to optimize its practice of it asset management? the use of digital technology is evolving toward comprehensive solutions to manage it using a single repository and a single interface, dramatically reducing the costs and complexity of managing their resources, including desktops, thin clients, laptops, handheld devices and networks, all essential for a well function ci system. it is essential to automate, simplify and integrate their functions to manage it from a single console-based web. innovations in it continue to emerge in a frenzied pace, driven by the rapid advancement of technology for semiconductors. information is key assets of businesses in the postindustrial era. the correct investment in it has been pressured for tangible and sustainable results o p i n i o n s e c t i o n 77 and the management of it resources is essential to corporate success (paletta, 2008). the vision of management of it assets, however, needs to be expanded at a higher level of functionality and processes, since administering assets throughout the lifecycle involves much more than counts them to reduce costs. and to manage the physical assets and software within an organization requires an approach from the technological point of view to business processes. references altiris. gerenciamento do ciclo de vida de ti. disponível em: < http://www.altiris.com >. acesso em: 22 set. 2008. brown, a.b. a best practice approach for automating it management process. ibm: research division, 2005. câmara brasileira de comércio eletrônico. relatório final – vertical ebusiness 2005.disponível em: <http://golden.softex.br/portal/softexweb/uploa ddocuments/e-business.doc> acesso em: 18 set. 2008. cgi – comitê gestor da internet no brasil. pesquisa sobre o uso das tecnologias da informação e da comunicação no brasil 2007. disponível em: < http://www.cetic.br/hosts/2008/index.htm>. acesso em: 13 set. 2008. coen, l. gerenciamento de ativos: maior controle em ti. disponível em: < http://www.companyweb.com.br/lista_artigos.c fm?id_artigo=192 . fev, 2004 >. acesso em: 24 ago. 2008. coex, d.e., kreger, h. management of the service-oriented-architecture life cycle. ibm systems journal, v. 44, n. 4, 2005. csillag, j.m.; 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(2021) competitive intelligence and absorptive capacity for enhancing innovation performance of smes. journal of intelligence studies in business. 11 (1) 19-32. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 1 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive intelligence and absorptive capacity for enhancing innovation performance of smes abdeslam hassania* and elaine mosconia auniversity of sherbrooke, quebec, canada *a.hassani@usherbrooke.ca journal of intelligence studies in business please scroll down for article competitive intelligence and absorptive capacity for enhancing innovation performance of smes abdeslam hassania* and elaine mosconia auniversity of sherbrooke, quebec, canada *corresponding author: a.hassani@usherbrooke.ca received 19 january 2021 accepted 29 march 2021 abstract in dynamic and complex environments, it can be difficult for small and mediumsized enterprises (smes) to achieve business performance, innovate and survive, even though these actions are crucial for economic growth and competitiveness. competitive intelligence (ci) appears as a strategic practice to help them. although there are many theoretical studies that propose the relationship between ci and innovation, few studies have conducted empirical studies in the context of smes. the objective of this paper is to investigate how competitive intelligence enhances innovation performance in the context of a sme. based on a literature review and empirical data from several interviews with managers of one sme, our findings allowed us to propose a framework showing the contribution of ci to innovation performance relying on absorptive capacity. our findings also highlight that a prospector owner-manager can improve the results of ci in the sme and contribute to better innovation performance. keywords absorptive capacity, competitive intelligence, innovation performance, prospector owner-manager, sme 1. introduction small and medium-sized enterprises (smes) are considered the primary source in creating jobs and economic wealth (julien 1995; olawale and garwe 2010), employing more than 95% of the world’s working population (pellissier and nenzhelele 2013). in canada, smes account for 99.7% of total firms in terms of working population and contribute about 54% of canada's gdp (statistics canada, 2016). despite the importance of smes in economic growth, significant obstacles impede their sustainability, leading in most cases to failure. to overcome challenges and survive, smes need to improve their innovation performance (rujirawanich et al., 2011). innovation requires research and development (r&d) (baldwin and hanel, 2003), which is a determinant of innovation (raymond and stpierre, 2007). however, most smes do not have sufficient resources to invest in r&d (moilanen et al., 2014). moreover, they are not qualified to benefit from government assistance programs for r&d (institut de la statistique quebec, 2002). they are, more than ever, compelled to exploit external information (amara and landry, 2005; davila et al., 2009) by adopting environmental analysis activities such as competitive intelligence (ci) (guimaraes et al., 2016). ci allows companies to gather information from customers, suppliers, competitors and technologies and thus build a strong foundation for the innovation process (pacitto and tordjman 1999; tidd, et al., 2005). however, the literature shows that the effectiveness of ci in the context of smes depends on the company’s owner-manager profiles and the absorptive capacity of the company. indeed, the sme prospector ownermanager seems to contribute to more effective ci in acquiring and interpreting external journal of intelligence studies in business vol. 11, no. 1 (2021) pp. 19-32 open access: freely available at: https://ojs.hh.se/ 20 information (baldwin and gellatly, 2003). in addition, absorptive capacity allows the company to transform external information (cohen and levinthal, 1990) into knowledge, which in turn contributes to innovation performance (bayarçelik et al., 2014). although ci is useful for businesses, few studies have been devoted to smes (priporas, 2019; talaoui and rabetino, 2017). more specifically, there are few empirical studies that have treated the relationship between ci and innovation (calof and sewdass, 2020; hassani, 2020). however, to our knowledge, there is no framework that explains the role of ci in the innovation performance of smes in practice. this paper addresses this gap and proposes a framework for a better understanding on how ci contributes to innovation performance relying on absorptive capacity for better results. the proposed framework is based on empirical data and the published literature. the first section presents a literature review on innovation performance and ci, as the concepts supporting this study. the following sections present methodology and results. in discussing the implications of the proposed framework, the paper proposes several propositions predicting the positive impact of ci and absorptive capacity on innovation performance. 2. literature review 2.1 innovation innovation can be classified into four types: product innovation, process innovation, organizational innovation, and marketing innovation (oecd, 2008). innovation is considered to be the engine of growth and development for smes (raymond and stpierre, 2007). empirical studies have shown that the most successful innovative smes in canada, the united states and europe generate strong growth (baldwin, 1994) and are able to survive for long periods (baldwin and gellatly, 2003). innovation performance is a critical requirement for business competitiveness (baldwin and gellatly, 2003; song et al., 2015). it can be defined as a concept with two dimensions such as efficiency and effectiveness (alegre et al., 2006). according to those authors, efficiency refers to the degree of effectiveness of innovation, and effectiveness refers to the use of resources in terms of the time and cost required to complete the innovation project. similarly, guimaraes et al. (2016) emphasize that innovation performance represents the degree of effectiveness of the firm in implementing innovation, which in turn has a significant impact on the organization’s performance. to stimulate innovation, companies invest more and more in r&d. large companies can cover the costs associated with r&d activities and spread the risks associated with innovation across their entire project portfolio (st-pierre and mathieu, 2003). they have access to resources to invest in equipment, marketing and technical work, which can lead to major innovations (laforet, 2008). however, most smes do not have sufficient resources to invest in r&d (moilanen et al., 2014). therefore, to promote and conduct innovation better, organizations need to be proactive in identifying and exploiting opportunities. to do this, these organizations, and in particular smes, should have anticipatory approaches such as ci (calof and sewdass, 2020; guimaraes et al., 2016). in addition, absorptive capacity is also pointed out as being crucial to convert the information collected into knowledge useful for the innovation process (andreeva and kianto, 2011, cohen and levinthal, 1990). 2.2 competitive intelligence ci is an evolving concept (brody, 2008). its definition presents a challenge for both academics and practitioners writing in french (jakobiak, 2006; larivet, 2001) or in english (brody, 2008; smith et al., 2010). ci is an amalgam of disciplines covering economics, marketing, military theory, information science, and strategic management (pellissier and nenzhelele, 2013). in addition, ci is different from industrial espionage, which is both an illegal and unethical activity (crane, 2005). ci is both a process and a product (vedder et al., 1999). the society of competitive intelligence professionals (scip) defined ci as the systematic and ethical collection, analysis and management of external information that can affect the company’s planning, decision-making and business operations. ci can also be defined as a product, which refers to intelligence information about competitors’ activities from public and private sources, and its scope is the present and future behavior of competitors, suppliers, customers, technologies, acquisitions, markets, products and services, and the general business environment (vedder et al., 1999). ci has been considered to be the 21 fourth factor for the survival of enterprises after capital, technology and talent (bao, 2020). the main objective of ci is to provide an alert system for external turbulent events that may have an impact on the company’s strategy and performance (ngamkroeckjoti and speece, 2008). the three main sources of such environmental turbulence are: market, technologies and competitors’ intensity (jaworski and kohli 1993; ngamkroeckjoti and speece 2008). many studies have highlighted that smes prefer to monitor sources in their immediate environment (johnson and kuehn, 1987; ramangalahy, 2001). this environment consists of customers, competitors, and suppliers (smith et al., 2010), and technologies (bao, 2020; calof and sewdass, 2020; jaworski et al., 1995). ci is essential for business because it not only provides a solid foundation for the innovation process (pacitto and tordjman, 1999; tidd et al., 2005), but because its absence can also be considered a barrier (stpierre and trépanier, 2013) or even a factor in the failure of innovation (wycoff, 2003; baldwin et al., 2000). 2.2.1 customers’ intelligence information and innovation performance customer engagement enables enterprises to effectively enhance the success rate of radical innovation and incremental innovation (wang and xu, 2018). to innovate, enterprises must identify potential customer needs, and collect and analyze their demands, which can help generate new ideas for products and services (bao, 2020). according to bao (2020) and kohli and jaworski (1990), intelligence information from customers is essential for companies. indeed, intelligence information increases the level of innovation performance (bayarçelik et al., 2014) and helps the development activity of new products (bayarçelik et al., 2014; voss, 2012). more specifically, customers’ intelligence information improves both radical innovation performance (nguyen et al., 2015; frambach et al., 2016) and incremental innovation (laforet, 2008; nguyen et al., 2015) in particular, in the early stages of the innovation life cycle (laforet, 2008). a study by tanev and bailetti (2008) found a positive correlation between customer intelligence information and innovation in smes. 2.2.2 competitor intelligence information and innovation performance competitor analysis is the soul of ci (bao, xie, li, 2003). ci helps enterprises analyze competitor strengths and weaknesses, predict their strategies, and evaluate their new products, especially their prices, costs, profits and development (bao, 2020). prior research advises companies to monitor competitors in order to develop a greater ability to accelerate product innovation activities (lee and wong, 2012; laforet, 2008) and innovate in those areas where competitors are weak (story et al., 2015). ci on competitors has an impact on different types of innovation in companies. it contributes to radical service innovation (cheng and krumwiede, 2012). in the same vein, frambach et al. (2016) noted that intelligence information from competitors stimulates the exploitation of skills and leads to the development of radical innovation. 2.2.3 suppliers’ intelligence information and innovation performance suppliers are a very important information source for helping firms’ innovation performance (dahlander and gann, 2010). the participation of suppliers in the innovation process contributes to a potential source of sustainable competitive advantage (bao, 2020). suppliers often establish strategic partnerships with customers and competitors to implement technologies, processes or new products. to gather information from suppliers, the company can therefore conduct primary research (slater et al., 2012). according to carbonell and rodríguez escudero (2010), intelligence information from suppliers allows the product development team to understand the market dynamism and act faster, which can contribute to new-product performance. zhang and chen (2014) argue that intelligence information from suppliers helps companies to improve innovation performance. nassimbeni and battain (2003) highlight the fact that suppliers contribute to innovation in different forms, such as the provision of new product / process technologies, or the development of joint projects. supplier intelligence information is also one source of innovation and has a positive effect on innovation performance (bao, 2020). 22 2.2.4 technologies intelligence information and innovation performance several research results highlight the importance of technologies as a rich information source, which contributes to the emergence of innovative ideas. information from technologies allows organizations to be more competitive (duncan 1972; souitaris 2001; vedder et al., 1999). the literature highlights multiple tools and technology platforms that can help companies gather information about their external environment. the internet, especially social media, are the sources of information most often mentioned in the literature (roch & mosconi, 2016). teo and chow (2001) argue that the internet helps companies gather quality market information and make more informed decisions. in the same vein, afuah (2003) emphasizes that the internet improves the integration of innovation activities through the exchange of ideas with external actors, especially with customers. social media, on the other hand, is at the same time a kind of source and a tool for gathering information about competitors' offers and customers’ needs (itani et al., 2017). laforet (2008) notes that the companies, especially smes, that are more interested in technologies can achieve a high degree of novelty in their products, which helps innovation performance. 2.3 sme owner-manager and competitive intelligence ramangalahy et al. (1997) found that, among several organizational factors, strategy is the factor that best explains ci. in the context of smes, the strategy is intimately linked to the profile of its owner-manager (geraudel, 2008). in fact, the owner-manager has a relevant impact on the strategy and behavior of their company over time (serrano-bedia et al., 2016). the literature has pointed out that the sme’s owner-manager is concerned with the collection, analysis and dissemination of information (ramangalahy, 2001). to perform in innovation, the owner-manager, among other responsibilities, develops new technologies and implements new processes, especially those that allow for the generation of new knowledge on the market (baldwin and gellatly, 2003). these processes may include, for example, how companies coordinate and disseminate information flows from their customers, competitors and suppliers to their research and development teams and production units (baldwin and gellatly, 2003). according to the strategy typology of miles and snow (1978), the prospector ownermanager, characterized by innovation, proactivity and risk-taking, significantly improves ci (chandler and jansen, 1992). thomas et al. (1993) argue that proactive managers who analyze the external environment can detect disturbances and react before the emergence of threats. similarly, the prospector owner-manager analyzes the external environment, selects promising opportunities and formulates strategies (chandler and jansen, 1992). belley and ramangalahy (1994) note that the prospector owner-manager contributes greatly to developing new activities (innovation) and to anticipating new needs and market demands (strategic planning). in addition, the effectiveness of ci is related to the prospector owner-manager in acquiring and interpreting external information, especially in smes (baldwin and gellatly, 2003). 2.4 absorption capacity, competitive intelligence and innovation performance cohen and levinthal (1989, 1990) define absorptive capacity as a firm’s ability “to recognize the value of new, external knowledge, assimilate it, and apply it for commercial ends.” the literature shows that there is a link between absorptive capacity and innovation. indeed, absorptive capacity contributes to improving innovative capacity (cohen and levinthal, 1990) and innovation performance within the firm (andreeva and kianto, 2011; bayarçelik et al. 2014; lichtenthaler, 2016). previous studies have highlighted that absorptive capacity has been viewed as a possible moderator of various determinants of innovation performance (moilanen et al., 2014). absorptive capacity helps managers understand the effect of ci on the organization performance (najafi-tavani et al., 2016). bellamy et al. (2014) report that firms’ absorptive capacity positively moderates the relationship between ci and its innovation performance. wang et al. (2010) argue that to exploit the benefits of information gathered from suppliers, the ability to assimilate and transform this information is required. in the same vein, the results of the study by guimaraes et al. (2016), which was conducted on 1000 companies representing a variety of 23 sizes and business sectors, shows that organizational absorptive capacity is positively related to ci practices and innovation performance. in the context of smes, zobel (2017) points out that a high assimilation capacity allows a good understanding and dissemination of information coming from customers, competitors, suppliers and technologies. according to pacitto and tordjman (1999), it is useless to have a variety of information sources without being able to exploit emerging information. 3. methodology the purpose of this exploratory study is to investigate the contribution of absorptive capacity and ci to innovation performance. a qualitative research approach is appropriate for an exploratory study. a case study was conducted which involved close observation of the phenomenon of interest in a real-life context (eisenhardt, 1989; yin, 2017). in addition, a case study approach is recommended for investigating the topic of the contribution of ci to the innovation performance of smes, since it has been relatively unexplored. the case study and data collection were conducted within an sme located in canada, referred to here as "company a". 3.1 data collection multiple data-collection methods, including semi-directed interviews, document analysis and non-participant observation, were used for triangulation (miles and huberman, 2005; yin, 2017). semi-structured interviews were conducted with a sample of seven members of company a, including the chief executive officer, and six managers and middlemanagers representing management, marketing departments, the development of new services, and systems engineering. the managers were selected using the nonprobabilistic method of convenience. data was collected between november 2016 and march 2017. before each interview, a list of topics was sent to the interviewees. nine interviews in total, including three interviews with the chief executive officer (ceo), were conducted in the field. the interviews were audio-recorded, with the authorization of the interviewee, and were transcribed verbatim. these interviews lasted between 60 and 90 minutes. in addition, we were nonparticipating free observers in company a. data was collected by note-taking in several activities, which mainly involved weekly meetings and strategic-planning workshops. secondary data was collected from official documents and company a’s website. for data analysis, we used a thematic analysis to refine the grouping of themes and thematic categories and subcategories (saldaña, 2013). table 1 describes the characteristics of the firm studied and the interviewees. concerning the sampling unit, a medium-sized company was taken into consideration. this company offers professional, scientific and technical services, and develops design services for companies operating in the manufacturing sector. 4. results 4.1 innovation in company a company a has an innovation process called "development offering". this process aims to develop new technological solutions, new approaches and working methods to create added-value for customers. to generate new ideas, the ceo reported: table 1 characteristics of the company sample and interviewees. aaccording to north american industry classification system (scian), (canada, 2017). baccording to industry canada (2019), a micro-company has less than 5 employees; a small company between 6-99 employees; a medium company 100-499 employees; and a large company over 500 employees. company code sub-sectora company sizeb interviewee positions code number of interviewees company a scian 5414 specialized design services medium ownermanager ceo 3 manager 1 1 manager 2 1 manager 3 1 manager 4 1 manager 5 1 manager 6 1 “ideas are generated through different techniques. these techniques can be creative workshops that are organized around a service development project or specific meetings to discuss the emergence of a new technology or a work approach. the creativity workshops within company a have led to several innovative projects. for example, operations support projects, cost reduction applications, and other projects associated with operational excellence and industrialization activities.” 4.2 competitive intelligence in company a ci activity has been identified in company a as "strategic monitoring". ci allows the company to develop a new vision, strategies and new projects. as manager 1 explains: “we have already done strategic monitoring; we reviewed the market trends before doing our strategic planning.” the most prominent ci activity in company a occurred when the concept of industry 4.0 emerged. in this context, the ceo of the company mentioned: “in doing the strategic monitoring, industry 4.0 emerged. we retrieved this information to clarify our position in the market and develop a new project.” in the same vein, manager 2 reported that: “industry 4.0 is the result of reflection, monitoring, and especially customer needs analysis.” the ceo plays an important role in the business of ci within company a. indeed, his presence at conferences, fairs and exhibitions, and local and international shows allows him to collect information on market dynamics and trends through exchanges with experts and ceos of other companies. manager 2 and manager 4 emphasized: “our ceo often generates quality information and creative ideas.” (manager 2) “our ceo is a visionary person, using his great ability to analyze the market, he manages to unlock crisis situations.” (manager 4) the primary data in our case-study shows that company a uses ci to collect information from multiple external sources. manager 1 claimed: “the activities organized by various professional and socio-economic associations allow the leaders of company a to interact with the presidents, directors and managers of other organizations including competitors. these events promote the exchange and collection of strategic information.” according to all managers interviewed, the most important source of useful information is the customers. manager 2 pointed out: “some members of company a are directly connected to their customers' factories, which allows them to collect information about the needs of these customers. in addition, company a directors organize regular meetings with clients to evaluate projects and therefore to have feedback on their product and service development work.” collaboration with external partners, especially with suppliers, plays an important role in acquiring information. manager 1 and the ceo mentioned: “our company has established partnerships with suppliers, which led to the deployment of a new technological solution.” (manager 1) “we are in constant contact with some suppliers to develop products and meet the needs of customers.” (ceo) for monitoring the external environment’s dynamics, company a uses many technologies and platforms. several managers talked about the importance of technology platforms in ci’s business. for example, manager 3 and manager 5 argued: “for gathering new information, our employees use the internet, especially digital media.” (manager 3) “in order to gather information, company a uses the internet, in particular professional networks, social media, blogs, forums and google alerts.” (manager 5) 4.3 absorption capacity within company a the ceo of company a understands absorptive capacity as: 25 “our ability to organize the work, to be able to deploy and execute the actions we must do to achieve our goal. it's the organizational capacity to execute the blueprint.” specifically, in the context of industry 4.0, manager 1 noted: “industry 4.0 is a novelty for our company. at first, the absorptive capacity is the capacity to self-learn, to define what this element is. also, to conceptualize and define the situation. in a second step, formalize it and transfer it.” an organization's absorptive capacity is based on its ability to gather, transform and exploit external knowledge. in company a, the ceo pointed out: “a good understanding of the market needs for innovation and our ability to assess the effect of technology solutions for customers and help our teams better identify, value and then gain external knowledge.” for other managers, the valuation of external knowledge depends on its impact on the strategy and its effects on the company's outcome, whether related to an opportunity, a threat or new technology. regarding the transformation and exploitation of external knowledge, company a relies on the varied skills of its employees. indeed, most employees are highly qualified (about 90% of employees have engineering, master's degrees or phd training) combining knowledge and experience in several fields. their skills allow for the transforming and exploiting of external knowledge in the form of concrete and competitive projects. manager 2 emphasized: “experienced employees have been instrumental in using their previous knowledge, turning it into new knowledge, and then creating new and innovative projects.” however, company a has to improve their absorptive capacity through taking up some challenges. indeed, most of the employees have technical skills but they miss management skills. the ceo, and managing director said: “they want to develop more professional and technical experience but not in management.” this challenge is more important in multidisciplinary activities. in fact, as manager 1 pointed out: “most projects are multidisciplinary and informal, presenting a management challenge for the firm.” this challenge is both intra-departmental and interdepartmental, which requires managers with technical and managerial skills. 5. discussion & implication: propositions the objective of this paper is to investigate how competitive intelligence can enhance innovation performance relying on absorptive capacity to reinforce the potential results in a sme context. this section presents a set of propositions and discusses some implications from these findings. these propositions are based on analyzed empirical data and the theoretical literature. to present our main findings and data results in company a, we adopted a narrative perspective (seixas et al., 2021). this allows us to discuss the implications of our results for ci and absorptive capacity in regard to its contribution to the innovation performance of company a. first, our findings suggest that despite a lack of resources, smes can practice ci, at least partially (fleisher and blenkhorn, 2001). however, this activity can remain incomplete, unsystematic and informal, which makes it inefficient (bergeron 2000; dishman and calof, 2008) if the smes have no absorptive capacity or engagement by top management. at company a, the ceo conducts brainstorming, imagination and ideation exercises with several topand middle-managers to bring out innovative ideas. according to mcadam and mcclelland (2002), the expertise and imagination of ceos are components of creative problem-solving. the strategic planning activities, held periodically by the ceo, aim to anticipate changes in company a’s external environment. in this sense, the literature reveals that a ceo with a proactive personality is able to understand market trends and therefore anticipate planned changes (becherer and maurer, 1999). based on this understanding, the prospector-ceo enhancing ci activities in smes were observed and lead us to proposition 1 (p1). 26 p1: the prospector owner-manager seems to contribute to ci. according to several managers in company a, employees are directly connected to customers, allowing them to understand the needs and preferences of these customers (kohli and jaworski, 1990). customer needs and preferences are the main ingredients for new ideas, products and services (narver et al., 2004). the transformation and exploitation of customer insights into innovation rely heavily on the skills of the individuals at company a. coordination and communication with customers contributes to creating new knowledge and to increasing absorptive capacity, which in turn leads to innovation (gatignon and xuereb, 1997). in company a, intelligence information, which means data and information gathered from customers analyzed in context by managers, contributes to innovation performance. the contextual knowledge and experience are related to absorptive capacity. these observations are related to the two following propositions: p2: intelligence information from customers enhances the innovation performance of smes. p1b: absorptive capacity enables improving information from customers and contributes to the innovation performance of smes. our findings revealed that company a is more oriented towards improving their understanding of customer needs and preferences than to conducting competitormonitoring. this orientation is in line with groom and david (2001) who stated, "small organizations with high revenues are more satisfied with current intelligence than small organizations with low revenues". however, literature suggests that excessive customer orientation can hamper the monitoring of changes in the external environment (koberg et al., 1996), as was the case of company a during a period before a ci strategy was implemented. company a would have taken full advantage of its innovation activities if its employees were collecting strategic information about competitors. our findings show that a low intensity of information from competitors created a barrier for innovation and growth of the company. in addition, company a identified several lost opportunities of innovation after implementing ci practices. according to theodosiou et al. (2012), information from competitors is relevant to help identify their objectives, strategies, activities, offers, resources, capabilities and competitive advantage. however, managers at company a mentioned difficulties in collecting strategic information about their competitors. based on our findings, information from competitors can enhance innovation performance, especially if supported by information analyses and absorptive capacity. this understanding translates to the following propositions: p3: intelligence information from competitors enhances the innovation performance of smes. p2b: absorptive capacity improves the use of competitor information and contributes to the innovation performance of smes. as the oecd report (2008) points out, companies in most countries prefer to collaborate with customers and suppliers rather than with competitors and private r&d centres to protect their development model. indeed, the study’s results show that managers at company a are more open to collaborate with suppliers, which allows them to collect information on customers and competitors. collaboration with suppliers allows these managers to identify opportunities for developing new industry 4.0 technological solutions and become a leader in this domain. song and thieme (2009) report that the participation of suppliers in ci activities has an impact on innovation performance. in addition, frequent exchanges between employees of company a and their external environment including vendors strengthen their absorptive capacity, which in turn facilitates the transformation of information. their relationships with suppliers serve to stimulate the exploitation of individual absorptive capacity, and thus enhance organizational absorptive capacity, which contributes to the success of innovation (cohen and levinthal, 1990). our findings showed that company a analyzes the information or the intelligence information from suppliers to help to improve innovation performance, and the contribution of the manager’s absorption capacity was useful. these findings lead us to the following propositions: p4: intelligence information from suppliers enhances the innovation performance of smes. p3b: absorptive capacity improves the use of suppliers’ information and contributes to the innovation performance of smes. 27 our results suggest that company a has focused on information technologies to identify future needs, which culminated in innovative projects and innovation performance. findings reveal that these projects contributed to an increase of 15% in business revenues. this practice is in line with the literature that suggests that data and information from technologies allows firms to create new technical solutions and develop new products (gatignon and xuereb, 1997). varied information technologies, including social media, blogs and forums, and google alerts, allowed the managers of company a to monitor changes related to new technological trends. ci including information from technologies helped company a make the shift to industry 4.0 and become a leader in their region. many studies have pointed out that technologies are considered an information source, which contributes to business competitiveness (souitaris, 2001; vedder et al., 1999). to better use these information sources, firms need individuals with prior knowledge in the field to take advantage by means of absorptive capacity (cohen and levinthal, 1990). our findings show that company a had some 100 engineers with technical training and experience in technological fields. these skills were crucial to transform technological information into innovative projects. these results are related to the following propositions: p5: intelligence information from technologies enhances the innovation performance of smes. p4b: absorptive capacity improves the use of technology information and contributes to the innovation performance of smes. these propositions emerged from the data analysis and allowed us to propose a conceptual framework to illustrate how ci contributes to innovation performance (figure 1). this theoretical framework is based on the understanding that ci comprises information collected from customers, competitors, suppliers and technologies. the capacity to analyze and integrate this information is represented by absorptive capacity that reinforces the potential of the innovation performance. moreover, ci also benefits from the important contributions of the prospector owner-manager in the context of an sme. 6. conclusions, limitations and future research this paper presents an exploratory case study that allowed a framework proposition showing how ci contributes to innovation performance and why absorptive capacity is important for better results. this framework fills a theoretical gap and is supported by empirical data collected during the case study. our findings suggest three main contributions. first, ci requires a prospector owner-manager characterized by a profile of innovation, proactivity and risk-taking. this type of ownermanager analyzes the external environment and detects disturbances, which contributes to better results from the ci (north and varvakis, 2016). second, the findings have highlighted that the contribution of ci to the innovation figure 1 framework showing the flow from competitive intelligence to innovation performance. 28 performance of smes is mainly based on the collection, analyzing and exploitation of information from customers, competitors, suppliers and technologies. more specifically, our case study shows that understanding customer needs and preferences allows companies to create innovative ideas, as proposed by narver et al. (2004). however, we also understood that focusing more on clients without considering competitors strategies, activities, and objectives (theodosiou et al., 2012) can lead to the loss of growth opportunities, and to the failure of the smes. our findings also allowed us to understand that collaboration with suppliers is seen as an opportunity to gather information from customers, competitors, and the market as well as to develop new creative ideas, which aligns with previous studies (see song and thieme, 2009). the sme studied has invested and given particular importance to technologies, both as tools and information sources. these decisions seem to be relevant to enable them to be able to monitor the dynamic business environment, which allowed them to capture opportunities and develop new products. this same aspect was also pointed out by gatignon and xuereb (1997): even though the business environment has changed since this time, technologies have been constantly evolving and disrupting established practices in business. at this point, to face technological challenges and continue to innovate in smes, it is important in future research to investigate the ambidextrous organizational-learning habits to mitigate a lack of resources. third, the findings show that the firm's absorptive capacity is essential to understanding the contribution of ci to innovation activities, as proposed by najafitavani, sharifi and najafi-tavani (2016). in addition, božič and dimovski (2019) argue that absorptive capacity is essential for ci because it plays an important role in transforming data into rich information and knowledge. although this is only an exploratory study, our findings can guide managers to make the best choices for ci practices, to develop competitive advantage and be more agile than their competitors are. sme ceos and managers need to consider their managers’ profiles, as well as their involvement in operations, for innovation performance within the firm. this study proposes a framework, certain limitations, and several propositions that should be investigated in future research. as a limitation, the observation approach, whether systematic or electronic, may have an intrusion effect of the observer (beaugrand, 1988). second, the results obtained are not generalizable because of the chosen research approach, as well as due to the variability existing between smes (julien, 2005; tidd et al., 2005). third, given that there is no single way to innovate (tidd et al., 2005), and that ci practices are heterogeneous, future research can test our propositions using a larger sample and survey in order to gain quantitative evidence regarding our conclusions. this will improve the understanding related to innovation performance in smes, as they are an important component of the economy of all countries. additionally, in current contexts of digital transformation, and industry 4.0 where ci is needed (ottonicar et al. 2018) including the assimilation capability (hassani and mosconi, 2018), it would be relevant that future research could investigate the role of analytics capability on innovation performance. in link with the own-manager, future research can also study the managers’ ambidexterity, which it is important for intelligence-based activities (bordeleau et al., 2020). acknowledgements this work was supported by the mitacs canada accelerate program. the authors thank all industrial partners for their support of this research. 7. references afuah, a. 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(2017). benefiting from open innovation: a multidimensional model of absorptive capacity. journal of product innovation management, 34(3), 269-288. jisib-vol-12_nr-1(2022) (3).pdf journal of intelligence studies in business vol. 12 no. 1 (2022) open access: freely available at: https://ojs.hh.se/ pp. 65–82 mobile applications adoption and use in strategic competitive intelligence: a structural equation modelling approach milind thomas themalil abstract this article examined the key determinants of mobile applications’ adoption and use in strategic competitive intelligence. a quantitative research based on a survey of 150 participants drawn from strategic competitive intelligence practitioners and analysts was used to examine and validate the extended utaut2 model to identify the key determinants of mobile applications` adoption and use in sci. pls-sem algorithm was used to analyse to the importance-performance map analysis that showed the greater absolute importance of cognitive psychological perceptive which this study addressed by examining key determinants of behaviour intention and user behaviour. keywords: strategic competitive intelligence; utaut; utaut2; adoption; mobile 1. introduction competitive intelligence has become a global phenomenon in today`s environment that is characterised by global competition. big data analytics, ai, iot, 5g/6g, cybersecurity, as well as the adoption and use of mobile applicatwitter, and telegram have enabled highspeed availability, transfer, and analysis of large amounts of data collected and accumulated by individuals and organisations over the years (maune, 2021). in the last decades, companies have invested resources dramatically in competitive intelligence (ci) systems, which enabled business users to discover their rich, reliable, and relevant data. ci is providing companies with the tools to make informed decisions. it is enabling companies to keep ahead of the competition and industry trends. the past decade has seen a tremendous growth in mobile applications usage the world over. by the end of 2020, reports estimated that there were about 3.5 billion 66 smartphone users worldwide (maune, 2021). according to statista.com website, an estimated 1.4 billion smartphones were sold in 2020 alone. this has increased the demand and use of mobile applications by companies. what is not known, however, are the major key determinants for the adoption and use of mobile minants have on behaviour intentions and use behaviour of mobile applications in sci is still mystery. thus far, ci research has focused primarily on the same phenomenon, how to gather information to make better decisions (solberg, 2019 cited by maune, 2021). research is now starting to address ci from a business intelligence intelligence this time around using algorithms as a predictive tool. previously, ci research was more concerned with web and desktop applications but there is a rapid shift towards mobile applications due to information available anytime, anywhere from everyone who has enced by an increase in the number of mobile application and the number of active users per day (maune, 2021). mobile intelligence has now combined bi, transactions, and multimedia. mobile applications have become the biggest companies that are ignoring mobile applications for intelligence are doing so at their own peril. what is currently unknown is how deep they can be relied on by intelligentsia? what business leaders often fail to understand are the key determinants for the adoption and use of mobile applications in sci? this usually serves as a differentiator among ci practitioners and analysts. with the development of a number of mobile applications and the increase in mobile penetration globally, it is critical for sci practitioners and analysts to appreciate the key determinants for the adoption and use of mobile applications in sci. mobile applications have become the focal area for new ideas and big data analysis with more and more organisations turning to these platforms to map their strategies. in this dynamic world, business leaders need to know what their competitors are up to. additionally, they need to gather the trends, patterns, and relationships they see emerging across mobile platforms. the question that should be asked mobile applications platforms have become new areas to look for business opportunities. ci is very important in this regard and should be prioritised to identify these opportunities. the aim of this study was to empirically examine and validate the proposed path analysis model (maune, 2021). the model was an extension of the utaut2. we analysed the data use of mobile applications in sci. behaviour intention and use behaviour from a cognitive psychological perspective was used. more spewere; (i) to establish the key determinants for the adoption and use of mobile applications in intention on use behaviour in the adoption and use of mobile applications in sci, and (iii) to develop a path analysis model suitable for the adoption and use of mobile applications in sci. to achieve this, the authors adopted a positivism research philosophy. the authors used a deductive research approach to gather data through an online survey sent to ci practitioners and analysts as well as those involved in decision making in various organisations. an explanatory research design assisted the researcher in examining the relationship between variables as well as assisting in identionnaires were sent through different online ings have both managerial and practical implical, societal, political, and educational. the remainder of the article will be as dates the proposed path analysis model and the hypotheses will be followed by the research method used. this will address the research respondents and procedure, measurement, approach to sem, analysis, model adopted, and the structural model analysis. thereafter, discussion of results will follow. the study`s implications for research and practice as well as its limitations. the study conclusions will be given and the article will end with a reference list. 2. literature review in this section, the study presents an overview tance and use of technology (utaut2) model 67 cusses the new constructs that were added to the utaut2 (that is, perceived risk, trust, by maune (2021). 2.1 theoretical framework of technology (utaut2) based on a review of the extant literature, developed utaut as a comprehensive synthesis of prior technology acceptance research. utaut has four key constructs (performance behavioural intention to use a technology and/ or technology use. we adapt these constructs to which using a technology will provide beneities; is the degree of ease associated with consumers’ use of technology; is the extent to which consumers perceive that important others (for example, family and friends) believe they should use a particular technology; and conditions refer to consumers’ perceptions of the resources and support available to perform performance expectancy, effort expectancy, behavioral intention to use a technology, while behavioral intention and facilitating conditions determine technology use. also, individual difference variables, namely age, gender, and experience are theorised to moderate various above that was necessary to make the theory applicable to this context. or pleasure derived from using a technology, and it has shown to play an important role in determining technology acceptance and use such hedonic motivation (conceptualised as ence technology acceptance and use directly tam, 2006). in the consumer context, hedonic motivation has also been found to be an important determinant of technology acceptance and use (childers, carr, peck, and carson, 2001; hedonic motivation as a predictor of consumers’ behavioural intention to use a technology an important difference between a consumer use setting and the organisational use setting, where utaut was developed from, is that, consumers usually bear the monetary cost of such use while employees do not. the cost and pricing structure may have a sigularity of short messaging services (sms) in china is due to the low pricing of sms relative to other types of mobile internet applications (chan, gong, xu, and thong, 2008). in marketing research, the monetary cost/price is usually conceptualised together with the quality of products or services to determine the perceived as consumers’ cognitive tradeoff between the peretary cost for using it (dodds, monroe, and grewal, 1991). the price value is positive when to be greater than the monetary cost and such price value has a positive impact on intention added as a predictor of behavioral intention to prior research on technology use has introduced two related yet distinct constructs, namely and . experience, as an opportunity to use a target technology and is typically operationalised as the passage of time from the initial use of a technology by categories with different periods of experience. experience as three levels based on passage of time: post-training was when the system was initially available for use; 1 month later; as the extent to which people tend to perform behaviours automatically because of learning et al. (2005) equate habit with automaticity. conceptualised rather similarly, habit has been operationalised in two distinct ways: 68 kim and malhotra, 2005); and second, habit is measured as the extent to which an individual believes the behavior to be automatic (limayem et al., 2007). consequently, there are at least two key distinctions between experience and habit. one distinction is that experifor the formation of habit. a second distinction is that the passage of chronological time (experience) can result in the formation of differing levels of habit depending on the extent of interaction and familiarity that is developed with months, different individuals can form various levels of habit depending on their use of a tarperhaps what prompted limayem et al. (2007) to include prior use as a predictor of habit; and likewise, kim and malhotra (2005) controlled for experience with the target technology in their attempt to understand the impact of (2005) also noted that feedback from previous consequently, future behavioral performance. in this context, habit is a perceptual construct in technology use have delineated different technology use. related to the operationalisation of habit as prior use, kim and malhotra (2005) found that prior use was a strong predictor of future technology use. given that there are detractors to the operationalisation of habit as prior use (see ajzen, 2002), some work, such as that of limayem et al. (2007), has embraced a survey and perception-based approach to the measurement of habit. such an operationalisation of habit has been shown to directly affect technology use over and above the effect of intention and moderate the effect of intention on technology use such that intention becomes less important with increasing in the context of other behaviors have been reported in psychology research (see ouellette and wood, 1998). utaut2 model. 69 2.2 conceptual framework 2.2.1 identifying constructs to incorporate into utaut2 this section presents an overview of the four constructs that were added to utaut2 and discusses them in detail (see maune, 2021). the constructs are perceived risk, trust, subcomplements the utaut2 constructs as given through a literature review carried out by maune (2021). the conceptual framework developed in the previous study (maune, 2021) formed the basis of the current study. in technology acceptance and use, perceived risk and trust have proven to be strong predictors of behavioural intention (see maune, 2021). risk has been considered a strong driver of behavioural intention and use behaviour of mobile applications. recent developments in the operations of big technology companies have caused risk and trust to be amongst the strongest predictors of behavioural intention and use behaviour of mobile applications in gathering sci data. the use of mobile applications in sci gathering has become popular recently. technology developers are coming up with useful tools to gather sci data from mobile application platforms. the platforms among others. these platforms are proving to be rich mines for sci. borrowed from the theory of reasoned and the theory of planned behaviour (tpb) other reasoned action models is the idea that behaviour is guided by intentions (ajzen, 2012). subjective norms are the individual’s he or she should engage in the behaviour and are assumed to capture the extent of perceived social pressures exerted on individuals to engage in certain behaviour. o’connor and armitage (2003) argue that subjective norms are a function of normative beliefs. to them, normative beliefs represent pressures that are and friends with respect to the behaviour in question. normative beliefs and the personal motivation to comply with such beliefs and (o’connor and armitage, 2003). with respect to tive norms represent actors’ perceptions about pressures generated from important significant others with respect to the behaviour (chatzisarantis and biddle, 1998). measures of subjective norms also respect a personal tendency to comply with pressures to the self-determination theory, psychological events that include compliance and pressure, represent control, and therefore, it is argued that subjective norms cover only the controlling dimension of personal experience. the subjective norm is also based on salient beliefs, called normative beliefs, about whether particular referents think the respondent should or should not do the action in question (east, 1993). east (1993) further argues that like expected values, measures: , the likelihood that the referent holds the normative belief, and the motivation to comply with the views of the referent. thus imi is the determinant of the subjective norm. according to the tpb model, subjective norms predict the intention, which in turn predicts use behaviour. subjective norm is a strong 2015). according to bandura (1997), cacy refers to beliefs in one`s capabilities and knowledge to organise and execute the courses of action required to produce/perform certain behaviour/attainments. studies by bandura dictor of behaviour and behavioural change. by its effect on perseverance. the more people believe that they have the capacity to perform an intended behaviour, the more likely they are to persevere and, therefore to succeed (ajzen, 2012). a considerable body of research attests motivation and performance (see bandura and locke, 2003). subjective norms are used to comused to complement performance expectancy and effort expectancy. research by roy (2017) were strong predictors of behavioural intention and use behaviour in mobile applications. 70 related models hinge on intentionality as a key underlying theoretical mechanism that drives behaviour. many, including detractors of this class of models, have argued that the inclusion of additional theoretical mechanisms is importthese constructs have become critical in the recent past in determining the adoption and use of mobile applications in sci gathering. with sci taking major strides in helping companies achieving sustainable competitive advantage, mobile applications have become based on the study by maune (2021) as well as the above explanations, perceived risk, 2.2.2 hypothesis development this section presents the hypotheses that were developed to validate the proposed model in the review of theoretical and empirical studies in the sections above. these hypotheses are to validate and test the proposed path analysis model by maune (2021). therefore, we hypothesised the following: h1. the greater the individual`s performance expectancy regarding mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h2. the greater the individual`s effort expectancy regarding mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h3. the greater the individual`s social the level of behaviour intentions to use mobile apps in sci. h4. the greater the facilitating conditions are perceived as favourable to mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h5. the greater the hedonic motivation is perceived as favourable to mobile apps use, research model. 71 the higher the level of behaviour intentions to use mobile apps in sci. h6. the greater the price value is perceived as favourable to mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h7. the greater the individual`s habit regarding mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h8. the greater the subjective norms are perceived as favourable to mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h9. the greater the individual`s self-efthe level of behaviour intentions to use mobile apps in sci. h10. the greater the perceived risk is seen as favourable to mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h11. the greater the individual`s trust regarding mobile apps use, the higher the level of behaviour intentions to use mobile apps in sci. h12. the greater the individual`s behaviour intentions to use mobile apps, the greater the likelihood of the individual`s use behaviour of mobile apps in sci. 3. method this article targeted scips and analysts as well as those in decision making. this study was conducted in the context of mobile applications use in sci. all applications that can be downloaded from application stores such as play store and app store among others were evaluated within the scope of mobile applications. these applications have made it easy for individuals and organizations to access large amounts of data. mobile applications have both increased and strengthened the role of sci in decision making globally. they have become big data mines for gathering intelligent information for decision making in competitive environments. 3.1 respondents and procedure via email and whatsapp platforms to sci practitioners and analysts. the questionnaire was generated was then sent to the respondents. the survey needed approximately 15 to 20 minutes to complete. before this, a pilot questionci knowledge to elicit salient features, ambigusuch questions were deleted or rephrased in the main questionnaire. completed questionnaires were returned, automatically through the google forms platform to the corresponding author by 98 respondents (65.3%). after cleaning the data, that is, removing observations with missing data, and suspected unengaged respondents, 96 (64% response rate) were retained for analysis. the sample size used was guided by marcoulides and saunders (2006). in this study, unengaged respondents response for all consecutive items (for example, a 7 throughout all the observed variables). table 1 denotes the demographic descriptive statistics of the study. variable category fre-quency percentage gender male 74 77% 22 23% age <20 21 – 30 12 12.5% 31 – 40 37 38.5% 41 – 50 11 11.5% >50 36 37.5% experience up to 1yr 9 9.4% 1 to 2yrs 2 to 3yrs 5 5.2% 3 to 4yrs 4 4.2% 5yrs or more 78 81.2% education college bachelor`s degree 1 1% master`s degree 55 57.3% phd 40 41.7% 3.2 measurement this article adapted the measurement scales from prior research (table 2). the latent variables and the measurement items are as given in table 2. the scales for the utaut2 constructs, that is, performance expectancy, effort tions, hedonic motivation, price value, habit, and behavioral intention were adapted from 72 and the scale for trust was adapted groß (2015), while the scales for subjective norms, from shneor and munim (2019). all items were measured using a seven-point likert–type scale, with the anchors being “completely disagree” and “completely agree.” gender was coded using 1 or 2 dummy variables where 1 represented men and 2, women. age was measured in years, while experience was also measured in years. use behaviour was measured using both scale and frequency of mobile applications use. the researcher created an online questionnaire using google forms in english and was reviewed by university staff, scips and university students for content validity, completion time, and simplicity. the online selected individuals from the researcher`s whatsapp professional groups who were not part of the main survey. preliminary evidence showed that the scales were reliable and valid. latent variable measurement items factor loadings source pe ( pe2. using mobile apps increases my chances of achieving things that are important to me. pe3. using mobile apps helps me accomplish things more quickly. pe4. using mobile apps increases my productivity. 0.995 0.824 pe1-4 adapted and expectancy” in and ee ( ee1. learning how to use mobile apps is easy for me. ee2. my interaction with mobile apps is clear and understandable. ee4. it is easy for me to become skillful at using mobile apps. 0.819 0.848 0.798 from “effort expectancy” in si (social si1. people who are important to me think that i should use mobile apps. should use mobile apps. si3. people whose opinions i value prefer that i use mobile apps. 0.710 0.999 si1-2. ( technologies i use. using mobile apps. from “facilitating conditions” ( 0.914 0.959 from “hedonic motivation” in price value. 1.000 from “price value” in 1.000 et al. (2012). 73 pr ( pr1. i would not feel completely safe to provide personal information through mobile apps. pr2. i am worried about the future use of mobile apps platforms because other people might be able to access my data. information via mobile apps platforms. pr4. the likelihood that something wrong will happen with the mobile apps platforms is high. 0.782 0.945 0.819 (2016). tt tt1. i think they are honest. tt2. i think they are trustworthy. tt3. i think they provide good services to users. tt4. i think they care about their users and take their concerns seriously. tt5. i think they keep users’ security and privacy in mind. from “trust” in groß (2015). sn sn1. people who are important to me think that i should use mobile apps in sci. to use mobile apps in sci. sn3. my colleagues think that i should use mobile apps in sci. sn4. my friends think that i should use mobile apps in sci. 0.827 0.864 0.917 from “subjective norms” in shneor and munim (2019). se (selfplatforms in sci. se2. i have the expertise needed to use mobile apps. mobile apps in sci. platforms in sci. 0.627 0.906 0.922 from “subjective norms” in shneor and munim (2019). bi ( bi1. i intend to continue using mobile apps in sci in the future. bi2. i will always try to use mobile apps in sci. bi3. i plan to continue to use mobile apps in sci frequently. 1.000 from “behavioural intention” (2012). ub (use ub1. i frequently use mobile apps in sci. ub2. i spend much effort in using mobile apps in sci. frequency: roughly estimating please indicate how many times have you used mobile apps platforms in sci in the past year? (please indicate the number of times). 0.890 0.887 1.000 from “subjective norms” in shneor and munim (2019). 3.3 approach to structural equation modelling there are several distinct approaches to sem this study adopted the approach by maune, matanda, and mundonde (2021) the partial least squares (pls) using smartpls 3 software to analyse data. the pls-sem was used because of the small sample size and its predictive accuracy. despite its limitations, plssem is useful in applied research projects and sciences, marketing, organisation, management information system, and business stratcleaned before imported into smartpls 3. 3.4 analysis the pls path modeling estimation for this vations came out of the path analysis model: 74 ple regression (maune et al., 2021). as part of the measurement model evaluation, some items (see table 2) were omitted from the analysis due to high cross-loading and low factor loadings (<0.600) (gefen and straub, 2005). to test the reliability of the constructs, the study used cronbach`s alpha and composite reliability (cr) (table 3). all the crs were higher than the recommended value of each construct exceeded the 0.700 thresholds. convergent validity was acceptable because for reliability and validity, along with the factor loadings for the items are as shown in table 3. discriminant validity was assessed by loadings vif cronbach`s alpha composite reliability ave pe1 0.995 2.400 0.866 0.909 0.834 pe3 0.824 2.400 ee1 0.819 1.459 0.760 0.862 0.676 ee2 0.848 1.683 ee3 0.798 1.538 si1 0.710 1.856 0.809 0.855 0.751 si2 0.999 1.856 0.914 2.380 0.865 0.935 0.877 0.959 2.380 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 sn1 0.827 1.599 0.841 0.903 0.757 sn2 0.864 2.550 sn3 0.917 2.637 se2 0.627 1.349 0.785 0.866 0.689 se3 0.906 2.203 se4 0.922 2.075 pr1 0.782 2.980 0.833 0.887 0.725 pr2 0.945 3.546 pr4 0.819 1.528 bi1 1.000 1.000 1.000 1.000 1.000 ub1 0.890 1.506 0.734 0.883 0.790 ub2 0.887 1.506 bi ee hm ht pe pr pv se si sn ub bi ee 0.743 0.710 0.736 0.518 0.298 0.514 pe 0.471 0.548 0.554 0.010 pr 0.179 0.142 -0.138 -0.385 0.047 0.501 0.579 0.619 0.400 0.230 0.021 se 0.810 0.720 0.603 0.499 0.105 0.056 0.443 si 0.453 0.449 0.382 0.566 0.397 -0.102 0.404 0.458 sn 0.547 0.623 0.521 0.358 0.448 -0.151 0.639 0.570 0.699 ub 0.664 0.675 0.678 0.701 0.264 0.038 0.650 0.650 0.442 0.475 75 was greater than the inter-construct correla2015), with all values below the threshold of 0.900 implying the establishment of discriminant validity (see table 5). 3.4.2 structural model ity of the construct measures, the results of the structural model were evaluated. maune et al. (2021) citing tenenhaus et al. (2005) and avkiran (2018) argue that the structural model analysis is done to provide supporting evidence to the theoretical model: “where: is the endogenous construct and i represents the exogenous constructs, while jo is the constant term in this (multiple) regression model, ij and j tion condition applies.” hypothesised in the research framework. the structural model was assessed based on the r2, q2 the goodness each structural path determined by the r2 value for the dependent variable, the value for r2 1992). the results in table 6 show that all r2 2 establishes the predictive relevance of the endogenous constructs. predictive relevance of the model is achieved when q2 is above zero (0). the results tion of the constructs (see table 6). the structural model was also checked for bi ee hm ht pe pr pv se si sn ub bi ee 0.848 0.742 0.890 0.518 0.404 0.557 pe 0.350 0.604 0.528 0.267 pr 0.137 0.324 0.261 0.428 0.255 0.501 0.674 0.641 0.400 0.227 0.200 se 0.825 0.886 0.623 0.562 0.373 0.232 0.510 si 0.304 0.489 0.380 0.474 0.271 0.204 0.308 0.341 sn 0.574 0.770 0.575 0.396 0.533 0.345 0.703 0.630 0.675 ub 0.775 0.893 0.829 0.818 0.312 0.194 0.759 0.810 0.428 0.636 2, and q2. hypothesis rel ationship stdev t statistics p values 2.50% 97.50% 1 pe -> bi 0.724 0.348 2.083 0.037 0.414 1.727 2 ee -> bi -0.210 0.233 0.900 0.368 -0.595 0.197 3 si -> bi -0.364 0.189 1.922 0.055 -1.108 -0.145 5 -0.246 0.352 0.700 0.484 -1.145 0.240 6 0.173 0.322 0.538 0.591 -0.192 0.972 7 0.503 0.191 2.637 0.008 0.252 1.148 8 sn -> bi -0.011 0.419 0.026 0.980 0.393 0.717 9 se -> bi 0.865 0.425 2.036 0.042 0.562 1.873 10 pr -> bi 0.244 0.257 0.951 0.342 -0.324 0.658 12 bi -> ub 0.664 0.053 12.623 0.000 0.545 0.752 r2 r2 adjusted q2 bi 0.931 0.924 0.906 ub 0.441 0.435 0.344 76 77 of all sets of predictor constructs in the structural model. the results in table 3 show nous constructs and corresponding exogenous values are clearly below the threshold of 5. therefore, collinearity among the predictor constructs is not a critical issue in the structural model. we therefore examined the results as shown in table 6. 3.4.3 importance-performance map analysis (ipma) the ipma was computed to determine the relative importance of constructs in the pls path analysis model. in this analysis, importance endogenous variable in the path analysis dialatent variable scores. this analysis is particularly important in prioritising managerial actions. it is critical for managerial focus to be directed at improving the performance of those constructs that exhibit a large importance regarding their explanation of a certain target construct but, at the same time, have a relatively low performance. in this case, a construct is more important if it has a higher absolute total effect on use lute importance than any other constructs mance if it has higher mean latent variable displays greater performance than any other 4. discussion the key determinants of mobile applications utaut2 model were examined. more emphasis was placed on the cognitive psychological perspective of behavioural intention and use behaviour. adoption and use of mobile applications were considered planned behaviour. a path analysis model developed in the previous study (maune, 2021) was tested using plssem algorithm in smartpls software to ascertain critical paths and relationships. the results of the study are tabulated in table 6. of note, however, was the omission of latent variables et al., 2012; groß, 2015). these latent variables were omitted because of high-cross loadings or low factor loadings (gefen and straub, 2005). the paths were, however, not supported by the data. in light of this, it is important for future studies to validate this using a bigger found otherwise. these paths were, however, not supported by the data. the following latent despite previous research pointing otherwise 78 et al., 2016; roy, 2017; shneor and munim, chao, 2019; tarhini et al., 2019; khurana and tistics. consequently, the results were in line with various studies as shown in appendix 2 relationships between the variables. the structural model was assessed for 2, q2 of paths, with the results shown in table 6. miller, 1992; briones-penalver et al., 2018). sci practitioners and analysts relates to agerial action is likely to bring the greatest improvement of a selected target construct in the pls path analysis model. in this study se proves to be critical for managerial action because of its highest total effect (0.574) (see formance, it would be better for management to focus their efforts on se, in the knowledge that it has a higher importance and its improvements is likely to lead to larger improvements in explaining ub. all else the same, a one unit rise in the performance of se would bring about a 0.574 increase in the performance of ub (see importance-performance analysis. construct performance total effect bi 52.083 0.664 ee 46.889 -0.139 49.791 -0.164 64.410 0.334 pe 58.950 0.481 pr 69.406 0.162 42.448 0.115 se 34.432 0.574 si 50.923 -0.242 sn 44.228 -0.007 ub 46.303 4.1 implications for research this study addresses the call of the previous study (maune, 2021) that emphasised the need to empirically examine and validate the proposed path analysis model/framework. this path analysis model was developed from literature as an extension of the utaut2 (see lication is critical for ci analysts and practitioners given the amount of data that is kept and passes through mobile applications. this data will go a long way in mapping sustainable competitive corporate strategies. results from this study have implications for further future research. despite the popularity of the utaut2 in examining and testing relationships of constructs in the adoption and use of technology, this study followed a different approach by extending the utaut2 framework. this was done by adding four other constructs borrowed from other theories (maune, 2021). the proposed framework was examined empirically to determine key antecedents to behavioural intention and use behaviour of mobile applications in ci. through this approach, the study adhered to the cognitive psychological perspective of human behaviour in decision making. relation to bi and ub. intention and use behaviour of mobile applications in sc,i empirically. this gap in knowledge was uncovered in the previous article (maune, 2021) that used literature review to develop a conceptual framework of behaviour intention and use behaviour of mobile applications in sci. an extended framework was developed to identify key antecedents to behavioural intention and use behaviour of mobile applications in sci. perspective antecedents in behavioural intention were given much attention in this study. the study validated these key antecedents to behavioural intention through plssem algorithm. moreover, this study combined the utaut2 constructs with other four and trust) to examine their link with behaviour intention and use behaviour in sci. results were not far-off from previous studies as shown in appendix 2 in maune (2021). this study complements prior research that investigated relationships between utaut2, bi, and ub in this study hypothesises that performance 79 facilitating conditions, hedonic motivation, trust, and perceived risk were determinants of behaviour intention and use behaviour in sci. not supported by the path analysis model. these by maune, 2021) and support the idea that use behaviour is a planned behaviour (shneor and and ub (liu and tai, 2016; barua et al., 2018; chao, 2019; tarhini et al., 2019; khurana and jain, 2019; gharaibeh et al., 2020). 4.2 implications for practice and bi, yet, performs poorly in explaining and deriving managerial implications, one is able to derive recommendations to drive bi and ub. the model has some key implications that are valid for sci. practitioners and analysts relates to the fact important is the ipma to managerial decision making. the ipma helps management determine important constructs in the pls model. in this study the ipma clearly shows important determinants critical in the adoption and use of mobile applications in sci. it is particularly important in prioritising managerial actions. ipma is helpful for managerial actions to be focused at improving the performance of those constructs that exhibit a large importance regarding their explanation of a certain target construct. in this case, constructs with a relatively higher importance but a relatively low performance are particularly interesting for improvements and must be the focus of management. in fact, investing into the performance improvement of a construct that has a very small importance for the target construct would not be logical, since it would have little impact in changing (improving) the target construct. in this study, se is particularly important for explaining the target construct, ub. in a ceteris paribus situation, a one-unit increase in the performance of se increases the performance of ub by the value of the total effect, which is 0.574. at the same time, the performance of se is relatively low, so there is substantial room for improvement. consequently, in the pls path model example, construct se is the most relevant construct for managerial actions. 4.3 limitations this article examined the key determinants of mobile applications` adoption and use in sci using an extended utaut2 model. using online questionnaires which proved to be a challenge due to the cost of using internet and stress of being locked at home. initially, the researcher had targeted 150 respondents but due to a number of reasons such as the one mentioned above, 98 responses were received. after the data cleaning process, only 96 were found suitable for use for the purpose of this study. participatory methods may be planned, to include various groups in the study. a bigger a longitudinal study would also be useful in future studies that measure relationships between variables. in addition, future studies may extend the empirical analyses by considering advanced pls-sem techniques such as methods to uncover unobserved heterogeneity and conclusions. researchers are encouraged to consider a lot of research ethics to overcome challenges associated with the covid-19 pandemic. despite all this, the researcher had to forge ahead with what works, because truth is a normative concept – truth is what works. 5. conclusion the relationships proposed in this study in extend academics` understanding of the key determinants of mobile applications adoption and use in sci. the study placed more emphasis on the cognitive psychological perspective of behavioural intention and use behaviour. tion and use of mobile applications a planned behaviour. 80 to examine and validate the path analysis model developed by maune (2021), the study followed a deductive approach with primary data collected through an online survey. the study applied the pls-sem algorithm to analyse relationships between latent and observed variables. respondents were drawn from ci practitioners and analysts across the board. were sent via email and whatsapp platforms. completed questionnaires were returned automatically through the google forms platform to the author by 98 respondents and after data cleaning process 96 responses were retained for analysis. reliability tests such as cronbach`s alpha, commonotrait ratio. once the construct measures of the structural model were then evaluated. the structural model was assessed for good2, q2 with the results shown in table 6. demonstrated predictive relevance of the conbriones-penalver et al., 2018). of importance, the path analysis model because the two paths were not supported by the model. this was sci practitioners and analysts relates to agerial action is likely to bring the greatest improvement of a selected target construct in the pls path analysis model. in this study se proves to be critical for managerial action because of its highest total effect (0.574) (see determine the relative importance of constructs in the pls model. the authors recommend management to prioritize the results of ipma. references 2016) intention of adoption of mobile payment: an analysis in the light use of technology (utaut),” pp. 221–230. ajzen, i. 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(2021) the first wave impact of the covid-19 pandemic on the nasdaq helsinki stock exchange: weak signal detection with managerial implications. journal of intelligence studies in business. 11 (2) 30-42. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 2 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index the first wave impact of the covid-19 pandemic on the nasdaq helsinki stock exchange: weak signal detection with managerial implications kalle nuortimoa* and janne härkönenb auniversity of turku, finland buniversity of oulu, finland *kalle.nuortimo@shi-g.com journal of intelligence studies in business please scroll down for article the first wave impact of the covid-19 pandemic on the nasdaq helsinki stock exchange: weak signal detection with managerial implications kalle nuortimoa* and janne härkönenb auniversity of turku, finland; buniversity of oulu, finland; *corresponding author: kalle.nuortimo@shi-g.com received 2 september 2021 accepted 24 september 2021 abstract the global pandemic caused by the coronavirus disease (covid-19) came mostly as a surprise and had a major effect on the global economy. this type of major events that can bring societies to nearly a total standstill are difficult to predict but have a significant impact on business activities. nevertheless, weak signals might be possible to detect beforehand to enable preparation for the impact, both globally and locally. this study analyses the impact of the first wave of the covid-19 pandemic on the nasdaq helsinki stock exchange by utilising large-scale media analytics. this entails gaining data through media monitoring over the entire duration of the pandemic by applying black-box algorithms and advanced analytics on real cases. the data analysis is carried out to understand the impact of a such global event in general, while aiming to learn from the potential weak signals to enable future market intelligence to prepare for similar events. a social media firestorm scale, similar to the richter scale for earthquakes or sapphir-simpson scale for hurricanes, is utilised to support the analysis and assist in explaining the phenomenon. the results indicate that pandemics and their impact on markets can be studied as a subset of a media firestorms that produce a sharkfin type of pattern in analytics. the findings indicate that early signals from such events are possible to detect by means of media monitoring, and that the stock exchange behaviour is affected. the implications include highlighting the importance of weak signal detection from abundant data to have the possibility to instigate preventive actions and prepare for such events to avoid maximum negative business impact. the early reaction to this type of events requires a very streamlined connection between market intelligence and different business activities. keywords covid-19, early signals, nasdaq helsinki, signal detection, social media 1. introduction the contagious coronavirus disease (covid19) caused by severe acute respiratory syndrome coronavirus 2 (sars-cov-2) first identified in wuhan, china in december 2019 caused a large global outbreak and major public health issue (lu et al., 2020). the world health organization (who) declared covid19 a pandemic on 11 march 2020 (ferrer, 2020). these types of rare and unpredictable outlier events, which can have extreme impacts, resemble the black swan events (taleb, 2007): phenomena with almost zero beforehand predictivity and a large global influence. analysing the impacts of the pandemic can prove lucrative as the covid-19 coronavirus pandemic resulted in global lockdowns, sharply curtailing economic activity, while representing a unique experiment with substantial impacts. in the northern europe, in finland, the nasdaq helsinki stock exchange companies were also hit by covid-19, the journal of intelligence studies in business vol. 11, no. 2 (2021) pp. 30-42 open access: freely available at: https://ojs.hh.se/ 31 pandemic influencing the valuation of most listed companies. studies covering the impact of the pandemic on the stock markets have started to emerge. however, the previous research is yet to present a more detailed timeline of the events and to cover and discover possible early warning signals of the event. specifically, large-scale media analytics over the period have not been applied for the purpose. this study analyses the impact of pandemic events on the nasdaq helsinki stock exchange (omhx). the pandemic caused by the coronavirus disease and the course of events are analysed by the means of large-scale media analysis, covering the events from the very first stages for a period of more than a year and a half. the impact of covid-19 is attempted to be understood in general, in terms of the media coverage and the simultaneous events in the stock exchange. the analysis consists of machine-learning based large-scale media analytics to cover a vast pool of media. instead of a before-and-after approach on the impact on the stock exchange, a higher-level general event influence analysis is carried out. specific focus is on the influence of the first wave of covid-19 by dividing it to stages (figure 1). this paper is organised as follows: a brief literature survey is provided in section 2, followed by the detailed description of the research method in section 3, followed by the impact analysis of the corona pandemic in section 4. the discussion in section 5 further addresses the experienced phenomenon in the context of the study and discusses the relevant implications. finally, the paper is concluded. 2. literature review the coronavirus created a global, national, societal, regional, political, economic and commercial crisis, which can be characterised as a disruptive period of instability, uncertainty, and danger, but at the same time, a period of accelerated diffusion of digital technologies and initiatives (karabag, 2020). this type of crisis influences risk management and decision-making under uncertainty (aven, 2013). the impacts of the covid-19 coronavirus pandemic include short-term decreases in emissions, consequences on the deployment of macroeconomic monetary and fiscal stimuli, investments in green deals, and possible further deglobalisation (helm, 2020), impacts on travel and tourism (li et al., 2020), and mandatory closures and reopening of businesses (walmsley et al., 2021). the influence of market reactions to unanticipated, catastrophic events, has been studied for example in the case of the 9/11 terrorist attacks in the usa (carter & simkins, 2004), and in the case of war (schneider & troeger, 2006). generally, in case of any unexpected news, the markets tend to over-react and as more information becomes available and people understand the influences, the market seems to correct itself (phan & narayan, 2020). concerning the stock markets, the consumer industry in the chinese stock market was transitorily impacted by the pandemic in the first three trading days following the start of the pandemic (yan & qian, 2020). significant negative effects on chinese stock returns were observed across all companies (al-awadhi et al., 2020). also, in africa, stock markets reduced significantly during and after the start of the covid-19 pandemic, usually between -2.7 % and -20 %, while the effects were restrictive (takyi & bentum-ennin, 2021). in the usa, the initial impact on the stock market was in the same ballpark as the great crash of 1929, the great depression crash of 1933, and the black monday crash of 1987 (contessi & de pace, 2021). in europe, the stock markets also showed volatility, some markets being more volatile than others (aslam et al., 2021). the impact of pandemics on macroeconomic performance has aroused research attention, while many studies have attempted to explore the effect on the financial markets. these studies indicate the large economic cost of pandemics (elnahas et al., 2018, bloom et al., 2018). table 1 lists further studies that have a focus on covid-19 and the related impacts. when starting to investigate the influence of any unanticipated significant crisis, explanations can be sought by looking at black swan events as defined by taleb (2007), or other relevant concepts such as emerging risk. emerging risk can be considered meaningful and complementary by relating it to known unknowns and black swans to unknown knowns, unknown unknowns, and a subset of figure 1 the research setting. 32 known knowns (flage & aven, 2015). the unknown unknowns that involve the lack of awareness, in practice or in principle, are also referred to as black swans by taleb (2007) and have been linked to seeking for patterns to reveal risks (leidner & schilder, 2010). the research on black swan events in general can be divided into three different stages – preblack swan event, about the black swan event, and post-black swan event (parameswar et al., 2021). social media monitoring, despite its challenges, provides means for the market intelligence function to discover similar events (töllinen et al., 2012). table 1 studies focusing on the impacts of covid-19. focus methodology reference march 2020 stock market crash triggered by covid-19. s&p1500 evidence. event-study methodology (mazur et al. 2021) covid-19 generated negative shocks on the equity markets. event-study method (harjoto et al., 2021) the impact of the covid-19 pandemic on the stock market crash risk in china. estimating conditional skewness (liu et al., 2021) how trust affects global stock market volatility during covid-19. market volatility assessment (engelhardt et al., 2021) covid-19 outbreak and stock market reactions in australia & impact of a stimulus package. negative events assessment. event-study methodology (rahman et al., 2021) covid-19 pandemic and global stock market volatility. egarch (1,1) model (uddin et al., 2021) the influence of government policy responses to the covid-19 pandemic. estimation methods including a random-effects model (zaremba et al. 2021) collapses in the stock markets of 18 major countries during the first wave of the covid-19 pandemic indices and mild explosiveness (contessi & de pace, 2021) the impact of covid-19 on stock market volatility between the u.s. and china. quantile-on-quantile (qq) method (gao et al., 2021) time-frequency relationship between the recent covid19 pandemic and instabilities in oil price and the stock market. wavelet method (chien et al., 2021) the effect of the governments’ responses to fighting the covid-19 pandemic on the returns in the stock market index. difference generalized method of moments (dgmm) (chang et al., 2021) comparative assessment of the impacts of the covid-19 pandemic on the us stock market. multivariate garch, restricted correlation models, dcc and adcc (yousfi et al., 2021) the impact of economic policy uncertainty (epu) on the crash risk of the us stock market during the covid-19 pandemic. gram–charlier series expansion method (dai et al., 2021) potential explanations for the unprecedented stock market reaction to the covid-19 pandemic. text-based methods (baker et al., 2020) stock price reactions to different stages in covid-19’s evolution. hypothesis (phan & narayan, 2020) twitter affecting stock market decisions during the covid-19 pandemic. financial sentiment analysis of influential twitter accounts (valle-cruz et al., 2021) the initial impact of covid-19 sentiment on the us stock market. correlation between covid-19 sentiment and 11 select sector indices of the unites states (us) stock market (lee 2020) the impact of the outbreak on bitcoin. vader scoring (pano et al., 2020) understanding the dynamics of public responses to events under uncertainty. fusion of four deep learning (basiri et al., 2021) analysis of tweets by president donald trump during the early spread of the covid-19 pandemic across the united states. wader, a rule-based model (yaqub. 2020) shifting sentiments during the covid-19 pandemic. machine learning classification on deep learning language models (zhang et al., 2021) the large data-set approach has been applied on emerging topics in the field of competitive/market intelligence that have discussed technological innovation focused for example on the competitive intelligence process (casarotto et al., 2021). however, the large-scale media analysis has not been, to a large extent, applied before to analyse the impact of pandemics, or to detect early warning signals to help in speeding up managerial actions in companies. recent future studies claim that covid-19 would not be a black swan, as a black swan event is defined as being unpredictable, a total surprise, and that the emergence of another coronavirus was predicted by many working in the emerging infectious diseases (eid) field (inayatullah, 2020). hence the argument in this case would be that if there is a weak signal, the phenomenon could not be called a black swan. this has an interesting link to the market intelligence function, and it can cause some debate on how to categorise different events. the identification of weak signals is considered a method to identify strategic surprises in a firm’s environment, while implementing information technology in collection and treatment of the weak signals (lescab, 2019). also, predictive analytics is discussed in the context of market intelligence. the predictive analytics enable informed decisions through a blend of data, analysis, and scientific reasoning (nettleton, 2014). attempts have been made to predict future behaviours by finding patterns in the data through various algorithms (larson & chang, 2016). the data processing, analytical technologies, business centric practices, and methods of business intelligence can also be applied on market intelligence (shmueli & koppius, 2011). specifically, the predictive analytics and social media analysis provide an opportunity to gain first-hand market intelligence applicable to various areas (jeble et al., 2016). the analytics can involve descriptive analytics that entail activities of summarising historical performance to predictive analytics involving estimating potential future events and assessing possible actions to optimise business outcomes (apte et al., 2012). high impact applications are possible in market intelligence through social media monitoring and analytics via sentiment and effect analysis (chen et al., 2012). nevertheless, regardless of the evident potential, ensuring the generation, dissemination, and responsiveness to modern market intelligence remains an ongoing challenge, necessitating further research (romero et al., 2021). advanced predictive analytics is necessary to find weak signals or early warnings of significant events. 3. research method the approach used in this study applies media monitoring with black-box software, including machine learning-based opinion mining on a vast pool of media that covers billions of online documents, including editorial and social media (some). the vast pool of media includes all the data from over 3 million some, and over 100,000 news and other media sources. both free access and subscription-based media are monitored by utilising computer software to collect data. the media coverage of the corona epidemic was monitored and analysed for a period of more than a year and a half on a keyword basis, starting from the very first stages of the appearance of covid-19. the ongoing keyword searches were applied to a large dataset available through a media monitoring software, mined by black-box algorithms. the keywords used included “corona virus” and “covid-19”. the global searches were intentionally limited to finland, and the finnish language, to save computational resources due to the enormous number of relevant data points existing globally. the total number of identified relevant data points with the defined limitations through the computer assisted media monitoring were 569,997 at the time of extracting the data for the analysis. the data include all the pandemic related media coverage in finland during the focus period. this first step of the research of collecting the data on the entire media coverage of covid-19 in finland was carried out with the help of a commercial black box media monitoring software m-adaptive (nuortimo, 2021). the exact digital algorithms on how the software operates are not known to the researchers, but the data was collected reliably by the software making automated relevance judgements on the data points available through the pool of media accurately, the same way every time. specific relevant events in the media were harvested based on the requirements by the researchers. these relevant events in the media formed the attention timeline for the pandemic. the magnitude of the media attention is revealed 34 both in some and the published media. the computer-based media monitoring software used (m-brain, 2015) has different lexicons (corpus) for several languages, including finnish, which is the main language used in the data analysis in this study. the algorithms used by the software first calculated the local sentiments for each identified event by comparing the media event to the search terms, whereas the results were presented for the entire event by indicating the sentiment (neutral, negative, positive, mixed, or unknown sentiment). the sentiment classification accuracy was about 80% at most. noteworthy is that human classification is not 100% accurate either and is dependent on the individuals carrying out the analysis. human based classification is typically not fully consistent among different individuals and is limited to a small number of data points, limiting the possibilities of analysis. the benefit of an algorithm-based analysis is that the computer does the analysis consistently, the same way each time, and can deal with a vast amount of data. the opinion mined sentiments are grouped and compared. the black box software approach has limitations by it providing limited benefits in terms of mainly detecting larger influences. further application of the gained data was necessary. hence a more thorough validation through comparison against findings with a similar software, or by human, might prove beneficial. the pandemic related media coverage was plotted on a timeline to reveal the magnitude of media attention during its course and reveal the main spikes in attention. in the second step the data on the nasdaq helsinki stock exchange (omhx) behaviour was obtained from kauppalehti (finnish multichannel news outlet focusing on economic phenomena and the money market) and the percent change was plotted on the same timeline as covid-19 media attention to enable comparison and reveal how the stock exchange was being affected. the direct causality was not tested but was assumed. specifically, the spikes in media attention were compared to the changes in omhx behaviour to analyse whether any weak signals appear through the media that might be beneficial for future market intelligence to enable learning and avoid the maximum impact of unexpected events of this nature. in the third step, the magnitude of media attention on such unexpected events was put into context to enable estimating the significance of spikes in the media attention and the event classification was attempted. a some firestorm scale (nuortimo et al., 2020), similar to the richter scale for earthquakes or sapphir-simpson scale for hurricanes, was utilised to analyse the spikes in the media attention, and assist in explaining the phenomenon, and possibly enable estimating the impacts of potential risks. in the fourth step, selected media hits appearing during the times of early spikes of the media attention were investigated to further analyse the possibilities of recognising early signals of events leading to the realisation of major risks. finally, the analysis results were used to distil implications for future market intelligence, and implications for managers dealing with risks that relate to several issues, such as crisis communication and stock market behaviour. the research process is illustrated in figure 2. 4. corona pandemic impact analysis the impact of the coronavirus pandemic on the nasdaq helsinki stock exchange was analysed by plotting the media hits over an extended time period to visualise the development of the media attention on covid-19. the development of the nasdaq helsinki stock exchange was plotted on the same timeline to enable the analyses. the analysis indicates that early stages of the covid-19 pandemic, the first wave between 3/2020-6/2020 can be figure 2 research process. 35 considered a media firestorm due to its sharkfin shape in the media analysis and the type of strong influence (figure 2). however, when comparing to a traditional scandal-based media firestorm, covid-19 and the related media communication are not focused on a single person or company. instead, it has a large fundamental influence of a black swan type of phenomenon with crisis type effects (figure 3). the actual covid-19 cases are included in the illustration to enable comparison to the real situation. the main spike of the covid-19 related media hits (marked fs in figure 3) and the linkage to the change in the finnish stock index is clear. this period of high media attention fits the time-period when the omhx stock index collapsed approximately 30%. the media spike is almost exactly in line with the stock index development during the largest peak. the stock exchange recovery began almost immediately after the initial hit. the deepest drop in share prices occurred between 17.2-10.3.2020, while weak signalling from the coronavirus situation in china to the finnish market started to evolve earlier in the beginning of the year. noteworthy is that the first true finnish case of covid-19 was discovered on january 27th, 2020, and the daily cases started appearing from february 10th onwards. this link to the reality in finland may have affected the stock exchange drop. figure 3 finnish coronavirus related media hits/omhx stock exchange behaviour and actual cases of covid-19. 36 concerning the market intelligence function in companies, the small media spike (marked e in figure 3) in 28.12.2019-1/2020 can be considered an early warning or weak signal to the finnish stock exchange that could have been derived from the news about china’s situation. the same signal can be present also in different types of media firestorms, for example those involving some and scandals (nuortimo, 2020). the early warning signals are studied for example in the competitive intelligence literature (lescab, 2019). however, the negative news seemed not to be yet influencing stock-exchange, or the general situation in finland at the time. figure 4 presents the media sentiments classified by media type during the first wave of the pandemic. the findings indicate that the media sentiment has been mainly negative in discussion forums, opposed to the editorial newsfeed, which is larger, and mainly neutral and positive. the editorial newsfeed includes more editorial style communication, also with risk-reducing elements and multiple views. the discussion forums have mainly been a channel for spreading concern about the covid-19 pandemic. in general, the coronarelated negative hits were mainly concentrated to discussion forums, which is logical due to more general sentiments, including the content of some. in order to analyse the impact of the earlystage media-spike, the nuortimo et al. (2020) scale for some firestorms was applied as a basis for estimating the general influence. even though the original scale was developed for analysing media scandals, it seems to be valid also for this type of an incident. although the situation differs from a typical singleincident based firestorm, such as a personal scandal, which is typically a more intense and visible as a negative burst targeted towards a single person or entity, this case seems to form a similar effect, which in this case was a global large scale media firestorm. the pandemic and its effect on media visibility in this case can be considered to resemble a some firestorm. a level 3 firestorm on a scale from 1 to 3, as in the nuortimo model, is considered to have a large global influence: the covid-19 pandemic presents a viable example of an event with global influence. when estimating the impact of the corona media-spike in the finnish language, both the editorial and some sources included the following variables to be addressed: the length of the media spike/days, the height of the spike (media hits some/editorial) and the percentage of negative media hits. by multiplying these variables, a figure that indicates the magnitude of the media attention on the scale 1 to 3 is determined. the magnitude equals the length of the media spike/days, multiplied by the figure 4 media sentiment related to covid-19 pandemic. 37 height of the spike (media hits some/editorial), multiplied by the % of negative media hits. the result in case this case would be = approximately 90 days * 4000 media hits * 0,2(20%) negative media hits resulting in the figure of 72,000, in the finnish language context only. this would mean the magnitude of the media attention on the global scale would reach the value 3 (1-3 scale) in the nuortimo model based on the finnish hits only. the figure would be much larger with the total global hits, which makes it a rather large figure considering that this is based on the finnish hits only. gaining global media coverage, the global media hits are limited by the available computational power. also, despite the unusually low percentage of negative hits related to the media firestorm, the length and intensity contribute to the influence. hence, the measured influence in general can be seen as global and very large, with influence on all companies at all levels. after the initial analysis of the large pool of media sources to reveal the magnitude and trend of media attention, specific focus was given on the potential early warning spikes on the timeline of media attention. the covid-19 media hits falling within the potential early warning signalling period in different media were analysed (table 2). by the end of january 2020, a logical weak/predictive signal chain from different media was in place to possibly enable predicting the main spike of the covid-19 related media hits (the fs event in figure 3). with the help of the predictive signal, it might have been possible to partly estimate the drastic effect of the events on the finnish stock exchange starting on february 17th, 2020. the specific level of action taken by individuals and corporations during the time are outside of the scope of this paper. nevertheless, this paper indicates that a weak signal of the upcoming corona pandemic existed, and finnish corporations could have used the signal to react to the event beforehand. the case of covid-19 and the timeline of related media attention presents an example of 1) a real-life weak signal, and 2) the capabilities to detect significant events via modern media-analytics. the major question in the managerial reaction would be whether the early warning signal from chinese virus spread could have possibly been better utilised by the finnish companies. in the early warning signal analysis, it was eventually clear that this type of virus could cause a global pandemic. hence, early indications of major threats might be possible to link to early actions with logical reasoning in corporate management. in this case some of the preventive measures that were eventually started in march-april 2020 could have been initiated already in the beginning of the year. however, whether the companies have spotted this signal in their media monitoring and market intelligence function remains open in this analysis. in general, if comparing the covid-19 media firestorm to the earlier studied some firestorm scale 2 incident (nuortimo et al., 2020), where the loosing of corporate reputation caused by a wrong wording was a general reason for corporate actions, this firestorm did not seem to clearly influence the corporate image or reputation. predicting upcoming media firestorms and being able to link them to logical reasoning might benefit the future corporate market intelligence function. table 2 samples of main topics appearing in the media during the potential covid-19 early warning signalling period. source date topic indications news/finnish institute for health and welfare 16.12.2019 what is coronavirus start of discussion local news, “aamuset” (city media for turku) 9.1.2020 pneumonia cases in china possibly originated from coronavirus first signals of coronavirus in china local news 30.1.2020 who announces coronavirus as a global threat virus is spreading from china, who global threat classification facebook 30.1.2020 coronavirus is more lethal than seasonal influenza, spreads more slowly for now first popular estimates of threat severity news/ “lentoposti” (aviation news) 30.1.2020 klm cancels chinese flights first corporate actions “yle” news (the finnish broadcasting company) 31.1.2020 coronavirus death toll now over 210 persons, keeps spreading in china more implications of threat severity yle areena 31.1.2020 chinese tourist had coronavirus in rovaniemi, finland first signs of virus spreading to finland 5. discussion this study highlights the possibilities of estimating and measuring the impact of largescale media appearance (covid-19 pandemic in this case) on stock-listed companies (nasdaq helsinki in this case) via algorithmic media monitoring by targeting a vast pool of media through suitable algorithms. the presented approach consists of a large dataset media sentiment analytics via a black-box software, applied on covid-19 over an extended timeperiod, initially appearing as a media firestorm, and comparing the timeline of events to stock market behaviour. the magnitude of the media firestorm is assessed and implications for company analytics considered. the main results are as follows: 1) the impact analysis of covid-19 based on a large dataset and media firestorm scaling can indicate an influence at a general level, such as the immediate impact on stock exchange performance. the sentiment and visibility in different media, including the social media and editorial sources, can reveal some general issues related to the impact, i.e., how negative has the sentiment been, and how much media coverage is in question. 2) the early warning signal could be spotted in this case to provide insights for preventive action, should this type of analysis be utilised in corporations. 3) the managerial actions could be initiated more proactively in case they need to react to early warning signals. 4) theoretical debate remains, whether the event can be considered a black swan due to both global and local weak signalling received from the event. this provides basis for some general scientific counterargumentation. the main managerial contribution includes the possibilities for faster indication of negative future events that may come with early warning signals before the firestorm of large-scale media attention. being able to link this type of modern analytics to the imminent risks by the means of logical reasoning may benefit the future corporate market intelligence function and enable earlier corporate reaction or risk management. hence, managerial actions could also be planned faster and more accurately. in this case, if the actions could have started already in time of the early warning signal with allocation to different functions of the company, obvious functions would have been crisis communication, financial planning, and health, safety and environment in hrfunction. the scientific research method development aspect is beneficial compared to interviews and questionnaires. this type of an approach is a relatively fast way to get the main event influence from a large dataset. to get to the detailed topic level, a hybrid approach (nuortimo, 2021), could be applied. the novelty of this research lies in the innovative combination of data, methodology, and modern analytics. the findings support earlier studies on predictive analytics that aim for informed decisions through finding patterns in data and combining the data with logical reasoning. when comparing to the literature, the debate of classification of the covid-19 coronavirus pandemic remains, whether the event is a black swan and if it has some early warning signalling. globally, there has been previous signs of earlier pandemics (eids) before (inayatullah, 2020), and locally the warnings have been received also in finland. in case of measuring the event, this article tests the some firestorm scale (nuortimo et al., 2020) level 3 and has implications. even though level 3 of the scale can contain multiple types of events with a global influence, the scale seems to be applicable for measuring the general event magnitude also in this case. as a scientific contribution, this paper proposes two possible event classifications: 1. black swan with both global and local early warning signaling 2. social media/media lvl 3 firestorm with: a) features that relate to global pandemics b) some level of early warning signaling, usually related also to scandals c) lower level of measured negative sentiment in general newsfeed compared to a regular scandal d) large diverse global influence on multiple sectors e) no clearly visible influence on corporate image or reputation 39 one major limitation of this paper, however, involves the fact that the inaccuracies related to the algorithmic analytics prevents reaching a 100% research validity while utilising a black-box software. utilising a second software in parallel could have increased the validity. nevertheless, in this case, 100% validity may not even be necessary, because the goal is to measure the general level of influence, not the details related to, for example, corporations. the get to the detailed level, a hybrid approach (nuortimo, 2021) is suggested, while leaving some room for further studies related to the covid-19 coronavirus pandemic influence. also, this study does not carry out correlation analysis. future research concerning media firestorms is required to further validate the scale to assess the magnitude of different types of events, while the general scaling level seems appropriate for assessing this type of events with a large impact as well. 6. conclusion better integration of the market intelligence function, namely media monitoring through the utilisation of new tools, may enable linking the early warning signals of significant future events to necessary corporate actions or risk management earlier than currently possible. the findings of this article agree with inayatullah (2020) in that covid-19 was not a total black swan and could have been partially anticipated. the magnitude of events might be possible to assess by means of media firestorm scaling to provide input to company processes to have grounds for reacting to different events spurring from the business environment. these events also include black swan type media firestorms that have a very large impact and low predictivity. in the case of the coronavirus pandemic, the early warning signal was available from china’s situation to the finnish market before the market reacted. the type of approach suggested in this paper can be 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(2021). rise and fall of the global conversation and shifting sentiments during the covid-19 pandemic. humanities and social sciences communications, 8, 120. doi:https://doi.org/10.1057/s41599-02100798-7 36 o p i n i o n s e c t i o n the development of north sulawesi through competitive intelligence julyeta p.a runtuwene, audy aldrin kenap and verry ronny palilingan 1 1 universitas negeri manado, kampus tomohon, sulut, indonesia email: info@mail.unima.ac.id received september 3 2012, accepted february 9, 2014 abstract: in this paper we present how competitive intelligence was introduced into the north sulawesi in indonesia. starting from education and to the development of a threshold of graduated student in that field, it was necessary to move to the conquest of local policy positions to be sure that the methods and tools of competitive intelligence will be used to second regional development. the sulut region constitutes a living laboratory where the methods and tools of competitive intelligence have been used not only to develop a competitive intelligence regional unit, but to create policy conditions enabling the development of this unit. keywords: competitive intelligence, indonesia, north sulawesi, sulut region 1. synthetic presentation of the north sulawesi region (sulut) the north sulawesi province was recognized in 2011 and has about 2.5 millions inhabitants, among them 65% are catholic. the region is characterized by several volcanoes still active for some of them and by several diving spots of international value. the province gets its revenues mainly from the fisheries and from agriculture, but different natural resources are threaten by different market shifts. for instance the introduction of cloves into cigarettes (after the extraction of the oil from the cloves) is decreasing because people will smoke less or will smoke lighter cigarettes. in the same way copra oil and palm oil are competing. it is urgent to develop new products from the natural resources or to promote a better quality to maintain available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 1 (2014) 36-42 mailto:info@mail.unima.ac.id https://ojs.hh.se/ 37 o p i n i o n s e c t i o n a high price level. the following maps extract shows the geographical location of manado city: figure 1. the manado area (from http://www.north-sulawesi.com/northsulawesimap.html) 2. method several year ago the university of aix marseille (paul cezanne) developed with the universitas negeri manado (unima) a joint dea program in technology watch and competitive intelligence. this cooperation was conducted in such a way that students may follow the dea in france in marseille at the crrm, and in unima in the tomohon city in the north sulawesi. both groups of students develop during the dea (now called master second year) various projects dealing with the development of the region as well from a natural resources point of view as of a global approach to get better local conditions favoring industrial and tourism development. after the dea or the master degree, some students continue their study to get a phd in competitive intelligence in marseille (crrm, university aix-marseille iii). the development of this process during more than 15 years paved the way for the development of a local consciousness about competitive intelligence not only focused on industry development, but concerned globally by the social impact of the development of the region. various subjects such as water resources, fish resources, development of tourism, the creation of added value products from natural resources, energy alternatives, the use of competitive intelligence to improve various educational programs, contributed to create among various different slices of the local society a deeper concern for the critical points to be examined in depth and if possible solved to improve the local social conditions as to achieve a long term competitive advantage. at the very beginning, the students (most of them coming from various local institutions such as towns districts, administrations, education, police, private companies) planned to develop locally a competitive intelligence unit which will provide key strategic information to think-tanks, for them to be able to formulate advice and recommendations for local decision makers. however, it was very rapidly noticed that many internal forces did not accept the idea to move ahead, since this will http://www.north-sulawesi.com/northsulawesimap.html 38 o p i n i o n s e c t i o n modify the local political power in place today as well as some industrial positions. it was then decided to used competitive intelligence not only to promote new economic and development conditions, but to move to local policy to promote in some key positions people which will have a competitive intelligence background and which will be able to facilitate a global move of the local stakeholders to new horizons. this is the story of this global development of competitive intelligence in north sulawesi, that we are going to present here, underlining the main steps of its development and the actual stage of development opening the way to a new mind set among decision makers 3. the structure of the local decision makers the region is politically structured around a governor, and for the manado city a bupati (equivalent to a mayor in the western world, with a land extension far larger than the simple town area) since the bunaken island (one of best diving spot in the world also depends of manado city). the university play a critical role through the education of local people involved in the municipality, administration and other local structures. there are seven universities in the region among them three are of importance and the largest one being unima. from a political point of view, the main political parties present are the democratic party which is the one party were the president of indonesia sby belongs to, and the golcar party of the former president magawati. the election which are organized as well for the governor as for the election of deputies and bupati are controlled by a supervisor which is appointed by the central government in jakarta. other structures are also present for instance the police which depends on the bupati, and the army which is linked to the central government and to the governor. other institutions private or public are more of less related to the former decision makers, except for religious power structure which is divided in two parts, one christian (the larger part) and the second muslim. the relationships with the central government and more specifically with the democratic party are important since many local decisions concerning the election organization as well as the validation of the candidates, etc. are related to them. 4. creating a critical mass it is clear than in regions like the north sulawesi, where competitive intelligence is quasi unknown and where most of the population is rather conservative, the people in place is reluctant to move to new (may be uncertain) conditions. we therefore think that the introduction of the competitive intelligence concept, method and tools necessitate the creation of a critical mass of people to spread the idea in various areas of the inhabitants. the following table summarizes the results obtained from 1993 to 2010 through the development of the dea, master, and phd for indonesian students with a focus on ci (from north sulawesi and other parts of indonesia). 2010-09 2008-07 2006-05 2004-03 2002-01 2000-99 1998-97 1996-95 1994-93 dea sulut 16 18 12 13 16 20 21 0 0 dea other 0 2 3 0 0 0 5 3 4 phd sulut 0 5 2 0 2 6 0 0 0 phd other 1 2 0 0 0 0 2 0 0 table 1. sulut sulawesi utara (north sulawesi) the number of students and more specifically the various subjects developed in the dea-master thesis as well as in the phd, created to a certain degree a critical mass necessary to implement a local competitive intelligence spirit. in the same time we edited two books in english dealing with regional and industrial application of competitive intelligence, with various examples all related to the indonesia development. (dou 2003, dou 2007) 39 o p i n i o n s e c t i o n we also developed a phd dealing with the study of the development of added value products in the region. these ideas came out of the competitive intelligence field. energy being a very hot problem because of the lack of energy resources, different works were done on biodiesel and different conferences presented about this subject related to ci (liow 2010, kister 2010). 5. development of a close relationship with the democrat party one of our most talented students developed during her phd a project, the creation of a competitive intelligence center in indonesia, close to the french notion of a model of economic intelligence (manullang 2003a, 2003b) with a national senior advisor connected. during her phd (manullang 2005), several key conferences were developed in jakarta 1 mainly, with the venue of various top french people in the field 2 (alain juillet, philippe clerc, henri dou). this gave the opportunity for her/the student to have various contacts with national indonesian policy makers and then to promote this idea. other meetings of the same type were also held in bandung , medan, manado). the result was half of what we expected: because we did not have any indonesian success story in the domain the decision makers if the assisted to the various conferences and talks did not feel concerned and the idea to promote competitive intelligence at the national level failed. but, in spite of this failure, the person who promoted the idea integrated the democrat party at a key position enabling her to present and push ci at the national level some of the initiatives which will be developed in sulut. this was the starting point of the use of the methods and tools of competitive intelligence on two ways: one technical using the patent analysis to promote locally new ideas of development by showing clearly that the creation of added value products from local resources will be possible since in the world the same resources were the source of profit through new products and applications. it was obvious that in these various analyses we take 1 see http://s244543015.onlinehome.fr/ciworldwide/?p=2 8 2 see http://www.ciworldwide.org and from china see http://s244543015.onlinehome.fr/ciworldwide into account the local level of competences as well as the facilities available to select the right products and technologies to develop and use (dou 2004). the second step paved the way of the development of a strong political interaction that we have to create: one of our phd student (tulungen 2006) from the region was jobless and we took this opportunity to present its candidature at the national political instances to fill the role of mediator and guarantor of a fair progress for future local elections. because competitive intelligence was known at a certain level of the political instance (thanks to the work of the very start promoter), he was granted the job. 6. competitive intelligence influence and human network information it is well know that besides the classical role of implementing and facilitating the decision in companies and institutions competitive intelligence presents other aspects such as the development of human networks and the creation of spheres of influence. in unima, the only cooperation agreement with a foreign university was at this moment the one concluded with the university of aix-marseille (crrm). this situation opened to the local students the opportunity to have various grants from the local governor and from the local municipalities to study in france. this situation favored a better perception of competitive intelligence in the university and helped for the promotion of one of our phd students at the grade of vice rector of unima (tuerah 2003). two years after (2008) the same student became rector of the university. two years later, the position of professor in competitive intelligence was created in the unima university opening the way to a more structured development of this discipline. this was achieved in 2010. the person in charged, got her phd in marseille and presented 4 years before the project to develop a competitive intelligence unit in the region (runtuwene 2007) to one of the main conference held in jakarta. she developed also the local facilities: internet via satellite and office in town to shelter the competitive intelligence centre in manado. the last step, but not the least, was to gain a top political position in the regional hierarchy. this http://s244543015.onlinehome.fr/ciworldwide/?p=28 http://s244543015.onlinehome.fr/ciworldwide/?p=28 http://www.ciworldwide.org/ http://s244543015.onlinehome.fr/ciworldwide 40 o p i n i o n s e c t i o n was achieved in 2010 with the election of the bupati of manado (lumentut 2008) city of one of our phd students. the election was difficult since the first round gave rise to a suit which conducted the judge to call for a second new election which was wined definitely in october 2010. 7. the recent development at the beginning of 2011, there was the official announcement of the creation of the competitive intelligence unit of the manado region. it operates from the university, in close relationship with the manado city and the national poll representative. in these conditions we created locally the triple helix (leydesdorff 1998) condition enabling the development of various public and private partnerships in area such as the promotion of cloves, coconut products, corn, tourism, etc. to gain broader strategic abilities for regional competitive advantage. this competitive intelligence unit, the first in indonesia will be promoted at the national level being in the same time leverage for the regional development but also an attractive structure to implement real and robust projects. it must also be noted, that a few years ago, the work done by various competitive intelligence students helped to develop a project to clean the city in relationship with tourism development. this led manado city to obtain the title of the best cleaner city of the year in indonesia (“adipura”), the price was given to the city by the president sby in person 3 ). also in the same time manado city was choosen to organize the world ocean summit which bring to the city various foreign delegates and promote the city and its vicinity (for instance the bunaken islands diving site, etc.). these realizations helped since they show to the inhabitants that international initiatives may go through when they have a guideline and a road map closely related to competitive intelligence. 8. conclusion in this example, we have shown that to create the conditions necessary to start the introduction of the competitive intelligence concept, methods and tools in an area where this discipline is quite unknown took several years. the same situation 3 see phd thesis lumentut, opus cited. can be reach if one wants to develop competitive intelligence activities in an area where the education of the stakeholders has not been to the level. this is the case for instance in certain poles of competitiveness. of course if you set up some basic conditions and practice the policy of the “laissez faire”, the implementation of competitive intelligence can be done in time, but it will take too long. we are now in a world where the speed of almost all activities increases. if you are not going fast enough your competitors will overpass you and you will not be able to catch up. the second point which is important is that competitive intelligence is related to social cohesion and then its perception by the local people is important. cases of success are needed and winning the “adipura” context and hosting the world ocean summit were two elements which show directly the usefulness of the competitive intelligence process (those two events were widely related to efforts made in the local press and tv). the third point which is important to recall is that policy makers decide. if they are not convinced of the efficacy of the method or if they feel that they are taking some risks, nothing will happen. it is clear, that for developing countries a strong commitment from the policy makers is necessary. in developed countries and for instance in countries like france, which have created various poles of competitiveness, it is clear that the role of the central government should not end after the selection of the poles or after some initial evaluation processes. the role of the central government should be permanent and it should be done through the road map and the governance of the pole, in close relationship with a competitive intelligence unit which will provide independently of the stakeholder information that is strategic enough to be the seed of a starting collaboration between the participants. the animation (this is true for a region as well as for a pole of competitiveness) need to be catalyzed and among the best catalysts the use of patents analysis (dou 2009) (apa 4 automatic patent analysis) is important since it provides an unique information filling the gap between fundamental aspects of research and industrial development. 4 see http://www.matheosoftware.com/en/products/matheo-patent.html. http://www.matheo-software.com/en/products/matheo-patent.html http://www.matheo-software.com/en/products/matheo-patent.html 41 o p i n i o n s e c t i o n on a regional point of view and to create a strong motivation among the inhabitants, new techniques have to been used. in fact giving information even of high quality is not enough. people need to break the silence (perlow 2003) and open a fair collaboration 5 . to reach this objective stories which will make them dream are necessary. on a r&d point of view the application of this storytelling management (salmon 2007) can be done through the use of patent analysis. this will provide the best way to construct a history of the development of products and services and show clearly that what others do can also be done here. because the story will concern resources found locally over many decades, even centuries, focus should be on bringing back people to their roots and strengthen the local cohesion. we used a form of storytelling management to pick up innovative attitudes and maintain the local unity. now the actors are on stage and they must succeed if they want to maintain their position and continue to be backed up by the inhabitants. of course it will be a difficult challenge but “the game is worth the candle”, as we say, and we believe that this will create an incentive strong enough to develop the condition of success without falling, as is pointed out “in the triple mezzogiorno” by jean marie rousseau on the nega-development (rousseau 2010). acknowledgement we wish to thank professor henri dou for his help and involvement in the development of the technology watch and competitive intelligence in the manado region., as well as miss sri damayanty manullang for her constant help in favor of the development of competitive intelligence in sulut. bibliography henri dou, sri damayanty manullang and dou jean-marie jr, 2003, sri manullang, competitive intelligence, technology watch and regional development, editor editor muc consulting group, december jakarta indonesia isbn 979-98236-0-9 5 opposite to the silence, but with the same result, is the development of a constant «noise» done by the exchange of perfect useless information. henri dou and sri manayanty manullang, 2004, competitive intelligence and regional development within the framework of indonesian provincial autonomy, education for information, n°22, june henri dou, sri damayanty manullang and dou jean-marie jr, 2007, competitive intelligence and technology watch for industry development, editor departemen perindustrian, indonesia henri dou, 2009, palm oil strategy – general considerations and strategic patent analysis asia pacific journal of innovation and entrepreneurship, vol 2, pp. 75-93 sri damanyanty manullang, 2003a, veilles , intelligence compétitive et développement régional dans le cadre de l'autonomie en indonésie., colloque sur l'information elaborée, ile rousse, mai, ile rousse, colloque sur l'information elaborée, octobre 2002isdm n°6 article 38 information science for decision making, http://www.isdm.org sri damayanty manullang, 2003b, increasing innovative thinking in indonesia. the case study of coconut, embrapa, brasilia, brésil, colloque international, méthodology d'analyse de l'information, october 29th sri damayanty manullang, 2005, for an indonesian program in competitive intelligence for the economic development of the nation, phd thesis, university aix marseille, centre de saint jérôme. franky tulungen, 2006, application of competitive intelligence for the development of the minahassa region (north sulawesi). strategy for the development of smes in the domain of cloves and jatropha curcas; phd thesis university aix marseille, centre scientifique de saint jérôme. philotheus tuerah, 2003, statistical analysis in technology watch. implication in the educational program of north sulawesi, phd thesis university aix marseille, centre scientifique de saint jérôme. julyeta runtuwene, 2007, regional development in indonesia. the creation of the competitive intelligence unite of the province of north sulawesi, university of marne la vallée veicke lumentut, 2008, application of competitive intelligence to sustainable tourism development strategy in manado city, north sulawesi, indonesia, phd thesis, university of aix marseille, centre de st jérôme http://www.isdm.org/ 42 o p i n i o n s e c t i o n christian salmon, 2007, storytelling, la machine à fabriquer des histories et à formater les esprits, edition la découverte, paris leslie perlow 2003, is silence killing your company ?, harvard busibess review, vol 81, n°5, may leydesdorff l.et etzkowitz h., 1998, the triple helix as a model for innovation studies, (conference report), science & public policy vol. 25(3),pp.195-203,1998 http://users.fmg.uva.nl/lleydesdorff/th2/ihe98.ht m herdy liow, 2010, bibliographic study and use of the method and tools of the competitive intelligence for the study of the production of biodiesel in indonesia. strategy for the development of energy sources in the sulut, phd thesis, university aix marseille, centre scientifique de saint jérôme jacky kister, herdy liow and henri dou, studies of process design of biodiesel industry using competitive intelligence methods, vsst, toulouse, octobre 2010 jean-marie rousseau, 2010, in the triple mezzogiorno? southern italy – eastern germany, eastern poland. regioanal development forum redefo, ministry of regional development, editors antoni kuklinski, emilia malak-petlika, piotr zuber, 2010 isbn 978-83-7610-170-5 (see the article of jean-marie rousseau: quo vadis europe? competitiveness among stumbling blocks. http://users.fmg.uva.nl/lleydesdorff/th2/ihe98.htm http://users.fmg.uva.nl/lleydesdorff/th2/ihe98.htm 42 competiveness from contextualisation of supply chain knowledge gabriela lópez 1 , steve eldridge 2 , salomón montejano 1 , patricia silva 1 1 human resources department, production and quality, universidad autónoma de aguascalientes, aguascalientes, méxico 2 operations management and logistics department, manchester business school, manchester, uk gabynvest@yahoo.com.mx received june 3, revised form 10 september, accepted 22 september 2012 abstract: this paper provides a discussion about the need of a continuous contextualisation of knowledge practices in organisations. also, a proposal of a knowledge representation to contextualize and diagnose supply chain knowledge is presented. the proposed knowledge representation is a codification to incorporate context in a way that some form of diagnosis of supply chain practices can be carried out, which could reveal possible favourable and unfavourable effects of practices in a supply chain. in addition, this paper has been constructed in excel® as a prototype, with the aim of being used in workplaces to support decisions making in smes supply chains. for this investigation, a number of best practices have been analysed. also, focus groups and individual interviews to operations managers, from global, small and medium enterprises, have been carried out. subsequently, it has been possible to integrate the proposed coding representation to enable a contextualisation and diagnosis of supply chain knowledge. keywords: knowledge management, supply chain, competitiveness, contextualisation, diagnosis 1. literature review 1.1 supply chain nature and competitiveness an effective implementation of knowledge management is required by supply chains in order to remain competitive. supply chains are strategic frameworks to ensure customer value, relationships, resources optimization, and practices integration. through this investigation, inadequacies for an efficient knowledge management cycle, in supply chains, have been identified. such identified inadequacies avoid completion of the knowledge cycle in supply chains. mainly, there is a lack of contextualisation and structure for supply chain knowledge (sck). consequently, organisations are not gaining the benefits from self-learning, adoption of best practices, which are elements, incorporated in an effective knowledge management implementation. along supply chains there are two relevant flows: information and materials. information is the raw material of knowledge, which requires contextualisation in order to become executable; an important difference between knowledge and information. knowledge in supply chains can be in the form of best practices, however to consider these as cures for everyone is a mistake, instead these can work in different contexts. an integrated and collaborative supply chain (sc) of an organization offers full potentials to become competitive (hoek, 2006). the nature of supply chains is to integrate key business available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 42-50 mailto:gabynvest@yahoo.com.mx https://ojs.hh.se/ 43 processes like: materials sourcing, inventory management, routes to market, forecasting, production programming and physical distribution in companies. lambert and cooper (2000) define a “supply chain as operations from end user through original suppliers who provide products, services, and information that add value for customers and other stakeholders”. today, there is a competition among supply chains meeting customer needs and to facing globalization, complexity, relationships and change. “meeting customer needs better than the competence is a source of competitive advantage” (grant, lambert, stock, and ellram, 2006). for this reason, supply chains are urged to continuously improve their practices. in complex business conditions higher levels of integration may be required and appropriate supply chain practices may be adopted. “a supply chain must be connected, in communication and collaboration to improve efficiency in its practices” (desouza and chattaraj, 2003). integration of practices implies planning and controlling all operations so they can fit together as ‘a unified whole’ (barki and pinsonneault, 2005). integration of all practices in a supply chain requires what trent (2008) state an “end-to-end perspective” which is to look across the whole supply chain processes; from planning to delivery (stewart, 1997). 1.2 best practices laugen et al. (2005) state that “continuous improvement of best practices in all areas of the organization will lead to superior performance capability, leading to increased competitiveness”. best practices are one of the types of external and internal knowledge that can be used in the supply chain. therefore, the discovery and adoption of best practices knowledge offer a full potential to become competitive. in the literature, best practices focus on supply chains factors, among others, on information sharing, time, value, suppliers’ reduction. information sharing is important for supply chains, especially about markets, for example, demanddriven supply chain concepts and quick response (qr) logistics, under the umbrella of ‘just-in-time’. also, best practices integrate information about efulfilment within lean (trent, 2008) and agile manufacturing philosophies, target the collection and sharing of key information. best practices also indicate outstanding performance for the supply chains in terms of time, for example, reengineering of processes, single minute exchange dice (smed), resources optimisation and bottlenecks elimination. addition of value is another important factor described in best practices, which include advance planning systems, benchmarking, optimisation methods and value chain. best practices also describe success factors such as organisations alliances (ahumada-tello, zárate cornejo, lópez, and alberto perusquia velasco, 2012), cross-functional teams, partnerships and outstanding information systems like enterprise data interchange (edi), enterprise resource planning (erp), barcodes, collaborative planning and forecasting replenishment (cpfr), efficient customer response (ecr), mass customisation. the reduction of supplier base is another factor on which best practices have been focused. other best practices include outsourcing and supplier strategies and external (vertical) integration strategies from upstream suppliers and downstream customers. these aim organisations to focus on core processes, which have a more differential advantage. the rest of the processes are outsourced, including practices such as subcontracting manufacturing, transport, and warehousing and inventory control services. in general best practices dictate a need of supply chains for a holistic or endto-end perspective (trent, 2008), which is related to the integration of practices, another main characteristic of supply chains purpose. however, it can also be dangerous if possible unfavourable effects are not considered (section 1.5) from best practices. this is also because the term “best practice is rather relative, not an absolute standard” (ungan, 2004). best practices are knowledge artefacts originated from experiences describing a full process but only describes successes but no failures (weber, aha, and becerrafernandez, 2001) and it is important to recognise and measure such possible unfavourable effects. similarly, compatibility, has been identified by ungan (2004) as one of the main elements impacting the implementation of best practices suggesting better understanding and mapping of practices leading to better implementation. this represents a full cycle of improvement too, which is needs to be well recognised and systematic in organisations processes, and can be reinforced by the knowledge management processes. 1.3 knowledge management according to hult and ketchen (2005) “knowledge management appears to be an intangible creator of superior performance in the supply chain by matching knowledge elements, such as, memory, learning capacity, use and access knowledge with the supply chain strategy”. an effective knowledge management focuses on enhancing the learning process through processes of the knowledge 44 management cycle (figure 1). the four main processes of knowledge management are described as follows:  discovery of knowledge, which is the process of acquiring knowledge  capture of knowledge, referring to maintain knowledge from the main elements (people, entities) of an organisation  sharing knowledge is the activity of knowledge collaboration  application of knowledge is the process of become knowledge executable (becerra, et al., 2004) figure 1: processes of the knowledge management cycle (becerra, et al., 2004) these processes of knowledge management are similar to the learning processes (kresbach-gnath, 2003), which are focused on the vision of the organisation:  identification of knowledge (analysis of current environment and situation of company)  diffusion of knowledge (employees participation, training, communication)  integration and modification of knowledge (leadership, cooperation, workshops)  action of knowledge (strategy, projects). 1.4 structure for supply chain knowledge no pre-existing structure to represent supply chain knowledge (sck) was identified that could accommodate the knowledge contained in best practices. the lack of structure for best practices knowledge represents a barrier making it explicit to capture knowledge. thus, the construction of a structure for supply chain knowledge taking best practices as a main source is recognised as highly desirable. there is a need to structure knowledge in order to enable integration and processing of supply chain knowledge, for example, converting implicit knowledge into explicit knowledge, in other words, being able to capture, to record knowledge (2nd process shown in figure 1). there is a need of a structure of compatible supply chain knowledge. becerra et al. (2004) stated that “knowledge needs to be structured and captured in order to be applied or actionable” (4th process of the km cycle). unstructured information might overwhelm practitioners who instead of transferring key concepts and creating learning environment and reflexion (1st process of the km cycle), focus on mini projects with no available time to convert information into knowledge. in consequence, the understanding, implementation and integration of practices are affected. today’s managers seem overloaded with unstructured knowledge that grow rapidly and massively, which in consequence affects sharing key concepts to their employees, making complex a conversion of information into knowledge and continuous understanding of practices. it is important that organisations recognise that information is the raw material of knowledge. “a large piece of the organisation’s knowledge asset is unused each day without a mechanism to capture and convert it into articulated to adopt new practices and for knowledge” (radding, 1998). there is a need of a possible structure to move towards a way to capture, making more sense out of the endless and unstructured knowledge and information that progressively accumulates. however, in the literature review, knowledge engineering attempts to help humans in their jobs by trying to make knowledge explicit, by representing knowledge especially within a machine. best practices can remain as information if not contextualised and applied, as will be discussed next. 1.5 contextualisation for supply chain knowledge continuous improvement of practices is necessary to become competitive, for better decision making 45 and for deliberate strategies, which is part of “strategic learning” (axelsson, et al., 2005). at the same time, it is important to recognise and measure opportunities (i.e. best practices) in order to positively impact organizations competitiveness (grant, et al., 2006). there is a need to contextualise best practices knowledge continually, the nature of knowledge is timeless different from information which is “limited timeliness” (radding, 1998). “the efficacy for any practice can only be determined in the context of a particular firm’s strategic and environmental contingencies” (huselid, 1995). to start quantifying this kind of contextualisation is important, which means being aware of practices impacts in alternative contexts. bessant (2003) suggests, for example, a regular revision and assessment of practices for their successful implementations. best practices only describe the processes but not its suitability or consequences if they were adopted in different contexts. lindvall (2003) stated that “knowledge must be captured, stored and organized according to the context of each company in order for it to be useful as well as efficiently disseminated”. the term “best practice is rather relative, not an absolute standard” (ungan, 2004), who also identified three weaknesses in best practices:  they do not provide reasons why they are considered best  they only rarely link the practices investigated to company performance  they are considered generic, best for all companies’. best practices frequently do not specify nor clarify the context in which best practices are suitable to be adopted. at present, the unfavourable consequences of best practices do not seem to be systematically recorded and do not specify with evidence contexts in which they could work. it is important to manage best practices knowledge to avoid ambiguity about their possible effects, acknowledging its compatibility with a specific supply chain context. by revealing the possible unfavourable consequences the discovery of knowledge may be enabled. to start quantifying these kind of interrelationships is relevant, “it is important to recognize best practices as specific to certain situations” (swan, newell, and robertson, 1999). the less knowledge about supply chain practices is contextualised; fewer benefits are obtained from its adoption, in consequence and more assumptions are required involving more risk. in fact, if practitioners do not identify beforehand the possible impacts of a best practice, unfavourable impacts may be created when it is adopted. in summary, the process of discovering supply chain knowledge is restricted by the lack of quantified, context-specific details provided by the best practices knowledge. when adopting practices, these may develop different capabilities that might or might not be suitable for different sectors. in the literature, most of the examples of best practices (described in section 1.2) were related only to certain sectors, such as the automotive and food sectors. for instance, quick response logistics was originally created in and for the fashion and apparel sector (christopher, 1992). when adopting practices, a practitioner should be aware of other sensible aspects not commonly revealed in currently disseminated best practices. for example, erp systems usually considered best practice involves high interdependencies that could affect multiple business functions and organisations simultaneously when adopted. for instance, it would be interesting to know which best practices are suitable to develop specific capabilities, as an example:  how flexibility capability can be improved with computer-based automation and realtime process control (tracey, vonderembse, and lim, 1999).  how innovation capability can be inhibited with licence controls (thomas choi, 2004)  how time reduction can be improved with specific distribution methods (hult and ketchen, 2005) quantification of the appropriateness of a practice on a given supply chain context seems to be required, so it can be adjusted accordingly. in other words, there is a need of continual awareness of what practices are suitable to what specific contexts (i.e. sectors). supply chains need to ensure that the implementation of best practices is carried out in a way that is suitable to their business context. currently there is no articulation of the possible context-specific conditions of a supply chain. thus, best practices knowledge should be moderated and contextually-specific, so as to allow the creation and control of knowledge. 2. methodology from the previous sections, it was identified a number of weaknesses in the knowledge artefact best practices. there is a need to contextualise best practices in supply chains, but also to recognise failure experiences. such inadequacies impede the successful implementation of the knowledge management processes (section 1.3), consequently 46 a continual learning of supply chains in this new era of competition among supply chains. therefore, the methodology of this project was adapted and focused on answering the following research question: how to structure and contextualise supply chain knowledge? basically, in this case, knowledge is defined as applied information about practices along the supply chain. two main research cycles were carried out to structure and contextualise supply chain knowledge. the first research cycle of the project both theoretical and practitioners view were explored in order to investigate possible forms to structure supply chain knowledge. this cycle includes focus group, diagramming and coding best practices in matrices. a tentative structure was constructed, which is presented in the results section 3. the purpose of the second research cycle was to address the contextualising knowledge in the supply chain domain. the methods used include coding, interviews and focus groups. the result was a diagnosis presented in section 3. some of the methods used in this research were the exploration of literature, observation (best practices dissemination), focus groups, diagramming, coding, construction of matrices and individual interviews for validation. some explored techniques, which were integrated in this proposal contextualisation in excel® included: knowledge engineering (knowledge representation), best practices content, foresight methodologies. later, diagramming content best practices helped to design the proposed structure (presented in section 3) and contextualisation in the form of diagnosis, which was evaluated in focus groups. the focus groups were integrated by significant professionals on operations management. coding was used to quantify practices content as will be shown in section 3. various matrices representing the knowledge base were followed by the diagnosis population. and finally, a validation stage was carried out presenting drafts of the constructed contextualisation in focus groups and by populating the knowledge base. the proposed structure and contextualisation is presented in the following section of results. 3. results by the end of the research cycles described in section 2, a structure that allows a contextualisation of supply chain knowledge was possible to be constructed, which is in the form of diagnosis that reports eight types of effects (figure 2). figure 2: contextualisation of a practice through a structure and diagnosis the proposed structure, in the area of knowledge engineering, as adeli (1990) defines is considered a “representation mapping medium” of knowledge. in the proposed structure, a practice is defined as a full process of a successful experience, but more important, in this project, also describes failure experiences. the context of a supply chain is codified by stakeholder, sector, indicator of performance and area (sia). this proposed structure of practices allows linkage to suitable and unsuitable entities conditions or effects of a specific supply chain context. the proposed structure represents three main elements:  entities. individual, tool, environment, and method (item) and its suitability to a specific supply chain context  conditions (qualitative and quantitative)  relationships (impedes, stimulates other entities conditions) the sia coding aims to link every condition of a practice element (item) to the context of a specific supply chain. this way, it is possible to know practices even stakeholder, and to offer a possibility to evaluate and integrate supply chain knowledge. these relationships were quantified, represented based on texts about best practices. texts written by experts, who describe a number of relationships (effects) among specific elements and its conditions in practices of a specific supply chain; this is specific areas, sectors, in other words, specific supply chain context. moreover, experts describe a quantification of these relationships or effects in two main types: favourable (stimulate) and unfavourable (impede) impacts on other elements and its conditions in practices. therefore, the proposed quantification and contextualisation intends to provide a template to give order and to allow an organic grow of such important knowledge about best practices in supply chains. a supply chain expert, based on this structure, can grow the knowledge base by coding the structure elements. during the diagnosis process (see figure 4) coded practices are compared to those defined by a user or member of a specific supply chain context, and then possible effects (favourable or unfavourable) are displayed (figure 4). 47 the proposed contextualisation process presented in figure 3 allows a continual contextualisation of supply chain knowledge and the evaluation or diagnosis (figure 4) of internal practices configurations and those along the supply chain. this diagnosis is able to quantify supply chain knowledge, such as, entities, attributes and relationships (figure 5). the diagnosis follows what van der vaart and van donk (2002) recommended, firstly, to measure the relationships among practices; and secondly, the practices against the overall supply chain’ performance. the diagnosis quantifies practices’ effects among internal practices and those along the supply chain, which allows an effective knowledge management and decision making. figure 3: entity relationship diagram of the structure for supply chain knowledge 48 figure 4: logic of the diagnosis constructed based on the proposed structured and contextualisation figure 5: section in excel® for coding supply chain knowledge 49 4. discussion in the literature review, there was not identified an existing quantification of the possible effects of practices in specific supply chain contexts. besides, best practices are important knowledge artefacts that do not report failure experiences. the proposed structure was focused on solving the need of providing order to the massive information about best practices that can be generated. besides, such structure allowed creating a diagnosis for specific stakeholders and sector. continually extending and evaluating knowledge it can be possible to support the learning process or knowledge management in supply chains. this way supply chains can focus on their own business, understanding and moderating their own practices. this is by adapting practices to what seems to be the most appropriate for current context. practices can be modified according to the business style and operating environment of a supply chain. there are limitations in this study, for example, the qualitative perspective of the methodology, and specifically the way relationships can be introduced into the system which depends on the expert’ subjectivity about what a best practice is. however, to minimize this problem, in future it is intended to include a monitoring (moderation module) activity, where various experts can review the quantified, structured information before it is used by practitioners of a specific supply chain. also, in the future it is intended to introduce a technology that allows a direct capture of knowledge, into the proposed structure, directly while the expert is writing. for supply chains a way to become competitive is to focus on their practices as significant knowledge artefacts that require contextualisation to specific supply chain configurations. supply chains must be attentive of the potential weaknesses of practices of specific supply chain contexts in order to become competitive. through this work it was possible to provide a structure and contextualisation of supply chain knowledge, which aim to support an effective implementation of knowledge management in supply chains. this way to supply chains can obtain the benefits from adopting best practices, implement continuous supply chain learning, integrate operations and therefore, develop a deliberate strategy to become competitive. 5. conclusion this research work proposes a structure to supply chain knowledge, which enables the four processes of the knowledge management cycle. the proposed structure aims to take into account specific supply chain contexts. this contextualisation can help supply chains to moderate the adoption of best practices. this proposal of contextualisation supports the report of unfavourable effects (failure experiences) from practices. the way to report such effects is possible with a diagnosis process, which based on the proposed structure helps to contextualise and visualise the possible effects, in this case, 8 types of effects (worst, best, barrier, cure, hidden benefit, hidden cure, bad side effect, barrier side effect). the objective of this work was to make available a contextualisation to supply chain members, for that a diagnosis based on a structure and contextualisation has been constructed in excel®. the proposal helps to implement an easy and continual evaluation and contextualisation of own practices, not only those internal but practices of the whole supply chain. also, to support the integration of practices, this consequently supports supply chain learning. additionally, a continual contextualisation helps to revamp the creation of an end-to-end perspective in supply chain, which is relevant in this new era of competition among supply chains. 6. further research there are other needs to be covered in order to fully implement knowledge management in organisations, for example: deep change in culture, such as open conversations, good personal relationships, (ahmadi and shirzade, 2011), organizational structure and work values. references adeli, h. 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(2004). factors affecting the adoption of manufacturing best practices. benchmarking: an international journal, 11(5), 504 520. weber, r., aha, d. w., and becerra-fernandez, i. (2001). intelligent lessons learned systems. expert systems with applications, 20(1), 17-34. vol10no2paper1 to cite this article: teubert, u. (2020) thinking methods as a lever to develop collective intelligence. journal of intelligence studies in business. 10 (2) 6-12. article url: https://ojs.hh.se/index.php/jisib/article/view/566 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index thinking methods as a lever to develop collective intelligence ursula teubert* *ursula.teubert@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 2,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10, no. 2, 2020 thinking methods as a lever to develop collective intelligence ursula teubert pp. 6-12 big data analytics and international market selection: an exploratory study jonathan calof and wilma viviers pp. 13-25 atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzes, riccardo bonazzi and pp. 26-31 francesco maria cimmino on the relationship between competitive intelligence and innovation jonathan calof and nisha sewdass pp. 32-43 intelligent information extraction from scholarly document databases fernando vegas fernandez pp. 44-61 thinking methods as a lever to develop collective intelligence ursula teubert* *corresponding author: ursula.teubert@gmail.com received 30 january 2020 accepted 20 april 2020 abstract this publication describes a methodology and framework for the use of thinking methods as a lever to develop collective intelligence. the purpose of the described methodology and framework is to leverage in an optimal way thinking methods well-chosen to the decided purpose and objective of a specific task. the conscientious use of thinking methods allows individuals and teams to better deploy brainwork and “wire” individuals into a collective thinking process, increasing agility and quality of collective sensemaking and collective intelligence. this methodology can be taught in combination with teaching content like innovation models or marketing, with the objective that students acquire not only the content but also learn to implement it, using the most efficient thinking methods. keywords collective intelligence, creative thinking, critical thinking, thinking methods 1. problem formulation our educational system is focussed on teaching content and analytical thinking. in competitive intelligence (ci), critical thinking was introduced, to avoid judgements based on cognitive bias and to assure the usage of a complete analytical grid. but how can we lever our natural human intelligence into an agile collective intelligence? based on the practice of thinking methods i propose a methodology in the format of a group learning process, to work and think together collectively. as a result, complex problem-solving or collective sensemaking become processes of a collective thinking network. 2. literature review the focus is put on thinking as a process and thinking methods in the field of science and economy. the social aspect of the human being is approached from a neurological aspect. there are examples from the living arts: theatre, improvisation, and ancient martial art traditions that are based on instant networked acting and thinking. collective thinking, collective sensemaking and collective intelligence result as networked thinking processes. in 1968, a study conducted by land and jarman stated a strong decrease in the creative thinking score of children, that remains at a level of less than 2% for adults. the creative thinking score was 98% for 5-year-old children, 30% for 10-year-old children and 2% for ages 25 and older (land, jarman, 1968). why is this so? land and jarman stated two kinds of thinking processes when it comes to creative thinking. these are divergent thinking, “where you imagine new ideas, original ones which are different from what has come before but which may be rough to start with, and which often happens subconsciously”, and convergent thinking “where you judge ideas, criticise them, refine them, combine them and improve them, all of which happens in your conscious thought”(land, jarman, 1968) and continues “[...] throughout school, we are teaching children to try and use both kinds of thinking journal of intelligence studies in business vol. 10, no. 2 (2020) pp. 6-12 open access: freely available at: https://ojs.hh.se/ 7 at the same time, which is impossible.”(land, jarman, 1968). in the field of intelligence studies, heuer pushes for a sound basic education in analytical thinking and decision making, especially in large organizations. the following two statements are considered key to understanding the need of thinking methods in our often too simplistic world: 1. “pay more honor to doubt. [...] we do not know. or there are several potential valid ways to assess this issue. should be regarded as badges of sound analysis, not as dereliction of analytic duty.” (pp. xxv, heuer, 1999) 2. “the mind is poorly wired to deal effectively with uncertainty (the natural fog surrounding complex, indeterminate intelligence issues) and induced uncertainty (the man-made fog fabricated by denial and deception operations).” (pp. xx, heuer, 1999). heuer proposes to apply critical thinking for complex analysis in the field of intelligence. statement one has been integrated into the complete curriculum of executive mba studies at insead. nearly every course treats at least one business case with a complex setting, where the analysis shows that there’s not one solution, instead “it depends”. this is a very practical way to bring more reflection and analytic thinking into general management worldwide. statement two will be addressed later in this article. natural science philosophical essays from the mid-20th century document discussions showing how scientists proceeded to find ground-breaking theories. g. holton cites a tentative of a. einstein to describe how he’s proceeding when thinking scientifically: “basically a cyclic process starting at the point where it should end. it is based on an axiom (one wishes to achieve), experiences lived through and deductions that allow to link the axiom with the experiences lived through.” (holton, 2004). on the other hand, einstein does not give any information on how the axiom came into his mind. this thinking process is what we call today expert intuition, which belongs to the creative thinking methods. if we want to understand how the abovementioned axioms emerge, we find an interesting answer in gladwell, (2005). “snap judgements and rapid cognition take place behind a locked door.” gladwell choose different personalities: a star tennis trainer, vic braden, who could predict that double faults would happen just before they happen, and the billionaire investor george soros and his decision making “... the reason he changes his position on the market or whatever is because his back starts killing him. he literally goes into a spasm, and it’s this early warning sign.” (p. 51, gladwell, 2005). interestingly holton challenges analytical, scientific thinking, based on a specific focus group: scientists that were recognized by the scientific community via various prizes. he’s analyzing their deliberations about expert intuition in scientific research. if we apply pattern analysis to holton (2004), heuer (1999) and gladwell (2005) it stands out that all of them search credibility associating their work with personalities recognized by the community. holton does this through internationally recognized scientists, heuer through a second foreword and an introduction to his book written by different personalities recognized throughout the intelligence community, and gladwell through vips. heuer’s approach to thinking is based on the conscious mind in order to do an analysis that is as objective and detailed as any possible and reducing the risk of errors based on cognitive bias or other rapid neurological mechanisms, that our brain can perform (gladwell, 2006) (eagleman, 2015). critical thinking takes time, but allows us to develop in a structured workflow of the analysis of complex situations. but what about situations that either need instant decision making (e.g. firefighters saving people from a burning building)? or when one must decide in a complex and/or dynamically developing situation with very scarce information to make an overall picture of the situation? here we find instruction through “presence of mind” (duggan, 2010) a core skill taught in asian traditions of martial arts including yoga, ai-ki-do, ken-do, and karate. presence of mind can also be achieved through meditation techniques. basically what happens is that we allow our brain to apply its, often extremely fast, mechanisms of pattern recognition and thin slicing. when “presence of mind” goes hand in hand with a strong expertise we talk about expert intuition. this expert intuition is what scientists can rely on when they’re developing new theories or discovering new natural phenomenons. in history we also have the military strategist von 8 clausewitz who described “presence of mind” as a tool to prepare strategic fights and conquer other countries (duggan, 2010). with neuroscience we can already localize where the diverse mechanisms are executed in the brain. we also have proof that training our brain allows “brain plasticity”, sometimes bridging neuronal connections that have, for example, been separated during an accident (pp. 184, eagleman, 2015). our brains are large neuronal networks. and they are “[...] primed for social interaction. after all, our survival depends on quick assessments of who is friend and who is foe. we navigate the social world by judging other people’s intentions.” (pp.149, eagleman, 2015). “every moment of our lives, our brain circuitry decodes the emotions of others based on extremely subtle facial cues.” (p. 154, eagleman, 2015). so this is where collective intelligence can emerge, or be trained. 3. methodology thinking methods are not taught at school. they’re not part of the curriculum at university. usually, if you run into a question, the answer is “you’ve got to think”. but who will tell you which kind of thinking works best for the question at hand? and in any competitive setting, the question of “friend or foe” is key. i developed a methodology to teach and train thinking methods and their application at work or in daily life. the methodology can be trained through real life complex case studies or it can be taught and trained together with content teaching, like innovation theory, marketing, or various other content subjects. 3.1 introduction and setting thinking together is a social act. and it bears certain risks: the other will know you better and could use this knowledge against you. it is crucial that the participants or the team members, wishing to train following this method, have the possibility and mindset to accept the basic settings: openness, mutual respect, trust and discipline. without such setting, collective thinking cannot emerge. learning is always linked with emotions and other people. this is especially true when teaching thinking methods to an educated audience. or in the words of maria montessori, 1870 – 1952, an italian physician who developed a self-driven learning method for children: “education should no longer be most imparting of knowledge, but must take a new path, seeking the release of human potentialities.” (montessori) 3.2 individual awareness here the task for any participant is to become aware about what she or he really does, when she or he decides to think. and to listen and understand how each other participant proceeds, when she or he decides to think. as no thinking methods exist in the curriculum of schools and universities, we state that the differentiation between “experts” and “common people” to estimate a collective intelligence level, that we see in research about collective intelligence, doesn’t apply. here we can state stronger differences depending on culture, gender or individual mindset. the methodology differentiates thinking methods used to understand, to find ideas, to analyze, to hypothesize, to decide. astonishingly people rarely link thinking methods to objectives: when applying thinking methods for decision making, e.g. in a brainstorming process, or analyzing a case study using thinking methods from ideation, this is when we can be sure to have a poor outcome. participants are also questioned about the setting in which they search for specific thinking tasks, and while some people prefer to walk through the forest for inspiration and finding ideas, others do the same to analyze an important question. at the end of this step, participants have a more structured overview of how and when to apply their thinking methods, and they achieved a first overview over the thinking methods capacity in the group, including a first glance on how other participants think. 3.3 collective awareness the next step is to link thinking methods, so that the group can start to practice collective thinking. this can be done in sub-groups. the application of theatre methods to develop collective spontaneity can be efficient. what can be achieved here is an increase in the awareness level and live first aha-moments. during the collective awareness step a first timetable is introduced, describing the link between brain frequency and thinking methods that fit the brain frequency. it helps to note the hour of day a person estimates to be usually in this very brain frequency (e.g. just before falling asleep and when waking up the human 9 brain frequency is relatively low, which fosters the creative thinking capacity of the brain), and add which specific tasks from the daily life could be done best with a specific thinking method, i.e. at a specific brain frequency. 3.4 enrich the role of this step is to turn from awareness into active practitioner. these can be individual practitioners and collective practitioners of thinking methods and collective thinking. social neuroscience brings first results and support to understand this step: “half of us are other people. [...] brains have traditionally been studied in isolation, but that approach overlooks the fact that an enormous amount of brain circuitry has to do with our brains. we are deeply social creatures. [...] our societies are built on layers of complex social interactions. [...]all of this social glue is generated by specific circuitry in the brain: sprawling networks that monitor other people, communicate with them, feel their pain, judge their intentions, and read their emotions. our social skills are deeply rooted in our neural circuitry.” (p.147, eagleman, 2015). in the setting of this methodology, based on trust, mutual respect and a win-win collaboration mindset, it becomes possible to develop social dynamics inside the learning collective. it can be measured through an increasing creativity of the participants as individuals and in (sub-)groups. 3.5 new at this point the manual of thinking methods, with a large collection of thinking methods, comes into action. the learning process follows the demand of the participants, as it is a creative learning process. as mentioned by (adriansen, 2010), the teaching concept is better not directly result-oriented, but gives room for unexpected requests of participants. 3.6 apply the objective is to apply all thinking methods learned, on individual and on group projects. participants frequently change roles: they ask advice or thinking support from the group for a personal project or question, they become part of the co-thinking group for another project, or they facilitate for a project to choose thinking methods and settings to find ideas, answers, or understanding. when teaching a group of people over a longer time, it becomes useful to include theatre methods, like automatic answering or improvisation theatre, to train their spontaneity. this is only possible once the members of the group have achieved a sufficient level of mutual trust, feeling safe in the group learning process. let’s take the example of improvisation theatre or automatic answering. people interact extremely fast, so their brain will use its repertoire of thin slicing, cognitive bias, implicit association, and so on. figure 1 the methodology: a learning process. 10 “the structure of spontaneity [...] improvisation comedy is a wonderful example of the kind of thinking that blink is about. it involves people making very sophisticated decisions on the spur of the moment, without the benefit of any kind of script or plot.” (pp.111, gladwell, 2005). again, we’re learning from creating awareness of our own biases. starting from the awareness we can go further. training spontaneity will also include decisions to act under the influence of, for example, cognitive bias or implicit association. we are creating awareness. once people are aware of their biases, they have a chance to attack change. 4. methodology application the described methodology has been developed and tested during 4 years lecturing in innovation leadership and marketing classes of 33h lecturing time, to master-ii students at sorbonne university. also, it has been developed and tested during 5 years of lecturing at a one-day workshop in critical thinking and creative problem solving at the institute for competitive intelligence. both formats are very different in lecturing time and audience. it gave me the opportunity to optimize the learning outcome of thinking methods in a compact format and to achieve a certain degree of an active collective intelligence behaviour in the master-ii lecture. 4.1 the case of teaching critical thinking and creative problem solving to ci professionals a one-day workshop is very short to get participants accustomed to new learning and thinking methods. still it is a great opportunity to start from an actual, complex problem of the participants and develop during the day stepby-step solutions, applying different thinking methods, leveraging individual and group thinking methods. “people interpret information individually and then collectively. collective learning is important. understanding weak signals advances by trial and error, or ‘learning by doing’.” (de almeida lesca, 2019) thinking methods are a strong lever to increase the quality of collective sensemaking and the agility of collective intelligence. further research is under preparation. 4.2 application of methodology: the case of foresight and long-term strategy development industries with a strong r&d tradition have the chance of a huge intangible asset in their experts’ knowledge. still it can be difficult to access the knowledge and include it into estimations of the future and strategy development. the methodology uses different thinking and group thinking tools to access expert intuition, to visualize it and use it for a long-term strategy proposal. this method allows one to strip-off various cognitive biases and taboos. in order to propose it as a regular tool for strategy development, further test series have to be conducted. 4.3 application of methodology: the case of teaching innovation & entrepreneurship as stated by adriansen “with critical thinking being among the core values in higher education, can we then also foster creative thinking?” (p.1, adriansen, 2010). the presented methodology seeks to teach students in-depth expertise using innovative learning and thinking methods to link this very expertise to the active knowledge and daily life of each student. teaching both innovation theory and thinking methods, using various example business cases, invites students to link expertise and sources of knowledge around them, proceeding them following the various thinking methods so as to find new solutions. giving them the possibility to choose the topics of the practical exercises from their real life is a strong motivator. in addition, theatre methods support the learning of communication skills, spontaneity, savoir-être and growth mindset. during the four years of teaching, the main objective was to make students become active innovators, and this has been achieved. as a collective, but also as individuals, their capacity was developed to detect and leverage entrepreneurial opportunities from their daily life and professional environment through thinking methods and individual and collective sensemaking to find hands-on solutions. key insights from these lectures are that: ● at university (as in many similar settings) students arrive in a passivestudent-consumer-mindset. interactive and hands-on teaching sequences showed very positive results. 11 ● first exercises in creative thinking and other thinking methods help to defocus, to find a key that can change the maze, and show positive results. all students start to link novel solutions to real problems from their personal experience, to analyze and improve them through the innovation theories and analytical tools provided during the course. ● the more the course advances the more the students collaborate, think together and support each other to succeed. the course ended with a class that elaborated two team and individual projects per person, and a very agile collective sensemaking and collective intelligence activity. 4.4 application of methodology: some examples of missing thinking methods in a few examples we show how neglecting the use of thinking methods in brainstorming or decision-making processes can lead to inefficiencies that could be avoided, by simply applying thinking methods purposefully. 4.4.1 example time management versus improbable innovation ideas one important aspect of management training is time management. still sometimes it may make sense to check the compatibility with the objectives. let’s take the example of a very innovative technology development company. every monday from 9am till 10am the list of ideas for the innovation management is evaluated. these ideas would need the deciding managers to be in a calm, low brain-frequency mode, to be capable to conduct divergent, creative thinking, to understand the possible value in each idea. this is rarely the case at 9am, as people are still in the morning rush to get things done. so these managers meet to decide which ideas to keep, which ideas to stop still decision making needs another way of thinking other than creative thinking. how probable is it that they will keep an idea with the potential of disruptive innovation? here a simple check of the settings and the choice of the best thinking method would give the company higher chances to surprise through innovativeness in the future. 4.4.2 example brainstorming with concise summary of the proposed idea brainstorming means bringing as many ideas and as diverse as possible ideas together. as already stated above in land (1968), it is not possible to do divergent thinking and convergent thinking at the same time. this are two opposite thinking methods. if they’re separated in time, the summaries can be done without problem after the divergent creative thinking brainstorming has finished. 4.4.3 example: diamond with a proper diverging ideation phase, then converging to a set of chosen solutions when working with the diamond, we start with a phase of divergence, finding as many possible or impossible ideas, proposals, settings, dreams, and images. the difficulty is to stay strictly in the divergence phase and stick to creative thinking, which means a low brainfrequency mode of all participants. this could be during a one-day workshop. it could run from 8h till 10h the phase of divergence, then half an hour coffee break, to converge to a set of chosen solutions by noon. let’s assume that all participants aren’t morning people. we have good chances that our team stays in a calm creative thinking mode between 8h and 9h. but as soon as the pressure to deliver a set of “realistic” solutions by noon comes to mind, the end of the divergence phase will turn into a converging phase, as it becomes tempting to swap to analytical reasoning. participants will focus on which idea will get a vote, for example from the general management. then, the quantity and diversity of the idea phase is narrowed down, due to switching from creative thinking to analytical thinking and decision making. if our team is very disciplined they’ll stick with critical thinking. but the funnel wasn’t filled to the optimal extent. probably it would have been advantageous for each member of the team to take home a writing pad, take note of ideas before falling asleep in the evening and when waking up in the morning and to send them in a voice message when commuting to work. alternatively, if team dynamics are wanted, the session could start after lunch, when all team members are a bit tired, their brains are in low brain-frequency mode, and they have time to think together calmly with the 12 converging phase being planned the next day during morning hours. this is the best time for our brains to do critical thinking and decide through a thorough analysis. 5. references adriansen, h.k. (2010), how criticality affects students’ creativity. in c. nygaard, n. courtney & c. holtham (eds.) teaching creativity – creativity in teaching, pp.65-84. libri publishing, uk angelou, maya (2013) mom & me & mom, virago press uk ariely, dan (2010) the upside of irrationality, the unexpected benefits of defying logic at work and at home, harper, business & social science bearden, neil. decision making science: the principle of charity bit.ly/1re4zau black, j. stewart (2014) it starts with one, changing individuals changes organizations, pearson, management daft, r. l., weick, k. e., (1984) toward a model of organizations as interpretation systems. academy of management review, vol.9 no2, pp.284-295 de almeida, f. c. & lesca, h. (2019) collective intelligence process to interpret weak signals and early warnings. journal of intelligence studies in business. 9(2) 19-29. duggan, william r. (2010) strategic intuition: east meets west in the executive mind, 1st quarter 2010, clariden global insights eagleman, david (2015) the brain the story of you, canongate edinburgh london gesteland, richard r. (2012) cross-cultural business behavior, a guide for global management, 5th edition 2012, copenhagen business school press gladwell, malcolm (2005) blink, the power of thinking without thinking, penguin books hazelton, suzanne (2013) great days at work, how positive psychology can transform your working life, kogan page. heuer, richards j. (1999) the psychology of intelligence analysis, center for the study of intelligence, central intelligence agency. holton, gerald (2004) intuition in scientific research, lna #38 libres propos sur la physique land, george, jarman, beth, (1968), research study to test the creativity of children, https://www.ideatovalue.com/crea/nickskilli corn/2016/08/evidence-children-become-lesscreative-time-fix/ laureiro-martínez, daniella, brusoni, stefano, zollo, maurizio cognitive flexibility in decision-making: a neurological model of learning and change, croma working paper 09-14 laureiro-martínez, daniella, brusoni, stefano, zollo, maurizio (2010) the neuroscientific foundations of the exploration exploitation dilemma, journal of neuroscience, psychology, and economics, american psychological association, vol. 3, no. 2, 95– 115 laureiro-martínez, daniella, canessa, nicola, brusoni, stefano, zollo, maurizio, hare, todd, alemanno, federica, cappa, stefano f. (2014) frontopolar cortex and decision-making efficiency: comparing brain activity of experts with different professional background during an exploration-exploitation task, frontiers in human neuroscience cognitive neuroscience, médium, transmettre pour innover, 2014, association médium, 4 éditions a year, issn 1771-3757 (written in french) meyer, erin, (2014) the culture map, breaking through the invisible boundaries of global business, publicaffairs, new york montessori, maria, biography and pedagogy, https://en.wikipedia.org/wiki/maria_monte ssori o’connell, andrew (2013) stats & curiosities from harvard business review, harvard business review press pascale, r., sternin, j., sternin, m. (2010) the power of positive deviance, how unlikely innovators solve the world’s toughest problems, harvard business press paul, r., elder, l., 2003, kritisches denken, begriffe & instrumente, stiftung für kritisches denken. santos, josé, (2007) strategy lessons from left field , harvard business review, issue april 2007 soilen, k.s. (2019) making sense of the collective intelligence field: a review. journal of intelligence studies in business. 9 (2) 6-18 taylor, ros, (2013) creativity at work, supercharge your brain and make your ideas stick, kogan page. vol10no2paper3 to cite this article: grèzes, v., bonazzi, r., & cimmino, f.m: (2020) atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making. journal of intelligence studies in business. 10 (2) 26-31. article url: https://ojs.hh.se/index.php/jisib/article/view/568 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzesa*, riccardo bonazzia and francesco maria cimminoa aentrepreneuriat & management institute, university of applied sciences western switzerland, hes-so valais wallis, switzerland; *vincent.grezes@hevs.ch journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 2,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10, no. 2, 2020 thinking methods as a lever to develop collective intelligence ursula teubert pp. 6-12 big data analytics and international market selection: an exploratory study jonathan calof and wilma viviers pp. 13-25 atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzes, riccardo bonazzi and pp. 26-31 francesco maria cimmino on the relationship between competitive intelligence and innovation jonathan calof and nisha sewdass pp. 32-43 intelligent information extraction from scholarly document databases fernando vegas fernandez pp. 44-61 atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzesa*, riccardo bonazzia and francesco maria cimminoa aentrepreneuriat & management institute, university of applied sciences western switzerland, hes-so valais wallis, switzerland *corresponding author: vincent.grezes@hevs.ch received 20 january 2020 accepted 15 may 2020 abstract companies’ environments change constantly and very quickly, so each company must be aligned with its environment and understand what is happening to maintain and improve its performance. to constantly adapt to its environment, the company must integrate a learning process in relation to what is happening and become a "learning company." this posture will ensure organizational effectiveness in relation to changes in the environment and allow companies to achieve goals under the best conditions. our project aims at delivering a competitive and collective intelligence service allowing to support decision making processes through the diagnostic of alignment between internal knowledge of the organization and available external information. keywords contingency theory, environmental scanning, knowledge-based view, learning organization, machine learning 1. introduction each company’s environment changes constantly and very quickly, so the company must be aligned with its environment and understand what is happening to maintain and improve its performance. to constantly adapt to its environment, the company must integrate a learning process in relation to what is happening and become a "learning company". this posture will ensure organizational effectiveness in relation to changes in the environment and allow them to achieve goals under the best conditions. contingency theories suggest that there is no single best way to behave, coordinate or lead, and that in different situations, a style of management and leadership may not be effective (fiedler 1964). therefore, the optimal organization or management style is dependent on different external and internal variables: the is no universal way to lead. moreover, those theories argue that effective organizations must be aligned within their subsystems and environment. according to this approach, the effectiveness of decision-making depends on aspects of the situation, such as the amount of relevant information held by the leader and his or her subordinates, and the acceptance of the decision by the subordinates (vroom and yetton 1973). organizational learning theory (cangelosi and dill 1965) supports that to be competitive in a changing environment, the company must adapt its actions to achieve its goals and optimize the degree of alignment between expected and achieved results. for learning to occur, the company must (1) make a conscious decision to change in response to the journal of intelligence studies in business vol. 10, no. 2 (2020) pp. 26-31 open access: freely available at: https://ojs.hh.se/ 27 circumstances, (2) consciously link the action to the result and (3) remember the result. initial learning takes place at the individual level. however, it becomes organizational learning once the information is shared, formalized, and stored in the organization to be transmitted and used for decision-making. these personal, organizational and environmental approaches to learning inspired us to name our project : “atman” which refers, in the hindu philosophy, to the concept of “vital breath” coming from inside (self) or outside the body (cosmic) to a transpersonal relationship (organizational). the first part of the learning process involves the acquisition of data in the form of a "memory" of valid action-result links, the environmental conditions under which they are valid, the probabilities of the results and the uncertainty surrounding this probability. links are constantly updated, either by additions or rejections based on new evidence. there are many ways to acquire these links, including experience, experiments, benchmarking, and transplantation, but they must consist of a conscious effort to discover, confirm or use a cause and effect, or simply be blind actions based on chance. successful companies then analyze their environment for signs of change, real or anticipated, to determine whether change is necessary: this implies that they (a) have learned which indicators are important to analyze and (b) have learned what degree of change in the environmental indicator requires a change in actions. the second part of the process is interpretation. organizations continuously compare actual results with expected results to update or add to their "memory". unexpected outcomes should be assessed to determine the causal link, appropriate actions or new actionresult links specified if necessary, and enhanced learning. the third step is adaptation or action. it is at this point that the company takes the interpreted knowledge and uses it to select new action-result links appropriate to the new environmental conditions. the main point here is that it is a continuous process of adaptation to environmental conditions. once the adaptation is completed, the company's knowledge base is updated to include the new action-result link, probabilities, uncertainty, and applicable conditions. the process is ongoing. this feedback is an ongoing and iterative process. 2. state of the art competitive and business intelligence solution providers are now able to offer services based on the use of artificial intelligence interfaced with the user in the form of a chatbot that processes the company's marketing, sales, customer relations, operations and internet of things data, for example those found at crystal.ai. in addition, many conceptual proposals for environmental monitoring are proposed in the literature (camponovo g., pigneur, y. 2004a, 2004b; camponovo g. 2009; grèzes et al. 2012; de almeida, f. c., lesca, h. 2019). the link between environmental monitoring and corporate learning is also considered by choo (2001). however, these approaches do not take into consideration the computational diagnosis of the alignment of the company’s internal (tacit and explicit) and external data, nor the added value of an additional organizational recommendation service. nevertheless, several data mining techniques can be considered to deal with the computer diagnosis of the alignment of internal and external company data (see figure 1). natural language processing (nlp) is a field of computer science concerned with the interactions between computers and human (natural) languages. with the diffusion of techniques of data mining (the set of processes developed to acquire huge amounts of information) we made developments in the field of text-mining based on the same principle, but the data is extracted from texts. with the diffusion of commercial websites that have a huge amount of feedback via user comment and social platforms such as twitter and facebook, researchers have the possibility to access a new field of data: opinion/sentimental driven data. this research area is called sentiment analysis (sa) or opinion mining (om). before reviewing the two principals’ families of methodologies to make a figure 1 data mining technics involved in text analysis. 28 sentiment analysis, it can be useful to give definitions of sentiment analysis (sa) or opinion mining (om), to clarify. vindoline, g., & chandrasekaran, r. m. (2012) define it as “the computational study of people’s opinions, attitudes and emotions toward an entity”, while nasukawa, t., & yi, j (2003) explain that “the essential issue in sentiment analysis is to identify how sentiments are expressed in texts and whether the expressions indicate positive (favorable) or negative (unfavorable) opinions toward the subject”. figure 1 shows there are two main methodologies: the “lexicon-based approach” and “machine learning” that are involved in computing natural language data to extract meaning. the lexicon-based approach is the conversion of a character string (a text) into a list of tokens. to make this operation we had two different approach: dictionary based, or corpus based. the dictionary is the simplest to use, is based on an established map of sentiment where words are pre-categorized. corpus based is where you have access other the pre-categorized sentiment labels, also to a context. the core of machine learning is creating an algorithm based on data for solving a specific task. for the analysis of sentiment, we can use different algorithms, some examples are discussed here. the decision tree algorithm is compared to a tree structure. each internal node represents a test on an attribute (value above or below a certain number) and each branch represents the result of the test. bilal (2016) and wan & gao (2015) have used this method. the support vector machine is a binary linear classificatory, which is capable of classifying a value between two classes by a predetermined training set. here, a text document is not suitable for learning because the input is a vector space and the output is 0 or 1. for this reason, he needs to be formatted properly, as in patil (2014). neural networks are based on a universal approximation theorem that allows us to find patterns between the input and output. this “learning” process is generally based on an “example,” more formally called prior information. boiy (2009) and neethu (2013) use this technique. 3. research question in order to facilitate and accelerate the acquisition and processing of relevant information related to the alignment between the organization, its subsystems and its environment, our research question is: how can one promote organizational learning by prescribing useful information based on the continuous evaluation of its current knowledge? 4. objectives our solution aims at comparing internal company data (business intelligence) with external company data (environmental scanning) to provide a diagnosis of the company's alignment with its environment (technical innovation). this diagnosis will allow the realization of organizational and strategic recommendations for the company (service innovation). the consideration of the recommendations and the implementation of actions by the company will make it possible to modify the company's internal data. this learning will allow the company to realign itself with its environment. 5. methodology to develop this system, we first tested the interest of the alignment diagnostic of two groups of actors using the lexicon approach. the tests were focused on the alignment between the knowledge of the group of actors and the firm’s formal knowledge. the test’s methods were interviews of actors and quantitative analysis of qualitative data with figure 2 example of translation and comparison of phrases. 29 r. this approach allowed us to realize a lean prototype of the expected process. to illustrate our approach of nlp with r studio, we illustrate a simple example by using two public sources available on gutenberg.org. let us assume that the internal knowledge of the organization is contained in the strategy book “the art of war” by sun tzu. the external knowledge is described by the first chapter of “on war” by clausewitz. we assess these two pieces of information in three steps. the first step is internal and external data collection. we convert the two texts into a data frame (in figure 2 we show how we translate one of the first phrases in each book). the second step is data interpretation. the document frequency matrix allows one to create polarized word clouds that show the words in common and the words specific to each text. in our example, both sources describe how to deal with the enemy, but the first chapter of clausewitz seems to focus on war whereas the book by sun tzu appears to describe how take advantage of different types of ground. the third step is identifying learning and prescription to action. the frequency correlation matrix looks at correlations between words to identify clusters. in our example, the book by sun tzu (figure 4, top left) seems to focus on how to beat an enemy. however, the first chapter by clausewitz extends this notion (figure 4, top right) and describes how to conduct war. from this, we can suggest to integrate the external source with the internal sources (figure 4, bottom). 6. technology description our technology development aims at delivering three improved services. these are internal and external data collection, data interpretation and learning and prescription to action. 6.1 data collection internal data collection is a management information system that centralizes and unifies the collective intelligence through knowledge management. our proposal aims at facilitating and accelerating acquisition and processing of pertinent information useful to the organization’s alignment with its subsystems and environment through external data collection. 6.2 interpretation the accompaniment and analysis of results aims to lead the organization to understand and interpret the indicators to consider the actions to be taken in order to adapt and align itself as closely as possible with its environment. human intervention is necessary here to identify the important indicators to be analyzed, and to teach the software the relevant variables and thresholds involving change or learning on the part of the organization (machine learning process). 6.3 action and learning the company’s internal documents automatically update, which allows validation of the alignment process (figure 4). 7. development and first results initial tests were carried out in two situations. the first was a diagnosis of the alignment between the knowledge of a group leading a tourist destination (association council of municipalities) and the content of all the steering studies carried out for their destination (internal tacit and explicit knowledge). the test or our method made it figure 3 example of word cloud of data. 30 possible to highlight the shortcomings and bias of the studies, the distortion between knowledge and content, and to promote the adaptation of the organization to fill the identified gaps. the second situation was a diagnosis of the alignment between the learning achieved after professional training by a group of collaborators and the formal program. this test revealed the contrast between what participants retained and what the presentation documents contained. this has made it possible to improve the organization of the transmission of the message and to identify the points to be reinforced. 8. business benefits and discussion the preliminary study produced a proof of concept that extends the company’s current services and creates a clear competitive advantage in the strategic intelligence market, based on a unique positioning in terms of intelligence supported by artificial intelligence technologies. the commercial potential and the extension potential of the solution are linked to the adaptation of the algorithm to different languages. this makes it possible to consider the extension of geographical markets. the expected revenue model is based on licensing the use of the diagnostic application, customization of the modules, referral services for decision making and training services for the companies in the use of the application. 9. discussion and conclusion our initial results show an interest in continuing the research and integrating the formalization of the knowledge of all employees into the organization’s knowledge base to align the data as closely as possible with the available external information. figure 4 example of correlation. 31 our research limits at this point are based on the capacity to develop and test the external data analysis module (technical innovation on fast data retrieval, machine learning, nlp) and the recommendation process development (service innovation). in addition, the learning effects of the recommendations will have to be measured. further research will focus on the processing of alignments of several sources of internal data with the external data, such as the measurement of the effects of the recommendation on the decision-making process of the organization. moreover, an extension of the technique could be particularly useful in terms of competitive intelligence, particularly in the context of the use of the business model canvas as a benchmarking tool (grèzes et al. 2012) and could be scalable to several type of organization according to the scanning of internal knowledge as a basis for the external monitoring process. 10. references de almeida, f. c., lesca, h. (2019) collective intelligence process to interpret weak signals and early warnings. journal of intelligence studies in business bilal, m., israr, h., shahid, m., & khan, a. (2016) sentiment classification of roman-urdu opinions using naïve bayesian, decision tree and knn classification techniques. journal of king saud university-computer and information sciences, 28(3), 330-344. boiy, e., & moens, m. f. (2009) a machine learning approach to sentiment analysis in multilingual web texts. information retrieval, 12(5), 526-558. camponovo, g, pigneur, y. (2004) extending technology roadmapping for environmental analysis. proceedings of the colloque sur la veille stratégique, scientifique et technologique camponovo, g, pigneur, y. (2004) information systems alignment in uncertain environments. proceedings of decision decision support systems (dss) camponovo, g. (2009) concepts for designing environment scanning information systems. international journal of business and systems research cangelosi, v. e., and w. r. dill. 1965. "organizational learning: observations toward a theory," administrative science quarterly (10:2), sep., pp. 175-203. choo, c. (2001) environmental scanning as information seeking and organizational learning. information research, vol. 7; number1, october 2001, p. 1 dogson, m. (1993) organizational learning: a review of some literatures. organization studies. fiedler, f. e. (1964). a contingency model of leadership effectiveness. advances in experimental social psychology (vol.1). 149190. new york: academic press. grèzes, v., liu, z., crettol, o., perruchoud, a. (2012) from business model design to environmental scanning: the way to a new semantic tool to support smes' strategy. proceedings of echallenges e-2012 nasukawa, t., & yi, j. (2003) sentiment analysis: capturing favorability using natural language processing. in proceedings of the 2nd international conference on knowledge capture (pp. 70-77). acm. neethu, m. s., & rajasree, r. (2013) sentiment analysis in twitter using machine learning techniques. in 2013 fourth international conference on computing, communications and networking technologies (icccnt) (pp. 1-5). ieee. patil, g., galande, v., kekan, v., & dange, k. (2014) sentiment analysis using support vector machine. international journal of innovative research in computer and communication engineering, 2(1), 2607-2612. vinodhini, g., & chandrasekaran, r. m. (2012) sentiment analysis and opinion mining: a survey. international journal, 2(6), 282-29 vroom, v.h. and yetton, p.w. (1973). leadership and decision-making. pittsburgh: university of pittsburgh press weill, peter; olson, marorethe h. (1989). an assessment of the contingency theory of management information systems. journal of management information systems, 6(1), 63. wan, y., & gao, q. (2015) an ensemble sentiment classification system of twitter data for airline services analysis. in 2015 ieee international conference on data mining workshop (icdmw) (pp. 1318-1325). ieee. vol10no3paper1 to cite this article: garcía-madurga, m.a. & esteban-navarro, m.a. (2020) a project management approach to competitive intelligence. journal of intelligence studies in business. 10 (3) 8-23. article url: https://ojs.hh.se/index.php/jisib/article/view/586 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a project management approach to competitive intelligence miguel-ángel garcía-madurgaa,* and miguel-ángel esteban-navarrob adepartment of business administration, university of zaragoza, spain; bdepartment of journalism, audiovisual communication and publicity, university of zaragoza, spain; *madurga@unizar.es journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 3,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10,no.32020 opinion: a project management approach to competitive intelligence miguel-ángel garcía-madurga and miguel-ángel esteban-navarro pp. 8-23 an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukari pp. 24-37 the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry stefan zwerenz pp. 38-62 the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyen and nguyen phong nguyen pp. 63-79 financial intelligence: financial statement fraud in indonesia muhammad ikbal, irwansyah irwansyah, ardi paminto, yana ulfah and dio caisar darma pp. 80-95 a project management approach to competitive intelligence miguel-ángel garcía-madurgaa,* and miguel-ángel esteban-navarrob adepartment of business administration, engineering and architecture school, campus río ebro, university of zaragoza, zaragoza, spain; bdepartment of journalism, audiovisual communication and publicity, faculty of arts, university of zaragoza, zaragoza, spain. *corresponding author: madurga@unizar.es opinion article received 9 june 2020 accepted 26 october 2020 abstract the research problem that this study seeks to solve is to examine the relationship between competitive intelligence (ci) and project management (pm). these disciplines coincide in their threefold approach to action, collection of results, and ability to react in response to environmental signs. however, the academic and professional literature has not explored the possible synergies between ci and pm, with the exception of the seminal proposals by prescott in 1988 and 1999. the aim of this opinion article is to propose a new methodological approach for the production and transfer of ci in accordance with the international standards of pm. the methodology consists of an inductive reasoning process from specific observations and evidence gathered in our professional experience as ci practitioners over twenty years, contrasted with the findings of the scientific literature, the pmbok® guide of the project management institute, and with the ci model proposed by the most relevant spanish technical standards in r&d&i management and strategic intelligence management. the paper discusses the vision of intelligence production and dissemination in a project with five phases or groups of processes: initiation, planning, execution, monitoring and control, and closure. also, the responsibilities of the human intelligence team are exposed. this proposal could be an alternative to the departmental-based intelligence cycle model more aligned with the organizational culture and the usual operational practices and business processes of companies, founded on the design and deployment of projects with a specific beginning and end that is carried out to create a product, service or unique result. it is concluded also that there is a need for undertaking experimental implementation and case studies of this proposal in companies and their assessment by future academic studies. keywords competitive intelligence, intelligence cycle, intelligence production, pmbok, project management 1. introduction in a vuca context (volatility, uncertainty, complexity and ambiguity of the current world) it is necessary to continually reconsider routines to survive. in the society of knowledge, today's certainties always become tomorrow's absurdities (drucker, 1995). looking around over a time horizon confirms that the only permanent thing is change. organizations with a flexible corporate culture in relation to transformation establish warning systems that journal of intelligence studies in business vol. 10, no. 3 (2020) pp. 8-23 open access: freely available at: https://ojs.hh.se/ 9 allow anticipation. competitive intelligence and project management help by identifying, facing and managing situations of change and, therefore, maintaining leadership positions. competitive intelligence provides relevant information, evaluated and analysed, oriented to the making and execution of decisions (global intelligence alliance, 2013 a). it especially stresses the prevention of risks and threats and the identification of opportunities, which makes it a useful tool for the design of the organizational strategy, the start-up of operations and the making of actions of influence in the exterior. the bibliographic reviews show a broad coincidence in literature specialized in the distinctive elements of their nature (calof and wright, 2008; garcía-alsina and ortoll-espinet, 2012). however, solberg (2016) found in a recent study that existing definitions of competitive intelligence overlap with definitions of other more established fields of study, like decision sciences and marketing. competitive intelligence can be applied to the deployment of all managerial functions (planning, organization, human resources management and control) and in all functional areas of a company (garcíamadurga and esteban-navarro, 2018). the generic term competitive intelligence includes several specialized intelligences of use in the company: strategic intelligence, environmental scanning, customer intelligence, competitor intelligence, marketing intelligence, technical intelligence and supplier and manufacturing intelligence. project management is a management model that arose in the united states in the mid-20th century to guide the execution of complex processes that require the mobilization of numerous resources (financial, human, material and informative) and the participation of several functional units in an organization. a project is a temporary effort with a specific beginning and end that is carried out to create a product, service or unique result (project management institute, 2017). the projects are planned following deterministic models, such as the work breakdown structure (wbs), critical path method (cpm) and program evaluation and review techniques (pert)that set objectives and clear deliverables, and which give oversight as they are executed. this requires continuous monitoring and documentation that allows one to maintain a high control over what is done and its effects, in order to quickly correct the course and align the actions with the decisions if necessary. it is crucial for the success of a project to have information about the activities and the evolution of the environment in all its phases. the pmbok® guide, fundamentals for project management (2017, 6th ed.) of the project management institute (pmi®, non-profit organization created in 1969 to defend the interests and serve professionals) is the reference document for a significant number of professionals around the world and it is considered the international standard. the competitive intelligence and the project management disciplines coincide in their threefold approach to action, collection of results and ability to react in response to environmental signs. at a glance, and attending to its aims, intelligence reveals itself as a great help to manage projects. considering that intelligence processes look for concrete results, they could be inspired by the methodology of this management model. on the other hand, organizing and carrying out activities as projects is a common practice in companies and also part of the skills of managers and middle managers, unlike in the case of intelligence. however, none of the academic literature, professional literature or technical standards of both disciplines have ever explored the possible synergies between both disciplines; with the exception of the proposal by prescott (1999) and vedder et al. (1999), still undeveloped twenty years later, to consider intelligence as more of a process to be used by many in the execution of projects than an organizational function. hence, it is considered relevant to enquire about new ways of incorporating intelligence into organizations to support the change and so strengthen their ability to adapt to a dynamic and constantly evolving environment. the aim of this paper is to propose a new methodological approach for the production and transfer of competitive intelligence in accordance with the international standards of project management for its experimental implementation in companies and its assessment by future academic studies. this new approach can contribute to the expansion of the practice of competitive intelligence and, in the disciplinary field, to explore an improvement of the intelligence cycle more aligned with the way in which companies execute their business processes. the methodology consists of an inductive reasoning process from specific observations 10 and evidence gathered in our professional experience as competitive intelligence practitioners over twenty years. this method of reasoning is founded on the assumption of various premises collected through informal participant observations. this includes what is learned from others, where there is not full assurance but where it provides a sufficient basis to develop arguments to compare in an inference process with the current theories and models. the method is founded on the emergent grounded theory approach that proposes “to develop a theory based on a participant’s experiences and perspectives of a phenomenon” (corbin and strauss, 2008). the researchers do not need “clearly specified objectives, research questions, or a hypothesis before the initiation of the research project” (flynn and korcuska, 2018). we contrasted the developed arguments with the findings of the scientific literature, the pmbok® guide of the project management institute, and the cyclical model of intelligence, as it is proposed by the most relevant spanish technical standards in r&d&i management and strategic intelligence management (aenor, 2011; aenor, 2015; une, 2018). these spanish standards have no iso equivalents. the results are a discussion about the dynamics of the management of competitive intelligence projects and the responsibilities of the human team involved. 2. literature review 2.1 identifying the problem the practice of competitive intelligence can be present throughout an organization or restricted as support for one or several strategic processes. companies can choose between different models of implementation: occasional or usual purchase of intelligence reports from specialized companies, creation of an intelligence department with their own means, total or partial outsourcing of their management, or they can even dedicate part of the day of some management to the production of intelligence after equipping them with competence. many organizations still lack some kind of stable competitive intelligence structure. the consultant crayon (2018) has detected that, from 700 interviews of experts and consumers of competitive intelligence from 54 countries, in 17% of the companies interviewed no employee performs intelligence and in 24% only part of the day is dedicated to it by a single employee. it is also observed that, as the size of the company increases, so does the economic support given to competitive intelligence: 80% of the companies investigated with more than 1,000 employees have a specific intelligence team. according to a global report by the global intelligence alliance (2013b), 80% of the companies interviewed with an implemented competitive intelligence process show satisfaction with their return in spite of the benefits, which are usually not direct or immediate. a report by the competitive intelligence foundation indicates that the main contributions of competitive intelligence are manifested in the creation of new products or services, reduction or elimination of costs, time savings, improvement of margins, increase or the creation of new sources of income and achievement of the company's financial objectives (fehringer et al. 2016). a study of hundreds of companies from different industrial sectors that use competitive intelligence concludes that companies where the value of intangible assets has a higher q tobin put more money in their budgets to intelligence, which is more valued by top management (erickson and rothberg, 2012). the classic intelligence model presents the production of intelligence as a continuous and repetitive transformation process of information and knowledge articulated in a series of phases, which form a cycle. it begins with planning and direction, which includes the identification of intelligence requirements. the second phase consists of the collection and technical processing of information from documentation, via human and technological sources from different channels. it continues with the evaluation, integration, analysis and interpretation of the said information with a prospective orientation. it follows with the protection and communication of intelligence to predetermined users, generally with restricted diffusion. it concludes with an assessment of the whole process, taking into account the results of the application of intelligence, which can activate new intelligence needs and re-start the process. there is a broad consensus regarding the basic configuration of the intelligence cycle (figure 1), although the stated activities are grouped according to the authors in four, five, six or even seven stages (generally to separate the reception and the processing and whether or not to include the assessment report) and with certain variations in their denominations, 11 which generates confusion. there is an exhaustive compilation of the visions of the intelligence cycle in anglo-saxon literature (pellissier and nenzhelele, 2013). although the intelligence cycle is considered the ‘heart of the intelligence system’ in an organization (kahaner, 1998), this model has never been exempt from criticism coming from the perspective of its practical application. these deficiencies in the operations of the intelligence cycle have been outlined (clark, 2004; esteban-navarro and carvalho, 2012): • it encourages no communication between those who obtain information and analysts. • it arbitrarily assumes that analysts can control all variables on their own. • it makes it difficult to know the real quality of data, as it masks potential problems during collection. • it responds poorly to emergency situations where intelligence is required, even if it is provisional before having enough information. • it does not establish channels to integrate the knowledge of a situation that the intelligence recipients have or the variations in their demands during the collection and analysis of information. • it prevents managers and conductors from participating in the production of intelligence in a technological environment that enables easy and rapid access to information. therefore, it has even been proposed to view the cycle as a fundamentally theoretical model (mcgonagle, 2016). it has also been indicated that the cycle is not able to respond to the variety of needs of competitive intelligence: it works well for longterm strategy design tasks and technological surveillance, but is poorly adapted to the production of tactical intelligence on sales and marketing (mcgonagle, 2007). in addition, this model is irrelevant facing a very common situation in the business world: a single person that has the role of both collector and analyst, and even that is the user of the intelligence. as a matter of fact, after the cold war the intelligence cycle was considered dysfunctional and bureaucratic by those who systematized it, the us government intelligence services. this was due to the inherent problems it posed, such as the difficulty in dealing with uncertainty, identifying threats and emerging adversaries, working on unforeseen objectives, and facilitating communication between teams (hulnick, 2006). calof, richards and santilli (2017) have also concluded that the traditional model of competitive intelligence “appears to be inadequate to address the intelligence challenges arising from the speed of change in the environment, increasing data complexity, and the growth of international activities”. 2.2 searching for an alternative however, the intelligence cycle model continues to be presented not as a model but as the model of universal validity. to correct this divergence between theory and practice, competitive intelligence should evolve towards more flexible and networked work models, as happened with strategic planning. it is a matter of considering competitive intelligence more as a process to be used by many instead of a function attended by a few at the service of a few (mcgonagle, 2007). another relevant issue related to the model is where the intelligence function should be placed in the organizations. solberg (2010) showed that intelligence often comes from an initial marketing research function in the marketing department, and develops to a special and separate department, where the practitioners build a strong organizational culture. the special departmental model of intelligence causes communication problems with top managers, so an advisory model to place a senior advisor to the ceo as the person responsible for the first and the last functions in the intelligence model has also been proposed: formulating the needs and delivering the results. solberg (2010) discussed the pros and cons of these and other placement models figure 1 universal model of the intelligence cycle (prepared by the authors). 12 of intelligence function implemented in companies from an organizational perspective: the professional model, the top-down model, the integrated intelligence model, the down-up model, and the departmental model. within this search for alternatives, prescott (1999) already suggested, expanding on an idea outlined in prescott and smith (1988), to explore the possibilities offered by project management when they suggested approaching competitive intelligence with a project focus: ‘competitive intelligence must be managed as a core business process. projects are the basic building blocks of an actionoriented competitive intelligence program. that is, making the intelligence production process operational is a project’. that same year vedder et al. (1999) also proposed that companies could choose not to have specific intelligence units and perform ad hoc intelligence work when necessary, managing them as projects. however, twenty years later neither prescott nor other authors have developed an operational model of the process of intelligence production understood as a project, more aligned with the professional skills and the usual work procedures of the intermediate staff in in the departments with the highest demand and use of intelligence in companies (senior management, project management, r&d, marketing and operations). exploring new contributions to competitive intelligence from other disciplines, in this case engineering, is in accordance with the recent suggestions of solberg (2016) about the scope for a new research agenda for intelligence studies in business. solberg (2016) warned that the compartmentalization of competitive intelligence in the social sciences “has been to the disadvantage of its development as a discipline”. the application of project management techniques and tools to competitive intelligence has the following relevant implications for its practitioners: it helps to identify the diverse needs of stakeholders; it contributes to prioritize resources and ensure their efficient use; it allows practitioners to accurately budget in advance, as well as stay on schedule and keep costs and resources on budget; it improves communication between stakeholders; it reduces the risks of project failure; and, consequently, it increases the satisfaction of internal and external customers. this aim is aligned with the suggestions of calof, richards and santilli (2017) to break the traditional model of an in-house competitive intelligence unit and to move towards “a crosspollination approach whereby others in the firm contribute to all intelligence activities”, mainly in the selection of key topics and participation in the analysis. in this way, alnouraki and hanano (2017) have exposed the impact of business intelligence on modern and flexible organizations when it is integrated into corporate strategic management. they proposed a framework that facilitates their integration with a balanced scorecard methodology. our proposal explores another option complementary to the strategic vision, more focused on the operational dimension of the companies. in recent practical research about the implementation of business intelligence in relation to the role of information systems integration and enterprise resource planning, zafary (2020) suggests it is time to investigate “suitable approaches by a focus on the appropriate factors for successful business intelligence implementation and by a comparative analysis of ways to boost business intelligence preparation”. in the meantime, competitive intelligence can support the following plans and activities of project management as described in the pmbok® guide (2017, 6th ed.): identification of stakeholders (point 13.1) and monitoring of their engagement (13.4); planning of risk management, specifically the identification of risks, the qualitative and quantitative risk analysis, the monitoring of risks and the planning and implementation of risk responses (11.1;11.2,11.3;11.4; 11.5; 11.6; 11.7); and planning of procurement management (12.1). the proposal of this project management approach to competitive intelligence is founded in the comparison of the similarities and differences of the two disciplines in various categories (nature, scope, practice, process, recipients, and human resources) and, therefore, what they can learn from each other, as shown in table 1. there is an important coincidence in the nature, the main objectives, and the recipients of both disciplines, with the relevant exception that the ic is also focused on understanding the external environment and not only on supporting managerial decisions and decision-making, as pointed out by solberg (2016). obviously, there are differences in the processes, but these are not obstacles to collaboration. table 1 comparison of competitive intelligence and project management (prepared by the authors). competitive intelligence project management nature actionable knowledge. x x look for suitable results, not for generic knowledge. x x focus on risk reduction. x x search opportunities. x scope enrich the intellectual capital of the organization. x x principal focus actually to support strategic decisions. x seeks knowledge about the environment in which organizations develop their activity. x principal focus actually to accompany development of operations. x practice most common practice actually in companies. x a standardized practice. x it is exercised in a formal or informal way. x process consists of a series of processes whose outputs constitute the following process inputs. x x continuous and repetitive transformation process of information and knowledge articulated in a series of phases. x temporary effort with a specific beginning and end that is carried out to create a product, service or unique result vs. cyclical intelligence process. x determined by the triangle constituted by the variables scope, time, and cost; fixed all of them, any modification of a variable necessarily implies the modification of the other. x continuous monitoring and documentation exercise that allows to maintain a high control over what is done and its effects. x recipients end users are the key decision makers. x x managers and directors of the companies have significant responsibilities in relation to the objectives, plans and actions of the design and planning of the processes. x x the interaction between producers and users is complex, but they try to build communication channels and information flows. x x communication and activity processes between stakeholders are clearly established. x human resources highly specialized competences. x common skills of managers and middle managers. x specialized director in this field is a common place in the organization chart on companies. x frequently outsourced. x 3. discussion 3.1 intelligence production and dissemination is a project the five groups of processes of project management are initiation, planning, execution, monitoring and control and closure (figure 2). consequently, the main processes for carrying out a competitive intelligence project should correspond to each of these groups. the initiation processes consist of the identification of intelligence and information needs based on the intelligence requirement received and the realization of the project's constitution. the planning process corresponds to the drafting and approval of the management plan. the execution processes consist of two complementary and interdependent processes: the collection of reliable and credible information and the analysis and evaluation of information. and the closing process corresponds to the dissemination of knowledge and the protection of information and intelligence created. the management of the competitive intelligence project would include planning, 14 organizing, monitoring, controlling, reporting and taking the pertinent corrective actions of all the project processes that are necessary in a continuous way. the execution of an intelligence project should consider at least the following aspects: objectives and expected results, tasks to be performed, necessary material and immaterial resources, milestones that must be met (including start and end dates), formal revisions to evaluate the progression of the project, identification and risk management, control and documentation of results and changes and, finally, necessary support activities. the organizational structure of a competitive intelligence project should be established in accordance with the requirements and policies of the organization and the specific conditions of their projects. the experience of previous projects, if any, should be used to select the most appropriate organizational structure. it should also be designed in a way that encourages communication and collaboration among all participants. the competitive intelligence project team should have at its head two key figures: the chief competitive intelligence officer (ccio) of the organization and the project managers of the various intelligence projects. 3.2 the team the chief competitive intelligence officer of the organization must actively participate in the management of intelligence projects: • in the initiation phase they lead the beginning of the project, collect the requirements, are the spokesperson before the client (internal or external) and the highest authority for the project, draw up the constitution minutes and names the competitive intelligence project manager, guaranteeing the alignment of the objectives with the strategy of the company. • in the planning phase, they facilitate the work with the competitive intelligence project manager and the team, assigning them the necessary time, means and information. • in the implementation and follow-up and control phases, they supervise the competitive intelligence project manager and once again exercise the role of project leaders before the management, resolving figure 2 competitive intelligence project management (prepared by the authors). 15 conflicts that are outside the competence of the project manager, approving the changes and ensuring the fulfilment of the goals and objectives. • in the closing phase they approve the deliverables before being sent to the client and ensure the administrative closure of the project. when a situation arises with multiple projects in parallel, the chief competitive intelligence officer must proceed to organize the integrated management of the project portfolio. to do this, they will consider aspects such as the alignment with priorities according to the strategy, the policy and the established objectives; the balance between short and longterm projects, between lowand high-risk projects, etc.; the global supervision of the progress of the projects, taking into account the impact of the evolution of the internal and external context during its execution; and the optimization of shared resources. the chief competitive intelligence officer entrusts the management of intelligence projects to the managers of intelligence projects, people of recognized experience and prestige who assume the leadership of the work team (normally multidisciplinary) that can be of a temporary nature and even be outside of the organization (e.g. university departments, technology centres, intelligence companies). depending on the organization, the intelligence manager should identify and coordinate one or several project managers corresponding to different markets, activities and technology domains. the competitive intelligence project manager plans and organizes the work, makes decisions, supervises and checks the execution of the project and controls and creates commitment with the team, among other tasks. their operational responsibilities include to: • design and develop the processes of initiation, planning, execution, monitoring and control and closure of the competitive intelligence projects assigned. • determine the objectives and requirements of the client and stakeholders in the project, as well as delimit the scope and control of its execution throughout the life cycle of the project. • determine the deliverables and validate this information together with the client. • gradually transform high-level information into detailed action plans throughout the life cycle. • prepare the project management plan and all subsidiary plans that are necessary. • constitute and direct the project team to meet the objectives. • prepare and document descriptions of the positions or functions of the team members and other important actors for the project, including attributions of responsibility and authority. • lead and ensure the execution, monitoring and control of assigned projects, controlling and documenting possible deviations and establishing the necessary corrective measures. • control project documentation. • coordinate with other departments and processes of the organization to ensure the effective progress of the project. • anticipate the changes in the projects and implement the necessary processes to manage and control these changes. • advise the chief competitive intelligence officer in the establishment of e.g., strategies and budgets, and respond to technical and organizational issues related to project management. • review the fulfilment of objectives, action plans and indicators of the projects, reporting the results to the chief competitive intelligence officer. • evaluate the success of the projects assigned in relation to the quality of the service or product, the deadlines, compliance with the budget and the degree of customer satisfaction, considering the objectives and requirements documented and approved by the client. • document and reflect on the lessons learned. the management of intelligence projects imply the creation of ad hoc teams with the participation of specialized technicians in the search, collection and analysis of information. these processes can involve a large amount of knowledge (e.g. technical, legal, intellectual property, economical, and/or sociological), so total or partial subcontracting will be at the discretion of the organization. the processes and associated activities can also be performed by a single technician based on the size and means of the company. 16 3.3 initiating processes a competitive intelligence project is activated with the approach of an intelligence requirement by the chief executive officer (ceo) of the organization or a functional unit. each intelligence requirement or group of related requirements generates a specific intelligence project with its own plan, means, processes and unique actions. the requirements can be general and prolonged in time or specific and singular. applications from functional areas that express needs of the processes (e.g. knowing the activity of a competitor and making a prospective of their intentions) as well as monitoring critical issues of the environment will be addressed. intelligence requirements may originate as a result of the evolution and different applications of the products, processes, materials and technologies based on the organization or the demands expected or expressed by the interested parties or external to it. likewise, they may arise due to the socioeconomic, legislative, normative or project evolution or actions of the competition. the chief competitive intelligence officer will evaluate the intelligence requirements to discard, promote, prioritize and organize the projects that it considers to be of the most strategic value given the available means. the results will be validated with the ceo of the organization. the methods and criteria for the evaluation and prioritization of the requirements and, therefore, of the project, will integrate the needs of the users and other interested parties, the alignment with the strategy of the organization, the technical and economic viability, the expected result, legality, and sustainability. once the requirements have passed this first evaluation according to general strategic criteria, there is a second criterion based on factors weighted and previously established by the chief competitive intelligence officer. the selection procedures to be used in this phase can be qualitative (e.g. a weighting matrix) or quantitative (e.g. npv, irr). initially, requirements that can be satisfied in a better way by other processes of the organization (e.g. market studies) will be redirected to them. requirements that involve only basic information on a specific topic will also be discarded, but not before advising the plaintiff where and how to obtain it in the most effective and efficient manner. the main process of initiating a competitive intelligence project is the conversion of the intelligence requirement that activated it into intelligence needs, which will be specified below as information needs that will subsequently lead to specific information demands (figure 3). the conversion of intelligence requirements into intelligence needs must consider both the foreseeable use figure 3 from intelligence requirement to information resources (prepared by the authors). 17 and the final recipients of the intelligence produced. for the conversion of the intelligence requirement into the need for intelligence, the project manager must always bear in mind that users need intelligence to apply it, so they mainly seek the necessary, rather than a lot of information, through a simple and powerful process to achieve benefit from its use. as the end of the intelligence process is to respond satisfactorily to the needs of your client, the participation of the latter in the determination of intelligence needs from the general requirement is highly recommended for the success of the process. the intelligence project manager will assess, depending on the case and the circumstances, the need for the user to participate also in the formulation of information needs. in any case, it is recommended that those responsible for the strategic processes of the organization participate actively in the evaluation, validation and prioritization of the detected intelligence needs. the intelligence project manager is also responsible for transforming the identified intelligence needs into information needs. if the project has a team it will get support from the analysts for this work. each information need will give rise to different demands for information, of a more specific nature, which will be raised and expressed formally. the basic principle that must be followed is that generating concrete questions will lead to precise answers. procedures will be devised to propitiate the formulation of information needs and their upwelling as conscious needs capable of being formalized as demands, expressing themselves in a suitable way to interrogate the sources of information. the start-up processes will be included in an act of constitution of the competitive intelligence project, with the following contents: general description of the project, justification, general requirements, director (indicating responsibility and authority), measurable objectives, initial risks, summary of the schedule, budget initial, approval criteria and interests. 3.4 planning processes the planning processes establish the scope of the project, determine, describe and review the objectives and goals of the project, and define the course of the actions necessary to achieve the objectives. the result is the project management plan, whose degree of detail depends on factors such as the magnitude and complexity of the project. its design will: • ensure by the chief competitive intelligence officer that all the necessary means are available to complete the figure 4 initiating processes (prepared by the authors). 18 project, agreed upon and approved by the chief executive officer and all involved. • identify the participants involved in the execution of the project, mainly those with identified information and skills in documentation. this should define the necessary competence in terms of training, skills and experience of the personnel working on the project. • define the support roles, when required for the implementation of the project (e.g. information systems, information security, and logistics). • make sure that the organizational structure of the project is adequate. • encourage effective and efficient communication and cooperation among all project participants. all agreements, including informal ones, that affect the performance of the project should be formally documented. 3.5 executing processes the execution processes complete the work established in the project management plan. the most characteristic aspects of competitive intelligence projects are the steps that include obtaining of reliable and credible information figure 5 planning processes (prepared by the authors). 19 and the analysis and evaluation of the information. information demands will be resolved during the process of obtaining information. they are satisfied by identifying and locating heterogeneous information sources that are public access, free or paid, to create a repository with the most appropriate material, consisting of information extracted from documentary or statistical databases, raw material price lists, directories of companies, academic publications, web pages, and social networks. human resources are another asset that is highly sought after and valued in intelligence projects: these include clients, employees, competitors, suppliers, market analysts, journalists, shareholders, and experts. their participation is necessary in most intelligence projects. hence, the chief competitive intelligence officer, with the collaboration of project managers, must be concerned with creating, activating and using a network of internal and external informants to collect information. when using these sources, it is very important to document the information collected, to facilitate its later use and analysis (e.g. minutes of meetings with suppliers or customer visit reports). it is advisable to start with the collection of information from open sources. this starts from the premise that expert professionals are available in this task, because it is cheaper, simpler and helps to limit the information to be collected by human sources, and then, if it is not necessary, to resort to them. on the other hand, the use of human resources may involve legal risks if not done correctly (e.g. it may be illegal for former workers of some companies to provide relevant information if they signed confidentiality agreements at the time), so it is recommended to take extreme precautions in figure 6 executing processes (prepared by the authors). figure 7 monitoring and controlling processes (prepared by the authors). 20 this regard and systematically resort to the safest sources. the user can also provide information for the production of intelligence, because their knowledge of the organization, the environment and their experiences are fundamental inputs for the analysis. the user can indicate and help evaluate sources of information, can facilitate access to their personal contacts and can produce very useful documents during the performance of their activities. the information retrieved must be validated to discriminate which data contribute to satisfy the information requirements formulated, in terms of reliability and credibility. the ultimate goal is to find time-pertinent, relevant and useful information to solve the user's intelligence needs. this will make it easier to determine if sufficient and quality information is already available to proceed in their integration and analysis, or if the information gathering process should continue. it is convenient to document the processes of searching for and selecting information. in particular, the recovery strategy follows and indicates, keywords, descriptors, operators used, geographical or temporal segmentation. when the needs raised require a deep analysis, the information obtained is put to use for decision-making through three activities. first, we proceed to integrate data from different sources in order to create a whole of greater relevance and scope than that covered by each information separately. next, an analysis of that information is carried out to determine what information is accurate and relevant, to put it in context and establish relationships to understand the subject investigated. finally, these data are interpreted to achieve an understanding of the phenomenon and to forecast its possible consequences and evolution. the enhancement may require re-activating processes to obtain information, so procedures must be established to ensure the continuous communication between the leaders of both tasks. effective decisions are based on the analysis of data and information. this information processing can include both qualitative and quantitative techniques. as a result, we obtain formal information that can be complemented with other information of an informal nature (e.g. comments from a client or provider, or answers in an interview) and even with subjective assessments. there is a wide range of methods and analysis techniques. the person in charge of the competitive intelligence must establish procedures that minimize and guarantee the control of possible biases that may occur during the analysis. 3.6 monitoring and controlling processes the monitoring and control processes ensure compliance with the project in terms of time, cost, quality, anticipating problems, deviations and facilitating the adoption of corrective and preventive measures. if necessary, these processes will require the modification of the initial plan. 3.7 closing processes the closing processes are carried out to complete all the activities of the competitive intelligence project and formally terminate it. figure 8 inputs and outputs of a competitive intelligence project (prepared by the authors). 21 the most important closing process for competitive intelligence projects is the dissemination and protection of the information obtained and the intelligence created and transmitted. the results of the competitive intelligence project will have two forms. the first is called ‘alert’ and deals with the implications of the transcendental changes in the environment for the strategy and the plans of the organization. the second is ‘proposed decision’ for intelligence requests emanating from the different functional areas. regardless of whether they are contemplated in the competitive intelligence project, all findings that may be of interest, presumably for other projects, should be preserved, forming a repository of strategic information or a buffer of findings (figure 8). the effort of competitive intelligence is not a process of compilation but of socialization of information and available knowledge. the knowledge created is not intelligence until it is transferred successfully to its recipient. in any case, the communication of the intelligence product must be carried out through secure channels and maintain the proper level of secrecy or confidentiality. the timing of the dissemination of intelligence products depends on the nature of the end user, the intelligence needs to which it responds, the thematic or geographical coverage of the matter, the availability of new information or whether the organization is in a crisis situation. the chief competitive intelligence officer must establish procedures to identify those aspects of the intelligence provided that require clarification or expansion, have been more relevant to decision making, are relevant for implementation by users, have contributed more value to the business process with which it is linked or have generated new intelligence needs. when the intelligence transfer has been effective it can lead to the beginning of a new process of intelligence production, destined to solve new needs generated from the achieved results and the assimilation of the intelligence communicated. 4. conclusions the main conclusion is that companies will be able to implement a documented project management methodology that will establish a detailed plan for each intelligence project, with clear objectives and deliverables that will be monitored as it is executed. the methodology will include the management of the processes of obtaining reliable and credible information, and of analysis and enhancement of information as well as dissemination and protection of knowledge. the proposal here could be an alternative to the departmental-based intelligence cycle model more aligned with the organizational culture and the usual operational practices of companies. this traditional model is founded on the design and deployment of projects with a specific beginning and end that are carried out to create a product, service or unique result. the combination of systematic activities and project management that arise in response to specific proactive and reactive intelligence needs favours the prediction of opportunities figure 9 closing processes (prepared by the authors). 22 and timely solutions of possible problems, guaranteeing the necessary permeability of organizations against the environment and avoiding the indiscriminate dissemination of information. likely, this project management approach to competitive intelligence will contribute to the use of competitive intelligence in all business processes and managerial functions, and not only in strategic decision making. overcoming departmental structures as unique ways of organizing intelligence processes helps to break down cultural and, above all, organizational barriers. because of this, and considering the development of intelligence as a project aligned with project management, this methodology facilitates its understanding by managers and their integration into the general dynamic as a subproject of support linked to a general project of creating a product or service. the only goal should be to ensure that the relevant information about the environment has been captured, evaluated, analysed, contextualized and made available to decision-makers at the right time, which will undoubtedly contribute to improving their competitive position. the latter will also facilitate communication between collectors, analysts and users, and, in particular, the participation of managers involved in the management of a project in the processes of obtaining and analysing information, after equipping them with basic or advanced skills through in-company training. sometimes, competitive intelligence is practiced spontaneously on an individual basis, in response to an urgent need to gather information and make decisions in changing environments. in fact, almost all companies produce intelligence in some basic way, whether or not they are aware of it. this model of production and transfer of intelligence presented differs from the sequential approach in the form of a cycle developed more than sixty years ago, which underlies the spanish technical standards une 166006 and une-cen/ts 16555-2. for the validation of this proposal, it is necessary to conduct experimental implementations and case studies in companies using a project management methodology and their assessment by future academic studies. in conclusion, it is necessary to think and act in competitive intelligence more with the entrepreneurial and project focused culture of a business manager than with the bureaucratic and secret procedures of an intelligence officer in an intelligence service. different intelligence tribes need to explore on their own and innovate techniques for their specific functions in the diverse organizations where they serve. 5. references aenor asociación española de normalización. 2011. une 166006:2011. gestión de la i+d+i: sistema de vigilancia e inteligencia = r&d&i management: technological watch and competitive intelligence system. madrid: aenor. aenor asociación española de normalización y certificación. 2015. une-cen/ts 165552ex:2015 gestión de la innovación. parte 2: gestión de la inteligencia estratégica = innovation management. part 2: strategic intelligence management. madrid: aenor. alnouraki, m. and hanano, a. 2017. integration of business intelligence with corporate strategic management. journal of intelligence studies in business, 7(2): 5-16. calof, j. l. and wright, s. 2008. competitive intelligence: a practitioner, academic and inter-disciplinary perspective. european journal of marketing 42(7-8): 717-730. calof, j., richards, g. and santilli, p. 2017. integration of business intelligence with corporate strategic management. journal of intelligence studies in business, 7(3): 62-73. clark, r. m. 2004. intelligence analysis: a targetcentric approach. washington, dc: cq press. corbin, j. and strauss, a. 2008. basics of qualitative research (3rd ed.). thousand oaks, ca: sage. crayon. 2018. state of market intelligence. retrieved from https:/www.crayon.co/state-ofmarket-intelligence drucker, p.f. 1995. managing in a time of great change. new york: truman talley books. erickson, s. and rothberg, h. 2012. intelligence in action: strategically managing knowledge assets. new york, ny: palgrave macmillan. esteban-navarro, m. a. and carvalho, a. v. 2012. producción y transferencia de inteligencia. in j. l. gonzález-cussac ed., inteligencia. valencia: tirant lo blanch, pp. 110-170. fehringer, d., hohhof, b. and johnson, t. 2006. state of the art: competitive intelligence. a competitive intelligence foundation research report, 2005-2006, full report. alexandria, va: 23 competitive intelligence foundation. retrieved from static.canalblog.com/storagev1/vtech.canalblo g.com/docs/f_060608_stateofart_sum.pdf flynn, s. v and korcuska, j. s. 2018. grounded theory research design: an investigation into practices and procedures, counseling outcome research and evaluation, 9(2): 102116, doi.org/10.1080/21501378.2017.1403849 garcía-alsina, m. and ortoll-espinet, e. 2012. la inteligencia competitiva: evolución histórica y fundamentos teóricos. gijón: trea. garcía-madurga, m. a. and esteban, m. a. 2018. inteligencia competitiva y dirección de empresas. valencia: tirant lo blanch. global intelligence alliance. 2013a. intelligence process – turning data into insight. retrieved from https://www.m-brain.com/wpcontent/uploads/2015/04/10847.pdf global intelligence alliance. 2013b. the state of market intelligence in 2013: global mi survey findings. retrieved from https://www.mbrain.com/wpcontent/uploads/2015/04/10848.pdf grant thornton. 2016. women in business; turning promise into practice. grant thornton international business report 2016. retrieved from https://www.grantthornton.global/globalasset s/wib_turning_promise_into_practice.pdf hulnick, a. s. 2006. what´s wrong with the intelligence cycle? intelligence and national security 21(6): 959-979. kahaner, l. 1998. competitive intelligence: how to gather, analyze and use information to move your business to the top. new york, ny: touchstone. mcgonagle, j. j. 2007. an examination of the 'classic’ ci model. journal of competitive intelligence and management 42: 71-86. mcgonagle, j. j. 2016. competitive intelligence. in: p. oleson ed, the guide to the study of intelligence. falls church, vi: association of former intelligence officers, pp. 55-60. pellissier, r. and nenzhelele, t. 2013. towards a universal competitive intelligence process model. south african journal of information management 152: art. 567. retrieved from https://sajim.co.za/index.php/sajim/article/vie w/567 prescott, j. e. 1999. the evolution of competitive intelligence: designing a process for action. apmp professional journal, spring, 37-52. retrieved from http://files.paulmedley.webnode.com/20000002397ce398c7e/competitive%20intelligence%20a -z.pdf prescott, j. e. and smith, d. c. 1988. a projectbased approach to competitive analysis. strategic management journal, septemberoctober, reprinted in i.e.e.e. engineering management review 16(2): 25-37. project management institute. 2017. a guide to the project management body of knowledge: pmbok guide. washington, dc; newtown square, pa: project management institute, 6th ed. solberg-søilen, k. 2011. management implementation of business intelligence systems. inteligencia y seguridad 9: 46-67. solberg-søilen, k. 2016. a research agenda for intelligence studies in business. journal of intelligence studies in business, 6(1): 21-36. une asociación española de normalización. 2018. une 166006:2018. gestión de la i+d+i: sistema de vigilancia e inteligencia = r&d&i management: monitoring and intelligence system. madrid: aenor internacional. vedder, r. g., vanecek, m. t., guynes, s. and cappel, j. j. 1999. ceo and cio perspectives on competitive intelligence. communications of the acm 42(8): 109-116. zafary, f. 2020. implementation of business intelligence considering the role of information systems integration and enterprise resource planning. journal of intelligence studies in business, 6(1): 59-74. 5 competitive intelligence and complex systems brigitte gay university of toulouse toulouse business school, france b.gay@esc-toulouse.fr received june 1, revised form 10 september, accepted 27 september 2012 abstract: the economy reflects a dynamic interaction of a large number of different organizations and agents. a major challenge is to understand how these complex systems of interacting organizations form and evolve. the systemic perspective presented here confers an understanding of global effects as coming from these ever changing complex network interactions. another main endeavor is to capture the interplay between individual firms’ alliance strategies and the dynamic interactions between all firms. in this paper, we advocate the use in competitive intelligence of a complex systems approach originating in statistical physics to understand the intricate meshes of interfirm interactions that characterize industries today, their dynamics, and the role major organizations play in these industries. keywords: competitive intelligence, real-world networks, statistical physics, visugraph introduction because we need in competitive intelligence (ci) to analyze massive data in real time, using network visualization techniques to explore intricate interactions among organizations or agents is not enough. large data streams require quantitative tools. the complex network approach developed in statistical physics is particularly adapted to the analysis of large networks. we advocate that recent developments in this field would help address the many issues ci is confronted with at this level. physicists using a complex network approach have tried to infer the structural properties of large empirical networks. statistical regularities have been observed in very diverse real-world networks (communication, biological, or social networks, etc.) when they were compared with network models generated with different stochastic algorithms, in particular small-world and scale-free network models (watts and strogatz, 1998; barabasi and albert, 1999). progress in statistical physics was hence initially made with the identification of a series of unifying principles and statistical properties found in most empirical networks examined. researchers anticipated that these studies would result in a better knowledge of the evolutionary mechanisms of complex networks as well as of their dynamical and functional behavior. we know however that the onset and outcomes of growing networks can be very different. in addition complex networks have heterogeneous structures that vary and extend over many possible levels. comparing interfirm network structures across different industries has indeed recently revealed that though real-world growing networks may apparently share many properties they can be in fact very different (gay, 2011). moreover, they can deploy overtime very dissimilar architectures and switch from one particular structure to an altogether available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2012) 5-14 mailto:b.gay@esc-toulouse.fr https://ojs.hh.se/ 6 different one. major players also operate differently in the systems analyzed (gay, 2011). researchers must learn to evaluate the differences in the processes that take place on complex networks and start understanding the idiosyncrasies of both systems and agents’ behaviors. a recent shift in research on complex networks is to investigate more fully differences in network structures that may epitomize different behaviors. in this way the subtle dynamics that shape the different systems are also investigated. in particular, new contributions on structural properties have been made thanks to the development and use of novel metrics in statistical physics. they have for example provided evidence for the presence in networks of hierarchies (when applying k-core decomposition methods), communities ordering, and assortative mixing (barrat et al., 2004; girvan and newman, 2002; milo et al., 2002; newman, 2002; seidman, 1983; shen-orr et al., 2002). we use here some of these metrics to try to establish an understanding that complex webs of interactions that characterize industries today, as well as their evolution and dynamics, must also be considered a fundamental goal in competitive intelligence. to achieve this, we analyze the alliance networks of firms interacting in two different industries, the pharmaceutical industry (network 1) and the equity industry (network 2). we demonstrate that the two networks maintain many differences and that understanding networks dynamics is essential. 1. looking for statistical ‘irregularities’ in network structures and firm position networks are conceptualized here graphtheoretically, i.e. as objects containing nodes and links. a network is thus, in very general terms, a graph whose nodes identify the elementary constituents of the system, the interconnections between these constituents being represented by the linkages in the network. the nodes here are firms and the links actual contracts between firms. to assess the nature of the particular structure of the two experimentally observed interfirm alliance networks, we use 5 main network properties:  degree,  degree centralization (freeman, 1979),  the k-core (seidman, 1983),  the assortative coefficient (newman, 2002), and  degree modularity (newman, 2006). to capture the dynamics of the processes, we use different time windows. we then use the resulting adjacency matrices to construct the network metrics utilized. we study network 1 from 1998 to 2007 and network 2 from 1993 to 2008. fig.1 shows the topology of the two networks (static data). the two graphs make evident the difficulty of analyzing intricate meshes of interfirm transactions. both graphs also show that some firms or hubs (larger nodes on the graph) make many more transactions than others. the fact that there is a power structure in each industry is manifested, though we know nothing more about this phenomenon here, past the fact that some players in each industry deal a lot more than others. we do not know about its consequences, its level of influence on the industry in general and on its members. 7 fig. 1. network 1 (left), network 2 (right). node size is scaled to standardized network degree, or deal number, in the total network, reflecting variation in the extent of degree connectivity among the organizations. the darker lines indicate the presence of repeat ties between firms. network structure in network 2 is highly cohesive. the presence of a hierarchical structure is also apparent in both networks. hubs are tightly interconnected in network 2, but not in network 1. we will now use some network metrics to see if we can learn more from the power structures we observe and to refine the analysis. 1.1. analysis of network 1 the first metric we used is degree centralization. the degree of a node in a network is the number of links connecting it with other nodes. degree centralization indicates how centralized an entire network is and is hence a macro-level measure. it is calculated as the sum of the differences between the maximum and each individual’s centrality score, normalized to range from 0 to 1 by dividing by the theoretical maximum centralization. a star network has maximum centralization, with value 1. our data reveal that the interfirm network power structure varies and actually weakens over time, as demonstrated by variations in the centralization index (fig. 2). network 1 is first highly centralized, with few hubs. more hubs however increasingly participate in the network, though to an ever less extent and the network power structure hence weakens progressively. it is widely assumed that most social networks have a ‘community structure’, where nodes can be part of a tight group, while others may act as bridges between them. we use a new community centrality measure that identifies the participation of each node (central or not) within one or more communities in a network, defined by the leading eigenvectors of a characteristic matrix or ‘modularity’ matrix of the network (newman, 2006). this measure helps to better understand how hubs/central firms operate within the different structures. in the first period, central players have small values for their community centrality, indicating that they operate globally (fig. 3). the situation is however reversed in the latest period as central organizations have higher values for their community centrality. firms with a higher degree tend then to exert control within communities rather than across the overall network structure. the network power structure thus evolves from globally to locally effective. 8 fig. 2. decrease in degree centralization overtime – network fig. 3. change in community degree network 1 we also measured degree assortativity to link organizational and in particular hubs behavior to the structuring of the interfirm network. the assortative coefficient measures degree correlations. in other words, correlated graphs are classified as assortative if nodes tend to connect to their connectivity peers, and as disassortative if nodes with low degree are more likely connected with highly connected nodes. networks of neutral mixing of their degree show none of these tendencies. correlations are measured by the assortativity coefficient r, or pearson correlation coefficient for the degrees at either side of an edge (newman, 2002). the theoretical range is [-1, 1]. 0 5 10 15 20 25 30 35 40 period 1 period2 period 3 period 4 c e n tr a li za ti o n i n d e x ( % ) 0 0,5 1 1,5 2 2,5 0 0,1 0,2 0,3 0,4 0,5 c o m m u n it y c e n tr a li ty degree centrality community centrality, period 1 community centrality, period 4 9 we find strong variation with assortativity in the network (table 1). we find a value for the assortativity coefficient of r = 0.483 in the first period indicating strong disassortative mixing, i.e., hubs are primarily connected to less connected firms. hubs are thus not linked together. though the network remains disassortative, r increases continuously until the network shows neutral mixing in the latest period with r = 0,015. firms then interact with all kinds of firms, similar or not. linkages of hubs among themselves are therefore not a feature of the interfirm network as it is never assortative. 1.2 analysis of network 2 centralization data also establishes that, as network 1, network 2 is dependent upon hubs for (fig. 4). however we observe 2 peaks, the network is first highly centralized; centralization decreases afterwards and then regains some momentum though power is at that time distributed among more central organizations. these variations in the network power structure constitute key points that alert to change, individual as well as systemic. to probe these modifications further, we used the k-core decomposition method. fig. 4. network 2 centralization network 1 r coefficient period 1 -0,483 period 2 -0,306 period 3 -0,103 period 4 0,015 table 1: assortativity coefficient the k-core decomposition is based on a recursive pruning of the least connected nodes (fig. 5). the nodes displayed in the most internal of the shells of the network are those forming the central core of the network. applying this method allow us to identify the inherent layer structure of a network and thus gain information about its hierarchical structure and the placement of hubs (globally central if in the innermost k-cores and locally central if hubs are merely members of the outer kcores). applying the k-core decomposition method, we investigated which firms made it to the central core by looking at the correlation between the degree of the nodes and what is called the coreness value. we determined the existence of 22 consecutive k-cores. 0 5 10 15 20 25 30 period 1 period 2 period 3 period 4 period 5 c e n tr a li za ti o n i n d e x ( % ) 10 we find that hubs with the highest degree are within the inner shell of the network (only 2 hubs out of the first 58 firms with high degree are in the 18and 20core respectively for the period 19892008, while all others belong to the innermost set of nodes, the 22-core; 89% of the nodes in the inner core are hubs). there is therefore a clear global hierarchical structure. there is no k-core fragmentation; the remaining nodes forming a kcore systematically belong to the same connected component (static and temporal analysis). fig 5 (bottom) reveals the importance of examining dynamic displays of interactions, including the links between major players in the innermost kcore. we know the extent of the involvement of each hub in the system during each period (5 periods in total) as the nodes have been replaced by color-coded histograms that account for their degree centrality (standardized total number of transactions per firm) at each time point. visugraph visualization software allows positioning nodes according to their activity as they occur by (gay and loubier, 2009, 2012). we thus find that some hubs are highly active at all times whereas others have dropped their activity significantly after the second period. interestingly, from period 4 onwards, more hubs become extremely active, thus explaining away the centralization data in fig. 4. an easy way to pursue the analysis is to ‘tag’ the nodes/firms with additional data such as firms’ date of creation, number of employees, market capitalization, country of origin, etc. in fig. 6, we investigate whether the same category of major players operate at all times. we find that basically one category of major players in this industry (pink nodes) operate during the first peak of centralization, shown in fig. 4 while a second category, including more major players (blue nodes) becomes very active from period 4 to period 5, explaining away the second centralization peak, as well as the decrease in the centralization index observed during this second peak (fig. 4). 11 fig 5. central players’ localization (top) and networking activities (bottom) – network 2. the top figure shows the number of major players in the different states (usa). two categories of hubs are active (blue circles for category 1, red circles for category 2). the bottom figure highlights the activity in the latest 2 periods (periods 4 and 5) of more major players (within blue circle). this change is due to the sudden increase in transacting activity of the ‘category 2’ players displayed in the top figure. 12 fig. 6. dynamics of the transacting activity of major players from period 1 to 5 – network 2. pink rectangles represent category 1 players and blue rectangles category 2. when we compare the images in fig. 5 (bottom) to that in fig. 5 (top), we see the relevance of thinking of firms as interconnected organizations. the top figure gives the impression that a few isolated clusters of key firms operate in the us. in fact all major players in this industry are interacting between themselves, independent of their location, and they time their activity. to verify if these major players not only interact between themselves but also operate globally, we measured the community degree index. fig.7 shows the results for community centrality. they highlight that while community centrality is correlated with degree (r 2 = 0,75), the two are not perfectly correlated. the effect is stronger for major players: they clearly transcend borders (lack of correlation dc/community centrality for hubs). we find the same results whether we look at static or dynamic data. therefore hubs control the network at all times even when their number increases and another category of actors surpasses the previous one. 13 fig. 7. community centrality network 2 using degree assortativity, we find that major players mix not only with other major players but also with less connected, smaller, organizations. the network is indeed non-assortative for the whole period (r = 0.008) and falls under the slightly assortative mixing if we look at discrete time periods (r values ranging from 0,006 to 0,04). the non-assortative nature of the network establishes that major players interact among themselves but also with peripheral players. a more detailed analysis (data not shown) reveals that hubs tend to interact repeatedly between themselves while their deals with peripheral players are rarely repeated even though hubs interact with many different small players at all times. these small players allow hubs to have rapid expansion strategies when needed or to cope with uncertainty and crisis situations such as the subprime crisis. 3. discussion what have we learnt from these data? for network 1, we’ve demonstrated that the influence of central players, strong at first, weakened rapidly through time and most importantly, that their influence is global in period 1 and only local in the last period examined. not shown was that central players in period 1 were high tech players with radical innovations while as hubs were mostly among the top 10 global pharmaceutical companies in the last period. we’ve also shown that the relations were mostly asymmetrical, i.e. hubs interacted essentially with peripheral players. hubs did not interact among themselves, except at the very end. for network 2, we showed again that the power structure varied, but with 2 distinct phases and peaks. using the k-core decomposition method linked to dynamic visualization techniques, we quickly demonstrated that one category of major firms in the equity industry dominated the first phase. the 2nd phase is explained by the sudden arrival of a new category of big players in this industry. this time, major players interacted heavily between themselves and we could measure the differential co-involvement of the different hubs 0 1 2 3 4 5 6 7 0 0,05 0,1 0,15 0,2 c o m m u n it y c e n tr a li ty dc 14 through time. big firms in this industry also interact with smaller, less active firms. these peripheral firms are always dependent upon hubs and hubs clearly have a global influence for all periods of times. 4. conclusion we want to stress the importance of considering the links between organizations or agents in ci. economic and financial systems are built on interdependencies. understanding their dynamics is crucial as these networked systems change rapidly. though we’ve only used a very small set of metrics, we’ve proven that inter-organizational networks are very different and evolve differently. none of the metrics used here give a sense of ‘universality’ or of common mechanisms regarding the growth and dynamics of complex networks. the major role of big firms in both fields does not come as a surprise. we’ve demonstrated that hubs operated differently between networks, that different categories of hubs intervened, that hubs interact tightly or not at all among themselves, and that the power structure of a network can collapse (in this case, -in network 1-, when it is led by highly innovative firms). we’ve also shown that major companies in both industries have different strategies and timing, and can operate globally or locally. this was done using a very small set of network metrics and a visualization software that can render networks dynamic, another key goal for ci analysts. ongoing work consists of matching visualization techniques with statistical physics, accessible directly on graphs. this will give more input on systems and their agents. “more is different”. we highlight the importance of progressing in the field of statistical physics to help ci practitioners address differences between economic and financial systems, as system dynamics evolve rapidly due to endogenous as well as exogenous events (bubbles and busts, radical change, globalization, new rules, etc.). we also call attention to the importance in ci of understanding the interplay between microand macrobehavior (i.e. the influence the strategy of individual firms may have on the macro systems they are embedded in and the constraint/influence that these economic or financial systems in turn may exert on individual organizations). the ultimate goal is to give managers guidelines to help them understand the different environments in which they operate and position their firms. some firms can also change/govern economic/financial environments or alter their power structure. references barabási, a. l., & albert, r. (1999). emergence of scaling in random networks. science, 286, 509– 12. barrat, a., barthélemy, m., pastor-satorras, r., & vespignani, a. (2004). the architecture of complex weighted networks. proceedings of the national academy of sciences usa, 101 (11), 3747–3752. freeman, l. c. (1979). centrality in social networks: conceptual clarification. social networks, 6:223–258. gay, b. (2011) universal dynamics on complex networks, really? a comparison of two realworld networks that cross structural paths (…) but ever so differently. in: “social network mining, analysis and research trends: techniques and applications”, eds, i-hsien ting, tzung-pei hong and leon s.l. wang, national university of kaohsiung, taiwan, in: igi global, ny, usa. isbn 978-1-61350-513-7 (hardcover) -isbn 978-1-61350-514-4 (ebook) isbn 9781-61350-515-1 (print & perpetual access). gay, b., & loubier, e. (2009). dynamics and evolution patterns of business networks. paper presented at the international conference on advances in social network analysis and mining (asonam), athens, greece. gay, b., & loubier, e. (2012) « worldwide dynamic evaluation of complex business networks.” in: "dynamic analysis for social network". editor: carlos andre pinheiro, iconcept press. isbn 978-14610987-3-7. girvan, m., & newman, m. e. j. (2002). community structure in social and biological networks. proceedings of the national academy of sciences usa, 99, 7821–26. milo, r., shen-orr, s., itzkovitz, s., kashtan, n., chklovskii, d., & alon, u. (2002). network motifs: simple building blocks of complex networks. science, 298, 824–27. newman, m. e. j. (2002). assortative mixing in networks. physical review letters, 89, 208701. seidman, s. (1983). internal cohesion of ls sets in graphs. social networks, 5, 97–107. shen-orr, s. s., milo, r., mangan, s., & alon, u. (2002). network motifs in the transcriptional regulation network of escherichia coli. nature genetics, 31, 64–68. watts, d. j., & strogatz, s. h. (1998). collective dynamics of ‘small-world’ networks. nature, 393, 440–442. 5 technical intelligence approach: determining patent trends in open die forging marisela rodriguez 1, alejandro palacios 1 and dante cortez 2 1 national graduate and research school, tec de monterrey, mexico 2 innovation senior manager, steel company x, mexico email: marisrod@itesm.mx, alejandropalaciosmata@gmail.com and dante.cortez@gmail.com received january 10, accepted 5 may 2014 abstract: open die forging is an important process for alloys and steels present in a variety of industries, such as in the aerospace industry, construction, mining and general machinery. during the forging process several wear mechanisms occur: thermal fatigue, plastic deformation, mechanical fatigue, etc. causing quality damage and economic losses. academy and industry are devoting significant efforts to confront this situation where research acquires a key role. under this context the objective of our research is to apply patent analyses as part of a competitive technical intelligence methodology on open die forging. in particular, a keyword-based patent analysis and a patent citation analysis were developed to identify the organisations, countries, inventors, and technological trends more important for this area. keywords: open die forging; competitive technical intelligence; patent analysis; citation analysis. 1.0 introduction forging is a manufacturing process where metal is pressed, hit or compressed under great pressure to create high-strength parts (forging industry association, 2013). the open die forging process involves the formation of preheated metal pieces placed between an upper and lower die attached to a press (scotforge 2014). this process can be used for a wide range of alloys and steels in a variety of industries, such as in the aerospace industry, construction, mining, general machinery, etc. available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 1 (2014) 5-15 https://ojs.hh.se/ 6 typically, metal parts are worked on at their recrystallisation temperature, which is between 1900°f and 2400°f for steel. the open die forging process improves the quality of the material via the transformation of the mould structure, which removes any gaps that may be present in the steel (scotforge 2014). one of the problems of the open die forging process is the tools that are used are relatively expensive. therefore, the process is economically attractive only when a large number of parts are produced and/or when the mechanical properties required in the finished product can be obtained only by a forging process, which has been previously described (shen et al. 2004). similarly, the wear produced in the tooling during the metal forming process must be accounted for. during the forging process, dies are subjected to mechanical and thermal stresses induced by thermal cycles and other forging operations, which damage the dies’ surfaces and sub-surface layers (magri et al. 2012). due to this adverse environment, several wear mechanisms occur: thermal fatigue, plastic deformation, mechanical fatigue, etc. after long-term wear failure has occurred, dies must be removed from service and discarded once the workpiece is either out of dimensional tolerance, exhibits poor surface finish, or sticks to the dies or transfer mechanisms (choi et al. 2012). because there are a significant number of factors involved, it is important to detect the primary technological research trends in the open die forging process. the objective of our research is to apply patent analyses as part of a competitive technical intelligence methodology on open die forging. in particular, a keyword-based patent analysis and a patent citation analysis were developed to identify the organisations, countries, inventors, and technological fields with a more worldwide presence. this approach is part of a master’s thesis in quality and manufacturing systems at x, where the author is y (2014). the idea of analysing open die forging came from a project that the competitive technical intelligence unit at x developed for steel company x. this project is confidential, and therefore, this paper presents the subsequent research developed during the master’s thesis. here we removed the names of our institute as is suggested by jisib for the evaluation. this paper is organised in the following sections. first, we present the theoretical background of competitive technical intelligence and patent analysis. then, the analysis is described in the methodology section. the results and discussion of our research are presented afterwards. finally, the conclusion and limitations of the research are discussed. 2.0 competitive technical intelligence competitive intelligence (ci) is a necessary, ethical business discipline for decision-making based on understanding the competitive environment (scip 2013). at its most basic description, intelligence is analysed information (fuld 2014). competitive intelligence is understood as a discipline in which, through a systematic, ethical process, is responsible for monitoring the competitive environment of a particular industry. this discipline is also seen as a proactive approach for strategic planning, where information regarding the environment is obtained, transmitted, evaluated, analysed and made available to the customer as the end result that supports cognitive decision making (rodríguez and lopez 2000). competitive technical intelligence (cti) is the analysis of sensitive business information of external scientific research or technological threats, opportunities or developments that can potentially affect the competitive position of a company (ashton et al. 1994). according to ashton et al., cti pursues three main objectives: 1. provide early warning of external technical developments that represent potential threats or opportunities for the business. 1. evaluate new products, processes and prospects for cooperation in science and technology to generate appropriate responses. 2. anticipate and understand trend-related changes in the competitive environment as a preparation for organisational planning and strategic development. in addition, competitive technical intelligence consists of monitoring the business environment, which involves scientific and technological developments related to processes of research, development and innovation, technology acquisition policies, joint ventures, research and development portfolios, etc. (rodríguez and escorsa 1998). 2.1 patent analysis in cti in an organisation, patents are considered the most valuable output indicators in the process of technological innovation (hidalgo et al. 2009). it is important to state that almost 90% of all 7 technological information can be found in patent publications (blackman 1995). patent documents are an important source of competitive intelligence that companies can use to gain strategic advantages; for many years, patents have been considered indicators of technological progress (rodríguez and tello 2012). there are several patent classification systems: the international patent classification (ipc), the united states patent classification system (uspcs) and the cooperative patent classification (cpc). ipc is a hierarchical classification system of increasing complexity; it is divided into classes, sub-classes, groups and sub-groups. the world intellectual property organisation defines itself as a “hierarchical system of language independent symbols for the classification of patents and utility models according to the different areas of technology to which they pertain” (wipo 2014). the cooperative patent classification is a bilateral classification system, which has been jointly developed by the european patent office (epo) and the united states patent and trademark office (uspto). the cooperative patent classification improves patent searches, with more detailed classifications and with added and revised sections. ipc has over 70,000 technology entries, whereas cpc has over 250,000. moreover, cpc has an additional section: “general tagging of new technological developments; general tagging of cross-sectional technologies spanning over several sections of the ipc; technical subjects covered by former uspc cross-reference art collections [xracs] and digests” (epo 2014). 2.2 keyword-based analysis the keyword-based patent analysis uses information from patent incidences, which includes defined keyword frequencies and co-occurrences between them. the outcomes of this analysis are used to identify trends in advanced technology, discover new technological opportunities, predict new technological concepts, and develop technology roadmaps (choi et al. 2012). the keyword-based patent analysis can also be used to compare the strategic positioning of a certain industry to several countries. by studying patent frequency of assignees from different countries, analysts can determine which countries are taking the lead in different technological areas. similarly, researchers can analyse the profiles of inventors/organisations to identify the contributions of a specific patent that establishes relations with countries or technological classifications (trappey et al. 2011). a patent map uses patent information to create specific graphs and charts that provide simple, intuitive ways to address complex technical information (zha and chen 2010). a simple form of representation is through patent incidences, which may be expressed in terms of particular patent information, such as assignees, inventors, countries, ipcs, or based on a defined time period. 2.3 patent citation analysis a patent citation analysis is useful to identify knowledge flows at distinct levels: national, industrial, business and technological. the patent citation analysis intends to find all patents that have been cited by (i.e., backward citations) and those that cite the analysed patent (i.e., forward citations). this type of analysis is useful to detect state-of-theart technology or to determine high similarity inventions (park 2013). similarly, a patent can also cite non-patent literature, not only scientific articles but also a mixed set of other publications, such as conference proceedings, books, newsletters, among others (list 2010). additionally, patent citations made to scientific literature in a particular sector have been used as an indicator of scientific activity within research and development in this area (bergmann et al. 2008). 3.0 methodology for this research, patent insight pro was used, which is a patent research, analysis, mapping and visualisation software. developed in india in 2004, this software provides decision support solutions, information analysis, and technology monitoring. patent insight pro provides global services to industries that produce energy, electronics, medical devices, etc. (patent insight pro 2014). figure 1 illustrates the methodology of this research, which departed from the proposal by rodriguez and tello (2012) on its six stages, where the variations in the patent analysis were implemented by the aforementioned author of the master’s thesis. 33 figure 1. competitive technical intelligence and patent analysis. adaptation from tello & rodriguez, 2012. the following are the descriptions of the six steps shown in figure 1: 1. planning: refers to the objectives statement, scope, and limitations and includes allocation of resources and responsibilities. 2. selection and information gathering: primary and/or secondary sources of information. in our case, we focused our attention to the patent source of information. 3. information analysis: different methods can be used. in this case, we developed a patent statistical analysis, which is based on 4 steps: data cleaning. the patent data obtained from the “selection and gathering of information” step are cleaned; the fields of assignees, inventors, countries, etc., are filled with the latest information. trend identification. the purpose is to identify the primary applicants, patent codes (ipc, cpc, uscp, etc.), countries and keywords. generation of matrices and technology maps. in this step, we generate matrices and technology maps that link the identified trends. citation analysis. backward and forward patent citation analysis is recommended to identify inventions that are highly related to the original patent. 4. diffusion of results: disseminate information to stakeholders. 5. project evaluation. the project is evaluated by the stakeholders to receive feedback and to identify areas for improvement. 9 6. decision making. this part of the methodology is performed exclusively by the company or the primary decisionmakers involved. this purpose of this step is for the company to use the results presented in the cti report to develop action plans based on the analyses performed. it is important to clarify that, as was mentioned in the introduction, the project developed for the steel company x is confidential and therefore, cannot be disclosed in this work. this paper presents a supplementary study, where the author of the master’s thesis developed a search string that is different from the one used in the project. the search strategy was expanded by increasing the range of years and modifying the terms used in the keywords, which resulted in a greater number of patents for analysis. for the purpose of this research, we will focus on the patent analysis stage; similarly, we will cover the first 3 steps of the methodology because the last steps involve the dissemination of information, stakeholders’ project evaluation and the decisionmaking process. 3.1 planning in this phase, we established the scope, objectives and participants of the project. the research focused on patents published between 2008-2014. the objective was to identify top companies, inventors and trending technologies developed in the field of open die forging. 3.2 selection and gathering of information the collection and analysis of the patent data were performed using the patent insight pro software program. we selected the period of time from 2008 up to march 15 th , 2014. this search was conducted on the espacenet database to retrieve a large number of patents worldwide, which would provide an accurate perception of the latest progress in this field. we first searched the abstract and claims sections of the patent documents using (open die forg*) as the primary keywords. however, several of the results were not within the scope of our research because in several cases, the primary keywords were not listed as the patent’s central invention or were related to industries different from the forging industry. finally, to perform the search, we used the terms, [open die forg* and (tool* or die*)], as the primary keywords. the established keywords provided accurate results according to the scope of our analysis. 3.3 patent density to perform the search in espacenet, we used boolean terms to transform our keywords into a search string. through the patent search in espacenet, we obtained the following results: 86 published patents (80 patent families and 6 individually issued patents), 194 inventors, 78 assignees, 22 ipc main groups, 112 ipc full groups, 9 cpc main groups and 45 cpc full groups. figure 2 presents the patent trend by year. the xaxis in the graph indicates years, and the y-axis indicates the number of published patents. as we can see, there is a steady increase in patent publication since 2010. 10 figure 2. patent density. data from espacenet using insight pro. 4.0 results and discussion 4.1 data cleaning once we obtained all of the patent documents, we proceeded to filter and clean the data, specifically the ‘assignees’, ‘inventors’ and ‘country’ fields. this task is useful for merging similar terms, updating patent information to the latest assignees, avoiding repeated information, etc. in this stage, internal keywords were identified (453 different keywords in total) among the most repeated words in the title, abstract and claims sections of the 86 patents. the following results are from 2008 to 2014. 4.2 patent activity and main trends 4.2.1 top organisations organisations with the highest numbers of patents were identified; the top 3 organisations in descending order are the following:  ati properties inc. (usa): 7 patents  wuxi turbine blade co. (china): 5 patents  national machinery co. (usa): 3 patents 4.2.2 top countries a strong patent activity was detected primarily from china (52 patents), followed by the usa (13 patents) and germany (4 patents). 4.2.3 top ipc full-digit codes as previously stated, the ipc system offers an international categorisation for different inventions, which allows a trend analysis in different technological areas. the top 10 ipc full-digit code trends are shown in figure 4. 11 figure 3. top 10 ipc full-digit code trends. data from espacenet using insight pro. the following are the descriptions of the top 3 ipc full-digit codes shown in figure 3:  b21d28/14. working or processing of sheet metal or metal tubes, rods or profiles without essentially removing material; punching. shaping by press-cutting; dies.  b21j5/02. methods for forging, hammering, or pressing (for working sheet metal or metal tubes, rods, or profiles b21d; for working wire b21f); special equipment or accessories. die forging; trimming by making use of special dies.  c22f1/18. changing the physical structure of non-ferrous metals or alloys by heat treatment or by hot or cold working/highmelting or refractory metals or alloys based thereon. 4.2.4 top cpc full-digit codes as seen in section 2.1, the cooperative patent classification system refers to a technological classification, which contains a revised and more detailed description of each group and sub-group compared with the ipc system. the following figure shows a timeline with the trend of the primary cpc 8-digit codes. figure 4. cpc full-digit code timeline. data from espacenet using insight pro. there are 5 primary cpcs that jointly present a patent trend: • c22f1/183 • c22c14/00 12 • b21j1/06 • b21j1/025 • b21j1/003 the c22f1/183 and c22c14/00 codes are related to metal processing, with a focus on treatment of titanium alloys. moreover, the b21j1/06, b21j1/025 and b21j1/003 codes relate to the metal treatment by forging, pressing, etc., with subclassifications, such as heat treatment and material preparation. 4.3 technology map generation 4.3.1 technology map organisations vs ipc full-digit codes to visualise the patent activity of organisations, we generated a technology map that link the top 10 assignees with the top 10 ipc full-digit codes; figure 5 presents an example of such a map. figure 5. organisations vs. ipc full-digit codes. data from espacenet using insight pro. it should be noted that the company, ati properties inc. (usa), has had a remarkable amount of activity in technological inventions in the following fields:  c22f1/18 changing the physical structure of non-ferrous metals or alloys by heat treatment or by hot or cold working/high-melting refractory metals or alloys or based thereon; and  c22c14/00 metallurgy; ferrous or nonferrous alloys; treatment of alloys or nonferrous metals. alloys/alloys based on titanium. 4.3.2 chinese patents section 4.2.3 presents china as the country with the greatest patent activity in open die forging. the results show that the top applicants have, on average, 3 patents per organisation. however, there are numerous universities, companies and independent inventors who have a single published patent (31 of 41 chinese organisations), which altogether, places china as the primary country in open die forging activity. additionally, as shown in figure 6, there is an increasing patent publication trend in this country. 13 figure 6. patent density in china. from 2009 to 2013, the percentage of patent publication has grown by approximately 160%. 4.3.3 identification of technological trends for this part, we focused on several of the primary topics in open die forging (dies for forging, lubricants and hydraulic presses) to identify technological trends. for this task, an analysis of the title, abstract and claims of patents was performed. here, we present the 2 primary trends supported by 2 examples of the identified patents. 1. dies for forging. new die forms tend to be a more efficient process, which prevents deformation of parts and increases the life of the die. cn202334187. zhengzhou jinyang electric co. (china) has proposed a structure with a bottom-top-closed opening, which reduces the deformation in the heat treatment process. cn202752519. yancheng liken forging co ltd (china) has designed a die to reduce the forging strength and increase the life of the die. 2. lubrication systems pursue the uniform application of lubricant in the die system and forging pieces. jp2008207194. kurimoto ltd. (japan) has designed a device for the uniform application of lubricant in a press forge using lubricant spray nozzles. tw201036728. amada co. ltd (taiwan) has developed a set of punching dies, which includes a lubrication system for the same purpose. 4.4 citation analysis as seen in section 2.1 patent analysis in cti, a patent citation analysis is useful to find highly related inventions of a certain patent. the patent us8613818 processing routes for titanium and titanium alloys, was selected due to its importance throughout the investigation. this patent is the one with the most members in their family of patents, with a total of seven (usa, taiwan, china, australia, mexico, canada and wo-world). moreover, it belongs to the primary assignee of our research, ati properties inc. (figure 3), and is also classified into the primary ipc full-digit code (c22c14/00), as shown in figure 4. this patent has 11 backward citations but no forward citations. the citation tree for this patent is shown in figure 7. 14 figure 7. citation analysis for patent us8613818. three of the most recent patent cites are presented on table 1. . patent number title assignee publication date us20070193018 methods of beta processing titanium alloys ati properties inc. 23/aug/2007 us20050145310 method for producing homogeneous fine grain titanium materials suitable for ultrasonic inspection general electric company 07/jul/2005 us6569270 process for producing a metal article honeywell international inc. 27/may/2003 table 1. three backward citations for patent us8613818. 5.0 conclusions through the patent analysis methodology incorporated into the discipline of competitive technical intelligence, we identified the key players in open die forging, which include countries, universities, companies and organisations. similarly, it was possible to establish the primary lines of research through the analysis of patent classification systems, such as ipc and cpc. by means of technology maps, it was possible to identify the most important research lines of the primary applicants. additionally, this section presented an analysis of the patent activity of china because it is the primary country that is developing and protecting technology in open die forging. we also identified technology trends, where major advances are presented in forging dies, lubricants and hydraulic mechanisms for process control. finally, through the citation analysis of patent us8613818processing routes for titanium and titanium alloys, it was possible to find highly related inventions to that patent based on backward citations; this analysis could also provide insights into the evolution of a certain industry. the methodology of competitive technical intelligence and patent analysis makes it possible to gather information regarding leading organisations, research areas, etc. through this methodology, it was possible to identify trends that could represent a business opportunity or threats to the open die forging industry. this methodology could be combined with other types of analysis (market analysis, porter five forces, etc.) to enrich and make the process of strategic decision-making more precise. acknowledgement we would like to thank the steel company x who provided important advice for the master’s thesis of alejandro palacios. we would also like to thank francisco paredes (research assistant at the quality and manufacturing center at tec de monterrey) for his help in the electronic artwork. references ashton, b., johnson, a. & stacey, g. 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(2010). study on early warning of competitive technical intelligence based on the patent map. journal of computers, 5(2), 274–281. http://www.epo.org/searching/essentials/classification/cpc.html http://www.epo.org/searching/essentials/classification/cpc.html https://www.forging.org/forging-facts#1 http://www.patentinsightpro.com/ http://www.scip.org/re_pdfs/1395928684_pdf_frequentlyaskedquestions.pdf http://www.scip.org/re_pdfs/1395928684_pdf_frequentlyaskedquestions.pdf http://www.scotforge.com/sf_facts_opendie.htm http://www.wipo.int/classifications/ipc/en/ 16 o p i n i o n s e c t i o n analysis of knowledge transference processes in first mission activities of universities: portfolios as proposal of analytical tool for competitive intelligence functions victor cavaller 1 1 open university of catalonia (uoc), spain email: vcavaller@uoc.edu received december 11 2013, accepted april 7, 2014 abstract: the relationship between higher education activities follows a sequential cycle focused on knowledge transference. the aim of this paper is to examine the details of the following associated questions of debate about kt (knowledge translation) in education mission activities (first mission): relationship between teaching activities and scientific research, correlation between learning and teaching quality, entrepreneurship and the bologna process: the reform of education systems and finally, learning & teaching outcomes. this analysis allows a systematic approach to the specific goals of the bologna process that include promoting the student centred model, increasing the autonomy and accountability of universities, strengthening the responsibility of institutions for the quality of teaching, highlighting the excellence of learning, enhancing the quality of research and the transference of knowledge, as a basis for a competitive economy. in order to achieve this goal, from a ci (competitive intelligence) perspective, portfolios represent a critical tool for education systems as training-for-self-assessment, promoting new forms of support for the excellence of learning & teaching activities and designing of curricula and programmes. keywords: knowledge transference, university assessment, portfolios, competitive intelligence, bologna process. available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 1 (2014) 16-25 mailto:vcavaller@uoc.edu https://ojs.hh.se/ 17 o p i n i o n s e c t i o n 1. introduction in the last decades, the relationship between learning and teaching, traditionally defined as ‘transmission of knowledge’ activities, and the interconnection with research, understood as the ‘generation of new knowledge’ have become problematic (elton 1992; rowland 1996, coaldrake and stedman (1999). we could highlight the following reasons:  “knowledge is now generated in the context of application”. (nowotny et al. 2001) gibbons explain the changes in the constitution of science and in research practice as a consequence of a new paradigm of knowledge production attributing to the growing contextualization and socialization of knowledge. (gibbons et al., 1994) “the old paradigm of scientific discovery – characterized by the hegemony of theoretical or, at any rate, experimental science; by an internally-driven taxonomy of disciplines; and by the autonomy of scientists and their host institutions, the universities – was being superseded by a new paradigm of knowledge production, which was socially distributed, application-oriented, trans-disciplinary, and subject to multiple accountabilities” (nowotny et al. 2003).  the ‘learning and teaching’ interaction has changed through a new model defined as student centred. “students are not passive. they come with their own perceptual frameworks” (erikson, 1984), “students learn in different ways” (briggs-myers, 1980; kolb,1984), “learning is an active dynamic process” (cross,1991), “students construct their own meaning by talking, listening, writing, reading, and reflecting on content, ideas, issues and concerns” (meyers and jones, 1993).  the flow of kt processes involved draws a complex network relationship, and this factor has important repercussions in the domain of the first mission in higher education: first, the activities associated with the first mission of universities have two faces: teaching and learning. learning processes, as a result of teaching processes, refers to the acquisition of knowledge, skills, and competencies. teaching provides sources to learning, and learning provides professionals, researchers and also future teachers. we must appreciate this difference in order to set different actors, achievements and consequently, indicator systems, as a first criterion of classification, maintaining the loop of their relationship. since now, we have seen that second mission activities are based on processes where scientific research provides new knowledge. we have showed activities that correspond to a first moment of diffusion and extension by means of scientific production and networks, and activities in a second moment when this shared scientific production crystallize in a knowledge product to commercialize or in a degree of expertise, as a guarantee for research contracts. it is important to distinguish the correlation of each of these two phases of research with teaching.  finally, the intangible benefits of higher education, the complexity and interdisciplinary are issues surrounding assessment and accountability in higher education. “quality in higher education is a multidimensional concept, which should embrace all its functions, and activities: teaching and academic programmes, research and scholarship, staffing, students, buildings, facilities, equipment, services to the community and the academic environment”. (unesco, 1998) the lack of a definition of kt flow and parameters for this new paradigm that follows here the sequence of learningteaching-research activities has been an obstacle to define indicators, and consequently, educational systems were witnessing a deep transformation currently ongoing to third mission requirements all around the world. furthermore, recently chalmers (2007) has proposed a framework for dimensions of quality learning-teaching practice. the four dimensions are conceptualised in a “diagram with input, process, output and outcome indicators, all of which are necessary for a more complete understanding of the institution. the different levels of involvement of the institution and the people in the institution are identified as critical, as it is the people who must provide the commitment and the engagement with the process if change is to take place”. (chalmers, 2007). 18 o p i n i o n s e c t i o n for us, the relationship between higher education activities follows a sequential cycle in both directions, using the research mission as a link from learning-teaching to entrepreneurship, entrepreneurship as a link from research to learning-teaching, and learning-teaching as a link from entrepreneurship to research. figure 1: stream activity of kt processes associated to three missions of universities in the next sections, we will examine the details of the following associated questions of debate about kt processes in 1st mission activities:  relationship between teaching activities and scientific research  correlation between learning and teaching quality  entrepreneurship and bologna process: the reform of education systems  learning & teaching outcomes: portfolios 2.0 relationship between learning, teaching and research activities there is considerable research literature that reviews empirical evidence on the complex interaction between learning (l), teaching (t) and their interconnection with research (r) in higher education. the concept of “teaching-research nexus” has been explored by trowler and wareham (2007) making a review of the empirical evidence, we could explore their relationship, in descendant order (r-t-l: research to teaching to learning) and in ascendant order (l-t-r: learning to teaching to research), comparing the possible contrasting perspectives: positive, negative, and null (adapting qamar, 2004) on continuous or disrupted university scenarios where this sequence is developed. in descendant order (r-t-l), a positive perspective would make evident that “research helps in expert and contemporary knowledge; leads to credibility enhancement, increase lecturer confidence and students appreciate teachers who present research”. in ascendant order (l-t-r), a positive perspective would show that excellence in learning will become excellent future teaching and in a next step “teaching can be particularly good for young researchers because it can reinforce their ability to expound and clarify their thinking (...) and can elucidate gaps in the academic’s knowledge base”. the horizon in this order is entrepreneurship. research is “thought to be good for staff development, institutional image and reputation, and student recruitment” in both senses, a negative perspective would say: “there is limited time, energy, and commitment, for a faculty to do both teaching and research. research and teaching are different enterprises, and require contrary personality characteristics”. dispersion of activities decreases quality. from a null perspective, research and teaching are different enterprises, and there would not be a correlation between them, while in teaching and learning quality could observe only a weak relationship. quality in research, teaching and learning would not be contradictory goals, but there would not be perceptible evidence in any of the teaching social actions learning research k product transference 19 o p i n i o n s e c t i o n reviews of the presence of a negative or positive relationship between them a great number of variables are involved in learning, teaching and research activities that must be included in empirical research studies: areas (disciplines, empirical or social sciences, departments), levels (individual, departmental and institutional), institution or actor (type, class size, department size, level of study, sex, etc.), parameters (inputs, outputs, skill or outcomes) and there are other tangible factors as resource size or intangible as reputation or institutional culture, that condition the results and their meaning in comparative studies. unfortunately, the heterogeneous scenarios that the combination of these variables provides have been since now a great obstacle to achieve significant conclusions. as a synthesis of the present background, we can highlight some evidences from empirical research:  weak relationship: the evidence gathered by qamar (2004) in several reviews of empirical research on the relationship between teaching and research in higher education (faia: 1976, feldman: 1987, allen: 1996, hattie & marsh: 1996, braxton: 1996, etc.) “suggests that research and quality teaching are not contradictory roles. however, we cannot conclude from the information at hand that the link is strongly positive (...)”.  difficult generalization. “there is a positive influence of research on teaching, and in other cases not; that students both appreciated and are sometimes irritated by staff engaging in research; that “some of the most inspiring teachers are able researchers, but not all; that some prominent researchers are good teachers, but not all” (rowland, 2000).  contract factor (actor and organization): teacher/research contract explain the effect of time spent on teaching on research. vidal i quintanilla (2000) show that “some aspects involved in teaching activities hinder good research. for instance, having to teach several different courses, huge groups of students, having many hours of teaching and also having an unfavourable teaching schedule, reduces the possibilities for research”.  disruption behaviours at heterogeneous scenarios: the evidence indicates the relationship between teaching and research may be more or less modestly positive depending to stage of academic career: “it is likely to be stronger at postgraduate than undergraduate levels” qamar (2004). drennan (1999) discovers that the match between research assessment exercise (rae) and teaching quality assessment (tqa) indices is strong for science subjects and weak for social sciences. “one of the biggest consequent problems is averaging scores across all departments of an institution, as drennan (1999) and drennan & beck (2001) do. (...) an institution could have high tqa scores for some departments but low rae scores and vice versa” qamar (2004).  the lack of significant information about quality: the subjectivity inherent tendentious valuation is included in a great number of assessment references for studies, reports or rankings. for instance: in the peer review process of the rae and in assessors’ evaluations in the tqa; for defining the international reputation in rankings like shanghai jiao tong university or world university ranking of the british times higher education; in the studies based in faculty and administration perceptions of neumann (1993) rowland (1996) smeby (1998) leslie et al. (1998); or in the student perceptions studies on the effects of lecturer research on learning of neumann (1994) jenkins et al. (1998) lindsay et al. (2002)  process time factor. a problem observed among some of the studies as faia (1976), noser et al. (1996), linsky & strauss (1975) is the calculation of the link between research and teaching measures that cover different time frames . the analysis of the sequence that goes from lt to r must include the lifetime measure output factor.  the multidimensional and complex object of the analysis could point out the preference in use of meta-analysis (the statistical integration of separate studies applied by feldman: 1987, allen: 1996, hattie & marsh: 1996). “a study by ellis (2001) finds a compelling match between english departments which scored highly on the rae and those who do well on the tqa. examining scottish universities drennan (1999) calculates that over 70% of the variation in means tqa scores can be explained by rae scores” qamar (2004). 20 o p i n i o n s e c t i o n  critical analytical problems. the conclusions from empirical evidence studies are conditioned by critical problems inherent in using the technique to gauge the relationship and the process to measure the linkage between research and teaching. in this sense, correlation studies like linsky & strauss (1975), faia (1976), centra (1983) kremer (1990 & 1991) hattie & marsh’s (1996) noser et al (1996). but, “though it is a measure of linear association between two variables correlation does not imply any cause and effect relationship. causal relations cannot be proved based on correlation coefficients” qamar (2004).  size range sequence. different results could be obtained depending on the analyzed range of the sequence (l-t-r or just t-r), the phase of the sequence (l-t or t-r); the order of sequence (r-t or tl). there is a singular link between research, teaching and learning excellence. “evidence suggests that students in subject areas with the highest research assessment scores are more positive about their learning experience than were students in subject areas with lower scores”. (surridge, p., 2008) the research interferences observed in the study of vidal i quintanilla (2000) come from entrepreneurship: “research collaboration with external institutions usually requires travelling and this affects teaching activities, and the most specialised research affects the most general and basic courses negatively. the setting-up of new programs increases the time required for teaching and in consequence decreases research activity. in the debate about the correlation between learning and teaching quality, another one with social and economic repercussions is involved. “the effects of teaching quality on wage growth are unclear and we are unable to conclude whether quality effects result in temporary or permanent increases in earnings”. however, “does it pay to attend a prestigious university? (chevalier, 2003)” some studies have analyzed the social impact of learning: “data released by the higher education statistics agency (hesa) shows that in 2006/07 on average 95.2% of first degree students from russell group universities had entered employment or further study within a year of graduating. this is 3.3% higher than the rest of the sector (not including russell group institutions) and a 0.4% increase on the russell group’s figures for 2005/06”. “nearly 80% of staff in leading grade departments are employed in russell group universities” (russell group, 2008) 3. entrepreneurship & education systems. initiatives to education system reform: europe and eua in europe, the overarching aim of the bologna process (understood as its original sorbonne declaration and the joint decisions made at various follow-up conferences held in bologna [1999], prague [2001], berlin [2003], bergen [2005], london [2007]) is to create a european higher education area (ehea) based on international cooperation and academic exchange, facilitating mobility of students, graduates and higher education staff and supporting their personal development; offer broad access to high-quality higher education, based on democratic principles and academic freedom. (bp, 2009) the main changes proposed in the bologna process, including legislative reforms and changes in the institutional structure (since 2007), increasing the autonomy and accountability of higher education institutions, diversification of heis, elimination of social and other barriers in access to tertiary education and possible transformation of existing tertiary professional education, which is governed by legislation on secondary education, into tertiary sector institutions (professionally oriented study programmes), emphasis on cooperation with employers, strengthening the responsibility of institutions and students for the quality of instruction, highlighting the role of lifelong learning, enhancing the quality of university research and, last but not least, a larger flow of financial resources into the tertiary sector” (bptnr, 2009) . “the overall aim is to improve the efficiency and effectiveness of higher education in europe. the bologna process spells out a number of “action lines” in which learning outcomes should play an important role (adam, 2004, 2006). the main consequences of the bologna process are: “qualification frameworks play a key role in developing the european higher education area” (qf_ehea, 2009) as “important instruments in achieving 21 o p i n i o n s e c t i o n comparability and transparency. qualification frameworks describe the qualifications of an education system and how they interlink. national qualification frameworks encompass all education qualifications – or all higher education qualifications in an education system. they describe what learners may be expected to know, understand and be able to do on the basis of a given qualification (learning outcomes) as well as how learners can move from one qualification to another within a system. qualification frameworks thus focus on outcomes as much as or more than procedures, and various learning paths – including lifelong learning”. (gallavara et al., 2008). “given that one of the main features of the bologna process is the need to improve the traditional ways of describing qualifications and qualification structures, all modules and programs in third level institutions throughout the european higher education area should be (re)written in terms of learning outcomes” kennedy et al. (2006). accreditation systems of programs: “one of the purposes of the bologna process is to encourage european cooperation in quality assurance of higher education with a view to developing comparable criteria and methodologies” (gallavara et al., 2008). in eua, the forum for the future of higher education´s annual symposium focused on assessment and accountability in higher education (cambridge, 2007) following the department of education’s commission report (2006) focuses on access, affordability, quality and accountability, came to the following conclusions related to he assessment: 1) “traditionally, institutional quality has been measured by inputs, largely in terms of financial resources and the academic qualifications of students prior to their enrolment”, but “improved accountability is vital to ensuring the success” “of academic programs and institutions to serve the changing educational needs of a knowledge economy”. in order to increase the quality in higher education, their managers “must become more transparent about cost, price, and student success outcomes and explicit in its analysis of outputs”. 2) providing timely and meaningful feedback loops on performance, efficiency and potential both to students, to teachers, to researchers, to innovation managers and to administrators at higher levels is a question of great importance on to transforming universities into kt and entrepreneurial organizations capable of using their experience to improve. 3) the concept of entrepreneurship applied to first mission activities means a structured set of scaffold assessment to identify and assess student and teacher progress and potential into use their knowledge, and also to promote their analytical, practical and creative skills and attitudes, to become society’s leaders. &. the specific goals of the bologna process also include the promoting of research in higher education and placing more attention on life-long learning as a basis for a competitive economy. following the spirit of bologna, international and national institutions have developed systems of quality learning, quality teaching and quality research. the bologna process has brought about actions to developing assessment and accreditation systems. 4. learning & teaching outcomes: assessment of and for learning and teaching: qualifications frameworks and portfolios the specific goals of the bologna process include promoting the student centred model, increasing the autonomy and accountability of universities, strengthening the responsibility of institutions for the quality of teaching, highlighting the excellence of learning, enhancing the quality of research and the transference of knowledge, as a basis for a competitive economy. from a teacher centred to a student centred model: stephen adam, university of westminster; following the bologna process spirit, the use of learning outcomes is intimately linked to the adoption of student-centred learning. learning outcomes are an integral part of an output-focused approach to teaching, learning and assessment. the role of the teacher moves towards being a facilitator/manager of the learning process. learning outcomes relate to external reference points (qualification descriptors, levels, level descriptors, subject benchmark statements) that constitute ‘new style’ qualification frameworks. 22 o p i n i o n s e c t i o n (adam, 2004; 2006) this alternative model focuses on what the students are expected to be able to do at the end of the module or program. hence, this approach is commonly referred to as an outcome-based approach. statements called intended learning outcomes, commonly shortened to learning outcomes, are used to express what is expected that students should be able to do at the end of the learning period” kennedy et al. (2006). in this context, portfolios represent “the beginning of a period of considerable change which will impact on the organisation of education and training systems, the forms of support for learning within society, the organisation of educational institutions and the development, organisation and delivery of curricula and programmes” (attwell, g., 2007). but: what are the learning and teaching dimensions that parameters portfolios must show in order to assure the quality of knowledge transference and the acquisition of analytical, practical and creative skills and attitudes? following the objectives of the bologna process, in the last few years, three trends have been promoted related to criteria, methodology and tools regarding assessment on higher education where portfolios have got a critical role:  assessment of learning and teaching. international and national institutions have developed indicator systems and agencies of quality learning, teaching and also research and transfer. encouraging european cooperation in quality assurance of higher education has produced a great development of comparable criteria and methodologies” (gallavara et al., 2008) involved in assessment and accreditation systems. internal selfevaluation and external review, conducted openly by independent specialists with international expertise are vital for enhancing quality (unesco, 1998).  assessment for learning and teaching. the overall aim of the bologna process is to improve systematically the efficiency and effectiveness of higher education in europe. the development of portfolios has been a “response to different pressures on the education and training systems: the implementation of e-portfolios impacts on the organisation and pedagogic approaches to teaching and learning”. (attwell, g., 2007) portfolios are a purposeful collection of work that illustrates efforts, progress, and achievements that provide a straightforward means for students to collect evidence of professional or generic graduate skills, and proprietary certification (cooper, 1999; cooper & love, 2000, 2001, 2002).  assessment-for applied to assessment-of. in the university context, the use of portfolios has been developed “as a tool for documenting personal and institutional achievements” (jokinen et al., 2009) setting consequently as a strategic function in the extended accountability of universities realizing the student centred model of the bologna process. barret and carney (2005) have been discussing about the conflict between constructivist (assessment for) and positivist paradigm (assessment of). nevertheless, “portfolios can serve both individual and institutional purposes” having two roles, personal, as a tool of self-development, or sample, as an extended curriculum vitae (jokinen et al., 2009). the bologna process spells out a number of “action lines” in which learning outcomes should play an important role. (adam, 2004, 2006) one of the logical consequences is that, by 2010, all programs and significant constituent elements of programs in third level institutions throughout the european higher education area should be based on the concept of learning outcomes, and that curriculum should be redesigned to reflect this” (kennedy et al. (2006). learning outcomes are statements of what a learner is expected to know, understand and/or be able to demonstrate after completion of a process of learning. (kennedy et al., 2006) the outcomes cover both cognitive (describe, explain, analyse etc.) and practical skills (work with others, present, write etc.). (adc–ltsn, 2009) “individuals and employers need to start measuring the outcomes, not just the outputs of training and learning – not ‘what did i learn?’ or ‘what accreditation have i gained?’ but ‘how have i improved the way i work?’” (simmonds, 2004) “the use of learning outcomes is intimately linked to the adoption of student-centred learning. learning outcomes are an integral part of output-focused approach to teaching, learning and assessment. the role of the teacher moves towards being a facilitator/manager of the learning process. learning outcomes relate to external reference points (qualifications descriptors, levels, level descriptors, subject 23 o p i n i o n s e c t i o n benchmark statements) that constitute ‘new style’ qualification frameworks (adam, 2004; 2006). qualifications frameworks also play a key role in developing the european higher education area as “important instruments in achieving comparability and transparency”. a qualification framework describes the qualifications of an education system and how they interlink” (gallavara et al., 2008). “it shows what a learner knows, understands and is able to do on the basis of a given qualification – that is, it shows the expected learning outcomes for a given qualification. it also shows how the various qualifications in the education or higher education system interact, that is how learners can move between qualifications. qualifications frameworks therefore focus on outcomes more than on procedures, and several learning paths – including those of lifelong learning – may lead to a given qualification” (qf_ehea, 2009). 5. form, categories of learning and teaching procedures and moments of assessment: parameters of learning and teaching portfolios the portfolios are now becoming essential tools for personal development planning (pdp), managing continuous professional development (cpd), gaining accreditation for prior learning (apl) and career management. “it is possible to distinguish between three broad approaches: the use of eportfolios as an assessment tool, the use of eportfolios as a tool for professional or career development planning (cdp), and a wider understanding of e-portfolios as a tool for active learning”. (attwell, g., 2007) “competency-based university education, in which lifelong learning and flexible learning are key elements, demands a renewed vision on assessment. within this vision, assessment of prior learning (apl), in which learners have to show their prior learning in order for their goals to be recognised, becomes an important element” (joosten-ten brinke et al. 2009). learning involves “the acquisition of competencies, understanding, knowledge, or skills, anytime and anywhere” (livingstone, 2001) and “goes far beyond this formal learning. non-formal and informal learning are two other important categories of learning that deserve more attention within the formal education system” (joosten-ten brinke et al. 2009, colardyn and bjornavold, 2004). “non-formal learning is not legally or socially recorded” and there isn’t any certification involved, while informal learning comes from life experiences (joosten-ten brinke, 2009). “it should not matter how something is learned exclusively, but it matters what is learned in relation to further personal development (spencer et al., 2000l; joosten-ten brinke et al. 2009) conclusions the quality in higher education is a multidimensional concept, which should embrace all its possibilities as an object, by means of a correlated analysis where portfolios could be used to convey and provide online, timely and meaningful information: for learning and teaching about knowledge, skills, attitude and competences, implemented on activity related to contents, works, practices or experience, on categories of formal, non-formal and in-formal processes, of learning, teaching and academic management, by means of the evidence of inputs, outputs, outcomes, and knowledge transfer processes, to assessment of different actors and levels such as national, institution, department, teacher, learner, in term of performance, efficiency and potential, at every moment, prior, during or postprocess of learning-teaching. 24 o p i n i o n s e c t i o n table 1: analytical parameters of learning and teaching objective activity categories process element level analysis moment knowledge content formal learning input national performance prior skills work no-formal teaching output institution efficiency during attitude practices in-formal management outcome department potential post competences experience process teacher learner table 2: analytical parameters of learning and teaching references adam, s. 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(2020) interpreting, analyzing and distributing information: a big data framework for competitive intelligence. journal of intelligence studies in business. 11 (1) 6-18. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 1 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index interpreting, analyzing and distributing information: a big data framework for competitive intelligence eduardo luis casarottoa,*, guilherme cunha malafaiab, marta pagán martínezc, and erlaine binottoa auniversidade federal da grande dourados, brazil; bempresa brasileira de pesquisa agropecuária, campo grande, brazil; cuniversidade federal de são carlos, são carlos, brazil * eduardocasarotto@ufgd.edu.br journal of intelligence studies in business please scroll down for article interpreting, analyzing and distributing information: a big data framework for competitive intelligence eduardo luis casarottoa,*, guilherme cunha malafaiab, marta pagán martínezc, and erlaine binottoa auniversidade federal da grande dourados, brazil; bempresa brasileira de pesquisa agropecuária, campo grande, brazil; cuniversidade federal de são carlos, são carlos, brazil *corresponding author: eduardocasarotto@ufgd.edu.br received 28 february 2021 accepted 29 march 2021 abstract this paper aimed to develop a data-based technological innovation framework focused on the competitive intelligence process. technological innovations increasingly transform the behavior of societies, affecting all sectors. solutions such as cloud computing, the internet of things, and artificial intelligence provide and benefit from a vast generation of data: large data sets called big data. the use of new technologies in all sectors increases in the face of such innovation and technological mechanisms of management. we advocated that the use of big data and the competitive intelligence process could help generate or maintain a competitive advantage for organizations. we based the proposition of our framework on the concepts of big data and competitive intelligence. our proposal is a theoretical framework for use in the collection, treatment, and distribution of information directed to strategic decision-makers. its systematized architecture allows the integration of processes that generate information for decision making. keywords big data, competitive intelligence, technological innovation 1. introduction innovation in its complexity adopts new social and organizational technologies as main components. the concept of "innovation" is defined as product and process technological innovation (ppt) in the 1992 and 1997 editions of the oslo manual, with technology being considered one of the steps leading to its implementation. since the third edition of the manual in 2005, with the inclusion of the service sector, the term "technological" has been removed from the definitions of innovation as companies in the service sector could mistakenly interpret it as "using hightech facilities and equipment" (oecd, 2005, p. 17). even if the term "technological" is no longer part of the innovation concept, the interpretation makes it explicit that all innovation, in essence, is already technological (oecd, 2005). innovation is commonly associated with computer elements (hardware and software) that have capabilities to generate, store, process, and distribute data in large volumes, called big data. its use can contribute to the discovery of new opportunities in corporative technological innovation (li, zhang & hu, 2017). data based technological innovation proves to be a process of change in the environment and management in organizations, especially if used together with the competitive intelligence process. competitive intelligence has been practiced along with the other support functions in companies because it brings appreciated value to the decision-maker (vuori, 2011). it is a vital journal of intelligence studies in business vol. 11, no. 1 (2021) pp. 6-18 open access: freely available at: https://ojs.hh.se/ 7 component of the planning and strategic management process, gathering data and information in a broad strategic vision context that allows the forecasting or projection of events in its competitive environment (bose, 2008). the context of the study involves the dynamics of technological innovations, those based on data (big data), and the need for efficient and safe use of the large volume of data generated in the environments of organizations. we also observed ethical components of safety and reliability when building business models (wolfert, ge, verdouw & bogaardt, 2017). the objective of this paper is to propose a framework for an integrated process of big data intelligence in organizations. previous studies discussed and highlighted big data and competitive intelligence approaches together, for example hughes (2017); calof, richards and santilli (2017); rothberg and erickson (2017); vajjhala and strang (2017); erickson and rothberg (2016); shi, lee and whinston (2016); wei et al. (2016); bruneau and frion (2015) and erickson and rothberg (2013). zhang et al. (2020) developed a bibliometric review about big data in business research and they suggested that researchers pay more attention to research topics such as decision making to leverage experience from the information management field to offer practitioners improvements in big data research and applications. another suggestion is to make advancements in studies with big data relating to research and the field of business using interdisciplinary integration. our study brings innovation from a theoretical perspective by addressing an emerging theme as a new digital paradigm (urbinati, bogers, chiesa & frattini, 2019). in this paradigm, companies generate value by digitizing their services and products, and the consequent analysis of media contents becomes a key success factor in the big data environment (jimenez-marquez, gonzalezcarrasco, lopez-cuadrado & ruiz-mezcua, 2019). hence, our study can spur analysts and researchers to develop tools that enable the capture, processing, and analysis of data, turning this data into actionable intelligence for decision-makers. organizations have different degrees of complexity, especially in relation to technological articulation and intensity. additionally, having plenty of databases does not necessarily fit into the "big data" concept. the framework has been developed in two stages. in the first stage, we explored the literature in order to identify the framework's structuring theories. these are big data and competitive intelligence and their relationships with technological innovation and strategic management elements. these are widely used in research in the area, resulting in knowledge management, organizational performance management, marketing strategies, production strategies, organizational processes, decision making, and the organization's resources and capabilities. in the second stage, we propose a framework, its theoretical basis, as well as its application. 2. theoretical background 2.1 2.1. big data information and communication technologies have provided, through evolution and application, huge impacts on society and the economy, especially in the last three decades. the changes provided by the adoption of these technologies are evident and continue to present opportunities and challenges, such as in the case of big data (sonka, 2014). big data has been described in different ways throughout its development and consolidation. the apache hadoop platform defined it in 2010 as "datasets which could not be captured, managed, and processed by general computers within an acceptable scope." (chen, mao & liu, 2014, p. 173). mckinsey & company describes big data as the next frontier for innovation, competition, and productivity (manyika et al., 2011). a comparative study by the international data corporation (idc) descfibe it as "a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high-velocity capture, discovery, and/or analysis." (gantz & reinsel, 2011, p. 6). other authors have considered it to be "a set of techniques and technologies that require new forms of integration to uncover large hidden values from large datasets that are diverse, complex, and of a massive scale." (hashem et al., 2015, p. 100). from a managerial perspective, it is relevant to highlight that big data provides managers with access to information and generates subsidies to the ability of decision making (sonka, 2014). the promise and value 8 of big data go far beyond what is known, and have limitations only in their capabilities and human resources. according to the idc definition, the characteristics of big data may be described by the 4vs (volume, variety, velocity, and value) which are also used by hashem et al. (2015), sonka (2014), and gomes and braga (2017). the classification into five aspects to better understand the 4vs is significant because of the large-scale data in the cloud. these are data sources, content format, data storage, data preparation, and data processing (hashem et al., 2015). such characteristics and classification allow us to consider big data as an innovation, because it meets the definitions proposed by freeman, clark and soete (1982), senge (1997), and o'sullivan and dooley (2008). they introduce a new way of generating, processing, and making information available so it can be replicated infinitely at acceptable costs and can be exploited for both personal and organizational benefit to add value. the advent of big data establishes itself as a development of technological innovation relating to other innovations such as cloud computing and the internet of things (iot). with the first one, this is because the development of cloud computing offers solutions for the storage and processing of massive volume data sets. with iot, this is because they are two interdependent technologies that must be developed together since the dissemination of iot leverages the growth of data by categories and quantities, allowing the application and development of data (chen, mao & liu, 2014). we have added this relationship to artificial intelligence, as it also deals with increasing volume, velocity, and variety of data, allowing the delegation of hard recognition and learning patterns and other tasks to computer-based approaches (o'leary, 2013). we highlight that the context of big data and related technologies bring with them the uncertainties of security, or insecurity, on the part of the agents and especially individuals when they make their data available and maintain, in some way, some or all control over its use (tene & polonetsky, 2012). compliance with legal principles can be a detriment to competitiveness since it can generate a competitive advantage or disadvantage depending on the mode of use and attention to them. it can be detrimental if a company or institution does not accommodate the legal environment that extends beyond the limits of a given territory. 2.2 competitive intelligence the definition of competitive intelligence encompasses two vital concepts for the business environment. first is the meaning of "competitive", which refers to processes that involve competition between at least two agents. second is the concept of "corporate intelligence", defined as an ability to predict possible changes in a future temporal universe and prepare for an intervention, a process in which the parties use the operating environment to collect data, information, or knowledge in decision making and then implement actions (breakspear, 2013; köseoglu, ross & okumus, 2016). the competitive intelligence concept has been studied in the field of management in several areas of strategic administration, and it is common to use other names that sometimes cause confusion between the terms. the majority of them occur in relation to the distinction of the competitive intelligence business. many uses these terms as synonyms, linking business intelligence to the information technology companies and describing it as the set of tools that allow the generation of information in business environments such as data warehouses, data mining, crm, and olap tools, among others (abraic, 2012). competitive intelligence refers to a broader process, encompassing the obtaining and processing of information that comes from networks maintained by competitive intelligence systems in which the business intelligence information is inserted (abraic, 2012). considering competitive intelligence as a process and a product at the same time has its roots in the assumption that the more one understands the strengths and weaknesses of competitors, the better the conditions to formulate an effective strategy are. competitive intelligence is, first, an analytical process of transforming disaggregated data into usable strategic knowledge about competitors' intentions, capabilities, performance, and positioning; and, second, a result of this process as a final product (bernhardt, 1994). the competitive intelligence process results in information that generates recommendations for future events, in addition to reports that justify past decisions in decision making (gomes & braga, 2017). in the search 9 for information in the competitive environment, companies may not find clear answers to develop their strategies. for the correct articulation of competitive intelligence activities, the united states central intelligence agency (cia) described a cyclical process of five interdependent phases: planning and direction, collection, processing, analysis, and production and dissemination (bernhardt, 1994). competitive intelligence is both a process and a product (intelligence) (bernhardt, 1994). an effective competitive intelligence process, supported by the society of competitive intelligence professionals (scip), is executed in a continuous cycle, called the competitive intelligence cycle. the cycle is a process in which information is collected, evaluated, analyzed, processed, and made available as intelligence for use in decision making, consisting of planning and direction, collection, analysis, dissemination, and feedback (bose, 2008). this cycle is an update of bernhardt's (1994) initial model, in which processing, analysis, and production are all grouped in phase three (analysis), phase four includes distribution, and finally, insertion of feedback is found in phase five. previously, bose (2008), calof, and dishman (2002) presented a five-phase model for competitive intelligence, in which the fifth phase consists of decision making. the difference between the models demonstrated by calof and dishman (2002) and bose (2008) is only semantic if only phases one to four are considered. however, phase five differs, as calof and dishman (2002) defines phase five as decision making, while bose (2008), defines it as feedback. however, this difference can be mitigated by considering that the decisionmaking process results in feedback to the competitive intelligence system. in this way, it can be considered that both process are included in the same phase. besides the five-stage models proposed by bernhardt (1994a), calof and dishman (2002), and bose (2008), fleisher (2004) and brummer, badenhorst, and neuland (2006) presented a four-stage model. moreover, de pelsmacker et al. (2005) and nasri (2011) have outlined processes with six stages: planning and focus, collection, analysis, communication, process/structure, and organizational awareness/culture. keiser's previous study (1987) presented a six-stage model, consisting of the definition of rivals, data that better define them, specific sources to be researched, classification of these sources and delimitation of a cooperation strategy in the information collection, blending and analysis of the information, and monitoring of the rivals according to the results coming from the information sources (köseoglu, ross & okumus, 2016). köseoglu, ross, and okumus (2016) used contributions from brummer, badenhorst, and neuland (2006) by inserting four elements to support the construction of the process in the planning and steering stage of the bernhardt (1994) model. these include intelligence users and decision-makers, other users, data needs, and the key intelligence topics (kits), developed by herring (1999). we chose the figure 1 big data intelligence integrated process (bdiip). 10 model proposed by köseoglu, ross, and okumus (2016) to serve as a reference for our framework proposal. 3. framework proposal our proposal is presented in two parts. the first, the big data intelligence integrated process (bdiip, figure 1), is based on the competitive intelligence cycle of bose (2008), however, in the fifth phase we also consider the decision-making suggested by calof and dishman (2002), the characteristics of big data (4vs) of chen, mao and liu (2014), and we include variables of brummer, badenhorst, and neuland (2006) later adopted by köseoglu, ross and okumus (2016). in the second part, we present the big data intelligence framework bdif (figure 2), based on the theoretical interpretation of bdiip. our framework is supported by five points of interest essential for its definition: 1) who are the actors that effectively are the potential targets, influencers, and/or decision-makers to define the profile and market positioning?, 2) what is the real need for data?, 3) definition of the key-topics for searching, 4) what are the main generating sources and which kinds of data should be mined from the ones available?, and 5) definition of a big data intelligent searching cycle from the key-elements of the competitive intelligence cycle, validated by the elements characterized as big data (4v). subsequently, each of these points will be contextualized. additionally, the big data tools allow the analysis itself to identify the relevant descriptors in the information. 1) main potential targets, influencers, and/or decision-makers and 2) data needs: first, as a characteristic of big data, the large volume of data is often presented in different ways for the same purpose. as such, redundancy and the noise level are problems that must be followed-up and minimized to improve data performance. such characteristics are, for example, enhanced by the structure of data in relational databases and also by data generated via iot (chen, mao & liu, 2014; hashem et al., 2015). as well as prior knowledge of the types of data required, knowing the users, or clearly defining them, is a key-point in the search for the information needed for the intelligence process (bose, 2008). this is fundamental for planning the process of collecting and analyzing data to convert them into useful information (oliveira, 2013). within the competitive intelligence process, the users of the information need to be previously known and defined, as this is essentially an internal process. in practice, we suggested using big data to identify the decision-makers, users, or influencers in a given business environment and what kind of information is used or figure 2 big data intelligence framework (bdif). 11 disseminated by them, in the environment outside the organization. 3) definition of key topics for searching: key intelligence topics (kits) are used to improve the planning of competitive intelligence process activities. these topics have been previously defined by intelligence users and analysts, and segmented into three functional categories: strategic decisions and actions, early warning topics, and description of the main competitors in the business environment (herring, 1999). in the traditional competitive intelligence process, the identification of the topics related to the main competitors and market conditions is the last stage of the definition. however, in the process that we propose, it will be used as the main instrument to identify opportunities and risks in an environment and, from this information, start the generation of the intelligence process based on big data. we suggest big data tools to monitor the market, reversing the definition of the main topic processes by the users for big data analysis, mainly using unstructured data. this includes, for example, data analysis or text mining. 4) generating sources and data availability: data sources may be classified as social media, machine-generated, detection, transactional data, and iot (hashem et al., 2015). the different source availability provided by the big data environment allows a vast range of searches. however, unstructured data represents a great challenge, since in some cases this type of data does not undergo a prior evaluation as to its authenticity and validity. these are subject to a lack of veracity or credibility. this is unlike structured data from official or better-known databases, which may contain errors, distortions, or lack updates, yet is still in some way "certified" by the publishers. we propose that operationalization in an autonomous way verifies the ethical and legal veracity and viability of the use of this data. that certifies or minimizes the choice of the bases since the ownership and privacy in the universe of big data represent a big challenge. however, many of these challenges have their origins in technical issues and are based on the legislation and organizational aspects that can be met by technical measures, a prerequisite that allows analysis without binding the user's identity (jensen, 2013). 5) valuation of the big data intelligent searching cycle: valuation occurs from the keyelements of the competitive intelligence cycle, its final evaluation, and verification of the principles of collection, treatment, and distribution of data and information. by meeting ethical standards of privacy, use, and tenure rights, they consider the definition of competitive intelligence as a systematic and continuous business process to collect, ethically and legally, information about targets in the business environment (shaker & gembicki, 1999) and mainly disconnected from the association to corporate espionage. ethical and moral conduct is a significant part of the strategic process (köseoglu, ross & okumus, 2016) and also is essential to meet the ethical demands on the asymmetry of power concerning the domain of information between users and large corporations. the validation done by attributing values such as trust and transparency gives credibility to the use of the tool in the generation of knowledge and intelligence (carbonell, 2016). so far, the searching process integrates the concepts and principles of competitive intelligence and big data, particularly regarding the searching, processing, and transformation of data into actionable information. in certain aspects, it is similar to processes already used for obtaining and producing information. for this purpose, the tenet for using it takes into consideration the tasks of the process, integrated within a broader context, such as in laboratories, centers, or information production and distribution cores. in organizations, the big data intelligence integrated process (bdiip) may be used as an operationalization structure for data/information capturing, storing, processing, and distribution in intelligence operational centers. it is not a closed-system process, but a cluster of processes with integrated operation platforms for adding value to available data and/or produced for specific analysis originating from several interfaces that possibly require analysis and operation with diverse resources and knowledge. it is also an organic framework susceptible to inferences and interference according to the needs of the organization at a given time. the framework is based on the management area, defined as strategic management elements, and contextualized in knowledge management, organizational performance management, marketing strategies, production strategies, organizational processes, resources and 12 capabilities of the organization, and decision making. given their characteristics, we consider that the elements are not static as they can move to a multidisciplinary scope, adding other factors and subjects to meet a determined demand such as the price analysis of a given product, in a business environment, by the production or marketing strategic vision linked to explanatory or predictive statistical analysis. the process explores the main characteristics of big data defined as the 4vs presented and discussed by chen, mao and liu (2014) and the elements of the competitive intelligence cycle proposed by bose (2008) and calof and dishman (2002), which allowed the development of the big data intelligence framework (bdif; figure 2). our proposal has resulted in the construction of the big data intelligence integrated process (bdiip; figure 1) considering the following fundamentals, as presented in figure 2: 1) intelligent search: contemplates phase 1 with planning and direction of the competitive intelligence cycle, according to bose (2008). in this phase, the pre-phase elements were adapted from köseoglu, ross, and okumus (2016) to the bdiip (figure 1). they consist of targets, influencers, decision-makers, data needs, key-topics of searching (herring, 1999), and generating sources of data. in order to sustain and improve the decision-making process, it is necessary to fit it into a relevant strategic context for the business to be able to answer essential questions (bernhardt, 1994; oliveira, 2013). that is the data search for effective planning in the big data universe, whereas the objectives are determined, and it is defined which methodology to seek. the integrated process differs from the competitive intelligence process as it can meet several demands simultaneously or one problem in several ways, while competitive intelligence focuses on one problem at a time. this stage of the framework does not contemplate big data that is only about definitions which may or may not be executed in large databases. 2) strategic elements of management: these are also part of phase 1 of competitive intelligence. they consist of the disciplinary filter of the search process since the use of big data or its analysis can be an instrument for maintenance or generation of advantage. this filter should preferably be applied and integrated into the search engine so that the results are objective and targeted. however, it can be applied manually a posteriori, which means the analyst applies the filter according to the interest or need after data collection. the definitions of strategic elements of management may be adapted accordingly to specific needs. the adoption of the term "strategic elements of management" is only a representation used to define this phase that does not restrict a broader use of content, practices, and processes in the management area that can lead to the development of a specific project, and can be replaced by emerging theories and new holistic proposals. 3) big data universe and related technologies: these include cloud computing, iot, artificial intelligence, and other new technologies that emerge in this scenario. this phase covers the foundations of big data and all the complexity of the very definition of the term big data with its characteristics, classification, and challenges. this includes, for example, the adequacy of researchers and entities to follow data protection laws. in this stage of the framework, there are three characteristic elements of big data: volume, variety, and velocity defined by hashem et al. (2015), sonka (2014), and gomes and braga (2017). this is in addition to the classifications of data sources (social media, machinegenerated, detection, transactional data, and sensorization) and format and content (structured, semi-structured and unstructured) (hashem et al., 2015). the volume refers to the enormous amount of data generated in large databases and media almost instantly, allowing the use of data-mining to identify sources of intelligence generation. the dedicated data, such as sensor measurements (iot) and the use of artificial intelligence, are in the early stages but with future potential for integrated use. variety deals with different types of collected data that include video, image, text, audio, and structured or unstructured data. as a dimension of big data, it deals with the concept of data that expand into different formats. velocity represents the ability to generate data in real-time and rapid dissemination (hashem et al., 2015). the velocity has a significant impact on the performance of business innovation actions, as it is necessary to quickly integrate different types of data in a timely manner to generate efficiency and effectiveness in the process (ghasemaghaei & calic, 2020). 4) collection and storage: we contemplate phase 2 of the competitive intelligence cycle 13 (bose, 2008) and the variety of characteristics and the volume of big data. this also meets the need for "data storage" classification and its tasks: documentation, guidance, graph, and value. these are forms of data preparation: cleaning, normalization, and transformation (hashem et al., 2015). 5) analysis: this contemplates phase 3 of competitive intelligence and the value characteristic of big data. it refers to the process of discovering the hidden values of large data sets with various types and fast generation (hashem et al., 2015). although the presence of volume and variety characteristics are inherent, the value designation begins to be reasoned on the quality of the data analysis. for this, they rely on the use of competitive intelligence analysis techniques, business intelligence, and big data analysis, as well as supporting tools for decision making. at this stage, the analyst's expertise improves the use of this tool and the generation of results. depending on the project and, especially, the way the results are disseminated, this is the last stage of big data. the probability is that the information for decision making is passed on even if using data in a way that could not be considered big data conceptually, only data transmitting the information. the distribution of this information, in competitive intelligence publications, is approached as the idea of producing actionable intelligence, with the primary role of modeling and influencing strategic thinking by interlocution between analysts and management (gilad, 2016). 6) distribution: this contemplates phase 4 (distribution) of bose's intelligence cycle (2008). it follows the same pattern of information distribution as competitive intelligence, which means information is disseminated directly to interest groups through publications, meetings, lectures, and field activities, among other traditional forms. however, an organization's intelligence department may also adhere to the use of platforms and applications to increase the interaction and use of information. depending on the application architecture, it may or may not be considered big data. 7) decision: the final phase of the competitive intelligence cycle. the information, once made available, may or may not be used in decision making. in this phase, the involvement of intelligence analysts with other organizations’ members will be decisive in adding value to the competitive intelligence process as a whole, as well as in directing the actions of the organization. all members' interactions can be measured through feedback, which will also serve as inputs for the re-start of the intelligence process. 8) description of big data characteristics: according to hashem et al. (2015) and other previously cited authors. 9) description of the competitive intelligence cycle: according to bose (2008), calof and dishman (2002) and other previously cited authors. 10) validation or valuation: the final step of the framework measures the utility of the process for decision making. we consider "value" to be interpreted as "veracity" (gomes & braga, 2017), unlike the "v" value in big data. the process, understood as a cycle, has its beginning for a question-less purpose or analysis in which many factors and resources (human, financial, temporal, and technological) were committed for the benefit of the project. the final characteristic of the information generated should be measured by its capacity to enable better decision making. the higher the quality or veracity, the greater the value of the process. the metrics for this evaluation should be defined in each project in phase 1 of the competitive intelligence cycle. the returns may also be gauges of the quality of the actionable information developed by the organization's intelligence department. 4. discussion we understand that big data, through new technologies such as social media and iot, enables organizations to develop innovative business models and products considering three dimensions for decision making and gaining advantages: creative use of technology and big data, unlocking innovation through collaboration and co-creation, and sustainability agendas (nudurupati, tebboune & hardman, 2016). using big data together with the organization's capabilities and resources can lead to advantages in the business environment. the importance of human skills and intangible resources associated with learning and organizational culture creates a specific capacity for the corporation. perhaps it is unlikely that big data alone can generate or maintain any advantage for the organization (gupta & george, 2016). big data can be considered a new element capable of producing competitive differentials, provided it is handled with intelligence and adequate tools, observing its characteristics of 14 velocity and variety. however, the generation of massive data volume, variety, and velocity does not guarantee the best decision-making or obtaining any advantage, and for this, it is necessary to extract its most fundamental characteristic in the process: the value generation. big data provides the opportunity to collect and integrate various datasets for the identification and extraction of information used to improve decision making (ayankoya, greyling & calitz, 2016). for organizational goals to be achieved, using big data is important to understand how each of its characteristics affect the results to allocate them in the best way. this is a key task to improve performance (ghasemaghaei & calic, 2020). we highlight that the universe of big data associated with cloud computing, iot, and artificial intelligence transforms management systems. however, having a large volume of data does not necessarily guarantee that you have the right information at the right time. big data, combined with sophisticated business analysis tools, has the potential to provide companies with insights into customer and market behavior, enabling faster and more effective data-driven decision making (kelly, 2014). therefore, the introduction of competitive intelligence works as a strategic tool to manage and process raw information and turn it into useful information at the right time, targeting the decision-maker. the adoption of intelligence in the big data strategic processes changes the environment because the adoption of competitive intelligence tools such as business intelligence and big data analytics streamlines actions, interpretation, and the consequent generation of information in the form of actionable intelligence. special attention should be given to the fact that the speed of changes, uncertainties, and complexity of competitive environments impose on analysts and decision-makers a pressure for assertiveness, reinforcing the importance of adopting competitive intelligence as a flexible and adaptable approach (mohammadalian, nazemi & tarokh, 2013). the developed framework considers the interactions of human resources and their capabilities for interpretation, analysis, and distribution of information in the form of intelligence. it was developed to be used in the core of organizational intelligence, which uses the business intelligence resources and expertise of its researchers and analysts. this conception is justified because "big organizations have implemented big data adoption and development for business value creations through the result of big data analytics applications" (adrian, abdullah, atan & jusoh, 2016, p. 174). organizations with different purposes and large corporations can help the members of the decision-making process with information without requiring an economic counterpart. we understand that big data, associated with an intelligence process, is a source of some advantage. however, there is a need to combine people, tools, management, dataoriented culture development, and human skills to obtain this advantage (kabir & carayannis, 2013). we also emphasize that by adopting advanced analysis technologies, organizations can make use of essential data for the development of innovative insights into products and services (günther et al., 2017). we reinforce the adoption of new technologies as a process given the need to prepare data capture and processing architectures, as well as the time needed to generate databases that represent big data in its essence. however, as the framework allows for interaction and fragmentation, such fragments can be executed in the form of specific projects for information analysis and process execution sharing. the adoption of new technologies allows the use of partners to perform tasks that are beyond the physical and technical capacity of the organization. the framework grants interactions between companies and analyst partners for the production of information that can be disseminated in order to generate better results and extract value from the data and the process that allows better decision making. 5. final considerations, remarks, and limitations the huge development in technological innovations influences and transforms social and commercial relationships and significantly alters productive environments. this context served as a premise for our proposal. we started from one which, using large data sets (big data) together with the competitive intelligence process, can improve decision making and, consequently, maintain, or generate some advantage for organizations. our study brings contributions and innovations when considering the use of big data integrated into the theory of competitive 15 intelligence. it presents the ability to generate information for the decision-making process from the use of new technologies for data generation, storage, and integration. our proposal of the big data intelligence framework (bdif) demonstrates the capacity of data collection in the processing and distribution of information that can be used as a reference for the systematic construction of intelligence cores. as limitations of the proposal, we recognize that an intelligence core alone may not be able to generate all the data to produce the necessary knowledge to be made available, as well as for the transmission of information. it is essential to build cooperative relationships through commercial or other partnerships. for future research, we propose implementing bdif for the formation of the intelligence core in organizations or other interest groups. further, the continuity of tests with the practical and theoretical application of the big data intelligence integrated process (bdiip), developing targeted studies is possible. we also highlight, in relation to the practical application, the possibility of developing integrated field tools to initialize the use of the framework and disseminate the content appropriately at the right time, as well as new studies for the proposition and realization of value. finally, we considered that the generation of information for the intelligence process, with the ability to create a variety of advantages for the organization through technological innovations such as big data, starts from the premise that human capacity has to define the types of data, making the human capacity the defining factor of information quality (human perception of value). the whole process of generating knowledge is the result of an algorithmic reaction, or a succession of steps, including emotional components, that lead to a determined final result. 6. references abraic. associação brasileira dos analistas de inteligência competitiva. 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(2020). a bibliometric review of a decade of research: big data in business research-setting a research agenda. journal of business research. online available at: https://www.sciencedirect.ez50.periodicos.cap es.gov.br/science/article/pii/s01482963203074 75. accessed december 2, 2020. 5 benchmarking competitive intelligence activity helen n. rothberg 1 and g. scott erickson 2 1 marist college, poughkeepsie, usa hnrothberg@aol.com 2 ithaca college, ithaca, usa gerickson@ithaca.edu abstract: this paper reports on results drawn from a comprehensive database formed from public financial reports and a proprietary benchmarking survey conducted by a major competitive intelligence consulting firm. our overall aim is to identify different circumstances in which knowledge development and knowledge protection have greater or lesser importance. very little work has been done on a industry-wide (or wider) basis concerning intellectual capital and/or competitive intelligence activities in firms and how that may vary according to circumstances. the wider study and database are designed to better address such questions. in this study, we look at one piece of this overall research program, specifically how competitive intelligence activity varies in distinctive environments. based on these results, as practitioners better understand their environments, they can make better decisions on the level and aggressiveness of their own ci operations as well as on protection and counterintelligence efforts. the results will also begin to move scholarly work in the field into these new areas of macro studies and strategic choices. keywords: competitive intelligence, knowledge management, competitive capital 1. background competitive intelligence (ci) is a field drawing increasing interest from scholars, both on its own merits and as an important piece of a firm’s knowledge assets. much of the standard knowledge management (km) and intellectual capital (ic) theory applies directly to ci as it focuses on a specific type of knowledge, that concerning competitors, but ci also has its own theory and practice, going beyond the standard km/ic concepts, most notably within its specialized gathering and processing techniques. in past work, the connection between ci and km/ic has been explored, particularly how competitive knowledge is an additional valuable intangible asset, beyond the standard theoretical constructs of human, structural, and relational capital (bontis 1999, edvinsson & sullivan 1996). in addition, however, ci adds to the discussion by emphasizing the importance of data and information as valuable precursors to knowledge. ci operations can often obtain pieces of data and information that can be turned into knowledge proper with appropriate analytical processing— available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2012) 5-11 https://ojs.hh.se/ 6 what we’ve termed competitive capital in another context (rothberg & erickson 2002). further, ci starkly demonstrates the need for security as the knowledge valuable to one party is often likely to be similarly valuable to its competitor(s) (rothberg & erickson 2005). as such, ci is appropriate as a topic in the study of knowledge assets, providing a different perspective and deeper insights beyond the standard fare of the discipline. by better understanding how ci works and its best practices, we are able to add also to our knowledge concerning km in general. this alternative point-of-view has the potential to add deep insights as we move beyond the standard ways of assessing and managing organizational knowledge. competitive intelligence, in much the way km/ic did, grew first out of practice (gilad & herring 1996; fuld 1994). while there is something of a scholarly trail before ci was recognized in the late eighties and early nineties, the discipline as we know it really grew out of observing what was happening in industry. competitor analysis at the cursory level was giving way to more formal, complete, and innovative methods of uncovering information concerning one’s competitors and turning that, through appropriate analysis, into knowledge and actionable intelligence. the methods are now well-enough developed to merit textbook-like treatment (fleisher & bensoussan 2002). basically, ci practice includes a scanning function (public information and other sources, including heavy use of the internet), human intelligence, and more active gathering techniques (mcgonagle & vella 2002; prescott & miller 2001). from the resulting information and knowledge, ci practitioners seek to glean competitive strategies and actions, anticipating and countering those moves threatening their firms (gilad 2003; bernhardt 1993). competencies range from pure library functions to highly competent, seasoned analytical teams (wright, picton & callow 2002; rouach & santi 2001). the basic structure of most ci operations is a mix of data, information, and knowledge-gathering processes with analytical tools and techniques. as just noted, sometimes the information assetgathering is from secondary sources. in other, usually more sophisticated operations, the sources can be primary, human intelligence or from purpose-driven active gathering. tools for analyzing the information assets range from environmental scanning to war games. other differences in operations can include reporting topics (project-driven or ongoing operations), size and make-up (internal or external) of the ci team, reporting level (c-suite, dispersed), and budget. as we’ll discuss, our overall research program is aimed at understanding how and why these differences exist and whether certain ci operations are better for certain circumstances. in a wider context, in past work, we’ve looked at how firms vary their knowledge strategies (both development, as with km and ic and protection/competitive analysis, as with ci) according to circumstances. essentially there are differences in the degree to which firms invest in identifying and growing knowledge assets, and there are also differences in the threat posed by competitors in appropriating these assets through ci. the firms themselves may also employ ci to a greater or lesser degree. much of our scholarship has been focused on the how and why. if you can identify circumstances, industries, and firms that aggressively develop knowledge (or not) and that aggressively pursue competitive intelligence (or not), then we begin to get a better sense of the strategic implications for each. in this paper, we’ll report on competitive intelligence practice in two very different scenarios. in one, situation, knowledge is extremely important for competitiveness, so both the creating firm and its competitors are quite interested in the proprietary knowledge and in using it for competitive advantage. we’ll refer to this as a high-value knowledge scenario. alternatively, we also look at a situation, wherein knowledge is apparently not particularly useful to the originating firm nor to its competitors. this will be the lowvalue knowledge situation. we’ll elaborate on each situation a bit more in the discussion and then look specifically at how firms in each scenario conduct their ci operations, if they exist at all. from this analysis, we should be able to help guide ci investment and practice for firms facing different competitive environments. 2. strategic protection factor (spf) framework and the fuld & company database we have previously developed and analyzed a framework describing four different scenarios concerning knowledge development and knowledge protection, two aspects of km that are seemingly in some conflict with one another (erickson & rothberg 2012, rothberg & erickson 2005). at its simplest level, the more knowledge is developed and spread throughout an organization and its network partners, the more vulnerable it is to competitor capture. the natural conclusion is that knowledge is valuable to both its originator and to potential competitors. 7 our research, however, indicates that this view is too simplistic. while valuable knowledge is something firms want to leverage through distribution, not all firms possess valuable knowledge and not all valuable knowledge is relevant or transferable to competitors. there are a number of potential reasons for this state of affairs, too lengthy to go into here in any detail, but most are familiar to those in the km field (tacitness, complexity, specificity) or those with a background in strategy (life cycle, value chain, etc.). these conceptual ideas can be backed up by in-depth quantitative support, demonstrating knowledge that is valuable in an industry (or not) and of apparent interest to competitors (or not) (erickson & rothberg 2012). these two variables yield four potential states of affairs, as with any two-by-two matrix, that we have characterized as the strategic protection factor (spf) framework. in short, these break down as:  spf 45: high levels of km, high levels of ci  spf 30: low levels of km, high levels of ci  spf 15: high levels of km, low levels of ci  spf 5: low levels of km, low levels of ci for this analysis, and to gain readily comparable results, we chose to look at the two extremes (spf 45 and spf 5) in this paper, the situations where the differences in practice would be most noticeable. when knowledge is valuable to all, as in high/high spf 45 or when knowledge has questionable value to all, as in low/low spf 5, we should find the clearest distinctions in practives hence, this paper examines industries in which knowledge is extremely valuable, based on the level of intangible assets (intellectual capital) required to compete as well as industries in which knowledge is of little value, at least formally, with low levels of intangible assets apparent. the first group of industries in our analysis also includes high levels of competitive intelligence activity (self-reports on capabilities combined with number of participating firms), suggesting the knowledge is also important to competitors. again, we’ll refer to this as highvalue knowledge. the second group includes low levels of ci and limited participation, demonstrating little to no competitor interest in acquiring knowledge. this is low-value knowledge. the data used in this analysis are from a large database constructed to examine the entire knowledge development vs. knowledge protection issue in greater detail. the full database include five years of financial information from 2,000 or so firms (2006-2010) as well as five years of data from a proprietary fuld & company benchmarking study on competitive intelligence capabilities. from this database, for the larger project, we constructed a breakdown of industries according to the value of intangible assets (calculated by a variation on tobin’s q, market capitalization over physical asset value) and, as noted, the prevalence of ci activity in the industry. tobin’s q has a long history of use in measuring intangible assets (tobin & brainard 1977) and remains useful up to the present day (villalonga 2004). a wide variety of metrics for intellectual capital exist, but if one wants to measure across a number of firms, the objective and readily available financial data found in tobin’s q make it the preferred tool (tan, plowman & hancock 2007, sveiby 2010). indeed, it is the only practical way to try to determine ic levels across the number of firms included in our database. the fuld & company data come from a worldwide competitive intelligence benchmarking study conducted over several years. the available data, at the time we were given access, included almost 1000 respondents providing self-report responses to a variety of questions concerning ci practice in their firms. the result is an unparalleled in-depth look into ci operations, on a number of levels. we used the data to construct industry-by-industry snapshots of the number of firms and level of sophistication of competitive intelligence activities. of note is that the fuld & company benchmarking results matched up well, on this industry basis, with an earlier study we conducted using society of competitive intelligence professional (scip) membership database. as noted earlier, represented here are the industries that were the highest of the high in terms of both variables (intangibles value according to the tobin’s q variation and ci activity) and those in the lowest quadrant of the framework, with low intangibles value and low, but nonzero, ci activity. 3. methodology and results from within the wider study, we identified eight industries in the highest part of the highest knowledge sector with enough observations (firms and years) to justify a closer look. all of these industries had a market capitalization to assets ratio above 1.4 combined with, multiple firms utilizing aggressive ci. at the other extreme, we identified eleven industries in the lowest knowledge sector with appropriate observations. each of these industries had a market capitalization to assets ratio 8 below 1.0 and had minimal ci participation by firms. the highest sector, for example, included sic 2834, pharmaceutical preparations, and sic 7372, prepackaged software. pharmaceuticals shows a cap/assets ratio of 1.94 and twenty-seven different firms that report some level of ci activity (many at very high levels and with significant resources devoted to the initiatives). software has a ratio of 2.14 and thirty identifiable firms with ci operations. essentially, we have firms here with extensive intangible assets/ic (firms valued at about twice as much as their physical assets would justify) and extensive industry ci activity. alternatively, the lowest sector includes industries such as sic 351, engines and turbines, and 4931, electric services, with cap/asset ratios of 0.71 and 0.43, respectively. each of these industries includes only a single firm with any ci activity, and even that is at a relatively low level. these are very different circumstances and very different approaches to knowledge. the firms here are worth less than their tangible assets would imply (no intangibles evident) and very little ci activity is taking place. from these categories and the industries/firms identified in each, we were able to take a closer look at the fuld & company dataset. from within the highest sector, we were able to select 96 observations from different respondents to the benchmarking study. similarly, we were able to draw 11 observations from the lower sector. while more equal samples would be preferable, remember that the nature of the data is that the one sector has lots of ci activity while the other has little. so, almost by definition, we’re going to see fewer participants in the lower sector. even so, the results provide some interesting results, with respondents answering a number of questions concerning their ci operations, including time in place, budget, processes used, types of research employed, analysis techniques, and perceived value to their organizations. these topics are organized in the table 1, using the spf references noted earlier. significance tests are not included due to the small and unbalanced samples, as well as the exploratory nature of this particular application. table 1 competitive intelligence characteristics characteristic responses spf 45 ne (n = 96) spf 5 (n = 11) time >4 years 2-4 years 1-2 years <1 year 0.33 0.11 0.15 .040 0.00 0.20 0.00 0.80 budget >$2m $1-2m $500k-1m $250-500k $100-250k <$100k 0.09 0.05 0.07 0.15 0.20 0.44 0.11 0.11 0.00 0.33 0.22 0.22 processes top-down requests intro to key intelligence topics (kit) wider use of kit’s embedded in decision-making 0.33 0.33 0.24 0.10 0.45 0.36 0.18 0.00 secondary research primarily web add other external sources tap into internal sources integrated internal and external 0.15 0.23 0.36 0.26 0.00 0.55 0.36 0.09 primary research none recognize value, not timely use friendly human network integrated internal and external 0.23 0.25 0.30 0.22 0.45 0.36 0.18 0.00 analysis none occasional basic use more analytical tools use advanced analytical tools 0.19 0.37 0.32 0.11 0.00 0.45 0.45 0.09 value perception limited or none recognized as necessary formal justification and evaluation conviction important to decision-making 0.10 0.44 0.37 0.10 0.18 0.64 0.18 0.00 9 4. discussion as is clear in the table, we have focused this discussion on how ci operations in these two different circumstances are distinct in experience, budget, techniques employed and perceived value to the organization. in the high-value knowledge industries, the ci operations are decidedly more mature. the majority of respondents report functions more than a year old and 44% have been in place for more than two years. this contrasts with the industries with less knowledge emphasis showing fully 80% of firms with ci operations less than a year old. while ci capabilities are an evolving competency, when knowledge is viewed as important, firms appear to have started earlier and so to have been in place for a longer period of time. this maturity does not necessarily translate to budgets, however. the high-value knowledge group does not show significantly higher budgets than the low-value group. the absolute numbers are higher, in terms of firms with budgets in the $1 million plus category, but in terms of percentages, there are not distinct differences. this state could reflect several things. initially, it doesn’t take much to punch up the percentages in the smaller lowvalue knowledge group, where a single firm in both the >$2 million and $1-2 million categories pushes the percentages into double figures. secondly, even if knowledge hasn’t been valued and firms are late to the game, they may still choose to enter in a big way once they make the decision to pursue competitive intelligence. and, finally, we are dealing with sizable budgets throughout these responses, and a very credible, ongoing ci operation in a high-value industry can be conducted at the lower but still considerable budget levels. indeed, the difference between a seasoned ci operations that knows its budgetary requirements and a startup operations looking to make a big splash with a big budget is something one does see in industry (and that we have had reported to us in related depth interviews). so time in place and some of the other variables we’ll be discussing have not necessarily resulted in higher budgets for ci. beyond budgets, another sign of ci maturity is decentralization of the function, a move to a structure where the ci manager(s) have more independence. in such situations, not only do directives come from top management but the ci operation(s) have some freedom to pursue and analyze knowledge on a more persistent, independent basis. in particular, they may be more completely incorporated into decision-making at lower levels, providing the ongoing insights that improve more decentralized management. instead of ad hoc fetch requests from the c-suite, they are more integrated on an on-going basis into actual operating units. here, both the high-value and low-value knowledge groups still skew heavily to top-down requests, but the high-knowledge industries have firms that are moving much more noticeably to ci independence with both wider use of analyst-initiated “key intelligence topics” and reported embeddedness in decision-making. the differences aren’t extreme, but they are noticeable and are possibly indicative of a more critical place in the organizational for the more mature firms in the high-value knowledge industries. the items in the table then cover the nature of information used by intelligence operations. in terms of secondary research, the results are both expected and unexpected. the high-value knowledge group shows a wider disparity in practice, with some respondents reporting only web sources of information while others show a full range of integrated inputs, both inside and outside the core firm. the low-value knowledge group, on the other hand, shows no respondents at either extreme (just web or fully integrated). it’s no surprise that the high-value group has more emphasis at the higher levels of secondary research, those results are as expected and appear significant. what is surprising is the higher percentage of firms using the presumably less sophisticated web-only approach. there may be reasons for this, however. mature ci operations may have more insights into what the critical data sources are in their industry. base on their knowledge and experience, they likely already know the key secondary information resources to monitor on a regular basis and have already done their homework with potential internal and external sources of research. more experienced ci operations may also value primary research more highly than secondary, as the next group of results indicates. this question needs more research and may not apply widely (only a small percentage of the high-value knowledge group, fifteen percent, report this result) but it is certainly an interesting anomaly. in the primary research area, the results are more predictable and more consistent. the high-value knowledge firms here have a clear emphasis on more developed practices, including an established human intelligence network, including both internal and external sources at the highest level. over half the firms report these capabilities (52%) while the percentage for low-value knowledge firms is only 18%. over 80% of these low-value knowledge 10 firms report non-existent or untimely primary research inputs. the analytical tools applied question also has some puzzling results. the high-value knowledge group shows almost 20% of firms reporting no analysis while the low-value knowledge group has none. the results between the groups at the presumably more mature analysis levels are then similar, though with somewhat higher percentages to the low-value group (reflecting the absence of responses in the lowest category). once again, this result could use more study. but a possible explanation lies in the greater experience and knowledge in the high-value group. because analysis of competitive data has been done previously, the reporting systems may include key indicators that have already established their value. the firm already knows these indicators meaning and contribution, so further analysis isn’t necessary, just monitoring. but that is speculation, the topic needs more attention to fully address the unexpected results. finally, the table includes results concerning the perceived value of competitive intelligence in the organization, something of an overall measure of acceptance and support. these results are as expected. in the low-value knowledge group, the contributions of ci are either unrecognized or seen as necessary but perhaps beyond the current capabilities of the firm (82%), thus having no formal role. the high-value knowledge group, on the other hand, shows close to half (47%) of firms with some formal role for ci and/or a conviction by top management that its input is critical in decisionmaking. all in all, the data provide evidence that the ci operations in the high-value knowledge group have been in place longer, generally with larger budgets, are more decentralized with more independence in their efforts, use more advanced primary research techniques, and is more valued by top managers in their organizations. the evidence on the sophistication of secondary research techniques is more mixed, as is that on analytical tools applied. each of these may have explanations but definitely calls for more study. 5. conclusions this paper is a slice of a larger study that uses publicly reported financial data and a major competitive intelligence benchmarking study to assess the importance of knowledge to the originating firm (intellectual capital level) and to competitors (competitive intelligence activity level). based on those more global results, we have identified two groups, those where knowledge is unambiguously important to both originator and competitors and those where it is unambiguously unimportant. industries and their respective firms from these groups were then mined for additional data on their competitive intelligence attitudes and activities. the results showed some clear distinctions, especially in the maturity and resource levels of competitive intelligence operations as well as in their role in the organization and their datagathering and analysis approaches. while evident and likely significant in most cases, the differences were not always huge and in a couple of examples (secondary research and analytical techniques) were not necessarily as expected. so the results were interesting and, to a degree, confirm lend weight to the idea that different knowledge development and knowledge protection circumstances will lead to different operational practices by firms. in particular, high-value knowledge environments may be associated with greater maturity and effort in ci operations. we look forward to providing further insights on these matters. acknowledgement: the authors appreciatively acknowledge fuld and company for providing much of the key data used in this study. references bernhardt, d. (1993), perfectly legal competitor intelligence—how to get it, use it and profit from it, london: pitman publishing. bontis, n. (1999) managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field. international journal of technology management, 18 (5-8), 433-462. edvinsson, l. & sullivan, p. (1996) developing a model for managing intellectual capital. european management journal, 14(4), 356364. erickson, g.s. & rothberg, h.n. (2012), intelligence in action: strategically managing knowledge assets, london: palgrave macmillan. fleisher, c.s. & bensoussan, b. (2002), strategic and competitive analysis: methods and techniques for analyzing business competition, upper saddle river, nj: prentice hall. fuld, l.m. (1994), the new competitor intelligence: the complete resource for finding, analyzing, and using information about your competitors, new york: john wiley & sons. gilad, b. (2003), early warning: using competitive intelligence to anticipate market shifts, control risk, and create powerful strategies, new york: amacom. 11 gilad, b. & herring, j., eds. (1996) the art and science of business intelligence. jai press: greenwich, ct. mcgonagle, j. & vella, c. (2002), bottom line competitive intelligence, westport, ct: quorum books, inc. prescott, j.e. & miller, s.h. (2001), proven strategies in competitive intelligence: lessons from the trenches, new york: john wiley & sons. rothberg, h.n. & erickson, g.s. (2005) from knowledge to intelligence: creating competitive advantage in the next economy. elsevier butterworth-heinemann: woburn, ma. rothberg, h.n. & erickson, g.s. (2002) competitive capital: a fourth pillar of intellectual capital? in world congress on intellectual capital readings, bontis, n. ed., elsevier butterworth-heinemann: woburn, ma. rouach, d., and santi, p. (2001), competitive intelligence adds value: five intelligence attitudes, european management journal, 19:5, 552-559. sveiby, k-e. (2010) methods for measuring intangible assets, www.sveiby.com/articles/intangiblemethods.ht m. tan h.p., plowman, d. & hancock, p. (2007). intellectual capital and the financial returns of companies. journal of intellectual capital, 8(1), 76-95. tobin, j. & brainard, w. (1977) asset markets and the cost of capital, in r.r. nelson & b. balassa, economic progress, private values, and public policy: essays in honor of william fellner, nelson, r. & balassa, b. eds., north holland: amsterdam. villalonga, b. (2004). intangible resources, tobin's q, and sustainability of performance differences. journal of economic behaviour and organization, 54, 205-30. wright, s., picton, d., & callow, j. (2002), competitive intelligence in uk firms: a typology, marketing intelligence and planning, 20:6, (october), 349-60. http://www.sveiby.com/articles/intangiblemethods.htm http://www.sveiby.com/articles/intangiblemethods.htm issn: 2001-015x v o l 3 , n o 3 ( 2 0 1 3 ) c o n t e n t s alessandro agostino, klaus solberg søilen and barth gerritsen cloud solution in business intelligence for smes –vendor and customer perspectives pp. 5-28 helen n. rothberg and g. scott erickson intelligence in the oil patch: knowledge management and competitive intelligence insights pp. 29-36 josé esteves and josé curto a risk and benefits behavioral model to assess intentions to adopt big data pp. 37-46 applying competitive intelligence: the case of thermoplastics elastomers marisela rodriguez salvador and luis francisco salinas casanova pp. 47-53 o p i n i o n s e c t i o n nowshade kabir and elias carayannis big data, tacit knowledge and organizational competitiveness pp. 54-62 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2013 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/22') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/7') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/8') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/9') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/10') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/12') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, december 27 2013 e d i t o r i a l n o t e v o l 3 , n o 3 ( 2 0 1 3 ) the journal continues to draw mainly on articles presented at academic conferences on topics related to competitive intelligence. in 2013 scip organized a first conference in south africa, under the leadership of asa du toit, the journal’s editor for africa. the first article by agostino et al. entitled “cloud solution in business intelligence for smes –vendor and customer perspectives“ identifies key success factor for smes of cloud based business intelligence products. most important ksfs identified in this study were the level of software functionalities, the ubiquitous access to data, responsive answers to customer support requests, handling large amounts of data and implementation cost. the study also shows that smes prefer industry tailored software, monthly or quarterly billings, and contact by email or phone for service. the second article by helen n. rothberg and g. scott erickson entitled “ intelligence in the oil patch: knowledge management and competitive intelligence insights” argue with extensive empirical data and examples from oil-based industries that practitioners are one step ahead of academia in the sense that many organizations have a connection between their knowledge management and competitive intelligence functions. while the natural inclination of most working in the fields of km and ci is that more is always better, both theory and practice suggest that sometimes a more measured approach may be better, the authors conclude. the third article by esteves and curto entitled “a risk and benefits behavioral model to assess intentions to adopt big data” develops a model that predicts the intention to adopt big data technologies. the article by salvador and casanoa entitled “applying competitive intelligence: the case of thermoplastics elastomers” provides a practical case of the competitive intelligence methodology applied to the thermoplastics elastomers industry, specifically within the styrenic block copolymers category. the authors identify a solution for a mexican company to support their decision-making process. the last article by kabir and carayannis entitled “big data, tacit knowledge and organizational competitiveness” show how big data is a source of firm’s competitive advantage. as always we would first of all like to thank the authors for their contributions to this issue of jisib. on behalf of the editorial board, sincerely yours, dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 55 brazil evolutions in ci and some aspects of a current scenario francisco carlos paletta cidade universitária, brazil e-mail: fpaletta@ipen.br received june 18 2013, accepted 10 august 2013 abstract: ten years have gone since competitive intelligence was regarded as being in its initial phase in brazil, according to the statistics from the application of the internationally accepted program for the sector. this article talks about the evolution of the brazilian scenario in this field of activity and about aspects of the current reality which entitles us to outline the evolution of the practice of intelligence, as well as what is thought to be its application and results. the work focused mainly on three aspects: the evolution of the concept of competitive/economic intelligence in the southeast region of brazil; the biggest recurring deficiencies in ci projects and obstacles to their execution; and the major recurring skills highlighted in the projects. the article shows culture as an influence that favors the aspects that affect the desires and decisions of companies located in brazil. conclusions point to an evolutionary scenario regarding the volume of project results in big companies and the presence of fragmented discourses in a market eager for a bigger volume of closed deals, less worried about delivery depth and quality. keywords: competitive intelligence, business strategy, organizational sustainability, evolution of ci in brazil, ci practice, ci projects. introduction ten years have gone by since competitive intelligence was regarded as being in its initial phase in brazil, according to statistics from the application of a program that is accepted as being representative of processes identified as competitive or economic intelligence and different from business intelligence (bi)1, marketing intelligence2, and market research3 processes, among others. nowadays, we can discuss the evolution of the available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2013) 55-61 mailto:fpaletta@ipen.br https://ojs.hh.se/ 56 brazilian scenario in this field of activity and aspects of the current reality allow us to outline the evolution of the practice of this concept, as well as what is thought to be its application and results4. method the basis of study for this article is approximately 100 medium and large sized brazilian companies monitored for at least 5 years by business strategy and ci (consulting companies located in sao paulo) consultants that work with medium and large sized companies, in addition to scientists holding patents who want a strategic plan in the field of innovation/feasibility of new businesses). the results considered were those described according to the view of the organization's main decision makers in line with the evolution/highlight of the business shown through internal numbers and/or external metrics. we know that the dynamics of life is more and more intense and it is worth to investigate how such dynamics leads our actions and skills to solve problems capable of expanding our capacity to build the reality we wish for. approaching such question requires a qualitative analysis, which is what this article proposes to do. the goal here is not to exhaustively investigate all analysis aspects possible, but rather to understand some aspects of the actions and reactions of brazilian companies in their market in a more in-depth fashion as to reveal they are connected to other aspects that also have a huge impact. the conclusions hereof and the analyses point to a global reflection on how we do what we do and on how we realize that we walk the path that should take us to the expected results. the analysis on the evolution of ci in the brazilian scenario is highlighted here, and it reveals some aspects that according to the proposal are relevant in the current scenario. the basis of study: 60 medium and large sized companies researched, monitored for at least 5 years by business strategy and ci consultants. experiences and results of academic classes, experience in ci congresses and panels held within such period by the consultants involved in the projects also complement the contents for later analysis. the 3 main focus points for the conclusive analyses were: 1) the evolution of the concept of economic/competitive intelligence in the southeast region of brazil. the southeast region of brazil holds the 3 largest metropolises in the country. according to the census carried out in 2010, the southeast region is the most populated in brazil 80,353,724 people where sao paulo, the biggest city in brazil, is home to 41,252,160 people. the southeast region is also the place with the highest concentration of income and businesses, and sao paulo is the # 1 place home to international companies and hq’s of brazilian companies, in addition to being the third biggest megalopolis in the world and being known as the “city of excesses.” 5 the southeast region is responsible for over 70% of the value of industrial transformation in brazil and has the highest gdp vs. the other regions. 6 2) the biggest recurring deficiencies in projects and which were obstacles to their execution 3) the results of the analyses on the evolution of the ci concept and practice in brazil point to a spreading of the subject, but without the maturity of ownership over the use or control of results. in addition to that, they also point to an application which is often scattered and targeted at the core education of the competitive intelligence analyst, which happens mainly when designing the intelligence plan, followed by the cross analyses of critical information, as shown in table 01. 57 table 1. evolutions of the concept and practice of ci in the southeast region of brazil in the last 10 years. evolutions consequences for brazilian companies comparison of results in 10 years evolutions of the concept of competitive intelligence initially unknown, competitive intelligence became more and more popular mainly in the southeast region and among large sized companies. higher attendance of executive in related events. increase in the amount of executives who attend such events. increase in the proposal and execution of ci projects. boom of ideas and consultancy for a broad concept. increase in courses, sites, workshops, speeches, blogs, higher participation in forums, more freedom to interact with the concept. increase in the amount of professionals working in the ci market. more projects identified as ci projects. increase, from hundreds to thousands, in the amount of professionals that received of direct ci education. (attendance in workshops, subjects in graduate/mba or specialization courses.) adaptation of the practice of the concept to the understanding of each professional and/or brazilians' culture trend not to follow processes and use their creativity instead (pdca). over 60% of the companies visited believe they carry out ci in their own way. lack of structured processes and the non-observance of programs, due to neglect or ignorance. from a lack of process to a difficulty to identify valid ci processes. results insufficient because they do not approach the completeness required in the concept. defense of more awareness of interrelations, operational coherence, and results. beginning of the systemic discourse. interest in networks and the search for relevant information. no connection with what is actually done. presence of the proposal, but with traditional implementation plans. as if the concept alone could generate a different practice. lack of awareness that changing action is required in order to change behavior. no comparative evolution. division of focuses when offering projects according to the type of education obtained (generally, education is incomplete). an initial general view is missing. it is usual to suit the intelligence need to the focus of the professional hired. (monitoring of the competition, management of knowledge, strategic planning, among others.) companies have problems to find the right professional, which often results in the fact that the concept is not understood or in fragmented results. fragmentation of the solution. evolving: with the creation of the web 2.0, weak signs suggest a growing participation and domain of the collectivism as cultural skill for ci programs. more quality in proposals to solve problems and challenges and good use of brazilians’ cultural skill. more integration and focus on the business. positive effects and results rely on local culture, rather than on what was planned as strategy. future possibility: the discourse is incorporated into practice. 58 the second analysis focus table 02 were the main challenges faced internally which, depending on the depth of the view and on the awareness of the contractor, limit project results more than the external difficulties to find the relevant information required to make the right strategic decision suited to the moment, time, location, and breadth. such datum is not right only when it comes to the services provided where the intelligence need was related to a product and process to collect relevant information, but mainly of a single area or mainly external, with no main need to make the business more intelligent. the table resumes a study that started in the 90's and was exposed in the book veille technologique et competitivité l’intelligence économique au service du développement industriel (dou,1995 pg 11). such study has a grouped analysis of 7 of the main skills highlighted when using ci, making the practical use of relevant information in some countries evident. based on that, a chart with trends was generated7. out of 7 of those main skills, 4 were present in companies located in brazil at 50% rate of all projects, which, in spite of being considered in a small sample (30 out of 60 companies analyzed), such answer intensity indicates, at least, a trend towards the development of a dormant potential in the current brazilian scenario and which already produces concrete results in highly strategic projects, i.e., the capability to respond to stimulus is high8. the table below highlights how such skills arose and impacted the result of each work. 59 table 2. recurring obstacles found when executing ci projects main problems consequences for brazilian companies impacts on current results mainly with chairmen/ceo's: a) focus mostly internal (vs. external); b) arrogance regarding knowledge; c) lack of strategic focus. a) believe the problem is internal or b) they have all the knowledge and skills required to be successful and make decisions alone, or c) that the hq has the strategy, everything is ready, or it is implicit. obstacle to project execution. obstacle to the synchronization between the external and internal environments. operation without a purpose, with no strategic focus. company with highs and lows and/or dependant on a favorable market, economy, or product. president or chairmen are far from the operational reality or the local culture. the company is not capable of identifying the type of intelligence it needs. lack of perception of the current reality. no thoughts about operational coherence with the strategic direction. if the project is carried out without the prior identification of the intelligence need, results are compromised because a target does not exist. the main decision maker or the manager of the strategic area in question does not have visionary or strategic characteristics. limited sight or lack of courage or long term desires (seek something beyond his/her period of employment or the goals he/she defined). ci hiring is difficult and slow (long term, if any), followed by a slow execution due to lack of response to the command. lack of energy and internal alignment. timing and synchronization are missed. fragmentation of the execution. (happened frequently in the development, research, or innovation departments.) division between departments, conflicts of interests. generally, maintaining tasks separate prevails. prevents the execution of solutions such as they had been proposed, preventing the systemic effect of results. limited breadth. lack of financial resources or long term planning culture. short term vision prevails and the company does not invest in the project or starts it, but does not end it. the company does not accept fund management integrated with commercial initiative. stakeholders lack strategic capability (professionals who implement the strategy defined). current executives who perform tasks without using strategic thinking are often not capable of carrying out a project that requires a higher degree of thinking. the team never has time to meet, does not understand the coherence between the process and the result desired, and thinks the project needs to provide answers, rather than ask questions. 60 table 3. main skills that helped the projects to achieve success, based on dou studies. conclusive analysis more than a program that proposes a variety of techniques to collect relevant information from the market and the environment, competitive intelligence is a strategic tool that relies directly on the foresight of projects’ stakeholders and supporters to maximize its results relating both to the technique and relations, in order to make the business and processes more and more intelligent9. in brazil, it is possible to see a significant evolution both in the amount of applied projects and in the better education and growing experience. a negative factor is the discursive market, where the lack of planning and depth has a huge impact. analyses also point to an original situation which is ignored by companies' decision makers and owners: how hard it is to manage and sustain businesses in brazil, both regarding the strategic commercial management and the strategic financial management, which are especially discrepant when compared with countries in europe and north america10. becoming aware of such issue and the corrective measures may be critical strategic implementations in the field of ci, which may increase competitiveness significantly in times filled with opportunities, such as the one we are living now. at last, they point to the appearance of an attitude that is more systemic and coherent with a positive aspect of our culture, as shown in table 3 above, including the ability to work in teams in a fun and creative fashion, in addition to the ability to innovate. that is, being aware of the ability to produce wealth respecting the brazilian tools and originality, and succeeding without having to make huge efforts. references [1] h. dou. veille technologique et competitivité; l’intelligence écono mique au service du développement industriel. dunot, paris, 1995. [2] h. maturana, f. varela. el árbol del conocimiento; lãs bases biológicas del entendimiento humano. buenos aires, 2003. [3] h. r. maturana; j. mpodozis. origen de las especies por medio de la deriva natural. o la diversificación de los linajes a través de la conservación y cambio de los fenotipos ontogenéticos. museo nacional de historia skills consequences for brazilian companies impacts on current results highlights of the brazilian culture which are already present in ci projects collectivism use and propagation of relevant information. learning, improvement of communication, and feedback. use of collective intelligence. the entire company becomes more intelligent as time goes by. intelligence is spread around the departments, and no longer concentrated usually in the commercial or technical (production) departments. individual talent individual talents step up and lead the process. highlighted performances to: act as data miners; identify the need for intelligence; keep the team focused; design the strategic plan. when using such skill, a single actor assures most of the results of the project. higher amount of case publications in congresses in brazil and abroad, highlighting government and private companies located in brazil. brazilians awarded in competitiveness/innovation contests, as well as writers of national and international books. strategic & operational synergy quick assimilation of actions relevant to make the company more competitive. team more focused on the business and more aligned. higher quality and quantity of solutions obtained. the evolution of the business provides safety. the client’s/market’s perception of the company’s competitive edge is inevitable. national culture use of creativity in processes and in the use of information technologies and resources available. ability to do more using less. positive results with the smallest investment possible. produces more relaxed and spontaneous atmospheres. ability to innovate. 61 natural, publicación ocasional n° 46, santiago. 48 pp. 1992 [4] h. maturana, f. varela. de máquinas y seres vivos. lumen, buenos aires, 2003. [5] j. castro e p. abreu. influência da inteligência competitiva em processos decisórios no ciclo de vida das organizações. ci, inf. (online) 2006, vol35, n3, pp15-29 issn 0100-1965. brasilia df brasil. [6] j.r. saul. la civilization inconsciente. anagrama, barcelona, 1997. [7] l. bersou. manual da empresa rica a velocidade que transforma receitas, custos variáveis e recursos monetários em lucros. trevisan. são paulo, 2010. [8]l. bersou. apostila x. bca consultoria. são paulo 2000. [9] l.quoniam, a. lucien. intelligence competitive 2.0. hermès, paris, 2010. [10] p. dupin. l’éeuilibre de forces entre les résultats des projects d’intelligence compétitive et les aptitudes professionnelles identifiées. thèse université du sud toulon-var, 2009. francisco carlos paletta table 1. evolutions of the concept and practice of ci in the southeast region of brazil in the last 10 years. table 3. main skills that helped the projects to achieve success, based on dou studies. conclusive analysis [1] h. dou. veille technologique et competitivité; l’intelligence écono mique au service du développement industriel. dunot, paris, 1995. [2] h. maturana, f. varela. el árbol del conocimiento; lãs bases biológicas del entendimiento humano. buenos aires, 2003. [3] h. r. maturana; j. mpodozis. origen de las especies por medio de la deriva natural. o la diversificación de los linajes a través de la conservación y cambio de los fenotipos ontogenéticos. museo nacional de historia natural, publicación ocasional n 46, santiago. 48 pp. 1992 [4] h. maturana, f. varela. de máquinas y seres vivos. lumen, buenos aires, 2003. [5] j. castro e p. abreu. influência da inteligência competitiva em processos decisórios no ciclo de vida das organizações. ci, inf. (online) 2006, vol35, n3, pp15-29 issn 0100-1965. brasilia df brasil. [6] j.r. saul. la civilization inconsciente. anagrama, barcelona, 1997. [7] l. bersou. manual da empresa rica a velocidade que transforma receitas, custos variáveis e recursos monetários em lucros. trevisan. são paulo, 2010. [8]l. bersou. apostila x. bca consultoria. são paulo 2000. [9] l.quoniam, a. lucien. intelligence competitive 2.0. hermès, paris, 2010. [10] p. dupin. l’éeuilibre de forces entre les résultats des projects d’intelligence compétitive et les aptitudes professionnelles identifiées. thèse université du sud toulon-var, 2009. 40 developments in business intelligence software1 zhanna abzaltynova janice williams blekinge institute of technology, sweden e-mail: zhanna.abzaltynova@gmail.com, jawil79@yahoo.com received november 10 2012, accepted 6 may 2013 abstract: in today’s economy the requirements in business intelligence environments are changing dramatically. this research paper tested underlying constructs. hypothesis one sought to test if vendors seek to provide complete bi solutions following all four stages of the ci cycle. the evaluation of bi vendors indicates that all vendors examined do not support planning & directing phase, except for astragy that gives users consultations to plan and arrange their ci, its absence did not influence the overall performance score. the second hypothesis sought to test if bi vendors fail to provide good enough solutions for the analysis part of the intelligence cycle. the research findings indicate that only two bi vendors, sas and qlikview, delivering the analysis phase of the intelligence cycle in a proper way. the third hypothetical construct concerns bi vendors’ attempts at making considerable changes in software each year, with each new upgrade. by tracing and comparing the developments of the vendors selected it has been concluded that all bi vendors, irrespective of whether it is a leading traditional vendor or small innovative bi, follow the same tendency in introducing bi enhancements by striving to make its software cost-effective, simpler, faster and flexible for use, scalable to manage increasing amounts of data in businesses, accessible to employees at all levels of organization. hypothesis four sought to find out if the bi vendors’ software tested can be divided into a number of meaningful subgroups. with reference to evaluation and analysis and empirical findings, it has been concluded that the bi vendors can be divided into sub groups and hence has been classified based on their support of the phases of the intelligence cycle, their developments and market information. the 1 this paper is an adaptation from a master thesis under the same title completed at bth in 2010. available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2013) 40-54 mailto:zhanna.abzaltynova@gmail.com mailto:jawil79@yahoo.com https://ojs.hh.se/ 41 subgroups range from advanced, competent, partially competent, and inadequate to absolutely inadequate. among the bi vendors assessed, none satisfied the criteria in the advanced category. hypothesis five aspired to determine if the bi software evaluated should fall under a different term as some of them do not follow the entire bi cycle. the analysis of empirical findings identified that qlikview and tibco spotfire deliver the so-called next generation in-memory analytics, which is faster, much simpler, more flexible and scalable and meet the present-day business needs to a far greater extent if compared to traditional bi. keywords: business intelligence, competitive intelligence, business intelligence software, data management, development, business analytics software, ssav model. introduction bi has become of much interest to many organizations in the fast changing business environment of today. in business week it is highlighted that the recession is fostering interest in bi software, which helps companies analyze the data they collect for new cost-cutting or sales opportunities (rachel king, 2009). with the present dynamism in the business environment business managers are looking for answers to their questions, and they need these answers much more quickly than in the past. to this end bi software plays an integral role in his process. with all this, there is an increasing demand for a faster turnaround on information requests which places more pressure on the information technology (it) organizations/bi software vendors who will now have to take on a more flexible and organized approach to providing for bi software users and to establish competitive advantage. business intelligence for competitive advantage has become one of the prime prerequisites for competitive advantage in the market place. it is the domain responsible for gathering that information and making it available to decision-makers. for improved decision making, and to enable a competitive advantage, the need for more current information continues to grow. most companies are putting out the effort to satisfy this need, but their progress and capabilities vary widely (ibm redbook, 2004). this research will therefore highlight the developments made by various vendors and the ones who seem to have established a good competitive advantage. in addition to this, the goal is to produce and deliver products quickly and at the lowest cost possible, and to maintain good client satisfaction among bi software users. problem formulation business intelligence plays an integral role in the decision making process of many organizations today. there are an increasing number of organizations who provide software applications that are aimed at helping companies implement bi systems. these vendors provide various packages which do development overtime while others may have few developments much to the disadvantage of the users. bi vendors must take into consideration technological innovations and evaluate their ability for improving their existing products. at present bi has attracted much attention from information specialists as well as the business community. this increased attention has given rise to a number of software applications provided by the various vendors who seek to capitalize on these companies’ need to implement bi systems. evaluations have been made of software provided by bi vendors however the focal point of this research is to highlight whether or not these vendors have added more value to the traditional database management software applications. scope of the paper the purpose of this research is to examine the developments that have occurred with business intelligence software in the last decade. the study will determine and analyze business intelligence software available in the market and trace the developments the major business intelligence vendors are producing in order for companies to stay competitive in a rapidly changing business environment. the thesis research questions are outlined in table 1. 42 table 1. research questions q. 1  what subgroups can the software evaluated be divided into? q. 2  do the bi vendors provide good enough solutions for the analysis part of the intelligence cycle? q. 3  should some vendors of so-called bi software fall under a different category based on the components of the bi cycle? q. 4  do bi vendors make considerable changes in software each year with each new upgrade? empirical research the empirical research was performed with the view to study, analyse and evaluate bi vendors and their products. due to the time constraint and limited access to bi information of some vendors, not all bi vendors were covered in the research. the following bi vendors included in the empirical study: information builders, microstrategy, ibm cognos, sas institute, sap business objects, microsoft, qlikview, tibco spotfire, actuate and astragy. having studied a number of evaluation approaches undertaken by various research organizations with inclusion of ssav model and having taken into account the objectives of the research, the empirical study was devised to: examine general characteristics of bi functions; perform an analysis of bi software in terms of four ci cycle phases (planning & directing, data collection, analysis and dissemination) for each bi vendor; to trace the developments introduced by each bi vendor in their recent releases & present general comparison and similarity of where those enhancements are directed at; to perform an analysis of market share, market segments and pricing structure of bi evaluated. and finally, as per research results, the empirical study endeavoured to categorize bi vendors into a number of subgroups. the empirical study was performed by way of observations and experiments using the free software trials available at the vendors’ web-sites as well as white papers, presentations, data sheets, news with the view to gather information on general characteristics of bi functions, recent bi releases and market statistics. evaluation criteria of the bi software as per ci cycle phases, presented in the ssav model as the class of process variables, were taken into consideration herein. each vendor was evaluated as per each criterion of the four ci cycle phases and rated from not applicable (0) to excellent (4) score. an overall score and then an average score for each intelligence cycle phase were calculated to perform an analysis of bi software. however, it is necessary to point out that the ssav evaluation model included, performed bi software evaluation according to three classes of variables as process variables (i), product variables and process variables (ii). unlike this research, which attempted to include only process variables (ii) in the evaluation (examination of how a bi function supports a particular ci cycle activity), together with the study of bi software recent enhancements and analysis of market information. participants in an effort to find solutions to the research questions previously outlined, the researchers selected from among the top bi software vendors. to achieve the relevant data the software provided by these vendors were measured on the criteria of the ci cycle phases of planning and directing, data collection, analysis and dissemination. the bi vendors operate in countries across the globe and provide products that are popular enough in the bi software market. it was decided to use those among the top vendors in order to give rational representation of the vendors who actually make new developments in their software gradually. the bi vendors have been mentioned in the initial section of this description. instrument to collect data an instrument was designed to collect the empirical data on the software. the evaluation instrument was designed to determine the level at which the bi vendors provide software based on the ci cycle represented in this study. each phase was allotted a score of one which gives the evaluation instrument a 43 score of zero to four. the scale which follows indicates scores which were used to determine the support of each vendor’s software for each stage of the intelligence cycle. range-elucidation 0. n/a 1. poor 2. satisfactory 3. good 4. excellent this scale was developed by the researchers in order to facilitate the use of the quantitative research method effectively. this ensured the collection of statistics for data analysis. the software provided by these bi vendors were assessed and based on the details provided by white papers, demos and information from the sites of these vendors, they were scaled accordingly. analysis of bi vendors as per ci cycle the table presented below shows a summary of empirical findings that include bi software evaluation as per evaluation criteria reflected in the appendix with the average scores calculated for each phase of the intelligence cycle, examination of developments introduced by the tested bi vendors and analysis of their market information i.e. market share, customers and pricing strategy. as per the table (1) below, bi software evaluation determined that the planning & directing phase of the intelligence cycle is not supported by any vendor. though, astragy consultants advise users to plan and direct as well as arrange their intelligence system. with respect to the data collection phase, bi software vendors tested support this phase in a fair way with the total average score (3.16) for all vendors (figure 16). sap business objects is assigned the highest score for the data collection phase, followed by information builders, ibm congos and astragy. though, astragy does not provide any bi functions and can be considered more as ci vendor, it was also included and evaluated along with all other vendors. microstrategy turned out to have the lowest score for data collection phase and is the last in the list. the source for the table below, in the evaluation summary. note: cells highlighted in part ii of the table (2) shows the areas where bi enhancements took place (either in data warehousing, analytics or information delivery). part iii bi market information – market share for astragy is not provided by the vendor, therefore is highlighted in grey. those bi vendors that deliver its bi products to corporate & sme segments are highlighted in grey, but for microstrategy, which provides its bi software to mainly corporate customers (with “c” indication) and qlikview cell is indicated with “m” sign that means this vendor is a leader in the midmarket segment. pricing strategy is indicated with “s” for standard pricing structure that include named-user and cpu-based, “f” – flexible pricing structure that include other pricing choices but for standard ones. 44 2. summary of bi software evaluation total average score for the data in the table 1 is shown in figure 1. we see sas in first place, infobuilders on second and astragy on third place. figure 1. bi vendors rating on data collection data collection total average score (3.16) 0.00 1.00 2.00 3.00 4.00 sa p in fo bu il de rs as tr ag y ib m sa s mi cr os of t ql ik vi ew ti bc o ac tu at e mi cr os tr at eg y information builders ibm congos sap business objects sas microstrategy qlikview tibco spotfire actuate microsoft astragy i. bi software evaluation by ci cycle phases (with indication of average total scores) 1. planning & directing 0 0 0 0 0 0 0 0 0 0 2. data collection 3.75 3.62 3.81 3.5 1.5 3 3 2.5 3.25 3.6 3. analysis 1.75 2.25 2.75 4 2.5 4 3.8 1.5 3 3.5 4. dissemination 3.92 4 4 3.6 3.94 3.5 3.1 3.4 3.8 3.4 ii. bi software developments data warehousing business analytics information delivery iii. bi market information market share as of 2007 6.00% 14.00% 26.00% 14.4 0% 5.88% 1.57% 0.59% 2.76% 10.60% customer segments c m pricing strategy s f f f f f f s f s 45 as per the figure 2 presented below, sas institute and qlikview are the best in delivering the analysis phase. again, astragy was ranked with other vendors though it does not support any bi functions. actuate was given the lowest score and support analysis in a poor way. in general, total average score for the analysis phase amounts to (2.9) for all bi software evaluated, which is below the scores for the data collection and dissemination phases. thus, the evaluation findings prove the thesis hypothesis that bi vendors fail to provide good enough analysis part of the intelligence cycle. figure 2. bi vendors rating in analysis with respect to bi vendors rating in the dissemination phase provided in the figure 3 below, sap business objects, ibm cognos, microstrategy and information builders are the best in dissemination followed by microsoft, sas institute, and qlikview. tibco spotfire has the lowest score for the dissemination phase, therefore is the last among bi vendors. total average score for the dissemination phase is (3.67) for all bi vendors tested, which is the highest among all ci cycle phases and determines that bi vendors deliver this phase in a more competent way if compared to other ci cycle phases. figure 3. bi vendors rating in dissemination analysis total average score (2.9) 0.00 1.00 2.00 3.00 4.00 sa p sa s mi cr os of t ql ik vi ew as tr ag y tib co in fo bu ild er s mi cr os tr at eg y ib m ac tu at e dissemination total average score (3.67) 0.0 1.0 2.0 3.0 4.0 sa p ib m in fo bu il de rs mi cr os tr at eg y sa s mi cr os of t ql ik vi ew as tr ag y ac tu at e ti bc o 46 table 3. summary of bi improvements vendor name previous release recent release improvements introduced in: 1. information builder webfocus 7 webfocus 7 (with new features)  information delivery-user interface & reporting;  analytics; 2. microstrategy microstrategy 8 microstrategy 9  data warehousing;  analytics;  information delivery: user interface & reporting; 3. ibm cognos cognos 8 ibm cognos 8 version 8.4  data integration;  information delivery: user interface & reporting;  analytics; 4. sap business objects business objects xi 3.0 business objects xi 3.1  data integration;  information delivery: user interface & reporting; 5. sas institute sas 9.1 sas 9.2  data integration;  analytics;  information delivery: user interface & reporting; 6. microsoft sql server 2005 sql server 2008  data warehousing;  analytics;  information delivery: user interface & reporting; 7. qlikview qlikview 8 qlikview 8.5  analytics;  data integration;  information delivery; 8. tibco spotfire spotfire dxp tibco spotfire 2.2  analytics;  information delivery: user interface & reporting; 9. actuate actuate 9 actuate 10  information delivery: user interface & reporting; 10. astragy astragy enterprise edition astragy enterprise edition (with new features as add-on modules on request)  analytics;  data collection;  dissemination; 47 the table 3 presented above, provides an overview of bi previous and recent releases introduced by the vendors with indication of areas where these improvements or developments took place either in data warehousing, business analytics or information delivery. upon the information provided above, one can come to a conclusion that each vendor endeavours to introduce significant and new enhancements/developments each year either with current release or presenting upgrades within an existing release. the following vendors delivered new bi releases: microstrategy, ibm cognos, sap business objects, sas institute, microsoft, qlikview, tibco spotfire, and actuate. information builders presented its bi software under name webfocus 7 with new enhancements and astragy introduced new features in its product astragy enterprise edition as add-on modules on request. microstrategy, with its recent release microstrategy 9, delivers bi with greater scalability, performance and efficiency as well as merges bi applications cohesively and consistently to all departments and workgroups at the organization. ibm cognos version 8.4 endeavours to extend bi to a broader range of business users at all levels of organization and provide greater access to information through advanced search capabilities. sap business objects in business objects xi 3.1 empowers users with flexibility to access all information regardless of format, shape & size and location; deliver bi platform that support heterogeneous environments and offer integration with data sources from a variety of vendors. sas, through its recent release sas 9.2., delivers a wide range of benefits for both business users and it departments, for instance, by improving and simplifying advanced analytics to all decision makers. microsoft, with its sql server 2008, provides businesses with high levels of security, reliability and scalability, enables to reduce time and cost to develop and manage their data infrastructure as well as delivers a comprehensive platform. information builders significantly improved reporting and analysis functions to deliver efficiency and simplicity of use to all business users. qlikview 8.5 with its in-memory business analysis endeavours to deliver bi with greater speed, flexibility, ease-of-use and visual interactivity. actuate 10, with its comprehensive ria-ready platform strives to provide costeffective bi and reporting applications that reduce costs and ensure efficiency. and finally, tibco spotfire and astragy also introduced improvements with the aim to deliver more efficiency and simplicity. cost-effectiveness to a wide range of business users. summary & analysis of bi market information according to the table 2 evaluation summary presents the worldwide market shares of the bi software of the following vendors: sap, ibm, information builders, microstrategy, sas institute, microsoft, qlikview, actuate, and tibco. astragy market share is not reflected in the figure as the vendor did not wish to reveal the market share of its product. unfortunately, due to limited access to these data and inability to separate and identify bi revenues from the overall revenues of some vendors as ibm, microsoft and tibco, the bi vendors’ market shares for 2008 were not presented herein. market share of the following bi software: information builders, microstrategy, qlikview, actuate and tibco for 2007 was derived with bi software market revenue as of 2007 (5, 1 billion usd) and the vendors company revenues. therefore, the market share of the aforementioned vendors is approximate and rough. more clear graphical presentation of bi software market shares presented in the figure (4). 48 figure 4. bi software market shares as of 2007 according to the summary of bi software market shares, sap has the leading market share with 26% followed by sas institute – 14.4%, ibm – 14 % and microsoft 10.6%. the bi vendors having the least market shares are qliktech and tibco. astragy is listed in the summary table with no indication of its market share as the vendor wished not to disclose its market share. the remaining part of bi market 18.2 % pertains to the rest bi vendors, not included into the research due to the time constraint. with respect to customer segments (table 2), the analysis revealed that almost all vendors deliver its bi software to both enterprise and sme businesses with the exception of microstrategy that provides bi to mainly corporate customers and qliktech is considered a leader in mid-market segment. as per the table (2) shows that the majority of bi vendors evaluated provide customers with flexible or multiple license options, these are sap, ibm, sas institute, microsoft, microstrategy and tibco. other vendors as information builders, actuate and astragy have standard pricing structure based on either named-user or cpu-based or both. besides, some vendors deliver web-based software and offer saas pricing model such as sap, ibm, microstrategy, sas institute, microsoft and qlikview. in addition, some vendors offer distinctive features in their pricing models: sap delivers user-role-plus-server approach, ibm cognos `s pricing is role and task-based, microsoft offers no-charge-for-end-users pricing and qliktech `s pricing is cost-efficient as users have to buy what they use. bi software classification as per the evaluation and analysis of empirical findings, the bi software can be logically classified into subgroups in terms of its intelligence cycle phases with consideration of their developments and market information. bi vendors, in terms of the support of ci cycle phases, were grouped according to the overall performance of four (4) phases (planning & directing, data collection, analysis and dissemination). bi software is grouped as follows: 1. advanced: bi software in this group outperforms in all four ci cycle phases such as planning & directing, data collection, analysis and dissemination. this bi software has one of the leading market shares, is employed successfully in all market segments, introduce significant developments on annual basis and have the flexible pricing strategy. 2. competent: as all bi software evaluated does not support planning & directing phase, they can be termed “competent” as they support other three ci cycle phases (data collection, analysis and dissemination) in an excellent or almost excellent way. they bi vendors market share as of 2007 1.57% 2.76% 0.59% 18.20% 26.00% 14.00% 6.00% 5.88% 14.40% 10.60% sap business objects ibm congos information builders microstrategy sas institute microsoft qlikview actuate tibco spotfire others 49 also have the leading market shares, work in all market segments, introduce developments on annual basis and have the flexible pricing strategy together with the standard one. 3. partially competent: if bi software perform well at least in two ci cycle phases, it is included in this group. besides they can work either in all or some of the market segments, have either leading or non-leading market shares, provide enhancements annually and have either flexible or standard pricing structure. 4. inadequate: if bi software outperform only in one of four ci cycle phase, they are included in this group. moreover, they work either in all or some of the market segments, provide enhancements annually and have either flexible or standard pricing structure. 5. absolutely inadequate: when bi software fails to excel in any of the four ci cycle phases, it is positioned in this group. it can be present either in all or some of the market segments, have significantly small market share, provide developments annually and have either flexible or standard pricing structure. this classification is applied in the figure (5) as follows. figure 5. bi software classification on the basis of the evaluation criteria, sas institute and microsoft are positioned in the group of competent bi software; sap business objects, ibm congos, information builders and qlikview are included in the group of partially competent bi software; and finally, microstrategy and actuate are placed in the group of inadequate bi software. there is not any bi software, at least among the software tested, that could be positioned in the advanced and absolutely inadequate category. qlikview could be placed into the competent group if it had the market share relevant to this category. in addition to the bi software classification presented above, qlikview and tibco spotfire software can fall under a different term other than bi software as they deliver the so-called next generation in-memory analytics, which is faster, much simpler, more flexible and scalable and meet the present-day business needs to a far greater extent if compared to traditional bi. these software vendors are completely different from traditional bi vendors as they provide greatly enhanced & efficient analytic capabilities and do not follow the entire bi cycle, and therefore we propose to term them as “business analytics software” instead of bi software classification advanced competent sas institute microsoft partially competent sap business objects ibm congos infobuilders qlikview tibco spotfire astragy inadequate microstr-gy actuate absolutely inadequate 50 bi software. besides, as astragy does not support any bi functions, it should also be termed differently as ci software, not bi software. conclusions & recommendations hypothesis one sought to test if vendors seek to provide complete bi solutions following all four stages of the ci cycle. in terms of the support of ci cycle phases; bi vendors were grouped according to the overall performance of four (4) phases (planning & directing, data collection, analysis and dissemination). the evaluation of bi vendors indicates that all vendors examined do not support planning & directing phase, except for astragy that gives users a consultations to plan and arrange their ci, its absence did not influence the overall performance score. information builders and sap business objects excel in data collection phase; sas institute and qlikview are the best in analysis; sap business objects and ibm cognos surpass in dissemination phase. it should be noted that astragy was evaluated along with other vendors though it does not provide any bi functions but only provide common functions for supporting the ci cycle phases. the second hypothesis sought to test if bi vendors fail to provide good enough solutions for the analysis part of the intelligence cycle. the research findings indicate that only two bi vendors, sas and qlikview, delivering the analysis phase of the intelligence cycle in a proper way. the overall findings also indicate that bi vendors fail to provide good enough solutions for the analysis part of the intelligence cycle as total average score provided by the evaluation instrument (see figure 4) among bi vendors for the analysis phase fell below the average scores for the data collection and dissemination phases of the cycle. the third hypothetical construct concerns bi vendors’ attempts at making considerable changes in software each year, with each new upgrade. by tracing and comparing the developments of the vendors selected it has been concluded that all bi vendors, irrespective of whether it is a leading traditional vendor or small innovative bi, follow the same tendency in introducing bi enhancements by striving to make its software cost-effective, simpler, faster and flexible for use, scalable to manage increasing amounts of data in businesses, accessible to employees at all levels of organization. most of the vendors introduced a support for heterogeneous environments and data sources from a variety of vendors. hypothesis four sought to find out if the bi vendors’ software tested can be divided into a number of meaningful subgroups. with reference to evaluation and analysis and empirical findings, it has been concluded that the bi vendors can be divided into sub groups and hence has been classified based on their support of the phases of the intelligence cycle, their developments and market information. the subgroups range from advanced, competent, partially competent, and inadequate to absolutely inadequate. among the bi vendors assessed, none satisfied the criteria in the advanced category. hypothesis five aspired to determine if the bi software evaluated should fall under a different term as some of them do not follow the entire bi cycle. the analysis of empirical findings identified that qlikview and tibco spotfire deliver the socalled next generation in-memory analytics, which is faster, much simpler, more flexible and scalable and meet the present-day business needs to a far greater extent if compared to traditional bi. besides, they do not follow the entire bi cycle and it is suggested herein to term them as business analytics software instead of bi software. moreover, as astragy does not support any bi functions, it is also suggested to term it differently as ci software, not bi software. bi software is among the many software that organizations utilize to ensure their stay in the market. bi enables organizations to make well informed business decisions and thus can be the source of competitive advantages and perform the ultimate objective improving the timeliness and quality of decisions. developments in bi software eventually play the role of improving the overall performance of the organization using them by enabling the company to respond quickly and adapt to changes. it is within this framework that this research has been directed and is alluded to by the hypotheses above. fundamentally, the evaluation of bi software development has gleaned data which shows that bi software vendors have made significant improvements with their product offerings. developments in information delivery, userinterface, reporting, analytics, and data integration are evident with bi vendors examined for the purpose of this research. bi vendors have also seen developments in their possession of market share 51 among these software providers. it has been observed that sap business objects has the leading market share as opposed to other competitors. majority of these bi vendors also provide multiple licence options in the market. generally bi vendors do make significant developments with bi software over time and this they have all recognized is necessary to ensure competitive advantage. with regards to the intelligence cycle, one can allude that few are lacking much in data collection and dissemination, very few are supporting analysis duly, but all bi vendors used for the purpose of this research fell short on the planning and direction phase. based on the findings it is being suggested, further investigation of all bi software vendors is recommended with an in-depth analysis of ci cycle phases based on the enhanced evaluation criteria as well as newly approached analysis and evaluation of recent bi developments, present market shares and pricing structures is suggested for further studies. a further analysis of bi market share for 2008 should be carried out to reflect the presentday situation. the research will provide further details concerning the developments that have been made in bi software among a select group of vendors, the extent to which the software provided by these vendors cover the areas which comprise the business intelligence cycle. it will also further highlight the new developments that have taken place with the software compared to previous release by vendors, the market share of the software and the market that exists for these providers. the objectives of this research were inclined towards analyzing bi software available in the market as well as tracing the developments that have taken place within the sphere of bi software. specifically, the improvements which have taken place over the past five years, determine the compatibility of bi software to the phases of the intelligence cycle, determine subgroups that bi software vendors may be classified as and assess the changes that these bi vendors have made based on the new upgrades that are announced at intervals. the empirical and theoretical research has revealed a number of findings as it relates to the developments in bi software. it has been deduced that of the selected bi vendors used for his research, most satisfy all three phases of the cycle, except that of planning and direction. data collection, analysis and dissemination were applicable to all vendors from a satisfactory basis to excellence in terms of compatibility with the phases. the research has also revealed that bi vendors have made significant improvements in data integration, information delivery, analytics, user interface and reporting. bi vendors are therefore cognizant of the fact that innovation plays an integral role for survival in the bi market. assessment of the developments in bi software has been propelled by the need to create cost effective products for the various users groups of their software. as per the analysis of the empirical findings of only (10) bi vendors due to time constraint, we identified that sap business objects followed by information builders, ibm congos and astragy excel in data collection phase; sas institute and qlikview are the best in analysis; sap business objects and ibm congos surpass in dissemination phase. it should be noted that astragy was evaluated along with other vendors though it does not provide any bi functions but only provide common functions for supporting the ci cycle phases. besides, it is made obvious that analysis phase is not supported in a good enough way by bi vendors basing on the total average score for all bi software for analysis (2.9) compared to the total average scores for data collection (3.16) and dissemination (3.67). besides, the empirical findings helped to identify that bi vendors introduce their releases with new developments each year. by tracing and comparing the developments of all (10) vendors, we came to a conclusion that all bi vendors, irrespective of whether it is a leading traditional vendor or small innovative bi, follow the same tendency in introducing bi enhancements by striving to make its software cost-effective, simpler, faster and flexible for use, scalable to manage increasing amounts of data in businesses, accessible to employees at all levels of organization. moreover, most of the vendors introduced a support for heterogeneous environments and data sources from a variety of vendors. in addition, the analysis of bi software market share, customers and pricing strategy in the empirical findings revealed that sap business objects had the largest bi market share of 26% percent as of 2007, followed by sas institute, ibm 52 congos and microsoft. hence, further analysis of bi market share should be carried out to reflect the present-day situation. the analysis of customers` segments showed that almost all vendors deliver its bi software to enterprises and sme businesses, but for microstrategy that work mainly with corporate segment. the investigation of bi software pricing strategy identified that majority of bi vendors employ flexible or multiple choice licensing models along with traditional licensing as nameduser and cpu-basis. some of bi vendors as sap business objects, ibm, microstrategy, sas and microsoft also support saas pricing model. yet, more detailed analysis of pricing structure and actual cost ought to be made to create a much clearer picture of bi software market. finally, as per the results of the software evaluation, based on the overall scores of ci cycle phases, bi software can be classified into five groups: advanced, competent, partially competent, inadequate and absolutely inadequate. sas institute and microsoft are positioned in the group of competent bi software; sap business objects, ibm congos, information builders and qlikview are included in the group of partially competent bi software; and finally, microstrategy and actuate are placed in the group of inadequate bi software. the analysis of empirical findings identified that there is not any bi software, at least among the software tested that could be positioned in the advanced and absolutely inadequate category. moreover, qlikview and tibco spotfire with its in-memory analytics are suggested to term as business analytics software due to its distinction with traditional bi software and non-adherence to the entire bi cycle. accordingly, the objectives hereof were fulfilled through the theoretical and empirical findings as well as analysis of the empirical findings. in conclusion, further investigation of all bi software vendors is recommended with an in-depth analysis of ci cycle phases based on the enhanced evaluation criteria, as well as newly approached analysis and evaluation of recent bi developments, present market shares and pricing structures is suggested for further studies. references aberdeen, g. 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(2008) evaluating business intelligence software testing the ssav model, working paper, blekinge institute of technology, sweden. suppiah, s (2009) vendors in gartner's bi magic quadrant 2009. retrieved from http://www.gartner.com/it/page.jsp?id=500 http://www.evaluation.com/ http://www.aurorawdc.com/whatisci.htm http://www.businessweek.com/technology/content/mar2009/tc2009032_101762.htm http://www.businessweek.com/technology/content/mar2009/tc2009032_101762.htm http://dssresources.com/history/dsshistory.html http://www.pcmag.com/encyclopedia_term/0,2542,t=bi+software&i=38583,00.asp http://www.pcmag.com/encyclopedia_term/0,2542,t=bi+software&i=38583,00.asp http://www.realitysoftware.ca/services/software-development/business-intelligence/ http://www.realitysoftware.ca/services/software-development/business-intelligence/ http://www.sap.com/sapbusinessobjects http://www.sas.com/ http://www.sas.com/ 54 http://www.networkworld.com/news/2009/0129 09-vendors-in-gartners-bi-magic.html, on 0520-2009. thierauf, robert j. (2001) effective business intelligence systems, quorum books, westport, usa. the chartered institute of management accountants (2008) improving decision making in organizations: unlocking business intelligence. retrieved from www.cimaglobal.com, on 2009-02-17. van grembergen, wim (2001) information technology evaluation methods and management, idea group publishing, hershey, pa, usa. vriens, dirk jaap (2003) information and communications technology for competitive intelligence, idea group inc, hershey, pa, usa. http://www.networkworld.com/news/2009/012909-vendors-in-gartners-bi-magic.html http://www.networkworld.com/news/2009/012909-vendors-in-gartners-bi-magic.html http://www.cimaglobal.com/ problem formulation scope of the paper table 1. research questions vol6no1paper2 kss to cite this article: søilen, k.s. (2016) a research agenda for intelligence studies in business. journal of intelligence studies in business. vol 6, no 1. pages 21-36. article url: https://ojs.hh.se/index.php/jisib/article/view/140 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a research agenda for intelligence studies in business klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article a research agenda for intelligence studies in business klaus solberg søilen department of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se received 5 january 2016; accepted 19 march 2016 abstract this research paper defines the scope for a research agenda for competitive intelligence (ci), market intelligence (mi) and more generally for intelligence studies in business. respondents in the survey defined the scope to include analysis, traditional phenomena or problems, new phenomena, transor cross disciplinary studies, methodological issue and industry specific studies. respondents were also asked to come up with terms for a good definition of the study. we found that existing definitions of ci in use are overlapping with definitions of other more established fields of study, like decision sciences and marketing intelligence. respondents agreed that it’s practical to define the study in terms of understanding the external environment. in the discussion a parallel is made to the notion of surrounding world analysis and stevan dedijer’s ideas about social intelligence. a broad discussion leads to a renewed interest for disciplines studied by the humanities as we show what has been lost in the development of the social sciences. implications are shown and future studies suggested. keywords business intelligence, competitive intelligence, intelligence studies, market intelligence, research agenda 1. introduction 1.1 a brief historical perspective deshpande and webster (1989, p.1) remind us that “when drucker (1954) first articulated the marketing concept, he noted that marketing was not really a separate management function but rather the whole business as seen from the customer's point of view.” in much the same way today the disciplines studying information and intelligence have chosen a particular point of view of a particular department (marketing), of a particular technology or service (big data, business intelligence and data-as-a-service, or daas) or from the question of competitive advantage (intelligence studies (is), whether it’s state or business) or strategy, which could be called the outside view. the problem is that there are many views or perspectives studying the same phenomenon, and to a large extent their respective adherents or researchers do not read each other’s work or refuse to see the phenomenon from any perspective but their own. we have created a scientific landscape of compartmentalization and overlaps which has now mainly become a disadvantage to further understanding. instead of tackling the methodical challenge, focusing on the notion of understanding as opposed to the promise of theory we instead end up feverishly hunting for the next management buzzword which only confirms the symptoms. it wasn’t always that way. the competitive advantage issue is an age old perspective going back in europe to the foundations of the first city states (venetia, firenze) and before that in asia to the foundations of nation states and empires (the mauryan empire, the state of wu, the state of qin), with contributions from men like marco polo, machiavelli, kautilya, sun zi and han fei zi. the same question is asked again during the industrial revolution by adam smith and in modern times by michael porter (solberg søilen, 2012, p. 17). as a discipline intelligence studies journal of intelligence studies in business vol. 6, no. 1 (2016) pp. 21-36 open access: freely available at: https://ojs.hh.se/ 22 starts as state intelligence with men like r.v. jones in britain in 1939 and sherman kent in the usa, and as a function relevant for business with stevan dedijer in sweden in the early 1970s (solberg søilen, 2012, p. 19). on the macro level the discipline may be said to have a twin sister in the study of geopolitics where we look at the correlation between history, geography and the notion of power, which survives after the second world war and pops up in the social sciences with the frankfurter school, as critical theory. as applied to the world of international business we often talk of geoeconomics: both are theoretically anchored in evolutionary theory, not as neoclassical economics in the study of physics. the discipline coined geopolitik was developed by the swedish political scientist rudolf kjellén (1864–1922), who was influenced by the german political geographer friedrich ratzel (1844–1904) who again was influenced by scholars like the prussian geographer carl ritter (1779–1859), alexander von humboldt (the founder of modern geography) and the german historian leopold von ranke (1795–1886) (solberg søilen, 2012, p. 21). fast forwarding to today, the difference between information science in business, businessand market research and intelligence studies is mainly one of perspective, scope and dates and less about content and scientific method. intelligence studies in business sees the organization much like an intelligence organization, an offspring of the study of state and military intelligence, searching for significant pieces of information that affect the business as a whole, not searching to see how selected experiences fit into oversimplified theoretical models. when adam smith wrote his famous book in 1776, this compartmentalization did not matter as political sciences then was an integrated part of economics and business studies in what is called political economy. long before that, with plato and aristotle, it was all studied as philosophy, as opposed to the natural sciences. the compartmentalization of knowledge in the social sciences has since become an advancement to the body of knowledge about man as well as a hindrance as the method and logic continues to dominate at our universities, despite excellent scholarship in the 1970s and 1980s that shows that this is an intellectual impasse (see e.g. hodgson, 1988). it’s with theory as with great empires: their glow continues long after they have been surpassed (for example, england in the 19th century and the us in the 20th), an observation which itself fits into an evolutionary approach. at the end, what decides the value of these different perspectives is to what extent they can show to be of relevance to practitioners. academics must from time to time ask practitioners to what extent their work is being used and has positive effects for companies and for society at large. drucker hardly wrote any articles for scientific journals, but he was always a favorite among practitioners, simply because his books were relevant. thus it is real relevance that social science disciplines should strive for, not “academic impact,” or the amount of articles or to what extent they are being cited by colleagues. the idea that basic research (as opposed to applied) is of great value in the social sciences is still to be proven even though it is true that the same method continues to do wonders for the natural sciences. to know what to study researchers need to agree on what problems are of importance. the natural way to do this is to ask practitioners and academics alike what areas or problems they think deserves more attention based on unresolved problems they observe and are confronted with. solberg søilen (2014) did a survey of what content readers of the journal of intelligence studies in business (jisib) wanted to see. it said that readers are looking for more case study material. the survey also found that there is an even balance between those who think there is too much and too little technical content in the existing literature. some readers also want articles in languages other than english. however, can these findings be used to draw general conclusion for the whole field of intelligence studies in business? we think not. thus another more ambitious survey was planned to define a research agenda for the discipline as such, and thus identify the research gap. 1.2 an introduction to current literature wright and calof (2006) study current ci practices among different cultures. the same authors did an evaluation of the study of the ci field two years later (calof and wright, 2008). solberg søilen (2013) presented an overview of articles on competitive intelligence in jcim and cir, two earlier ci 23 journals. teo and king (1996) did an assessment of the integration of business planning with information systems, and teo and choo (2001) did an assessment of using the internet for ci. none of these articles tackled the question of defining a research agenda. in more established business fields that also attract more research, similar projects to evaluate the field and lay out research agendas are more frequent. for example, deshpande and webster (1989) defined a research agenda for organizational culture and marketing. guest (1997) did the same for human resource management (hrm). closer to our own field, varun grover (2001) defined a research agenda for knowledge management (km), rumelt and teece (1994) did the same for business strategy, gibson et al. (2004) did this for business intelligence (bi) and almashari (2002) defined an agenda for enterprise resource planning (erp) systems. intelligence studies can be divided into a private and a public side, or one related to business and the other to the affairs of the state. research agendas in military and state intelligence have a longer history and have come further as a discipline. landon-murray (2013) presents a literature inventory and research agenda for intelligence studies. marrin (2005) argue, much like calof and wright (2008), that in ci intelligence should continue to be done within the parameters of other disciplines. landon-murray (2013) argues that “previously, students likely to pursue careers in the intelligence field completed liberal arts degrees—commonly political science and history at the undergraduate level and international relations at the graduate level” (p. 745) and that this corresponds to demand by practitioners: “intelligence organizations like the central intelligence agency (cia) do not want graduates who have been educated to be ‘intelligence specialists’” (p. 748). dorondo (1960) argues that intelligence courses should teach broad concepts from a variety of academic disciplines (like economics, political science and sociology) and issues, with less focus on intelligence specializations. meredith et al. (2012) argue for greater engagement between academia, bi vendors and bi customers, with an outline of a research agenda. dhami et al. (2015) present a list of problems that deserve more attention. on the top they place methods for assessing and improving forecasting accuracy and examining communication of uncertainty using verbal and numerical probabilities. andrew (1997) wants to see greater intelligence sharing with foreign agencies, which was also what happened later. a similar development is occurring with daas today for private organizations where organizations are starting to rent information instead of buying it. we do not have to agree with all suggestions presented in these research agendas as much will depend on the industry we are in and on when the suggestions were made (many are quickly outdated). to be representative, surveys on research agendas try to gather data from a broad group of users and researchers. others base their assessment on what has been done previously in scientific journals, thus what seems to be missing, or what authors themselves say are missing. we shall attempt to do both here in this paper. 1.3 research on intelligence courses offered there is a positive correlation between the number of researchers in an area, the number of courses and the amount of research produced, even though the causal relationship is less evident. again we will have to refer to research done for intelligence studies. according to campbell (2011): “between 1985 and 1999, the number of non-government higher education courses on intelligence increased from 54 to between 200 and 300” (p. 308), “by 2005 the number of unclassified courses offered within the military intelligence community had grown to 1 417, with national security agency (nsa) courses making up 46 percent of this number” (p. 309) and “the number of non-government courses in intelligence has now grown to over 840, with more than 100 civilian institutions providing some form of intelligence education” (p. 309). there are no phd programs in intelligence studies, except for at the american military university, but it is possible to defend a thesis in intelligence related topics both within business studies and computer sciences in 24 many countries. see for example solberg søilen (2004). in comparison, courses in ci and intelligence studies in business are probably far fewer even though no similar survey has been published. an unpublished survey from 2004 in sweden shows that there were 23 courses in omvärldsanalys (which translates to “surrounding world analysis”) at swedish universities and colleges. however, most courses today are offered by business consultants, like the strategic and competitive intelligence professionals (scip) and the institute for competitive intelligence (ici). 1.4 research questions this article is a continuation of the article “a place for intelligence studies as a scientific discipline” (solberg søilen, 2015), where focus is on what the journal’s readers want to see articles about. the article also shows what many ci practitioners think makes ci unique. the examples show that the content they list is not exclusive to ci. however, the article also suggests that there are problem areas within intelligence studies in business that are not covered by other studies and suggest that these be further investigated to build a research agenda for intelligence studies in business. the article suggests that the lack of scientific development in the field is related to how we chose to define it. a working hypothesis is that ci is defined differently by different practitioners and that this is a part reason for the confusion. thus in the survey we asked people to define ci and/or intelligence studies and react to an established definition. in the analysis a number of dimensions are identified in the form of working hypotheses where ci may be said to bridge a gap in relation to other fields of study related to method, perspective, technology, function and actor. in this article we investigate the working hypotheses and identify a specific research agenda by way of a survey. two research questions were formulated: 1. what research do practitioners think ci/is should focus on? (in what areas would you like to see more research?) 2. what definition of ci/is do practitioners think is better and why? (respondents get to react to an established definition) based on these questions three research questions were put in the survey: 1. in what areas would you like to see more research done within competitive intelligence and intelligence studies? 2. what definition of competitive intelligence and/or intelligence studies do you prefer? (how do you define it?) 3. what do you think about this definition: “intelligence studies deals with all the things which should be known in advance of initiating a course of action.” the definition was chosen to extract more information from respondents. the definition from the clark task force of the hoover commission was chosen as it is well established, is wider than ci and is the result of a cooperative academic effort. most other definitions of ci presented are suggested by individual academics or professionals. 2. method data was gathered over linkedin and the jisib mailing list. on linkedin we posted the survey (surveymonkey.com) at the scip members group with a population of ca. 22 000 registered users. the journal jisib has ca. 800 registered users. the time period allowed for responses was three weeks. in total, 270 complete responses were gathered. out of these respondents five deep interviews of 30 minutes each were carried out using skype. these respondents were chosen randomly from different industries to avoid industryspecific interests. the following industries were represented: software, aeronautics, management consulting, pharmaceuticals and academia. 3. data to include data of all responses directly in this paper was not possible due to limited space. instead we publish every 10th answer, shown in table 1. the analysis and statistics are done for the whole set. some shortening of the text as well as language and grammar editing has been done for the original answers. 25 table 1 a sample of data gathered from the survey. r indicates the response number, made up of every tenth answer from the survey. q1 asks: in what areas would you like to see more research done within competitive intelligence and intelligence studies? q2 asks: what definition of competitive intelligence and/or intelligence studies do you prefer? (how do you define it?) and q3 asks: what do you think about this definition: “intelligence studies deals with all the things which should be known in advance of initiating a course of action.” r q1 q2 q3 10 motivations of employees none sometimes we do not take actions, it is more to do with decisions 20 foresight the gathering, analysis and spread of information and knowledge created to support decisions and anticipation it is about more than what is known, it is about understanding and anticipation 30 risk management all activities undertaken to secure and maintain responsiveness to client needs all things cannot be known. there are many variables, unseen and unforeseen and observation biases that come into play. 40 internet of things none none 50 strategic conversation (cf. kees van der heijden) actionable knowledge i miss the bit that you have to act all the time (where inaction is a type of action) 60 cases with quintuple helix ∗ competitive intelligence must interact with three essential elements: (1) the competitive environment that issues weak signals, (2) the mass of information (big data) that includes weak signals and noise, 3) the decision maker that processes and translates the information i don’t agree with this definition 70 veracity of sources ◊ the study of decision-making based on an understanding of the external competitive environment too broad 80 competitive intelligence ci is the process of monitoring the competitive environment it is a general definition 90 intelligence analysis toolsets used in military / government insights for strategic and tactical decisionmaking the definition broadly covers the meaning 100 industry strategy, energy and earth resources competitive intelligence concepts for strategy could cover the concepts 110 science of education the power of creating an opportunity agree 120 decision making process and cognitive bias decision support tool too broad and diverse 130 international research, in "developing" markets. the application of marketing analysis techniques the scip definition works no, the decision may be to take no action. that is a decision not a course of action. 140 consumer products, case studies, stories about success and failure none overly wordy 150 what is the value added of intelligence in business or economics? ci assembles several practices, theories, models, techniques etc. maybe an analogy can be in the wine sector, when talking about "assemblage" the definition is related to early warning. i think this may a distinction from others disciplines. "anticipation" is a key aspect and it needs to be taken into account 160 broader, more external perspective ci is knowledge and foreknowledge about the entire business environment that results in a decision/action this definition is similar to mine 170 in the game area intelligence studies deals with all signals about things which should be known in advance before the organization initiates a course of action, which should alert the organization about an environmental change with a potential impact the definition is good, but restrictive 180 network/platform strategy, applications of activity-based intelligence and other "discovery/data intelligence" methods in ci organizational design/agility and ci. ci approaches for treverton's "mysteries" ∞ rather than existing approaches based on "puzzles" complexity and ci/strategy. more like dr rahul basole is doing with computational enterprise analyticsχ the creation of decision advantage through external observation and sensemaking i don't think the definition is appropriate anymore. it is the product of a legacy of organizational structures, and intelligence targets & methodologies – which have shown to be ill-suited for 21st century problems. furthermore, the definition presupposes the intel customer has the situational awareness and understanding to know when, if, and where they need to make decisions – they frequently don't. 26 190 influence and soft power to act as a catalyst to concentrate all the national and regional industries, universities and institutions to promote the development and defend the global interest of the nation and region it seems to be speaking of the same point i made. 200 measuring the value of ci, actual impact of ci as part of the decision making process scip definition is fine. intelligence to enhance business decision-making and organizational performance to create a competitive advantage. not good enough. focus on understanding the external environment as a factor in the decision making process. 210 information access and reuse of data. knowledge about your customers, competitors, etc. intelligence assessment sounds good 220 ci in the relationship with organizational ambidexterity ci helps the managers to understand the complexity of the competitive environment to make the right decisions. it is too general 230 applying data science to competitive intelligence ci is an ethical and legal way of gathering actionable information it is right 240 data-driven competitive intelligence i see ci as an information management discipline focused on supporting managerial decisions based on data about the market and the competitors. intelligence studies is about how to design these information management processes. too broad 250 more industry specific a tool that helps the anticipation of actions to mitigate failures & crises yes, this is a good definition 260 health and security a process of research, development and innovation for better intelligence yes i do agree 270 daas a broad definition is better agree ∗ the triple helix innovation model focuses on university-industry-government relations. the quadruple helix embeds the triple helix by adding the ‘media-based and culture-based public’ and ‘civil society’ as a fourth helix. ◊ veracity is an open source distributed version control system primarily written by sourcegear llc which integrates not only the artifacts placed under version control in the repository, but also associated data for features such as the integrated bug tracking system and agile “build management” tool. ∞ gregory f treveton is the author of intelligence for an age of terror (2009). in the book treveton explains: “in contrast to puzzles, no evidence can definitely solve mysteries because, typically, they are about people, not things” (p. 18). he suggests that we can normally “know” something based on recent history and perhaps some theory, which factors are important to monitor. this could be applicable, for example, in the case of russia’s inflation rate or whether israel might strike iran. for mysteries the product is the best forecast. treveton also writes about a change from “need to know” to “need to share”. χ rahul basole is an associate professor and director at the georgia institute of technology. his research fuses system science and visualization to study technology strategy, innovation management, and transformation of complex enterprise systems. 4. analysis the following can be said from the 270 responses and the five deep interviews: answers vary significantly. respondents may have misunderstood the questions, maybe due to reading and answering too fast, which may be a problem with e-surveys and emails in general today. for example, respondents sometimes did not write definitions where this is asked for and are more interested in promoting their own ideas about ci in general. this information tells us instead how respondents think about ci, which can be useful, but is less useful for answering the specific research questions. it may also be that respondents think very differently about what ci is. there was no difference in regards to these issues between those who answered on linkedin and those who answered by return email. the discrepancy was just as large between the two sources. a large part of respondents who give definition suggestions seem to have a poor understanding of what a definition is – and what is required of a definition answering instead with what they see ci as being, how they work with ci or how they would like it to be. however, some careful conclusions can be made for each question. 4.1 q1: in what areas would you like to see more research done within competitive intelligence and intelligence studies? data about what is researchers should focus on can be divided into the following groups: 1. analyses, such as foresight, cases with quintuple helix, treverton's "mysteries," 2. 2. traditional phenomena or problems, like hrm, risk management, soft power, measuring the value of ci, information access, 3. new phenomena, such as the internet of things, aas solutions, 27 4. transor cross-disciplinary studies, such as intelligence analysis toolsets used in military / government, industry strategy, energy and earth resources (geoeconomics) and applying data science to competitive intelligence, 5. methodological issues such as identifying and avoiding cognitive bias or publishing more cases, 6. industry specifics or focusing more on certain industries, such as consumer products, and health and security. in summary, the most requested areas requested are: analyses, traditional phenomena or problems and transor crossdisciplinary studies. 4.2 q2: what definition of competitive intelligence and/or intelligence studies do you prefer? (how do you define it?) what elements are emphasized in the definition of ci and is? the most recurring elements are about the individual steps in the intelligence cycle, responsiveness to client needs, actionable knowledge, signals from the competitive environment, relationships to big data, decision makers, strategy, seeing opportunities (“blue oceans”), knowledge and decision making with the entire business environment in mind. the most recurring element in the answers is that it’s about supporting managerial decision and decision-making. this occurs in 33% of the answers. the second most important element is that it’s based on an understanding of the external environment present in 15% of answers. third is that it’s about actionable knowledge/information was included in 11% of answers. other answers suggest that it’s about following the ci cycle, following customer needs, working in a questions and answer format, a combination of detecting weak signals, applying big data and translating it to decision makers, that it’s linked to strategy or that it’s about putting it all together or acting as a catalyst. the problem with the answers from the first question is that it’s an area already covered by other established fields of study. there are several journals on decisionmaking, most of which are related to medicine and health. in scopus there are 4291 articles, books and papers about decisionmaking in medicine and several journals on the topic, 2183 in decision sciences, 1897 in computer science, 1505 in psychology, 1477 in health professions, 1476 in nursing, 945 in business, 931 in dentistry, 852 in economics and 797 in mathematics. the decision-making sciences have their own journals like the journal decision sciences and societies like the decision sciences institute. not only practitioners but even most academics pay little attention to these overlaps. thus scip focuses on decisionmaking in their definitions and material, like when the organization says it “focuses on decision-making, to create competitive advantage”. ci defined on wikipedia also emphasizes decision-making. the second most popular answer, that the study is about the understanding of the external environment, is a unique definition as that notion is not covered by other established scientific disciplines as far as i have been able to see. no other established research communities are looking at this phenomenon today it seems. the third most popular answer, that it’s about actionable knowledge/information, talks about an end product, or the end result of the intelligence process. as such, it is considered too narrow to build the basis for a scientific study. as a curiosity, only a few of the 270 respondents use the term preferred by google in their new bi service, “actionable insights.” 4.3 q3: what do you think about this definition: “intelligence studies deals with all the things which should be known in advance of initiating a course of action.” for the third question we wanted to extract information from respondents by asking them to respond to an established definition. in total, 46% of respondents thought the definition by the hoover commission can be used for intelligence studies and ci. a further 17% of respondents have objections toward the notion of “should be known” in the definition, as they argue that ci is largely about what you cannot know in advance. another 17% think that the definition is too broad and 12.5% of respondents have objections to the use of the term ‘action,’ which they see as significantly different from the term ‘decision,’ which they prefer. 28 5. discussion 5.1 the problem of overlapping definitions the definitions of ci, marketing intelligence and market intelligence are too close and overlapping to be separate disciplines. a comparison of definitions on wikipedia illustrates this (italics added by author): a. “competitive intelligence is the action of defining, gathering, analyzing, and distributing intelligence about products, customers, competitors, and any aspect of the environment needed to support executives and managers making strategic decisions for an organization.” b. “marketing intelligence (mi) is the everyday information relevant to a company’s markets, gathered and analyzed specifically for the purpose of accurate and confident decisionmaking in determining market opportunity, market penetration strategy, and market development metrics. marketing intelligence is necessary when entering a foreign market.” c. “market intelligence is the information relevant to a company’s markets, gathered and analyzed specifically for the purpose of accurate and confident decision-making in determining strategy in areas such as market opportunity, market penetration strategy, and market development.” despite this, ci and marketing intelligence have developed into two separate professional and academic communities with their own groups of scholars, journal and conferences. marketing intelligence has developed within the study of marketing, ci largely on the outside. market intelligence has developed as a hybrid and a parallel to ci within marketing. for comparison we could also add strategic intelligence: d. “strategic intelligence (stratint) pertains both to the collection, processing, analysis, and dissemination of intelligence that is required for forming policy and military plans at the national and international level and to qualities that equip leaders to be effective strategists.” strategic intelligence follows the elements of the intelligence cycle and is directed towards strategy. in the definition from wikipedia it is used for state and military intelligence. however, the term is frequently used in business contexts, as a quick search in any of the scientific databases will show. 5.2 the relationship between fields of study and scientific journals any scientific field of study must be related to one or more scientific journals. if we start from the top, or from a broad perspective, all journal names with the term ‘intelligence’ in the most prestigious scientific database, web of science, are related to the study of psychology. in the database scopus there are others. when we go down to the level of articles 73,381 in scopus are on ‘intelligence.’ of these, 66,448 are in computer science and 38,597 are in mathematics. further down the list comes business with 1450 articles and there are 470 in decision sciences alone. of these, most articles are published in marketing intelligence and planning (emerald) (756), international journal of technology intelligence and planning (inderscience) (224), international journal of business intelligence and data mining (inderscience) (200) and the journal of intelligence studies in business (halmstad university) (46). past and present journals that are outside of the two major databases or non peerreviewed include the journal business intelligence (from 07/01/2003, 6 months), competitive intelligence review (from 1998 to 2001 in wiley-blackwell journals, frontfile content), international journal of intelligence and counterintelligence, and gfk marketing intelligence review. the journal of competitive intelligence and management (jcim) cannot be accessed through university databases at present (property of scip). the number of specific articles published about ci, marketing intelligence, market intelligence and strategic intelligence in each of these journals are listed in table 2. 29 table 2 studies and corresponding scientific journals. the keywords list the fields of study by relevant terms. the first column lists first names of journals in the fields. the figures represent number of articles. at the end there is a summary of articles in each field and a division of classification it is listed as a paper in business, decision science or social sciences. rank indicates the summation of articles. key words journal name competitive intelligence market intelligence marketing intelligence strategic intelligence sum rank decision support systems 50 37 16 21 124 1 journal of intelligence studies in business 46 8 6 19 79 3 international journal of technology management 39 13 3 18 73 4 information and management 23 4 7 16 50 6 strategic management journal 22 4 5 13 44 8 long range planning 20 10 5 25 60 5 marketing intelligence and planning 10 34 42 12 98 2 management science 14 14 9 12 49 7 industrial marketing management 8 13 13 6 40 9 journal of business research 3 10 7 4 24 10 eureopan journal of marketing 0 6 12 0 18 12 journal of strategic studies 0 0 0 21 21 11 scopus (total results) 9185 7473 2890 5633 business 1676 1507 776 1025 decision sciences 876 517 213 507 social sciences 711 592 206 808 decision support systems has the most articles published in ci, but then it has been listed in web of science since 1991. jisib is number two, but published its first issue in 2011. marketing intelligence and planning is not listed in wos, but has been in scopus since 1983. thus based on the age and name of the journal it is no surprise that it is leading in articles on marketing intelligence and is number two in market intelligence, after decision support systems. long range planning has the most articles in strategic intelligence (business context) and has been listed in wos since 1986. considering that jisib, with only four years of publications, is already the third most published journal in these fields we can conclude that the other journals, with far more issues and articles per year, publish a modest number of articles on the subjects of ci, market intelligence, 30 marketing intelligence and strategic intelligence. intelligence studies in business cannot define itself as yet another version of the same, but must be defined as different from other disciplines. in the survey we saw that respondents favored a focus on the external environment in the definition and that this term is not occupied by other studies or scientific journals. this is also the understanding of a much cited article by chen et al. (2002): “competitive intelligence (ci) aims to monitor a firm's external environment for information relevant to its decisionmaking process” p. 1. a suggestion based on the data collected in our survey could be that: e. intelligence studies in business is about how companies study their external environment and how that contributes to their competitive advantage. in an earlier article gbosbal and kim (1986) speak about “environmental intelligence” in the same way. gilad (1989) makes the same distinction between ci, as scanning competitors and markets as opposed to environmental scanning, which is much broader, but also where it is more difficult to add value. when we compare the literature, marketing intelligence is more about the micro perspective, what is going on in the company and the market. only to a lesser degree does it study the macro factors that influence that market (macro-economic, political, judicial, environmental, scientific, technological, social, infrastructural factors). intelligence studies, on the other hand, is just as much about the macro perspective, the factors that the company cannot influence but have a decisive effect on its operations. simply put, it’s about what goes on in the world and how that affects the company’s competitive advantage. it is also about the company perspective, not about the perspective of the state, which again separates it from [state or military] intelligence studies. respondents found the definition of the clark task force of the hoover commission from 1953-55 to be good, but too broad. for the sake of order it’s reaped here: f. “intelligence deals with all the things which should be known in advance of initiating a course of action.” in summary, definition e seems to be the best option when compared to the data gathered in the survey and from the deep interviews. 5.3 setting a research agenda: the broader perspective the suggestions by the respondents in the survey and the deep interviews gave us a list for a research agenda. in this paper, however, there must also be room for a broader discussion where less frequent answers are discussed. the question of a research agenda is ultimately the question of how and where we as employees in companies may learn about the surrounding world that is relevant for the competitive advantage of the organization. gilad (1989) suggests that the irrelevance of much environmental scanning can be solved by looking beyond obvious sources (“be entrepreneurial”), by harvesting the power of the entire company (“be economic”) and by focusing on what specific users say they need (“be essential”) (idem). setting a research agenda is also a question of who can do the job. does it have to be ci experts? are we looking at some sort of super librarian for the web 2.0 age? ci has for a long time been of interest to the library sciences, even though librarians have their own journals and professional societies. can’t we give the whole job to a computer geek? after all business intelligence, big data and the internet of things are mainly studied by engineering types. or, to take a diagonally opposite view, maybe the whole thing can be given to a good social science researcher or a wise man (as in the humanities). after all, for each question we ask about the world there is a set of answers and the scientific methods are the same, shared by all of the social sciences and some of the humanities. the ways we answer these questions gives birth not only to different research agendas but also decides the scientific home of the study. for now, let’s simply acknowledge that there will be different approaches and that some academic groups like bi are more successful scientifically than others. that is largely the result of being more relevant. as for the question of how and where we may learn the most about keeping an organization competitive, there are numerous 31 possible answers, of which many have been suggested in terms of the topics in this survey. if we look to existing theory, much of the literature focus on different flows of information into organizations, starting with the article by gbosbal and kim (1986) focusing on trade publications, suppliers, bankers, consultants and customers. another approach that continues to attract little or no attention in the scientific literature is travelling and reading, maybe in part because they are though to belong to the humanities, the study of history, geography and literature. 5.3.1 travelling as a way to learn about the external environment a good intelligence worker or analyst is a person who has travelled and seen a lot, is well-read and is part of an influential network of people, according to the formula: reading, watching and listening. we must read broadly and in order to watch and listen we need to travel. to identify the macro factors in the larger, international environment, we need to know what is going on in the world because things in the world affect us. this is the perspective of intelligence as surrounding world analysis, as defined by stevan dedijer, but also suggested by respondents in the survey. as such, it is very different from what students learn at university in the social sciences. the intelligence expert should be able to solve the following problem given by a decision maker: “i need to make this decision, now tell me what i need to know to do it correctly.” how do we study and train employees for this task? there are basically two questions; what is it that i need to know and how do i become good at it? the point made here is that the answer to these questions should also decide the research direction of the discipline. it is suggested here that we become good at ci also by travelling and seeing the world. or, recalling the story of drucker in the introduction, we are often better off reading books, instead of reading scientific articles, which tend to give a fragmented and overly theoretical (dogmatic) view on reality. the notion of “learning by travelling” has been a method followed ever since marco polo went on his big journey and wrote a book about it, and peter the great went to the netherlands to learn how to build ships. it was the tradition of the english aristocracy with the “grand tour” and it has been the method of big industrialists, like ferdinand porsche when he visited the us to learn about mass production at the ford factory and when robert bosch went to work with thomas edison in new york. in germany it was and to some extent still is the tradition that young apprentices organized in student unions (burschenschaft) traveled (wanderjahre) for some years before they set up their own shop, much like in goethe’s novel “wilhelm meisters wanderjahre” (see also steer, 2008). in much the same way, state intelligence organizations have thousands of people stationed in other countries and other departments, such as the foreign department, and make sure their employees travel the world on a regular basis if for nothing else than to keep up with current affairs. if this is a relevant direction in reality then it should be so in theory too. still there is little research in this direction. the problem is to a large extent that the neoclassical paradigm, which still dominates studies in business and economics, despite the fact that its usefulness has been refuted decades ago (see, for example, hodgson, 1988). neoclassic scholars consistently avoid topics covered by the humanities, which they see as less scientific just because they are less rigid simply because they belong to another domain of knowledge about human life. in other words, the problem is to a large extent the way we define what is scientific for the study of man. many will argue that intelligence as “wandering around the world” is more fitted as a study for the humanities. in comparison, asian societies have been more inclined to see competitive questions from a broader and more practical perspective (japan in 1960s and 1970s, china today) while western societies, since the 1970s, have come to see travelling primarily as entertainment and personal enrichment (an end in itself). my students have hardly heard about the twin cities of chongqing and chengdu as one of the great industrial hearts of the world, and they are ignorant about wenzhou, where around 90% of global eyewear is made, guangzhou, where around 70% of bags and suitcases for european and us mass markets are made, or any of the other 50 or so chinese niche cities. instead they know (much like consumers) about the brands themselves – not how they are made, or where or who the owners are. the business schools where they go continue to spread a curriculum void of historical parallels, detached from geography, with no real interest in questions of 32 ownership, but filled with oversimplified business models, common sense truisms and gossip about fast fortunes made (success stories). the development of the social sciences after wwii lead to an extreme form of compartmentalization (specialization not being the major problem), of which intelligence studies has also been a victim to the point that it almost annihilated itself as a study with ci. this can also be explained by the study’s false perception of itself, as the topic was driven forward by practitioners, more as a consultancy fashion and a fad then a scientific study. from a consultancy perspective one might say there is nothing wrong with this. as one term gets used up (does not sell) another is introduced, much like when ci consultants exchanged ci with market intelligence and today market intelligence with foresight, much without thinking about the difference in meanings. from a science perspective, however, this is troublesome. 5.3.2 reading as a way to learn about the external environment maybe reading is just another way of travelling. anyway, surfing the internet is not the same thing. it’s an illusion to think that we have become smarter because of the increased amount of data available on the internet. most new data added each day are youtube videos (all those funny cats and dogs), our comments on facebook and twitter, information which is not even accurate or interesting, but appeals to our narcissistic and voyeuristic nature. i will keep this discussion for an upcoming article, dealing with daas and other aas. reading is mostly a missed opportunity. much valuable information and knowledge is only available in books (including e-books) but the knowledge they contain demands time for reading and reflection. we also need to read continuously because we forget continuously. intelligence work is just as much about finding time to become knowledgeable. instead our days are filled with disruptions and multitasking, which basically means doing many things poorly. surfing and sifting through information and knowing where it is is not the same as knowing, much less remembering. for example the nsa knows it has data about future crimes and terrorist attacks, but it cannot extract it, so it does not matter. on the other hand, they have so much data that they can always find something that looks suspicious but isn’t. amazon.com has plenty of data about what i read but cannot tell me what book i want to read next. our open office landscapes and working environments are not made for reading. when we come home we have other (family) obligations. trying to catch up with the world for 5-15 minutes before falling asleep by stacking books on the bedside table is not a solution. the best opportunity many of us have for reading is to do this while travelling: on planes, in cars (audio), in airports and on trains. others try to catch up during summer vacation, but it is mostly a romantic image. disruptions are also the nature of vacations. thus instead of reading we have skimming. instead of knowing we have know-about. instead of building our own opinion we follow those of others who somehow seem to us to know more. we follow management fads like “blue oceans,” co-creation, innovation or csr, simply because it seems a good idea at the time and critical thinking somehow takes too long. of course, most people are too busy being entertained to read anything at all. all of this is no critical of any individual or mankind, simply a reminder of our cognitive limits. there are basically two ways to learn, through our own personal experience and those of others. what we read, watch or listen to depends on what we want to know, for example what industry we are studying, but we can still say something in general about types of sources, their relevance to the questions we face and the degree of trust we can place in their answers. table 3 summarizes these sources of information and how we interpret them. the problem with types of sources is often a tradeoff between trust and relevance. it’s easy and quick to see what is relevant, but it takes time to write it and to make it trustworthy. by the time the product (book) is ready many will have forgotten and moved on to the next big thing. instead we need to learn to wait for the book. popular sources know what we want to know but cannot deliver the answers. their headlines become unfulfilled promises. scientific sources are often too narrow to be relevant, focusing on some narrow correlation. still, we can give some general advice for reading to break with some of our worst biases: try to read in different languages (to get different perspectives), rotate your sources, for example every year (for example, 33 table 3 media sources and trust. source type example type trust relevance scientific books springer-verlag reading very high medium popular books bantam publishers reading high high scientific articles journal of marketing reading very high medium popular articles (including newspapers articles) the economist reading high medium reports, white papers eiu: country reports reading high high social media messages twitter reading/watching low low video and tv programs youtube or cnn watching low low radio programs bbc world news listening medium medium podcasts local radio stations listening low low exchange the economist with der spiegel). break your own search patterns, letting chance chose for you. for example buy books at bookshops where you are more likely to find books you did not know of before. moreover, good intelligence is about the network of people you have access to. informed and resourceful people tend to find each other at the best at places like the world economic forum. linkedin is a pseudo version of a good network, more suited for marketing purposes. being informed is a question of who we chose to listen to, but also who we have access to. besides books, the most important source for intelligence in business is industry reports and country reports, more so than even scientific articles. 5.3.3 industry and country reports as a way to learn about the external environment the longer we have been in a business, the more we know about it (even though there is always a risk that we become blind to solutions because we get stuck in habits). industry experts frequently claim they require no help from ci experts as they do not know the business. this is a dilemma; the ci expert comes with a toolbox but frequently doesn’t know the material he is set to work with. it’s impossible to be an expert on all industries, simply because there are so many and they are so different. at the same time, their numbers are finite and there is some consensus about their classification. the harvard business school (hbs) site lists around 50 different industries on its website, the economist intelligence unit (eiu) site lists about 100 “subjects” (table 4). together they give us an idea about the scope of what we need to know for the competitive advantage of companies. the hbs list consists of: accommodation, accounting, advertising, aerospace, agriculture and agribusiness, air transportation, apparel and accessories, auto, banking, beauty and cosmetics, biotechnology, chemical , communications, computer, construction, consulting, consumer products, education, electronics, employment, energy, entertainment and recreation, fashion, financial services, food and beverage, health, information, information technology, insurance, journalism and news, legal services, manufacturing, media and broadcasting, medical devices and supplies, motion pictures and video, music, pharmaceutical, public administration, public relations, publishing, real estate, retail, service, sports, technology, telecommunications, tourism and transportation. out of fifty-two industries, twenty-four can be classified as production (46%). they represent 41.8% of the papers available on the hbs site. this is of importance for the competitive advantage of nations, which builds largely on our ability to export, a lesson often forgotten (solberg søilen, 2012b). some industries are underrepresented in the number of studies: these include the insurance industry, travel, accommodation (hotels), tourism and medical devices. some divisions are also misleading, like the separation between it (1) and technology (126). the aerospace industry has few studies, but it’s also an industry with few actors. some areas may be said to be overrepresented in terms of the number of reports or information available about them: these include publishing (48), health (106) and financial services (180). the amount of papers says nothing about the quality of information. for the “subjects” listed by eiu, i have divided them into industries, analyses, studies and topics in table 4. the reason for this mix of categories by eiu has to do with the kind of knowledge customers ask for and the specialties of eiu employees. topics are open to larger changes over time, industries less so. as indicated by respondents 34 table 4 eiu subjects. no. industry analysis discipline/study topic 1 automotive benchmarking economics business environment 2 banking company analysis innovation capital flows 3 education competitiveness international relations productivity sovereign credit/risk 4 energy corporate strategy smes and entrepreneurship cities 5 financial services country data geopolitics mercosur 6 food security country risk econometrics commercial research and advisory 7 healthcare credit risk labour consumer goods 8 investment demographics macroeconomics cost of living 9 islamic finance risk monetary policy livability 10 cross border finance and investment forecasting and policy analysis migration currency 11 debt markets predictive modelling regulatory impact china data services 12 oil global trends climate change infrastructure 13 retail indices democracy global economy 14 market entry emerging markets development 15 operational risk eu integration gender 16 foreign direct investment politics economy 17 public policy foreign policy 18 research employment environment 19 scenario analysis evidence-based solutions 20 security in this survey there is a demand for research papers in specific industries. our lists show the scope for such studies. we could also have listed country reports, which besides industry reports are the major focus of eiu, but these are obvious for everyone with an elementary course on geography. 6. conclusions and implications in this paper we identify a research agenda for ci and intelligence studies in business. according to respondents, practitioners and academics should focus on analyses, such as foresight, cases with quintuple helix, treverton's "mysteries", traditional phenomena or problems, such as hrm, risk management, soft power, measuring the value of ci, information access, new phenomena, like the internet of things, aas solutions, transor cross-disciplinary studies, such as intelligence analysis toolsets used in military or government, industry strategy, energy and earth resources (geoeconomics), applying data science to competitive intelligence, methodological issues such as identifying and avoiding cognitive bias or publishing more cases and industry specifics, or focusing more on certain industries, like consumer products, and health and security. respondents think that ci should be defined around supporting managerial decisions and decision-making but in this article we show that this is associated with certain methodological problems, as the area identified is already covered by other scientific groups and journals. the result is a considerable overlap. respondents’ second suggestion is that the definition should be around the understanding of the external environment. this is a better definition from the point of view of defining a unique research agenda. it also corresponds with the understanding of intelligence as surrounding world analysis and the broader definition of social intelligence as defined by stevan dedijer. 35 in the discussion we try to show how the development towards compartmentalization in the social sciences has been to a disadvantage to the development of ci and intelligence studies in business as disciplines. we show how notions like reading and travelling have always been the way companies have learned about the surrounding world and suggest reasons for why this lesson has been forgotten. the implication of this research helps to form some consensus around what kind of problems are interesting for researchers to take on for intelligence studies in business. there are suggestions in the discussion of this paper that indicate that it would be of interest to see a compilation of courses offered in ci and its equivalents around the world. it would also be interesting to see how the tradition of traveling-as-learning continues in companies today. furthermore, it is of interest to better understand how companies succeed with intelligence within specific industries or subject areas. the future of intelligence studies in business continues to lie primarily with its symbiosis with new technology. a generation ago it was the 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(2008). goethe's science in the structure of the wanderjahre. university of georgia press. teo, t. s., & choo, w. y. (2001). assessing the impact of using the internet for competitive intelligence. information & management, 39(1): 67-83. teo, t. s., & king, w. r. (1996). assessing the impact of integrating business planning and is planning. information & management, 30(6): 309-321. f treveton, gregory (2009). intelligence for an age of terror. cambridge university press, uk zhiqiang, zheng, fader, peter, padmanabhan, balaji (2012). from business intelligence to competitive intelligence: inferring competitive measures using augmented site-centric data. information systems research. 23(3): 698–720 varun grover, t. h. d. (2001). general perspectives on knowledge management: fostering a research agenda. journal of management information systems, 18(1): 521. wright, s., & calof, j. l. (2006). the quest for competitive, business and marketing intelligence: a country comparison of current practices. european journal of marketing, 40(5/6): 453-465. page 4 editors note vol 11 no 3 editor’s note vol 11, no 3 (2021) some personal reflections on 11 years of jisib editorial notes and production for now, this is the last issue of jisib. the reason is that funding for open-source journals through nos-hs has been halted for all journals ending in 2022. jisib had financing through 2021. there may be a revival of open-source initiatives and then it’s possible to continue if we can obtain the funds, but for now jisib will be put on pause. jisib came out regularly between 2011-2022, so for 11 years. for eight of these years the journal received funding from vr and nos-hs. nos-hs is the joint committee for nordic research councils in the humanities and social sciences. it’s a cooperation between the research councils in denmark, finland, iceland, norway and sweden responsible for research within the humanities and social sciences. we are very grateful for continuous support received from nos-hs. it has been instrumental for the advancement of open-source publishing in sweden. the journal was started at a time when the interest for competitive intelligence (ci) was declining, during the first decade of the 21st century. bibliometric analysis shows that jisib has been the primary outlet for scientific articles on ci for the past decade. most articles have been in the border between ci and business intelligence, or more specifically between software and web-solutions, web-intelligence, and social media intelligence. some articles have been in market intelligence and other closely related areas. in france there has been a continuous interest for “intelligence economique” and in sweden “omvärldsanalys”. we have also seen new areas emerge and some areas increase in popularity, like collective intelligence, foresight and insight (competitive and market insight). however, the core of the content is much the same despite this relabeling. it’s still about processes for providing decision makers with need-to-know information. at the beginning, the editorial note basically just presented the content of the issues. as such, the first editorial note written was a general introduction and a welcome to the new journal (vol 1, no 1, 2011). the second editorial note speaks of the importance of open access journals for the free and equal advancement of science to people around the world (vol 2, no 1, 2012). we could have gone with private publisher too, but a majority of the editors were convinced that it was important for science to be free and easily accessible and that this was the future. we still believe so. in the third editorial note (vol 2, no 2, 2012) the focus was on different ci conferences as contributors and sources of articles for the journal. the journal has always relied on these conferences for good and relevant content. the next editorial note is on the journal being indexed by ebsco, and applying to get indexed by others, first web of science (vol 2, no 3, 2012). the early days of the journal focused on reviewing what had already been done. typical of this was my article “an overview of articles on competitive intelligence in jcim and cir” in that issue. this was also a time when i was able to work closely with my old mentor per jenster from cbs. we published “the relationship between strategic planning and company performance – a chinese perspective” as a result of per having moved to china and working at ceibs. the sixth issue of jisib featured articles by prolific contributors such as a.s.a. du toit and sheila wright (vol 3, no 2, 2013). many contributions in the next issue came from the 2013 scip conference in south africa under the leadership of a.s.a. du toit, the journal’s editor for africa (vol 3, no 3, 2013). in 2014 we were indexed by scopus and this was noted in the first editorial note of 2014 (vol 4, no 1, 2014). in the next issue i published a so called spot-check, a market survey to see what readers and users prefer to see as content. much of the challenge in theory is often to align the reality of intelligence with theory, to make sure they follow each other and are in sync. if not, theory tends to become irrelevant. this resulted in “a survey of users’ perspectives and preferences as to the value of jisib a spot-check” (vol 4, no 2, 2014). the last issue of 2014 presented some case studies, a gap that had been identified in the spot-check in the previous issue. this last year jonathan calof and i had been working with sap to try to write some large cases on intelligence studies, but it will probably take another year or so before we know the results. journal of intelligence studies in business vol. 11, no 3 (2021) p. 4-16 open access: freely available at: https://ojs.hh.se/ 5 the first issue of 2015 presented papers from two conferences (vol 5, no 1, 2015). the second issue presents articles from the eckm 2015 conference. vol 5, no 3 marks a landmark as this is the first issue after the design facelift made possible with the nos-hs grant (vol 5, no 3, 2015). the editorial note presents some self-reflection on intelligence studies as a discipline. my article is entitled: “a place for intelligence studies as a scientific discipline”. in the next issue i take one step further with “a research agenda for intelligence studies in business”. the next issue, no 2, is on user perspectives on business intelligence. my own contribution here is: “users’ perceptions of data as a service (daas)”. i was never a tech guy so could not make many contributions in this area. instead, i have written numerous articles on the user perspective, related to marketing and customers’ expectations. my latest contribution there was published last year on how households look at central bank digital currencies: “household acceptance of central bank digital currency: the role of institutional trust”. for the last issue of 2016 i did an update of the problem studied in my doctoral dissertation on industrial espionage: “economic and industrial espionage at the start of the 21st century – status quaestionis”. in the first issue of 2017 i tried to gather my ideas about how intelligence is related to geopolitics and founded in biology. it was based on the ideas expressed in my book “geoeconomics”. the article is entitled “why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies”. it summarizes the way i still teach intelligence studies in sweden today under the swedish term “omvärldsanalys”. i have given this course for 20 years now, first at bth then later in halmstad, and as a guest lecture at other universities. in the second issue of 2017 i revisited a favorite company: ericsson, this time doing a comparative case study with another major swedish company, sca: “why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company”. among a series of conclusion, the article shows a major obstacle to good and well-functioning intelligence organizations: the all-knowing manager. many managers simply do not listen to good intelligence because they think they know best. the issue deals with “how companies work and fail to work with business intelligence”, as the editorial note suggests (vol 7, no 2, 2017). no 3, 2017 has an even closer look at the implementation of new technology, as in the editorial note title: “how companies succeed and fail to succeed with the implementation of intelligence systems”. our article in that issue is called “the perception of useful information derived from twitter: a survey of professionals” and shows that a large majority of managers find twitter useful, but only half think that those who tweet have useful things to say. “it may be that intelligence professionals can find valuable information about markets, industries, and products without the person tweeting having any valuable information: “it may also be that ‘the value of the information lies in the things that are not said. (…) intelligence professionals know that corporate tweets come from communication departments and professionals. they may know how to read what they see or what is between the lines, so to speak. in that lays the valuable information’ however user of twitter think that overall those they are following have useful things to say. about 22% think that they get their most valuable information from twitter. this may seem low but is rather significant. however, it may also change with time”. the survey was done during a time when twitter was more popular. these studies are a bit like fresh milk and need to be updated regularly to be relevant. the next editorial note is entitled “the disciplines of management and it have indeed merged: new empirical data” (vol 8, no 1, 2018). by this time social media intelligence had become dominating for all kinds of market intelligence. gathering information is now mostly about forms of web-intelligence. intelligence and social research are now closely related (vol 8, no 1, 2018). we see this in the next editorial note title as well, “social media intelligence” (vol 8, no 2, 2018). this issue had, for the first time, an editorial note that looks backwards and compares previous issues to confirm the strength of this change in how companies gather information. the next editorial note is named “why you should be interested in intelligence studies” (vol 8, no 3, 2018). in it i argue for what i think is the core of intelligence studies: “it is suggested that the difference between information science in business, businessand market research and intelligence studies is mainly one of perspective and scope and less one about the content of problems or scientific methods used. intelligence studies in business see the organization much like an intelligence organization, the offspring of the study of state and military intelligence, where the aim is to find information that affects the business as a whole (as in ‘surrounding world analysis’ or in swedish ‘omvärldsanalys’). a study of intelligence studies – management information or information sciences that does not explain which outside events affect the business becomes sterile and uninteresting. the essence of intelligence is to scan the world for relevant developments, to find out what is going on that afftects our organization (need-to-know, strong signals, trends). how 6 to do this should be the focus of the subjects’ research agenda and what sets it apart from other disciplines studying information in a business context.” p. 4 there is also a summary of my conviction about what has gone wrong in the study of business in general and for the study of information in particular: “sometimes this goal seems far away as when reading about how a new technique is applied to an industry in a specific market. sometimes i miss hearing about how basic methods like traveling to foreign countries (the spirit of marco polo) and reading books may be the best methods for understanding what affects an organization. we must always remember that the technology is only there to facilitate the process, it never explains why things happen and it seldom helps us in the actual understanding of the data. statistical analysis does not explain why or how things occur: at best it summarizes what has happened. authors of articles i read in other journals too often miss the difference between correlation and causation. what is then so special and different with intelligence studies? intelligence studies at the present at least are less a series of theories than a new perspective on (micro and macro) economics. intelligence studies is not exclusively about management, but also about economics as it’s just as relevant for how nation states become competitive. it is the suggestion that competitive organizations of all sizes are best organized as intelligence organizations, focusing on the process of gathering, analyzing and delivering need to know information to decision makers. this is a different way of looking at organizations and what they do. competitive organizations today all basically work with information. it is how they work with this information that decides whether or not they will succeed. the importance of building a formal intelligence organization was realized more than two hundred years ago in the military domain with the prussian and russian armies. in the study of business this was first realized with the shift in thinking that came with the information age and the development of computers, the realization that competitive advantage is more about what you know than what machinery you own or how much money you have in your accounts. if the introduction of it represented the 1.0 version of this development, then the introduction of the internet represents the 2.0. many saw this development coming. some experts thought that it would not only lead to intelligence studies being introduced as a special function in the organization but that we would see the implementation of separate departments of intelligence, or that the whole current division and structure of business activities, into marketing hrm, finance, would be abandoned for functions of intelligence gathering. when this did not materialize many started to question the value of the approach all together. many still think that the approach failed, that the perspective has passed and been surpassed by other subjects and disciplines. i disagree. even though things have not happened as quickly as many expected or hoped, we are still moving in that direction now more than ever. b2b digital marketing is a good example. today it is less about push marketing and sales and more about gathering and distributing valuable information to potential customers. when customers see that we are knowledgeable not only about our products but also about the industry we are in, they start to trust us and we are able to build a customer relationship. this is not only changing how b2b marketing is done, but also the competences needed to succeed in b2b marketing. on the state or macro level we are living in a period of (neo-) mercantilism and geoeconomics where intelligence is key. the states that are succeeding economically today are countries like china, singapore, and south korea, but also norway. these are representatives of state capitalism, not free market liberalism. the individualist, liberalist model supported by neoclassical economics and its foundation in the writing of adam smith (not always fairly interpreted, so i prefer to call them the marginalist school), walras, marshall and samuelsson, have greater difficulty convincing readers today. as piketty showed in his vast empirical project about capital, their (our) societies led to an extreme wealth being assembled at the very top with very little trickle-down effects. when the crises came it was the rest of society that had to take the hit, while the elites bailed themselves out to save a dysfunctional system. after a period of prosperity, which lasted for some four generations (and was only extended during the past two generations through massive debt), the populations in the western world are experiencing a decline in their standard of living. these causes were all missed by the marginalist school whose members have been advising governments for more than half a century. the consequences of these policies have been massive protests and disbelief almost hatred of their own elites as in the us, but also in france, the uk and italy. the point is that our leading social science paradigms and especially our economic and management theories that brought us here by not being relevant and, worse, by supporting the wrong policies; regardless of the good intentions, which many of my colleagues even doubt. mainstream economics combined with too narrowly and fragmented studies of management obsessed with a method of small empirical investigations have become the 7 supporters, not only of an elite – the status quobut more worryingly of an uncompetitive society. now, for business studies that is almost what we should call a contradiction. our reigning business theories and research are making us less competitive. the new economic powers in the east have copied what has been done well in the west, but it is unlikely that they will copy our leading social science paradigm. it is the message china sends out when it says “…with chinese characteristics”. chinese leaders are following the thinking of drucker, schumpeter, and michael porter; more so than the winners of the nobel prize in economics and their schools of thinking. they are not reading our thousands of small business journals, even though their own scholars are taking a larger part in the work of running them and contributing to them. instead they are first and foremost inspired by their own values, their own history and their own thinkers of strategy and philosophy. china is already a superpower of intelligence gathering, which they see as essential for strategy. not only have our theories of political science been contested, but there is now clear critic of western moralism. there are hardly any independent thinkers outside the western world who believe in the good intentions of western political and economic interferences anymore. as we in the west have failed to keep up the living standard of our middle classes (our promise to the voters) “eastern arguments” are starting to convince a large part of our own populations in the west. the failure of the western world to compete becomes a confirmation of the weaknesses of our strategic thinking (the weakness in our political system to make plans), and in our ideas which at the end is a critic of our reigning social science projects. eastern ideas will be closer to practice. the west is left with a number of paradoxes. for all our interest in strategy during the past two decades we have no strategy, no long term thinking and no major infrastructural projects. instead we are consumed with our immediate problems and crisis handling. we are so obsessed with the critic of china as a dictatorship that we refuse to see that they are undertaking the largest infrastructural project in world history (the belt and road initiative, or bri), that their mercantilist ideas are engulfing our markets but also helping to improve the living standard of people living in the developing world. our media is full of stories about chinese exploitation in the developing world, which also exist, but forgetting that exploitation even slavery used to be our specialty for centuries and the hallmark of the british empire. now, what does this all mean for business studies? it means we have to search for other paradigms other than the existing one if we want to become competitive again. we have to become more interested in what is actually going on in the world, more curious. this reality must be led by business disciplines.” after this rather long explanation of the context of the study it’s back to essentials in the next issue, as the editorial note is entitled “developing new models for intelligence studies”. it says “the aim of any social science is to develop theories and/or models to better understand the business reality. we are happy to see that a majority of contributions this time do exactly that.” very few articles in fact take this seriously, but in this issue we see a few attempts at least. the bigger question is also to what extent this theory building is possible in the social sciences. most contributions are attempts. it’s quite possible that the social sciences are best treated as an art, as peter drucker suggest. in the issue (vol 9, no 1, 2019) i also write an article entitled “how managers stay informed about the surrounding world”. it’s out of this wish to be practical and useful. it’s an important question for intelligence studies and one that has to be frequently updated empirically to be of value to managers. the conclusions were quite telling, i think: “• no one said they read books • new media companies are dominating as providers of competitive information: google, youtube, linkedin, facebook, twitter • people watch tv news first of all, to the extent that the content is available on youtube • trade shows are a major source of information • radio is not a significant source of information anymore, with the exception of in places like the african continent and to a certain extent in france • humint is still considered highly relevant for information gathering, on all levels and across organizations. this includes “coworkers and colleagues”, but also gossip and “friends in the media”. • many managers say they get their best information through emails, from google and the act of googling. this makes google llc the single most important source for competitive intelligence. • a number of reports are widely popular, for example from oecd, imf, and the world bank, but also those that are distributed by the major consulting companies. • most managers read a combination of their local and/or national news and international news. • the most popular sources offline are the economist, wsj, and ny times.” p. 32 8 at this time there was a strong notion among practitioners that “open source is mostly noise”. ben gillad, one of the founders of ci, is among those who raises his voice often on this topic, as with his recent book “the opposite of noise: the power of competitive intelligence“ (2021). it may be because of noise that managers are willing to pay for good information because searching in open source material is often found to be a waste of time, literary. there is good material on the web, but it takes too much time (and training) to find it. in my above-mentioned article, i suggest an intelligence model that takes this noise into consideration, inspired by the shannon–weaver model of communication1. this is shown in figure 1. it suggests that managers’ intelligence set (what they know) is a function of reading, listening and watching disturbed by noise in the form of entertainment, other work activities and pauses and nonproductive activities over time, corrected for the individual’s ability to remember (memory retention) and to use/implement of what they have learned. i called this the manager’s model for staying informed. around this time collective intelligence was a hot topic and the next editorial note was entitled “a deeper look at the collective intelligence phenomenon”. my own review article was called “making sense of the collective intelligence field: a review”. it concluded that “the collective intelligence field is valuable, truly interdisciplinary, and part of a paradigm shift in the social sciences. however, the content is not new” p 6. this was later the start for a major bibliometric research project with some colleagues that resulted in an article that has just been accepted in technological forecasting & social change entitled “understanding the structure, characteristics, and future of collective intelligence using local and global bibliometric analyses”. it basically shows who are the major contributors, what academic tribe they belong to and where the study has been going. the next editorial note is entitled “the argument that ‘there is nothing new in the competitive intelligence field’” (vol 9, no 3, 2019). the reason for writing this somewhat provocative piece was that many ci professionals who had been around for a while saw nothing new in ci and complained about it. in the editorial note i explain that “another way to explain this development is to say that ci has evolved, thus is no longer the same”. the problem, i think, is that experts were trying to check up on what they did, if it still existed, unwilling to see that the field had moved on and become something else. what was this new form? i suggest that intelligence studies now is more about “data mining, search engine optimization, social media marketing and digital marketing in general.” vol 10, no 1, 2020 was entitled “on the 10th anniversary of jisib: reflection on academic tribalism.” it was the 10th anniversary of the journal. in the editorial note i use the possibility to address the problem of academic tribalism for the development of science: 1 the shannon model has as its origin a model by h. nyquist (1924) who uses “intelligence” instead of “information”. figure 1 the manager’s model for staying informed. 9 “the unnecessary division of networks that look at the same phenomenon is sometimes referred to as “academic tribalism.” academic tribes become a barrier to learning and this can result in closemindedness. this is also according to my own experience. academic clustering is a similar mechanism whereby graduates from one institution favor those who come from the same institution, but there are also those universities that systematically refrain from this. among these is harvard university, which seldom hires their own phds, or so i have been told. if so, that is probably better for the progress of science. where is it meaningful to draw a line between academic groups then? everyone will agree that the natural sciences are quite different from the humanities. between psychology and business though there is much overlap with psychology in business. between accounting and management, a good understanding of how to manage a business requires the knowledge of income statements, balance sheets and how to set up a cash flow analysis. one way to think about division is if the method is different. according to this criterion most social scientists should be able to do each other’s work, and subsequently go to each other’s conferences. another meaningful division is based on experience and the depth of specialization obtained by the discipline. this criterion is less precise. i do not pretend to have the answer, but i think it’s a pity that all these tribes exist, with their own buzzwords often studying more or less the same phenomenon, with the same methods. what distinguishes intelligence studies from other tribes is, in my opinion, first of all that we see that the private organization is better organized as an intelligence organization, with focus on information gathering and analysis. it has less to do with departments of marketing, hr or accounting, even though the one does not exclude the other. another way is to see the intelligence organization as a superstructure, a layer that exists above all functional departments where the aim is to achieve a competitive advantage through better information. in this respect the need for ceos is not unlike those of ministers of state. now, is this perspective so radically different that it deserves its own tribe with its own journal and conferences? that is the important question. and in some way, i cannot help but think that learning would be better without them, that is, it would be better if it was all one big interchangeable group, going to one another’s conferences, and writing for each other’s journals. science would benefit from it. from time to time i have also peeked over into other groups and joined their conferences. what is astonishing especially for an outsider is that you are immediately confronted with a pecking order that is related to who has been there the longest and published the most in the group. this cannot be an advantage for the advancement of science, i tell myself. but, then again, pecking orders seems to be the rule rather than the exception for most social creatures, not only chicken.” p. 4-5 academic tribalism is probably a major reason why the social science are not moving forward in the way many had expected, helping organizations to solve practical problems and making them more competitive. our job should not be to produce as many articles as possible, or to gather as many citations as possible from google scholar but to try to be relevant, that is of real use. this was easier before when many professors were also business consultants and the pressure to publish in journals was lighter. vol 10, no 2, 2020 is entitled “the impasse of competitive intelligence today is not a failure. a special issue for papers at the ici 2020 conference”. the editorial note is a continuation of the previous under the title “the argument that ‘there is nothing new in the competitive intelligence field’”. this was to show that there is a problem, but that that problem is more in the way we study these subjects, the methodology. i start with a brief historical perspective: “intelligence studies started as strategy, the “art of troop leader; office of general, command, generalship", both in europe (in greece as stratēgia, but first of all much later with carl von clausewitz’ book “on war”, 1832) and in china much earlier with the seven military classics (jiang ziya, the methods of the sima, sun tzu, wu qi, wei liaozi, the three strategies of huang shigong and the questions and replies between tang taizong and li weigong). the entities studied then were nation states. later, corporations often became just as powerful as states and their leaders demanded similar strategic thinking. many of the ideas came initially from geopolitics as developed in the 19th century, and later with the spread of multinational companies at the end of the 20th century, with geoeconomics. what is unique for intelligence studies is the focus on information— not primarily geography or natural resources— as a source for competitive advantage. ideas of strategy and information developed into social intelligence with stevan dedijer in the 1960s and became the title of a course he gave at the university of lund in the 1970s. in the us this direction came to be known as business intelligence. at a fast pace we then saw the introduction of corporate intelligence, strategic intelligence and competitive intelligence. inspired by the writings of mikael porter on strategy, as related to the notion of competitive advantage the field of competitive intelligence, a considerable body of articles and books were written in the 1980s and 1990s. this was primarily in 10 the us, but interest spread to europe and other parts of the world, much due to the advocacy of the society of competitive intelligence professionals (scip). in france there was a parallel development with “intelligence économique”, “veille” and “guerre économique”, in germany with “wettbewerbserkundung” and in sweden with “omvärldsanalys,” just to give some examples. on the technological side, things were changing even faster, not only with computers but also software. oracle corporation landed a big contract with the cia and showed how data analysis could be done efficiently. from then on, the software side of the development gained most of the interest from companies. business intelligence was sometimes treated as enterprise resource planning (erp), customer relations management (crm) and supply chain management (scm). competitive intelligence was associated primarily with the management side of things as we entered the new millennium. market intelligence became a more popular term during the first decade, knowledge management developed into its own field, financial intelligence became a specialty linked to the detection of fraud and crime primarily in banks, and during the last decade we have seen a renewed interest for planning, in the form of future studies, or futurology and foresight, but also environmental scanning. with the development of big data, data mining and artificial intelligence there is now a strong interest in collective intelligence, which is about how to make better decisions together. collective intelligence and foresight were the main topics of the ici 2020 conference. all articles published in this issue are from presentations at that conference. the common denominator for the theoretical development described above is the information age, which is about one’s ability to analyze large amounts of data with the help of computers. what is driving the development is first of all technical innovations in computer science (both hardware and software), while the management side is more concerned with questions about implementation and use. management disciplines that did not follow up on new technical developments but defined themselves separately or independently from these transformations have become irrelevant. survival as a discipline is all about being relevant. it’s the journey of all theory, and of all sciences to go from “funeral to funeral” to borrow an often-used phrase: ideas are developed and tested against reality. adjustments are made and new ideas developed based on the critic. it’s the way we create knowledge and achieve progress. it’s never a straight line but can be seen as a large number of trials and solutions to problems that change in shape, a process that never promises to be done, but is ever-changing, much like the human evolution we are a part of. this is also the development of the discipline of intelligence studies and on a more basic level of market research, which is about how to gather information and data, to gain a competitive advantage. today intelligence studies and technology live in a true symbiosis, just like the disciplines of marketing and digital marketing. this means that it is no longer meaningful to study management practices alone while ignoring developments in hardware and software. the competitive intelligence (ci) field is one such discipline to the extent that we can say that ci now is a chapter in the history of management thought, dated to around 1980-2010, equivalent to a generation. it is not so that it will disappear, but more likely phased out. some of the methods developed under its direction will continue to be used in other discipline. most of the ideas labeled as ci were never exclusive to ci in the first place, but borrowed from other disciplines. they were also copied in other disciplines, which is common practice in all management disciplines. looking at everything that has been done under the ci label the legacy of ci is considerable. new directions will appear that better fit current business practices. many of these will seem similar in content to previous contributions, but there will also be elements that are new. to be sure new suggestions are not mere buzzwords we have to ask critical questions like: how is this discipline defined and how is it different from existing disciplines? it is the meaning that should interest us, not the labels we put on them. unlike consultants, academics and researchers have a real obligation to bring clarity and order in the myriad ideas.” the editorial note in vol 10, no 3, 2020 is entitled: “labeling or science-by-buzzwords: the semantic trap in academic research and how to get out of it”. in the editorial note i suggest a way to get out of the buzzword-mire of the social sciences. we should instead focus on the problems: “the social sciences are drowning in new fancy academic terms or buzzwords, labels with unprecise definitions, rebranding phenomenon that somehow seem familiar. we are all surrounded by smart cities, innovation, and sustainability. what do these terms mean that we could not express earlier? introducing them also raises new questions, which at first may seem provocative: are there dumb cities too, if so where? do we carry out research at our universities that is not innovative? does the literature on sustainability make our products more sustainable? above all, these new fields are formulated in almost suspiciously positive terms attracting the attention of our politicians and echoed everywhere. how can anyone be against smart cities, innovation and sustainability? it must 11 be good, important and therefore it deserves funding. creating new terms to describe what is mostly old and familiar problems (relabeling) is not helping move science forward but instead hindering its development as it leads the researcher to believe he or she is setting out on a new quest, while often just ignoring past literature, especially that written in french and german languages, which then suddenly does not apply. the same is true for intelligence studies. “research” today is too often reduced to searching for articles in one of two commercial databases: web of science (clarivate analytics) or scopus (elsevier), basically consisting of articles that have been written during the past two generations. here we are supposed to cite the most cited articles, even though the same ideas (but with different words) have been expressed numerous times before in older articles, books or are just common sense, so that whoever wrote the first article become popular. this then is the pyramid scheme of the brave new world of the social sciences, a system that creates academic peacocks. the majority of social science researchers today are not first of all knowledgeable in say economics or business, but of how to produce articles. that is a skill that has less to do with what is happening in the real world of social behavior. that is the price we must pay, some say, but the actual production of research also attracts very little attention outside of the circle of academics who contribute to it. moreover, it makes our business education less relevant. ask yourself, if today’s business education was relevant, why are the chinese outperforming the west? why are there so few famous business schools in economically successful countries like germany, taiwan, or south korea? who teaches you how best to succeed in business life, the authors of the most cites scientific articles in business and management or the chinese classic authors, like confucius or sun tzu? when i got interested in intelligence as a business student it was based on the notion that better information can make organizations more competitive. this was still during the first generation after the start of what was called the information age, when companies realized that information and knowledge, not physical assets, were the most important ingredients for business success. there was no internet, nor mobile phones. i was interested in the following questions: 1. how do organizations work with information? 2. what is the most effective way for organizations to work with information to obtain a competitive advantage? 3. why are organizations not working more effectively with information? i was interested in these questions from an international perspective, curious about the relationship between specific cultures and production. so, much like marco polo, i asked myself: 4. what can we sell to other countries and what can we buy from them? 5. what is the best way of doing this? i am still predominantly interested in these questions and marco polo seems to follow me in my thoughts wherever i go and seek new knowledge. i am not interested in the semantics surrounding these questions, the new terms that are introduced more as labels than to give a more exact definition of the underlying phenomenon we are looking at. to make things even worse, these new labels change, and quite frequently, in what looks like ever-shorter life cycles of social science research fields, replacing each other after quick overlaps. it is much like watching trends in the clothing industry. suddenly you realize that your corduroy pants that work perfectly and have no holes in them need to be changed out. your surroundings demand it. to take a more fitting example: i was interested in how people work together with information as we started a research project on why employees hide information. here, i am not interested in collective intelligence, competitive intelligence, co-creation, wisdom of crowds, knowledge management, complex systems, or systems theory, just to take some examples. i am first of all interested in the problem. many academics mix labels with theory. theory does not mean to name labels, but to present similar problems in other studies, to say if they reached similar or different results and to try to explain why this may have been the case and what it means for our own study. this can be done almost completely without using labels. still, i tend to spend more time on semantics than on actual problems, very much against my own will. it’s like my academic surroundings impose this on me. it seems that most business researchers fall into the same semantic trap. it’s not only due to how we label problems with key words in databases, but also to the way we organize ourselves as researchers. the process can be explained as follows: business researchers quickly try to own the terms that they become interested in instead of focusing on the problems and problem areas that they are interested in. instead of broadening the field, we narrow it, becoming specialists in ever smaller parts, all with their own labels. after a few rounds we are no longer in contact with business life anymore. there is another variation of this problem and that is when the academic discipline is in close contact with industry even though it is erroneous. to me the scariest example of this is the study of economics after keynes, which is sometimes referred to as neoclassic economics. it seems clear to me that the major reason that banks, the financial sector and the organizations supporting this industry pay lip service to the study of modern economics is that it legitimizes a corrupt and close to bankrupt system that does little good to others outside of its own members. any problem can be studied from the perspective of numerous terms. often it does not matter which term we use as there are many terms that overlap and can be relevant simultaneously. 12 instead of accepting this, academics strive to own the terms they chose to use and to disown others, especially those that are closely linked. as soon as we identify ourselves with one term, we start to oppose other, similar terms, treating them almost as competitors, as we often compete for the same or similar research positions and grants. new academics come along and pick their label, often by accident, for example, when adopting the preferred label of a supervisor, until each term forms or constitutes an academic tribe. these academic tribes then develop their own conferences and journals, and an internal struggle finds place, a race to establish legitimacy around an internal hierarchy most often built on the popularity (impact) of articles, and less so on the quality of the content or its relevance. it’s also possible to be in several tribes at the same time, even though academics normally have a clear preference of one above the other, simply because it’s difficult to excel in more than one area. as an example, authors in the field of collective intelligence also study artificial intelligence, collective behaviour, swarm intelligence, complex systems, machine learning, human-computer interaction, multiagent systems, sustainability, information systems design, crowd work, evolutionary computation, social decision making, empathy justice, foresight, futures research, crowdsourcing, information systems network, and/or democratic theory. collective intelligence is used synonymously or in combination with co-creation, wisdom of crowds, opens source, social systems, and social complexity, all with their own tribes. within intelligence studies we have subtribes in the form of competitive intelligence, market intelligence, competitor intelligence, business intelligence, enterprise resource planning, social intelligence, all of whom deal with the problem of collective intelligence. close by there are the tribes of futures studies and foresight. in a corner sits the library sciences. across the road there are the tribes of decision making, decision sciences, information sciences. all are quite familiar with the same phenomenon studied as collective intelligence. in other disciplines there are similar labels and key words, for example collective behavior in the study of sociology. the problem is that researchers seldom direct their attention outside of their own tribe. this is not only an odd scientific process, but we are witnessing an enormous waste of intellectual ability and potential. so, how do we solve it? to become more relevant academic research must redirect its focus from buzzwords to problems, not just smart “research gaps” in the literature. instead of listing keywords, researchers, academic journals and academic databases should list problems (1), and the problems should be stated in full sentences (2) using as few (3) and as simple words as possible (4). we should also insist on clear, mutually exclusive definitions. by searching for problems instead of labels it will become much easier to find relevant research across different labels and disciplines. we need to be much stricter when admitting new labels. if a new term is not exact and not much different from a previous term it should be declined. focus should be on what the germans since the 19th century understand by “verstehen”, as the "interpretive or participatory" examination of social phenomena, not on coining new terms. today new terms often come to life because we did not read enough, or we thought more about internal marketing and our own self-promotion instead of focusing on problems that are important for humanity. we are all guilty of this to a certain degree as it’s difficult to escape the logic trap that is our current social science research system. we need to instill a new critical process of thinking by asking: what problem does this field of study lay claim to? are there other studies that lay claim to the same problem? if yes, go back to the previous field. if it does not exist anywhere, and if you are 100% certain, only then can you coin a new term after consulting with your peers. this process would lead to the merger of most of all existing social science research today. the same could then be done with conferences and academic journals. larger academic groups will again improve the quality of journals and conferences, thus improve the advancement of science. to complicate things further labels are sometimes decided outside of academia. the world of business is basically changed by its practitioners, not by academics. as an example, competitive and market intelligence is now often replaced by competitive and market insights (cmi) in many major companies. the intelligence label was always problematic and the association to the world of spying never quite washed off. it did not help that many successful business intelligence companies functioned more as private eyes with aggressive methods despite organizations like scip setting standards to the contrary. many were also skeptical to what they understood as an anglo-saxon and predominantly american agenda to spread the practice of industrial espionage advocated by consultants centered around langley. the difference between the term intelligence and insights is not significant. it basically means the same: valuable information, need-to-know for the competitiveness of the firm. put differently, there is hardly any part of insights that cannot be seen as intelligence and vice versa. however, it could be argued that market insight is a broader take on business information. it could be said that it brings together a wider group of fields, both practitioner and academics, some of whom were left behind in the process when smaller academic tribes were created. market researchers, business intelligence specialists and all kinds of information scientists are now lured back together under the umbrella of 13 earlier pioneers like the visionary businessman alvin toffler, the mathematician claud shannon, and gabriel naudé, the father of library sciences, just to give a few examples. the “insight people” have already started to form their own group. academics are likely to follow. other academics are already finding themselves sitting in groups that are no longer relevant wondering what happened. the academic projects that are the most successful will always be those that follow the development in business life. the discipline of digital marketing is a good example. digital marketing is fundamentally different from the old “brick marketing,” to the point that if you do not understand its logic today then your education is not relevant any longer. it took academia a long time to understand this and for a few years the whole discipline of marketing was terribly far behind reality. the advancement of the field still almost exclusively finds its place in business organizations. academics are mostly trying to run after and catch up with the practitioners in this field of study. one reason for this is that advancements in digital marketing demand substantial it infrastructure that academics do not have easy access to. the situation is similar in business intelligence, which is basically about new software today. the leading ai experts do not work in academia but in the major tech companies. it is all about being relevant and useful. in intelligence studies there is a demand on us that we integrate business practices with more technology (hardware and software). only then can we hope to make real academic contributions in this field. we stand in front of an almost awkward situation: the intelligence field has never been more relevant in the history of mankind as information has become the most important ingredient for competitive advantage. and the more information, and the better information, the more valuable the company. all the new and major mnes around us are living proof of this, whether it be alphabet (google), netflix, spotify, facebook or alibaba. to understand and be able to contribute to this domain we must be interested in the same problems that they are trying to solve. to this aim the labels are often just distractions, a semantic trap.” the editorial note in vol 11, no 1, 2021 raises a warning: “the internet is leading the world towards forms of totalitarianism: how to fix the problem”. the problem is real, also in the western world, as we have seen through a series of revelations, not only those of mr. assange and mr. snowden. as an example, after the editorial note was published, the head of danish intelligence was arrested, it seems, for having told the press that his employer not only cooperated with nsa but had become a mere tool for american espionage in europe. he is still in prison. needless to say, the intelligence services in the western world are confronted with a real legitimacy problem as part of a democratic political system. how did surveillance go wrong? “it is difficult to imagine intelligence studies as separate from information technology as we enter the third decade of the 21st century. the current issue of jisib bears witness to this integration with a strong focus on big data applications. hardly anyone today would or could do without the internet, but the project that started with us government financing in the 1960s, with packet switching, and in the 1970s with arpanet and saw commercial light in the 1990s is helping countries turn into totalitarian systems where totalitarianism is defined by a high degree of control over public and private life. public life is influenced by hacking, troll factories, fake news/propaganda, and interference in elections. private life is influenced by massive surveillance. to borrow the title of the book by zuboff (2019) we now live in “the age of surveillance capitalism”. business intelligence systems lie at the heart of this transformation, but so do artificial intelligence and robotics. and the trend is global. in the west the suppressors are mostly private monopolies (e.g. google, facebook), while in the east it is primarily the government that is snooping (e.g. china’s social credit system). face recognition is likely to become as popular in the west as it is in the east. it is also easily forgotten that no city was better surveilled than london, which started to build its cctv technology in the 1960s. the system is now being updated with facial recognition, just like the one we are criticizing the chinese for having. some forms of surveillance may also lead to great advances in our societies, like access to government forms and statements electronically and a non-anonymous central bank digital currency (cbdc), which promises to reduce corruption and tax fraud, and could be used for easy distribution of universal basic income (ubi). fintech promises to be highly disruptive. we are moving into an orwellian world of surveillance more or less voluntarily, often applauding it. “i have nothing to hide” the young man says, but then he later becomes a minister and starts to worry about the traces he has left on keyboards. the five eyes intelligence alliance, or any other major service, can pull out extensive analyses of behavior and personality on most of us now as we continue to exchange our personal data for access to searches and social media, but also subscription-based services. most chinese think that the social credit system is a good thing. this is for much of the same reason: they believe it will not be used against them and think that they will 14 do well. we all tend to be overoptimistic about our abilities and opportunities. it’s not before we fail that the full implications of the system are felt: lack of access, credit, housing, and no more preferential treatments. the result threatens to worsen the lack of social mobility and increase the growing conflict between the super-rich and those hundreds of millions who risk slipping from the middle class to being counted among the poor, many of whom live in the western world. the truth is another essential part of our civilization that we are now tampering with. on the internet, few users can tell facts from lies, but we think we can. most of those who grew up only with the internet never really learned how to think critically. the old library of physical books was the best guarantee that lessons learned from history would be transferred to future generations without anyone mingling. for that same reason, books were also seen as real threats to tyrants and have been censured and burned. the last time that happened in the west on a large scale was in nazi germany, but it is happening again now in subtler forms as amazon and other giants act as arbiter and refuse books with certain content based on value judgements. a world which relies all too much on the internet should recall that the information there can be switched off in a second. old books are often not even accessible, having been exchanged for online solutions. the situation in the brave new social sciences is much the same, everyone is running after the latest articles without ever questioning if the same ideas have been published before (difficult to know now). thus, much academic literature suffers, becoming a tedious process of repetitions under new brands. in a society where everyone is a writer, no one really reads or has much of importance to say at the end. how do we solve these problems? step one on the internet is serious encryption as to make data private. step two is to give all personal data back to the users, that is, to take it away from the private companies and then indirectly away from the security services. that will eliminate the “free” business model and lead to more subscription-based products instead. step three is to break up the monopolies, and before that to tax them properly. step four is to return to books that have stood the test of time (real peerreviewed) whether online or offline. (the learning process is probably only half as good on the screen). we need to go from a culture of skimming data back to reading and discussing it. technology and management practices should be a part of that solution. otherwise, it looks like we will continue down the road that leads to totalitarianism. the internet right now is making shopping easier, but most people are becoming less aware of realities, less smart, less critical. only a small part of the population is able to use it to their advantage for understanding the world around them. it would be great to see more articles develop ideas and products for how we as societies can go in this direction.” my last editorial note (vol 10, no 2, 2021) is entitled “intelligence studies as an alternative approach to the study of economics”. it revisits an old favorite topic, but taken a step further: one learns much more about economics from good factual observations of reality as events happen around the world than by spending time reading economic theory. the reason is that most economic theory is inaccurate or irrelevant: “i am sitting at home looking through two thick books used in business education a hundred years ago and wondering how they are outdated. they are full of detailed knowledge about markets, products, production, and legal issue between countries. today everything is lifted to a more abstract level and many parts have become their proper disciplines. how successful has this change been when it comes to understanding business and economics? the study of economics, but even business and management today, are too far removed from the reality they are trying to describe. to study economics has instead ironically become a guaranteed way not to understand much about real economics; for example, how money is created and is distributed through private banks or how the gold market works. instead scholars know econometrics, or they adhere to some group with a favorite journal. as we know, far earlier than adam smith, for example with marco polo, at the heart of economics lies the notion of competitive advantage. in the thick books i am sifting through that notion is never lost. it’s all about understanding markets to find an opportunity or a niche. intelligence studies suggests that the way to become competitive is to learn about the world by focusing on cultures, history, geography, people of influence, markets, resources and knowledge. there is a strong relationship of causation between the survival of companies and that of a nation state, as the latter can be seen as the sum of the former. if we take one more step, the notion of competitive advantage has always been related to the study of geopolitics, realpolitik and today what we understand by geoeconomics. it is also closer to the german and english tradition of political economy, seeing that it is counterproductive for any attempt to understand societies to separate politics from economics, or from psychology for that matter. they are all parts of the same social system, as luhmann argues. try to take out any part and you miss the picture. the study of culture today is part of anthropology or sociology; thus, business students seldom learn much about it. the 15 geography they are supposed to have learned in high school (but few do). the same for history. so, it is becoming clear that too many bits and pieces are missing in our education for us to be able to draw valuable conclusions about how to make money on a grand scale. when austrian economists wanted to take out history from economics there was a serious battle in european universities (“methodenstreit”). those arguing for removing history and ever more specialization won, in part because germany had lost wwii and the new superpower wanted to set its own rules, even in the study of people and society. the separation between micro and macroeconomics is now close to complete. and, what else is “marketing” but a subset of geography? students today study “marketing” instead of actual markets, in lagos or mumbai, assuming that all are more or less the same and that the models that university professors and consultants make up are universal. “entrepreneurship” is studied like an exciting new fruit, not as an ancient game of willpower, sweat and tears. do these studies really help young men and women become entrepreneurs? i doubt it. in the meantime, companies in the western world are being surpassed by their asian competitors, whose employees often do not have a business education. for as long as the western world was doing well economically, no one really questioned the subjects, models and theories presented at business school. it was assumed there was some sort of correlation, i guess, even though most successful entrepreneurs had a natural science background or no diploma at all. now things are different. a good way to start is by going back to the main question of competitive advantage. it’s there that intelligence studies are, defining methods for how to understand markets and events as they unfold before us. jisib has always tried to reflect this shift by publishing articles on markets, industries, different countries, new technologies, and especially software that shows how companies can become competitive. how to obtain a competitive advantage is still about gathering intelligence. what happened this week with the coup-d’état in guinea when president of guinea alpha condé was captured by the country's armed forces? no one at business school can tell you because they don’t study that. it shows the irrelevance of most modern social science. if we really want to understand economics, we should study what happens in the world’s many markets and countries. in that sense intelligence studies is a better replacement for the study of economics in its current form.” you learn economics best by gathering as much experience as you can from people who work with actual economic problems, either in the private or public sector. thus, intelligence studies is also a method for how to study economic behavior. in the article by van der pol entitled “collaboration network analysis for competitive intelligence”, the author proposes a method that allows for the identification of collaboration strategies in a static and dynamic setting that also makes it easier to communicate on the results. the article by olaleye et al. looks at how strategic thinking and competitive intelligence can result in innovating capabilities through management support. faris muhammad and sri hartono look at purchasing factors for instagram users. majidfar et al. look at an intelligence management model for national level organizations and found that attention to the managerial and operational levels is more important than environmental factors. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. this is by no means the end of intelligence studies in business. for my own part, last year was my most productive in more than a decade and i hope to continue with the same number of hours spent on research. however, there will be other outlets for these articles and publications, as there will be for all those papers presented by colleagues at intelligence-related conferences that take place every year. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief, jisib 16 literature gilad, benjamin (2021). the opposite of noise: the power of competitive intelligence. independently published. nyquist, h. (1924). certain factors affecting telegraph speed. bell system technical journal, 3; 324-46. søilen, k. s. (2013). an overview of articles on competitive intelligence in jcim and cir. journal of intelligence studies in business, 3(1). jenster, p., & søilen, k. s. (2013). the relationship between strategic planning and company performance–a chinese perspective. journal of intelligence studies in business, 3(1). søilen, k. s. (2014). a survey of users’ perspectives and preferences as to the value of jisib-a spotcheck. journal of intelligence studies in business, 4(2). solberg søilen, k. (2015). a place for intelligence studies as a scientific discipline. journal of intelligence studies in business, 5(3), 35-46. søilen, k. s. (2016). a research agenda for intelligence studies in business. journal of intelligence studies in business, 6(1). søilen, k.s. (2016) users’ perceptions of data as a service (daas). journal of intelligence studies in business. 6(2) 43-51 söilen, k. s., & benhayoun, l. (2021). household acceptance of central bank digital currency: the role of institutional trust. international journal of bank marketing søilen, k.s. (2016) economic and industrial espionage at the start of the 21st century – status quaestionis. journal of intelligence studies in business. 6 (3) 51-64. søilen, k.s. (2017) why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies. journal of intelligence studies in business. 7 (1) 5-37. søilen, k. s. (2017). why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company. journal of intelligence studies in business, 7(2). søilen, k.s., tontini, g. and aagerup, u. (2017) the perception of useful information derived from twitter: a survey of professionals. journal of intelligence studies in business. 7 (3) 50-61 søilen, k.s. (2019) how managers stay informed about the surrounding world. journal of intelligence studies in business. 9 (1) 28-35 søilen, k.s. (2019) making sense of the collective intelligence field: a review. journal of intelligence studies in business. 9 (2) 6-18 solberg søilen, k. (2019). the argument that" there is nothing new in the competitive intelligence field". journal of intelligence studies in business, 9(3), 4-6. copyright © 2021 jisib, halmstad university. all rights reserved. 5 cloud solution in business intelligence for smes – vendor and customer perspectives alessandro agostino , klaus solberg søilen , bart gerritsen department of management and technology, halmstad university e-mail: klasol@hh.se faculty of industrial design engineering, tu delft e-mail: b.h.m.gerritsen@tudelft.nl received november 12, accepted 20 december 2013 abstract: the aim of this study was to identify key success factor for sme customers of cloud based business intelligence products. a deep interview was made with four producers and a questionnaire was carried out among 36 smes. the findings suggest that the most important csfs were the level of software functionalities, the ubiquitous access to data, responsive answers to customer support requests, handling large amounts of data and implementation cost. each of these factors addresses a specific area that customers pay close attention to during the adoption process of a cloud bi solution. offering ubiquitous access to date and respsonsive answers to customer requests are particularly emphasized for smes. we also found that industry tailored software is preferred, monthly or quarterly billings, and contact by email or phone for service. the paper shows recommendations, implications of research and suggests further research on the topic. keywords: business intelligence, sme, cloud computing, ubiquitous computing introduction the amount of data available for analyses is growing considerably and ibm estimates 90% of the data in the world has been created in the last three years (ibm research, 2011; negash, 2004). in the last thirty years, storage space has been increasing dramatically whereas its cost has followed the opposite trend (storage trend study). more businesses are realizing the massive potential that lies in their data. this is a potential that can be leveraged to make better decisions, offer more value to both customers and shareholders, and discover patterns that could be “disruptive” (scholz et al., 2010; sheikh, 2011; nyblom et al., 2012). the discipline that specializes in turning data into useful information is sometimes called business intelligence (bi). why it is important for the bottom line of a company to have better information, is a crucial question and has been available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2013) 5-28 mailto:klasol@hh.se mailto:b.h.m.gerritsen@tudelft.nl https://ojs.hh.se/ 7 addressed by nyblom et al. (2012) and watson and wixom (2007). having access to the right information at the right time increases the likelihood of making better decisions (yeoh and koronios, 2010). these will bring tangible benefits to the organization, both in terms of “increased revenue” and/or “decreased costs”. the importance of any it solution can be measured in terms of how it affects, directly or indirectly, the two aforementioned basic metrics (poston and grabski, 2001; tata consulting service white paper, 2012; rust, 2002). a competitive advantage can be achieved not only through innovation in markets or products. storing, collecting and analysing information have become a new frontier of competitiveness, and scholars foresee that data will become a new “corporate asset” and main source of revenue (brown et al., 2011; raisinghani, 2004). many cios (chief information officers) now consider business intelligence a top priority for their organizations (gartner, 2013), after many data analytics best practices have proved to offer considerable benefits to enterprises and individuals (lavalle et al., 2011; may, 2009). moreover, the benefits arising from the collection and analysis of data are not restricted to a specific industry, but may relate to the majority of organizations (gangadharan and swami, 2004; raisinghani, 2004). many sectors have already gained benefits from big data, but many organizations also still need to understand how to obtain value from it (lavalle et al., 2011). historically, bi systems have been mainly adopted in large and multinational enterprises (olszak and ziemba, 2012; wong, 2005) which could afford the considerable cost required in terms of money, expertise and capabilities. as remarked by scholars (solberg søilen and hasslinger, 2012b; hwang et al. 2004), the resources necessary to implement a traditional bi tool are not available in most smes. bergeron reports similar findings and suggests that conventional bi systems would not meet the needs of smes (bergeron, 2000; insideinfo whitepaper). furthermore, despite the precautions taken, the failure rate that characterizes bi projects, over 50%, (beal, 2005; meehan, 2011; laskowski, 2001; legodi and barry, 2010 found in adamala and cidrin, 2011) does not encourage smes to invest in what is seen as risky activities. although major organisations have led the way in introducing and implementing business intelligence solutions, the recent speed of globalization, competition and the amount of data to be processed has forced smes to evaluate the purchase of bi tools (olszak and ziemba, 2012; wong, 2005). these software applications help a small business compete with larger ones, increase market share or provide insights and patterns that otherwise cannot be seen (grabova et al., 2010). olszak and ziemba (2012) surveyed businessowners and managers of smes, who confirmed the importance of analyzing data even in a small company: problem formulation in the last few years, uncertain and turbulent economic conditions have forced companies, small as well as bigger ones, to find ways of streamlining operations and cutting costs in many areas (östling and fredriksson, 2012; sheikh, 2011). the increase in data volume calls for an efficient way to manage the information within an organization, especially of a sme where the use of information technology consistently lag behind (rath et al., 2012). the advent of cloud computing could represent a breakthrough for the it segment, since the advantages brought in by this technology are particularly appealing to smes (benlian et al., 2009; rath et al.). the importance of this technology is also demonstrated by the growth achieved in this market in recent years. the cloud software-as-a-service (saas) market grew by over 17% in 2012, reaching $14.5 billion in revenue and is expected to hit $22 billion in 2015 (bucur, 2012). idc forecasts that the amount of revenue generated by saas bi suppliers will expand three times as fast as the overall bi market for the year 2013, logging a compound annual growth rate (cagr) of 22.4% (deng and zhang, 2012). if smes can find ways to successfully deploy cloud bi systems, it is reasonable to assume that those solutions will boost their competitiveness and provide a means to manage the information more efficiently. however, despite the promising numbers and high expectations, the saas business intelligence market currently represents only 3% of the total bi turnover and the adoption rate among smes is still low (figure 1; fsn, 2012; rath et al.; scholz et al., 2010). 8 figure 1. smes business intelligence adoption a variety of factors might explain this poor result, such as the novelty of saas technology, which has still to spread, or the fact that applications characterized by a high strategic importance for a company, such as bi, experience lower adoption in a cloud setting. volatile market conditions force business intelligence suppliers to adapt their offerings to current customers’ needs. the knowledge of which key factors affect the decision of a sme to adopt a cloud bi solution is mostly unexplored. the ability to investigate this problem will have practical as well as theoretical benefits:  understanding the real needs of smes in terms of managing information, through the adoption of bi systems, in a more comprehensive way. the “use” of information has a dramatic influence on the performance of a sme (lybaert 1998 found in scholz et al., 2010). in addition, bi systems appear to be adopted mostly in large and international companies, so previous studies have been focused on those organizations (scholz et al., 2010; olszak and ziemba, 2012; wong, 2005). the needs of smes are quite different than for big companies (scholz et al., 2010; olszak and ziemba, 2012).  preventing the development of initiatives or projects with poor market appeal or suggesting that bi suppliers should focus on critical issues that otherwise would have been overlooked – resulting in a more compelling offering for the customers.  providing a solid ground for future research by validating and adding new perspectives to the current body of knowledge in the field of business intelligence, well aware that the value of these studies will decline rapidly with time, given the advancement of technological innovation (yeoh and koronios, 2010). based on this we have defines the following research question (rq) for this study: rq. what are the key success factors for the adoption of a cloud bi solution in small and medium sized enterprises (smes)? 38 table 1. key adoption factors in business intelligence previous research a unique definition of small and medium sized enterprise has not been put forward yet (carter and jones-evans, 2006). for the purpose of this study, a company is considered a sme if it fulfills the following requirements:  up to 500 employees and $25 m in annual revenue in the unites states (carter and jones-evans, 2006).  less than 250 workers; a maximum annual turnover of €50 million or €43 million in the balance-sheet, for european enterprises (carter and jones-evans, 2006).  for asian companies there is not an official definition and it varies greatly from country to country. for instance, chinese companies with 2000 employees can still be considered medium businesses, whereas in lao, a company with more than 100 employees is considered a big company (harvie, 2004; xiangfeng, 2007). according to rockart (in vodapalli, 2009), critical success factors (csfs) represent a number of areas where the achievement of great results will ensure a competitive position for the individual, department or organization (anthony, dearden and vancil, 1972 found in olszak and ziemba, 2012). it is worthwhile remembering that a mere list of key success factor does not automatically imply the success of the project (adamala and cidrin, 2011). as remarked by scholars (yeoh and koronios, 2010), a list of key success factors identified for the development of information systems, such as bi, is only a part of the task necessary to ensure the project’s completion. the key factors represent the areas that, if successfully managed, can increase the likelihood of a successful adoption. software evaluation criteria refers to making preference decisions over the available alternatives that are characterized by multiple attributes (jadhav and sonar, 2009). an initial research revealed that the key factors concerning the adoption of a business intelligence software have been considerably covered (adamala and cidrin, 2011; yeoh and koronios, 2010; vodapalli, 2009), both in term of smes (olszak and ziemba, 2012; wong, 2005) and software-asa-service (godse and mulik, 2009). however, the key factors in adopting saas business intelligence solutions in smes have not been sufficiently treated. little has been said regarding the connection between smes and cloud bi, therefore there is a lack of a proven framework that can be used for analyzing the domain. we developed these ideas following a similar approach adopted by other scholars (scholz et al., 2010; yeoh and koronios, 2010), represented in table 1. organization perspective process perspective technology perspective adequate budget support from senior management competent bi project manager sufficient skilled staff/team clear business vision and plan past experience and cooperation with a bi supplier rolling out training initiatives well defined business processes and issues well defined users’ expectations adjusting the bi solution to users’ business expectations understanding how and when data will be delivered integration between bi system and other systems (desktop applications, software..) data quality bi flexibility and responsiveness on users’ requirements appropriate technology and tools user-friendly bi system delivers actionable information 9 other scholars (scholz et al., 2010) have faced a similar challenge during an investigation of traditional bi systems. they have developed a framework to link it software adoption in smes, bi adoption and bi success factors. based on this we present here two areas which will be taken into consideration in building the framework that helps answer the rq:  critical success factors: csfs for it/bi software implementation: focus on smes  evaluation criteria: it packages and software-as-a-service evaluation criteria the factors belonging to these distinctive areas will be combined, resulting in a table that will be initially refined with the results from the qualitative interviews and then tested with a self-completion questionnaire. critical success factors (csfs) in bi have been treated by many authors (eckerson, 2005; wise, 2007; yeoh and koronios, 2010; olszak and ziemba, 2012) and they could be considered a set of tasks and procedures that should be addressed in order to ensure bi systems accomplishment (olszak and ziemba, 2012). in this paragraph, these factors are reviewed and particular attention is paid to the ones related to smes. table 2 summarizes the literature on the argument. 10 table 2: software-as-a-service evaluation factors (godse and mulik, 2009; benlian et al., 2009; sheikh, 2011; sharma et al., 2010, saugatuck technology report, 2009, jadhav and sonar, 2009) the bulk of studies on critical success factors have focused on large companies and it is believed that not all the factors are applicable to the small and medium sized enterprise environment (wong, 2005; bergeron, 2000; insideinfo whitepaper). these studies analysed traditional and expensive it/bi projects, commonly characterized by long implementation periods; whereas the typology of bi systems we focus on in this study requires a minimal implementation effort (sheikh, 2011). given this premise, the use of past research on critical success factors seems inappropriate for the purpose of this study. indeed, there are substantial differences between cloud and traditional bi implementation, in terms of resources, complexity, and architecture. this research offered valuable foundations applicable throughout the whole research. not all factors presented in table 1 and 2 will appear in the final framework and some of them have been adjusted to fit the context of this investigation. elements such as clear business vision and plan, support from senior management, well defined business processes and issues, sufficient skilled staff are typical of long it projects, which require multiple interactions between the client and the vendor, given the amount of resources required to roll-out the initiative. the overall process of adopting a cloud functionality architecture usability vendor’s reputation cost risk mitigation customization of the interface enhance capabilities embed reports on multiple platform (blogs, web, email..) ability to deliver ad-hoc business analyses capability of the software package to run on wide variety of computer platforms present and display data effectively error reporting integration (api, connectors..) scalability and system response time reliability security (backup, recovery) simple user – interface offline support platform support for mobile/tablet devices ubiquitous access collaborative reporting and analytics ability to support different combination of user types (beginners, intermediate, advanced) number of clients/users brand value and popularity certificates and standard requirements effective manuals and training tools level of service offered annual subscription one time implementation costs maintenance cost easy to buy special contractual agreements flexible subscription 11 business intelligence solution is less complex and these factors do not play a major role. another example is rolling out training initiatives, which represents a customer support activity. generally, saas bi software is easy to use and the training support is mainly delivered through online libraries, tutorial videos, 24/7 call center, and email services. it packages and software-as-a-service (saas) evaluation criteria in this section we discuss the different criteria that are evaluated before the purchase of a software. focus is on the it solutions evaluation criteria, with a specific consideration for saas cloud factors. research on the key criteria for purchasing cloud saas software has been carried out by several authors (godse and mulik, 2009; benlian et al., 2009; sheikh, 2011; sharma et al., 2010; xin and levina, 2008; jadhav and sonar, 2009). given the focus of this paper on cloud saas software, it’s necessary to understand precisely which are the fundamental factors that drive the purchase of these solutions. table 2 was originally developed by godse and mulik (2009) and grouped together, in s simple and comprehensive way, the more important evaluation factors characterizing cloud saas software. however, during our research we found other factors not listed in the original version of the table, which help explain new discoveries: 1. functionality: it represents the sum or any aspect of what a product, such as a software application or computing device, can do for a user (searchsoa, 2005). one of the main concerns that potential customers have, before buying any saas product, is to understand the real functionalities. in the previous paragraphs we highlighted some benefits of cloud products. however, by comparing cloud bi and traditional bi functionalities, the former comes off worse. the limited 2. customization allowed by a saas products is far outdone by traditional solutions, which provide cutting-edge analyses created specifically for the needs of a different set of clients. 3. architecture: in this category we refer to the security, reliability, scalability and integration of the it architecture. security is a crucial aspect that every saas vendors should address, clarifying doubts that companies have in letting third-parties manage confidential and sensitive information (godse and mulik, 2009). scalability refers to the ability of the product to maintain the same performance despite the increase in utilization. reliability indicates the product’s ability to work and remain available to the users under specific environmental conditions for a given amount of time. finally, a product is easily integrated if it can be combined with other applications. 4. usability: this section refers to the features that facilitates the interaction between the user and the software. examples are the user-interface and all the tools that support the customers in troubleshooting (godse and mulik, 2009). even though the saas products are generally easier to use than traditional software, there are different level of “usability”. 5. vendor reputation: this specific attribute is valid for all software purchases, irrespective of the product's features and architecture. therefore, our initial assumption is that it should be taken into consideration for cloud solutions. 6. cost: the total cost of ownership is composed of two elements. the consulting and configuration services go under the name of implementation cost. the monthly or annual fee that is due to the supplier in exchange of the right to utilize the software is named subscription cost (godse and mulik, 2009). 7. risk mitigation: in this section we grouped all the activities that facilitate the transition to a new product. 12 table 3: research method method our research follows a two-stages approach, qualitative and quantitative, as summarized in the table below. stage one: qualitative – defining the previous theories, gain up-to-date market insights and categorization of key factors. an extensive literature review in two main domains was conducted. the subsequent step involved the analysis of the table, aimed at identifying possible weaknesses or improvements agreed by bi experts, daily bi users and bi vendors. indeed, some previous theories explain the factors in generic terms, while this investigation is aimed at representing key adoption factors for smes in a more detailed manner. this process is done through four interviews. the research assumes that experts' judgments and experience could add important value in situations where theory is incomplete or obsolete (yeoh and koronios, 2010). finally, factors coming from the literature review, improved with the interviews’ data, and were consolidated into a single table. stage two: quantitative empirical assessment of the model. due to the limited academic literature about our problem, stage one was used to provide a solid ground for the following analysis. here, the preliminary table (table 4), resulting from the qualitative interviews was further assessed and validated with a quantitative method. based on this table, all the content was carefully shaped into a survey. the research instrument was used to capture respondents’ perceptions and empirically classify the importance of the factors. a pool of candidates, who fulfilled the following requirements, were selected: “smes’ employees who use a cloud business intelligence solution”. none of the participants had any relationship with the authors. to deepen the understanding and assure a certain level of reliability, three different data sources were used: secondary data. as this is a fast changing research area, papers older than five years could not offer much value. therefore, throughout the paper not only did we use books or publications, but we also extensively relied on recent research papers and analyses made by trustworthy professional firms and as found at recent conferences (gartner, aberdeengroup and idc) or information was found directly by business intelligence suppliers. qualitative interviews. all interviews were held through skype and notes were taken for future reference. even though face-to-face interviews are preferred for in-depth studies aimed at grasping nuances in the interviewees’ behaviours, videocalls through skype can also represent an effective way, given money and distance constraints (haygibson, 2009). the first bi expert is the co-founder of rj metrics (www.rjmetrics.com), a philadelphia based company that sells cloud business intelligence/analytics solutions, with a focus on ecommerce organizations. the other knowledgeable person in the area of business intelligence is the marketing manager of insightsquared (www.insightsquared.com), whose main offering is centred on sales analytics, optimization and forecasting. both companies deal repeatedly with small and medium sized business owners. regarding the bi users’ point of view, a first interview was conducted with the marketing purpose of research research methods research group 1. previous theories in light of cloud bi. gaining new insights on the bi market. help in the categorization process semi-structured interviews case. four interviews with bi experts, vendors and customers of business intelligence software solutions 2. ranking the importance of key adoption factors questionnaire 36 smes who have implemented a cloud bi solution 13 director of a mexican company with less than 150 employees, which provides solutions for human resource departments. the second was an interview with the head of the analytics department of soliditet, a 100+ years old stockholm based company with 250 employees, market leader in providing credit and business information for companies based in the nordic regions. anonymity has been preserved according to wishes the web-based questionnaire. another source of primary data comes from the self-completion questionnaire. the purpose of the questionnaire was to rank the importance of the factors listed in table 4. the limitations posed by the rq restricted the available representative sample. being aware of this difficulty, we made sure to have a pool of respondents large enough to draw insightful conclusions. the structure of the questionnaire's questions, the language used in formulating them, and the recommendations made by bryman and bell’s (2011) have been taken into consideration. nine questions were asked, both open-ended and with multiple choices, with a preference for the latter. indeed, bryman and bell (2011) remark that closed-questions are more suitable for comparison among variables, which also represent the nature of our research here. sample and limitations regarding sampling, the rq and the framework represent the most important delimitation criteria for the sampling choice (miles and huberman, 1994). the cloud bi subject, accounting for only a small portion of the total bi market, restricted from the beginning the sampling procedure. in addition, the available sample was further restricted by considering other criteria such as the size of the companies (smes) and the actual utilization of a cloud bi software. out of the total population composed of 388 bi customers, 342 “good” addresses were selected, which constitute the total sample. the rest of the contacts were either info@addresses, phone numbers or e-form compilations which have been discarded. after completing the email collection, a web-survey was created and published online. an email, including the link to the questionnaire, was sent to all 342 addresses and a time limit was set to 60 days. 19 emails were automatically received with the notification of maternity leave, job change, not availability or wrong address. 36 full responses were received, generating a 10% response rate. according to braun hamilton (2003, found in solberg søilen and sabanovic, 2012), the average response rate for web survey is roughly 13 percent, but he affirms that this number could vary. this result could be seen in two ways. from one side, bryman and bell (2011) affirm that the absolute size of the sample carries the most weight. the two authors also claim that there is not a standard procedure for evaluating sample size. it depends on a number of considerations and there is not a definitive answer (bryman and bell, 2011). returning to the results achieved by this study and considering the year 2012, the cloud bi segment represents 3% of total market (figure 4; fsn, 2012; rath et al. 2012; scholz et al., 2010), hence the available representative sample was lower than other research conducted on traditional business intelligence (adjusted for the revenue difference). results and analysis by combining the previously mentioned factors, we created a table that has been assessed and refined with empirical data. the development of this framework has been necessary to reach the objective stated earlier. the process of categorization showed to be a difficult one. on the one hand, authors who have previously studied bi suggest dividing critical success factors in four categories: technological, organizational, process and environmental (yeoh and koronios, 2010). scholars who have studied cloud computing software have used a different approach, as shown in table 2 (godse and mulik, 2009). since this research combines multiple aspects, previous suggestions are not fully applicable to this investigation. others have recognized the limitation of pre-defined frameworks (vodapalli, 2009). we decided to categorize and label the key factors according to both the author’s previous experience and the results from the interviews. the decision to not apply other authors’ categorization is not a critic of these studies, but has been necessary due to the nature of this research. the result of the process is shown in table 4. the concepts will be used as a guide for the questionnaire development. 14 table 4: categorization of key adoption factors for saas bi in creating the table, we prioritized the factors that have been discussed across all the interviews. other factors, that represent a specific view of one or more interviewees (not all), have been included in the table only after careful evaluation, trying to separate subjective and objective views. the insights generated from the discussions reveal some differences with the information found in the theories. support: all four interviewees pointed out that supporting activities are becoming more crucial in establishing a good client-vendor relationship. this area has been emphasized both by customers and suppliers of bi software. in table 2 there is mention of the level of service offered, which is a quite broad statement that might also include the support activities. however, after the interviews we considered appropriate to create the category support (table 4). this provides a more detailed representation of different elements. flexibility: flexibility has been mentioned by scholars as a critical factor for the bi adoption and implementation (olszak and ziemba, 2012; sheikh, 2011). the interviews revealed that flexibility spans over multiple areas and customers pay attention to most of them before purchasing the solution. in addition to that, a discussion around the social network and web-data analyses came up multiple times. the increasing influence of social networks on the customers’ opinion has attracted performancefunctionality ability to share reports through the software web interface the level of functionalities and capabilities offered by the product the speed of the product in performing analyses the ability to handle data in real time the ability to manage different amount of data ability to offer actionable insights the effort required to deploy the product on a large scale basis integration tablet and mobile integration ability to handle multiple sources of data (excel, google documents, etc.) level of integration with other bi applications or databases flexibility the level of flexibility in terms of contract agreements and conditions the simplicity of the interface the level of skills needed to perform meaningful analyses web-data analysis the level of customization and personalization ubiquitous access to data offline access to data the payment method functional or industry needs reliability provider’s brand reputation (including partners, suppliers and testimonials) the level of security guaranteed by the vendor ( backup, recovery and privacy) support vendor’s clarity to customer support requests responsiveness to general support requests the level of support offered by the vendor (chat, 24hour) cost of ownership the amount of implementation cost (training, setup..) the amount subscription cost (monthly or yearly fee) 15 the attention of companies, who monitor closely what happens throughout the web. the flexibility of a bi software to analyze not only common data sources (e.g. csv or excel), but also unstructured data (text and social media content) is in high demand. integration: according to previous theories (table 3), the integration between the bi software and other applications already situated in the customer’s organization represents a critical area. during one of the discussions, the interviewee linked to a market study carried out in 2012 by an independent advisory firm and a well-known authority in the area of business intelligence (dresner advisory services, 2012). it revealed that over 66% of companies taking part in the study, rely on two or more bi tools at the same time. therefore, integration is also referred to among different bi applications. however, given the focus of this investigation on small and medium sized enterprises, the integration among bi tools is more related to big and multinational companies with various business units. key factors from the qualitative interviews rj metrics’ co-founder during the interview many factors were discussed and we will categorize them in four areas. the functionalities took a substantial part of the discussion, and the interviewee emphasized their importance for smes. in particular, he explained that the majority of customers are not interested in having a vast number of features across different domains, but prefer a software able to perform a few analyses, but of high quality. for example, rj metrics provides a software mainly to e-commerce companies, where cohort analyses and trends spotting represent two essential functionalities. with the advent of social networks, collaboration and sharing have become pillars of many applications since they encourage users to communicate and work together. the interviewee mentioned that customers are not very keen on using multiple software tools at the same time. they prefer to have everything in one place and this is one of the main factor they look for before buying the software (e.g. “can we share reports within the software?”). cost and deployment time have been mentioned together and they do influence the final decision. rj metrics takes seven days to deploy the overall solution and customers appreciate this short installation time. not only does it reduce the overall cost, but it also minimizes the number of problems typical of the implementation phase. supporting activities are not only restricted to the after sales customer support, but represent the overall ability to assist users in using the software and provide a detailed explanation to doubts or questions. this includes the area of security, where prospects perform a detailed due diligence before letting external parties manage sensitive data. marketing manager of a mexican company the marketing department of the company uses birst software. the conversation lasted almost one hour and was detailed. after a brief introduction of his company’s operations and analytics activities, we discussed his perspective on the key adoption factors. the ability to produce fast analyses was the first area in the dialogue. as previously mentioned, his company provides solutions for human resource (hr) departments, and payroll management is one of the most important service. payroll activities are characterized by remarkable seasonal trends, since the bulk of the work is done at the beginning and at the end of each year. in these two periods, the interviewee explained, the company runs a lot of promotional campaigns, mainly delivered through the website. he personally has a six weeks time window to tweak the advertising material according to real time data response, delivered on a daily basis. the ease of implementation was another concern he had before purchasing the solution, which has been deployed in three weeks. a long implementation time could reduce the overall roi generated by the bi investment, and generally prospects pay close attention to this aspect and evaluate the track record of bi suppliers in previous projects. flexibility has been debated. in his department, the users analyse data for different purposes, including tracking campaigns’ results, evaluating new opportunities and measuring customers’ satisfaction. the employees in charge of each analysis, examine data and present results in different ways. the bi software should be able to 16 accommodate all the users’ needs. in addition, he mentioned the importance of offering insights to the customers. often bi solutions not only provide an answer to many questions, but also leave users with new doubts. head of analytics department at soliditet soliditet’s analytics department makes use of two bi tools. one is spss software for statistical calculations, while for the cloud part it uses a microsoft product. the conversation started with a brief overview of the business intelligence market and how soliditet is trying to exploit some opportunities through analyses of the company's spreadsheets. the discussion became particularly interesting since the beginning, when the interviewee mentioned that soliditet is looking for another bi solution and it is in the process of evaluating different options. one of the main requirement was "we want a solution wellintegrated with tablets", which is one of the main tools used by the company to interact with the customers. therefore, this type of integration was important not only for the company itself, but also for fostering the relationship with customers and prospects. the integration aspect came out again when he made clear that spss software will remain the main tool used by the business analysts and both solutions should work together. then the discussion moved towards the cost of ownership, which was an important point for the company. the interviewee was well aware of the costs for different bi solutions and he explained that spss software was chosen as a compromise to the expensive, although powerful, traditional bi applications. another area that got considerable attention was the reliability of the software. the company is looking for a solution that fits the budgetary requirements, but it does not want that the financial limitations would lead to the purchase of a solution with limited value for the company. marketing manager of insightsquared the simplicity criteria was the central point of the discussion, since interviewee claims insightsquared acquired many customers primarily by luring them with an easy-to-use software. indeed, the software sold by the company takes only 48 hours to get installed and it is intuitive. according to him, it is difficult to create a general list of the most important functionalities for a cloud bi software, because it is highly dependent on the industry segment. however, he did think that a few of them should represent a cornerstone of every bi software: ease-of-use has already been mentioned. configurability is another one, since companies have their own way of using data, which is often unique. hence, the level of customization for the cloud software is fundamental. nonetheless, provided the limitations of cloud technology, customization cannot reach the same levels of the traditional bi implementations. however, the software has to be able to accommodate different users’ needs, not only in more superficial subtleties such as colour or font preferences. moving to a different area of discussion, the marketing manager claims that a very simple software, such as facebook or twitter, simplifies the activities related to the customer service. by creating a self-explanatory product, there is a little need for online tutorials or pop-up guides. however, he agrees that technical problems do occur and a customer support team is essential to promptly solve some targeted questions. for instance, each screen of insightsquared software is equipped with an "about this report" section to guide users when they need a little more information on how certain calculations are made. integration also came up as an interesting part of the dialogue and the interviewee provided insightful information on this point. he states that his company often receives questions related to integration with third party data source solutions. for this reason, insightsquared is currently dedicating a good amount of resources to improving the offering in this area. nonetheless, he points out very clearly that it is complex to find a trade-off between the financial investment necessary to develop a new integration and the total number of integrations available. indeed, the development of new connectors is important, but scaling up the product is also a crucial aspect. it is not possible to satisfy all the customers and therefore it’s fundamental to prioritize and integrate the most popular systems such as crm and erp solutions. lastly, flexibility was the last argument of the discussion. surprisingly, not only has insightsquared not built the software around flexibility, but it has also put some limits on the level of flexibility. stage two: findings and discussion 17 in this section we will present and discuss the findings of the quantitative analysis. further, we provide an analysis regarding the implications these results might have, both practically and in future research. the section begins with the analysis of figure 2. key adoption factors mean values the overall results and then it focuses on the comparison between the categories mentioned in table 4. due to the inability to draw significant figure 3. key adoption factors – descending order statistical conclusions from the data gathered, the analysis will be centred on polar results or, to be more precise, on results that scored extremely well or poor in the questionnaire. figure 2 represents the overall results and it can be understood that the higher the value in the bar chart, the more important is the specific key adoption factor, according to the survey’s respondents. hence, in figure 3, we represent the key adoption factors in descending order. 18 table 5: key adoption factors descending order overall results from the analysis of the questionnaire’s results, the single most important factors are represented by the software functionalities. other authors discuss this element in their works (sheikh, 2011; jadhav and sonar, 2009), but without paying particular attention to its importance. from these results, it is clear that cloud bi’s customers care about the software’s functionalities. even though it is quite normal that a prospect pays attention to the functionalities of an application, the highest score achieved could be explained in the following way: as previously mentioned, in the past years the number of business intelligence vendors have increased greatly. some of them specialize in a particular niche of the market; for instance rj metrics provides solutions for e-commerce businesses. therefore, the customers expect a software that effectively addresses most of the problems in a specific domain. we will not analyse minutely all the other key factors in this short paper, but it is interesting to provide a more detailed picture of the most and least important ones; ubiquitous access to data (using any device, in any location, and in any format), responsive answers to customer support requests, handling big amount of data and implementation cost earned their position in the highest end of the table. all of these factors belong to different categories, resulting in four different categories for the first five elements. this is a remarkable finding and stresses the significance of excelling in multiple areas and not focusing on a single one. ubiquitous access to data is an order key adoption factors 1 the level of functionalities and capabilities offered by the product 2 ubiquitous access to data 3 responsiveness to general support requests 4 the ability to manage different amount of data 5 the amount of implementation cost (training, setup..) 6 ability to share reports through the software web interface 7 the speed of the product in performing analyses 8 the effort required to deploy the product on a large scale basis 9 the level of customization and personalization 10 the amount subscription cost (monthly or yearly fee) 11 level of integration with other bi applications or databases 12 ability to offer actionable insights 13 the level of security guaranteed by the vendor (backup, recovery and privacy) 14 vendor’s clarity to customer support requests 15 provider’s brand reputation (including partners, suppliers and testimonials) 16 the simplicity of the interface 17 the level of skills needed to perform meaningful analyses 18 the level of flexibility in terms of contract agreements and conditions 19 the ability to handle data in real time 20 ability to handle multiple sources of data (excel, google documents, etc.) 21 web-data analysis 22 offline access to data 23 tablet and mobile integration 19 important factor that confirms the results of previous studies (table 2). in addition, with increasing access to the internet and the internationalization of many companies, bi customers know that their data reside in multiple locations and thus expect the bi software to connect all the sources together. in this way, data accessibility from anywhere and at any time (sheikh, 2011) becomes not only feasible, but also necessary to have a better understanding of the overall company’s performance. cloud computing and its technological architecture foster data accessibility whenever a connection is available. the users do not have to worry about different data formats or computer platforms (table 2), since the files containing the data are stored in a separate location (“the cloud”). in order to offer the customers real ubiquitous access to data, we suggest cloud bi vendors to focus on two aspects: web browsers and multiple devices integration. it is true that cloud technology works whenever a connection is available, but users have different preferences regarding web browsers (oh and lee, 2011). as a consequence, it is the vendors’ duty to make sure that data is represented in the correct way, irrespective of the web browser used by the customer. moving to devices integration, gartner research (2013) forecasts a shift from desktop pcs to mobile devices in the following years. this escalation of smartphones and tablets’ sales undoubtedly promotes ubiquitous data accessibility, provided that cloud bi sellers are able to show the same results on multiple devices. responsive answers to customer support requests achieved the third highest position. this factor does not represent a specific software functionality but is more related to the perceived experience that customers have during and after the purchase. this result gives evidence to the importance of serving customers in a professional way, in addition to offering a valuable software. if we look at the other key adoption factor belonging to the category “support”, it scored slightly above average and strengthened the importance of providing a good customers service in the decision process of choosing a cloud bi software. why is the customer service so important? it might be that small and medium sized enterprises can only rely upon a limited number of resources in comparison with big enterprises. the latter often have an appropriate department responsible for solving it-related problems while smes might not have the technical or financial capabilities to deal with complex problems of this sort. this could explain why smes rated so highly the importance of the customer service. further, a software capable of handling big amount of data is a fundamental requisite for the customers. given the rapid growth of data available (ibm research, 2011), a cloud bi software should be able to combine millions or even billions of data points and detect valuable trends or patterns. doing this operation within an acceptable time span represents a challenge from a technological point of view and bi suppliers should dedicate resources to address this important matter. finally, the total implementation cost is the last factor that scored 4 or above. cost is definitely one of the main benefits offered by saas products and customers still pay attention to this aspect (table 2). however, what is interesting to highlight is that the highest ranking was achieved by the implementation cost rather than the subscription cost. by looking at traditional bi implementation projects, the implementation phase is the most critical one and it may last for years (watson and wixom, 2001), demanding important resources. despite this cloud bi implementation is not a process as critical as in traditional bi, customers may still be worried and this can explain why the one-time implementation cost scored higher then subscription costs. moving to the opposite side of the table, three factors stand out for their low scores: tablet and mobile integration, offline access to data and webdata analysis. in light of the precedent analysis pertaining ubiquitous access to data, the position reached by tablet and mobile integration seems counterintuitive. given the previous considerations and the gartner research (2013), analysing data through multiple devices should have been an obvious necessary functionality. nonetheless, our research reveals that this factor bears the lowest value. on the one hand, the representative sample of 36 respondents is not sufficient to draw a reliable conclusion and, as aforementioned, the results of this study can only provide a direction for 20 more in-depth research. on the other hand, it is possible that smes are not fully interested in displaying data on multiple devices. if they have a business restricted to a limited region or if they dispose of only a single office, the utility of having data everywhere loses some importance since there is no need to bring data around and display it on multiple devices. alternatively, the purchase of a cloud bi software might be the first data analysis solution adopted by some smes. hence, they would be more interested in basic functionalities and overlook others of minor importance. in any case, these are only tentative explanations and only represent the authors’ perspectives. offline access to data is the second least important key adoption factor. we have not found this element mentioned in the previous literature, but it came out during the qualitative interviews. the interviewees mentioned that one of the drawback of cloud technology is its dependence from the availability of the internet connection. it does not represent a problem in most western countries, but in the developing world it might be. this is the reason why offline access to data has been included in the study. however, the result speaks for itself. customers are not interested in accessing data in offline mode and this could have been foreseen in advance to some extent. indeed, when the decision of buying a cloud bi solution is made, the customer is well aware that most of the interactions with the software require an internet connection. the last element that scored poorly is the ability to analyse data coming from web-sources. despite social networks' popularity having risen and fallen in the early 2000s (ellison, 2007), in the past years it has gained considerable attention all over the world. initially these social platforms were used only as a means to communicate with friends, but later many organizations understood the enormous potential behind them. in fact, spontaneous customer feedback quickly spreads throughout the social networks, blogs, newsgroups and it represents a potential source of information for business intelligence tools (gamon et al., 2005). recently, the techniques developed to analyze this type of unstructured data have made great progress and we had expected a different score for this factor. most of the unstructured data belongs to web-content and a recent report released by myob business monitor reveals that the overall online social presence for small and medium sized companies is rather low (stafford, 2012), even though it is on an upward trend. this result can partially explain why the analysis of web-data sources scored poorly in the questionnaire. however, given the benefits achieved by those who extensively use social media channels and the expected growth in this domain (milman, 2013), the rank achieved by this key adoption factor may change substantially in the near future. three factors have been represented separately (figure 4), given their different nature: 21 figure 4. payment method, customer service and type of preferred solutions by looking at the figure 4, the first thing that immediately stands out is the staggering preference for solutions built towards the industry’s needs. therefore, from the result it’s clear that customers prefer to buy applications that deliver analyses only relevant to a specific market sector, and not industry-wide. indeed, buying a fit-all product offers minimal value. for instance, the type of analyses required in the supply chain industry differs from the ones needed by insurance 22 companies. in the former, customer will be more interested in spotting opportunities for cost reduction throughout the chain, by analysing performance level or by adjusting manufacturing production according to the different requests (baars et al., 2008). in the latter, insurers can gain significant value by detecting fraud through the cross-analysis of multiple sources of data, such as fraud patterns, accidents, social networks, and medical and criminal records (brat et al., 2013). however, given the focus of our study on small and medium sized organizations, where the boundaries between departments may not be well-defined or even exist, the result makes more sense. smes want a solution that offers benefits for the whole company, not merely for a single business department. this conclusion could differ for big organizations, where the hierarchical structure is usually more rigid. a second element appears in this study: customers prefer to pay the subscription costs either on a monthly or a quarterly basis. at first sight this factor seems not very important and we have not found any theory that discusses this in detail. however, it came out two times during the explorative interviews and it was included in the questionnaire. common sense would suggest that paying a software on a monthly basis is a daunting process for a company. nevertheless, smes prefer not to lock in with a single product for a long time and they reserve the right to cancel the contract anytime if the solution does not deliver the expected value. it is worthwhile remembering that for some smes the purchase of a cloud bi solution has never been done before and therefore there is an element of uncertainty and skepticism. by paying on a monthly or quarterly basis, having the freedom to cancel the contract without losing money becomes an important element and it could explain the outcome of the survey. lastly, it does not come without any surprise that phone and email are the most preferred methods for interacting with customer support. we included this question in the survey because various vendors extensively promote the availability of the live chat and the 24/7 support in their offering. even though our data set is not representative for the population of smes, there is an initial indication that customers still rely on traditional communication media. in the following paragraph we analyse the results for each category, referring to figure 4. as aforementioned, we can only draw tentative but still interesting conclusions by looking at the opposite results. there are three categories that got a similar score: support, cost of ownership and functionality-performance. customer support is an essential part that has to be incorporated into the product offering. during traditional bi implementations, support is given through training initiatives, consulting services and other activities (table 3). hence, there are often face-to-face interactions between the supplier and the customer. with cloud bi solutions, it’s likely that most of the services will be delivered online, including the customer support. for this reason, it’s crucial to adhere to certain quality standards and make sure the customer receive a good service. as expected, the cost of ownership revealed to be an important area that smes pay attention to. the previous literature recognizes its importance, as shown both in table 1 and 2. in fact, a minor financial risk is one of the main benefits offered by cloud technology (finch, 2007; olszak and ziemba, 2012). this is appealing for small and medium sized enterprises (benlian et al., 2009). hence, to some extent this result confirms previous theories. moreover, by going into the details, it can be seen that both the subscription cost and the implementation cost achieved similar results. this is important because it implies that customers are not lured by cheap offerings that address only one part of the total cost of ownership, but they pay equal attention to all the parts of the financial investment. therefore, cloud bi vendors should carefully balance their price regarding the total cost of ownership. the last area with a relevant score is functionality. this result also strengthens the previous analysis, where a key adoption factor that belongs to this category reached the first position in the survey. functionality is a big area that encompasses items quite different from each other. despite this difference, all the elements scored similarly in the questionnaire, except handling data in real time which is well below the average. generally, real time data comes from web-sources which are characterized by a quick spread of information: an article, an opinion or a statement. therefore, handling data in real time and the ability to analyse 23 data coming from web-sources are closely related and can explain the poor results achieved by both of these factors. in all cases, functionality plays a big role for smes, and this may not come as a surprise because every company is in principal interested in this category. however, common knowledge about cloud bi would suggest that often the functionalities and performance do not reach the high standards of traditional bi. this is due to two reasons. on average, cloud solutions costs less than traditional ones and the overall quality might be affected as a consequence. in addition, traditional bi solutions are built and customized specifically around the needs of the clients and the functionalities will be more accurate than a “universal” tool. despite these premises, the results of the study indicates that smes have high expectations in terms of performance and are not willing to pay for a cheap solution which does not add any specific value to the organization. on the opposite spectrum, a category that did not score as well as expected is integration. as remarked by the interviewees, one of the very first question asked by a potential customer is “how well does the solution integrate with my applications?”. thus, we expected a much higher consideration here. nevertheless, by looking only at the average result, the conclusions we would draw may be misleading. if we pay attention to figure 4, the score of each element belonging to the integration category differs substantially. the general level of integration is positioned well and it partially contradicts the previous conclusion about integration. the two key adoption factors that lowers the average result are mobile devices integration and the ability to handle multiple sources of data. we talked about the former in the previous section while it is necessary to think about the result achieved by the latter. as remarked by gamon (gamon et al., 2005), the potential sources of information for business intelligence are growing exponentially. valuable data are found not only in traditional spreadsheets, but also in blogs, social networks, activity logs and many places. therefore, if an organization is willing to have an overview of its customer base, it’s necessary to analyze multiple sources of data. there is a possible explanation of why this is not the case for smes. small and medium sized enterprises still rely heavily on data stored in traditional spreadsheet (e.g. excel) and more than 80% of them use desktop spreadsheet as the only analytical tool in the company (maguire and magrys, 2007; ashrafi and murtaza, 2008). this might partially explain why they are not interested in analyzing different data formats, but prefer to have a product for spreadsheet analysis such as excel. conclusions and implications based on the research findings, there are five key adoption factors that scored 4 and therefore are classified as the most important:  the level of software functionalities (all)  the ubiquitous access to data (sme)  responsive answers to customer support requests (sme)  handling large amounts of data (all)  implementation cost (all) each of these factors addresses a specific area that customer pay close attention to during the adoption process of a cloud bi solution. the importance of handling different amounts of data, the software functionalities and the implementation cost confirm what has been found in the previous research, both for traditional and cloud bi. on the other side, the score reached by the other two factors can be tightly connected to cloud technology. providing an excellent customer service becomes important where the face-to-face interactions are kept at minimum. finally, the increasing spread of data and the process of globalization calls for an ability to access data everywhere. in terms of the categories, the results do not show any important dominance in a specific area, but rather, there are 3 categories that reached a similar level: support, cost of ownership and functionality. this outcome strengthens the statement that smes look for a software that is complete on multiple areas and do not stick to one area in particular. practical implications this study has several important managerial implications, for providing more information and knowledge about the key factors for successful adoption of cloud bi software in smes. managers and head of departments can leverage the findings in order to craft better value propositions or prioritize areas of development according to what customers value the most. we suggest to bi suppliers the following areas of discussion: 24  it is commonly agreed that cloud software will become a cornerstone of almost every business (sheikh, 2011). this revolution has already started: from email services to traditional systems like crm, they are now being adopted in an on-demand fashion (sheikh, 2011). the classic concept of delivering goods to customers is being overcome by the idea of providing an ongoing service in exchange of a monthly fee (östling and fredriksson, 2012). therefore, even the sales process has to change from the “one-time” selling to the development of long-lasting relationships, with the attitude of offering value to clients on an ongoing basis. one of the most effective and successful ways to address this issue is to meet the customers’ expectations related to the specific software. from the questionnaire’s analysis it’s clear that successful cloud bi products excel in multiple areas, from the functionality to the reliability, going through customer support and a fair price-quality ratio. hence, balancing the resources in the appropriate way becomes an important matter, avoiding overlooking some areas or focusing too heavily on others. moreover, it is critical to shift the mentality from selling goods to delivering value to customers by building solid relationships (östling and fredriksson, 2012). whenever the customer perceives that there is no cooperation, the relationship will likely interrupt. this means the cancellation of contract and a loss of income for the bi provider.  bi vendors’ marketing managers should create material that reflects what customers really want. in this particular case, it’s fundamental to promote a bi solution as a comprehensive package that delivers high value at a fair price point, supported by an excellent customer support service. alternatively, it is also effective to mention the five most important key adoption factors and stress their importance.  one of the main reasons that motivate small and medium sized enterprises to embrace the cloud solutions is the perspective of lowering it costs (östling and fredriksson, 2012). this common perception is supported by real data and real companies who did experience a decrease of hardware and maintenance costs by adopting cloud technology (perry et al., 2009). the importance of costs is also reflected by the results of this study, but there are other areas of equal significance from the customers’ perspective. one of them is definitely customer support. in the past years, outsourcing has been grown steadily and became a global phenomenon (rao, 2004). with the improvements of telecommunications infrastructure, it operations can be managed efficiently in countries where labor cost is lower (rao, 2004). even though the financial benefits are immediately clear, the quality of the service can damage the reputation of the company, if it does not reach high standards. given the previous premise of a model shifting towards a customerrelationship focus, we suggest to think carefully before outsourcing the customer support activity for cloud bi software. it is fundamental that requests are handled by experienced people, who knows the software well and can make specific recommendations to solve any issue. this will help building trust in the relationship. the results of this paper can be leveraged by small and medium sized enterprises. they can benefit from a more comprehensive understanding of the factors that are critical for a successful adoption of a cloud business intelligence solution. on the opposite side, the factors that are not important can pose a serious threat to the achievement of adequate satisfactory levels. unlike the majority of previous studies, this investigation proposes five factors which are specifically tied to the needs of small and medium sized enterprises, providing a ground for future empirical research in this domain. the proposed set of key adoption factors is itself important, because it can act as a list of items to be checked during the evaluation process (wong, 2005). this helps to ensure that essential issues and factors are covered when an organizational plan to adopt a cloud bi solution for managing information (wong, 2005). moreover, it is of primary importance for business intelligence newcomers, who are evaluating the purchase of these solutions for the first time and may be confused by the amount of different alternatives available in the market. therefore, the results of this study can provide a guidance and a basis for evaluating and comparing different solutions. theoretical implications 25 this study has also interesting implications for future academic research. the literature highlights the necessity to study more thoroughly business intelligence in small and medium sized enterprises (benlian et al., 2009), since the majority of studies were focused on big organizations and the same results may not be applicable to the sme’s landscape. we found two areas where the contribution is substantial. first and foremost, the results expand the body of knowledge related to small and medium sized companies. they confirm that the needs of smes, in terms of bi software, differ from large organizations, at least on certain areas (insideinfo whitepaper): multiple sources of data, tablet and mobile integration and real-time data analysis. moreover, our findings provide new information of how smes evaluate a certain typology of it software. in addition, this investigation adds knowledge in connection to an up and coming technology: cloud computing. in particular, it focuses on a specific context in which this technology is used, for smes, which has been poorly explored in the past. as mentioned by yeoh and koronios (2010), in the market sectors highly influenced by technological innovations, such as cloud services, the value of previous discoveries declines over time. by using recent primary data, future research on critical success factors will be more reliable. suggestions for further research the commercial availability of cloud solutions dates back only few years. this is the case especially for cloud bi, which is still in the early phase of the growth curve (bucur, 2012). the implications of adopting a novel technology may not be fully understood yet. therefore, the respondents’ answers reflect this particular industrial situation. further research on the same topic in three or four years’ time is suggested, if not before, when the adoption rates of cloud bi software will likely be higher and the sample of suitable candidates will be larger. it would be interesting to see if, in the future, the key factors for adopting a cloud solution will differ and help understand the underlying motivations. a research 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(2021) strategic thinking and competitive intelligence: comparative research in the automotive and communication industries. journal of intelligence studies in business. 11 (2) 53-68. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 2 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index strategic thinking and competitive intelligence: comparative research in the automotive and communication industries mehmet emirhan kulaa and atılhan naktiyokb,* aerzurum technical university, business administration department, erzurum, turkey; bataturk university, business administration department, erzurum, turkey; * emirhan.kula@erzurum.edu.tr journal of intelligence studies in business please scroll down for article strategic thinking and competitive intelligence: comparative research in the automotive and communication industries mehmet emirhan kulaa and atılhan naktiyokb,* aerzurum technical university, business administration department, erzurum, turkey bataturk university, business administration department, erzurum, turkey *corresponding author: emirhan.kula@erzurum.edu.tr received 25 august 2021 accepted 24 september 2021 abstract the main purpose of this study is to examine the effect of strategic thinking skills of executives on competitive intelligence in high competition intense industries. the concept of strategic thinking represents a cognitive process that was examined along with system thinking, creativity and vision dimensions. on the other side the concept of competitive intelligence was evaluated with the dimension of competitive intelligence context and the competitive intelligence process as a process that represents the systematic collection of information about competitors through legal and ethical ways. in this study, the concepts of strategic thinking and competitive intelligence are examined around the related literature and to what extent these concepts are related to each other was investigated as well. since the research on this relationship has a unique attribution, it contributes to the related literature. to test the model formed in line with the main purpose of the research, data were collected from 628 executives, who work in five high competition intense automotive industries and three communication industries, using a questionnaire method. the developed hypotheses were evaluated with appropriate analysis methods. in addition, industrial differences were revealed by comparing the two industries with appropriate analyses. according to the findings of the analysis, the strategic thinking skills of both executives participating in the research as well as the executives working in both industries have a positive and meaningful effect on their competitive intelligence. the study has made a significant contribution to the literature in terms of examining and explaining the relationship between the concepts of strategy and competition through the interaction of strategic thinking and competition intelligence. keywords automotive industry, communication industry, competition, competitive intelligence, strategic thinking, strategy this study is derived from the phd thesis titled “strategic thinking and competitive intelligence: a comparative research in automotive and communication industries” by m.e. kula. 1. introduction business history is written on the interaction of strategy and competition. while the necessity of the strategy needs the existence of competition, the fiction and pattern of the strategy have been guiding the scope and dimensions of competition. today’s environmental conditions make it impossible for businesses to achieve sustainable success by only making some plans and applying these plans step by step. businesses have to find ways to cope with turbulent environmental conditions and hyper-competition. all of the journal of intelligence studies in business vol. 11, no. 2 (2021) pp. 53-68 open access: freely available at: https://ojs.hh.se/ 54 environmental factors that businesses carry out are vital activities and constantly changing. businesses have to adapt to this drastic change and manage the change correctly. considering the age of information technology we are in, it is not an easy task to evaluate all environmental factors separately and to achieve the big picture by combining the parts. so, business managers must find answers to ever-changing questions such as: why is one market and industry more profitable than another? why is it riskier to trade in one region than another? why are some businesses operating in the same industry more successful than others? what are the factors that make businesses successful or unsuccessful? what measures should managers take for the success of their businesses? however, all answers have a common purpose which is to give the business a competitive advantage. so, it seems possible to summarize all the questions stated above with a single question. how can businesses achieve a sustainable competitive advantage? in the study, it was assumed that managers who have strategic thinking skills can use their competitive intelligence skills more effectively. in other words, the proposition that strategic planning will create competitive advantage, which has been going on for nearly half a century, lost its meaning with the introduction of information technologies. therefore, in this study, the effect of strategic thinking, which is supposed to establish a bridge between the past and the future over the present, on competitive intelligence, which is a way of obtaining information that is supposed to provide competitive advantage, is examined. in this study, answers to three questions have been sought based on this essential inquiry: does strategic thinking affect competitive intelligence in industries with high competition intensity?": (1) can business managers think strategically in competitive industries? (2) do business managers care about the competitive environment and competitor analysis in competitive industries? and (3) how does strategic thinking affect competitive intelligence in the automotive and communication industries? 2. theoretical framework 2.1 strategic thinking strategic thinking is understanding that things cannot always be solved with a linear approach. for this reason, organizations have to find ways to adapt to environmental uncertainties in a more informed, agile and flexible way. at this point, strategic thinking emerges as a cognitive process that also takes competitive alternatives into account and reveals ways to solve environmentalorganization uncertainties more sensitively and prudently (fairholm and card, 2009: 22; o'regan, hughes, collins, and tucker, 2010: 59). in other words, strategic thinking is not a sequence of systematic plans, but a pattern of cognitive planning. rather than a road map to follow, it is a bird's eye view of all the roads to reach the destination. thinking strategically, of course, requires being able to make predictions about the future, which is about determining the direction of all variables affecting the organization (critelli, 2005: 48). in this respect, scenario and forecasting techniques attract attention as strategic thinking methods that organizations can use to discover unforeseen details and possibilities for the future (ramírez and selsky, 2016: 100). strategic thinking is seeing the future. however, it is not possible for managers who do not understand what has happened in the past to predict what might happen in the future (mintzberg, ahlstrand, & lampel, 1998: 126). in this sense, people who can think strategically are people who use the past by looking forward, and who can predict the future by looking back. therefore, strategic thinking can offer innovative solutions to complex events in a turbulent and hypercompetitive environment which has the potential to change the rules of competition and to depicture the future (zahra and nambisan, 2012: 220). as a result, the business environment is surrounded by many decisionmaking factors, and businesses are affected in some way by these decisions. the degree of impact is directly proportional to how effectively the enterprise can use its basic skills. for this reason, strategic thinking is the art of overcoming the opponent in a way and doing it with the same thing in mind that they are trying to apply to you (dixit & nalebuff, 2015: 7). mintzberg (1994b) argued that strategic planning is analysis and strategic thinking is synthesis, explaining the basic approach difference between strategic planning and strategic thinking. so much so that while strategic planning is concerned with how to implement the already determined strategic programs and methods, strategic thinking can 55 reveal the synthesis that will build the future of the business as a result of organizational learning. in other words, strategic planning is the analysis of systems and methods, while strategic thinking is a synthesis of intuitive, creative and innovative thinking (steptoewarren et al., 2011: 239). according to haycock et al. (2012), while strategic planning means the implementation of strategies within a systematic and logical system, strategic thinking is a process that encourages creative and innovative thinking to overcome the dynamic and often unpredictable difficulties encountered in today’s economy. this study was based on bonn’s threedimensional strategic thinking model (2001). while bonn (2001) defines strategic thinking as a cognitive way of solving strategic problems creatively with a rational approach, she states that strategic thinking consists of systems thinking, creativity and vision. system thinking deals with the organization as a whole in interaction with its environment. there is a backward working principle, first to the whole and then to each subsection of the system. it tends to formulate basic strategies with a general to specific perspective (haines, 2000: 34). in other words, system thinking is the ability to see the system as a whole in order to understand the properties, forces, patterns and relationships that shape the behavior of systems (pisapia, reyes-guerra and coukossemmel, 2005: 48). creativity is a human-specific intellectual process that can be beneficial to overcome existing problems to generate new ideas (i̇şcan and karabey, 2007: 104). in the organizational sense, creativity refers to the ability to establish extraordinary connections between all business ideas that constitute the reason for the existence of the enterprise in line with the interests of the organization (robbins and coulter, 2012: 166). the strategy is to be able to develop creative ideas and innovative solutions in order to gain competitive advantage. in this sense, creative thinking represents a process that starts with generating ideas (bonn, 2001: 65). vision expresses the future that businesses desire. the vision of a business is the declaration of its strategic intention that will enable the business to focus on achieving its goals and objectives (craig and campbell, 2005: 26). one of the most challenging tasks of managers is to keep the direction of the business stable under complex environmental conditions. in this sense, the vision can be defined as a vanishing point that shows the direction of the business (moon, 2013: 1700). vision, which is an important part of strategic thinking, helps business employees to work in a focused and motivated way without deviating from their goals. in addition, it contributes to businesses to see their current and future potential and to develop strategies accordingly (fairholm and card, 2009: 23). 2.2 competitive intelligence businesses that want to turn environmental threats into opportunities should obtain systematic information about their competitors. the competition information process predicts that businesses take three basic steps behaviorally: obtaining information about the competitor, interpreting and adapting (li, and calantone, 1998: 16). before giving details about the concept of competitive intelligence, which will be based on these three steps, it is useful to explain why the concept, which is also translated and used as competitive intel in the literature, will be used as competitive intelligence (systematic mind development on competitors) in our study. when the place of competitive intelligence activities in business activities is examined, it is seen that the focus of the concept is knowledge, but more importance is placed on analyzing the acquired information rather than (secret) information acquisition. in addition, competitive intelligence is not a business function, but a cyclical, systematic and external environment-oriented process that has certain steps between its beginning and end. in addition, competitive intelligence does not mean analyzing what happened in the past, but acting towards the future proactively (rouach and santi, 2001: 554; köseoglu et al., 2016: 163). as a result, competitive intelligence activities represent a dynamic and multidimensional structure as they are carried out in an environment where rules and players are constantly changing. in addition, although it is not compulsory to utilize artificial intelligence technologies for competitive intelligence applications, it is indispensable at the point reached, given its contribution to decision-making processes; information is no longer just the publicly shared news, but the algorithms hidden behind them (liebowitz, 2006: 13). in this sense, it will not be possible to call the concept of artificial intelligence artificial intel. considering all these reasons, using the concept of competitive intelligence as competitive intel will be a “not 56 wrong but incomplete” expression, while using it as competitive intelligence will be a “more accurate and holistic” form of expression. many different definitions of competitive intelligence have been made by different researchers. provided that the operating logic is the same, different perspectives are presented to the focal point of the concept in the definitions. before giving a clear definition of what competitive intelligence is, it would be appropriate to explain what it is not. competitive intelligence is not pages of thick reports, espionage, eavesdropping, information and document theft about the competitor. its simplest form is to analyze the public information about the competitor (fuld, 1995: 23). businesses basically want to learn about their competitors for three reasons: curiosity, enthusiasm, and foresight. they are curious about their competitors’ activities simply because they operate in the same industry, and this curiosity can be simply satisfying. curiosity is not satisfied with a certain level and if some of the competitors’ activities are appreciated, the desire to envy and be like them will increase. ultimately, as the industry and the competitor are constantly followed, it will be possible to make predictions about the future, independent of the competitor (west, 2001: 13; wright, pickton and callow, 2002: 352). these behavioral approaches, which affect the strategic decisions of businesses in the long or short term, form the basis of competitive intelligence applications. in light of the above information, competitive intelligence can be defined as systematically gathering information from the industry and competition environment, legally and ethically. i then involved processing, analyzing and sharing the information collected in order to take action-oriented steps and thus make predictions for the future in order to guide strategic decision makers in enterprises and to ensure that the enterprise gains competitive advantage. the twodimensional structure developed by saayman et al. (2008) was taken as the basis of the research of competitive intelligence within this study. they discuss the competitive intelligence context and process as described below. the competitive intelligence context: competitive intelligence is a series of activities that enable systematic information gathering from environmental factors. the context of competitive intelligence consists of a number of attitudes and behaviors that form a framework for information gathering activities and directly affect them. first, competitive intelligence activities require organizational awareness. managers should be aware of the events happening around them and develop an attitude in this direction in order to keep businesses competitive. on the other hand, managers should create a culture that encourages information sharing at all levels. this situation, which can be expressed as a culture of competition, includes all mental and operational activities that encourage internal information sharing and turn it into a useful tool. since organizational awareness, organizational attitude and competitive culture cannot occur with the will and efforts of managers alone, systematic information sharing should be ensured with active participation of employees. these elements, each of which constitute the context of the competitive intelligence process individually, come together to form the context of competitive intelligence. the competitive intelligence process: the basis of competitive intelligence is that businesses gain strategic and sustainable competitive advantage. in this sense, the process of competitive intelligence refers to the process of creating information that will provide a competitive advantage to the business. in the process of competitive intelligence, first of all, the necessary information is determined and the necessary planning is made. the processes of collecting data from the external environment, transforming the data into information by analyzing it and distributing it to the relevant units within the enterprise are carried out especially with the help of information technologies, all of which are referred to as information design. businesses internalize the information they obtain through the information design process, while making a competitive comparison, revealing the fundamental differences between themselves and their rivals. ultimately, the process operates both as an important tool in the strategic decision-making processes of businesses and as an output that enables the business to determine its competitive position relative to its competitors. 3. the research model and hypotheses 57 although the importance of strategic planning and analysis of the competitive environment is accepted within the study, the interrelation and interaction between the strategic thinking skills of managers and their competitive intelligence has been investigated, especially in industries with high competition intensity and mutual firm dependence by considering the effect of technological innovations. as a result, the following model has been developed by discussing strategic thinking and competitive intelligence processes around the relevant literature. in order to test the research model, the following hypotheses were developed in light of studies that reveal the relationships between the relevant variables by scanning the strategic thinking and competitive intelligence literature. for managers, strategic thinking refers to establishing a systematic and structural link between events that are likely to affect the business directly or indirectly. in other words, strategic thinking can be described as a dynamic and innovation-oriented process as well as being cognitive. therefore, decisions caused by strategic thinking are expected to be creative, original and changing rules in the competitive game (heracleous, 2003: 25; tovstiga, 2013: 16). the literature shows that strategic thinking and competitive intelligence start at the same point at the cognitive level. competitive intelligence requires a certain level of awareness and attitude before various information gathering activities. in addition, schein (2004) points out the importance of valuing new thoughts, beliefs and assumptions while listing three basic elements of creating an organizational culture. in this sense, it is thought that there is a strong relationship between strategic thinking and the scope of competitive intelligence, given that managers can create a competitive culture at a certain level by giving importance to creative thinking, and they can ensure their contribution to the long-term goals of the enterprise to the extent that they can convince employees. there is a significant relationship between the cognitive abilities of individuals and environmental factors. in other words, it is a process that requires the use of cognitive abilities for managers to consider and evaluate the complex structure that constitutes the business environment as a meaningful whole. businesses are the main actors of industries. in this sense, businesses that want to create a sustainable competitive advantage and strengthen their competitive position against their competitors must first manage to see the big picture formed by small parts as a whole. interpreting the big picture correctly to obtain the required information is possible with an organizational culture in which employees can demonstrate their creative talents. opening up space for creative activities that will result in innovation is directly related to the vision of that enterprise because vision is not just a text that represents the desired future. vision is the awareness and the attitude which an enterprise takes on about the future. vision is not a future plan determined by the manager of interest, but a process that all employees must participate in. as a result, the fact that business managers have strategic thinking skills with all the elements is directly related to the competition perception and competitive position of the business. for this reason, it is predicted that strategic thinking affects the scope of competitive intelligence. strategic thinking creativity system thinking vision ci context • awareness • competition culture • organizational participation ci process • focusing • information design • benchmarking competitive intelligence (ci) figure 1 research model: the effect of strategic thinking on competitive intelligence. 58 h1: strategic thinking affects the competitive intelligence context. h1a: system thinking affects the competitive intelligence context. h1b: creativity affects the competitive intelligence context. h1c: vision affects the competitive intelligence context. what businesses understand from the general conditions of the industry, which is called the big picture, is important. an industry becomes competitive through the behavior of the businesses in the industry before the structural features of that industry. for this reason, it is important to see the big picture, to create a forecast against strategic moves and competitive moves of competitors (gatignon and deshpande, 1994: 275). as a matter of fact, one of the main features of strategic thinking is developing foresight based on environmental analysis. managers who have strategic thinking skills should be able to develop a forecast beyond the horizon by successfully performing current situation analysis (hughes and beatty, 2005: 43). in this sense, strategic thinking skill requires focusing on the right information at the right time and completing the transformation of businesses through information design (garrat, 1995; 124). the disclosed information shows that there is a keen relationship between strategic thinking skills and factors such as planning and focusing, communication and analysis, information design and benchmarking, and the competitive intelligence process explained. as important as competition analysis is in the strategy formulation process, it is the focal points of managers in the industry that will guide the competition analysis. in addition, the way in which the information that will contribute to the strategy formulation process is obtained and how it turns into strategic information is also important. so much so that managers need creativity in business processes for both operational and strategic moves. while it is a necessity to support strategic moves with information about competitors, the way information is obtained and its interpretation often depends on the use of the creative skills of the employees in the relevant unit. in addition, businesses have to predict which steps to take and when and how to achieve their visions, which creates a need for systematic information, especially about the competitive environment. in other words, in terms of business activities, vision is not a dream but an imagined reality. for this reason, we predict that strategic thinking will affect the competitive intelligence process. h2: strategic thinking affects the competitive intelligence process. h2a: system thinking affects the competitive intelligence process. h2b: creativity affects the competitive intelligence process. h2c: vision affects the competitive intelligence process. managers who have strategic thinking skills want to depict future situations. in addition, they try to steer competition and change because, besides its other functions, strategy is the art of determining attitude and behavior according to the complex structure of the competitive environment (henderson, 1989: 140). in other words, the relationship between strategic thinking and environment is too extensive to be explained only by the relationship between the business and its external environment. strategic thinking is the ability to look at the competitive environment through the eyes of the competitor, and to evaluate the components of yesterday, today and tomorrow as a whole. such skills require the combination of cognitive ability and systematic knowledge, since businesses are living organisms that always interact with their environment. as a result, strategic thinking refers to the cognitive process that provides the collection, interpretation, transformation and evaluation of data that constitutes a sustainable competitive advantage of an enterprise (haines, 2000: 35; hughes and beatty, 2005: 4). in this sense, it is seen that strategic thinking is a precursor of competitive intelligence and has a strong relationship with competitive intelligence. strategy is a structure built on the strengths and weaknesses of a business. the main question to be answered while building this structure is whether the enterprise creates an added value in line with its goals and objectives. in order to answer this question, it is necessary to look at the structure called strategy from a more holistic perspective (jacobs, 2010: 4). this information highlights the importance of obtaining, interpreting and using information about competitors when needed in the strategy formulation process. 59 while strategic decisions need competitor analysis, depicting a bird’s eye view of the competitive environment in the mind and presenting the right perspective from the right angle is the strategic thinking skill. therefore, it is predicted that strategic thinking affects competitive intelligence. h3: strategic thinking affects competitive intelligence. h3a: system thinking affects competitive intelligence. h3b: creativity affects competitive intelligence. h3c: vision affects competitive intelligence. one of the main problems of strategic management is that it has not developed enough theory to describe the behavior of firms and industries. for example, although it is known that intense competition in the oligopoly market may change places with stability from time to time or new technologies and competitors may have a serious impact, it cannot be predicted when or what results will occur. this is because the oligopoly market matures as a result of the dynamic interaction between firms, government, labor, consumers, financial institutions and other environmental factors. for this reason, the industry structure in the oligopoly market does not affect firm behavior but the firm behavior determines the structure and competitive dynamics of an industry at the same time (levy, 1989: 167; bartlett and ghoshal, 1998: 87). in general, the market structure represents a continuum where businesses supply their goods and services and customers demand, with perfect competition and monopoly markets at both ends. within this continuum, the relationship between the total number of competitors and the impact of any competitor on the market is shown in figure 2. an oligopoly market is a type of market where there are few companies with a high interdependence and interaction, and many competitive tactics are used to eliminate competitors (hall and bensoussan, 2007: 259). in this sense, the automotive industry is an ideal example for evaluating the oligopoly market, with its small number of companies on a global scale and its differentiated products (goldberg, 1995: 892). indeed, sturgeon et al. (2009) stated that the automotive industry is unique, and that a small number of japanese, german and american companies dominate the industry on a global scale and direct the behavior of numerous small and medium-sized enterprises from automotive and other industries. in addition, çoban (2007) and daştan (2016) stated in their studies on the automotive industry that the automotive industry has a strategic importance, which has the potential to lead other industries in the economy, and state that the development of h ig h h igh l ow l ow number of competitors in the market the inf lue nce of any co mp etit or o n th e ma rke t st ruc ture perfect competition oligopoly monopoly figure 2 continuity of market structure. adapted from cambell & craig, organizations and the business environment, 2005, p. 407. 60 this industry is fundamental to trade policy for countries. staying competitive within this market structure will be possible by transforming creative thinking skills into innovative products, having a vision that will design the future, and responding to the behavior of competitors with strategic moves. in conclusion, considering the structural characteristics of the industry such as the degree of differentiation of the product in the automotive industry and its high place in the customer budget, the need for substitutes and suppliers, and the intensity of non-price competition on a global scale, it can be said that the automotive industry is located on the side of the oligopoly market, close to the perfect competition market compared to the communication industry (figure 2). therefore, it is predicted that managers’ strategic thinking skills are high in the automotive industry. h4. in the automotive industry, managers have higher strategic thinking skills than in the communications industry. another feature of the oligopoly market is the imitative firm behavior that develops because of firm interdependence. accordingly, for example, the price competition initiated by any firm to gain competitive advantage will be instantly responded to by other competitors who want to host in the industry (levy, 1989: 170). in this sense, the communication industry is one of the industries characterized by high competition, depending on its speed in technological change (ganesan, 2007: 1). explaining the imitative behavior of firms through price competition alone would be an incomplete perspective. firms can imitate not only price increase or decrease policies, but also business processes and outputs. he and mu (2012), comparatively analyzed the technological learning processes between chinese national companies operating in the communication and automobile industries and foreign companies that invest directly in china. according to the results of the research, compared to the automotive industry, companies operating in the communication industry can develop their technological learning skills and increase their technology capacity by competing directly with foreign companies. the communications industry had a lowcompetition market structure dominated by monopoly firms. however, the 1980s caused structural changes in the communication industry, as in many industries, with the transformation of the market structure from monopoly to oligopoly from the transformative effect of technology as of the 1990s. factors such as the privatization of state-controlled companies, the global widespread use of mobile phones and the internet network, and the redefinition of seller and customer relations meant a global spread of competition (trauth and pitt, 1992: 3; wang et al., 2004: 325). a limited number of companies in the communication industry compete to increase their market share over a large number of customers. in this sense, short-term tactical decisions are as vital as the strategic decisions of companies. a formal competitive intelligence program has a determining effect on tactical decisions and a guiding power for the firm, especially in oligopoly market conditions where price competition is tight. as a result, the degree of differentiation of the commodity in the communication industry and its place in the customer budget is low. considering the structural characteristics of the industry such as, for example, entry into the industry, and government permits, and the intense price competition on a local scale, it can be said that the communication industry is located on the side of the oligopoly market, but closer to the monopoly market compared to the automotive industry. therefore, it is predicted that managers’ competitive intelligence skills are high in the communication industry. h5. in the communications industry, managers have higher competitive intelligence skills than in the automotive industry. 4. method 4.1 determination of research population and sample selection considering that it will be suitable for the measurement of the variables in the model, it was deemed appropriate to conduct the research in industries with oligopoly market characteristics. it is accepted that the intensity of competition is high in both the automobile and communication industry within the oligopoly market structure (he and mu, 2012: 270). the research model investigates the effects of managers’ strategic thinking skills on their competitive intelligence. in this respect, while determining the scope of the research, managers who will directly or indirectly contribute to strategic decisions and who have 61 the authority to make competitive moves partially or fully were preferred. the scope of the research consists of automotive dealer managers which are executives of five companies with the highest sales brands according to automotive distributors association (www.odd.org.tr) in 2018 and for the communication industry, the provincial and regional directorates of the three turkish companies with the most subscribers according to the 2018 data of the information technologies and communication authority (www.btk.gov.tr). the sample size was calculated as 306 for the automotive industry and 306 for the communication industry (www.surveysystem.com/sscalc.htm), with a 5% margin of error within the confidence limits of 95%. considering the density of executives in the industries, the length of the survey form and the time they will devote to the survey, 500 surveys were distributed separately to both industries. after the incomplete, incorrect and damaged questionnaires were removed, a total of 628 questionnaires, 318 in the automotive industry and 310 in the communication industry, were evaluated. it should be noted that the questionnaire used for the research was created for the mentioned doctoral dissertation and the ethics committee approval was obtained (atatürk university legal consultancy dated 05.02.2019 and no. 48553601-000-e.19000433.057). 4.2 data collection tools: competitive intelligence scale and strategic thinking scale when examining the literature, a scale for measuring managers’ skills in competitive intelligence in turkey had not been developed. although a limited number of competitive intelligence surveys had been developed in the international literature, it was not possible to translate and use the scales exactly due to legal (radical differences in commercial and competition law) and cultural differences. therefore, a competitive intelligence scale was developed by utilizing studies including day and wensley (1988), dickson (1992), sawka, francis and herring (1996), hamel and parahalad (1996), li and calantone (1998), prescott (1999), guimaraes (2000), teo and choo (2001), qiu (2007), saayman et al. (2008), dishman and calof (2008), wright et al. (2013), the academic studies of köseoğlu et al. (2015), hall and bensoussan’s (2007) academic book and dugal (1996), hesford (1998), grooms (2001) and chen’s (2012) doctoral dissertations. in the questionnaire form, the items measuring competitive intelligence take place in the first 45 places and consist of two main (and six sub) dimensions. these dimensions are the competitive intelligence context and the competitive intelligence process. reliability analysis was conducted to determine the reliability of the competitive intelligence scale. according to analysis results, the correlation for any item is not lower than 0.30, which is taken as the cut-off point. for this reason, there is no need to remove any item related to the scale from the scale. generally, the reliability coefficient for the scale is 0.973. thus, the scale is considered to be reliable since this value is higher than 0.70 which is the acceptable limit for reliability. this strategic thinking scale has been used before and has been adapted from highly valid expressions. strategic thinking was examined in three sub-dimensions in the study. these are systems thinking, vision and creativity. the system thinking dimension consists of nine statements created by pisapia et al. (2005) and timuroğlu (2010). the vision dimension consists of nine statements created by timuroğlu (2010) and lahti (2003) and the creativity dimension consists of seven statements created by timuroğlu (2010) and murphy and reed (1991). in order to investigate the reliability of the strategic thinking scale, the internal consistency of the 25-item scale was investigated at the first stage. considering the items in the scale, it is observed that the total score correlation for any item is not lower than 0.30, which is accepted as the cut-off point. for this reason, at this stage, the analysis continued without removing any items from the scale. generally, the cronbach alpha coefficient of the scale was 0.960 as a result of reliability analysis and found reliable as well. 5. analysis and findings 5.1 factor analysis findings of scales in the second stage of the reliability and validity analysis of the strategic thinking and competitive intelligence scales, a varimax rotation exploratory factor analysis was applied. as a result of the second-level factor analysis applied to the strategic thinking scale, a three-factor structure was obtained by removing one item from the scale. it was observed that the three dimensions obtained explained 61.759% of the total variance, kmo 62 (0.958) and the barlett test was significant (p =.000) and the cronbach alpha value was 0.960. all fit index values of the structure (cmin/df: 4.77; gfi: 0.87; agfi: 0.85; cfi: 0.98; nfi: 0.97; ifi: 0.98; rmsea: 0.078) were determined to be at an acceptable level the 28-item structure obtained as a result of the fifth-level exploratory factor analysis performed for the competitive intelligence scale was verified and a six-factor structure was obtained. the first three of the six factors refer to the scope of competitive intelligence, and the last three to the competitive intelligence process. it was observed that the obtained six sub-dimensions explained 62.220% of the total variance, kmo (0.943) and the barlett test was significant (p =, 000) and the cronbach alpha value was 0.973. all fit index values of the structure (cmin/df: 3.74; gfi: 0.88; agfi: 0.85; cfi: 0.98; nfi: 0.97; ifi: 0.98; rmsea: 0.066) were determined to be at acceptable levels. 5.2 hypothesis tests findings in order to test the hypotheses that form the basis of the research and to determine the relationship between strategic thinking and competitive intelligence, a correlation analysis was performed on the data. correlation coefficients and descriptive statistics showing the relationships between strategic thinking (system thinking, creativity, vision) and competitive intelligence (competition intelligence context and competitive intelligence process) are given in table 1. based on the findings it is seen that there is a positive and significant relationship between strategic thinking and competitive intelligence in general at the 99% confidence level. a two-step regression analysis was conducted to determine the effect of strategic thinking and its dimensions on the competitive intelligence context, competitive intelligence process and competitive intelligence. in the first step, competitive intelligence context, competitive intelligence process and competitive intelligence are taken as dependent variables, and strategic thinking as an independent variable as a whole (sum of three factors). in the second step, the system thinking, creativity and vision factors that constitute strategic thinking are considered as independent variables, and the competitive intelligence context competitive intelligence process and competitive intelligence are taken as dependent variables. in terms of the reliability of the findings obtained in the regression analysis, the vif and tolerance values of the independent variables were shown to determine whether there was a multilinearity problem and it was revealed that these values showed that there was no multilinearity between the independent variables. detailed data on the findings are shown in table 2. first, the effect of strategic thinking on competitive intelligence context was examined. in the first step, strategic thinking as a whole has a significant effect (= 0.644; p <0.01) on the competitive intelligence context. by looking at these data, it can be said that h1 is supported. in the second step, the factors of strategic thinking (vision β = 0.320; p <0.01: system thinking β = 0.198; p <0.01 and creativity β = 0.196; p <0.01) have a significant effect on the competitive intelligence context and h1a, h1b, h1c are supported. table 1 correlation analysis of variables and dimensions. variables 𝐗" ss 1 2 3 4 5 6 7 1-system thinking 3.93 0.64 1 2-creativity 3.79 0.81 0.70** 1 3-vision 3.85 0.75 0.79** 0.74** 1 4-strategic thinking 3.86 0.66 0.91** 0.87** 0.94** 1 5-competitive intelligence context 3.85 0.65 0.64** 0.58** 0.66** 0.70** 1 6-competitive intelligence process 3.83 0.67 0.70** 0.62** 0.71** 0.75** 0.80** 1 7-competitive intelligence 3.84 0.63 0.68** 0.62** 0.70** 0.73** 0.95** 0.93** 1 63 table 2 the effect of strategic thinking and its factors on competitive intelligence, the competitive intelligence context and the competitive intelligence process. second, the effect of strategic thinking on the competitive intelligence process was examined. in the first step, it is seen that strategic thinking as a whole has a significant effect (= 0.727; p <0.01) on the competitive intelligence process. looking at these data, it can be said that h2 is supported. in the second step, the factors of strategic thinking (vision β = 0.316; p <0.01: system thinking β = 0.338; p <0.01 and creativity β = 0.140; p <0.01) have a significant effect on the competitive intelligence process and h2a, h2b, h2c are supported. finally, the effect of strategic thinking on competitive intelligence was examined. in the first step, it is seen that strategic thinking as a whole has a significant effect (β = 0.717; p <0.01) on competitive intelligence. according to these data, it can be said that h3 is supported. in the second step, the factors of strategic thinking (vision β = 0.335; p <0.01: system thinking β = 0.266; p <0.01 and creativity β = 0.182; p <0.01) have a significant effect on competitive intelligence and h3a, h3b, h3c are supported. the results of the independent two-sample t-test performed in order to reveal whether the industry variable makes any difference in terms of strategic thinking and competitive intelligence are shown in table 3. based on the findings, the industry variable creates a significant difference (p <0.01) in terms of system thinking, vision and strategic thinking. accordingly, it can be said that h4 is supported since the system thinking, vision and creativity scores of the participants working in the automotive industry are significantly higher than the scores of the participants working in the communication industry. on the other hand, it is seen that the industry variable creates a significant difference (p <0.01) in terms of the competitive intelligence context, competitive intelligence process, and competitive intelligence. accordingly, it can be said that h5 is supported since the competitive intelligence context, competitive intelligence process, and competitive intelligence scores of the participants working in the communication industry are significantly higher than the scores of the participants working in the automotive industry. 6. conclusion and evaluation this study was carried out to determine the effect of strategic thinking on competitive intelligence. in the literature review conducted for this purpose, it was seen that strategic thinking and factors affect competitive intelligence and its factors. for this reason, managers of the automotive and communication industries operating in the oligopoly market where the intensity of competition is high were selected as the sample and the effects of strategic thinking on the competitive intelligence were investigated by making an industrial comparison. for this purpose, by examining the strategic thinking and competitive intelligence models previously factors dependent variable competitive intelligence competitive intelligence context competitive intelligence process β t β t β t β t β t β t strategic thinking 0.717** 25.761 0.644** 21.635 0.727 ** 26.509 system thinking 0.266** 5.757 0.198** 3.941 0.338** 7.430 creativity 0.182** 4.092 0.196** 4.055 0.140** 3.195 vision 0.335** 6.766 0.320** 5.970 0.316** 6.507 durbin watson 1.367 1.368 1.447 1.447 1.433 1.437 tolerance 0.363; 0.391; 0.318 0.363; 0.391; 0.318 0.363; 0.391; 0.318 vif 2.756; 2.557; 3.145 2.756; 2.557; 3.145 2.756; 2.557; 3.145 r2 0.515 0.515 0.428 0.429 0.529 0.532 adjusted r2 0.514 0.513 0.427 0.426 0.528 0.530 f 663.614** 220.976** 468.062** 155.999** 702.702** 236.739** 64 developed in the literature, a research model was developed that reveals the relationship between strategic thinking and competitive intelligence. in line with the specified purposes, 628 executives operating in the automotive (318) and communication (310) industries were surveyed and the data obtained were evaluated and interpreted. it was possible to test the predictions for the purpose of the study by searching for answers to the research questions. the first question in the research was if business managers think strategically in competitive sectors. in order to answer this question, the averages and frequency distributions of the statements in the strategic thinking scale were examined and the general average of 25 statements belonging to the strategic thinking scale was found to be 4.02. accordingly, it can be said that the managers working in the automotive and communication industries have strategic thinking skills. strategic thinking has been analyzed separately according to its factors. the general average of nine statements measuring system thinking, which is the first sub-dimension of strategic thinking, is 4.37, the general average of six statements measuring the creativity dimension is 3.78, and the general average of nine statements measuring the vision dimension is 3.84. the results obtained indicate that the managers exhibit system thinking, creativity and vision behaviors, but they exhibit system thinking skills at a higher rate than others. this situation can be explained by the fact that there are many factors that managers should consider, especially in industries with high competition intensity. strategy was born out of the need to defeat the enemy. it is not possible to talk about the existence of a strategy without enemies. when considered in terms of business activities, the existence of a strategy requires the existence of a competitive environment (horwath, 2006: 3). according to ohmae, strategy is the most important element that differs from other business plans. the strategy is to gain competitive advantage. namely, no strategy will be needed in an environment where there is no opponent. for this reason, it will be possible to talk about the existence of the strategy if it provides a sustainable advantage against the rivals (ohmae, 1983: 36). according to chandler, strategy is the determination of the long-term main goals and objectives of an enterprise, allocating the necessary resources for these goals and objectives, and preparing appropriate action plans (chandler, 1990: 13). in the literature, it is seen that the unshakable integrity between strategy and competition encourages business managers to gain strategic thinking skills beyond classical strategic plans. table 3 findings regarding the strategic thinking and its factors with competitive intelligence, the competitive intelligence context and competitive intelligence process and in terms of industry variable. 1: one tail probability (right) 2: one-tail probability (left). factors industry n mean standard deviation t significance level system thinking automotive 318 3.99 0.56 2.01 0.0221 communication 310 3.86 0.71 creativity automotive 318 3.82 0.76 1.14 0.1271 communication 310 3.75 0.85 vision automotive 318 3.92 0.68 2.19 0.0151 communication 310 3.77 0.81 strategic thinking automotive 318 3.92 0.58 1.82 0.0351 communication 310 3.80 0.73 automotive 310 3.74 0.81 ci context communication 318 3.79 0.67 -2.23 0.0132 automotive 310 3.91 0.63 communication 310 3.96 0.68 ci process automotive 318 3.77 0.70 -2.07 0.0202 communication 310 3.88 0.64 competitive intelligence automotive 318 3.78 0.65 -2.37 0.0092 communication 310 3.90 0.60 when the literature is examined, it is seen that the automotive and communication industries are experiencing intense competition in the current century, and strategy and competition are the most fundamental dynamics of the industry. rubenstein (2001) drew attention to the speed and extent of the transformation in the automotive industry, stating that in 1900 there were 2000 motor vehicles and 20,000 registered horses in the usa, and by 2000 the number of motor vehicles became more than the people with motor vehicle licenses. shimokawa (2010), on the other hand, stated that the automobile industry in developed countries has at least ten percent of the gross national product, and therefore the automobile industry has reached the most important threshold in the history of the industry in the 21st century. developments in the history of the communication industry parallel those of the automotive industry. from an industry structure that was almost without competition with the monopoly and mandatory regulations of the states before 1980, the transition led to a new identity, where the intensity of competition reached a very high level over the last quarter century (trauth and pitt, 1992). factors such as globalization, mass production speed, increasing market share, innovations in information and communication technologies, changing game rules with new actors in industries, and speed of environmental change push companies to be more innovative and future-oriented, although there are many other components that they should consider. mintzberg et al. (2005) stated that the basic acceptance of strategy is that the actual situation experienced between the two actors in the market is called competition, and the ability to always remember that the competitors can do things better or differently, which is called strategic thinking skill. therefore, in parallel with these explanations, it has been determined that the managers of the automotive and communication industries express their system thinking, creativity and vision skills. the second question of the research is if business managers in competitive sectors attach importance to the competitive environment and competitor analysis. in order to answer this question, the averages and frequency distributions of the expressions in the competitive intelligence scale were examined. the general average of 28 expressions measuring competitive intelligence was 3.83. dimensions of competitive intelligence activities of managers were evaluated separately. the general average of 17 expressions measuring competitive intelligence context was 3.85 and the general average of 11 expressions measuring the competitive intelligence process was 3.83. accordingly, it can be said that the automotive and communication industry executives who constitute the research sample attach acceptable level of importance to competitive intelligence activities. competition is a phenomenon related to the past, present and future of the business. competition is the ability of a business to adapt its activities to the process of change occurring locally, nationally and globally in order to develop, grow, renew and even maintain its current status (kök and deliktaş, 2003: 17). in other words, competition is the ability of an enterprise to make more profit than other actors in the market or to realize all these in a sustainable order, beyond the longer survival. in this context, competitive intelligence predicts that businesses take three basic steps behaviorally: obtaining information about the competitor, interpreting and adapting (li, and calantone, 1998: 16). the information depicted here represents an indispensable resource and an economic value placed on the table of strategic decision makers in a processed form, beyond information obtained from any source. in other words, the information obtained through the activities of competitive intelligence guides the competitive position of the enterprise as well as the pioneer and guide of the innovation activities of the enterprise. it should be noted that the information age creates changes in the roles and responsibilities of managers. until a quarter century ago, perhaps the most fundamental problem of a manager was to make decisions under environmental uncertainty, while activities such as competitive intelligence make decision-making processes relatively easier. however, as an innovation created by the information age, managers who are in decision-making positions have to carefully create the information line that will affect their decisions (poali-scarbonch and guenec, 2011: 208). since the process that continues from the acquisition of data to its return to information is the precursor of the strategic decisions that will shape the future of the enterprises, it 66 obliges the information to be obtained in a systematic order and through a healthy filter. another common feature of the automotive and communication industries, along with their intense competition, is that the innovation and competition activities in the industries move from the top to the bottom on a vertical plane. in other words, the competitive moves of the administrative and sales units in both industries are limited. regional and provincial directorates, dealers and sales representatives cannot go beyond the competition policies determined by the senior management or the brand executive board. however, this does not mean that competition is lacking in practice. the determining factor for both industries is that price competition is determined within the strategic plan of the senior management. in competitive moves other than price competition, dealers have a limited range of action, though. the important factor for top management is that the flow of information moves from bottom to top. in other words, in both industries, the most basic information that will guide strategic decisions is created with the data obtained from customers. because in both industries, the substitution of the final product is available, albeit limited, so customer satisfaction must be provided at the highest level. additionally, in both industries, the customer is not only the purchaser of the product, but also the first feedback provider on the product. in this sense, the feedback to be obtained from the customers and the information to be obtained about the industry through the customers should be processed in a systematic order and reported to the senior management. all these requirements are possible with either a formal competition intelligence unit or a formal knowledge management system. according to the results of the analysis conducted on whether the industry variable has made any difference in terms of strategic thinking and competitive intelligence, the system thinking, vision and creativity scores of the participants working in the automotive industry are significantly higher than the scores of the participants working in the communication industry. the fact that competition in the automotive industry is widespread on a global scale and that there are many more components that managers must consider compared to the communication industry explains the results. in addition, it is observed that the scores of participants working in the communication industry on the competitive intelligence context of the competitive intelligence process have significantly higher scores than the participants working in the automotive industry. the communication industry is an industry with sharp and intense price competition compared to the automotive industry. again, compared to the automotive industry, although it is not easy to enter the industry, the services offered take a lower place in the customer budget, facilitating customer permeability in the market. in this sense, the high average of competitive intelligence and factors in the communication industry is due to the natural conditions of the industry and is in harmony with the real conditions of the industry. this study shows that strategic thinking affects competitive intelligence in competitive industries. business managers must realize that we are living in the information age. while knowledge is a bridge between land, labor force, capital and entrepreneurs, which are accepted as basic production factors in one aspect, it is now the fifth production factor in our age with another aspect. in this sense, although strategic planning maintains its importance, it no longer has an effect that will provide strategic superiority to businesses. the distinguishing feature that will make a good strategic plan better is not the power of the text but the mental power that makes the planning. for this reason, managers who have strategic thinking skills need information in order to interpret the dynamics of competition correctly, to predict their competitive positions and to determine their competitive positions correctly. knowledge is everywhere: countless and dynamic. for this reason, information that will reach business managers through only a filter will be useful. strategic thinking skill comes into play at this point. it is the business manager who has strategic thinking skills, who will determine which data to focus on and who will be involved in the process from among the infinite data whose location, time and form are unknown. this will be a tool that starts with the mental process and turns into a final output with the help of information management systems, which will provide a competitive advantage to the 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(2021) marketplace analysis of purchase decision factors for instagram social media users. journal of intelligence studies in business. 11 (3) 42-56. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 3 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index marketplace analysis of purchase decision factors for instagram social media users faris muhammada,* and sri hartonoa amagister management program, faculty of economic and business, mercubuana university, umb jakarta, indonesia; *farisperpus@gmail.com journal of intelligence studies in business please scroll down for article marketplace analysis of purchase decision factors for instagram social media users faris muhammada,* and sri hartonoa amagister management program, faculty of economic and business, mercubuana university, umb jakarta, indonesia *corresponding author: farisperpus@gmail.com received 31 august 2021 accepted 25 december 2021 abstract currently, the role of technology, such as the internet, is very important to support human activities. one of the uses of the internet is as a medium to support online shopping. in addition, the existence of instagram social media also affects consumers’ decisions in online shopping. this study analyzes the purchasing decision factors of instagram social media users on the marketplace. the variables used in this study are price, promotion, trust, security, instagram social media users and purchase decision. the research framework was developed using the theory of reasoned action. the sample in this study is consumers who have done online shopping. a total of 200 questionnaires were distributed via a google form, of which 102 were returned. the data analysis method in this study used smart pls 3.0. the results showed that all variables had a positive and significant relationship with online purchasing decisions. this research provides theoretical and practical implications. this study is useful for instagram social media users to consider the factors that purchasing decisions in online shopping have on the marketplace. keywords instagram users, online shopping, price, promotion, purchase decision, security, trust 1. introduction from mid-february 2020 until now (2021), indonesia was impacted by the covid-19 virus pandemic, and because of this people have choosen to carry out more shopping online. the choice people have made to shop online is due to the activity policies set by the government (prabawanti., 2020). during this pandemic, online shopping methods through social media have increased. in june 2020, facebook researched the increasing trend of online shopping methods during the pandemic and found that shopping through social media increased by up to 37% compared to before the pandemic (facebook, 2020). this indicates that people are more interested in shopping online during the pandemic for reasons of mental health and safety. based on data from the ministry of home affairs, by early 2020, indonesia's population was around 268.5 million, with internet users reaching 175.4 million and smartphone users amounting to 338.2 million people (twice that of internet users). in addition to the internet, several types of social media are often used. by january 2020, there were 160 million social media users in indonesia (wearesocial, 2020). the most popular social media are facebook, whatsapp, youtube, twitter and instagram, and many more. based on data from wearesocial in 2020, the most popular social media used is youtube at 88% of internet users in indonesia, followed in popularity by whatsapp, facebook and instagram (wearesocial, 2020). some of these social media have benefits for their users, such as providing entertaining, providing or sharing journal of intelligence studies in business vol. 11, no. 3 (2021) pp. 42-56 open access: freely available at: https://ojs.hh.se/ 43 information, communicating, or use in business matters. one of the most popular social media platforms today is instagram. the number of instagram users in indonesia in january 2020 was 63 million people with 50.8% female and 49.2% male (wearesocial, 2020). the role of instagram in the decision-making process in online shopping is as an intermediary or "bridge" before consumers make purchase transactions in the marketplace. the large number of instagram users provides an opportunity for rapid economic growth in the digital sector. some of the reasons people, especially women, do online shopping through instagram, is because they follow the trends displayed in their instagram feed and stories columns. consumers are also influenced by prices of products that are offered even though they don't need them (fauziah, 2018). in addition, several factors determine the goods consumers will buy in online the shopping marketplace. a survey conducted by idn times in the 2019 indonesia millennial report found that 60% of consumers chose price as the main factor in considering the products they would buy online, followed by features and promotional programs ranked second and third, respectively (idn research institute.,2019). in 2013, the international journal of engineering research and development released the results of research on the main factors influencing people who shop online. they found that trust is the strongest factor that influences online shopping decisions. trust is an important factor that can influence consumers to buy products online (mohmed, 2013). this research is reinforced by nawangsari (2018) who finds that trust has a simultaneous effect on purchasing decisions. regarding the influence of instagram social media on purchasing decisions, fredik (2018) found that instagram has a 33.2% positive influence on the promotion of product purchase decisions. regarding the factors that influence peoples’ decisions to shop online, the authors also found several results from previous research related to the analysis of peoples’ decisions to shop online. the research proposed by njoto (2018) found that promotions, namely advertising, sales promotion, and personal selling, have a significant effect on consumer purchasing decisions in the marketplace. meanwhile, research from lin pan (2019) found that safety is the main factor in determining consumer purchasing decisions. from several existing studies, it was found that there were no consistent results from the research, so this study intends to fill in the existing deficiencies. this research consists of several parts, starting from the background of the study, literature review, research methods, discussion of results, and conclusions. 2. literature review 2.1 industrial history in america, online marketplaces became popular in 1995 with the start of ebay and amazon. in china, the online marketplace started to get crowded after jack ma founded alibaba, which is now a giant marketplace. while in indonesia, the beginning of online stores began in 1999 with the establishment of the kaskus buying and selling forum. however, in the early days of online buying and selling forums, most people only used the platform to show their products. meanwhile, the transaction process was still done offline. a few years later, tokobagus.com became olx (circle, 2020). currently, there are many marketplaces with the strengths of their respective industries and the choice of payment methods is also increasingly diverse. the transaction process that was previously limited to debit and credit can now be done via a smartphone. some marketplaces even provide electronic wallets. this makes more and more consumers prefer to shop at online marketplaces because of the convenience they offers. this growth is said to be able to make e-commerce a major driver of the digital economy. it is predicted that the e-commerce market will account for usd 100 billion by 2025 (tokopedia, 2019). the marketplace is a new business model that is developing along with the rapid development of information technology infrastructure. the marketplace is designed to minimize complex business processes to create efficiency and effectiveness. with a marketplace, everyone can carry out buying and selling activities easily, quickly, and cheaply because there are no limits on space, distance, or time. conventionally, the market has several roles including facilitating transactions and providing infrastructure. indicators of marketplace activity are determined by the marketplace's ability to facilitate transactions, bring together sellers and buyers, and provide infrastructure. the efficiency indicator is related to the conciseness of time and costs 44 provided by the marketplace (l. alrubaiee, 2012). according to mulyaningsih (2015), there are several differences between a marketplace and e-commerce. in terms of product provision, the marketplace has many vendors/brands, while e-commerce comes from only one brand. then in terms of the business model, the marketplace can use the b2b (business to business and b2c (business to customer) business model, while e-commerce only uses the b2c (business to customer) business model, registration of premium brands, and advertisements. therefore, e-commerce income is derived exclusively from buying and selling transactions with customers. in terms of payment, for a marketplace it depends on the brand's policy on the marketplace as a third party, while ecommerce payments are directly from customers. regarding the process of shipping goods, for marketplaces, they are sent from the vendor/brand of the product provider, while ecommerce is sent from the same place and with the same method. 2.2 theoretical foundation the basic framework of thought in this study uses the theory of reasoned action (tra). this theory was developed in 1967. the theory was then continuously revised and expanded by icek ajzen and martin fishbein. starting in 1980 the theory was used to study human behavior (trafimow, 2009). the tra was formulated in 1967 in an attempt to provide consistency in the study of the relationship between behavior and attitudes. reasoned action theory was developed to examine the relationship between attitudes and behavior (trafimow, 2009). this theory explains that a person's behavior is influenced by intentions, while intentions are influenced by subjective attitudes and norms. attitudes are influenced by beliefs about the results of past actions. subjective norms are influenced by belief in the opinions of others and the motivation to obey these rules. simply put, this theory says that a person will do an action if she or he views the action positively and believes that other people want them to do it (kayati, 2018). some of the variables used in this study include price (x1) promotion (x2), trust (x3), security (x4), instagram users (y), and purchase decision (z). so for the framework of thought can be arranged as in figure 1. 2.3 hypothesis development based on several previous studies and referring to research variables, the following hypotheses can be developed: 2.3.1 influence of price on purchasing decisions of instagram social media users an important concept for marketers is price. pricing is a mechanism for obtaining value for the company. for consumers, price is the amount needed to get a product (gecit, 2017). price is an important factor in purchasing decisions, especially for frequently purchased products, and therefore influences the choice of figure 1 research framework. 45 stores, products and brands to consider (albari, 2018). fair pricing refers to price adjustments that offer the right combination of quality and service at a reasonable price (kotler and keller, 2016). many think that selling online is easier and more practical and economical because we don't need a store or a lot of human resources to do a business. it is enough with gadgets, credit for the internet and individual creativity to attract buyers. however, it turns out that running an online business is not as easy as many people imagine or predict. in reality doing business online turns out to have many obstacles related to competitors (because many people also do business online) and precisely because it is online, people find it easier to compare prices with one another (gain., 2017). prices are set by the seller under the quality and service provided. price is also the most visible element of the marketing mix, and pricing policies are often questioned by consumers. if consumers think that prices are unfair, they can leave the company or spread negative information to other consumers. price has a major influence on purchasing decisions that occur between sellers and buyers. alsalamin's research (2016) shows that most respondents consider price as an important factor that influences their purchasing decisions. this research is similar to that conducted by muliajaya (2019) which shows that there is a partially significant effect of price on the price of purchasing decisions. the same research was conducted by chadafi (2016) which showed that price had a positive effect on purchasing decisions. based on the discussion above, our first hypothesis is: h1: price has a positive effect on purchasing decisions of instagram social media users 2.3.2 influence of promotion on purchasing decisions of instagram social media users the role of promotion for the development of new products in the company is one of the most vital factors for the success of marketing a goods and services product (brata., 2017). promotion is part of a marketing strategy, where the promotion has a function to provide information, persuade, and remind consumers both directly and indirectly about a product being sold (kotler and keller, 2012). research conducted by panjaitan (2019) shows that promotion has a significant effect on consumer purchasing decisions for bright gas products. the results of this study are similar to those conducted by fredik (2018), njoto (2018), and lininati (2018), showing that promotion has a positive effect on purchasing decisions. based on the discussion above, our second hypothesis is: h2: promotion has a positive effect on purchasing decisions of instagram users 2.3.3 influence of security on purchasing decisions of instagram social media users security can control and maintain data provided by a consumer (kim and park, 2013). furthermore, security includes an online store's ability to control and maintain security over data transactions (raman and viswanatahan, 2011). based on several studies, anandita (2015) shows that there is a significant influence of security guarantees on purchasing decisions through social networking sites for students in surakarta. a similar study by fadhila (2017) shows that security has a significant positive effect on customer purchasing decisions in indonesia. khanna (2019) shows that in general six factors influence online purchasing decisions: convenience, security and privacy, productrelated factors, service-related factors, websiterelated factors, and personal factors. based on the discussion above, our third hypothesis is: h3: security has a positive effect on purchasing decisions of instagram social media users 2.3.4 influence of instagram social media users on purchasing decisions social media is an online media, where users can easily participate, share, and create content including blogs, social networks, wikis, forums and virtual worlds (kurniawan, 2017). social media can also be interpreted as a medium on the internet that allows users to represent themselves and interact, collaborate, share, and communicate with other users and form virtual social bonds. the number of instagram users in indonesia in january 2020 was 63 million people with 50.8% female instagram users and 49.2% male instagram users (wearesocial, 2020). one of the reasons people, especially women, shop through instagram, is because they follow trends that are displayed in the instagram feed and stories column (fauziah, 2018). research on the use of instagram social media has been conducted by 46 lininati (2018) and shows that there is a positive and significant relationship between instagram social media users and purchasing decisions at the food court. furthermore, similar research conducted by puspitarini (2019) showed that instagram social media users had a positive effect on purchasing decisions. based on the discussion above, our fourth hypothesis is: h4: instagram social media users have a positive effect on purchasing decisions 3. method 3.1 research design and operational variables the type of research used here is descriptive research. according to sekaran (2017:111), descriptive studies aim to help researchers to understand the characteristics of groups in certain situations (for example, explanations of certain market segments), think systematically about aspects in certain situations (for example, factors related to purchasing decisions), provide ideas for further investigation or research, and help make informed decisions. in this study the the dependent variable used is the purchase decision, the independent variables are promotion, price, trust and security and the intervening variable is social media instagram. the operationalization of variables in this study explains how to measure variables so that they can be operated, by explaining the dimensions, indicators, or variable measurement items in a table (mercubuana 2020:20). 3.2 data collection, sampling, and analysis techniques data was collected through a google form questionnaire with the conversion of statements into scores based on the likert scale as listed in table 1. based on the table, the scale used in the questionnaire ,is 1-5 which represents the answers of each respondent. this was tested for its effect on purchase decision. the population is a generalization area consisting of objects/subjects that have certain qualities and characteristics determined by researchers to be studied and then drawn conclusions (sugiyono 2018:80). the population in this study are all consumers who have shopped online at the marketplace via instagram at least once. for the sample itself, 200 questionnaires were distributed via a google form, of which 102 were returned. the sampling method is the non-probability sampling method with purposive sampling technique, namely the technique of determining the sample with certain considerations and criteria (sugiyono 2018:85). the data analysis uses smartpls 3.0 to test the outer model and the inner model, which tests the validity, reliability, r square, q square, gof, and hypothesis testing. table 1 likert scale. answer options score strongly disagree 1 disagree 2 neutral 3 agree 4 strongly agree 5 3.3 description of respondents and variabel the majority of respondents were women (62 people, 60.8%). this means that consumers who are active users of instagram social media are dominated by women. the majority of respondents were 30-34 years old (69 people, 67.6%). this means that the marketplace consumers who shop through instagram are primarily millennials. in terms of education, most respondents had undergraduate (s1) backgrounds (83 people, 81.4%). this is because it is related to the millennial age who already understand the operation of internet technology. most respondents had an income between 4,000,000 and 4,900,000 indonesian rupiah (65 people, 63.7%). the respondents were primarily employed as private employees (84 people, 82.4%). respondents in this study have a frequency of opening or using instagram social media every day (98 people, 96.1%). 3.4 variable description the research aims to examine the factors that influence the purchasing decisions of instagram social media users on the marketplace, with instagram as the mediating/intervening variable. after the distribution of 102 respondents, the following are the results of descriptive statistics from the research variables. 47 3.4.1 price variable distribution results the results of the distribution price variable show that the statement "before buying, i compare product prices on the marketplace with product prices on instagram" has the highest average value ( 4.520), which means that the average consumer considers product price information on instagram before deciding to buy. 3.4.2 promotion variable distribution results the results of the distribution promotion variable show that the statement "i know that the marketplace often holds promotions on instagram" has the highest average value of (4.578). this shows that average consumer knows about the promotion of the marketplace on instagram. 3.4.3 trust variable distribution results the results of the distribution of the trust variable show that the statement "i feel that product information from instagram provides the information needed by its users" has the highest average value of 4.480. this shows that the average consumer believes that instagram displays marketplace products needed by its users. 3.4.4 security variable distribution results the results of the distribution of the security variable show that the statement "in my opinion, the product information displayed on instagram is correct." has the highest average value, 4.520. this shows that the average consumer feels safe with the official marketplace product information displayed on instagram. this is reinforced by the official link included by marketplace on instagram. 3.4.5 instagram variable distribution results the results of the distribution of the instagram user variable show that the statement "i am considering buying a product based on comments/reviews from instagram users." has the highest average value of 4.637. this shows that the average consumer decides to buy products on the marketplace after they see comments/reviews on instagram. 3.4.6 distribution results of purchase decision variables the results of the distribution of the purchasing decision variables show that the statement "i will recommend others to look for product information on instagram before buying on the marketplace" has the highest average value of 4.520, which shows that the average consumer will recommend others to seek product information on instagram before deciding to buy products on marketplace. 4. data analysis smartpls 3.0 4.1 evaluation of the measurement model (outer model) the evaluation of the outer model is done by testing the validity and reliability of the measurements of the research model design. figure 2 analysis of the outer model source: pls 3.0 processing results. 48 4.1.1 validity test the validity test on the indicator is a benchmark that describes the relationship between the reflective indicator score and its latent variable. the validity test consists of convergent validity and discriminant validity. convergent validity: convergent validity is the correlation between the indicator score and its construct score and can be declared valid if the outer loading value > 0.7 and the ave value > 0.5 (ghozali & latan, 2015). figure 2 shows the results of the data processing algorithm with pls. all indicators have values or correlations between constructs and variables that meet convergent validity because the outer loading value is > 0.70. this means that the results obtained meet the validity criteria. after the outer loading value, we can see the convergent validity test from the ave value (ghozali & latan, 2015), which is > 0.5. from the data all variables have a value > 0.5 so it can be concluded that all indicators are valid and suitable for use in this study. discriminant validity: in the discriminant validity test, the values in the fornell-laker criterion and cross-loading tables are used. the fornell-lacker criterion value shows the correlation value between the variables themselves and other variables. the value of cross-loading shows an indicator, which is said to meet discriminant validity if the correlation value between indicators on the variable is greater than that of other variables (ghozali & latan, 2015). fornell-lacker criterion and cross-loading values can be seen in table 2. according to the data, we can see that all the correlation values of a variable are greater than the correlation values of these variables to other variables so that all variables can be declared valid. table 2 fornell-lacker criterion scores. source: pls 3.0 processing results. price instagram user’s purchase decision promotion security trust price 0.864 instagram users 0.676 0.762 purchase decision 0.616 0.709 0.854 promotion 0.581 0.673 0.522 0.806 security 0.500 0.645 0.606 0.580 0.889 trust 0.638 0.700 0.672 0.540 0.549 0.831 table 3 cross loading value. source: pls 3. processing results. price instagram user’s purchase decision promotion security trust h1 0.881 0.638 0.559 0.538 0.504 0.604 h2 0.891 0.589 0.580 0.510 0.476 0.589 h3 0.817 0.515 0.448 0.452 0.294 0.446 i1 0.428 0.756 0.494 0.527 0.483 0.472 i2 0.626 0.754 0.599 0.536 0.475 0.583 i3 0.510 0.789 0.548 0.443 0.462 0.509 i4 0.478 0.747 0.509 0.541 0.544 0.559 k1 0.495 0.656 0.886 0.494 0.617 0.565 k2 0.554 0.607 0.876 0.440 0.518 0.634 k3 0.538 0.547 0.798 0.400 0.402 0.523 p1 0.462 0.514 0.415 0.773 0.494 0.358 p2 0.422 0.556 0.434 0.804 0.482 0.418 p3 0.521 0.557 0.415 0.840 0.428 0.524 s1 0.447 0.563 0.559 0.423 0.885 0.492 s2 0.442 0.584 0.519 0.605 0.893 0.485 t1 0.488 0.543 0.495 0.455 0.451 0.831 t2 0.568 0.629 0.644 0.442 0.501 0.856 t3 0.529 0.568 0.525 0.450 0.413 0.804 49 table 4 value of composite reliability and cronbach's alpha. cronbach's alpha rho_a composite reliability average variance extracted (ave) price 0.830 0.840 0.898 0.746 instagram user’s 0.759 0.760 0.847 0.580 purchase decision 0.814 0.823 0.890 0.730 promotion 0.730 0.732 0.848 0.650 security 0.735 0.736 0.883 0.791 trust 0.775 0.780 0.870 0.690 according to the data in table 3, we can find out if all the correlation values between indicators on the variables are higher than other variables. therefore, it can be said that each variable has good discriminant validity. 4.1.1 reliability test a reliability test is a method of testing the reliability value of indicators on a variable seen from two values, namely composite reliability and cronbach's alpha. a variable is declared reliable if it has a composite reliability value and cronbach's alpha > 0.7 (ghozali & latan, 2015). table 4 shows the value of composite reliability and cronbach's alpha for each variable. according to the data in table 4, we can find out if the composite reliability and cronbach's alpha values for all variables > 0.7 have met the requirements and it can be said that the measurements in the study are reliable. 4.2 evaluation of the structural model (inner model) 4.2.1 r-squared (r2) value the value of r-squared (r2) on the structural model is a measure of how much influence certain independent latent variables have on the dependent latent variable. based on table 5, the r-squared value of the instagram variable is 0.675. it can be concluded that the effect of price, promotion, trust and security variables on instagram is 67.5%. the rsquared value of the purchase decision variable is 0.502, so it can be concluded that the influence of the instagram variable on the purchase decision is 50.2%. 4.2.2 value of q2 predictive relevance in addition to looking at the magnitude of rsquare, the evaluation of the pls model can also be done by looking at q2 to represent the synthesis of cross-validation and fitting functions with predictions from observed variables and estimates of construct parameters. q2 measures how well the observed values generated by the model and also the parameter estimates. the value of q2 > 0 indicates that the model has predictive relevance, while q2 < 0 indicates that the model lacks predictive relevance (ghozali and latan, 2015). based on table 6, it can be seen that the q2 predictive relevance for instagram's endogenous latent variable is 0.355 and purchase decision is 0.357. the value of q2 predictive relevance of the endogenous latent variable is > 0, so it can be concluded that the model already has predictive relevance. table 5 value of r-squared (r2). source: the result of processing smart pls 3.0 r square r square adjusted instagram users 0.675 0.662 purchase decision 0.502 0.497 4.2.3 quality index pls path modeling can identify global optimization criteria to determine the goodness of fit with the gof index. the gof index developed by tenenhaus et al. (2004) is used to evaluate measurement models and structural 50 models. in addition, the gof index also provides a simple measurement for the overall prediction of the model. the criteria for gof values are 0.10 (gof small), 0.25 (gof medium), 0.36 (gof large) (ghozali and latan, 2015). 𝐺𝑜𝐹 = %𝐶𝑜𝑚𝑚𝑢𝑛𝑎𝑙𝚤𝑡𝑦/////////////////// × 𝑅!//// = √0.367 × 0.589 𝐺𝑜𝐹 = 0,465 the gof value is 0.465, which means it can be concluded that the research model is good and also includes a large gof. table 6 value of q-squared (q2). source: processing results smart pls 3.0. 4.2.4 hypothesis test hypothesis testing in this study aims to determine the significance of the effect of exogenous variables on endogenous variables. the test is carried out using a bootstrapping process on smartpls 3.0. the basis for decision-making the influence between variables is considered significant at the level of 5% if the statistical t value compared to the t table value is 1.96. the test results with bootstrapping from the pls analysis are: test hypothesis 1 (influence of price on instagram users) based on the test results in table 4, we can see that the correlation of the price variable with instagram has a path coefficient value of 0.231 and a t value of 2.633. this value indicates that the value of the t statistic is greater than t table (> 1.96). this means that the price variable has a significant effect on instagram with the first hypothesis, namely price has a positive and significant effect on instagram. then hypothesis 1 is accepted. test hypothesis 2 (effect of promotion on instagram users) based on the test results in table 4, we can see that the correlation of the promotion variable with instagram has a path coefficient value of 0.251 and a t value of 2.580. this value indicates that the value of the t statistic is greater than t table (> 1.96). this means that the promotion variable has a significant effect on instagram with the third hypothesis that promotion has a positive and significant effect on instagram. then hypothesis 2 is accepted. test hypothesis 3 (effect of trust on instagram users) based on the test results in table 4, we can see that the correlation of the trust variable with instagram has a path coefficient value of 0.296 and a t value of 3.330. this value indicates that the value of the t statistic is greater than t table (> 1.96). this means that the trust variable has a significant influence on instagram with the fifth hypothesis, namely trust has a positive and significant effect on instagram. then hypothesis 3 is accepted. test hypothesis 4 (effect of security on instagram users) based on the test results in table 4, we can see that the correlation between the security variable and instagram has a path coefficient value of 0.222 and a t value of 2.675. this value indicates that the value of the t statistic is greater than t table (> 1.96). this means that the security variable has a significant effect on instagram with the fourth hypothesis, namely security has a positive and significant effect on instagram. then hypothesis 4 is accepted. test hypothesis 5 (influence of instagram users on purchase decision) based on the test results in table 4, we can see that the correlation of the instagram variable with purchase decision has a path coefficient value of 0.709 and a t value of 10.321. this value indicates that the value of the t statistic is greater than t table (> 1.96). this means that the instagram variable has a significant effect on purchase decisions with the second hypothesis, namely, instagram has a positive and significant effect on purchase decisions. then hypothesis 5 is accepted. sso sse q² (=1-sse/sso) price 306.000 306.000 instagram users 408.000 263.245 0.355 purchase decision 306.000 196.744 0.357 promotion 306.000 306.000 security 204.000 204.000 trust 306.000 306.000 51 4.3 indirect effect based on the results of the bootstrapping calculation in the specific indirect effects research above, the following can be generated: • price has a positive and significant effect on purchase decisions through instagram because the t statistic’s value is 2.750 which is greater than t table = 1.96 and also the p value is 0.006 which is smaller than 0.05. • promotion has a positive and significant effect on purchase decisions through instagram because the t statistic’s value is 2.536 which is greater than t table = 1.96 and also the p value is 0.012 which is smaller than 0.05. • security has a positive and significant effect on purchase decisions through instagram because the t statistic’s value is 2.486 which is greater than t table = 1.96 and also the p value is 0.013 which is smaller than 0.05. • trust has a positive and significant effect on purchase decisions through instagram because the t statistic’s value is 3.027 which is greater than t table = 1.96 and also the p value is 0.003 which is smaller than 0.05. 5. discussion based on the results of the above data processing against the proposed hypothesis, it can be seen that all the hypotheses that have been set by the researchers are accepted. the following is an analysis related to the influence between variables according to the proposed hypothesis: 5.1 the influence of price on purchase decisions through instagram users after testing the hypothesis, it is known that price has a positive and significant effect on purchasing decisions through instagram because the t statistic’s value is 2.750 which is greater than t table = 1.96 and also the p value is 0.006 which is smaller than 0.05. this is relevant to the results of the idn times survey in the 2019 indonesia millennial report which stated that 60% of consumers chose price as the main factor in considering the products they would buy online. 5.2 the influence of promotions on purchase decisions through instagram users after testing the hypothesis, it is known that promotion has a positive and significant effect on purchase decisions through instagram because the t statistic value is 2.536 which is greater than t table = 1.96 and also the p-value is 0.012 which is smaller than 0.05. this is relevant to research by njoto (2018: 612-618), which found that promotions, namely advertising, sales promotion, and personal selling have a significant effect on consumer purchasing decisions. 5.3 the influence of between security on purchase decisions through instagram users after testing the hypothesis, it is known that security has a positive and significant effect on purchase decisions through instagram because the t statistic’s value is 2.486 which is greater than t table = 1.96 and also the p value is 0.013 which is smaller than 0.05. this is relevant to research by anandita (2015, 203-210), fadhila (2017, 60-64) and khanna (2019, 1-9) which show that security has a positive effect on purchasing decisions of instagram social media users. 5.4 the influence of trust on purchase decisions through instagram users after testing the hypothesis, it is known that trust has a positive and significant effect on purchase decisions through instagram because the t statistic’s value is 3.027 which is greater than t table = 1.96 and also the p value is 0.003 which is smaller than 0.05. this is relevant to chadafi (2016, 1-8), zatalini (2017, 145-146) and nawangsari (2018, 61-67) showing that trust has a positive effect on purchasing decisions. 5.5 the influence of instagram social media on purchase decisions users after testing the hypothesis, it is known that the correlation of the instagram variable with purchase decision has a path coefficient value of 0.709 and a t value of 10.321. this value indicates that the value of t statistic is greater than t table (> 1.96). this means that the instagram variable has a significant effect on purchase decisions, which means that instagram has a positive and significant effect 52 on purchase decisions. this is relevant to the research of lininati (2018, 97-102), miranda (2017, 1-15) and puspitarini (2019, 71-80) which show that instagram social media has a positive effect on purchasing decisions. 6. conclusion and suggestions 6.1 conclusion the research aims to analyze the purchasing decision factors of instagram social media users in the marketplace. the analysis test uses smart pls 3.0 to analyze the correlation between these variables. by the analysis of the results and discussion in the previous chapter, the following conclusions can be drawn: • based on the results of the first analysis, price has a positive and significant effect on instagram. this means that price is the main factor in considering buying products on the marketplace through instagram. • based on the results of the second analysis, promotion has a positive and significant effect on instagram. this means that the promotion of products on the marketplace is consistent and routine on instagram, making instagram users consider buying products on the marketplace through instagram. • based on the results of the third analysis, it shows that the security variable has a positive and significant effect on instagram. this means that security by providing valid information is one of the things that consumers consider when buying products on the marketplace through instagram. • based on the results of the fourth analysis, it shows that the trust variable has a positive and significant effect on instagram. this means that the trust / confidence of a consumer in considering buying a product in the marketplace is very high. • based on the results of the fifth hypothesis test, it shows that the instagram variable has a positive and significant effect on purchasing decisions. this is supported by the variety of features provided by instagram to make it easier for consumers to find and compare the products they want to buy. • the results of the tests carried out state that the promotion, price, trust, security and instagram variables have a positive and significant effect on purchase decisions on the marketplace. 6.2 suggestions based on the results of the study and also the conclusions, the following are suggestions that researchers can give to managerial and further researchers. advice for academics: from the results of the r-square test, it can be seen that the effect of price, promotion, trust and security variables on instagram is 67.5%. while the influence of the instagram variable on the purchase decision is 50.2%. it can be expected that future research can expand the model by examining other aspects that also influence purchasing decisions using instagram on the marketplace. further research is also expected to re-examine purchasing decisions in the field of marketplace and social media with a larger number of samples, and with various other social media. suggestions for instagram users / consumers: as consideration and input for instagram social media users in buying products on the marketplace through information from instagram, this can be used as material to compare products through social media before deciding to buy on the marketplace. 7. references adani, m, r. 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(2019). imr 2019: begini kebiasaan millennial saat belanja online. diunduh dari : https://www.idntimes.com/tech/trend/bayu/su rvei-ims-2019-kebiasaan-millennial-saatbelanja-online-ims2019/3. pada 20 februari 2020. 56 wong, d. (2017). pengaruh ability, benevolence dan integrity terhadap trust, serta implikasinya terhadap partisipasi pelanggan e-commerce : studi kasus pada pelanggan ecommerce di ubm. jurnal riset manajemen dan bisnis (jrmb) fakultas ekonomi uniat vol.2, no.2, 155-168. doi: https://doi.org/10.36226/jrmb.v2i2.46 yustiani, r. & yunanto, r. (2017). peran marketplace sebagai alternatif bisnis di era teknologi informasi. jurnal ilmiah komputer dan informatika (komputa) 6.2, 45 zabar, a, a, & novianto, f. (2015). keamanan http dan https berbasis web menggunakan sistem operasi kali linux. jurnal ilmiah komputer dan informatika (komputa), 69. zatalini, n, s, & mudiantono. (2017). analisis faktor-faktor yang berpengaruh terhadap kepercayaan, minat beli dan keamanan bertransaksi untuk meningkatkan keputusan pembelian konsumen pada ecommerce lazada.co.id di semarang. diponegoro journal of management, volume 6, nomor 2, 1-12. zulfa, l & hidayati, r. (2018). analisis pengaruh persepsi risiko, kualitas situs web, dan kepercayaan konsumen terhadap keputusan pembelian konsumen e-commerce shopee di kota semarang. diponegoro journal of management, volume 7, nomor 3, 1-11. issn: 2001-015x v o l 1 , n o 1 ( 2 0 1 1 ) bernard dousset, anass elhaddadi and josiane mothe “content accessibility and semantic networks processed on foreign natural language analysis”, pp. 5-18 dominik ditter, klaus henselmann and elisabeth scherr “using xbrl technology to extract competitive information from financial statements”, pp. 19-28 marisela rodríguez salvador and manuel alejandro bautista reyes “methodology of integration for competitive technical intelligence with blue ocean strategy: application to an exotic fruit”, pp. 29-39 sahbi sidhom and philippe lambert “information design for “weak signal” detection and processing in economic intelligence: a case study on health resources”, pp. 40-48 michael steiner and michael ploder “knowledge and social networks: new dimensions of economic interaction between firms”, pp. 49-60 xinzhou xie and xuehui jin “the evolution of competitive intelligence in china”, pp. 61-75 luc grivel and olivier bousquet “discourse analysis methodology based on semantic principles application to brands, journalists and consumers discourses”, pp. 76-86 anass el haddadi, bernard dousset and ilham berrada “establishment and application of competitive intelligence system in mobile devices”, pp. 87-96 mourad oubrich “competitive intelligence and knowledge creation outward insights from an empirical survey”, pp. 97-106 szymon adamala and linus cidrin “key success factors in business intelligence”, pp. 107-127 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2011 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : arik johnson, chairman aurora wdc, united states raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden dr. sofiane saadi, directeur général du laboratoire en organisation et gestion des entreprises (loge) algeria. managing director nt2s consulting inc. north vancouver, bc, canada javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/22') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/23') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/24') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/9') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/10') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/12') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, december 30 2011 e d i t o r i a l n o t e v o l 1 , n o 1 ( 2 0 1 1 ) it is with great pleasure that we publish the first ten articles of jisib. the articles represent a broad collection of topics from within the discipline of intelligence studies. there is, we think, a balance in this issue between more managerial and more technical aspects of intelligence studies. in today’s world, intelligence problems are more often solved with the help of software and technical tools. it is no longer the case in organizations that managers work only with managerial aspects and technicians with technical aspects. instead it has become a requirement that each group know a bit of both. managers need to know how to operate software and new technical equipment and technicians need to know about the needs of end-users to be of value. this does not mean that professional specialties are about to disappear. it is more a sign that information technology is getting a tighter grip around the way we build successful organizations. any study of intelligence with the aim to be relevant needs to reflect this duality. it is also a pleasure to see that we have got authors from so many countries interested in the journal and from such different academic backgrounds, all interested in the same field and the same kinds of problems. when setting up the editorial board it was a goal, if not the primary, to include academics from different cultures representing both sexes. that the articles in this issue are written by authors from so many cultural backgrounds was not our intention, but more of a coincidence and reflects, we believe, the international interest in the journal. the final aim of the journal is to be of use to practitioners. we are not interested in theory for the sake of theory, and we do not want to publish solutions to small problems which will have no real impact in the intelligence field. with your help we will instead continue to publish scientific articles that are relevant for practitioners and academics alike. we specially want to thank the authors for this issue. we also want to thank all those who have been involved in the process towards creating the journal, and who have not been mentioned on the website, all those who have participated in discussions during conferences and in social networks. these are too many to list by name, but we want to thank in particular sheila wright, sven hamrefors and craig s. fleisher, who have all followed this project from the start. everyone who works for this journal do this on their own free time and are not remunerated. however, we do have other costs related to the journal. your donation is therefore highly appreciated. to learn how, look at the right hand column on the journal website. on behalf of the editorial board, sincerely yours dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 o p i n i o n s e c t i o n 54 big data, tacit knowledge and organizational competitiveness nowshade kabir and elias carayannis grenoble graduate school of business, france email: nowshade@gmail.com george washington university school of business, usa email: caraye@gwu.edu received october 10, accepted 19 december 2013 abstract: in the process of conducting everyday business, organizations generate and gather a large number of information about their customers, suppliers, competitors, processes, operations, routines and procedures. they also capture communication data from mobile devices, instruments, tools, machines and transmissions. much of this data possesses an enormous amount of valuable knowledge, exploitation of which could yield economic benefit. many organizations are taking advantage of business analytics and intelligence solutions to help them find new insights in their business processes and performance. for companies, however, it is still a nascent area, and many of them understand that there are more knowledge and insights that can be extracted from available big data using creativity, recombination and innovative methods, apply it to new knowledge creation and produce substantial value. this has created a need for finding a suitable approach in the firm’s big data related strategy. in this paper, the authors concur that big data is indeed a source of firm’s competitive advantage and consider that it is essential to have the right combination of people, tool and data along with management support and data‐oriented culture to gain competitiveness from big data. however, the authors also argue that organizations should consider the knowledge hidden in the big data as tacit knowledge and they should take advantage of the cumulative experience garnered by the companies and studies done so far by the scholars in this sphere from knowledge management perspective. based on this idea, a big data oriented framework of organizational knowledge‐based strategy is proposed here. keywords: big data, tacit knowledge, big data strategy, knowledge management, knowledge strategies and organizational knowledge available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2013) 54-62 mailto:nowshade@gmail.com mailto:caraye@gwu.edu https://ojs.hh.se/ o p i n i o n s e c t i o n 55 introduction one of the key driving forces of knowledge economy is knowledge intensity of economic activities (smith, 2002). in recent decades increasing dependence of economy on knowledge has bolstered by rapid pace of technological innovation and information technology revolution. this, in turn, propelled the emergence of new knowledge‐based industries and augmented share of knowledge as a resource in economic input in most traditional industries. knowledge, now, is recognized as a pillar of innovation, a source of economic growth and a central element in organization's competitive advantage (stehr, 1994). this heightened importance of knowledge, in part thanks to globalization and speedy technological advancement, obliges organizations to pay serious attention to their existing, potential and growing knowledge resources. present phenomenal growth of knowledge resource can be attributed to several factors such as continuous advances in information technology related hardware, development of new algorithms and programs, ubiquitous access to information thanks to the internet and steady decline of cost related to data creation, transmission and storage. in recent years, the combination of these factors has also prompted the appearance of a new knowledge resource, which is capable of further revolutionizing organizational knowledge landscape. this new knowledge resource is big data! big data is a unique knowledge resource that is immensely valuable to any organization. it helps transforming many of the traditional methods of conducting business activities. insights and knowledge from big data boost management’s ability to take well‐informed decisions (provost and fawcett, 2013). efficient use of data created and located within a firm and collection and analysis of critical data from external sources impact a firm's product, process and strategic innovation as well as marketing and operational capabilities. current development shows that big data has already become a major catalyst in bringing sweeping changes to a range of business processes in many industries. as a result of this, organizations’ interest in big data initiatives has intensified significantly. a study done by tata consulting (2013) shows that almost half of the companies surveyed have introduced some types of big data projects, and they are expecting a very high return from these initiatives. no doubt that big data is considered as a valuable knowledge resource. if that is the case, what type of knowledge is found in big data? can this knowledge be considered as tacit knowledge? what should be the right strategy for organizations to handle a knowledge resource as complex as big data? in the article we try to answer to these questions and offer a big data related strategy framework. the rest of the article is divided into several parts: a short discussion on the present interest in big data followed by a review of big data concept, analysis of knowledge and tacit knowledge in the context of big data, a holistic big data strategy model with explanation and finally, the closing remarks. why now? the emergence of big data phenomenon is the result of a blending of several rising trends: the proliferation of social and business networks, the growth of mobile telecommunication, dramatic cost reduction in data collection, storage, processing and transportation and the increased deployment of sensors and machine to machine communication along with technological advancement in cloud computing, smart icts, data mining and analytics (oecd, 2011). lavalle et al. (2010) assert that companies that use business information and analytical tools in their differentiation strategy have twice as many chances to be in the group of top performers than lower performers of their industry. big data can produce minimum two types of values to an organization. firstly, it can be a source of innovation. specially, it can enable development of new products, processes and services. secondly, use of various analytics on big data can generate knowledge and insights that can support and improve organizational decision making significantly (provost and fawcett, 2013). the present interest in big data grew mostly thanks to these new value creation possibilities that were unavailable to most companies even recently due to the high cost of data storage, processing and analyzing. big data – the concept big data is a concept that means, firstly, the volume of the data is too large. secondly, it is impossible to analyze it using conventional technologies, and thirdly, special tools and treatment are necessary to extract knowledge from it (manyika et al., 2001). another way of viewing big data is to regard it as a massive pool of data that o p i n i o n s e c t i o n 56 allows creating insights and values that are not possible to generate from smaller scale of same data (jacobs, 2009). douglas laney (2001) of gartner, while explaining the challenges related to data growth noted that there are three dimensions to this problem: increasing amount of data – the growth of its volume, inflow and outflow speed of data – its velocity and heterogeneity of the data types and sources – data variety, the three vs. this has become the industry standard in characterizing big data. however, many argues that along with this model, value, veracity and variability also should be included as they are more important than the attributes of 3vs (swoyer, 2012). the concept of knowledge definition of knowledge in organizational science differs from the classical epistemological view of knowledge as "justified true belief" (nonaka and von krogh, 2009). despite its long history, the concept of knowledge is still subjective, complex and opaque. as a result, we see numerous variations of definitions of knowledge depending on discipline, context, approach and task at hand. in a broader sense, and for the purpose of this article, knowledge can be defined as information that is validated, contextual, relevant and actionable (soliman and youssef, 2003). another similar definition is, knowledge is tested, validated and codified information (earl, 1994). scarbrough & barrel (1996) propose the content theory of knowledge, where knowledge is deemed as an object that can be codified and stored. this approach of objectification of knowledge brings flexibility to the perception of knowledge. knowledge as an object can be acquired, integrated, stored and disseminated much like a commodity and becomes a tradable product (carlsson et al., 1996). in knowledge science knowledge is also considered as information with meaning, information is data with context and data is a basic element of analysis (boisot, 1995). this concatenation of data, information and knowledge is the most popular model of their correlation in knowledge and information literature (rowley, 2007). tacit knowledge much of the theoretical understanding of tacit knowledge in knowledge science derives from polanyi's concept of tacit and explicit knowing (polanyi, 1962). tacit and explicit knowledge are two sides of knowledge continuum (nonaka and takeuchi, 1995). explicit knowledge is the type of knowledge, which can be expressed using common language and codes. it is fully transferable and easy to share (nonaka, 1991). tacit knowledge, on the other hand, is subjective and informal (polanyi, 1958; nonaka, 1995). taking after polanyi's view, the concept of tacit knowledge and its place in organizational knowledge creation was largely popularized by nonaka (1995) and defined as knowledge that indwells human mind and body (nonaka and von krogh, 2009). many subjectivist scholars believe that tacit knowledge cannot be articulated, captured or interpreted in any form as this type of knowledge gets developed and remains embodied only in the human mind (see tsoukas 2006). however, others conclude while some tacit knowledge is impossible to explicate, most tacit knowledge can be codified (nonaka, 1995; collins, 2010). we believe that reality exists independently from the human mind and knowledge, including tacit knowledge, can reside in various other silos apart from the human cognizance (searle, 1993). many other scholars also support this notion. walsh and ungson (1991) posit that knowledge resides in five venues of an organization: people, roles and organizational structures, operating procedures and practices, culture, and the physical structure of the workplace. hershbach (1995) believes technological activities embody a larger portion of tacit knowledge than we normally recognize. some researchers describe tacit knowledge as uncertain, unstructured, indeterminate, and indirect (see kikoski and kikoski, 2004) and others conclude tacit knowledge is the kind of knowledge which is implied but not yet documented (junnarkar and brown, 1988). these views support the idea that knowledge, insights, patterns, indicators and pointers embedded in big data and waiting to be extracted are a form of tacit knowledge. knowledge management strategy organizational knowledge management strategy refers to planning and deployment of methods, processes, procedures and guidelines of knowledge acquisition, organization, utilization and distribution in order to achieve business goals. knowledge being a valued resource, knowledge management strategy must be always aligned with the organization's business strategy (eisenhardt and santos, 2002). for example, focus of knowledge management strategy can be the development of intellectual capital using both knowledge o p i n i o n s e c t i o n 57 exploration and knowledge exploitation and as a result gain competitive advantage (zack, 1999) knowledge exploitation strategy builds upon existing knowledge and knowledge exploration on acquisition of new knowledge. both of them are vital in organization's overall knowledge strategy (ichijo, 2002). these knowledge strategies encompass knowledge processes that include knowledge creation, acquisition, integration, sharing, replication, storage, organization, measurement and identification (grant, 2008) and require performing balancing act between external and internal factors relevant to organization’s goals. big data strategy the sudden emergence of big data as a source for new knowledge, valuable insights, and innovation and, as a result, competitive advantage has caught many companies off‐guard. the fact that management can have a more holistic picture of their business and convert that knowledge to make more informed decision and improve overall company performance is forcing firms to adopt comprehensive big data related knowledge strategies. mere adoption of a strategy based on industry experience is not good enough. knowledge strategy, in this case, must be aligned with the expected insights and knowledge received from big data and correlated to the business strategy, so that this new knowledge can be implemented across the board. this means focusing on not just understanding how the insights and knowledge can be infused in the business processes but also take necessary actions to embed the new knowledge in the business processes of most critical areas starting from new product development to customer satisfaction and from manufacturing to logistics. big data strategy framework rubenstein‐montano et al. (2001) asserts that a holistic framework of knowledge management that covers general requirements and can be followed by any knowledge management initiative independent of methodologies and tools is essential. following this suggestion in this paper we propose a universal strategy framework suitable for any organization in relation to big data initiatives from knowledge management strategy perspective. prerequisites an organization must possess or develop several critical preconditions in order to implement an initiative successfully, to execute the processes smoothly and to ensure having expected outcome. management support for any transformation oriented knowledge project to become successful, it requires strong support from management (davenport et al., 1997). management support should include: giving clear motivational message to the organization about the importance of the big data project and its benefits in company's success, participating in identifying objectives and domain of the big data projects, allocating finance and other required resources and monitoring success. success of a big data project depends among others on having a clear understanding of what types of knowledge and insights are necessary in a decision making process. often, this requires knowledge way beyond data engineering skills of a data specialist. on the other hand, the business decision makers also need to have knowledge about what type of big data can provide needed insights. this means people involved in the big data project either have to have the necessary knowledge and education or they have to develop needed skills and core competencies. senior management's commitment and involvement in facilitating learning are crucial in building an adequately knowledgeable team capable of accomplishing big data project related assignments. infrastructure organizational infrastructure includes people, process, technology, structure and their correlation. big data related infrastructure needs to be focused on innovation and knowledge creation and, as a result, should have a high degree of flexibility and freedom. to achieve set strategic objectives organizational structure and roles should ensure a seamless flow of best practices throughout the firm. strategic goals setting and decision making in relation to the big data project should come from top management. if the big data initiative envisioned to be a large project, it makes sense to appoint a chief data officer who can oversee all data related projects. people big data projects need to have different skills set than organizations are normally accustomed to. this is one of the added reasons why it is necessary to pay special attention to the key success factor of a big data project ‐ people. depending on the kind of technologies the company is planning to implement, o p i n i o n s e c t i o n 58 it would require at the it level specialists in cloud architecture, hadoop, mapreduce, semantic webs and number of other key areas. vital to big data project are the holders of a new job title called data scientist. data scientists are necessary for making sense from big data. business intelligence professional understands the business decisions needs and capable of analyzing the big data in order to divulge correlations, knowledge and insights. figure 1: big data strategy framework data‐driven culture organizational culture is the collective programming that includes vision, norms, values, symbols, rituals, beliefs, habits and attitudes of the members that work as a normative glue in unifying the organization and influence the behavior of an individual member (hofstede, 1996).having a data‐driven culture that fosters implementation of big data projects is imperative for a firm that is striving to have competitive edge using data‐based decision‐making and business analytics. data‐ driven culture means having a clear understanding among the employees that data is everybody's business not just it departments and data has to be taken in consideration in almost all decision making. a study by economist intelligence unit shows that there is a strong positive link between data‐driven decision‐making and organizational performance. moreover, data driven companies with superior performance regard data sharing as a valuable process. they also consider that shared data needed to be used across the board and all units should collect data proactively (the economist, 2013). absorptive capacity the concept of "absorptive capacity" is defined as "ability of a firm to identify, assimilate and exploit knowledge from the environment" (cohen and levinthal, 1989: p. 569). absorptive capacity is considered as part of dynamic capabilities of the firm and are divided as potential absorptive capacity, which derives from knowledge acquisition and integration abilities and realized absorptive capacity, which encompasses transformation and exploitation of knowledge (zahra and george, 2002). absorptive capacity is the firm's capability of developing skills related to tacit knowledge (mowery and oxley, 1995). kim (1997) deems that it is the firm's learning and problem solving ability and kedia and bhagat (1988) view that absorptive capacity is firm’s ability to transform in accordance with technological shift. processes a key reason for paying attention to processes in strategy is the need for the organization to grasp how technologies, people, and processes in combination influence its business performance. goal setting the first and foremost goal for a company that is seriously investing in big data should be to depict a clear vision that emphasizes on the expected strategic outcome from the realization of the big data projects. in setting goals and developing roadmaps, all relevant departments and units need to participate. setting achievable and measurable goals is vital for the success of a big data project as half 59 of the big data projects initiated never get completed (lavalle et al., 2011). team building because of the complex knowledge and skill set that are required for receiving effective results from a big data project, it is necessary to organize the team according to organization's business objectives. the two most needed members of such a team are a data scientist and a business analytics professional. other members may include it specialists and workers from the business department most relevant to the data project. for example, if the big data team is working on finding a solution related to marketing, for best result it has to incorporate people from the marketing department as well (ohlhorst, 2013). mistake will be to assign the team to it department. analyzing information from a number of large corporations, researchers found that while it departments are highly efficient in data storage and protection, they are unable to offer solutions that can convert data into business value (beath et al., 2012). more over, organizations that are endowed with a large amount of big data, they have 70 percent more chances of having business intelligence projects initiated by the business community rather than it people (rowe and white, 2012). technology selection big data projects are complex systems requiring various types of information technologies that encompasses from storage to applications and include data warehouse solutions, information and data management, virtualization and visualization, different analytical tools to name a few. these elements can be divided into three categories: warehouse infrastructure, big data analytics platforms and big data applications. big data analytics is not a recent phenomenon. business intelligence tools are getting used in business decision making for more than several decades. what is new now is the explosive growth of data and capacity to store that data. the sudden popularity of big data can be attributed to the new technological platforms that haveemerged recently. they are capable of processing and analyzing data in various structures outperforming traditional database technologies in massive scale. selection of needed technologies will depend on the followings: data amount, speed of data flow, structure of data expected to be used, integration requirement of the data, expected outcomes from the data analysis, users' need, costs, etc. metrics selection the criticism of financial performance based management style that does not accommodate knowledge as one of the most valuable assets has been well documented (meyer and gupta, 1994). efforts have been made to develop performance measurement frameworks that are more encompassing and comprehensive in relation to intangible assets (epstein and manzoni, 1997) and which in various degrees encapsulate knowledge assets measurements (see for example: edvinsson and malone, 1997). since, big data analytics don't impact on the revenue generation directly, the roi analysis metrics should include indirect benefits that emanate from the big data initiative. plan implementation in line with the strategic goals and expected outcome, a firm needs to create and deploy a roadmap of big data initiative. along with setting objectives and milestones, selecting teams members and developing proof of concept one more important issue is to identify and obviate stifles related to the specificity of big data initiative environment. big data fundamentally differ from any other technology related projects. at one side, the team members work with the high velocity, high volume, high intensity and complex data in a real‐time environment of discovery and innovation, but the insights and knowledge garnered in this environment ultimately need to be aligned with traditional technology based environment of data compliance, governance, security and perfunctory decision making. organizations should be aware that this coupling of the two different environments might not go smoothly and may have a negative impact on the implementation of a well developed plan. outcome the big data generated by the organization's business processes and operational activities, which include innovation and knowledge related activities, as well as employee's skill development, have all the potential to become instrumental to developing competitive advantage. the big data base innovations are still in its infancy! early signs from various large corporations, however, demonstrate the immense possibilities that are hold in the tacit knowledge hidden in big data. improved human capital one of the fundamental elements of organizational intellectual capital is human capital (edvinsson and 60 sullivan, 1996). stewart (1999) defines intellectual capital as a combination of intellectual elements that include knowledge, information, intellectual properties and experience that are applied to generate wealth. the execution of big data projects requires hiring new talents and developing new professional skills among existing workers. the experiences of the professionals developed in the process of big data project are indubitably valuable assets. their contribution to the creation of new knowledge and innovative products, services and processes has a positive influence on the top and bottom lines of an organization. innovation most organizations understand that key to sustainable competitive advantage in today's globalized and wired world is innovation. in fact, innovation capabilities, arguably, are the most important determinant of firm's performance (mone et. al., 1998). big data is an enabler, a driver and a source of new products, processes, services, strategies and business models (manyika et al., 2011). through big data capturing, aggregating, storing and analyzing companies from every industry and sector have the potential to reap benefits of innovation. innovations originated and spawned from big data can be divided into three categories: big data‐driven innovation: innovation where big data is the primary material in the development of a product, service, process or model. one example is high speed trading. big data enabled innovation: in an innovation where big data works as a catalyst. examples are: determining marketing campaign effectiveness, using sensors data to predict machinery failure, monitoring customer's experience of a product and finding design and manufacturing problems. big data related innovation: technology, process and service innovation that opens new possibilities in handling big data. example could be a new in‐ house business analytics technique. new knowledge base knowledge acquired from diverse sources is crucial for creating new knowledge. organizations pursue externally sourced knowledge actively as the more knowledge absorbed from external sources the better the chances of new types of knowledge recombination and generation (cohen and levinthal, 1989). developing dynamic capabilities that help recognizing new possibilities and capturing new business opportunities thanks to aggressive acquisition of external knowledge, which in turn leads to better innovation, is a key to firm's competitiveness (zhou and uhlaner, 2009). big data initiative develops a kind of dynamic capability that contributes significantly to organizations knowledge base in respect to knowledge repositories, employees' knowledge foundation and absorptive capacity. conclusion in this paper, we have explored the idea that knowledge residing in the big data is indeed tacit and in most of the cases open to explicability. once extracted this new knowledge can be transferred, used and shared much like any other explicit knowledge. this new and unique knowledge has all the potential of creating economic value for an organization and bolster innovation, productivity and growth. thus, it is also a possible major source of competitive advantage. we then proposed a big data centric knowledge strategy framework that outlines requirements, processes and outcomes of a big data initiative that aims at 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(erim report series ers‐2009‐025‐org) rotterdam: erasmus research institute of management. http://www.myagiledata.com/articles/share/18759/ http://www.myagiledata.com/articles/share/18759/ issn: 2001-015x v o l 2 , n o 3 ( 2 0 1 2 ) c o n t e n t s helen n. rothberg and g. scott erickson benchmarking competitive intelligence activity pp. 5-11 stéphane goria how to adapt a tactical board wargame for marketing strategy identification pp. 12-28 yasmina amara, klaus solberg søilen and dirk vriens using the ssav model to evaluate business intelligence software pp. 29-40 marisela rodriguez salvador and luis francisco salinas casanova applying competitive intelligence: the case of thermoplastics elastomers pp. 41-47 klaus solberg søilen and anders hasslinger factors shaping vendor differentiation in the business intelligence software industry pp. 48-54 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2012 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, president of china institute of competitive intelligence, china raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/22') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/23') 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javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/8') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/9') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/10') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/12') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/31') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/13') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/14') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/15') 4 journal of intelligence studies in business halmstad, december 22 2012 e d i t o r i a l n o t e v o l 2 , n o 3 ( 2 0 1 2 ) jisib has entered into an electronic licensing relationship with ebsco publishing. it has also been selected to appear in ebsco’s business source complete database, which according to the company publishes “superior academic journals (…) with premium content of peer-reviewed, business related journals. “ jisib now also fulfills the official criteria of thomson reuters to be cited in their isi web of knowledge database. as such it has applied to be included in the database. however, by experience with other journals, we know this process can still take considerable time. after having had the journal’s first annual meeting for editors in december we would like to thank the old board members who are leaving and welcome the new ones. most contributions continue to come from best papers from a number of conferences related to intelligence studies. two out of five articles come from eckm 2012, which was held 6-7 september in cartagena, spain. track co-chairs for the mini track on competitive intelligence and km was g. scott erickson, ithaca college, ithaca, ny and helen n. rothberg, marist college, poughkeepsie, new york. two other articles are revised versions of papers presented at ecis, but not previously published in journals. the article by helen n. rothberg and g. scott erickson is about how to benchmark competitive intelligence activities. the paper identifies and measures different circumstances in which knowledge development and knowledge protection can have greater or lesser importance for a company. the authors believe that the results will start to move scholarly work in the field into the new areas of macro studies and strategic choice. the article by stéphan goria is on board wargames for businesses. it also gives a broad background of this field of study with the history of wargames and numerous historical examples. moreover goria shows the benefits with wargames by creating a new game and testing it for a market situation which found place in france between nintendo and sony. the article by yasmina amara, klaus solberg søilen and dirk vriens proposes a way to evaluate business intelligence software by introducing a new model, the ssav model. the article by marisela rodriguez salvador and luis francisco salinas casanova applies a competitive intelligence model to analyze thermoplastics elastomers (te), a class of polymers, for a company in mexico. the model shows numerous novel findings with important implications for the company. finally, the article by klaus solberg søilen and anders hasslinger show how vendors of business intelligence software try to differentiate themselves in this market. on behalf of the editorial board, sincerely yours, dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 page 4 editors note vol 7 no 3 editor’s note vol 7, no 3 (2017) how companies succeed and fail to succeed with the implementation of intelligence systems most papers in this issue deal with different sides of technological systems and managerial practices used for intelligence work in private organizations. empirical data from a number of countries and companies are gathered to illustrate how companies work and fail to work with business intelligence and competitive intelligence in organizations. the paper by rezaie, mirabedini and abtahi entitled “identifying key effective factors on the implementation process of business intelligence in the banking industry of iran” identifies key effective factors on the implementation process of business intelligence. thirty-nine factors were identified and classified in nine main groups, including organizational, human, data quality, environmental, system ability, strategic, service quality, technical infrastructure, and managerial factors. the paper by bisson and gurpinar entitled “a bayesian approach to developing a strategic early warning system for the french milk market” suggests a new strategic early warning system for companies and public organizations to better anticipate market changes and make more robust decisions. the paper by al rashdi and nair entitled “a business intelligence framework for sultan qaboos university: a case study in the middle east” aims to build a customized business intelligence (bi) framework for sultan qaboos university (squ). a prototype is tested with good results. the paper by søilen, tontini, aagerup and andersson entitled “the perception of useful information derived from twitter: a survey of professionals” is a survey of professionals about the value of the information or intelligence on twitter. it shows that twitter is perceived as a service for useful information but not for the reason one may expect, not because the content of the tweets gives valuable information, but because of what can be derived and extracted from the information that is being tweeted and not tweeted. the paper by calof, richards and santilli entitled “insight through open intelligence” is an opinion piece that gives suggestions of how to broaden the ci field with the help of open innovation. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2017 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 7, no 3 (2017) p. 4 open access: freely available at: https://ojs.hh.se/ 5 competitive intelligence and information technology adoption of smes in turkey: diagnosing current performance and identifying barriers sheila wright, christophe bisson, alistair duffy strategic partnerships ltd, uk, kadir has university, turkey de montfort university, uk e-mail: sheila.stratpartners@aol.com, cbisson@khas.edu.tr, apd@dmu.ac.uk received may 23, accepted 10 august 2013 abstract: the need for smes to behave in a more concise and coherent competitive fashion is well recognised. this study reports on an empirical study of smes in turkey. their responses were applied to a behavioural and information technology adoption framework which enabled the identification of areas where changes would be required for these firms to begin operating at a higher level of competence. the findings revealed significant scope for improvements on all strands of the diagnostic framework: attitude, gathering, location, technology support, it systems support and finally, use of intelligence-based output by decisionmakers. through free form responses, it was also possible to identify barrier to higher level adoption and performance inhibiters, which were subsequently, categorised and assessed for significance. keywords: competitive intelligence, information technology, adoption, smes, performance barriers introduction globalization and the fast improvement of information and communication technologies (ict) significantly increases the competitive pressure (bisson et al., 2012). leidner et al., (2011) indicated that “as the pace of technology increases, market preferences become increasingly dynamic as well” (p. 423). indeed, in addition to facing increasing numbers of traditional competitors, businesses can be one click away from extinction as they grapple with the relentless rise of ecommerce (chaffey et al., 2009). yet, the need to integrate intelligence into one’s product and services follows the quick rhythm of innovation (schilling, 2010) which is leading society away from an information rich age to an intelligence rich age (bourret, 2008). this paper reports on an available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2013) 5-29 mailto:sheila.stratpartners@aol.com mailto:cbisson@khas.edu.tr mailto:apd@dmu.ac.uk https://ojs.hh.se/ 6 empirical study of the sme sector in turkey, with particular emphasis on the adoption, or otherwise, by practitioners, of technological support and it support systems, in the pursuit of what wright (2011) has termed as intelligence based competitive advantage (ibca). the creation of knowledge and its application to business decision-making is deemed to be a key source of competitive advantage for firms (mcadam et al., 2007; nonaka & von krogh, 2009; sherif & xing 2006; von krogh, 2009; wang et al., 2009; yang, 2005). the conversion of information to intelligence is critical in this task as the volume of data and information grows exponentially, blurring a company’s understanding of its immediate and potential environment (bawden & robinson, 2009; foenix-riou, 2011; qamar et al., 2010). nearly 15 years ago, hitt et al., (1998) reported that “with changed dynamics in the new competitive landscape, firms face multiple discontinuities that often occur simultaneously and are not easily predicted” (p. 22). the competitive landscape has changed even more dramatically than they predicted (cravens et al., 2009), requiring firms to adopt an organisational philosophy, which integrates competitive intelligence (ci) tools and methodologies into the mind-set of all employees regardless of status (wright, 2011). this study was significant and unique because it addressed an important scientific gap in the literature, that being the level of information technology adoption combined with ci practices of smes in turkey. a key feature of this work was the recognition of the potential for it and is adoption to deliver ibca and the realisation that for smes in particular, this is no longer an option, rather a pre-requisite for success in an increasingly turbulent and complex business environment. the study is also a timely contribution which adds to the growing interest in this area, as noted by dhaliwal et al., (2011). why smes? why turkey? smes play a vital role in turkey as they comprise 98-99% of all firms, represent 81% of all employment and contribute 36% of the total gdp of the country (kavcioglu, 2009). while the world economy is dull, the light is now on turkey since its economy is currently one of the better performers, with 8.2% growth in 2010 (central intelligence agency, 2011) and is the second fastest growing economy in the world after china (bryant, 2011). turkish smes constitute a political power as many support the current prime minister, mr erdoğan (hubert-rodier, 2013) and they are very concerned at the current protests, and the potential for this to affect the success of their businesses. recent events in turkey have already had an impact on the country’s economy with the istanbul stock exchange suffering a 19% loss in value in just ten days between 31st may and 10th june 2013 (euronews, 2013). more fundamental problems exist though, as kavcioglu (2009) reported that turkish smes have marketing problems, compounded by a lack of information and technology expertise. this study therefore, was not only significant because no research of this type, or depth, had been undertaken thus far, but it included the unique aspects of technological support and it support systems. using empirical evidence, the aim was to identify and classify ci behaviour and attitudes of smes in turkey, against an extended typology of practice, based on that first produced by wright et al., 2002). the collection of information, its aggregation and dissemination allows a firm to build knowledge (chaffey & white, 2011; cook & cook, 2000; eren & erdoğmuş, 2004) which is an important contributor to competitive advantage (hanna, 2007; nonaka & von krogh, 2009; spraggon & bodolica, 2008; teece, 2005; tziralis et al., 2009; zha & chen, 2009). koksal (2008) underlines that “higher levels of information utilization are expected to increase company performance since companies learn to effectively manage competition, understand customer needs, and target profitable markets” (p. 418). thus, the adoption of information technology (it) is a challenge faced by all smes (chuang et al., 2009; nguyen, 2009). it can allow smes to become global players, most notably via e-commerce (chaffey et al., 2009). lester & tran (2008) stress that one of the most important components of an sme’s operation in today’s competitive environment is its it adoption, and the potential for it to enable or support strategic, tactical and operational decisions was recognised by sambamurthy et al., (2003) and 7 krishnan et al., (2007). huang et al., (2009) commented that “organizations introduce it governance mechanisms in order to rationalise and coordinate their it related decision-making so that it assets, efforts and investments are aligned with the organisation’s strategic and tactical intents” (p. 158). nearly 20 years ago, kettinger et al., (1994, p 48) stated that “the attainment of sustained it-based competitive advantage may be more of a process of building organizational infrastructure in order to enable innovative action strategies as opposed to ‘being first on the scene’” (p. 48). although it has been recognized as a key element of success in today’s hyper-competition (chaffey & white, 2011), the commoditisation and affordability of both hardware and software means it is no longer simply the act of ownership which delivers competitive advantage. the real benefit comes in the management and organisation of it such that it supports the firm’s decision-making and aids the achievement of objectives (chen, 2011; galliers, 2004, 2006; gallivan & srite, 2005; gorla et al., 2010; kappos & rivard, 2008; leidner & kayworth, 2006; leidner et al., 2011; ray et al., 2005; wade & hulland, 2004;). in their research, baptista et al., (2010) concluded that it was essential for “senior management to continuously raise awareness about the strategic possibilities of established technology to ensure that they do not ‘drift away' from business needs” (p. 182). nevo & wade, (2011) posit that “when it comes to it assets, it is not the things you have that count, but how you use them, or more specifically, how you combine them” (p. 143) yet dhaliwal et al. (2011) emphasised that the strategic business it alignment is one of the hottest research topics in the field of management information. the acquisition, retention and future development of ibca thus becomes essential to firms of all sizes, and its employees but especially to smes (bisson, 2003; lee & trim, 2006; tziralis et al., 2009; wright, 2011; zha & chen, 2009). the important of ci practice to smes within the extant literature of ci research, the focus is primarily related to large firms, (burke & jarratt, 2004; isoptt, 2006; smith et al., 2010; tarraf & molz, 2006; wagner, 2008) yet xinping et al., (2010) reminded us that the problems faced by larger organisations and their associated decision-makers are exactly the same as those faced by smes. the challenge for the latter is even more pronounced as they wrestle with these issues without the benefits of resource and expertise advantages, typically found in larger enterprises. in their study of small knowledge-intensive business service firms, huggins & weir (2012) noted that small firms were less likely to register patents, hold intellectual property rights, or own it based assets such as complex knowledge management intranets. as such, the ability of small firms to engage with ci practices and to leverage that as a source of competitive advantage is a key investment area in the eu. studies in france (larivet, 2009; smith et al., 2010) note the high level of government funded intervention and support which not only provides practical and intellectual assistance to their sme sector but results in a heightened awareness of the commercial benefit of such practice (smith, 2005). this becomes all the more important when it is realised that “in most countries, smes constitute the main source of employment and are increasingly active participants in the globalized economy” (bisson, 2010, p. 24). yet, the financial crisis which started in 2008 and shows no sign of retreating (bresson & bisson, 2011; evrard samuel et al., 2011; krugman & wells, 2010), only serves to enhance the importance of the sme sector to a country’s economic success. it could easily be argued that developing ci awareness within the sme sector of any country, and providing support which will encourage them to attain ibca is even more important now than it ever was. expert execution of ci requires dedicated software and hardware in order to obtain the right information in response to intelligence needs, the production of accurate analysis and its timely dissemination to the right person to take the right decision (bisson, 2010; gordon et al., 2008; wright, 2011). therefore, smes need to build their information system (is) for strategic purpose (franco et al., 2011a; garg et al., 2010; rouibah & ould-ali, 2002; zhang et al., 2010) as opposed to a purely operational purpose (bhagwat & sharma, 2007; litan & rivlin, 2001). as a consequence, a strategic information system (sis) needs to be built which becomes a vital influence on a firm’s success as it shapes strategy and contributes to the 8 implementation of that strategy (dhaliwal et al., 2011; galliers, 1991; 2004; 2006; ma et al., 2008; petrini & pozzebon, 2009; rishi & goyal, 2011). rouibah & ould-ali, (2002) also emphasised that “an sis, oriented toward external changes helps an organization to remain competitive and proactive” (p. 137). wang et al., (2003) state that “if appropriately deployed and used, information technologies could produce many strategic and operational benefits for organizations” (p. 2). whilst most research into the benefits of information technology (it) adoption and its links to the creation of sustainable competitive advantage has been conducted in the developed world and larger enterprises, (lee et al., 2011; quan & hu, 2006; roztocki & weistroffer, 2008; 2011; samoilenko, 2008) others advocate that it needs to be widely adopted equally by smes (chang et al., 2010; chuang et al., 2009; hanna, 2007; nguyen, 2009; sultan, 2007). these views are echoed by the authors of research into sme ci practice in canada (brouard, 2006; tannev & bailetti, 2008; tarraf & molz, 2006), in france (afolabi, 2007; bisson, 2003; knauf, 2007; salles, 2006; smith et al., 2010) and in switzerland (begin et al., 2007). mazzarol et al., (2009), reported that “ownermanagers from small firms need to be alerted to environmental changes, committed to innovation and willing to change or take action if required” (p. 338). lesca et al., (2005) also said that “in order to become more and more competitive, smes and above all smes of emergent countries need to capture international and transnational markets” (p. 1). the evidence above suggests that the combination of ci methods and technology tools by smes is critical, not only for all countries, but especially for a nation such as turkey which relies so heavily on that sector of its commercial constitution, for fiscal, trade and employment success. very few studies have been conducted in emerging countries (ifan et al., 2004; zha & chen, 2009) with only two in the country selected for the study reported here. taşkin et al., (2004) investigated the technological intelligence capacity in turkish companies, using a sample of 300 firms but no identification of firm size was evident. koseoglu et al., (2011) investigated the ci practices of privately held smes in the afyonkarahisar region with a particular focus on the use of internal or external resources. they applied six general hypotheses to the 216 usable surveys obtained from a 1000 random sample. from an unequal data set (71.3% services / 28.7% industrial/manufacturing) comparisons were drawn and it is not surprising that their findings suggested that service sector firms showed more deployment of both internal and external resources than industrial/manufacturing firms. that study did not especially enlighten us into the ci practices of smes in turkey, it simply served to identify our lack of knowledge of how ci practice is conducted in the sme sector in this important emerging market. methodology and methods adopted in contrast to the work of koseoglu et al., (2011) this study was conducted in the heart of the country, istanbul, and was framed within a wellregarded, empirically tested, proven typology of practice, first developed by wright et al., (2002). this model has been a platform or inspiration for further work and/or replication studies by authors such as adidam et al., (2009), april & bessa, (2006), bouthillier & jin, (2005), dishman & calof, (2008), hudson & smith, (2008), larivet, (2009), liu & wang, (2008), oerlemans et al., (2005), santos & correia, (2010), smith, (2005), tryfonas & thomas, (2006), whitehurst, (2008), wright et al., (2008) and wright et al., (2009a; 2009b). this provides evidence of validation of the measures developed and as such it was deemed to be one which was entirely appropriate to use as the foundation for this work. the overarching research approach was to identify the views of a community working in a variety of industry sectors, thus a constructivist/transformative approach was adopted, whilst accepting that any data collected could only be a reflection of ‘provisional knowledge’ as opposed to the discovery of indisputable ‘facts’. that said, and with regard to the robustness and grounding in practice of the questionnaire, the results are nevertheless indicative of an sme sector and as such, the study is perfectly capable of being replicated in the sme environment of other countries and used for comparison purposes. questions were asked which would reveal a type of behaviour or operational stance along the four http://www.tandfonline.com/action/dosearch?action=runsearch&type=advanced&result=true&prevsearch=%2bauthorsfield%3a(samoilenko%2c+s.) 9 original strands of ci practice: attitude, gathering, location and use. the opportunity was taken to extend that typology to include two further strands: technology support, identified as the degree of investment made to assist with gathering competitive information and it support systems, identified as the type of systems used to manage the flow of competitive information. this enabled greater investigation into the issue of practitioner engagement with strategic information systems which also coincided with the thoughts of lee (2010) who called for research of this nature to be more relevant to practice and to go beyond the technical aspects of is development. it was within these boundaries of relevance and practical application that this study was constructed and executed. the resultant framework and strand descriptors, which were derived from empirical evidence and against which responses were applied, is shown in table 1. the optimum level of performance, indicative of best practice is identified by the shaded areas of table 1, i.e. strategic attitude (a4), hunter gathering (g1), designated location (l2), high technology support (ts4), bespoke it systems (its6) and strategic user (u4). 10 table 1: a behavioural and operational typology of competitive intelligence practice attitude a1 immune attitude too busy thinking about today to worry about tomorrow. thinks that the firm is either so small, so big or so special that it enjoys immunity from competitors and thus ci is a waste of time. minimal or no support from either top management or other departments. a2 task-driven attitude finding answers to specific questions and extending what the firm knows about its competitors, usually on an ad-hoc basis. departments more excited about ci than top management who don’t see the benefits. a3 operational attitude a process, with the company at its centre, trying to understand, analyse and interpret markets. top management usually trying to develop a positive attitude towards ci because they can see it might increase profit, and therefore personal bonuses. unwilling or unable to think about the application of ci for the long term. a4 strategic attitude an integrated procedure, in which competitors are determined as those who are satisfying our customer’s needs, current and/or future. monitoring their moves, anticipating what they will do next and working out response strategies. receives both top management support, co-operation from other departments and is recognised by all as essential for future success. gathering g1 easy gathering firms which use general publications and/or specific industry periodicals and think these constitute exhaustive information. unlikely to commit resources to obtain information which may be difficult or costly to obtain. always looking for an immediate return on investment. g2 hunter gathering firms knowing that easy gathering information is available to all who care to look. realise that if ci is to have a strategic impact then additional, sustained effort is required. resources are available which allow researchers to access sources within reasonable cost parameters, back their instinct, follow apparently irrelevant leads, spend time talking, brainstorming and thinking about ci problems without always being pressured for ‘the answer’. firms which appreciate and support intellectual effort. location l1 ad-hoc location no dedicated ci unit. intelligence activities, where undertaken are on an ad-hoc basis, subsumed into other departments, with intermittent or nonexistent sharing policies. l2 designated location firms with a specific intelligence unit, full time staff, dedicated roles, addressing agreed strategic issues. staff have easy access to decision makers, status is not a barrier to effective communication. technology support ts1 simple tech support the company is just using the free web such as a search engine or looking at some web sites which require no specific knowledge. also use general office software such as spread sheets. ts2 average tech support using off the shelf products such as meta-search engines which simply reorganise publicly available information for own use. company might use web sites requiring specific knowledge (e.g. espacenet) and pay to use specialised websites and databases (e.g. patent and finance). 11 ts3 advanced tech support this information system holds vital and high level information as well as operational and tactical material. is fully integrated across the business and continually evolves to meet the firm’s requirements. content analysis (e.g. statistical analysis) provided. ts4 high tech support in addition to advanced tools, firms use ‘clever’ algorithms aimed at understanding automatically the competitive information collected. these algorithms are based on semantics. it systems its1 dismissive it systems does not use any it system to manage competitive information which may occur as the result of a considered decision not to engage with it systems for this purpose or may be out of ignorance of the potential which engagement might deliver. think that competitive information is in their minds and that they rely on their memories. its2 sceptic it systems has a system to manage competitive information but prefers to use paper based records. the firm declares that it does not trust it systems sufficiently, is concerned about the safety of information and is wary of their reliability. may be the result of a bad experience or ignorance of what is available to satisfy such concerns. its3 standardised it systems uses a standard off-the shelf system, usually purchased from a software vendor and installed on computers located within an organisation. no customisation or developmental work is considered worthwhile, either on the grounds of cost or lack of expertise in-house to be able to specify what the firm needs. its4 hosted it systems a standard system is used, but it is not managed by the company itself (e.g. pay per view system). the responsibility for managing it lies elsewhere, with the host, rather than the firm itself. the whole process is expertly overseen and protected as well as backed-up automatically to a distant secure location. its5 tailored it systems an off-the-shelf system or hosted solution is tailored according to an organisation’s needs regarding its competitive information. considerable intellectual effort is put into developing this over time as expertise increases and requirements change. its6 bespoke it systems unique to the firm system which has been designed in-house, aimed at collecting, analysing and disseminating competitive information in real time. the system is inimitable, being designed to meet the specific needs of specific decision-makers. funds are made available for adaptations, updates and upgrades over time. the system’s central role in delivering competitive information is recognised. use u1 joneses user firms tend to engage in the use of ci output, only because it is what everybody else seems to be doing and they think they should do the same. they try to obtain answers to disparate questions but no organisational learning is taking place rom one project to the next. has commissioned a ci report from a consultant because that is what everybody else has done. the expenditure will have little beneficial effect as the firm will be ill-equipped to either understand or act on its findings due to unfamiliarity with the terminology. the firm will have no organised process for ci, will use any output for short-term decisions only and will regard monitoring technology standard changes as their primary reason for adopting ci practice. u2 knee jerk user firms which obtain some ci data, fail to assess its quality or impact, yet act immediately. can often lead to wasted and inappropriate effort, sometimes with damaging results. such firms are most vulnerable to planted mis-information by more ci aware competitors u3 tactical concentrate their ci efforts to inform tactical measures such as price changes, promotional effort. some firms can successfully argue that ci loses 12 user its impact and timeliness if it gets stuck at the strategic level but are, nevertheless, acutely aware of its potential value to the business. willing to act on ci output and will carefully examine short term moves by competitors as well as their business plans to understand the potential effect on their own firm. u4 strategic user ci is used to identify opportunities/threats in the industry and to aid effective strategic decision making. all levels of staff, management and operational, are aware of critical success factors (csfs) and their attendant ci requirements. continuous, legal measures used to track competitors, simulate their strengths and weaknesses, build scenarios, and plan effective counter attacks. the entire focus is on the achievement of sustainable competitive advantage, assessing competitor m&a plans and predicting their long term behaviour. ci data is systematically applied to ‘what-if?’ discussions whilst contingency planning and counter intelligence is a part of normal strategic thinking. action plans are implemented and mistakes are seized upon as learning, rather than blaming, opportunities. open and facilitative management culture exists which epitomises trust and encourages involvement by all, regardless of position in the firm. 13 to ensure compatibility of analysis, the questionnaire used by wright et al., (2002) was adapted and each of the strands were transformed into diagnostic questions which could then be translated into a typology verdict for that individual firm. set apart from the main category questions, a self-declared position statement was offered which was used to either confirm or contradict answers given within each category. this served as a clarification mechanism which revealed any inconsistency in a typology verdict based on the allocations of answers to individual questions and the self-declared position statement. general questions were asked which allowed the responses to be classified according to turnover, sector, employee numbers, main markets and export activity. before execution the questionnaire was translated, back-translated, piloted and any issues of clarity or potential for misunderstanding were addressed. identifying target firms to receive the research instrument was accomplished with the assistance of the istanbul sanayi odasi (istanbul chamber of industry) which provided a membership list. this was cleaned to deal with duplicate data and to eliminate firms which were outside the eu definition (eu commission recommendation, 2003) of an sme in terms of turnover (< €50 million) and/or number of employees (< 250). a self-selecting sample of 371 firms indicated a willingness to take part in the survey and the link to the on-line questionnaire was sent to those firms. only 28 recipients of the invitation subsequently declined to respond. a total of 22 responses were deleted as their answers to the firm classification questions revealed that they too fell outside the scope of the eu’s definition of an sme. a further seven responses were identified as being from firms which had identified themselves as the local branch of a global company. these firms, although small in number, were considered to be less independent than a typical sme, would not behave in a comparable fashion and would potentially be acting under the direction of a much larger, potentially more resourceful entity. for these reasons, their responses were removed from the data set which resulted in a total of 314 returns being recorded, representing a response rate of 84.6%. the target group represented 55% of turkey’s trade, 45% of the country’s wholesale trade and generated 21.2% of turkey’s gross national product (istanbul metropolitan municipality, 2009). sample profile the results presented here are a sub-set of the larger survey referred to above but in accordance with this journal’s readership, the responses and analysis are derived only from the 144 firms which not only addressed all elements of the questionnaire but were able to indicate a response to the technological support, and it support systems sections, as they related to their ci practice. being an exploratory study this was considered to be an acceptable number of responses to conduct the analysis, albeit a self-selecting, convenience sample. the number of responses analysed by variable are given in table 2. table 2. sample profile turnover < €2 million 65 < €10 million 60 < €50 million 19 number of employees < 10 23 < 50 72 < 250 49 international contribution to t/o < 10% 43 < 25% 19 < 50% 22 < 75% 9 > 75% 16 don’t know 35 local vs global markets local 49 local and global 80 global 15 analytical approach the major objective was to demonstrate how the derived empirical evidence could be applied to the diagnostic typological framework which could then be used as a hierarchical framework of current and potential positioning for individual firms. it is anticipated that this could then be used to guide firms wishing to engage in best practice behaviours and improve their potential to move across the typology strands. this could also provide a 14 benchmark for other emerging countries which have a predominance of smes in their economy. the two major sector groupings were manufacturing with 86 returns and services with 58 returns which provided an initial over-arching sector allocation along each typology strand. subsequent analysis treated the 144 returns as being a representation of the turkish sme sector. results and discussion in order to determine the existence, or otherwise, of relationships between the five known variables: sector, turnover, number of employees, international contribution to turnover and dependence on local vs global markets, cross-tab analysis was undertaken. it was important not to lose any richness of the data and opinions given as these were considered to be highly valuable. as such, the deployment of statistical measures which could potentially, over-simplify matters was considered detrimental to the analysis process. to confirm this as a true situation, a pearson chisquare (placket, 1983) test was run on all elements of the data reported below and in all cases, it was obvious that any attempt to assign statistical significance to the data would be inappropriate as the pearson (p) did not reveal the required result of being less than 0.05. this does not mean that the results have no value. they are revealing in themselves and lead to appropriate conclusions for a study of this nature. the behavioural and attitude descriptors which formed the foundation for all questions asked are shown below, by typology strand, along with the responses gained and a discussion of the implication of those results. attitude the responses to this batch of questions were allocated to four major categories of competitive intelligence attitudes, a1 (immune), a2 (taskdrive), a3 (operational) and a4 (strategic). the results and analysis by variable for this strand of the typology are shown in table 3. table 3. attitude towards competitive intelligence practice count % (rounded) sector a1 a2 a3 a4 a1 a2 a3 a4 manufacturing 11 58 8 9 13 67 9 11 services 9 34 11 4 15 59 19 7 turnover a1 a2 a3 a4 a1 a2 a3 a4 < €2 million 9 46 6 4 14 71 9 6 < €10 million 9 36 9 6 15 60 15 10 < €50 million 2 10 4 3 10 53 21 16 number of employees a1 a2 a3 a4 a1 a2 a3 a4 < 10 3 13 4 3 13 57 17 13 < 50 8 49 8 7 11 68 11 10 < 250 9 30 7 3 19 61 14 6 int. contribution to t/o a1 a2 a3 a4 a1 a2 a3 a4 < 10% 5 29 5 4 12 67 12 9 < 25% 5 10 2 2 25 53 11 11 < 50% 4 12 3 3 18 54 14 14 < 75% 2 6 1 0 22 67 11 0 > 75% 1 12 1 2 6 75 6 13 don’t know 3 23 7 2 9 65 20 6 local vs global markets a1 a2 a3 a4 a1 a2 a3 a4 local 3 36 7 3 6 74 14 6 local and global 15 46 11 8 19 57 14 10 global 2 10 1 2 13 67 7 13 15 as the prime mover for ci effectiveness, a firm’s attitude towards such activity will colour its approach to all subsequent actions. a task-drive (a2) attitude dominated significantly across all the variables with the manufacturing sector being only slightly more competent than the services sector. overall though, the trend is clear. only 11% of firms in total demonstrated the best practice strategic attitude (a4) which is also linked to the small increase in a4 attitude, from firms with a larger turnover. this may well be explained as increased turnover being a direct cause, with the link towards greater strategic awareness and more advanced ci being practiced being an effect. it should be noted that this decomposition of the data gives the highest a3 value (25%), indicating that turnover is a major factor in differentiating between attitudes. that said, when asked the over-arching question of how they would describe their firm’s approach to ci, a greater swing towards a1 became evident with 48% saying that they were either too busy to think about it or that it was a waste of time. more in line with the data, 38% said that they tried to find answers to specific questions on a one-off basis (a2) and 14% said that they tried to understand, analyse and interpret markets on a short term basis. no firm agreed with the statement that they had an integrated competitive information process where they monitored competitors, anticipated their moves and planned their reaction strategy (a4). it might be reasonable to assume that an increasingly mature attitude would be observed as a function of company size, as measured by the number of employees but this is not the case. in fact the frequency of higher order attitudes decreases as the number of employees increases. the highest percentage figure exhibiting a2 behaviour was in the >75% of international contribution to turnover category. whilst accepting that the count had an influence here, the inference can be drawn that as firms achieve greater global exposure, there is a concurrent increase in the need for the adoption of a more positive attitude towards ci practice. the evidence suggests the verdict of a task-driven attitude (a2). gathering the responses to this batch of questions were allocated to two major categories of competitive intelligence gathering practice, g1 (easy gatherers) and g2 (hunter gatherers). the results and analysis by variable for this strand of the typology are shown in table 4. table 4. gathering behaviour count % (rounded) sector g1 g2 g1 g2 manufacturing 51 35 59 41 services 30 28 52 48 turnover g1 g2 g1 g2 < €2 million 33 32 51 49 < €10 million 35 25 58 41 < €50 million 13 6 68 32 number of employees g1 g2 g1 g2 < 10 14 9 61 39 < 50 36 36 50 50 < 250 31 18 63 37 int. contribution to t/o g1 g2 g1 g2 < 10% 20 23 47 53 < 25% 10 9 53 47 < 50% 13 9 59 41 < 75% 8 1 89 11 16 > 75% 10 6 63 37 don’t know 20 15 57 43 local vs global markets g1 g2 g1 g2 local 23 26 47 53 local and global 48 32 60 40 global 10 5 67 33 easy gatherers (g1) characteristics were demonstrated by the majority in all categories of analysis except just two. easy gatherers typically use general publications and/or specific industry periodicals as their main, or only, source of competitive information, tending to rely on passive and simple, environmental scanning frameworks. they mistakenly believe that these constitute an exhaustive information search and eschew the opportunity to operate at anything more than a base level of data collection. the two exceptions were the 23 firms which declared that <10% of their turnover came from an international contribution, which very closely matched the response of 26 firms which declared their market to be entirely local. these are also likely to be the firms with <50 employees. these firms, somewhat surprisingly, given the local nature of their business, were displaying what is considered to be the ideal, best practice, hunter gatherer (g2) characteristics which means they understand that g1 information is available to all who care to look. they also realise that if ci is to have a strategic impact on their activities, sustained effort, beyond the basic level is required. in g2 firms, resources are available which allow researchers to access sources within reasonable cost parameters, back their instinct, follow apparently irrelevant leads, spend time talking, brainstorming and thinking about ci problems without always being pressured for ‘the answer’. g2 firms appreciate and support the intellectual effort required to make ci succeed. they focus their information gathering efforts on competitors, customers, suppliers, patents and scientific articles (if relevant). they also consult with, and commission reports from, industry and sector experts, conduct competitor research internally, welcome both written and verbal evidence from verified sources. the manufacturing sector was roughly 60/40 in favour of g1, with services being slightly less dominant towards g1. somewhat worryingly, the trend towards g1 dominance is more notable as the turnover of the firm increases. one would expect for this to be the opposite in that as firms increase in size, their requirement to be more competitive increases concurrently. it is precisely at these stages in transition from micro to small and from small to medium, that greater effort in ci practice should be encouraged. it is possible to hypothesise that the larger firms are more likely to exhibit market follower characteristics as described by wunker, (2012), rather than first-mover or innovator behaviour (cleff & rennings, 2012; guimaraes, 2011). this may be due to their product range which exhibits commodity characteristics and are simply following the general direction of travel of a market. as such, they believe all they need to do is to monitor competitor offerings and read secondary data driven market reports. turkish smes are also ignoring the contribution which their own employees can make to their competitiveness. when asked how much competitive information their organization obtained from its own employees, a staggering 83% said that they either did not know, that none was obtained, or only a low or moderate amount was obtained (g1). just 17% declared that they garnered a high amount of competitive information from their employees, thus exhibiting hunter gatherer behaviour. when asked to state their firm’s position regarding training and preparing their employees about what information they should look for before they go to trade shows, exhibitions, conventions and other public events the results were more even. 55% stated that they did this ‘often’ or ‘always’, with 45% stating they either ‘never’, only ‘occasionally’ or did not know whether the firm engaged in this activity. whilst this shows a tendency towards g2 behaviour, it should also be recognised that this type of activity still relies on the more general aspects of information gathering, albeit it relatively cheap and quick to obtain. 17 a similar picture was revealed when asked whether they briefed their employees on what they should not talk about to competing firms. 31% said they either ‘did not know’, ‘never’ or ‘occasionally’ took this precaution to protect their sensitive information (g1) whilst 69% stated that they either did this ‘often’ or ‘always’ (g2). in attempting to reconcile these findings, it is quite likely that whilst the individual questions produced accurate answers as to where information was gathered, once asked to indicate a level of agreement with an overarching statement, a degree of wishful thinking may have entered the minds of the respondents. without the ability to seek proof of prior training and preparation of employees when attending events, the answers were perhaps a greater reflection of a desired rather than a current state. the results however, show that the firms in this sample lean significantly towards the actions of an easy gatherer (g1). location the responses to this batch of questions were allocated to two major categories which identified where the firm’s ci activity was centred: l1 (adhoc location) and l2 (designated location). the results and analysis by variable for this strand of the typology are shown in table 5. table 5. location of ci activity count % (rounded) sector l1 l2 l1 l2 manufacturing 79 7 92 8 services 53 5 91 9 turnover l1 l2 l1 l2 < €2 million 59 6 91 9 < €10 million 57 3 95 5 < €50 million 16 3 84 16 number of employees l1 l2 l1 l2 < 10 20 3 87 13 < 50 67 5 93 7 < 250 45 4 92 8 int. contribution to t/o l1 l2 l1 l2 < 10% 39 4 91 9 < 25% 18 1 95 5 < 50% 20 2 91 9 < 75% 9 0 100 0 > 75% 15 1 94 6 don’t know 31 4 89 11 local vs global markets l1 l2 l1 l2 local 43 6 88 12 local and global 76 4 95 5 global 13 2 87 13 the results from this strand were overwhelmingly in favour of an ad-hoc location (l1) which is not surprising given the task-driven attitudes and easy gathering verdicts of prior sections. without a designated location for ci practice, it is unlikely that the mind-set will develop, or that the benefits be identified. 18 technology support the responses to this batch of questions were allocated to four major categories which identified the level of technology support deployed by the firm in pursuit of ci practice. these were: ts1 (simple technology support), ts2 (average technology support), ts3 (advanced technology support) and ts4 (high technology support). the results and analysis by variable for this strand of the typology are shown in table 6. table 6. level of technology support deployed in ci practice count % (rounded) sector ts1 ts2 ts3 ts4 ts1 ts2 ts3 ts4 manufacturing 82 2 2 0 96 2 2 0 services 55 1 2 0 95 2 3 0 turnover ts1 ts2 ts3 ts4 ts1 ts2 ts3 ts4 < €2 million 63 1 1 0 98 1 1 0 < €10 million 56 2 2 0 94 3 3 0 < €50 million 18 0 1 0 95 0 5 0 number of employees ts1 ts2 ts3 ts4 ts1 ts2 ts3 ts4 < 10 22 1 0 0 96 4 0 0 < 50 70 1 1 0 98 1 1 0 < 250 45 1 3 0 92 2 6 0 int. contribution to t/o ts1 ts2 ts3 ts4 ts1 ts2 ts3 ts4 < 10% 39 2 2 0 90 5 5 0 < 25% 18 0 1 0 95 0 5 0 < 50% 21 0 1 0 96 0 4 0 < 75% 9 0 0 0 100 0 0 0 > 75% 16 0 0 0 100 0 0 0 don’t know 34 1 0 0 97 3 0 0 local vs global markets ts1 ts2 ts3 ts4 ts1 ts2 ts3 ts4 local 46 0 3 0 94 0 6 0 local and global 76 3 1 0 95 4 1 0 global 15 0 0 0 100 0 0 0 the somewhat worrying result from this data is the dominance of ts1 characteristics, in one case, 100% and very close to that figure in every other variable. there is a smattering of ts2 and ts3 returns but these are insignificant in number. what is significant is the total absence of any ts4 classifications which suggest either complete ignorance of the availability of such systems, a conscious decision not to adopt such a system on cost or lack of expertise grounds, or a wilful disregard for the benefits for such systems. in addressing the over-arching approach control questions, 88% of respondents said that they used common, freely available tools for web searching (ts1), just 5% used full versions of meta-search engines and specialist databases (ts2), 6% used software which permitted the collection, analysis and dissemination automatically (ts3) with just 1% saying they used software support based on semantics. this latter response is contrary to the data derived from earlier questions which sought answers to direct questions. as such, we believe those answers are more likely to be an accurate reflection of reality than the wishful thinking which may have been evident by the 1% reading for ts4 in the control questions. the results from 19 this strand is overwhelmingly in favour of an simple technology support (ts1). it systems the responses to this batch of questions were allocated to six major categories which identified the level of it systems deployed in pursuit of ci practice. they were: dismissive it system (its1), sceptic it system (its2), standardised it system (its3), hosted it system (its4), tailored it system (its5) and bespoke it system (its6). the results and analysis by variable for this strand of the typology are shown in table 7. table 7. it systems deployment in pursuit of ci practice count % (rounded) sector its1 its2 its3 its4 its5 its6 its1 its2 its3 its4 its5 its6 manufacturing 57 5 5 1 0 18 66 6 6 1 0 21 services 34 2 2 2 0 18 60 3 3 3 0 31 turnover its1 its2 its3 its4 its5 its6 its1 its2 its3 its4 its5 its6 < €2 million 43 2 3 1 0 16 66 3 5 2 0 25 < €10 million 38 3 3 2 0 14 64 5 5 3 0 23 < €50 million 10 2 1 0 0 6 53 10 5 0 0 32 number of employees its1 its2 its3 its4 its5 its6 its1 its2 its3 its4 its5 its6 < 10 16 0 1 1 0 5 70 0 4 4 0 22 < 50 48 2 3 1 0 18 67 3 4 2 0 25 < 250 27 5 3 1 0 13 55 10 6 2 0 27 int. contribution to t/o its1 its2 its3 its4 its5 its6 its1 its2 its3 its4 its5 its6 < 10% 28 3 1 1 0 10 66 7 2 2 0 23 < 25% 10 2 1 1 0 5 53 11 5 5 0 26 < 50% 14 2 1 0 0 5 64 9 4 0 0 23 < 75% 5 0 0 0 0 4 56 0 0 0 0 44 > 75% 11 0 2 0 0 3 69 0 12 0 0 19 don’t know 23 0 2 1 0 9 66 0 5 3 0 26 local vs global markets its1 its2 its3 its4 its5 its6 its1 its2 its3 its4 its5 its6 local 34 2 1 0 0 12 69 4 2 0 0 25 local and global 49 4 3 2 0 22 61 5 4 2 0 28 global 8 1 3 1 0 2 53 7 20 7 0 13 the first thing to notice in this data set is the relatively small percentage figures for its2, its3 and its4 with a complete absence of any its5 responses. the results for both manufacturing and services are polarised between its1 and its6, as are the combined results by turnover, number of employees and by international contribution to turnover. there is an increase in the number of firms with both a local and global market, adopting an its6 strategy but it is hardly significant. a small number of global market firms report an its3 approach but again, the low count does not provide significance. answers to the over-arching control questions do not necessarily support the high figures for its6 but do give credence to the returns for its1. a total of 63% stated that they did not use any it systems to manage competitive information and they relied on memories and the good will of staff to share what they learned (its1), 5% stated that they didn’t really trust computers and that they preferred to stick with traditional methods by using paper records (its2), 5% had bought a standardised system which they felt suited their needs. just 2% said that they had purchased a standardised system, hosted by a third party vendor for which they paid a fee (its4), no firm stated that they had installed a tailored system for exclusive use, hosted by a third party vendor (its5), with 25% declaring that they had designed their own system in-house, to suit their own unique needs. 20 the results from this strand, whilst showing good response for bespoke it systems (its), the derived data, supported by answers to the control questions, shows a significant leaning towards firms opting, either by a conscious decision not to engage, ignorance or lack of expertise, for a dismissive it system (its1). user the responses to this batch of questions were allocated to four major categories of competitive intelligence user profiles, u1 (joneses), u2 (kneejerk), u3 (tactical) and u4 (strategic). the results and analysis by variable for this strand of the typology are shown in table 8. table 8. user category on how ci output is deployed count % (rounded) sector u1 u2 u3 u4 u1 u2 u3 u4 manufacturing 17 18 21 30 20 21 24 35 services 12 13 15 18 21 22 26 31 turnover u1 u2 u3 u4 u1 u2 u3 u4 < €2 million 14 14 18 19 21 21 29 29 < €10 million 12 14 14 20 20 23 23 34 < €50 million 3 3 4 9 16 16 21 47 number of employees u1 u2 u3 u4 u1 u2 u3 u4 < 10 4 8 5 6 17 35 22 26 < 50 17 12 19 24 24 17 26 33 < 250 8 11 12 18 16 22 25 37 int. contribution to t/o u1 u2 u3 u4 u1 u2 u3 u4 < 10% 6 10 12 15 14 23 28 35 < 25% 4 2 7 6 21 10 37 32 < 50% 3 4 5 10 14 18 23 45 < 75% 2 3 1 3 23 33 11 33 > 75% 4 4 5 3 25 25 31 19 don’t know 10 8 6 11 29 23 17 31 local vs global markets u1 u2 u3 u4 u1 u2 u3 u4 local 8 13 12 16 16 26 25 33 local and global 18 15 19 28 22 19 24 35 global 3 3 5 4 20 20 33 27 on examining the data it is hard to reconcile the u4 descriptor with the number of firms which have declared this to be their modus operandi: 35% manufacturing and 31% services. given the relatively immature and unsophisticated verdict of easy gathering (g1), task-driven attitude (a2), ad-hoc location (l1), simple technology support (ts1) and a dismissive it system (its1), it is quite difficult to understand how this could translate into a strategic user (u4) category. what is evident though, is that if this is indeed a true reflection of what the firms think they are doing, they are clearly carrying out this task with inadequate, incomplete and largely publicly available, secondary data, within an overarching day-to-day problem solving attitude. even 29% firms falling within the < €2 million turnover category believe that they are using ci output at the strategic level although there is an equal figure given for the more likely allocation of tactical user. the increase in the prevalence of u4 as a function of turnover is of particular interest, especially when viewed with the decline in u1 and u2. from this, it could be inferred that companies exhibit more u4 and less u2 or u3 characteristics as their turnover increases. as the number of employees increases, u2 also decreases but this is matched by an increase in u4. 21 the micro firms with <10 employees are firmly rooted in the u2 category. the over-arching, control question revealed a more balanced state of affairs with 24% stating that they used competitive information but didn’t seem to retain any knowledge from that for the next time (u1), just 6% agreeing that they have acted on data obtained too quickly in the past which has not always worked out for the best (u2), 44% stating that they used competitive information primarily for price change and promotional decisions (u3) and 26% who thought they were operating at the highest level by using competitive information to help build scenarios and answer “what if” type questions (u4). in assessing behaviour related to contribution of international trade to turnover, and the firms view of their market, this is a confused result which is potentially an illustration of random selection having been made in answering these questions. this further reinforces the suspicion of mis-guided confidence, or a degree of wishful thinking by respondents in trying to reconcile reality. the answers given to prior sections discussed here would seem to fit that hypothesis. for the purposes of this discussion however, the evidence would seem to suggest a relatively equal split between tactical (u3) and strategic users (u4). this comes with a health warning though, as it is essential to pay heed to the findings of other categories. this would suggest that the returns for this section should be regarded as delusional at worst, or ‘wishful thinking’ at best. barriers to effective ci practice, is and it adoption this section was left open for respondents to reveal their true feelings. no pre-set options were offered but by employing the capabilities of the wellrespected qualitative analysis software, nvivo, four main themes emerged. the most commonly cited reasons for poor engagement with ci and it adoption was outdated, misleading, hard to find data. some respondents lamented the lack of information on company websites, not knowing where to look for information, insufficient externally produced sector reports, not being able to distinguish between quality and useless information. this epitomises a weak approach which focuses on secondary data only and makes no attempt to create or identify unique information from its own knowledge base. given the overwhelming prominence of easy gathering (g1) practices identified within this sample, it is not surprising that their perception of quality is skewed. the second largest category was inadequate financial resources. this confirms the task driven attitude (a1), simple technology support (ts1) and dismissive it system (its1) verdicts presented earlier. no organisational learning is happening within these firms and they lurch from one crisis to another, re-inventing the wheel and eschewing the development of an in-house capability. for smes this needs not be an all-singing, all-dancing dedicated ci unit or a bespoke it system, rather the nurturing of a volunteer employee who wish to take on the task of developing ci practice from the ground up. this is how ci develops in most firms, large or small, but particular in smes facing budget and resource constraints (huggins & weir, 2012). to sit back and continually complain that there are insufficient funds to even think about ci is a convenient excuse, rather than a valid reason for inaction. the question which owner managers must address is not “what will it cost the business now if we engage with ci and technology support?”, but “what might the cost be for the future of the business if we do not?”. this tends to focus the mind somewhat. the third major grouping was insufficient expertise in ci/poor quality staff. these are all problems which can easily be solved by recruiting the right type of staff who are willing to engage with the firm’s long-term goals and also have an interest in developing intelligence-based competitive advantage for the firm. it is easy to think of this sample as being predominantly from the micro segment. a review of table 2 however, shows that the majority fall into the small and medium categories, producing between €10 and €50 million turnover, employing between 10 and 250 staff, deriving a significant percentage of their turnover from international activities and carrying out their business in either local and global or purely global markets. these are not one or two person hairdressing salons or sandwich bars. they are fully fledged, commercial entities, operating in 22 seriously competitive sectors such as construction, energy, consumer goods, healthcare, high technology, manufacturing, information technology, packaging, textiles, marine, chemical processing, publishing industry, electronics and veterinary pharmacy. to cite lack of experience and poor quality of staff would again, seem to be an excuse for inaction rather than a genuine reason for non-engagement. insufficient expertise in ci or the lack of understanding of how it and is can support ci practice is purely a knowledge gap within the current set-up of a firm. it can be solved by either a training programme for a wiling employee or the hiring of one who already has that skill set. the final, and perhaps most revealing category of perceived barriers cited was managerial ignorance of ci and narrow-mindedness. respondents complained that ci was not seen as a systematic need, data was not consolidated or shared, there was poor communication or simple laziness on the part of owner-managers. these are more deep rooted issues of managerial style and culture which cannot be solved quite so easily. it is perhaps indicative of the commonly seen symptom of owner/manager ego-centrism (waylyshyn, 2012; white et al., 2012), bordering on arrogance, of immunity from anything which will derail the firm. it is precisely this type of firm which would benefit the most from the systematic adoption of ci practice and some, not necessarily high level, investment in it and is support to secure a less haphazard approach to business. that said, if the attitude is so entrenched, it is perhaps impossible to alter without a sea-change of personnel at the top of the firm. what can be confidently predicted is that those within the firm who have identified the need for ci, it and is adoption but have yet to see any hint of implementation, will move on and take their interest and skills elsewhere, most likely to a competitor. conclusions the overwhelming conclusion which can be drawn from this sample of turkish smes is that they are not innovators, they are, at best, followers. no investment is being made into future competitiveness with the focus being a reliance on the memory of a few people with no attention being paid to how that knowledge is retained by the firm. an active approach to ci, is and it seeks to secure that intangible asset of knowledge for future use. this helps to protect the firm against the consequences of a particularly knowledgeable individual leaving or retiring, or worse, a team of skilled specialists taking their expertise to a known competitor or a new entrant. at some point, firms which rely solely on memory and people for competitive advantage rather than processes and procedures will realise that without the latter, the former can, and probably will, walk out of the door and most likely join the staff of a competitor. succession planning is not about who will have who’s office when they retire, it is about ensuring that knowledge obtained by the firm, stays in the firm, for all time. the task-driven attitude means that these firms are only concerned about short term results and output. they are not pro-active, have little idea what is going on around them and are far from future driven. little evidence exists which would suggest there is any realisation of the need to invest in physical, human or technological resources to inform or increase competitive behaviour. this is difficult to reconcile given the current and increasingly worsening, turbulent nature of western economies. this is precisely the time when firms should be making such investments in order to prepare for the future. it can be summed up by one of the comments in the free text section of the survey which recorded “all the answers given above are for the period before the [economic] crisis. now we, including all the competitors, are in a huge mess”. this is what happens with a dismissive, immune, laissez-faire attitude and no real intent to stay competitive. each of these strands are connected. if improvements can be implemented in one, there will be improvements in another. a change in attitude leads to better gathering, better gathering leads to a known location and better co-ordination. better co-ordination informs the specification and needs from technology support which in turn enables the most appropriate it systems to be deployed in pursuit of ci excellence. this leads to better and more appropriate use of derived information by the firm in its decision-making process. it also identifies knowledge gaps which in turn drives intelligence needs analyses and prevents the firm from using analytical tools incorrectly. 23 finally, with all of the above in place, the firm can benefit from a stronger and more skilled use of the intelligence it obtains which leads directly to the attainment of the most desirable feature any firm could wish to hold exclusively, that of intelligencebased competitive advantage (ibca). the role of national sme business support networks are ideally placed to kick-start such a programme , not only in turkey but elsewhere across europe. the highly regarded chamber of commerce & industry programmes of accelerating ci proficiency among their sme community in france (smith et al., 2012) as well as similar programmes in belgium (larivet & brouard, 2012) and portugal (franco et al., (2011) are exemplars which could usefully be imported to turkey. ultimately, the onus rests with the owner/managers of smaller firms, or the executive teams of the larger firms to address any organisational, attitudinal and managerial style issues which are preventing their firms from capitalising from this type of activity, one which is increasingly more commonplace in their larger, domestic and overseas competitors (guimaraes, 2011; kaya & patton, 2011; nair & selover, 2012; tsai et al, (2011). further work as a small scale exploratory study, this work satisfies the requirements of such an approach. whilst some statistical tests were performed on this data, it very soon became clear that these would be provide further illumination beyond the descriptive statistics which are presented in this paper. where there was any correlation it proved to be statistically insignificant and as such, discarded. that said, there is always the scope for a larger, more substantial study to be undertaken which would perhaps enable the greater use of statistical methods which might reveal greater correlation between variables than has been possible here. this might be required were there any likelihood of public funds being spent on accelerating the ci proficiency of any sme community but more importantly, any country embarking on this for the first time that said, the evidence presented here has the potential to be regarded as base-line data for industry wide or sector specific comparative studies. the progressive nature of the typology framework would also lend itself very well to a longitudinal study which would identify at which point, and as a consequence of precisely which characteristics of attitude and behavioural changes, that an sme progresses, or regresses, from one category to another. it is hoped that this study might inform the design of future, preferably larger-scale studies, and provide guidance for european support agencies when attempting to derive best value for money for their efforts and to identify the potential, beneficial impact for those firms receiving their services. acknowledgements the authors wish to thank both mr mete meleksoy, general secretary of the istanbul sanayi odasi (istanbul chamber of industry), and mrs fugen camlidere, general secretary of kadir has university, without whom our research would not have been possible. we would also like to thank dr dawn coleby, university of leicester for her wise advice related to statistical significance. references adidam, p.t., gajre, s., kejriwal, s., 2009. crosscultural competitive intelligence strategies. marketing intelligence & planning. 27 (5), 666680. afolabi, b.s., 2007. la conception et l’adaptation de la structure d’un système d’intelligence economique par l’observation des comportements de l’utilisateur. doctor 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(2021) la veille stratégique entre l'efficacité décisionnelle et l’optimisation de la gouvernance : etude restreinte dans les organismes publics tunisiens. journal of intelligence studies in business. 11 (1) 57-68. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 1 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index la veille stratégique entre l'efficacité décisionnelle et l’optimisation de la gouvernance : etude restreinte dans les organismes publics tunisiens mostapha tayeb ben amora,* and fatma chichtia ahigher institute of accounting and business administration/institut supérieur de comptabilité et d'administration des entreprises (iscae) manouba, tunisia; *mbenamor967@gmail.com journal of intelligence studies in business please scroll down for article la veille stratégique entre l'efficacité décisionnelle et l’optimisation de la gouvernance : etude restreinte dans les organismes publics tunisiens mostapha tayeb ben amora,* and fatma chichtia ahigher institute of accounting and business administration/institut supérieur de comptabilité et d'administration des entreprises (iscae) manouba, tunisia *corresponding author: mbenamor967@gmail.com received 9 june 2020 accepted 26 october 2020 abstract (english) in this article, we highlight the role of strategic watch in a perspective of decision-making efficiency for a better optimization of governance, and this within the framework of a limited study on five (5) tunisian public organisms. an exploratory study was carried out through five semi-structured interviews. the results revealed that the use of watch practices is essential for internal knowledge sharing, transparency and administrative openness. a new frame work that tends to improve the decision-making system. it also allows the decision-maker to move from a state of self-satisfaction to a situation of acceptance of his decision by his environment in a climate of optimal governance. keywords decision, efficiency, optimal governance, public organism, strategic watch résumé (française) dans cet article, nous valorisons le rôle de la veille stratégique dans une optique d’efficacité décisionnelle pour une meilleure optimisation de la gouvernance, et ce dans le cadre d’une étude restreinte sur cinq (5) organismes publics tunisiens. une étude de type exploratoire a été menée à travers cinq entretiens semi-directifs. les résultats ont révélé que l’utilisation des pratiques de veille est indispensable au partage interne de la connaissance, à la transparence et à l’ouverture administrative. un nouveau cadre de travail qui tend vers une amélioration du système décisionnel. elle permet également le passage du décideur d’un état d’autosatisfaction à une situation d’acceptation de sa décision par son environnement dans un climat de gouvernance optimale. mots clés décision, efficacité, gouvernance optimale, organisme public, veille stratégique 1. introduction la survie de toute organisation dépend de ses "choix" (bérard, 2009), et la prise d'une décision est nécessaire aussi bien dans la sphère privée que dans la sphère publique, où le problème revêt une importance capitale dans la mesure où les décisions affectent directement la vie présente et future des citoyens. la prise de décision dans ce secteur est donc étroitement liée aux valeurs qui régissent le service public et se situe au cœur de la notion d’intérêt général. donc, l'enjeu parait fondamental aujourd'hui dans la mesure où l'administration publique est interpellée par de nouveaux défis liés à la compétitivité et à l’opinion publique. par suite, notre problématique est la suivante : "dans quelle mesure les pratiques de la veille stratégique journal of intelligence studies in business vol. 11, no. 1 (2021) pp. 57-68 open access: freely available at: https://ojs.hh.se/ 58 utilisées dans l'organisation publique tunisienne peuvent améliorer l'efficacité de ses décisions et l’optimisation de sa gouvernance?". de notre problématique principale se déclinent trois questions hypothétiques de recherche: quelles sont les pratiques de la veille stratégique dans les organisations publiques tunisiennes ? comment les organisations publiques tunisiennes élaborent-elles leurs décisions pour une optimisation de leur gouvernance ? quels sont les impacts des pratiques de veille stratégique pour une efficacité de la décision et une optimisation de la gouvernance? pour répondre à ces questions nous avons choisi le paradigme interprétatif qui se base sur l’interprétation de la réalité organisationnelle pour comprendre l’objet de la connaissance étudiée. sur la base de ce paradigme nous avons eu recours à une démarche qualitative de type inductive (miles et huberman, 2003) dont l'unité d'analyse est « une décision administrative efficace ». ce papier est scindé en trois parties : la première revient sur les soubassements théoriques en rapport avec notre problématique, la seconde est réservée au cadre pratique de la recherche, et enfin la troisième est destinée à la présentation et la discussion des résultats. 2. cadre theorique : la bonne gouvernance et l’efficacite de la decision : apport des pratiques de veille strategique a travers les pratiques de la veille stratégique, nous évoquons précisément l’analyse et la compréhension de ce monde organisationnel. cette première partie théorique traitera l’apport des pratiques de veille stratégique au niveau de la bonne gouvernance, et de l’efficacité décisionnelle dans le secteur public. 2.1 les pratiques de veille stratégique dans le secteur public en se basant sur un processus de veille et une information stratégique à forte valeur ajoutée au profit de la pérennité de l’organisation, de sa performance et de ses compétences. nous pouvons obtenir généralement une décision efficace et une bonne gouvernance. par conséquent la qualité de l’information est associée à la notion de la veille. 2.1.1 la qualité de l’information selon bourzigui (2018), la qualité de l’information a une dimension cognitive et comportementale, elle mène à la couverture des différentes préoccupations des parties prenantes, un champ de gouvernance élargi au niveau des pratiques de veille stratégique. dans ce cadre, la transparence administrative peut soutenir la bonne gouvernance, vu que l’administration ne peut plus continuer à se cacher derrière le secret administratif (lasserre et al, 1987). le partage de l’information au sein d’une administration ouverte permet aux parties prenantes de participer de façon indirecte à la prise de décision et par suite d’atteindre l’efficacité décisionnelle et l’optimisation de la gouvernance. 2.1.2 la notion de la veille la veille stratégique est une démarche ou processus cohérent qui peut mener à une aide à la prise de décision. etudier cet outil décisionnel revient à s’arrêter sur l’objet de la veille comme étant un concept et un processus d’une part, et d’autre part, comme étant un soutien décisionnel. la veille stratégique est une notion qui peut être analysée théoriquement à la fois en tant que concept (un outil de surveillance environnemental) et en tant que processus (un cycle continu d’opérations). en effet, dans un monde organisationnel caractérisé par l’incertitude et la turbulence où l’information et la connaissance représentent des avantages concurrentiels, l’administration qui pratique le processus de veille peut améliorer ses services et anticiper les changements pouvant impacter leur activités (drevon et al, 2018 ; chichti et al 2019). 2.2 l’efficacité décisionnelle et l’optimisation de la gouvernance en général, l'étude de l'efficacité de la prise de décision passe par l'analyse de l’optimisation de la gouvernance en plus de l’analyse de la relation entre le processus décisionnel (un ensemble de séances d’évènements développés) et les facteurs qui peuvent impacter d’une façon déterminante son efficacité (bérard, 2009). 2.2.1 optimisation de la gouvernance l’organisation des pratiques de veille stratégique, fait partie de la gouvernance de l’administration publique. en d’autres termes 59 la gouvernance des données et informations collectées constitue le fondement empirique de la gouvernance optimale de cette administration. c'est-à-dire une sorte d’amélioration de la gestion des connaissances comme étant un résultat d’intelligence et source de nouvelles compétences d’anticipation et d’innovation (chichti et al, 2019). ainsi la cellule de veille est le fil conducteur transverse de la gouvernance du patrimoine organisationnel, y compris le patrimoine informationnel, et mérite donc d’être rattachée directement à la direction générale (au décideur). par conséquent la finalité serait une optimisation de la décision par la bonne personne au bon moment (madhar, 2016 ; ayadi et al, 2019). généralement, cette gouvernance est définie comme partage du pouvoir entre différents acteurs. une sorte de transparence informationnelle, d’équilibre et de contrôle (bourzigui et al, 2018). vu sa situation économique difficile, l’etat tunisien a développé ses organisations publiques vers la prise de la décision optimale en favorisant les pratiques de recherche de l’information pertinente pour une meilleure prise de décision (chichi et al, 2019). 2.2.2 l’efficacité de la prise de décision de ce fait, les définitions proposées à la "décision" peuvent être d'un ordre économique, philosophique et psychologique. la définition économique identifie la décision comme un choix, et une réponse à un problème. la définition philosophique fait de la décision un acte positif, volontaire ou un choix optimal et la définition psychologique traite la décision comme un jugement, ou un engagement de responsabilité personnelle. la science managériale traite la décision comme un comportement, et finalement la veille stratégique conceptualise la décision comme un "extrant" (brouard, 2007, p.17). cependant la prise de décision peut être influencée par certains facteurs de natures différentes déterminées théoriquement : l’information, l’expérience du décideur et le contexte social. l'information : l’information est un ensemble de données qui constituent l’essence de la veille stratégique et aide à choisir la bonne solution (bergeron et al 2009). elle permet une meilleure compréhension des contraintes environnementales (mason, 1984 ; arnaud, 2016). l'expérience du décideur : certains auteurs annoncent la nécessité de la mobilisation de l'expérience et de l'intuition de la part du décideur pour être à la fois rapide et efficace (klein et al, 2014). plus profondément et selon dane et pratt (2007) l'intuition du décideur est un processus à part entière, qualifié de traitement de l'information disponible. en théorie du management stratégique, le rôle du décideur est conçu comme dynamique et changeant. c’est pourquoi la qualité du décideur consiste à aider le groupe et les organisations publiques à gérer la complexité croissante focalisée sur les changements environnementaux incessants (maltais et al, 2007). le contexte social : dans un contexte social, la décision n'est plus le fruit d'un calcul arithmétique, mais plutôt le résultat des forces institutionnelles. ce qui fait que la décision ne se présente pas comme la plus satisfaisante au niveau économique, mais la plus acceptée au niveau de son contexte social (olivier, 1997 ; scott, 2014). 2.2.3 la bonne gouvernance : « the corporate gouvernance » la gouvernance est généralement le partage du pouvoir entre les différents acteurs de l’organisation et entre l’organisation et toutes les parties prenantes. les maitres mots de la gouvernance sont la transparence, le contrôle, l’équilibre ou encore la responsabilité. une sorte de management démocratique et d’un système administratif de cadrage et de coordination interne et externe entre les acteurs (aryal, 2020). en théorie, la gouvernance a un impact positif sur la performance organisationnelle (bourzigui et al, 2018), vu qu'elle a une incidence sur l'administration publique en modifiant l'environnement dans lequel le service public agit tout en introduisant de nouveaux concepts et de nouvelles méthodes (brown, 2005). 2.3 impacts des pratiques de veille stratégique : efficacité décisionnelle et optimisation de la gouvernance l’analyse de l’impact de ce système d’efficacité et d’optimisation nécessite l’étude de la veille 60 stratégique à la fois comme un soutien décisionnel et comme une source d’efficacité (libaert, 2018). 2.3.1 la veille en tant que soutien décisionnel la veille stratégique est un processus de soutien pour la prise de décision fondé sur trois perspectives : la réduction de l'incertitude, la détection des signaux faibles et la légitimation des décisions. la réduction de l'incertitude : généralement, pratiquer la veille est une sorte d’attention et de vigilance permanente et ponctuelle. ce dispositif de veille constitué par une installation matérielle et personnelle de la démarche peut être mis en œuvre d’une façon manuelle (journaux, réseau humain), ou par mot clé dans des moteurs de recherche liés à des alertes sur internet, et en utilisant des logiciels de veille intelligente fondées sur un processus automatique. ce processus aide à réduire l'incertitude causée par un manque d'informations (daft et al, 2007). en particulier, des chercheurs ont annoncé le lien de corrélation entre le degré d'incertitude et les différentes pratiques de veille (auster et choo, 1994 ; patora wysocka, 2017). la détection des signaux faibles : la veille stratégique est un processus d'aide à la détection des "signaux faibles". ces derniers constituent les "micro-changements" qui se trouvent en "périphérie" de ce sur quoi le décideur est concentré (shoemaker et al, 2013).cet effort de détection fait partie de la détection de l'information de source humaine (el-akrouchi, 2015). elle permet ainsi de suivre les évolutions environnementales (lesca, 2011), une situation qui mène nécessairement à un enrichissement au niveau des connaissances de l'environnement de prise de décision. légitimer la décision :la veille stratégique est un processus qui permet de légitimer les décisions déjà prises. c'est-à-dire le décideur peut demander une information complémentaire pour légitimer sa décision (feldman, 1981). ainsi dans les régimes organisationnels bureaucratiques l'effort de collecte de l'information se focalise sur l'objectif de légitimer le "décideur", une chance de soutien "en aval". dans le secteur public, légitimer la décision administrative est une action quotidienne de l’agent public au titre de leader, généralement élu par voie démocratique. cette interaction entre ce qui est du système politique et celui du système administratif (politico-administratif) est complexe même dans les régimes démocratiques (maltais et al, 2007). en effet, dans l’organisation publique tunisienne les pratiques d’analyse sont focalisées sur la validation des actions administratives avec l’adaptation des choix selon les attentes de l’opinion publique. une démarche humaine pour valoriser et mettre en œuvre ces choix au sein de l’administration. 2.3.2 la veille en tant que source d'efficacité l'efficacité de la veille impacte positivement la performance de l'organisation. depuis la fin du siècle dernier les études ont démontré que la mise en œuvre d'un processus de veille stratégique est un centre de profit et non un centre de coût (roulet et al, 2015). dans cet figure 1 positionnement hiérarchique de l'administration publique tunisienne. 61 ordre d’idées, cohen (2004) a annoncé le phénomène « cause à effet » entre la veille efficace et la qualité de la prise de décision. mesurer l'efficacité de la veille stratégique, c'est mesurer le degré d'atteindre les objectifs, c'est-à-dire comparer les résultats attendus avec les résultats réalisés (roulet et al, 2015). l'objectif fondamental du processus de veille stratégique étant l'aide à la décision. 3. cadre pratique de la recherche l’administration tunisienne : un contexte spécifique de recherche dans l’objectif d’apporter une réponse à notre problématique, nous proposons d'explorer les pratiques de veille favorables à la prise de décision (pour la bonne gouvernance), et relatives au contexte administratif tunisien, et ce pour comprendre la relation entre le processus de veille stratégique et l'efficacité de la décision, vers une optimisation de la gouvernance dans un cadre administratif spécifique suite à une analyse qualitative et à travers cinq organismes publics choisis : une agence nationale, un observatoire, une entreprise publique, et deux écoles nationales. 3.1 cadre de la recherche : l’organisation publique tunisienne l’organisation publique tunisienne est un contexte particulier (jaziri et al, 2018 ; hizaoui, 2020). elle est organisée, structurée, hiérarchisée et, contrôlée par des fonctions qui s'exercent dans un cadre juridique et constitutionnel (cf. figure 1). elle fonctionne d'une part sous tutelle gouvernementale et présidentielle et d'autre part sous contrôle parlementaire, juridictionnel et institutionnel. l’objet de ce travail de recherche est d’étudier le rôle de la veille stratégique entre l’efficacité décisionnelle et l’optimisation de la gouvernance dans un contexte d’organisation publique. en fait, l’administration est la concrétisation majeure de l’etat, les fonctions de l’administration réalisent cet etat, maintenir l’ordre, assurer la prestation des services, informer, prévoir et surtout préparer les décisions étatiques. nous distinguons entre la décision gouvernementale (décision finale de l’orientation de l’action de l’etat) et la décision administrative (la décision exécutoire de l’orientation finale). les manifestations entre le 17 décembre 2010 et le 14 janvier 2011 ont prouvé que le corps administratif tunisien est en bonne santé. le secret du succès des organisations publiques tunisiennes mérite d'être étudié, surtout en relation avec le thème de l'efficacité processuelle et décisionnelle. 3.2 cadre méthodologique : approche qualitative exploratoire une approche qualitative exploratoire a été choisie. cette étude est utile lorsqu’on veut comprendre un phénomène (el wafi 2017). notre objectif de départ était de comprendre, à partir du point de vue de certains agents publics, la relation entre le succès des pratiques de veille stratégique et l’optimisation de la gouvernance au sein de l’administration publique tunisienne. nous avons interviewé cinq (5) agents publics responsables de veille stratégique ou d’un projet de mise en place de cette activité. dans les recherches qualitatives, la proposition ne provient pas uniquement de la « connaissance théorique ». ce qui explique les démarches suivantes : une démarche à deux temps : les entretiens ont été menés en deux temps. dans un premier temps nous avons procédé de manière informelle, libre, sans guide d’entretien préalable. cette étape était importante puisqu’elle nous a permis d’apporter des éclaircissements sur la manière dont les individus traduisent le rôle de la veille stratégique, elle nous a facilité la formulation des questions, à partir de la revue de la littérature dans le guide d’entretien, qui a été utilisé en deuxième temps. la phase formelle est fondée sur une série de cinq entretiens semi-directifs. la durée moyenne de nos entretiens était de 55 mn et variait entre 45 et 75 mn. deux démarches d’analyses : une analyse thématique manuelle, selon couvreur et al 2002(cité par el wafi, 2017 p.93),c’est la méthode d’analyse la plus souvent utilisée en sciences de gestion. pour étudier les différents thèmes nous avons retenu les portions de phrases, les phrases ou les groupes de phrases (thietart et al 1999). une analyse lexico-métrique dans l’objectif de valider la communication interne des entretiens (perret et al, 2012), nous avons opté pour un « recours à un outil informatique » (miles et huberman, 2003, p.88),par conséquent, à un logiciel d’analyse: « iramuteq » pour faire référence à une analyse métrique conduite sur le texte global de cinq entretiens (ratinaud et al, 2009). ce 62 texte a été formaté pour pouvoir être lu par le logiciel (iramuteq version 0.7 alpha 2). c'està-dire la suppression des numéros et des titres. l’analyse globale a été effectuée sur la base statistique et de nuage conceptuel. 4. resultats et discussion cette section est consacrée à l’analyse des différents résultats et ensuite à la discussion multidimensionnelle de ces résultats. 4.1 principaux résultats dans ce cadre nous allons présenter les principaux résultats à travers une analyse thématique et manuelle de chaque entretien séparément et à travers une analyse lexicométrique du corpus qui englobe le texte de tous les entretiens. 4.1.1 analyse thématique des entretiens pour analyser les entretiens nous allons présenter nos résultats à travers la classification thématique des verbatim de chaque entretien, puis nous allons recourir à l’interprétation thématique manuelle. à partir du texte original de chaque entretien nous avons extrait des passages liés à notre problématique appelés « verbatim ». selon le dictionnaire français « internaute », un verbatim est un vocabulaire et expression utilisée par une population qui s'adresse à une entreprise, à l'occasion d'une enquête. ces « verbatim » ont été catégorisés pour réduire le nombre d’informations (wacheux, 1996) et pour permettre la classification des entretiens par thème (t). les pratiques de la veille stratégique (vs) au sein de l’administration publique tunisienne : nos interlocuteurs ont mentionné que l’information environnementale est cruciale pour mettre en œuvre une activité de veille stratégique. cette information est nécessairement pertinente dans un cadre administratif officiel, le champ d’application est vaste et couvre plusieurs rubriques d’interventions informationnelles : de l’opinion publique et de la vie quotidienne des tunisiens (la question politique, la réalité économique, la situation sociale …). dans ce cadre de la nature multidimensionnelle du processus de vs, l’interlocuteur de l’organisation publique ax1 (directeur, 2 ans d’expérience, santé publique) a qualifié les pratiques de la vs comme étant une « veille informationnelle » puisque dans son service « les pratiques de veille stratégique sont fondées principalement sur la collecte des informations pertinentes ».face à cette estimation ouverte, l’interlocuteur de l’administration ax4 (directeur central, formateur) a réclamé que son service a thématisé le champ d’activité de la veille stratégique après avoir « convertir les rubriques de méthode d’analyse pestel en veille stratégique » (veille politique, veille économique, veille sociétale, veille technologique, veille écologique et veille législative). cependant, l’interviewé relatif à l’administration ax5 (directeur, formateur) a limité l’activité de son service dans la pratique de la veille « documentaire ou bibliothèque ». la veille stratégique est un outil d’aide à la décision :au niveau administratif, selon nos interlocuteurs, la décision ne sera efficace que lorsqu’ elle a été prise au bon moment, cette valeur est mesurée généralement par sa nature préventive et anticipative. ainsi, il est important de signaler que la totalité des interlocuteurs ont accordé un intérêt majeur à la veille stratégique, en liaison avec le processus de prise de la décision administrative en tant que source d’efficacité décisionnelle. l’interviewé e.ax1 a insisté que grâce au processus de veille stratégique son administration peut « prendre les décisions stratégiques efficaces au bon moment ». l’interviewé e.ax3, a été plus précis en disant que « …la veille stratégique est un facteur essentiel d’aide à la décision… ». plus profondément et pour l’interviewé e.ax4 la veille stratégique est un outil d’aide à la décision « …très efficace puisqu’elle mène à soutenir la décision de qualité efficace, fondée sur des informations pertinentes… un outil efficace, à l’écoute de l’environnement et à la détection des signaux faibles chez les acteurs… ». enfin, selon l’interviewé e.ax5 pour prendre la bonne décision et être dans la bonne voie « il faut instaurer la veille stratégique, comme outil efficace de soutien à la prise de décision au sein du secteur public ». la veille stratégique est un facteur de succès de la gouvernance : au niveau de ce thème, nos interlocuteurs ont valorisé le rôle de la veille stratégique comme facteur de succès de la gouvernance. pour l’interviewé e.ax1, les pratiques de la veille stratégique sont « un facteur de succès de la gouvernance puisque les 63 résultats n’ont aucun sens s’ils sont mal exploités par l’administration ». de même l’interviewé e.ax3 a qualifié ce rôle comme évident et a insisté que la veille stratégique est « un facteur de succès de la gouvernance, elle est fondée sur la gestion en transparence, correctement et en toute clarté ».en d’autres termes selon le même interlocuteur, la gouvernance est un « système d’information ». ce dernier, a évoqué que la gouvernance se base sur un système d’information par l’introduction de la technologie informatique et de communication (tic) c'est-à-dire cette intervention technologique est à la fois « une dimension principale de la gouvernance » et une voie prospective vers une situation meilleure à savoir la gouvernance électronique ou l’egouvernance. de façon plus claire, l’interviewé e.ax4 a considéré que la veille stratégique n’est pas seulement un facteur de succès de la gouvernance puisqu’elle permet « la participation indirecte de l’environnement aux choix stratégiques et à la prise de décision », mais elle permet en plus de « détecter l’avis de l’opinion publique ». l’interviewé e.ax5 a été plus précis lorsqu’il a soutenu l’idée que la veille stratégique donne « la chance à la participation et à rendre service d’une façon équitable et juste à temps ». il s’agit donc et selon cet agent public d’une question d’« ouverture » et de « transparence ». autrement dit, un contexte administratif dans un cadre de travail coopératif, ouvert et participatif, peut favoriser une participation indirecte des parties prenantes à la prise de la décision administrative efficace. un environnement soutenu par un climat de stabilité gouvernance optimale. le rôle de la veille stratégique dans les préoccupations des parties prenantes : dans ce cadre environnemental, la totalité des interlocuteurs ont reconnu le rôle à la fois important et déterminant de la veille stratégique dans les préoccupations des parties prenantes. pour l’interviewé e.ax1 le rôle est « important » c’est pourquoi les parties prenantes (les médecins par exemple) jouissent d’une priorité au niveau de la communication avec l’administration (ax1) ou au niveau de l’accès libre à l’information détenue par la cellule de veille. l’interaction « administration – citoyen » est ouverte et offre selon l’interviewé e.ax2 des réponses et des informations « sans limites bureaucratiques ». ainsi, d’après cet agent administratif « l’interaction constitue un acte de gouvernance » (en 2019 la cellule de veille a compté 188 milles interactions entre ax1 et les citoyens). d’après l’interlocuteur relatif à l’administration ax3, les parties prenantes peuvent à la fois influencer ou être influencées par « l’activité de la cellule de veille », plus précisément, et le plus important dans ce facteur que la situation stable n’est que « la conséquence que ce monde extérieur fait partie de notre préoccupation ». grâce à cette stabilité et selon l’interviewé e.ax4 on peut « éviter le phénomène de conflit ou de résistance au sein de l’administration publique » tunisienne. les retombées de la veille stratégique sur le fonctionnement interne de l’administration publique : il est unanimement reconnu par nos interviewés que les pratiques de veille stratégique jouent un rôle dans le fonctionnement interne de l’administration publique. pour l’interviewé e.ax1, ce rôle consiste au « partage total de toute sorte d’information de façon ponctuelle et à l’instant même, un partage qui se fait de façon automatique ». pour l’interviewée.ax2, la veille stratégique « a des retombées positives sur le fonctionnement de notre organisation et ce au niveau de la coordination, la collaboration et la coopération entre les différents services ». cet outil « peut aider aux partages des connaissances et informations pertinentes », il offre également « un terrain favorable à la prise de décision collective au profit de l’administration interne de l’école ». ces retombées ont été qualifiées encore positivement puisque l’interviewé e.ax5 a justifié cet aspect positif par « l’amélioration de la coordination entre les différents départements aussi bien au niveau hiérarchique qu’au niveau horizontal ». une « occasion » pour le partage des « connaissances ». la veille stratégique est une activité ponctuelle ou continue : nos interlocuteurs ont mentionné que la veille stratégique émane d’une volonté stratégique et que ce processus est une activité continue et non ponctuelle. pour l’interviewé e.ax1 la veille stratégique est une « activité quotidienne depuis des années … une action continue ». dans une vision plus large l’interviewé e.ax3 a reconnu que la veille stratégique est « fondée sur une volonté stratégique … elle fait partie de la politique interne de l’administration centrale … cette activité devient un investissement important, 64 un système d’information à part entier dans l’organisation publique ». plus précisément et pour les deux interviewés e.ax4 et e.ax5 la veille stratégique émane successivement de la « volonté stratégique rattachée à la direction » et dépend « de la conviction des grands chefs ». 4.1.2 analyse lexico-métrique : tentative de validation communicationnelle analyse statistique la capture d’écran suivante de la façade du logiciel est le résultat de l’analyse lexico métrique (discours) qui additionne les 5 entretiens à la fois : ces résultats distinguent 2856 occurrences (mots) dont 638 formes actives (mots les plus utilisés) 324 hapax (mot qui ne se répète qu’une seule fois dans l’un des 5 entretiens) et 1894 formes supplémentaires (des mots de liaison : le, la, de, et ...). ainsi, notre tentative de validation de la communication interne des participants sera focalisée seulement sur la catégorie des formes actives. la forme active lemmatisée d’effectif maximum, est la forme « veille » avec 44 formes actives, puis viennent les formes « stratégique » de 41 formes, organisation de 26 formes, information de 23 formes et décision de 20 formes. cette hiérarchisation fréquentielle des formes actives est une caractéristique de tous les cinq entretiens. un signe d’appartenance collective à l’objet d’étude et à la perception administrative cohérente de la problématique au sein de l’administration publique tunisienne. la liste suivante récapitule les valeurs de la communication interne des 5 entretiens successivement désignés face à la fréquence (f) de certaines formes actives (mots clés omniprésentes dans les cinq entretiens par fréquences différentes) : stratégique : f = 41 (4+6+10+13+8) organisation : f = 26 (8+7+6+3+2) information : f = 23 (8+6+6+2+1) décision : f = 20 (3+5+2+6+4) public : f = 16 (4+2+2+6+2) aide / aider : f = 13 (4+3+3+2+1) gouvernance : f = 11 (1+1+5+3+1) interne : f = 10 (2+1+3+3+1) environnement f = 10 (1+3+3+2+1) continuer : f = 07 (1+1+1+1+3) suite à cette logique administrative mentionnée, notre tentative de validation communicationnelle est interne entre les participants. cette tentative peut être supportée par l’idée collective que la veille au sein de l’organisation publique tunisienne est une source d’information continue pour comprendre l’environnement organisationnel, et pour améliorer le fonctionnement interne de l’administration publique dans le but d’aider les responsables à prendre des décisions dans un climat de gouvernance. le nuage de mots (nuage conceptuel) le nuage de mots ou « word cloud » est une représentation graphique des mots clés les plus utilisés dans un texte (discours). ces mots se positionnent par nombre d’occurrences, ils s’affichent dans différentes tailles de caractères d’autant plus visibles. ce nuage est le résultat d’une analyse lexicale, visualisée par un graphique structuré et par des mots pertinents qui permettent de synthétiser les principaux thèmes. la figure suivante (cf figure 3)est une sorte de réduit sémantique d’un texte dans lequel les concepts clés sont composés d’une unité de taille selon le poids de typographie utilisé lui permettant de faire ressortir leur importance dans le texte. l’interprétation de ce graphique nous permet de constater l’ensemble conceptuel valorisé dans les cinq entretiens grâce à l’analyse métrique. c'est-à-dire pour comprendre le système de veille stratégique il suffit de valoriser les formes les plus visualisés selon leur tailles (veille stratégique, organisation, information, administration, décision, public, gouvernance, environnement …). on peut imaginer la réponse collective suivante : le rôle de la veille stratégique est la collecte de l’information pertinente pour comprendre l’environnement organisationnel dans le but de prendre des décisions au sein de l’administration dans un cadre de gouvernance. de cette manière on propose de schématiser le modèle empirique selon la figure suivante (cf figure 4). figure 2 résultat de l’analyse lexico métrique et statistique de la totalité des cinq entretiens. 65 4.2 discussion multidimensionnelle des résultats d’après la problématique évoquée en liaison avec le rôle de la veille stratégique au sein de certaines administrations publiques tunisiennes au niveau de l’efficacité décisionnel et l’optimisation de sa gouvernance. nous discuterons les résultats obtenus des réponses suivant les trois dimensions suivantes : dimension n° 1 : les pratiques de veille stratégique au niveau de la multi-dimensionnalité des pratiques de veille stratégique : le processus est qualifié par nos interviewés comme étant une veille informationnelle (source d’information pertinente et de partage de connaissance). il est également qualifié comme étant une conversion de la méthode d’analyse pestel, en pratique de veille stratégique. ces idées sont soutenues par certains travaux scientifiques (khenissi et al 2010 ; arnaud, 2016) qui ont mentionné que l’information est l’essence de la veille stratégique, elle mène à une compréhension parfaite de l’environnement et de ses contraintes. elle permet également de choisir la meilleure solution (patora 2017). dimension n° 2 : argumentations des pratiques de veille stratégique au niveau de l’utilité de la veille stratégique : elle est reconnue par nos interlocuteurs comme étant un outil d’aide à la décision et un soutien à la qualité efficace de cette décision présumée prise au bon moment. en d’autre terme, la veille est un outil qui permet de rester à l’écoute de son environnement organisationnel, et donc d’agir convenablement du point de vue décisionnel. une telle proposition est maintenue par la majorité des travaux scientifiques (dawson, 2001 ; lesca, 2001 ; daft et al, 2007 et pollanen et al, 2016 ; libaert, 2018). au niveau du rôle de la veille stratégique dans la gouvernance : pour nos interlocuteurs cette démarche est un facteur de succès et un moyen pour améliorer les tâches préventives, la bonne gestion et la transparence. c’est également un moyen de communication, et un système d’information à part entière. la revue de la littérature a valorisé ce rôle joué par la veille stratégique comme facteur de succès de la gouvernance (bourzigui et al, 2018 ; brown, 2005 et guechtouli et al, 2014 ; madhar 2016 ; ayadi 2019). de même une nouvelle dimension de la gouvernance électronique peut donner figure 3 nuage conceptuel du corpus de la totalité des cinq entretiens. figure 4 schématisation du modèle empirique. 66 naissance à une nouvelle conception de l’environnement du secteur public (brown, 2005). cette nouvelle vision environnementale doit être prise en compte par les grands chefs de l’administration publique. en effet, l’egouvernance à travers la veille stratégique mène à l’amélioration des services administratifs (chichti et al, 2019). au niveau des préoccupations des parties prenantes :les interlocuteurs ont insisté sur la priorité de l’interaction avec les composants de l’environnement qui jouent un rôle déterminant de stabilité organisationnelle. les travaux scientifiques reconnaissent que la veille stratégique donne un sens à l’environnement et une capacité administrative d’anticiper les crises et éviter le phénomène de résistance (brouard, 2007 ; arnaud, 2016 ; bergeron et al, 2009 ; lesca et al, 2011 et drevon et al, 2018 ; jaziri et al, 2018 ; hizaoui, 2020). dimension n° 3 : impact sur les leviers de l’efficacité administrative au niveau des retombées de la pratique de la veille stratégique sur le fonctionnement interne de l’administration publique : les agents administratifs interrogés ont insisté sur la dimension coopérative de ces retombées fondées sur la coordination et la collaboration entre les services administratifs. cependant, par une vision plus large certains auteurs ont qualifié la veille stratégique par un centre de profit et non de coût, un moyen de création collective de sens et une amélioration de la communication interne, une nouvelle vision théorique introduisant l’innovation entraîner par l’idée de « l’implication » des agents publics à la prise de décision (lesca, 2003 et roulet et al, 2015 ; aryal, 2020). au niveau de la réponse sur la question la veille stratégique est continue ou ponctuelle : les interviewés ont reconnu de façon unanime que cette activité doit être permanente, rattachée aux choix stratégiques, et doit faire partie de la politique interne de l’administration et même de la conviction des dirigeants. la réponse semble plus profonde au niveau théorique vu que certains auteurs ont qualifié la pratique de la veille stratégique par un système de suivi multidimensionnel (guechtouli et al, 2014 et drevon et al, 2018). en d’autres termes en management public nous devons reconnaitre que la qualité du décideur joue un rôle important à aider l’organisation à gérer la complexité environnementale, y compris (maltais et al, 2007) à mettre en œuvre un processus de veille stratégique. 5. conclusion generale la veille stratégique est une activité permettant d’offrir une information pertinente à la bonne personne, et au bon moment. c’est un outil de surveillance de l’environnement organisationnel, qui permet au décideur d’être à l’écoute, et d’anticiper le phénomène de résistance ou de changement radical. c’est à travers nos investigations de recherche dans notre contexte d’étude, en l’occurrence cet environnement des institutions publiques que nous avons décelé la pertinence de la problématique concernant le rôle des pratiques de veille stratégique dans les organisations publiques tunisiennes pour améliorer l’efficacité de leurs décisions et optimiser ainsi leurs gouvernances, et nous avons ainsi à travers cette étude cherché à donner des éléments de réponses à nos questionnements. au niveau du cadre théorique ce rôle parait multidimensionnel, la veille stratégique cherche à la fois à rendre la décision administrative efficace en tant qu’outil d’aide à la décision, comme elle cherche encore à rendre la gouvernance optimale au sein de l’administration publique. en d’autres termes, le fait d’introduire la démarche de veille stratégique au niveau du processus traditionnel de prise de décision, le décideur sera mené de passer de la situation satisfaisante à la situation d’acceptabilité de la décision par son environnement. c'est-à-dire que le climat de la gouvernance administrative n’est plus un sentiment d’autosatisfaction, mais plutôt un résultat d’acceptation de la décision par son environnement administratif. une situation qui peut entrainer la stabilité organisationnelle continue. dans ce cadre, suite à notre étude empirique focalisée sur la démarche qualitative et fondée sur l’analyse thématique manuelle en premier lieu et lexico-métrique en second lieu, nous avons ciblé toutes les données collectées via cinq entretiens semi-directifs. il est donc évident que l’information fournie depuis les pratiques de la veille stratégique est déterminante, non seulement au niveau de l’amélioration du partage interne de la 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scenario planning» technological forecasting and social change vol 80, n°4, 2013, p. 815-824 thietart r. a. et al., «les analyses thématiques adoptent comme unité d’analyse une portion de phrase, une phrase entière ou, un groupe de phrases» edition 199, 1999, 460 p. wacheux f., méthodes qualitatives et recherche en gestion, edition economica, paris, 1996. page 4 editors note vol 7 no 1 editor’s note vol 7, no 1 (2017) business intelligence, big data and theory again, the articles for this issue are mostly about the application of new technology and about business intelligence, reflecting a strong development in corporations. the only exception is the first article, which is purely theoretical. the contribution by søilen, entitled “when the social sciences are based in evolutionary theory: the example of geoeconomics and intelligence studies,” is a theoretical article. it argues for why it was wrong to make the study of physics the model for the new social sciences after the second world war. moreover, it describes how this was done for the study of economics and how new studies like geoeconomics and intelligence studies have an advantage in this sense, and that a fresh look at theory is easier in these cases. hughes, in his article “a new model for identifying emerging technologies,” argues for the relevance of the intelligence expert despite the increase in new complexities required for understanding an industry, but he also emphasizes the importance for the analyst to learn more about big data. our technological systems are still ineffective at knowing the relevant data sources and how to connect the data in meaningful ways to derive value for the firm, but their importance is increasing. the author proposes a new forecasting model that incorporates a combination of technology sequencing analysis and big data tools within the organization while also leveraging experts from across the open innovation spectrum. salguero et al., in the article “proposal of an assessment scale in competitive intelligence applied to touristic sector,” present a mathematical ci model to be applied in the tourism sector, specifically for hotels. the model is also tested and fine-tuned, proving to have value for the ci function. the authors also present an extensive literature review. the extensive article by garcía and pinzón, “key success factors to business intelligence solutions implementation,” builds on previous literature published in this journal, such as cidrin and adamala (2011) and takes as a starting point the high number of bi projects that fail. the authors identify 13 factors that affect business intelligence solution success. the final article, by papachristodoulou et al., “business intelligence and smes: bridging the gap,” talks at great length about the problem of implementing bi in small and medium enterprises (smes). it shows how new products have changed to adapt to a new sector of customers. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2017 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 7, no 1 (2017) p. 4 open access: freely available at: https://ojs.hh.se/ 26 o p i n i o n s e c t i o n competitive intelligence cycle in the light of web 2.0 tools luc quoniam 1 and charles-victor boutet 2 1 laboratoire paragraphe, université paris viii, france 2 ufr ingémedia, ustv, france email: mail@quoniam.info, mnem00@gmail.com received september 3 2013, accepted february 9, 2014 abstract: we propose in this study, detailing our observations and research on the impact of the web 2.0, its associated tools, the cycle of the economic intelligence with new paradigms such as the many-to-many, new practices such as active seo allow any individual, firm, to impact heavily on the aforementioned round, both in terms of information circulation, as data collection. keywords: competitive intelligence, web 2.0, intelligence cycle, 1. introduction the information cycle in figure 1 (or intelligence, or competitive intelligence system) is a central landmark in economic intelligence. it is most often represented in a series of stages from planning needs to information diffusion, steps that will refine raw information into intelligence (dedijer, 1999). the information as such is a raw material. refined (integrated / assimilated by the subject), it becomes knowledge (stenmark, 2002) (skryme, 2000) (davenport, 1997). it is from this model that the cycle of information has been developed in the cycle which information is collected, organized, transmitted, evaluated, analyzed and made available to decision makers for inclusion in the decision making as shown in figure 1. available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 1 (2014) 26-35 mailto:mail@quoniam.info mailto:mnem00@gmail.com https://ojs.hh.se/ 27 o p i n i o n s e c t i o n however, in recent years internet 2.0 has spread: everyone can now easily create his own virtual territory composed of everything from one to thousands of sites, and virtually all the territories are considered to be participatory: everyone can write, promote his or her site (boutet and ben amor, 2010). the many-to-many model allows for wide dissemination of information for everyone and enables seo 2.0, whose heart activity is based on tools for mass application, allows, besides a better ranking, an echo globally as shown in figure 2, a de-facto better visibility. this participatory paradigm shift has prompted us to revisit the cycle in light of the aforementioned tools 2.0. figure 1. informational approach of the intelligence cycle 1.2 dissemination and active seo 2.0: for clarity, we will refer to the concept of "2.0" as the broad consequence of a disruption technically very simple: rules for authorizing access to information systems: internet, formerly arpanet, was created to across unix systems and related products, and network architecture was (and still is) together with the software architecture of such systems. in this context, any resource is subject to access rights: read, write and execute (rwx). until the age of 2.0 (also known as writable web), the right to write access, which allows scientists to post comments on the weblog of an unknown, was strictly controlled as regards the web, simply prohibited. since then, the norm is participatory and circulation of information: every internet user has the possibility of transmitting information, and with the right tools, engage in mass distribution. • automation by creating a constellation of linked websites, the user provides internet users a vast window on the information he wants to communicate • communicating information is through automation on a variety of media allowing writing (blogs, forums, social bookmarking sites ...) as shown in figure 3. . 28 o p i n i o n s e c t i o n figure 2. geographical visualization of global sources of visitors to the nutrisaveurs website after an hispanic, anglophone and francophone active seo campaign. the intensity of green color is proportional to the number of visits per territory. 2. glocadata harvesting the web is a system originally designed for information management (voss, 2007). its system of full text automatic indexation (e.g. google pagerank) has certain advantages. that said, in recent years, the manual indexing based on tags: folksonomies, has known a great success. this stigmergic 1 process characterizes a collective intelligence leading to the marking of web pages with specific keywords, marking supposedly handmade synonymous with high congruence between the marked page and tags that are affixed and therefore reliability. glocalization on internet apparent from the technical aspect of the writable web that leads to the emergence of such uses. in this sense, web 2.0 gives users the ability to find, organize, share and create information in ways both personal is globally accessible (martin, 2007). this phenomenon of glocalization therefore allows precise adaptability of web resources for the user and is a way for anyone who uses “active seo”, to allocate 1 stigmergy is a method of indirect communication in a self-organized emerging environment, where people communicate among themselves by changing their environment (wikipedia). the data it publishes, synchronously or not, other users efficiently as shown in figure 2. 29 o p i n i o n s e c t i o n figure 3. information push carried on the social bookmarking site myhealthclips.com for the hypcaloric meals brand nutrisaveurs. green, tags selected by us: "slimming", "diet", “régimen" (hispanic), "health", "food" that will allow any user seeking one of these words to find our publication. in red, the title link leads to the website of the acclaimed brand. 3.1 some implications on the intelligence cycle 3.1 diffusion-collection impact: at first glance, one may think of this cycle as an intern to a structure or an organization. however, the possibility of mass dissemination of information from a company "a" by the means aforesaid will possibly impacting on the collection of data from companies x, y and z such that illustrated in figure 4. 3.2 lobbying by diffusion-collection impact: visibility on the internet is a major issue because who is visible will generate traffic on a website of the reputation / legitimacy-about-to-one-keyword and sales. on the other hand, it is established that a surfer since cognitively limited in the act of searching through an engine, will restrict the navigation of some items among the first results given by the search engine (loc. cit., boutet and ben amor) (at internet institute, 2009) (iprospect, 2006), it is important to be at the top of search results for a given keyword 2 . 2 keyword: for a search engine, expression composed of one or several words. 30 o p i n i o n s e c t i o n figure 4. synoptic view of the impact of the mass distribution of information on collecting through the prism of intelligence cycles of several companies 3.2.1: finding the right keyword to be visible on the internet, one must still find a keyword inherent in his heart craft capable of trafficking. on this point, google offers “keywords tools” shown in figure 5, which bases its results on one side past queries users collected through cookies that expire in the very long term to permit a grouping of keywords and the other on statistics compiled by the firm of mountain view that quantify the research done on a keyword and to deduce the potential traffic obtained according to a geographical area and a target language for the website in the first position results following search criteria. 3.2.2: competitive analysis on the chosen keyword google sets its ranking following its famous algorithm: pagerank. if the latter is subject to a policy of opacity on the part of the firm, some parameters leading to a high ranking are notorious. a number of the most important are in the module "seo competition software market samurai", which provides a global view of competition on a certain keyword as shown in figure 6. the critical indicators include age of the domain name (da column), the pagerank (pr column), the number of pages indexed by google for that area (ic column: index count) and finally the columns blp (backlink page) and bld (backlink domain), respectively the number of backlinks pointing to the page in this classification and those pointing to the domain name of this page. given these results, it is possible to estimate whether a positioning among the top 10 (accessed by a majority of internet users) is possible or not. typically, a small number of backlinks from one of the top ten shows that we can reasonably expect to run for his spot, especially with us using the contributory aspect of web 2.0. indeed, we have the ability to post content including trackbacks (such <a http://www.mydomain.com> competitive 34 o p i n i o n s e c t i o n intelligence </ a>) that link to this site on any media type 2.0 figure 5. proposal for keywords related to "competitive intelligence" language: french, territory: france assorted research estimated monthly provided by google keyword tool. figure 6. top ten results for keyword "competitive intelligence" on google.fr french, established by the software market samurai on 14/02/2011. 3.2.3 massively disseminate information web 2.0 allows anyone to create blogs hosted on dedicated platforms for this purpose. we can choose to disseminate information on our forums, wiki, weblogs, or third parties on our own media, in figure 7, the screen capture tool "link farm evolution” which allowed us to create weblogs on 6149 third-party platforms: web 2.0 allows the construction of territories potentially unlimited and to massively disseminate our information to get 32 o p i n i o n s e c t i o n better visibility, the mere existence of these territories, but also because google will collect the information we have widely distributed among them. proof is that the top ten results on google.fr french language for the query "competitive intelligence", are three of our websites on 14/02/2011 as shown in figure 6: http://competitive-intelligence.blackhattitude.org is at rank 3, http://quoniam.info rank 5 and http://competitive-intelligence.charles-victorboutet.fr to rank 6. we expand on this type of manoeuvre to the next (called serp 3 domination) which is a strategy of influence pay (infra,) since it can give legitimacy to whoever takes many good positions on a particular keyword since "we must find ways to understand issues related to influence strategies implemented by various public and private actors (including lobbying) and apply the techniques of persuasion and influence” (mongereau, 2006). 3 serp: (search engine result pages) search results classified by search engines. http://translate.google.com/translate?hl=fr&sl=fr&tl=en&prev=_t&u=http://competitive-intelligence.blackhattitude.org http://translate.google.com/translate?hl=fr&sl=fr&tl=en&prev=_t&u=http://quoniam.info http://translate.google.com/translate?hl=fr&sl=fr&tl=en&prev=_t&u=http://competitive-intelligence.charles-victor-boutet.fr http://translate.google.com/translate?hl=fr&sl=fr&tl=en&prev=_t&u=http://competitive-intelligence.charles-victor-boutet.fr 33 o p i n i o n s e c t i o n figure 7. screenshot of the software "link farm evolution”: we've created a virtual territory consisting of 6149 blogs that are both 6149 locations spread our information and as many sources by which google will collect its information 4. information overload and speed "the constant growth of information internationally [...] is a problem which questions: how this information will be built, combined and processed" (dou et al., 2003) a fortiori since the 2.0 many-tomany context allows a greater flow of information, obviously in number and in speed, as tools to facilitate the disclosure of more instantaneous while requiring less knowledge of computers have emerged (weblogs, twitter, buzz ...). indeed, since the first automation devices for establishing route information from one individual to another during the years 1940 (rasse, 2005) until now, information is increasing in speed (up to microseconds for high frequency trading 4 ) transmission. the knowledge economy is an economy of speed: values are not stocks that are preserved in time, they decrease with the increasing speed of the process (quoniam and boutet, loc. cit.). to extract value from knowledge, then it must accelerate their use by the widest possible dissemination and at the same time, often precisely because of its dissemination, knowledge is socialized. that is to say, it becomes common heritage to competitors and potential users. it is the parable of the cathedral and the bazaar (raymond, 2001) in fact, the widely disseminated information is widely harvested. this synergy has a major impact on the cycle of ei), the face of this profusion, facilitated by the rapid development of internet and its applications, [...] how to find, 4 high frequency trading: an algorithmic trading subclass, based on short term trading. i.e. a scalping technique at the computer scale (micro-seconds). organize, disseminate relevant information, that giving comparative advantage to the company? (domenech et al., 2009). although "our culture may be less predisposed to such practices. yet they are essential (ibid.). 4.1 overload influence strategy the possibilities are a factor of 2.0 increase in the aforesaid information overload and it is possible, for who knows this and understands the fundamentals of the vertical model data display used by the vast majority of engines, to monopolize the space on a desired search term as shown in figure 8: on the sales site ebay: the seller of many usb memory-sticks instead of using the less expensive hollandaise auction system (a single announce for n times the same object), made the choice to pay n times tcost of listing to occupy the first pages in search engines. 34 o p i n i o n s e c t i o n figure 8. the same product occupies the front pages of research on research "usb", thus obscuring the competition in the eyes of potential customers. as users see few results, and this "few" being situated among two or first three results pages (at internet institute, 2009) (iprospect, 2006), a strategy of the screen where the information secret information (ramonet, 2001) is implemented: we are seen and our competitors are overlooked de facto. figure 8 also illustrates the principle of "serp domination." 4.2 push-pull rss aggregators are a good example of glocalization data (supra.): the user can choose to unionize a site that provides information via a data flow (aka rss) which allows him to obtain information in real time, using xml technology used to transmit the information content while the "presentation layer" will be managed by the rss reader (quoniam and boutet, 2008). during an information pull phase (first visit to a source of information and inclusion in rss feeds), the user initiates a push by registering information: information will now be to him and not vice versa. instead of having to introduce robots which will regularly collect information for him, or worse, to navigate himself to the information, the user is in a position facilitating ingenium 5 (le moigne, 2006), (ciceron, 2003): from one end of this mental area to another, there are such distances we have never traveled 6 (valery, 1992). between folksonomy and information intensive push-pull through “active seo”, 2.0 aspect heavily impacts on the process of data collection. conclusion the 2.0 aspect changes everything in terms of communication, information flow: the many-tomany, massive editing allows global impact, both in broadcasting as the harvesting, but also through the analysis tools needed to grip plethora of information that we have addressed in this article, therefore, the tools of 2.0 have a strong impact on the cycle of ei since are actually intended to handle the massive information. they offer attractive opportunities, particularly in terms of lobbying and are in fact, quite destined to occupy a major place in competitive intelligence in the future. it is possible to consider the cycle of ei as a new day cf. figure 4, days that we will discuss extensively in the course of our future research. 5 ingenium: this strange faculty of the mind is to discern and relate to conjoin (le moigne, 2006) 6 we see here a concept of mental area, concept on which de rosnay and schaer (2008) ask: what will happen when all humans will be interconnected? 35 o p i n i o n s e c t i o n bibliography at internet institute. “baromètre des moteurs avril 2009,” avril 2009. http://www.atinternet-institute.com/frfr/barometre-des-moteurs/barometre-desmoteurs-avril-2009/index-1-1-6-170.html. charles-victor boutet, et samy ben amor. “vers l'active seo 2.0.” les cahiers du numérique 6, no. 1 (juin 2010). cicéron, et a. yon. l'orateur. belles lettres, 2003. davenport, thomas h., et laurence prusak. working knowledge: how organizations manage what they know. 2 éd. harvard business school press, 2000. dedijer, s. “doing business in a changed world: the intelligence revolution and our planetary civilization.” competitive intelligence review (1999). http://www3.interscience.wiley.com/journal/7 1006093/abstract. domenech, sylvie, manuel marciaux, et dominique charnassé. “guide des bonnes pratiques en matière d'intelligence économique.” service de coordination a l’intelligence economique, février 2009. http://www.quoniam.info/competitiveintelligence/pdf/ebooks/guide_des_bonnes_ pratiques_en_matiere_d_ie.pdf. dou, henri, eric boutin, et luc quoniam. “de la création es bases de données au développement des systèmes d'intelligence pour l'entreprise.” isdm, no. 8 (2003). elliott, mark alan. “stigmergic collaboration: a theoretical framework for mass collaboration.” melbourne: university of melbourne, 2007. herring, j. “producing cti that meets senior management's needs and expectations.” scip competitive technical intelligence symposium (1997). heymann, paul, georgia koutrika, et hector garcia-molina. “can social bookmarking improve web search?” dans proceedings of the international conference on web search and web data mining, 195–206. wsdm '08. new york, ny, usa: acm, 2008. iprospect. “search engin user behavior study” 2006. http://www.iprospect.com/premiumpdfs/whi tepaper_2006_searchengineuserbehavior.pd f. le moigne, jean-louis. la théorie du système général théorie de la modélisation. les classiques du réseau intelligence de la complexité, 2006. http://www.mcxapc.org/inserts/ouvrages/0609 tsgtm.pdf. luc quoniam, et charles-victor boutet. “web 2.0, la révolution connectique.” document numérique 11, no. 1-2 (décembre 2008). martin, alban. l'âge de peer: quand le choix du gratuit rapporte gros. village mondial, 2006. mongereau, roger. intelligence économique,risques financiers et stratégies des entreprises. conseil economique et social, septembre 26, 2006. ramonet, ignacio. la tyrannie de la communication. gallimard, 2001. rasse, paul. la rencontre des mondes : diversité culturelle et communication. armand colin, 2005. raymond, eric s. the cathedral & the bazaar. revised. o'reilly, 2001. valéry, paul. introduction à la méthode de léonard de vinci. gallimard, 1992. voss, j. “tagging, folksonomy & co-renaissance of manual indexing?” arxiv preprint cs/0701072 (2007). http://arxiv.org/abs/cs.ir/0701072. http://www.atinternet-institute.com/fr-fr/barometre-des-moteurs/barometre-des-moteurs-avril-2009/index-1-1-6-170.html http://www.atinternet-institute.com/fr-fr/barometre-des-moteurs/barometre-des-moteurs-avril-2009/index-1-1-6-170.html http://www.atinternet-institute.com/fr-fr/barometre-des-moteurs/barometre-des-moteurs-avril-2009/index-1-1-6-170.html http://www3.interscience.wiley.com/journal/71006093/abstract http://www3.interscience.wiley.com/journal/71006093/abstract http://www.quoniam.info/competitive-intelligence/pdf/ebooks/guide_des_bonnes_pratiques_en_matiere_d_ie.pdf http://www.quoniam.info/competitive-intelligence/pdf/ebooks/guide_des_bonnes_pratiques_en_matiere_d_ie.pdf http://www.quoniam.info/competitive-intelligence/pdf/ebooks/guide_des_bonnes_pratiques_en_matiere_d_ie.pdf http://www.iprospect.com/premiumpdfs/whitepaper_2006_searchengineuserbehavior.pdf http://www.iprospect.com/premiumpdfs/whitepaper_2006_searchengineuserbehavior.pdf http://www.iprospect.com/premiumpdfs/whitepaper_2006_searchengineuserbehavior.pdf http://www.mcxapc.org/inserts/ouvrages/0609tsgtm.pdf http://www.mcxapc.org/inserts/ouvrages/0609tsgtm.pdf http://arxiv.org/abs/cs.ir/0701072 to cite this article: søilen, k.s. (2015) a place for intelligence studies as a scientific discipline. journal of intelligence studies in business. vol 5, no 3. pages 35-46. article url: https://ojs.hh.se/index.php/jisib/article/view/136 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a place for intelligence studies as a scientific discipline klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article a place for intelligence studies as a scientific discipline klaus solberg søilen department of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se received 7 december 2015; accepted 15 december 2015 abstract is the field of competitive intelligence (ci) or intelligence studies (is) a proper scientific field of study? the empirical investigation found that academics and professionals within ci and is could not agree upon what dimensions, topics or content are handled by their own area of interest that is not covered by other areas of study. in fact, most topics listed as special for ci and is are covered by other established scientific journals. most topics are covered by other disciplines. the data also showed that the same group could not list any analysis that is not used by other areas of study. it shows that a majority of the analyses the respondents think are unique to their study come from the area of strategy and military intelligence. however, this does not mean that ci and is do not have their own place or niche as a study and discipline. it is suggested here, but further investigation is encouraged, that ci and is bring a number of unique dimensions to the social sciences. keywords competitive intelligence, intelligence studies, science 1. introduction what is a good scientific discipline? when is an area of study a discipline? is the field of competitive intelligence (ci) or intelligence studies (is) a proper scientific field of study? these are the questions that this article will attempt to answer. in the literature prescott and bharadwaj (1995) define the area of ci as a practice. wright and calof (2006) set out to discover the nature of competitive, business and marketing intelligence by a country comparison. solberg søilen (2014) looks at the value a scientific articles on is for professionals. an analysis of articles published in earlier journals like cir and jcim is presented in solberg søilen (2013). du toit (2015) investigates the extension and trends in the is literature. she ranks the most published authors and evaluates their work. these three last contributions are part of an attempt to 1 the term ci was dominant in the literature until five years ago. today is is used as often. the term was suggested by sheila wright, the co-editor of jcim, for the new journal at the ici conference in reevaluate the study of ci which started only a few years back in time. more generally, leydesdorff et al. (2013) have written on how to do a mapping of sciences. earlier, morillo et al. (2003) have shown how research has become increasingly interdisciplinary. a discipline is different from what is called general knowledge in that it contains a body of particular knowledge, has experts and it must be possible to separate it from other areas of knowledge. a discipline is defined as a branch of science, developed by a group of specialists who all adhere to the same practice and research. to what extent is this true for ci and is? there have been no scientific articles that attempt to answer these questions for the study of ci and is1. there are different ways to answer these questions. one way is to go by the criteria of the larger publishers of scientific databases, like scopus and web of science (wos). bad nauheim in 2011. see the conference summary by arthur weiss at http://competitiveintelligence.ning.com/forum/topics/2011-ici-atelisci-conference journal of intelligence studies in business vol. 5, no. 3 (2015) pp. 35-46 open access: freely available at: https://ojs.hh.se/ 36 serious researchers publish in well-accepted scientific databases. a journal – and thus also a discipline – has much greater chances of attracting the attention of other scholars if it is accepted in these databases, even though there are others. the pressure is particularly high for getting into wos. the problem is that wos does not evaluate a discipline per se, but only the journal. the journal must follow certain publishing standards, have an editorial board, reviewers, an international focus and it must be cited by other journals. this last criterion is the difficult threshold for wos, as thomson reuters does not say how many times a journal must be cited. another problem is the question of if this means that all journals in wos represent a specific discipline. the answer is no. this is not one of the criteria by which journals are accepted into wos. there is also a significant number of overlap areas and journals in wos, so that an area such as marketing is covered by dozens of journals with little difference between them. if ci and is is not a discipline, is it then a scholarly approach? this is another question of relevance. a scholarly approach may be defined as an area that is multidisciplinary, interdisciplinary (knowledge that exists between or beyond existing academic disciplines or professions), transdisciplinary (a union of all interdisciplinary efforts) and crossdisciplinary, all with less focused practices. academic disciplines are more focused. that an area of study is a scholarly approach is not an assessment of content, practitioners or its use. biochemistry and geophysics are good examples. wright and calof (2006) recommend a stronger adhesion with other disciplines to develop a more robust research agenda. memheld (2014) shows in a case study how an initial intelligence effort is led astray. instead the solution is a combination of approaches. there are relevant historical and sociological aspects to consider for this investigation too. the 1970s and 1980s saw the start of an explosion of academic fields. many of these had a focus around a specific theme, like media studies, women’s studies or black studies. this was, to some extent, a continuation of a process that started at german universities in the nineteenth century whereby the term “discipline” was used as a catalog and archive for a new body of information produced by a scientific community. communities of academic disciplines can also be found outside of academia, within corporations and in government agencies. scip is an example for the field of ci. in fact, as we shall see, ci has been driven forward first of all by consultants, not academics. the starting point for any discipline is a clear definition of the area of study. so far there has been no agreement as to a definition of ci. if we google the question, the three first definitions we get are quite different. at entrepreneur.com it says “the process of gathering actionable information on your business's competitive environment.” on investopedia it says “the process of collecting and analyzing information about competitors’ strengths and weaknesses in a legal and ethical manner to enhance business decisionmaking”. on wikipedia it says “competitive intelligence is the action of defining, gathering, analyzing, and distributing intelligence about products, customers, competitors, and any aspect of the environment needed to support executives and managers making strategic decisions for an organization.” the first has a focus on the information, the second on decisions and ethics and the third on the intelligence cycle, porter’s five forces and decisions. another problem with these definitions is what in the study of logics is called “ignotum per ignotius”or “obscurum per obscurius,” which describes the making of a definition with the help of words that need further explanation. for example, what do “actionable information,” “competitive environment,” and “ethical manner” mean? what is ethical in one culture may not be so in another. when we try to see how these definitions are made there is no laying out of the “connotation” or necessary qualities of the term, which is what any definition requires. we then need to define the “differentia,” those qualities which separate one term from another. then we must spell out the property of the term, or the qualities that must belong to the term. jumping over this is typical for most definitions in the study of management. many new areas became popular after a bestselling book for practitioners becomes available. consequently, management theory is riddled with sophisms. the sophists used grandiloquent phrases and confused their pupils, all in the name of persuasion. winning a discussion was seen as more important than trying to lay out truths. afterwards, researchers are often called in to sort out the logic. 37 the more consistent definition of intelligence is about intelligence as the faculty of thinking, emotional intelligence or artificial intelligence, which are all very different phenomena. most scientific articles are also in these fields. the problem with the definition of our intelligence – the product and process of information gathering – is to a large extent the same for state intelligence, as dr. michael warner, a cia history staff reminds us: “we have no accepted definition of intelligence. the term is defined anew by each author who addresses it, and these definitions rarely refer to one another or build off what has been written before. without a clear idea of what intelligence is, how can we develop a theory to explain how it works?”2 most of the definitions suggested for the term state that intelligence makes little sense in the notion of private intelligence. what is needed for is is a definition that can fit both state and private intelligence. instead of reinventing the wheel, we can first look at what has already been done. the clark task force of the hoover commission in 1955 made the following definition: “intelligence [studies] deals with all the things which should be known in advance of initiating a course of action.”3 in the mid1990s the brown-aspin commission said intelligence was “information about 'things foreign' – people, places, things, and events – needed by the government for the conduct of its functions.” the definition fits for ci and is if one only replaces “government” with “organization.” the statement then reads “intelligence studies (is) is about 'things foreign' – people, places, things, and events – needed by the organization for the conduct of its functions.” 2 from https://www.cia.gov/library/center-for-the-study-ofintelligence/csi-publications/csistudies/studies/vol46no3/article02.html there is another problem with a great number of definitions; they tend to change over time, because the nature of what they study changes. this is the case with business intelligence (bi) for example. before the software business became engaged in the intelligence area, bi used to be understood as private intelligence, as opposed to state or public intelligence. the confusion lives on even today, even though bi has for many years now been a separate and large scientific discipline dominated by engineers and programmers. in bose (2008), for example, bi is still what is inside the company whereas ci is what is outside (p. 511). when the definition is completed we can move on to the question of classification, which is the next step in laying out a scientific area. one such classification of intelligence studies is suggested in jenster and solberg søilen (2009), p. 13. the classification helps us to place different forms of intelligence in a model, which shows how they relate to one another. in the model above, we have used a venn diagram to show the logic (figure 1). there are two large types of is, private and public intelligence, each representing two fundamental spheres of society. state and military intelligence are the two largest parts of the public sphere. in the private sphere we see that, for example, financial intelligence is smaller than and a part of competitive intelligence. we also see that private and public intelligence are not mutually exclusive, but overlap, as some problems are common for both the public and the private sphere. one way to continue with the scientific investigation about the nature of ci and is is to find out what areas are covered by the study that are not covered by other areas of study. in much the same way we want to know what analyses are covered by the study that are not covered by other studies. this will tell us something about the uniqueness of the study and how it relates to other disciplines (degree of interdisciplinarily, mulitidisciplinarity and cross-disciplinarity). this has not been done in the literature previously. many of the analyses used in ci go back to michael porter, for example as found in porter, 1980. tools and analyses used in ci have been analyzed by bose (2008). fleischer and 3 from the commission on organization of the executive branch of the government [the hoover commission], "intelligence activities," june 1955, p. 26. the interim report to congress was prepared by a team under the leadership of gen. mark clark. figure 1 classification of intelligence studies 38 bensoussan (2003) identify several strategic analytical techniques used in ci including the bcg growth/share portfolio matrix, the ge business screen matrix, industry analysis (porters five forces model), strategic group analysis, swot analysis, financial ratios, and value chain analysis. hussey (1998) identifies sources of information for doing a competitor analysis. sakys et al. (2013) show a way to do analysis for business intelligence in the classroom. in a similar article, sakys and butleris (2011) show how bi tools can improve management courses and training at the university. an extensive evaluation of bi projects is done by adamala and cidrin (2011). they show the role bi software plays for the success of business projects. bruneau and frion (2015) look critically at the quest for ever more data in bi. they suggest that big data can actually be a problem – not a solution – and suggest a way back to basics, to military strategy and how to formulate better questions. the answers to the two questions posed above will tell us about the study’s uniqueness. in this article we propose to answer these questions empirically. the method for finding the answers is explained in the methodology chapter in the next section. 2. method and research design a survey was sent to three active networks of ci practitioners (ci communities on linkedin, jisib readers and ci conference list participants), with an equal mix of academics and professionals. of a total population of an estimated ten thousand practitioners, we identified a sample of 3500 recipients from which we obtained answers from 286 respondents. the study was conducted in november 2015. it was followed up with deep interviews (20-40 mins) with twenty-nine practitioners (10% of respondents), randomly selected from the initial respondents. the research focuses on a relatively new phenomenon and is therefore of a more exploratory nature rather than a study aiming to uncover cause-effect relations or test hypotheses. the extent of researcher interference was moderate in the surveys and excessive in interviews. the study setting for surveys is non-contrived, meaning we study the phenomenon in its natural context. the unit of analysis is individuals. the time horizon is cross-sectional in the study, meaning we conduct the study at one specific time period. determining moderators for this study are thought to be education and profession as well as the ability to adapt to new technologies. the two questions asked were: 1. in your opinion, what is the part of the study of intelligence in business (competitive intelligence, market intelligence) that is not covered by other disciplines (strategy, management, marketing etc.)? in other words, what is it from a scientific perspective that makes the study of intelligence in business special or unique? 2. please take a few minutes to reflect on this question: can you list a number of analyses that you consider to be unique for intelligence studies in business, that is, analyses that are first of all used in intelligence studies (please rank them according to their uniqueness to the area of study, most relevant on top, etc.) the data collected are presented in the next section of the paper, in the empirical findings part. table 1 empirical data from surveys and interviews interview number part of study not covered by other disciplines corresponding discipline / area analyses not covered by other disciplines 1 connecting facts in a way that helps to make sense of information information science swot, porter’s five forces 2 it – data warehousing solutions it blank 3 the two steps procedure: 1. systematic and contextualized information 2. transform of knowledge into intelligence information science blank 4 neuro-business neuroscience theory of spontaneous order of business, relativity of time in business 5 competitor intelligence, intelligence for sales, win-loss analysis, wargames, market-sizing and forecasting, modelling. the study of people with whom you are going to do business. marketing & sales, strategy, managerial accounting, hrm competitor analysis, customer insights analysis, market-share analysis, opportunity analysis, propensity modelling for upsell/cross sell 39 6 the study of business contacts hrm people involved and their needs. changes (political, cultural, environmental, economical, etc.). 7 the link between market awareness and sound decision making marketing, decision-making war gaming, scenario analysis 8 the connection between information types and sources and decision making information science, sources/sci method, decisionmaking blank 9 the aspects that relate to gathering and disseminating intelligence, as well as the specific use of intelligence in strategic and tactical decision making strategy, decisionmaking practices and processes of intelligence gathering analysis, dissemination, decision-making; value of intelligence to decision-makers 10 “watch” (french “veille”) is not covered by other disciplines. ci is special because it mixes all approaches watch, interdisciplinary information plan, research plan, cartography, dynamic environmental analysis 11 competitive intelligence blank scip code of ethics for competitive intelligence professionals. studying patents, patent applications, and trademarks of competitors and the potential legal consequences of doing so. basic technical knowledge needed to understand competitive intelligence 12 eliciting information from competitors using human sources (humint) competitor analysis, humint analysis of competing hypotheses. listing key intelligence areas. counter intelligence audit 13 ci/mi as an integrator and synthesizer of other traditional disciplines, particularly, strategy and marketing (as well as innovation). strategy, marketing, innovation the body of innovation methods – business model as well as product/technology 14 none none 15 the study of intelligence in business deals with all methods and tools that allow information to be transformed into knowledge and intelligence knowledge management, information science the intelligence typology built by wright, bisson and duffy (2012) for companies and by bisson (2015) for public organizations. strategic early warning system. 16 the wide coverage of topics makes it unique. multi-disciplinary no specific 17 the "fog and the friction" (clausewitz). this is different from the strategy which is planned. imperfect information. the transdisciplinary approach, more open minded imperfect information, transdisciplinary how we produce knowledge, how we tend to validate information. to understand failures. try and avoid deception from our "allies and enemies.” monitoring. 18 strategy, management, marketing is very different from intelligence in business. management, marketing general theory of information analysis analysis of text 19 the development of business insights business insights porter, corner, war game, intelligence funnel, competitor profile 20 counter-intelligence/ securing confidential information within the organization counter intelligence, security scenario planning, war gaming, early warning, external technology watch 21 advanced analyses, anticipating events advanced analyses, anticipating events early warning, foresight, big data analysis, semantic analysis, competing hypotheses, physiologic profiling 22 its integration with strategy and marketing integration with strategy and marketing four corners, scenario analysis, five forces, pestl, mckinsey 7s 23 it management it management pestel, swot, value chain analysis, customer analysis, competitor analysis, supplier analysis 24 qualitative research in business context qualitative research lamp – lockwood analytical method for prediction / ach – analysis of competing hypotheses 25 decision making support decision-making data mining 26 early warning and forecast early warning, forecasting patent analysis, forecasting, strategic early warning and flexibility of integration with other methodologies 27 a collection method distinct from market research survey approaches information gathering war gaming, scenario analysis, win loss analysis, business model canvas (as data required), 4-corners analysis. 28 i cannot imagine any aspect, which is not related to others none all analyses associated with the environment of the firm. specifically: scenario analysis, five forces, forecasts, benchmarks and best practice 29 dynamics of several players: rivals, suppliers etc. the future of things industry analysis, future studies none 40 3. empirical findings in table 1 below we have restated a summary of the answers from those who participated in the follow-up interviews. a summary of some of the comments from the interviews are presented below. each statement is from a different respondent: “difficult questions! (…) answers reflect what i have seen at many companies, but this is not a general rule. in some companies all intelligence functions are executed by other departments.” “intelligence was always applied to decision making in conflict situations, especially in fast changing environments. (…) isn’t that a central issue in business too?” “competitive intelligence needs to be indigenized and customized from varied geography and cultures. a method that is effective in africa may not work in south america.” “intelligence in business excels in piggybacking other scientific areas and that is fine as much as it serves its clients’ needs.” “intelligence does not mean anymore insight, but the creation of knowledge for competitive and decision purpose. for the study perhaps a section dedicated to strategy would help to make the journal [jisib] stronger, then increase its impact factor and interest for the study of intelligence in business in general.” “some more focus on strategic intelligence and research will lend an interesting flavor.” “what should be more studied is the human side of ci. psychology and sociology, organizational behavior, and information behavior. we also consider too much information analysis, and we very rarely mention information synthesis. apparently information overload doesn't exist or is not taken seriously in ci (it is so much against the progress paradigm that says that more information is better because information is (always) a good thing, … which is wrong). we consider too much the idea of "information" and the informational approach (data-driven strategy), we do not consider enough the communicational approach nor the informative approach.” “intelligence studies in business need to enrich its own theory, while developing its own unique analysis method.” “my pov: intelligence as a discipline is part of all areas of management / corporate conduct (...) at any level of corporate decision making the right information at the right time is needed to enable strategic and tactical decision making. in the next section of the article we attempt to analyze the data gathered in the empirical part of the study. 4. analysis one way to start the analysis is to ask which areas of study or problems raised in the comments above do not have their own well established scientific journal. in table 2 we only added those areas where the answer could be in doubt. we did not list the more established and obvious areas where we know there exits corresponding scientific journals, like market research. there are many journals that cover topics not reflected in the journal names and that we will have missed. another limitation was that we only checked in two of the major databases, table 2 related problems areas and their corresponding scientific journals topics/databases web of science scopus corresponding journals future, future studies, futurology no yes journal of futures studies, technological forecasting and social change, the futurist world future society early warning no no none forecasting yes yes international journal of forecasting decision making no yes medical decision making, decision science letters, decision sciences counterintelligence no yes international journal of intelligence and counterintelligence security no yes computers and security, security journal intelligence no yes journals covering ai and computational intelligence watch/veille/surrounding world analysis no no none 41 namely wos and scopus. from the analysis we see that only early warning and watch/veille/surrounding world analysis do not have their own established scientific journal. however, these topics are covered in journals related to ci and is, like jisib. one surprising area suggested in the comments from the interviews was neurobusiness. neurobusiness is the capability of applying neuroscience insights to improve outcomes in customer and other business decision situations. it does not correspond to an established journal but is covered by scientific journals in neurosciences. two participants suggest textualization as an area of interest for ci and is. the science for this however was developed in computer science, not in the ci field. if anything it shows the multidisciplinary nature of ci and is. textualization is related to, but different from, the study of data mining. text and web mining tools track information sources and allow sifting through vast collections of unstructured or semi-structured data, which are beyond the reach of data mining tools (hearst, 2003). in table 3 we present the number of articles found on the different analyses suggested in the interviews. the examples of journals listed below are limited to those journals with the highest number of articles for each area of study. only analyses that were represented with five or more articles are included. for example, there was no article with “surrounding world analysis” in the title or topic field. from the analysis we see that the areas represented by the most article are: scenario analysis (1), swot (2), scenario planning (3), competitor analysis (4), war gaming (5) and analysis of competing hypotheses4 (6). moreover, we see that there is a large spread of journal areas for each of the analyses. this suggests that these are analyses that cannot be connected with any one particular study. another way to say it is that the analyses themselves are cross-disciplinary. in the next section we go over to the discussion of the data and analysis presented above. 4 analysis of competing hypotheses was developed by richards (dick) j. heuer, jr., a cia veteran. 5. discussion from the data collected it is not possible to identify any analyses which can be said to be exclusive for the study of ci or is. instead, most of the analyses come from other disciplines, primarily from strategy (corporate and military) and from the study of the scientific method in general. to take an example let’s look at the development and history of the swot analysis. it may have been developed by two harvard business school policy unit professors – george albert smith jr and c roland christiensen during the early 1950s. another hbs policy unit professor, kenneth andrews, is said to have developed its usage and application. all were specialists in organizational strategy, not in marketing. however, other sources claim that the swot was the continuation of albert humphrey’s work on the soft analysis in the 60s and 70s. humphrey worked on a research project at stanford university at the time. yet other sources argue that the first mention of the term swot can be traced back to when it was presented to urick and orr for the long range planning seminar held in zurich in 1964. the oldest article i could find about swot in scopus is from the same stait (1972). stait then worked for a company called orr & partners ltd, united kingdom. he has published no other scientific articles noted in scopus. there are no older sources for swot in wos. it suggests that the swot was first developed in britain, not in the us, but the evidence is not consistent. the swot 2x2 matrix may have been developed much later, in 1982 by dr heinz weihrich. it was initially popularized as the tows matrix. the seminar on long range planning became the journal of long range planning (lrp) in 1968 and is now a leading journal of strategic management5. since the 1980s, the swot has interested management professionals all over the world and today forms an integral part of strategic planning. looking at history, we can see that similar concepts to the swot were introduced in various research papers, but none of them survived. when we look to another popular model in ci and is, the intelligence cycle, we see that it 5 the same journal has published 20 articles on ci, most in 2006 and 2007. the first article on ci in lrp was ewusi-mensah, k. (1989), on how to develop a competitive intelligence system for it. 42 table 3 which analyses are presented with articles in scientific journals analyses no. of articles in web of science, with analysis term in title and selected examples no. of articles in scopus, with analysis term in title and selected examples war gaming 27 examples: art and humanities in higher education, social & cultural geography, cornell international law journal, futures, california management review 43 examples: simulation and gaming, arts and humanities in higher education, social and cultural geography, applied mechanics and materials, cornell international law journal, game studies swot 694 717 competitor analysis 78 examples: international journal of hospitality management, american economic journal, applied economics, ecology, maritime policy & management, journal of digital convergence 6 examples: tourism management, advances in culture, tourism and hospitality research, source of the document public administration review, journal of emerging technologies in web intelligence, place branding and public diplomacy scenario analysis 1774 2348 scenario planning 672 776 analysis of competing hypotheses 8 examples: the korean journal of public administration, journal of organizational behavior, journal of quantitative criminology, risk analysis, cladistics, journal of counseling psychology, military operations research 13 examples: social science research, research in social problems and public policy, journal of organizational behavior, journal of applied and industrial mathematics, risk analysis, journal of quantitative criminology, military operations research, the elgar companion to public economics: empirical public economics is basically a general research model, as found in any course on the scientific method. there is massive borrowing directly from the scientific method, not only for the cycle. bose (2008) writes: “the fundamental forms of analysis are: deduction, induction, pattern recognition, and trend analysis. the abilities required of tools and techniques to perform intelligence analysis are as follows. inductive reasoning: the ability to combine separate pieces of information or specific answers to problems, to form general rules or conclusions. it involves the ability to think of possible reasons why things go together.” pp. 519. this is the procedure for any researcher and for research in general. the data analysis tools mainly consist of data mining, statistical analysis and bi tools (wee, 2001). the logic behind the analysis of competing hypotheses belongs to the same discipline and scenarios or scenario analysis is as old as military strategy. war gaming belongs also to the same study. in conclusion there is no major type of analysis used in ci or is found in this study that can be said to be exclusive for these studies. instead we see that a great number of analyses are shared by most social science studies, as well as studies in the natural sciences. as we have seen above, most existing research into the phenomenon of “intelligence” as it relates to management and business is on artificial intelligence (ai) and emotional intelligence, which are also truly different domains of knowledge. the only research on intelligence existing in wos is related to bi, how to teach bi and the value of bi to management and business. that is to say, it relates to computer science or information systems, which are more developed disciplines. in scopus there are 48 articles dealing with intelligence analysis within business. most of these articles are in the international journal of business information systems, international journal of clothing science and technology and our own journal, the journal of intelligence studies in business. cir and jcim no longer exist as journals in the public domain, or in any of the major article databases. other ci and is articles are found in the journal of the operational research society and transformations in business and economics. most of these articles are on emotional and social intelligence. what we have to ask is what it is that the field of is does not share with more established fields of study like market research, long range planning and business intelligence? after all, if is cannot define such elements then it has no logical right to exists as a proper field. this however does not mean it cannot exist as an interdisciplinary or multidisciplinary field. i will suggest an 43 answer here that is is more than an interdisciplinary or multidisciplinary field. my observations are presented in the form of working hypotheses, divided into four different realms or dimensions: 1. method. the ethical aspects of the method for gathering information are unique for private intelligence. in state, military and public intelligence the ethics are different. 2. perspective. intelligence studies see the competitive organization as dependent on a well functioning intelligence, much like a state or the military has an intelligence organization. this perspective is unique in the study of management. 3. technology. a good intelligence system today, in any size company, is dependent upon business intelligence. is has a role to play here, to evaluate technology from a user perspective. 4. function. counterintelligence in business is an underdeveloped area of study within the study of management. it has no other theoretical home. 5. actor. neglected actor. the study of marketing has a focus on the market and customers. no other area of study has taken a special interest in competitors. this content is the argument for the existence of a proper study of is that goes beyond an interdisciplinary and multidisciplinary nature. it is inseparable from the ethical question of information gathering, it takes as its starting point the perspective of the intelligence organization, is inseparable from the user perspectives of bi and other technologies for information gathering, and it studies counterintelligence in business and focuses on competitors. this list is by no means final or complete. the working hypotheses are the results of reflections when discussing the topic and should also be tested empirically. there is yet another angle to answer the questions raised in this paper. any study which can claim to be useful has the right to some form of existence. ci has resulted in consulting for decades, even though the popularity of these services has varied and is declining. we see this dominance even today, in the fact that all major ci conference today start from a practitioner’s perspective. academics are in the minority and are left to a special track. also much of the development of the study has come from consultants. so even though this is no evidence of a scientific discipline, it is an indication that the areas have intellectual substance. at the same time, we see that the professional interest for ci is declining, as shown in figure 2. in figure 2, we see that the popularity of the two terms ci (blue/top) and is (red/bottom) are about the same at the end of 2015. the reduction in the popularity of ci coincides with the fact that ci consultancy has decreased and much of the academic literature has centered around is. the exact causes and effects of this are still to be uncovered. it may also be that ci has declined due to what users see as uncertainties about and around the field. a decade ago, many ci practitioners reinvested themselves under the label market intelligence, even though there is no evidence that the focus of its content shifted, for example for the consultant global intelligence figure 2 popularity of the terms “competitive intelligence” (in blue) and “intelligence studies” (in red) in google trends. 44 alliance (gia). another reason for the decline in ci interest may be due to the cycles that management theories follow in general, replacing one management fad with another. this question however must be the topic of study for market psychology and cannot be treated here. an issue that should be discussed at this point is whether or not it was right for the ci field to narrow down its scope at the start. while this may have made sense from a consultancy perspective – at least for a while – the same development may have led to the field’s decline in the longer run. it should be noted here that there has always been and continues to be great cultural differences in how the field is presented, as in the way that ci is taught and practiced in different cultures. in sweden it continues to be as “omvärldsanalys” or “surrounding world analysis”, which is much broader. the same is true in france, with the notion of “veille.” the academic literature has for most part been dominated by anglo-saxon contributions, which have followed the narrower perspectives of ci, as seen in cir and jcim. discussions among editors of jisib have so far led to a broader approach and broader acceptance of different types of articles and methods. where this is going and how analysis and contributions will look in the future we do not know. suggestions from the empirical parts of this article suggest future contributions should be more interdisciplinary, multi-disciplinary and crossdisciplinary in nature. more specifically, they should move away from the narrow focus on a limited number of analyses and leave the idea that these are in any way special to ci or is. focus could instead be more on helping decision makers prepare information, where that problem is studied from a wider perspective. this corresponds well with the understanding of intelligence both in the private and public sphere, even though the method and means are quite different. it also fits well with the definition of intelligence as suggested by the clark task force of the hoover commission: “intelligence [studies] deals with all the things which should be known in advance of initiating a course of action.” another maybe more difficult question is what sense it makes – especially for practitioners – to break the process of management down in this way and for them to separate strategy from decision making, information gathering and knowledge management. 6. conclusion this empirical investigation found that academics and professionals within ci and is could not agree upon what dimensions, topics or contents are handled by their own area that are not covered by other areas of study. in fact, most topics listed as special for ci and is are covered by other established scientific journals. most of these are covered by disciplines like information sciences, it, marketing, hrm, strategy, knowledge management and future studies, or they are truly interdisciplinary and/or multidisciplinary in nature. the data also showed that the same group of respondents could not list an analysis that is not used by other areas of study. it also shows that the analyses the respondents think are unique to their study come from the area of strategy and military intelligence, primarily. the most popular analyses in scientific journals are, in order of popularity, scenario analysis (1), swot (2), scenario planning (3), competitor analysis (4), war gaming (5) and analysis of competing hypotheses (6). this conclusion does not mean that ci and is do not have their own place or niche as a study and discipline. it is suggested here, but further investigation is encouraged, that ci and is bring a number of unique dimensions to the social sciences. these are, in terms of method, a continuous discussion of ethical aspects of the method for gathering and using information among private organizations. in terms of perspective, no other study offers the broad approach to decision making that is needed to make good decisions. instead these are often assumed. in terms of user aspects of new technology, ci and is is continuously applying technology in its work which is evaluated from a user perspective, primarily in business intelligence software. in terms of function, no other study deals with counterintelligence in business, a largely underestimated topic. in terms of actors, other disciplines continue to neglected competitors. in general, it is suggested that the is function is a way for academics to try to imagine in what way they can help bring information to decision makers. this seems to be the core of the field. ci and is are small areas of study compared to other management disciplines. 45 the interest for ci has reduced considerably over the last decade. much of this may be due to the fact that people have found it hard to understand what ci is. this in turn can be explained by the fact that it was never properly defined, and that new articles had other definitions and that there was a lack of consensus. this is not a criticism of ci as a discipline per se, but follow the pattern of most new management and social science disciplines. the study of marketing was in much the same situation a hundred years ago. however, we can say that the study could have focused more on laying out the boundaries of its domain as a discipline earlier. instead the area was largely developed and steered by consultancy interest. the first scientific journal was developed with the appearance of jcim and it had only a short life span, much due to a rift between academic and consultancy interests, it must be said. in general, i see no special conflict of interest between the two spheres. on the contrary, i think that a new fruitful discussion can bring forward a more robust discipline which will also produce clearer and longer lasting consultancy services. some may complain that the theoretical development goes too slowly for the discipline of is. on the other hand, it can be seen that the study has come a long way and survived in academia for more than half a century already since stevan dedijer introduced the topic of social intelligence in sweden in the early 1970s. one of the reasons why ci has seen a reduction in popularity may also be be due to the nature of the topic. alessandro comai, a long term consultant in the field who just defended his doctoral thesis at esade in spain, defines this problem well: “you need a set of special skills to sell consultancy services. companies hire specialists not generalists”. intelligence is about as broad as there is, and is more knowledge than skills. for some intelligence is about wisdom, which is even worse to sell. this then becomes somewhat of a contradiction if you try to sell intelligence as a consultancy product. the customers for this kind of expertise are more likely to be larger organizations, like governments and mnes. at the same time, today new technology is making it possible for smaller companies to develop their own intelligence system with a computer, some software and internet access. it’s unclear, however, which part of this service can be provided by tech people and which part can be delivered by intelligence professional and academics. at the end there is probably room for both. recent critical articles on ci may be a sign that the discipline is maturing. at least it could be said that in general it is a sign of maturity when a field of study starts to reflect on its own production. jisib has done so systematically in a number of articles over the past two years, but there is still much to be done. 7. references adamala, s., & cidrin, l. 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(1995). “competitive intelligence practices: a survey”, competitive intelligence review, vol. 6 no. 2, pp. 4-14. sakys, vigintas, kapocius, kestutis, butleris, rimantas (2013). the framework for business intelligence driven analysis of study course teaching efficiency. transformations in business & economics, vol. 12, iss 1a, pp. 429-442 sakys, vigintas, butleris, rimantas (2011). business intelligence tools and technology for the anlaysis of university studies management. transformations in business & economics, vol. 10, iss 2, pp. 125-136 solberg søilen, klaus (2014). a survey of users’ perspectives and preferences as to the value of jisib – a spot-check, vol 4 no 2, pp. 61-66 solberg søilen, klaus (2013). an overview of articles on competitive intelligence in jcim and cir, vol 3 no 1, pp. 44-58. stait, n. h. (1972). management training and the smaller company: swot analysis. industrial and commercial training, 4(7), 325-330. du toit, a. s. a. (2015). competitive intelligence research: an investigation of trends in the literature. journal of intelligence studies in business, 5(2), 1421. wee, t.t.t. (2001), “the use of marketing research and intelligence in strategic planning: key wright, s. and calof, j.l. (2006). the quest for competitive, business and marketing intelligence – a country comparison of current practices, european journal of marketing, vol. 40 nos 5/6, pp. 453-65. vol5no3 article2 coverpage vol5no3 article2 journal of intelligence studies in business vol. 13 no. 1 (2023) pp. 30–42 open access: freely available at: http://jisib.com/ swot analysis problems and solutions: practitioners’ feedback into the ongoing academic debate thomas king* united states fortune 50 company in the retail industry in minneapolis, mn thomasaking22@gmail.com shelly freyn united states alfred university freyn@alfred.edu jason morrison united states alfred university morrisonj@alfred.edu received 23 april 2023 accepted 12 may 2023 abstract the literature on swot is characterized by a debate among academics who have identified problems and proposed solutions for the strategic management tool, yet little research to date has captured practitioners’ perspectives. recent literature indicates that swot is still the most popular strategic management tool among competitive intelligence (ci) professionals. the purpose of this study is to bridge this academic-practitioner divide in the swot literature by conducting a cross-sectional survey that gathers practitioners’ feedback regarding whether they are experiencing the problems or employing the solutions proposed by academia. a survey was distributed via linkedin to collect data from ci and other business professionals who conduct swot in the workforce. the findings confirm that practitioners experience select problems identified by the literature. specifically, they may have too many factors per swot category, may be defining factors with ambiguous and unclear words, and may not have a means for resolving conflicts when factors fall in multiple categories (e.g., opportunity and threat). the findings also indicate that practitioners may not be consistently conducting swot as a structured business process, as proposed in the literature. the feedback provided by ci and other business professionals aids in closing the academic-practitioner divide by more clearly identifying persistent issues with swot and creating valuable and actionable insights that will drive the continual improvement of this popular strategic management tool. keywords: academic-practitioner divide, strategic management tools, swot 1. introduction the evolution of globalization and the ever-changing dynamics of digital * corresponding author technologies continue to disrupt established industry business models. for business leaders navigating an exceedingly volatile environment, maintaining a sustainable 31 competitive advantage requires innovative organizational processes in strategic management. specifically, these processes must deliver actionable intelligence on the macro-environmental forces driving disruption and reinforce an acute awareness of internal resources and capabilities. empowered by these innovative processes, business leaders may be better equipped to develop strategies that ensure survival and success in an evolving industry landscape. academia has introduced an array of strategic management tools to support business leaders in the development of such strategies with swot (strengths, weakness, opportunities, threats) analysis being one of the prevalent fixtures in mba programs. the pervasiveness of swot analysis has manifested in practice as this methodology is used by practitioners more often than any other strategic management tool (frost, 2003; qehaja, et al., 2017). this finding was further validated by a survey of ci professionals that confirmed swot as their primary strategy tool (author & hoffman, 2023). furthermore, the number of articles published on swot in peer-review journals has continued to increase over six decades (ghazinoory, et al., 2011; gürel & tat, 2017; helms & nixon, 2010), indicating a steadfast and growing interest in swot among academics. yet, amidst its popularity in practice and in literature, there remains an ongoing debate surrounding the fundamental value of employing swot for strategy development. at the core of the debate is swot’s methodological process and whether it can provide any value for strategy development. on the one side, academics dismiss the utility of swot due to inherent problems with the methodology; on the other side, academics have proposed solutions designed to salvage valuable insights (gürel & tat, 2017). while academics from both schools of thought have weighed in, little research to date has considered the practitioners’ perspective. empirical research is lacking regarding practitioners’ experiences with the alleged problems of the methodology or in what conditions swot is actually being used. the gap between proposed swot research by academia and lack of practitioner feedback epitomizes an academic-practitioner divide. in order to bridge the divide, academics must elevate the level of managerial relevance by inviting the practitioners’ perspective into the debate. according to jaworski (2011), managerial relevance is the degree to which practitioners perceive academic research as supporting their work because the findings are important, actionable, and meaningful. the present research aims to elevate the managerial relevance regarding swot by addressing three key research questions: • what are the fundamental problems with swot as identified in the literature and do practitioners experience these problems in practice? • what are the best conditions for conducting swot as proposed in the literature and do practitioners conduct swot in these conditions? • what are the current challenges that practitioners experience with swot and what can researchers learn from their feedback to improve the methodology? addressing these research questions will begin with a literature review that evaluates two bodies of literature in strategic management theory. the first comes from the resource-based view that serves as the foundation for assessing internal strengths and weaknesses. the second consists of the dynamic capabilities framework, which provides the foundation for identifying external opportunities and threats. from there, studies will be discussed that identify problems and propose ideal conditions for swot; thereby forming the hypotheses. the methodology section will discuss the survey development and distribution to practitioners, followed by a discussion of results, limitations, and future research opportunities. 2. literature review a review of the literature provided insight into the origins of swot and how its comprehensive approach to strategy has helped it persevere for more than half a century. although the earliest origins can be traced back to the 1950’s and 1960’s, weihrich (1982) was the first to introduce swot as a 32 strategic management tool (ghazinoory, et al., 2011). weihrich originally proposed swot as a key part of the strategic planning process through which practitioners conducted an audit of internal resources (i.e., strengths and weaknesses), scanned for potentially disruptive factors in the macro-environment (i.e., opportunities and threats), and analyzed these variables in a matrix designed to facilitate strategy development. decades later, swot is used more frequently than any other strategic management tool (frost, 2003; qehaja, et al., 2017) and remained uniquely capable of fulfilling a critical step in the strategic management process (gürel & tat, 2017). the unique capabilities of swot can be tied to its holistic approach to strategy, which by focusing on internal resources and external forces aligns with strategic theory from two parallel schools of thought: the resource-based view and the dynamics capabilities framework. 2.1. the resource-based view the resource-based view (rbv) looks explicitly at internal resources within the organization (kraaijenbrink, et al., 2009). according to the rbv, the fundamental strategic imperative of an organization is to acquire and control those resources that are valuable, rare, imperfectly mobile, inimitable, and non-substitutable to achieve competitive advantage (hunt & derozier, 2004). by focusing the strategic planning process internally, the rbv aligns with the process of auditing internal resources (i.e., strengths and weaknesses) in swot. valentin (2001) was among the first academics to bring swot and the rbv school of thought together in the literature. according to valentin, an rbv approach complemented swot by perceiving the organization as a collection of resources that operates in a larger environment with threats and opportunities. clardy (2013) built on the work of valentin by demonstrating how an rbv approach to swot presented three strategic actions: to invest to make strengths stronger, to take action to mitigate weaknesses, and to use strengths to capture opportunities. in this way, conducting swot from a rbv conceptualized the situational assessment so that an organization can employ internal resources (i.e., strengths and weaknesses) in response to external forces (i.e., opportunities and threats) in the environment to achieve a competitive advantage. 2.2. the dynamic capabilities framework the dynamic capabilities framework (dcf) addressed the process of scanning for potentially disruptive forces in the macroenvironment (i.e., opportunities and threats). according to the framework, the fundamental strategic imperative of an organization was to identify the likely trajectory of technology and the market and to acquire the necessary resources to maintain or achieve competitive advantage (kay, et al., 2018). teece (2007) called for a function within the organization such as a ci team to look externally, recognize macroenvironmental trends, then direct and redirect resources in the organization in response to these trends. by focusing the strategic planning process externally, the dcf aligned with the practice of scanning the macro-environment for potentially disruptive forces in a swot. the dcf is among the latest iterations of external models for strategy, but has yet to be tied to swot in the literature. according to kay et al., (2018), the dcf was based on previous external models like the five forces framework (porter, 1980). dcf expanded porter’s research by demonstrating how scanning the macro-environment can present strategic choices like seizing opportunities, acquiring necessary resources, or reconfiguring assets to achieve competitiveness (teece, 2007). with foundational skills in research, analysis, and communication, analysts on a ci team are well-positioned to serve in this capacity by scanning the macro-environment, analyzing key trends, and communicating findings to leadership who can then make informed decisions to maintain and achieve competitiveness (author & hoffman, 2003). although not yet tied to swot, scanning the macro-environment with a dynamic capabilities function like a ci team aligns with the process of identifying disruptive forces (i.e., opportunities and threats) so that an organization can reconfigure or acquire resources (i.e., strengths and weaknesses) to achieve competitive advantage. 33 2.4. problems with swot in a meta-analysis of swot research, ghazinoory et al., (2011) credited hill and westbrook (1997) for making important contributions to the methodological development by identifying a comprehensive list of problems. for this reason, the present research references hill and westbrook to test the issues practitioners may be experiencing. in their seminal study (cited over 1,500 times), hill and westbrook reviewed the swot process at over 50 organizations and recognized seven problems that practitioners may experience when using the methodology. these problems identified by hill and westbrook were ultimately used to develop the hypotheses for the study (table 1). table 1. hypotheses drawn from problems with swot as identified by hill and westbrook (1997). h1. practitioners are experiencing the problems identified by hill and westbrook (1997) while conducting swot. h1a practitioners do not verify factors with primary data. h1b practitioners do not verify factors with secondary data. h1c practitioners do not verify factors with analyses. h1d practitioners have no means of limiting the number of factors generated. h1e practitioners have no means of prioritizing factors. h1f practitioners are defining factors with unclear terms. h1g practitioners are defining factors with ambiguous terms. h1h practitioners have no means of resolving conflicts. h1i practitioners are experiencing a problem because there is no logical link to implementation. h1j practitioners are experiencing a problem because only a single level of analysis is required. the first problem identified was the lack of obligation to verify factors (i.e., strength, weakness, opportunity, or threat) with data or analyses; meaning practitioners may generate factors that are liable to subjectivity without analytic rigor. hill and westbrook (1997) also observed that there were no limits on the number of factors to be considered and no means of prioritizing factors in a swot. this can create confusion and reduce the degree to which factors are relevant to the organization. other problems that could contribute to confusion included unclear or ambiguous definition of terms and no means of resolving conflicts such as during the placement of factors (e.g., whether a factor is a strength or weakness). finally, hill and westbrook argued that there was no logical link to implementation and only a single level of analysis is required, resulting in practitioners squandering the valuable insights that swot can provide. 2.5. proposed conditions for conducting swot in addition, this study addressed the optimal conditions for conducting swot proposed in the literature. at the conclusion of the same meta-analysis, ghazinoory, et al., (2011) considered the previously mentioned problems and offered a model for the best conditions to conduct swot. specifically, ghazinoory, et al., suggested that the best conditions for the analysis are within a structured business process and within a stable market environment. more broadly, these conditions can be described by a two-by-two matrix in which the degree of structure around the business process is defined along the y-axis and the degree of stability in the market environment is defined along the x-axis (figure 1). 34 since these conditions were proposed in a meta-analysis and not empirically tested, this research aimed to test these conditions among practitioners for the first time. to test the extent to which a business process is structured, this study drew from empirical research in computer science that tested how well different modeling languages represent structured versus unstructured business processes (cardoso, et al., 2016). in order to apply this research to swot, the present study tested the degree to which swot was predictable and repetitive among practitioners according to the four types of business processes defined by cardoso, et al., and adapted from reichert and weber (2012). specifically, this study sought to understand whether practitioners conducted swot by: 1) following the same steps sequentially every time, 2) following the same steps generally but may go back to a previous step or skip a step, 3) following the steps loosely and in no particular order, or 4) conducting swot with unique steps and in a unique order each time. another optimal condition put forth in ghazinoory, et al., (2011) requires that swot be conducted in a stable market environment. in the financial literature, a stable economy and market are usually defined as “facilitating (rather than impeding) the performance of an economy” (schinasi, 2004, p. 8). in the absence of macro-economic shocks like the coronavirus pandemic, there are typically four indicators of a stable market environment that facilitate the performance of the u.s. economy: low unemployment numbers, low inflation, high consumer activity, and high investor activity (jareño & negrut, 2016). in order to test the long-term trends of these economic indicators in absence of macroeconomic shocks, this study used descriptive statistics to identify the median unemployment rate (u.s. bureau of labor statistics), personal consumption expenditures and gross private domestic investment (u.s. bureau of economic analysis), and inflation of consumer prices in the u.s. (world bank) for the last decade for which data is publicly available, specifically between january 2011 and january 2021. based on a review of the literature, the following hypotheses were developed to test for the first time whether practitioners are conducting swot in the optimal conditions as proposed by ghazinoory, et al., (table 2). table 2. hypotheses drawn from best conditions for conducting swot as proposed by ghazinoory, et al., (2011). h2. practitioners are conducting swot in the best conditions as proposed by ghazinoory, et. al., (2011). h2a practitioners are conducting swot as a structured business process. h2b practitioners are conducting swot in a stable market environment. 3. methodology as one of the first empirical studies to gather practitioner feedback on swot, the problems identified and ideal conditions proposed in the literature served as the foundation of the survey. questions were developed using the guidelines of being relevant and meaningful, unambiguous, and easy to answer from the perspective of the participant (connell, et al., 2018). a pre-test of the survey was conducted with business professors who had both taught swot as well as conducted swot as a practitioner. b u s in e s s p r o c e s s u n s tr u c tu r e d s tr u c tu r e d the best conditions for swot stable unstable market environment figure 1. best conditions for conducting a swot, modified based on model by ghazinoory, et. al., (2011). 35 additionally, business and ci professionals who have conducted swot participated in the pre-test. for valid inferences from survey data, respondents’ characteristics must reflect the target population (maholtra, 2019). to achieve this, a cross-sectional survey was distributed on linkedin using eleven groups whose title contained the term strategy or intelligence (e.g., strategic planning society, the strategic management society, strategic and competitive intelligence professionals). professionals in the intelligence field were considered particularly relevant as they are highly focused on supporting executive level leaders in making more effective strategic decisions (wheaton & beerbower, 2006). to ensure respondents fit the sampling frame, the linkedin post requested practitioners to participate only if they had conducted swot at their organization. upon completion of the six-week collection period, the survey had a total of 41 participants and a 100% completion rate. although limited, this does reflect the trend of declining response rates for organizational research (fulton, 2016). fulton argued that non-response is a growing issue and noted that “if there are no systematic differences between respondents and non-respondents, then the sample remains representative of the population and can provide valid inferences” (p. 4). taking into account that respondents were both affiliated with strategic management organizations and conducted a swot at their organization, the sample size was deemed acceptable for this pilot study. in the respondent pool, 40% identified as executives and 33% as managers, while analysts reflected 28% of the group. considering swot is a strategic management tool and managers and executives accounted for almost two-thirds of the participants, the position levels were deemed well represented. there was a representative distribution of responses related to company size in terms of employees: greater than 3,000 (39%), 1,000 – 2,999 (15%), 500 – 999 (5%), 201 – 499 (12%), below 200 (29%). gross annual revenue of the organizations represented among participants indicated nearly all were between $1 billion $10 billion (89%), with the rest greater than $10 billion. overall, it was determined that there was representation from a variety of industries: • industrials 22% • information technology 20% • professional services 20% • financials 15% • health care 12% <10% (in order): not for profit, materials, real estate. 4. results 4.1. problems with swot since hill and westbrook (1997) observed a lack of analytic rigor in how practitioners were generating factors for swot, practitioners were asked to rate on a likert scale (5=always, 1=never) how often they generated factors by consulting data and conducting analyses. findings revealed that all results were statistically significant to 0.1% and greater than neutral (3.0) which indicates that they often generate factors by consulting both secondary and primary data and by conducting analyses (table 3). these findings contradict hill and westbrook’s observation as practitioners do appear to be generating factors by conducting analyses and consulting primary and secondary data sources. table 3. descriptive statistics for the methods used to generate factors for swot (n=41) and (df=40). m sd t sig. consulting secondary data 3.73 1.245 3.762 ** conducting analyses 3.61 1.115 3.501 ** consulting primary data 3.54 1.098 3.130 ** note(s): m = mean; sd = standard deviation; n.s. = not significant; * = p <0.05; ** = p <0.01; ***= p <0.001 hill and westbrook (1997) proposed that practitioners had no means of limiting the number of factors generated for swot. practitioners were asked to what extent they 36 typically have too many factors per category on a 5-point likert scale (5=always, 1=never) and t-test results indicated that practitioners’ ratings were greater than neutral (3.0), suggesting that practitioners may at times have too many factors per category. practitioners were also asked to identify the typical number of factors generated per category in the model. results indicated five to six (43%) was most common followed by three to four factors (40%), seven to eight (15%) and nine to ten (3%) factors. despite most practitioners only having three to six factors per category, likert results indicate practitioners rated that there were too many factors per category. as such, these findings are consistent with hill and westbrook and infer that there still appears to be no means of limiting the number of factors generated. according to hill and westbrook (1997), practitioners had no means of prioritizing factors. results of the survey revealed that based on the 5-point likert scale of agreement (5=strongly agree, 1=strongly disagree), responses were statistically significant to 0.1% and were greater than neutral (3.0). these results indicate that practitioners agree that they have some understanding of which factors are more important than others (table 4). since practitioners appear to have a means of prioritizing factors, the results contrast the findings by hill and westbrook. table 4. descriptive statistics for the extent to which practitioners agree with the following (n=41) and (df=40). m sd t sig. i typically have a clear understanding of which factors are more important than others 3.49 .898 3.479 ** note(s): m = mean; sd = standard deviation; n.s. = not significant; * = p <0.05; ** = p <0.01; ***= p <0.001 considering valentin (2001) had proposed in the rbv that certain types of resources could be more valuable to competitive advantage than others, practitioners were asked exploratory questions regarding which tangible and intangible resources were most important to swot on a 5-point likert scale (5=very important, 1=not at all important). the results indicated that informational (µ=4.24), relational (µ=4.10), reputational (µ=3.73), human (µ=3.63), and organizational (µ=3.63) resources were significantly greater than neutral (3.0) at 0.1% significance level, and financial (µ=3.46) and intellectual (µ=3.34) were significantly greater than neutral (3.0) at the .05% significance level (table 5). the remaining categories of legal and physical resources failed to reach statistical significance, inferring both are considered to be of neutral importance. these exploratory findings suggest that a resource’s ability to facilitate competitive advantage for the organization may be one approach current practitioners are using to prioritize factors. table 5. descriptive statistics for the extent to which practitioners identify the following types of resources as important to a typical swot (n=41) and (df=40). m sd t sig. informational 4.24 .799 9.964 *** relational 4.10 .735 9.561 *** reputational 3.73 1.096 4.275 *** human 3.63 1.090 3.726 *** organizational 3.63 .942 4.309 *** financial 3.46 1.247 2.380 * intellectual 3.34 1.063 2.056 * legal 3.02 1.235 0.123 n.s. physical 2.78 1.255 -1.120 n.s. 37 note(s): m = mean; sd = standard deviation; n.s. = not significant; * = p <0.05; ** = p <0.01; ***= p <0.001 the problems of defining factors with ambiguous words or unclear words were also examined in this survey (hill & westbrook, 1997). practitioners were asked on a 5-point likert scale how frequently (5=always, 1=never) a factor is defined with ambiguous words and with unclear words, respectively. the results were insignificant or neutral (3.0) on the frequency at which they define factors with ambiguous words and unclear words, respectively. these results suggest that practitioners may at times be defining factors with ambiguous or unclear words, which aligns with the observations by hill and westbrook. another problem identified by hill and westbrook (1997) was that practitioners have no means of resolving conflicts when factors belong to multiple categories. practitioners were asked how frequently a factor belongs to multiple categories in a typical swot on a 5-point likert scale (5=always, 1=never) to determine whether such conflicts were being resolved. the results were insignificant or neutral (3.0) for the frequency at which a factor belongs to multiple categories, suggesting that practitioners may at times have factors that belong to multiple categories. since practitioners are still experiencing this problem, the results are consistent with the observations of hill and westbrook (1997) and infer that practitioners may not have a means of resolving conflicts when a factor does belong to multiple categories. this study also examined the problem of whether practitioners had no logical link to implementation and whether practitioners only conducted a single level of analysis, as observed by hill and westbrook (1997). in order to test the link to implementation, practitioners were asked to rate on a 5-point likert scale (5=always, 1=never) how frequently insights from swot were implemented directly into strategy development. practitioners’ responses were significantly greater than neutral at the 0.1% significance level, indicating that insights were frequently implemented directly into strategy development. in order to test whether practitioners conducted a single level of analysis, practitioners were asked to rate on a 5-point likert scale how frequently (5=always, 1=never) insights from swot are combined with another analytic technique. the results were significantly greater than neutral at the 0.1% level, suggesting that practitioners are conducting more than one level of analysis. these findings contradict the observations of hill and westbrook (1997) because practitioners appear to be linking swot to strategy development and practitioners are combining swot with additional analytic techniques (table 6). table 6. descriptive statistics for the frequency at which practitioners self-report the following happens while conducting swot (n=41) and (df=40). m sd t sig. insights from swot are implemented directly into strategy development. 3.78 .936 5.341 *** insights from a swot are typically combined with another analytic technique. 3.93 1.058 5.609 *** note(s): m = mean; sd = standard deviation; n.s. = not significant; * = p <0.05; ** = p <0.01; ***= p <0.001 a follow-up exploratory question sought to reveal which of the analytic techniques identified by ghazinoory, et al., (2011) practitioners used in combination with swot. the results showed that most practitioners combined swot insights with the following analytic techniques: • environmental 37% • balanced scorecard analysis 20% • statistical analysis 20% • multiple criteria decision matrix 15% • cross-impact analysis 7% 38 <10% (in order): cross-impact analysis, analytic hierarchy process, porter’s five forces, porter’s 4 corners, win/loss analysis, salesforce/crm data, scenario analysis, and keep, stop, start analysis. 4.2. proposed conditions for swot in addition to the proposed problems of swot, the survey examined whether practitioners are conducting swot in the best the conditions proposed in the literature. the first condition by ghazinoory et al., (2011) was that swot should be conducted as a structured business process. when practitioners were asked on a 5-point likert scale how frequently (5=always, 1=never) they conducted swot as a structured, step-by-step process, the responses were neutral (3.0) and failed to reach statistical significance. based on the survey results, this infers that practitioners do not appear to be consistently conducting swot as a structured business process, contradicting ghazinoory, et al. the second condition proposed by ghazinoory et al., (2011) was that swot should be conducted in a stable market environment. according to the u.s. bureau of labor statistics, the median monthly unemployment rate was 5.5%, which was determined to be low considering national average over the last 10 years is 5.7%. the median monthly personal consumption expenditures was $12,432 billion and the median quarterly gross private domestic investment was $3,206 billion, both of which were considered to be high based on national average over the last 10 years (u.s. bureau of economic analysis). the median annual inflation of consumer prices in the u.s. was 1.8%, which was considered to be low compared to an average of 2.0% over the last decade (world bank). since the median value for unemployment and inflation were low and personal consumption expenditures and gross private domestic investment were high, these findings suggest that practitioners have been conducting swot in a stable market environment over the last decade as proposed by ghazinoory, et al., (table 7). table 7. descriptive statistics for economic indicators between january 2011 and january 2021. m sd unemployment rate 5.5% 2.1% personal consumption expenditures $12,432b $1,306b gross private domestic investment $3,206b $478b inflation, consumer prices in the u.s. 1.8% 1.2% a complete summary of the hypotheses testing results is presented in table 8. table 8. hypothesis testing results. h1. practitioners are experiencing the problems identified by hill and westbrook (1997) while conducting swot. partially supported h1a practitioners do not verify factors with primary data. not supported h1b practitioners do not verify factors with secondary data. not supported h1c practitioners do not verify factors with analyses. not supported h1d practitioners have no means of limiting the number of factors generated. supported h1e practitioners have no means of prioritizing factors. not supported h1f practitioners are defining factors with unclear terms. supported h1g practitioners are defining factors with ambiguous terms. supported h1h practitioners have no means of resolving conflicts. supported 39 h1i practitioners are experiencing a problem because there is no logical link to implementation. not supported h1j practitioners are experiencing a problem because only a single level of analysis is required. not supported h2. practitioners are conducting swot in the best conditions as proposed by ghazinoory, et. al., (2011). partially supported h2a practitioners are conducting swot as a structured business process. not supported h2b practitioners are conducting swot in a stable market environment. supported 5. discussion the present study drew upon the works of hill and westbrook (1997) and ghazinoory, et al., (2011) to identify whether practitioners experienced problems with swot and conducted swot in the best conditions proposed in the literature, respectively. the findings show that while practitioners resolved some of the problems with swot identified by hill and westbrook (1997), four issues persist today. the first problem is that practitioners indicated that they may have too many factors per category. the next two problems are that practitioners appear to be defining factors with ambiguous words and unclear words, respectively. finally, the last problem is that practitioners may not have a means for resolving conflicts when factors could belong to multiple categories (e.g., opportunity and threat). this feedback more clearly identifies issues with swot from the practitioner perspective and provides valuable insight into improving the methodology. although the findings indicate that these issues with swot persist, exploratory findings offer a glimpse into how practitioners may be leveraging their industry expertise in an attempt to overcome these issues. for example, the practitioners indicated that informational and relational resources were particularly important for swot whereas legal and physical resources were not. these findings suggest that practitioners recognize the relative importance of different types of resources and may be limiting the number of strengths and weaknesses included in the swot to only the most important resources, especially considering that industrials, information technology, and professional services were the leading industries represented in the study. in addition to these four problems, the findings also show that practitioners are not conducting swot in the optimal conditions as proposed by ghazinoory et al., (2011). specifically, the findings indicated that practitioners may not be consistently conducting swot as a structured business process. this feedback is particularly insightful and actionable for practitioners because establishing a more structured business process for swot is an optimal condition that is actually within the control of an organization’s capabilities. in contrast, while practitioners were conducting swot in a stable market environment over the last decade, the relative stability of the market environment is outside of the control of an organization. as such, the optimal conditions as proposed by ghazinoory et al., (2011) reveals a void in that a more robust swot model may be needed for unstable market environments. although beyond the scope of this study, exploratory findings suggest that practitioners may already be experimenting with new ways to build a more robust swot model. for example, the analytic technique used most frequently in combination with swot among practitioners today was environmental analysis which is focused exclusively on better understanding disruptions in the macro-environment and often falls under the responsibility of a ci function. practitioners may be using environmental analysis to overcome this void with swot and as such, additional analytic techniques may offer a starting point in strengthening swot for more volatile macro-environments. this study represents one of the first empirical studies to capture feedback directly from practitioners on how swot is conducted in the workforce today. the 40 findings identified the problem areas that still persist and the suboptimal condition that may be undermining the value of a swot. collectively, these findings provide a roadmap for future research to develop a stronger and more robust swot methodology that better serves current practitioners. 6. conclusion the present study was a pilot test and represents one of the first attempts to empirically evaluate the swot process among current day practitioners. the results of the study help to close the academicpractitioner divide by identifying four ongoing issues with swot and revealing the suboptimal condition from the literature that still persist among practitioners. a few limitations in the present study included potentially ambiguous questions related to swot, the relatively small sample size, and the limited sampling frame during survey collection. in order to mitigate these concerns, a pre-test for the survey instrument was conducted to identify and correct any issues with question ambiguity before beginning survey collection. furthermore, filter questions and invitations to strategy and intelligence-specific linkedin groups were used to ensure a representative sample of the target population. although the sampling frame is limited, the respondents in the sample reflect the target population of practitioners who have conducted swot in the workforce and as such provide invaluable insights. future research efforts could focus on establishing a clearer understanding of why some problems persist with such a longstanding strategic management tool and whether new solutions could help practitioners overcome these problems. for example, such research could explore the role business and intelligence programs play in training practitioners on swot and how that may impact the manifestation and persistence of these problems. research could also explore whether conducting swot in collaboration with new technologies or additional strategic management tools could offer solutions for practitioners to overcome these issues. another opportunity for future research is to more clearly define the optimal conditions for conducting swot. this could prove highly relevant as practitioners conduct swot while navigating unique market dynamics or disruptive technologies (e.g., artificial intelligence) at any given time. for example, such research could explore whether practitioners agree that conducting swot as a structured, step-bystep business process is the best practice during more turbulent markets. furthermore, research could explore opportunities for practitioners to incorporate other strategic management tools at various steps within the swot process to strengthen and build a more robust strategic management tool that can adapt to both stable and unstable macro-environments. the application and adaptation with other analytic techniques identified in this study may offer a starting point. the practitioner feedback captured by this research provides a roadmap for future research to continue elevating the managerial relevance in the swot literature and closing the academicpractitioner divide on one of the most popular strategic management tools today. the authors would like to acknowledge [mba graduate assistant, university] for assisting with survey development. the authors of this paper hereby affirm that the submission has not been previously published and has not been submitted to or is not under review by another journal or under consideration for publication elsewhere, and, if accepted, it will not be published elsewhere in the same form, in english or in any other language, including electronically without the written consent of the copyrightholder. the authors also affirm that there is no conflict of interest. the anonymized research data will be made 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(2006). “towards a new definition of intelligence”, stanford law & policy review vol. 17, pp.319 – 330. world bank. “inflation, consumer prices for the united states [fpcpitotlzgusa]” available at https://fred.stlouisfed.org/series/fpcpitot lzgusa (accessed 17 march 2023). https://fred.stlouisfed.org/series/gpdi https://fred.stlouisfed.org/series/pce https://fred.stlouisfed.org/series/unrate https://fred.stlouisfed.org/series/unrate https://fred.stlouisfed.org/series/fpcpitotlzgusa https://fred.stlouisfed.org/series/fpcpitotlzgusa 51 an evaluation of business intelligence software systems in smes – a case study mattias nyblom, jenny behrami, tung nikkilä, klaus solberg søilen* *(corresponding author), halmstad university, box 823, 301 18 halmstad, sweden e-mail: klasol@hh.se received february 5, revised form 10 may, accepted 25 may 2012 abstract: this article proposes a simple model for evaluating the performance of business intelligence software systems based on what companies themselves find to be most important; efficiency, user friendliness, overall satisfaction, price and adaptability. companies want to know the different systems used, why they are used and how effective they are for different tasks. they are also concerned about the systems’ compatibilities. the study builds on a deep interview with eight swedish smes. the results show what terms are used by users, how they have solved their information needs and what problems arise in each company. it also shows that the decisions about what system to use are related to the experience specific individuals have had in other companies. keywords: business intelligence, software systems, business analysis, decision support 1. introduction in today's competitive environment companies’ “business intelligence software systems” have become a central concept. in the fierce competition that exists, it is important for a company to have efficient and effective software systems to collect, process and store data of various kinds. for example, you have to have a good system for customer management finance and so on. however, today there are so many different systems for these tasks that it has become important and meritorious for companies to handle the differences between these different systems. it is important to know what business intelligence software system is, which different systems that are used and how to use them. in this article we have chosen to examine these issues more closely by going in depth with the concept of business intelligence and examine how a few different companies use them, to bridge a gap between theory and practice. business intelligence is a general term for a variety of functions that support effective decision making within a company. in swedish, we often call it business analysis (affärsanalys) or decision support (beslutsstöd). the most common terms usually used in business intelligence are market analysis, environmental analysis, customer analysis, data mining, business activity monitoring and competitor analysis. the foundation of business intelligence is to have access to right information at the right time for decision makers in order to make the right decision. it is therefore important to have effective systems that can help the company to collect, store, compile and process data in different ways. such a system is called business intelligence software system. sabanovic and solberg søilen (2012) have previously examined companies’ available for free online at https://ojs.hh.se/ journal of intelligence studies in business 2 (2012) 51-57 mailto:klasol@hh.se https://ojs.hh.se/ 52 expectations and need in terms of business intelligence systems. companies have long used various business intelligence software system but these have never been so numerous, extensive, and advanced as today. this is also likely to continue, so that the technology tested here in this article will soon be outdated. an evaluation model however can be useful over time. it is important for companies to know about the different systems actually used today to find the system that best suits their business. there are reasons to believe that there is a discrepancy between theory and practice in this field, between what companies actually use and what the textbooks suggest they use. this is a particular problem for smes who do not have the resources to purchase tailor made business intelligence solutions. we also want to know why they are using the systems they have in place. 2. method this study started with a different purpose than it has now. the work began as a comprehensive survey of business intelligence software systems. the aim was to make a quantitative survey where we would get answers on business intelligence software systems from 50 different companies and then generalize and make conclusions. we began the study by sending out a questionnaire by mail to 274 companies. the companies were selected by a random generator that randomly selected 274 companies independently of their size, geographical location and industry (http://www.slump.nu/). the reason we decided not to have limitations of our sample to industry, geographic area or company size is because we believe that all the above factors have little or no impact on the research and the answers we wanted to get. the only restriction we had when it came to selecting respondents is that we would only contact companies in sweden. after a while we realized that business intelligence is a diffuse area to investigate in several ways. firstly, the term business intelligence is relatively new in sweden and companies have not really grasped what it is. we also reached the conclusion that it is a complex area to investigate since companies do not want to give out more information than necessary, since they suspect that this might be used to their disfavor. the answers were, in other words, difficult to obtain. we therefore restructured the entire work and instead of doing a quantitative study we chose to do a qualitative study based on a case-study method in which we examined a handful of companies in more details through deep interviews, to find out what system they use and how they experience how their system works for them based on a series of aspects. a case-study method is used in researches with purpose to study exclusively on a number of small selected cases (onwuegbuzie, johnson & collins, 2009). one of the goals with the case-study is to analyze and interpret attitudes and opinions from the selected sample toward a particular studysubject or object. another aspect that we took into account when we chose a case study is its’ usefulness to get answers according to matters like "how" and "why", which relate straight to the purpose of this article (cepeda and martin, 2005). thus this method was suitable because we wanted to narrow down the selection of the companies and do some deeper research into their practices. finally, we chose eight companies to work with, swedish smes. we came in contact with these companies when we did the quantitative study. in other words, we took the eight companies that were willing to answer our questions. we interviewed one person at each company and asked questions about the systems they use and how they would evaluate them. based on their own criteria we then evaluated each one based on our conversations, in the form of deep interviews. we also compared information about the companies and the information about each system from their respective websites. 3. empirical data we have contacted eight companies with questions about their business intelligence software systems. we have also looked more closely at what these companies are doing and how their information need looks like. below we present the information we received in a summary: 3.1 company 1: kungsäter industri kungsäter industri has been around since january 1972. it is a company focusing on making-up, i.e. drawing, cutting, pressing and merging technical textiles to large and small products. the number of employees in the company is around 50. most of these are in production. they manufacture products such as tents, floor cloths, door screens, covers, sheets, tablecloths and other silo solutions in technical textiles. all products are made according to customer order and customization. the company has a turnover of more than 50 million sek a year. the company uses a system called pyramid. this is a business system that is designed for both small and medium sized companies in several industries. http://search.proquest.com.ezproxy.bib.hh.se/docview.lateralsearchlink:lateralsearch/sng/author/onwuegbuzie,+anthony+j/$n?site=abiglobal&t:ac=219052535/record/1337576a0542eaca6f0/4&t:cp=maintain/resultcitationblocks http://search.proquest.com.ezproxy.bib.hh.se/docview.lateralsearchlink:lateralsearch/sng/author/johnson,+r+burke/$n?site=abiglobal&t:ac=219052535/record/1337576a0542eaca6f0/4&t:cp=maintain/resultcitationblocks http://search.proquest.com.ezproxy.bib.hh.se/docview.lateralsearchlink:lateralsearch/sng/author/collins,+kathleen+m+t/$n?site=abiglobal&t:ac=219052535/record/1337576a0542eaca6f0/4&t:cp=maintain/resultcitationblocks 53 it is designed to be used to finance, logistics, crm, manufacturing, e-commerce, project management and more (see www.unikum.se). kungsäter industri is using pyramid as a crm system, for example to manage information about their customers, and process it in a flexible way. according to our contact they are using this system because they think it is easy to handle and because they do not want to venture into a more advanced system for feelings that it will take too much time, be too expensive and too complicated for their needs. the company may consider switching system in about three years if the company evolves as they hope for. right now, they believe that they have a too small customer base for it to be necessary to engage in a more advanced system. 3.2 company 2: tidbecks tidbecks was founded in 1840 and has been around for over 170 years. over the years the company has evolved with time and is today a modern engineering company. tidbecks manufactures and supplies welded netting, welded mesh, crenellated grille, crenellated networks, customized wire products, wire mesh and stretch materials. the company has currently 34 employees in total and they have a turnover of approximately 60 million sek per year. the company uses a system called monitor. this is a system that can be used in the fields of manufacturing, purchasing, sales management (crm), warehouse, workshop information, and accounting. it is a complete business system designed for manufacturing companies (www.monitor.se). tidbecks is using the system for accounting and customer management. they believe it is a good program where they can store all the information they have in order to compile it into various documents. the reason why they have chosen to work with monitor is that they have previous knowledge of the program from another company where some of the staff were employed. our contact says that they sometime in the future may consider switching system to a more comprehensive system, but they are not sure about what they will use then. 3.3 company 3: evaldssons evaldssons’ has been around for 60 years. it is a construction company that undertakes all kinds of missions within the area of construction such as new construction, service, maintenance and repairs. they are specialists in construction, flooring, tiling and painting. the company has 30 employees and their turnover is around 35 million sek per year. complementary to sell the construction the company sell materials and products needed in construction such as tiles, different floor types, boards, plates, racks and other building materials. this is sold through an online shop. the company uses a system called visma. this is a business system that is comprehensive and can handle many business areas within a company. visma has a range of programs you can use depending on the company’s purpose with having the system. for example, the user can use the business system for financial statements, billing, payroll, training, sales support, customer support, logistics, time, projects, e-commerce, information storage and cash solutions (www.visma.se). evaldssons is using the system in all its activities and have therefore a custom made concept. according to the contact, the most important feature of the system is the customer management application. the reason why the company choses to use this system is, according to our correspondent, that the program is very well-made and has been on the market for quite some time. she also states that, as visma-customer, you have technical support 24 hours a day and this is the best feature with the product. despite the good qualities of the program, they do have plans to change the system in the near future. this is because they want a more internetbased system with larger capacity. she says visma is fine until they replace it and it has always worked for the company. 3.4 company 4: cejn cejn ab was founded by carl erik josef nyberg in 1955. cejn started their business in a basement in skövde with two employees. carl erik josef nyberg created a revolutionary quick clutch, which overcame many of the old models' deficiencies. the new clutch dramatically simplified the handling of compressed air and creates reliable and efficient connections. the invention laid the foundation for much of cejn modern product line, and was the starting point for cejn´s commercial success in global markets. today, cejn has 17 sales companies, six production units, and 450 employees worldwide (www.cejn.se). the company’s design is based on small external measurements and large internal measurements. in other words, their standard couplings have high flow capacity while being robust and easy. the company supplies the global market with high performance couplings and systems for hydraulics, compressed air, liquids and gases. the company’s product range also includes accessories such as adapters, hose, hose reels, air handling units, and http://www.unikum.se/ 54 blowguns. with a focus on customer satisfaction, cejn are focusing on innovative solutions that lead to a superior product. the company’s product range can be complemented with other products that meet its requirements for quality and performance (www.cejn.se). cejn’s strength lies in their intelligent technology solutions, along with high quality and efficiency. they are developing not only what is in demand today, but also takes the unexpected paths towards future development. the company strives to maintain the market leader position in high pressure hydraulics and intends to become a world leader in the plug-in technology for medium pressure hydraulic applications. the business intelligence system that cejn is using is simply excel, which may come as a surprise for such a large company. excel is a system written and distributed by microsoft. it features calculation, graphing tools, pivot tables, and a macro programming language called visual basic for applications. excel uses a grid of cells arranged in numbered rows and letter-named columns to organize data. it even now comes with a business intelligence add-in (www.office.microsoft.com). cejn also uses excel as a crm system. the reason they use excel is because it is simple to use and they have knowledge about it which means they don’t need to put effort and time to acquire the skill to use another system. cejn is satisfied with the system and does not want to change to another software. they would like to change to another system if the company grew bigger but right now they don’t have any plan to expand. 3.5 company 5: matthews swedot ab matthews swedot ab was founded in 1850. the company works with custom marking solutions and standardized marking solutions for various industries, such as marking of milk cartons. they also offer solutions for industries that require extra security, such as anti-counterfeit marking and security marking, for example the pharmaceutical industry. the company is american owned and it is also here that they have their headquarter. matthews swedot ab has 41 employees in sweden and the company is represented in countries such as germany, france and australia. the company uses a business intelligence software system called caesar crm. the system is suited for large companies and offers solutions for sales, marketing and management amongst other functions (http://www.caesarcrm.com). according to the contact the enterprise use the system to manage clients and record information about what the customers bought, as well as information on service visits. it can be likened by a sort of customer journal. the contact says that the reason for the choice of this system is because it is easy to use. the company has no plans to change the system because they are satisfied with how it works. the interviewee says that it is an efficient system that is adaptable to the company, but that the price is a little bit too high. 3.6 company 6: european furniture group european furniture group made its first windsor chair in 1885 in tranås, sweden. since then the company has grown into an international company that manufactures office furniture with a turnover exceeding 1000 million sek in year 2010. the corporation has 540 employees of which 300 works in sweden. their production, which takes place in sweden, denmark and finland, are driven by customer needs, which requires a functioning business intelligence software system. the company supplies more than 2000 complete workplaces, within the standard range, every week and most of them are ordered directly from the customer. according to the contact the company has just replaced its old business intelligence software system which is called sales maker with microsoft dynamics crm. the contact says that microsoft dynamics crm basically is a crm system, but that they also use it to make competitor analysis, manage products and information on quotes sent to customers. the contact also said that the company uses microsoft dynamics crm for the reason that it is easy to work with and because it is compatible with microsoft outlook, but also because it is suitable for the company's size. furthermore, the interviewee consider that the system is efficient and user friendly. the company is also pleased with the system and believes that it is adaptable to their business needs, but that the price is too high. 3.7 company 7: visiosign sverige ab visiosign has existed in sweden for almost two years. it is a subsidiary of parent company visiosign a / s, founded in 1999 in denmark. visiosign is a company with a focus on internal communications and digital signage. the main product is a software called info board. it can be divided into several different fields where you can link different information sources depending on what the customer wants. all solutions visiosign http://www.caesarcrm.com/ 55 makes are custom made and the company puts time to keep personal contact with existing customers. thus the software is to be rented while the hardware is bought off by the customer. there are only two people and a temporary assistant who works at the company in sweden. but there are about 300 employees who work at subsidiary companies and mother companies. the subsidiary's turnover is about two million, and there is a limit to what information they have as the company is newly established in sweden. visiosign uses a business intelligence system that is called insightly. insightly is a web based customer relationship and project management system. insightly is integrated with google docs, gmail and google calendar. the system uses google apps for login and authentication, so the user does not need to remember multiple passwords. insightly is a tool for the vital task of managing the company’s contacts and related organisations, partners, vendors and suppliers. the user can see everything about a contact on one page. insightly also links each contact to the people and organisations around them showing the relationships between contacts and employers, partners, suppliers, competitors, and co-workers (http://www.insight.ly). visiosign chose insightly because the system meets the company’s requirements. they also chose it because it is web based and inexpensive. visiosign is satisfied with the system and does not want to change to another one. the cost for the system is reasonable from the company’s point of view. they also think that the system is effective, user-friendly and adaptable. 3.8 company 8: creative tools creative tools ab operates as a department of a design and media company. it was established as an independent company in 2004. originally creative tools ab was a corporation between two companies: enthed animation and opus media tech. the company’s customer database, expertise, partnership and business relationships in the industry, was established early in the 90's. creative tools ab sells products and services for the production of 3d animation, visualization, and video. the company is owned and operated by paulo kiefer (ceo) and mona kiefer (marketing manager). the company offers its customers computer graphics software and hardware for their needs. creative tools ab also offer education in computer graphics applications, and various production techniques online. the company’s customers are game developers, architects, photographers, and visualization companies, animators, designers, interior design firms and advertising agencies. their customers range from private individuals, students, freelancers, to big international companies (http://www.creativetools.se). the company’s turnover in 2010 was 18 329 million sek with a profit of 614 000 sek. their turnover has been increasing steadily since the company was established. creative tools ab uses a business intelligence system called vtiger. vtiger is a crm system which “is a community-driven, fully open source, crm software. it enables small businesses manage leads, sales opportunities, quotes, invoices, support tickets, knowledge base, inventory and more. vtiger crm is used every day by over one hundred thousand businesses worldwide” (http://www.vtiger.com). the reason creative tools ab uses vtiger is because it’s free, complete and adaptive. they are satisfied with the system and have no need to change to another one. they give the system a four grade for its effectiveness and user-friendliness. the company has a positive attitude towards the system and is satisfied with it. 4. analysis theory states that companies use bis in different areas within the organization. this means that not only top management can benefit from the bis, but that also management lower down in the hierarchy can use this tool in order to access information and make better and quicker decisions (mohamed, philip & michael, 2008). this fits with the findings in this study. we found out that most of the companies we have been in contact with uses bis for managing clients, to get consolidated information in a quick and easy way. in order to do this you need to have an effective system. as can be seen in the table below and from the interviews we found that monitor and microsoft dynamics crm, which is used by tidbecks and efg, is the most effective systems among the eight different systems we received information about, according to the companies themselves. both companies rated the effectiveness of the systems with the highest grade. they stated that their systems help them significantly when handling information about their customers. the systems which have been graded lowest is the system pyramid, which is used by kungsäter industri and excel which is used by cejn. further, we can see a correlation between how effective and how user-friendly the systems http://www.creativetools.se/ 56 are. the more efficient the system is the higher the companies valued the ease of use and vice versa. the only company that deviates from this is cejn which stated that excel is average when it comes to effectiveness but exceptional when it comes to user-friendliness. with ms excel there is an add-in called powerpivot which enhances its business intelligence capabilities. in order to move forward in the research of business intelligence it has been suggested that there is a need to evaluate the different components of a bis. one area that can be analyzed, for example, is if the system is easily integrated with other systems (compatibility). a company should evaluate their potential bis to see if the system is well suited for the company’s total it solutions to achieve better support in its decisions (ghazanfari, jafari & rouhani, 2011). when we relate this with the companies that we have studied, we see that the concern mentioned above, that the system integrates easily with other systems, are taken into account. all of the companies except kungsäter industri think that their system is easily integrated with the existing systems in the company. there is going to be other systems that are better suited for the company. today there are so many different business intelligence software systems that it is of value for all companies to evaluate the different components of a business intelligence system in regards to their total needs. by doing this, the company can see if they are using a system that suites their company´s needs well and if the system used is worth keeping. by looking at the table below, which consists of factors that could be analyzed when evaluating the system and the values each company have accorded to their own system, we see that there are companies in this study that can benefit from reevaluating their system. company system efficiency user friendliness satisfaction price adaptability tot: kungsäter industri pyramid 3 3 3 2 2 2.6 tidbecks monitor 5 5 5 4 5 4.8 evaldssons visma 4 4 4 4 4 4.0 cejn exell 3 5 4 5 4 4.2 matthews swedot ab ceasar 4 3 4 3 4 3.6 efg microsoft dynamics crm 5 5 5 4 5 4.8 visiosign insightly 4 4 4 5 4 4.2 creative tools vtiger 4 4 4 5 5 4.4 5. conclusion business intelligence software systems is still a relatively unknown term in sweden and most of the companies we have been in contact with have little knowledge about the term. we noticed that companies better understand what we speak about when we reformulate the term to “decision support” or “business analysis”. in further research it may be interesting to look into why companies find certain business intelligence software systems effective (underlying factors). it may help further researchers in their work to get more accurate answers if they reformulated the concept of business intelligence into a language that people are more familiar with from the start. we have seen that all of the companies we have been in contact with use different business intelligence software systems without knowing that the systems they use falls under the umbrella business intelligence. we have also seen that most companies are in great need of their existing systems, to create value added and simply to compete. the systems help them in their daily work, especially when it comes to managing information about their customers. the survey created a better understanding for some of table 1: companies and business intelligence systems evaluations 57 the values of the systems. we see that the companies with the lowest average value are kungsäter industri and matthews swedot ab. both of these companies would be advised to do a more extensive evaluation of their systems to see if there is another system on the market that creates more value. considering how many different systems that exist and how much they differ from each other, it is important to possess knowledge of the different systems in order to find out which of them are best suited for a specific company. the companies we studied have found some factors that are important to them in their choice of system. this should be of value for developers and sales people. we have found that features such as efficiency, simple concepts and adaptability of the system are of importance. it is of value to possess a system that is simple to learn and understand. because bi systems are highly complex it is also important for a company to find people that already have knowledge of different systems when recruiting new employees, especially as it seems that new people often bring with them a change in bis systems. we see that the aspects of different business intelligence systems are very different and that their degree of sophistication is different, to the point where 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(2019) making sense of the collective intelligence field: a review. journal of intelligence studies in business. 9 (2) 6-18. article url: https://ojs.hh.se/index.php/jisib/article/view/405 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index making sense of the collective intelligence field: a review klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article making sense of the collective intelligence field: a review klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se received 3 june 2019 accepted 15 september 2019 “the world is bitterly, savagely competitive and intensely, vigorously cooperative, by way of alliances and partnerships, thus rapidly changing individuals and social systems alike.” “we are pulled toward a single social system on earth.” dedijer, 1999, p. 72 abstract the problem we want to solve is to find out what is new in the collective intelligence literature and how it is to be understood alongside other social science disciplines. the reason it is important is that collective intelligence and problems of collaboration seem familiar in the social sciences but do not necessarily fit into any of the established disciplines. also, collective intelligence is often associated with the notion of wisdom of crowds, which demands scrutiny. we found that the collective intelligence field is valuable, truly interdisciplinary, and part of a paradigm shift in the social sciences. however, the content is not new, as suggested by the comparison with social intelligence, which is often uncritical and lacking in the data it shows and that the notion of the wisdom of crowds is misleading (rq1). the study of social systems is still highly relevant for social scientists and scholars of collective intelligence as an alternative methodology to more traditional social science paradigms as found, for example, in the study of business or management (rq2). keywords collective intelligence, social intelligence, social systems, wisdom of crowds 1. introduction the popularity of the collective intelligence research area has increased significantly. the web of science lists 552 article with the term in the title, the first of which was written in 1989. the last 500 articles were written since 2005. research groups at the most prestigious universities receive grants to establish separate research centers and the ideas have received significant interest from the general public as well as politicians. at the same time the phenomenon seems old and familiar in the scientific literature. moreover, the field seems to be highly interdisciplinary and does not seem to fit into any of the established business, management or social sciences disciplines. so, what is new and valuable in this field of how we learn and make decisions together? (rq1). in addition, how are we to understand where collective intelligence fits in a larger social science context? (rq2) the research gap suggests that there is no critical review article journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 6-18 open access: freely available at: https://ojs.hh.se/ 7 that examines the phenomenon of collective intelligence from a historical context where the aim is to understand what this body of literature is about. 2. method this article attempts to answer the research question through the historical method, comparing what has been written in the past about learning together to the spread of collective intelligence during our own time. moreover, the attempt is to compare the collective intelligence literature to that of social intelligence. social intelligence was present in the 1970s, at the start of what became intelligence studies in business. the sources are scientific articles, books, internet articles and videos. i have attempted to follow a theme, inevitably missing much relevant information as the phenomenon is so wide and spread over synonyms containing the words intelligence, collaborative, collective, crowd, group, knowledge, open source, smart, social, and connectivity, just to mention some of the most relevant. the methodological problem here is first one of what articles to select and why. i have chosen to read the most cited articles first, the most popular non-scientific sources and what can be deemed significant scientific contributions over time, including books. this limited the sources down to less than fifty relevant publications, where about half are listed as references here. in terms of scientific articles, there were about thirty that had twenty or more citations in the web of science. all of them have been included here. i have not cited sources i have not read in their entirety. only a few have been discarded, as they were too technical. there are numerous limitations in this study. leading articles and leading scholars are reduced to citations on web of science and google scholar, which does not give the full picture. further, it would be interesting to go deeper into each of the disciplines mentioned in the articles, both when it comes to definitions, but more important to their actual meaning and content to detect similarities and differences, but also to investigate the theories and experience they build on. part of this is due to the limited number of pages allowed in the article by the journal. 3. literature review in 1886 francis galton, a cousin of charles darwin, wrote an article called “regression towards mediocrity in hereditary stature” which showed that there was a regression towards the mean with larger numbers. this was statistically proven by for example having a large number of people guess the weight of an ox at a fair. as the number of responses increased, the average guess ended up reflecting the actual weight, showing a simple linear regression of data points. the technique was useful for simple questions demanding numerical answers, but galton thought, as the title suggests, that the logic would lead to “mediocracy” when applied to other problems. this critique was considered common sense at the time, supported by scientists, humanists and men of letter alike (from henry david thoreau to friedrich nietzsche). however, despite the critique, the idea was useful in statistics and received renewed attention with the rise of computer science and in particular big data and now with artificial intelligence and digital marketing, for example when counting averages such as webpages visited or number of clicks on a webpage. this tells us about peoples’ behavior online. web 2.0 caught on during the first decade of the new millennium, the idea of creating content through interaction and collaboration using social media. in rapid succession, facebook was founded in 2004, youtube the year after and twitter the year after that. when competitors arrived, they were simply bought up, guaranteeing near-monopolies for the new data giants. due to the large amount of data collected, these companies are now able to predict our behavior more accurately as they collect more data on and from us. researchers saw this development coming, thus in 2002 howard rheingold argued that the most successful services in the future would not be hardware devices or software programs, but social practices online. in 2004 a young american journalist james surowiecki wrote a book with the provocative title “the wisdom of crowds”, based on galton’s idea. however, surowiecki takes the idea further delving into economics, rejecting adam smith and other economists for their focus on specialization. instead, he argues for decentralization: “decentralization's great strength is that it encourages independence and specialization on the one hand while still allowing people to coordinate their activities and solve difficult problems on the other”. (p. 71). 8 in other words, valuable information may not come through when only a few are in the know. he gives the example of the cia. the original idea of having a centralize intelligence agency as defined by bill donovan was later abandoned as the agency grew and more departments were established. these departments did not succeed in cooperating and sharing information, a consequence of which was the attacks on september 11th, 2001. the problem was timely and the book became a bestseller. “the congressional joint inquiry into the attacks found that the u.s. intelligence community had ‘failed to capitalize on both the individual and collective significance of available information that appears relevant to the events of september 11.’ intelligence agencies ‘missed opportunities to disrupt the september 11th plot,’ and allowed information to pass by unnoticed that, if appreciated, would have ‘greatly enhanced its chances of uncovering and preventing’ the attacks. it was, in other words, pearl harbor all over again.” (surowiecki, 2004; p. 68) surowiecki draws a parallel to galton’s contributions, but a critic may argue that the information workers at the cia are not your average visitor to the fair guessing the weight of an ox. the author is mixing experts and professionals with average people. quiz games are a good counter example; you only stand a chance of winning if you can manage to gather knowledgeable people on your team. if you make up the team with those who just happen to walk into the pub that evening your team will have a small chance of winning. lanier (2006) notes that the collective is more likely to be smart only when: 1. it is not defining its own questions, 2. the goodness of an answer can be evaluated by a simple result (such as a single numeric value), and 3. the information system, which informs the collective, is filtered by a quality control mechanism that relies on individuals to a high degree. lanier argues that only under those circumstances can a collective be smarter than one person. if any of these conditions are broken, the collective becomes unreliable or worse.” (wikipedia). another critical point is made by tammet (2009), who argue that in systems of pooling knowledge, like wikipedia, experts can be overruled by less knowledgeable persons. thus it is important to build software that immediately alerts the experts when changes to the entry are made and allow discussion on the issues, saving these for other users to partake in to judge who is right. to build this system as a galton-average-towards-the-mean would not work. in other words, wikipedia works well because it pools smart people, despite the disturbance of less smart individuals because there are special mechanisms built into the system to deal with their erroneous entries. maybe the best counter argument was a game of chess held in 1999 called “kasparov versus the world”, where the chess player played against over 50 000 people from more than 75 countries deciding moves by plurality vote. an expert system was put in place whereby four highly rated players (fide ranking) suggested moves first. these suggestions were mostly followed by ‘the world’. kasparov won despite the experts, but he admitted it had been a tough match. if kasparov had played against an average move we can assume that he would have won easily. instead it must be suggested that the wisdom in the crowd is a romantic idea that fits well with the reigning democratic political ideology in the western world and the equally dangerous belief that advancements in computer science will solve collective problems. it will certainly solve some, but new dangers will arise, as we saw with the invention of nuclear energy. surowieci is right when he says that “the idea of collective intelligence helps explain why, when you go to the convenience store in search of milk at two in the morning, there is a carton of milk waiting there for you, and it even tells us something important about why people pay their taxes and help coach little league.” (p. xiv), but not of the reasons he describes. there is milk in the store because the store managers knows how many customers buy milk on a specific weekday. the more of his business he can digitize the better information he will have on customer’s’ behavior. his other example is that many people pay their taxes because they know that it benefits all in society including themselves, especially as they get older. of course, most pay taxes because they 9 have to and do what they can to avoid paying them. so, these are not good examples of what the author wants to convey. looking at research during the past decade: among the more cited research articles in the field are woolley et al. (2010), presenting a short empirical experiment, where they found that social sensitivity and proportion of females explains why some groups work better together. in experiments like these, it’s difficult to know what are the causes and effects, and it may be that iq or other factors are better explanatory variables. woolley et al. publish another article in 2015 with the same test, but it’s difficult even to assess this one as it’s short and does not describe the method, analyses or show data. engel et al. (2014) argue that the same findings are just as true in online environments. the authors define collective intelligence as “the ability of a group to perform a wide variety of tasks” or “the general ability of a particular group to perform well across a wide range of different tasks”. this is different from other definitions, for example as defined in wikipedia: “the intelligence that emerges from collaboration, collective efforts and competition among individuals”. furthermore, there is an understanding in these articles that collective intelligence implies that the sum of the efforts from all individuals in the group are greater than the sum of each individual’s contribution, so that 2+2=5, as it were. this is an attractive idea, but there are no good empirical experiments that confirm this assumption. it may be true in some cases, as when members of a quiz team only know parts of an answer each but become convinced when they pool their arguments together, making a strong case for a specific idea, but then again we are dealing with experts not with the average person. there is one mathematical paper that addresses this problem. nguyen (2008) shows how the intelligence of a collective can be larger than the intelligence of its members through mathematical modelling. “these examples show that the relationship between the intelligence of a collective and the intelligences of its members is not linear” (p. 543). “thus, with some restrictions, one can claim that the hypothesis a collective is more intelligent than one single member is true.” (p. 561). however, the paper builds on the implicit assumption that every member knows the same and for example is not wrong on a specific issue, which can cause confusion in a group. knowing this the assumptions can hardly be said to be realistic when dealing with crowds. it is the same certeris parabus we find behind most of what has been written about economics since the second world war, we assume that all rational individuals can weigh alternatives and draw the right conclusions based on them. individual and cultural differences (reality) tend to destroy most of these social science models. we can also say, it’s the weakness of linear logic. when looking at videos on collective intelligence, bees and ants are often used as analogies to show what can be achieved in the social sciences. there is both substantial and interesting research on the behavior of bees and ants performed by natural scientists. the first time the term ‘collective intelligence’ appears in research is in a study of ants (franks, 1989). “the sharing and collective processing of information by certain insect societies is one of the reasons that they warrant the superlative epithet ‘super-organisms’ (franks 1989, p. 138).” but the comparisons between species, even different kinds of bees, are more complicated, as franks et al. remind us of in an article from 2002: ”nevertheless, both species do make use of forms of opinion polling. for example, scout bees that have formerly danced for a certain site cease such advertising and monitor the dances of others at random. that is, they act without prejudice. they neither favour nor disdain dancers that advocate the site they had formerly advertised or the alternatives. thus, in general the bees are less well informed than they would be if they systematically monitored dances for alternative sites rather than spending their time reprocessing information they already have.” (p. 1583) more to the point, people are not bees or ants and no one would like to be one, i believe, or to live according to their motives. this comparison is what is thought of as a mechanical worldview in the business literature. at the end it brings associations to fascism, hardly an attractive metaphor. instead we as human beings enjoy our irrationalities, our cumbersome ways even our flaws. it is part of what makes us human. this is no denying that human are animals, but our behavior seem to be substantially different from those of ants and bees in general making the parallels of limited value. 10 the most cited article on collective intelligence and honeybees by rajasekhar et al. (2017), argue that the algorithms developed over the past twenty years to understand their behavior are not well adapted to real life problems. the authors refer to an article by sörensen (2015), who express his concern on the current trends in metaheuristic research (i.e. higher-level procedure or heuristic designed to find, generate, or select a method for solving problem) in the following way “… it seems that no idea is too far-fetched to serve as inspiration to launch yet another metaheuristic. …we will argue that this line of research is threatening to lead the area of metaheuristics away from scientific rigor”. “the ideas should be presented in a metaphorfree language and more directly” (in rajasekhar, 2017; p. 45). in everyday business life a good collective intelligence system is developed as some sort of a business intelligence software. thus valuable contributions to the field of collective intelligence will continue to come from software development. this is a continuation of web 2.0, a comparison which has its own problems: “the most hyped examples of collective intelligence applications have been labeled as “web 2.0” applications. web 2.0 is an amorphous term used to define a computing paradigm that uses the web as the application platform and facilitates collaboration and information sharing between users” (gregg, 2010; p. 134). “the shift to a collective intelligence paradigm requires software developers to have different ways of thinking about how their how software might be used and what features would enable better visualization and use of information among groups of people. the new breed of collective intelligence applications needs to center around user defined data that can be reused to support decision making, team building, or to improve understanding of the world around us.” (p. 134). collective intelligence in this sense and for this group of researchers means developing new and better business intelligence software for collaboration. lykourentzou et al. (2010) sees collective intelligence as a continuation of a wiki. the authors present what they call a corpwiki, “a self-regulating wiki system for effective acquisition of high-quality knowledge content” (p. 18). “inserted articles undergo a quality assessment control by a large number of corporate peer employees. “. this is close to the description of a software the author of this paper developed in 2004 called subsoft, which never made it passed a beta version but was tested in local government organizations, not that it was unique. the core research question of the center for collective intelligence at mit is “how can people and computers be connected so that – collectively – they act more intelligently than any individuals, groups, or computers have ever done before?” (leimeister, 2010). this understanding is not that different from how software developers work. software is not developed in a vacuum but with the users’ needs in mind, users who become ever more collaborative. the software simply reflects this reality with continual technological discoveries, giving rise to new product developments. just as with the effort to advocate for open source in software development, there are efforts to influence how collective intelligence systems are made, so as to make them more beneficial for all. we are now in the domain of political science and law. schum et al. (2012) argue that the software should not be restricted to “government, scientific or corporate elites, but be opened up for societal engagement and critique” (p. 110). basically, what is suggested is not that different from wikipedia, but with some policy improvements on criteria: there should be: “transparency of data sources, algorithms, and platform use – control of users over their personal data – privacy-respecting data mining – self-regulation, self-healing – reliability and resilience – promotion of constructive social norms and responsible use – crowd-based monitoring of platform use, involving non-profit organizations – tools to alert problems and conflicts, and to help solving them – incentives to share profits generated from data and algorithms provided by users – mechanisms for managing unethical use.” (p. 112-113). thus, we may already make our first conclusion: that the body of literature published under the collective intelligence umbrella is truly interdisciplinary (conclusion # 1). 11 wolf et al. (2015), tests the ideas of collective intelligence to increase decision accuracy on medical decision-making. the authors found that “all ci-rules systematically outperform even the best-performing individual radiologist in the respective group”, and that “the findings demonstrate that ci can be employed to improve mammography screening”. (p. 1). again, in this case it’s experts “multiple radiologists” who give their input. these experiments do not confirm galton’s regression towards the mean but the fact that many experts perform better than one, which is common sense, but also costly and thus less practical in real life. a more promising solution to this problem seems to be artificial intelligence, using computers instead of humans, but that is for another paper on a different topic. a second conclusion is that we are confronted with the phenomenon we may call wisdom of the knowledgeable more than wisdom of the crowds (poking fun at surowiecki, who in turn pokes fun of charles mackay’s article about the ”madness of the crowds”. see mackay, 1841). the logic of crowds works for problems of how much an ox weighs or what the consumption of milk may be tomorrow, but not that well on problems of how to win a quiz tournament, or, closer to home, what goes on in a company or how to understand an industry. if we ask what the capital of senegal is we may get the correct answer among thousands of answers, but how are we to know which one to choose if we are not allowed to check with someone who is smarter, more knowledgeable than the rest (conclusion # 2). wisdom of the knowledgeable is common sense thus a less interesting conclusion. it is not the kind of title to sell books. what we can say is that the observation is reasonable and confirms what we have known for a very long time. there is another problematic aspect of the term ‘wisdom of the knowledgeable’ and that is the question of whether the knowledgeable are truly wise. the wise make decisions based on what is best from the wider perspective, in the long run. being knowledgeable by no means guarantees that we are wise. our modern society is becoming ever more short-term focused (financial markets, profits, product life cycles, etc.), increasing the gap between wisdom and knowledge. another way of saying this is that neither the crowd nor the knowledgeable seem very wise. (conclusion # 3). the next question to consider is whether the literature reviewed on collective intelligence literature is new. the phenomenon studied is part of the topics studied under what we call the information age, preceding the industrial revolution. alvin toffler was one of the pioneers in the digital revolution of the 1970s and 1980s (toffler, 1980). stevan dedijer, a contemporary of toffler, wrote more specifically on intelligence and developed what we call social intelligence. his predecessor at the university of lund, wilhelm agrell, explains in a foreword: “central to his work, his reading and vast correspondence was a concept of what he called social intelligence: the ability of individuals and organizations to orientate in an increasingly complex information environment… stevan foresaw the coming of an age where individuals and organizations alike would become dependent on this ability to collect, process and use information curiosity and insights information and the immense challenge of a coming information explosion” (p. 7) (dedijer, 1999) dedijer was well aware of the contributions that had preceded his own work. “if we look back before web of science and other databases collected that many articles the first insights of ‘organized intelligence,’ ‘social intelligence,’ and of a ‘planetary intelligence sphere’ emerged in the 1920s.” (dedijer, 1999, p. 69). “like mendel’s article in 1903 on genetics, they were totally ignored for decades. walter lippman advocated in his ‘public opinion’ (1922) the use of ‘organized intelligence’ in all fields of government. the philosopher john dewey in the l930s saw ‘organized and social intelligence’ as the only tool humanity could use to avoid the scylla of totalitarianism and the charybdis of laissez-faire market capitalism.” (p. 69). dedijer observed the changes that intelligence was brining during his own time: “the basic intelligence goal for individual countries is changing from intelligence for national security to intelligence for national growth and development.” (p. 67). as such, he also foresaw the change from geopolitics to geoeconomics that luttwak wrote about (luttwak, 1990) and he foresaw that mass communication would lead to “individualization of intelligence”, with users becoming more isolated, self-centered, and egotistic. the crowd would get louder, more 12 daring in its attack. we see this on social media today with the phenomenon of trolls, spilling over to populism and the weakening (not strengthening) of the democratic process (as is implicit in the “wisdom of crowds”). dedijer, who fought in the us military as a paratrooper during the second world war, worked on question of intelligence with the cia and w. colby, its director. the two friends shared information about how they saw the world changing and how the intelligence services should adapt. one of the developments colby did not anticipate was the importance of collaboration: “the second dimension i added to colby‘s intelligence ‘elephant’ was the emergence of development sciences related to the individual, various social systems, and humanity in general. all are engaged in ‘bridge building’ among biological, individual, social, technological, and global intelligence and social systems.” (p. 70). “‘bridge building’ [ – what we call interdisciplinary today ] is the name for current attempts at a holistic approach to all kinds of problems in every discipline or field. one of the best formulations of the bridge-building method is found in mathematics. s. singh in fermat‘s enigma: the epic quest to solve the world’s greatest mathematical problem (l998) tells how a. wiles proved in l995 a conjecture that confounded the greatest mathematicians for 358 years: ‘mathematics consists of islands of knowledge...each one with its own unique language, incomprehensible to the inhabitants of other islands... mathematicians love to build bridges. the value of mathematical bridges is enormous. they enable communities of mathematicians who have been living on separate islands to exchange ideas and explore each other’s creations.’ such bridgebuilding techniques are used in physics, as shown by nobel laureate s. weinberg in the development of individuals as well as social systems, including studies of the state of humanity.” (p. 70). interdisciplinarity of social systems was developed simultaneously, it seems, by a number of people, among whom the more influential included the german philosopher niklas luhmann (1968 and 1984), kenneth boulding (1956) and ackoff (1971) in the us. dedijer believed that the intelligence discipline was going to be valuable for the social sciences, but he also saw the difficulties the discipline was facing due to its unfortunate parallel and association to spying. “because of isolation and confusion among intelligence disciplines and the myth that intelligence is above all espionage, billions of individuals, organizations, and governments today use information technology yet fail to perceive the innumerable signals which tell of a new intelligence revolution in the evolution of humanity.” (dedijer, 1999, p. 71). this is a problem that the collective intelligence literature is also confronted with, by default so to speak, as will any new discipline that uses the term intelligence more in the sense of ‘information’ than ‘brains’. in conclusion, we have shown that collaboration and sharing of information was at the heart of dedijer’s idea of social intelligence. we argue that both collective intelligence and social intelligence is part of the same paradigm shift, like two waves of the same current. just like ai has come and gone with new enthusiasm and interest the past decades, so the ‘information turn’ is visited and revisited with certain intervals and different approaches. we shall understand all of these developments as part of an ongoing intelligence paradigm. this is our forth conclusion (conclusion 4). the term ‘intelligence paradigm’ can be related to systems thinking, as will be discussed further in the analysis below. the term is also used by lahneman (2010) related to international politics and security, and by zadeh, (2008), related to machine learning, but we shall keep these two tracks out. 4. analysis of the intelligence paradigm as systems thinking kuhn (1962) defined paradigm rather broadly as a development that “designates what the members of a certain scientific community have in common, that is to say, the whole of techniques, patents and values shared by the members of the community“. according to this broad definition there could be hundreds if not thousands of paradigms just in the study of economics and management alone. 13 ackoff (1971) writes about the paradigm shift required for the study of management to redirect to systems thinking, referred to as complex systems and complexity theory. the basic idea is that organizations stop thinking of themselves divided into sections such as marketing, hrm, and strategy, but instead as elements that form relationships. it’s the connectivity of the parts that is valuable, not the parts themselves. ackoff’s favorite example is the car. all the parts by themselves are useless, even added together as a sum they give nothing. it’s the right connectivity of the parts that give an automobile that is actually useful and can take us from point a to b. the principles governing how we run business organizations should not primarily be existing departments but the exchange of information, or intelligence. in other words, the private organization is best run as an intelligence organization, much like state intelligence institutions. many successful private organizations today do just that, like the largest wealth management fund in the world, blackrock. its offices and data facilities remind one more of the nsa than a classic bank. most major companies today look much the same, including google, facebook and amazon. the success they achieve is primarily determined by the value of the information they gather and analyze. whether we as employees work in marketing or hr we are spending more and more time learning about new computer systems, electronic gadgets and related services. without these skills we are worth little on the labor market. one problem is that universities and learning institutions often assume that students already know this. the individual disciplines (economics, marketing, hr) are not taking into consideration how these new technologies are changing professions. one example is marketing. students do not know digital marketing when they come to university. actually, that is what they come to learn. if the teacher assumes that these are skills that the students already know and that it’s enough to teach a broad set of general theories, then the education fails. in reality, we have all become information workers during the past generation. the major difference today seem to be that some build the systems (engineers) and others use them (engineers and everyone else). knowledge and skills have never been as important as now. even to work in a factory you need more than a high school diploma. never before in the history of mankind have companies been better at locating knowledgeable people and bringing them together, no matter where they are on the planet. this development matches poorly with the notion of wisdom of the crowd. companies are not hiring just anybody, but are getting better at finding those few who possess supervisor knowledge and experience. there is nothing appealing about the crowd except that all customers of the same product are worth just as much in terms of money (economic reasoning) and that one human life is not worth more than another (our shared human value). instead, the notion of wisdom of the crowd is appealing for political reasons, because it supports the notion that all citizens have a say and can control their own future through democratic elections, which is the basis of western societies. western governments support these ideas because it strengthens the status quo. in the same way, wisdom of the knowledgeable, besides being obvious as a term, thus dull, sounds elitist. the notion of wisdom of the knowledgeable brings up a painful contradiction in western civilization. it indicates a difference between democratic and meritocratic values, which is as old as western democracy and has been actively debated in europe since the early 1960s (young, 1959). to understand the popularity of collective intelligence it’s impossible to ignore these political aspects. politics may be the single most decisive factor for shift in scientific paradigms, not for having the ideas, but getting them implemented. for this reason, it shall be suggested that the intelligence paradigm shift is probably not going to come from the western world, but from asia. the asian way of conducting business and working is already in many ways similar to an intelligence approach. chinese companies thrive by learning from the west, by travelling to foreign countries and copying our products. the whole belt and road initiative (bri) is a gigantic collective and collaborative effort in the spirit of the competitive advantage of nations, an idea we used to master but have forgotten. as a result, it’s not we who know more about asia than they about us but the exact opposite: our students know next to nothing about them, while their students know much about us, and are keen learners. asian companies are not limited by compartmentalized knowledge. instead, they look for useful knowledge where they can find it (what works) and are in many ways better at solving problems. the popular notion is that 14 this is what we are good at, because we are more used to, or allowed to, question things. it was what the western world did well after the enlightenment. since then we have become less curious about the world, less eager to change it and instead more concerned with our own immediate private needs. a tragic example is that our social media applications have made us more isolated, not more collaborative. these services have made us less knowledgeable about the world, not more. dedijer understood this danger well as a leading nuclear physicist: “information technology is only a tool. always ask how effective and efficient it is in terms of improving your capability to identify and solve problems by acquiring and using the information it can help to provide. the it model of the future will more and more be “a thing that thinks’”, as we call artificial intelligence. ai is further away from being a reality than what we are led to think, where the delay in self-driving vehicles is just a reminder. this may be the real difference from dedijer’s social intelligence to surowiecki’s collective intelligence, that now we are discovering machines that can “think” (artificial intelligence): more effective, more interactive, and faster it systems that makes it easier to learn together. it is the study of how this is happening that lies at the core of collective intelligence. it is a world of new opportunities brought forward primarily by computer scientists and neuroscientists, but where social scientist will play an important part in evaluating applications and consequences. for this the literature will need be more critical. (conclusion # 5). as the example of the facebook–cambridge analytica data scandal has confirmed, social scientists should not be a gospel choir in the church of progress. the age of information is changing everyone’s lives. writing this research article is collective intelligence made possible by information technology, especially large databases (web of science) and fast internet connections (from home, or on the train on my way to work). instead of meeting colleagues and exchanging information on a topic, we write articles and share them. i try to locate those who know more than me and learn from them. that is an active process of collective intelligence. the idea of collective intelligence is as old as mankind, as man quickly discovered that he had to cooperate and pool ideas if he wanted to trap and kill larger animals like the mammoth. the notion has been a frequent topic in literature throughout time to the point where it is difficult to say who has contributed the most to it. the literature on collective intelligence is a good example of non-collaboration. ever greater specialization in the social sciences draws groups of scientists and researchers further apart even when they study the same phenomenon. the reason this happens is because the databases we use do not contain older articles (basically just the last fifty years), there are almost no articles in other languages than english (even though much progress was communicated in german and french), and researchers come up with new buzz words to establish their own careers and distinguish themselves from others, for personal and economic reasons. if the social science project was truly critical, this reinvention of the wheel should not be possible. in the german scholarly tradition, one is always confronted with the question of meaning. “what does that mean?”, with the clear goal of understanding a phenomenon. due to a systematic lack of such questions and aims, in the social sciences we now have dozens of groups, or tribes, studying the same phenomenon: artificial intelligence, collective intelligence, information sciences, and intelligence studies. the difference is the size of these groups, what networks they belong to and their financing. there are of course also differences in relevance and output of research. the larger question is if questions of collaboration will continue to be studied by multiple disciplines with little contact between them, or if the modern social science project will merge into something else. stevan dedijer suggested social systems theory, going back to bertalanffy (1968), and he explains: “the world is bitterly, savagely competitive and intensely, vigorously cooperative, by way of alliances and partnerships, thus rapidly changing individuals and social systems alike… we are pulled toward a single social system on earth.” (dedijer, 1999, p. 72). others, have elaborated the idea further. mainzer concludes that [we must] “learn to consider humans as complex nonlinear entities of mind and body… the 15 theory of complex systems explain what we can know and what we cannot know about nonlinear dynamics in nature and society… we need to ‘improve our knowledge of complexity and evolution’… mono-causality often leads to dogmatism, intolerance and fanaticism” (mainzer, p. 294-5) the same basic idea from the social systems literature in the social sciences is found in the complex systems literature in the natural sciences and in information sciences: behavior cannot easily be studied with small (for example, student group surveys), narrow (a few isolated variables) empirical projects with data of short duration (behavior changes in time and depending on circumstances). it requires the complexity of a multifaceted social structure. any modelling that tries to reduce reality to a correlation analysis performed on a few variables is of limited use. but, do leading scholars interested in collective intelligence interest themselves for systems thinking and complex systems today? yes, they do. 4.1 analysis of research areas to find out we analyzed the top-ranking scholars on collective intelligence according to google scholar, seeking out those with 1500 or more references. these are listed anonymously in the table according to their respective ranking. a total of five keywords or research topics are possible on google scholar, where it is common (but not certain) to list them according to the main interest of the researcher. five of the leading scholars are focusing on complex systems. that is more than for any other research area. two of the four leading mention complex systems as a specialty. table 1 keywords associated with the leading scholars on collective intelligence, according to google scholar. the columns show areas of study, ranked according to each person’s interest. the individual scholars are listed anonymously by ranking. rank primary secondary tertiary quaternary quinary 1 artificial intelligence ontology collective intelligence virtual assistants intelligent interfaces 2 intelligence augmentation collective intelligence open science quantum information quantum computing 3 collective behaviour collective behavior swarm intelligence collective intelligence complex systems 4 machine learning complex systems data mining information retrieval collective intelligence 5 democracy innovation innovation technology collective intelligence 6 computational creativity collective intelligence 7 self-organization collective intelligence cybernetics complex adaptive systems distributed cognition 8 learning analytics argument mapping collective intelligence human-computer interaction 9 knowledge engineering collective intelligence 10 collective intelligence artificial intelligence multi-agent systems sustainability 11 information systems design design visualization crowd work collective intelligence 12 artificial intelligence collective intelligence cultural algorithms evolutionary computation 13 biological physics statistical physics slime molds networks collective intelligence 14 social decision making collective intelligence empathy justice 15 artificial intelligence collective intelligence human-computer interaction 16 collective behaviors crowds computational social science complex systems collective intelligence 17 swarm intelligence collective behavior collective intelligence social behavior slime molds 18 neuroscience psychology education collective intelligence aging 19 population dynamics social systems collective intelligence 20 global futures research foresight futures research methodology global challenges collective intelligence 21 business analytics data science crowdsourcing collective intelligence 22 information systems network science computational social science crisis informatics collective intelligence 23 network science collective intelligence crowdsourcing 24 systems biology synthetic biology statistical inference self-organization collective intelligence 25 democratic theory constitutional theory political epistemology philosophy of science collective intelligence 26 computational intelligence collective intelligence natural language processing machine learning 27 digital innovation open innovation collective intelligence complexity computational social science 16 from the data we also learn that collective intelligence only appears once in the first position. on average, it is in the fourth place, which means that it is not a priority even for those who focus on this area. artificial intelligence is the most reoccurring specialization, occurring three times in first place. collective behavior is mentioned two times. the large majority of co-subjects are technical, related to information sciences at large, with few contributions from the social sciences. the variety of technical specialization is very large too. topics related to crowds occur four times in total, innovation four times. we conclude that the direction of complex systems as a way to study the social sciences, and problems of collective intelligence in particular, is still a highly relevant research direction according to leading scholars. (conclusion 6) 5. conclusions we have drawn a number of conclusions from the literature on collective intelligence. the collective intelligence literature is a continuation of contributions in what has been called the “information age,” a part of the “digital revolution.” this is a development brought forward by natural and computer scientists, but where social scientists have a role to play, first by studying the applications and consequences that technologies have on people and societies. the body of literature published under the collective intelligence umbrella is truly interdisciplinary (c1). the association to the notion of wisdom of the crowds is problematic for several reasons. the journalist surowiecki’s idea is an erroneous interpretation of galton’s contribution about the regression towards the mean in statistics. experience and empirical findings suggest instead that the wisdom of the knowledgeable is a more accurate term (c2). however, as our societies are becoming ever more short-sighted (financial markets, profits, product life cycles, etc.) there is an increasing gap between knowledge and wisdom in society. as a consequence, we argue that neither the crowd nor the knowledgeable are very wise (c3) and “wisdom of the wise” is a tautology and a meaningless expression. the content of the collective intelligence literature has been visited and revisited numerous times during the last half a century in the social sciences. as such, it can be seen as a part of a larger paradigm shift as noted in the first conclusion (c4). just as with artificial intelligence, every revisit seems to bring something new and have great potential value. but, the collective intelligence literature strikes one not only by its lack of historical perspective, lack of good data in some of its leading publications, but by a general lack of critical sense as to the phenomenon studied (c5). complex social systems seem still to be relevant for the study of intelligence related topics such as collective intelligence (c6). stevan dedijer made the same observations about the relation to social intelligence. the study of social systems based on evolutionary theory is a more fruitful scientific paradigm for the study of not only intelligence studies, but for the social sciences in general. 6. references ackoff, r. l. 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(2008). toward human level machine intelligence-is it achievable? the need for a paradigm shift. ieee computational intelligence magazine, 3(3), 11-22. vol11no2paper3 to cite this article: tulungen, f.r., maarisit, w., and rompas, p.t.d. (2021) competitive intelligence application: the case of geothermal power plant development in rural tompaso, north sulawesi, indonesia. journal of intelligence studies in business. 11 (2) 43-52. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 2 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive intelligence application: the case of geothermal power plant development in rural tompaso, north sulawesi, indonesia franky reintje tulungena,*, wilmar maarisitb, and parabelem tino dolf rompasc aagribusiness study program, faculty of agriculture, universitas kristen indonesia tomohon, indonesia; bpharmacy study program, faculty of mathematics and natural sciences, universitas kristen indonesia tomohon, indonesia; cinformatics engineering, universitas negeri manado, tondano, indonesia; *tulungen63@gmail.com journal of intelligence studies in business please scroll down for article competitive intelligence application: the case of geothermal power plant development in rural tompaso, north sulawesi, indonesia franky reintje tulungena,*, wilmar maarisitb, and parabelem tino dolf rompasc aagribusiness study program, faculty of agriculture, universitas kristen indonesia tomohon, indonesia; bpharmacy study program, faculty of mathematics and natural sciences, universitas kristen indonesia tomohon, indonesia; cinformatics engineering, universitas negeri manado, tondano, indonesia; *corresponding author: tulungen63@gmail.com received 2 may 2021 accepted 24 september 2021 abstract the vision of the community around geothermal power plants and the development of the power plants should be based on sustainable development principles, without jeopardizing the quality of life and justice for communities surrounding the power plant. this research aims to: (i) identify issues that arise as an result of the development of geothermal power plants in rural tompaso, and (ii) find solutions to the issues to minimize the conflicts that arises from further geothermal power plant development in rural tompaso and its surroundings. this study is based on the competitive intelligence research method. the results show that the development of geothermal power plants in tompaso has a negative impact on the natural and social environment. the technical solutions offered include: (i) bioremediation by cultivating plants that absorb arsenic; (ii) biosulfurization and desulfurization for reducing air pollution, especially sulfur; (iii ) floods and extreme drought managed by improving infrastructure and reforestation; (iv) social conflicts (land acquisition, working days, labor recruitment and settlement security) are solved by intensifying program dissemination to the community and involving local communities in decision making. the recommended policy provides incentives to the local community through strategic programs for the development of human and natural resources. keywords competitive intelligence, environmental issues, geothermal power plant, rural tompaso 1. introduction indonesia's vision in 2045 is to become the fifth strongest country in the world economically with a gdp of us $7.3 trillion and a per capita income of us $25,000. this can be realized by investment and trade: in industry, tourism, the marine environment, services, supported by reliable infrastructure and strong food, energy and water security. indonesia plans to launch a new renewable energy mix in 2050 making up 31% of the total national energy (kementerian ppn/bappenas, 2018). one renewable energy source that is environmentally friendly and supports sustainable development is geothermal energy. indonesian law no. 30 (2007), concerning energy, states that the national energy policy should be prepared based on the principles of fairness, sustainability and environmental insight to support the creation of energy journal of intelligence studies in business vol. 11, no. 2 (2021) pp. 43-52 open access: freely available at: https://ojs.hh.se/ 44 independence and national energy security. this policy confirms that energy diversification is a necessity to meet national energy needs. in the industrial era 4.0, the development of electric energy generation is a necessity to meet the energy needs of sulawesi island, eastern indonesia. one of the available sources of electrical energy is geothermal power plants (gpps). gpps are power plants that uses geothermal energy as an energy source. the objective of the development of gpps is the availability of geothermal energy to meet regional and national needs. it can be achieved by prioritizing the sustainable development principles without jeopardizing the quality of life and justice of the communities surrounding the plant. geothermal energy resources produce renewable energy that is clean and environmentally friendly. this energy is available in abundant quantities and can be exploited with many technologies (zhang et al., 2019). the development of gpps is one of the important energy sources that produce green energy that is free of carbon dioxide emissions in the world (hossain, 2016), including in indonesia. the development of geothermal power plants is aimed at meeting national energy needs in the era of industry 4.0 (salimova et al., 2019) and in the era of society 5.0 (fukuyama, 2018). the availability of this energy in the framework of supporting national development is necessary so that indonesia’s goal of becoming the fifth strongest country economically in the world can be realized. the development of gpps must be carried out by prioritizing the principles of sustainable development without endangering the quality of life and justice for the community around the geothermal power plant. this means that all progress with renewable energy should aim to improve human welfare and the quality of the environment. however, gpp development initially will have a negative impact on the surrounding community (social environment) and the surrounding natural environment. these negative impacts include the emergence of social conflicts in the community and loss of water resources. the most extreme impacts are that the surrounding communities may lose their homes, workplaces and business land due to the mudflows (farida, 2013). the construction of gpps is usually carried out by the urban community in the rural community. in this connection the urban community will bring technology and information to the rural community, and then the rural community will provide the material and energy back to the urban community. in this connection the urban community will exploit the village community (rambo, 1983) and efforts and policies are needed to balance the relationship between the two groups so that the negative impacts can be resolved. research on the problems posed by the development of gpps in rural areas and research related to their solutions is still minimal. natural environment problems related to water pollution by arsenic can be solved by designing special plants that can absorb arsenic in the wastewater reservoir (mohammed barznji, 2015) and air pollution by h2s can be solved by desulfurization and bio-desulfurization (munir et al., 2010). still research on the impact of the social environment is still lacking. however, comprehensive research related to natural and social environmental impacts and their solutions is needed to provide comprehensive information for stakeholders, including local communities. the north sulawesi lahendong gpp has been operating since 2001 and is currently producing electricity with a total capacity of 120 mw. this has met 60 percent of electrical needs in north sulawesi province. the lahendong gpp already has six gpp units, each producing 20 mw, of which the lasts two units, namely units 5 and 6, are in tompaso (handoko, 2010). the gpp in tompaso has acquired around 19 ha of land, nine ha of which are paddy fields. gpp tompaso has six production wells and two injection wells. the implementation of the well drilling project and the construction of the gpp in tompaso had caused problems for some people around the well fields and the gpp construction site. because of that, many residents refuse the presence of the gpp project for unit 8 that will be set up near water sources. based on these facts, the questions that arises are: (i) what are the negative impacts caused by the development of the gpp project on the social environment and natural environment in rural tompaso, and (ii) what are the solutions to solve the negative impacts caused by the gpp project in rural tompaso? based on these problems, the aims of this study are to identify problems in the 45 community caused by the development of gpps in rural tompaso and to find solutions to these problems to minimize conflicts arising from future gpp development in rural tompaso and its surroundings. the aim of this research is to provide input for pertamina geothermal energy (pge), the government and surrounding communities in geothermal management, which on one hand can meet national energy needs and on the other hand maintain the preservation of the natural environment as well as improve the quality of the social environment. 2. research method this research was conducted from january to june 2019 in tompaso district, minahasa regency, north sulawesi province, indonesia, especially in units 5 and 6 of the local gpp. this study uses the competitive intelligence (ci) research method as its policy research method (dou et al., 2019).. this can be used to produce a development strategy for businesses or organizations (tulungen et al., 2021). ci is a systematic process for collecting and analyzing data and information as well as understanding information in the context of compiling recommendations to answer problems faced by the organization (dou & manullang, 2003; tulungen, 2019). ci is a method of approach and set of tools to help create intelligence (dou et al., 2019). ci is a circular process (kahanner, 1997; vriens, 2004; garcia-madurga & esteban-navaro, 2020)(figure 1). a plan starts with a vision, but in reality problems arise relating to the achievement of the intended vision (tulungen, 2012). based on the research problems, an information-gathering plan was developed to solve the problems. the information collected is primary information and secondary information (dou & manullang, 2003). primary information aims at answering the first goal and secondary information aims at answering the second goal. sources of primary information are informants involved in the pge project and the people who are influenced directly by the development impact. information was collected through open-ended interviews with the informants and through direct observation at the project and affected locations. secondary information is from documents, such as textbooks, reports, scientific journals, and other documents. the collection of secondary information is mostly done through online sources (tulungen, 2020). data analysis is done by grouping the data according to themes, namely the social environment or the natural environment. each can be distinguished into sub-themes until it creates a unified whole and meaning. the results of the data analysis are then understood, through a deep and more comprehensive thought process (tulungen et al., 2020). based on this information, understanding can create intelligence as a recommendation for solving negative issues and further considerations for the development of the gpp and the community surrounding the gpp. 3. results 3.1 the natural environment 3.1.1 water pollution water pollution occurs in two ways, first at the time of well drilling and second at the end of the drilling. during drilling, the drill bit can be released if the drill bit hits a solid material. to remove the drill bit, the well that has been dug is filled with thousands of liters of diesel oil. as a result, the groundwater is polluted with the diesel oil. after the drilling is completed, water or water evaporation coming out of the well is discharged into the reservoir. this water may contain toxic heavy metals such as arsenic. because the reservoir cannot accommodate this wastewater at certain times, it overflows into the surrounding ground. as a result, surface water or ground water becomes polluted by arsenic. surface or ground water that is polluted with arsenic will contaminate agricultural fields, such as rice, with arsenic. the ground water that is used for drinking water by problems: company vision planning for data collection collecting data data analysis understanding information intelligence figure 1 the competitive intelligence process. 46 humans and animals will be contaminated with arsenic as well (hariyadi et al., 2013). based on the research by hariyadi, the quality of waste water from the lahendong gpp is poor, consisting of high arsenic concentrations of 1.2 mg/l (at point 1) and 1.26 mg/l (at point 2)(hariyadi et al., 2012). this amount exceeds the limit that can be tolerated, which is 0.05 mg/l for arsenic (presiden republik indonesia, 2001). exposure to arsenic can trigger liver, kidney and skin cancer and also heart disease. consuming arseniccontaminated water can cause miscarriages, low birth weight babies and poor cognitive development in children (rahman et al., 2009; tofail et al., 2009). water pollution by arsenic can be overcome by improving waste water storage tanks and treating the wastewater (mohammed barznji, 2015). planting the surrounding area with monochoria vaginalis, salvinia molesta and colocasia esculenta will help reduce the arsenic concentration due to their ability to absorb arsenic in wastewater from gpps. the highest arsenic absorption occurred in the roots of monochoria vaginalis (22,289 mg/kg), followed by the root of salvinia molesta (19,2335 mg/kg)(hariyadi et al., 2013). 3.1.2 air pollution air pollution is caused by increasing sulfur content (h2s) in the air. air pollution occurs both around the well or gpp as well as in locations far from wells in tompaso district. the level of pollution in the area around the wells is higher than the area far from the wells. this air pollution can be easily detected, for example by noting corrosion on zinc roofs faster than usual. this air pollution can also be seen from affected plants around the well, such as tomato plants that fail to bear fruit. in addition, rice production per ha is lower compared to before the drilling of wells by pge. for example, if farmers were able to harvest 15-20 bushels per 355m2 (waleleng), now they can only harvest 10 bushels per 355m2 (waleleng). the increase in sulfur content in the air will cause the release of greenhouse gases from below the earth's surface. with a gpp, these gases will reach the surface of the earth and therefor pollute the surrounding air. the air around the gpp was polluted by hydrogen sulfide (h2s) (layton et al., 1981). reducing the sulfur levels from the well into the air can be done by desulfurization. the higher the concentration of na2co3 solution, the more nahs is absorbed, which at a concentration of 11% can reduce h2s gas by 87.86%. in other words, if the concentration of h2s gas emissions from gpp activities ranges from 4800-6600 ppm, then with the absorption process the h2s gas emitted into the ambient air decreases to 582-801 ppm. with the process of bio-desulphurization (rhodococcus sp.) the formed sulfur crystals were an average of 52.01% on a field scale and an average of 71.28% on a laboratory scale (munir et al., 2010). decreasing the quantity of production due to sulfur exposure needs technological innovation to obtain plants that are resistant to high-producing sulfur. 3.1.3 flood and drought changes in land use from paddy fields to other crops and other uses have caused the water reservoir area to become narrow. as a result, if there is high intensity of rain it will cause flooding in the fields around the drilling that can impact the rice production. changes in land use from forest land to barren land have caused a reduction in water resources around the site. tree clearing due to land clearing for the gpp project and drilling have caused the loss of several of the springs around the project. water sources that irrigate rice fields in several villages in the tompaso sub-district are deminishing. areas in the downstream part of the gpp project are very vulnerable to drought and the loss of water has resulted in yearly losses of harvest. floods and droughts can be overcome by improving infrastructure, such as the normalization of the panasen river, and improving vegetation on the headwaters by building community forests or reforestation. this includes the requirement for pge lahendong to expand the area cleared for drilling wells from five hectares to ten hectares, of which five additional hectares are designated as village forests. 3.1.4 conversion of paddy fields to drilling fields the geothermal development project in tompaso has closed around nine ha of rice fields. of this, five hectares was for drilling wells and four hectares was for water pipelines from production wells to injection wells. this is contrary to the government policy regarding the acquisition of paddy fields. rice fields that are converted into drilling sites should be substituted with the same amount of land, but in reality there is no substitution of rice fields. 47 in the future it is necessary to consider rice fields as a final consideration in determining the location of well drilling. besides that, every productive land acquisition must be replaced by other land (presiden republik indonesia, 2011). the decision to locate the project on the paddy fields should be the last alternative, and an effort should be made to locate the project far from human settlement. 3.2 social environment 3.2.1 land acquisition conflict public concern first arises when land acquisition occurs. the concern is due to the lack of effort from pge to let people know the location of the project and the land acquisition. land was acquired before people were aware of where it would be and that the acquisition would occur. in addition, conflicts happened between members of the families who need to sell the land to the project. this is due to the fact that there are family members who have received the compensation of the family-owned land without the knowledge of other family members. to prevent the conflict during land acquisition, early socialization is needed in order for the local people to correctly understand the project planning and implementation. furthermore, the surrounding community should be involved in the decision making related to land acquisition and the fixed prices of the land. 3.2.2 worker recruitment conflict worker recruitment is carried out by a contracting company assisted by a working group. the working group consists of village heads (hukumtua) surrounding the well or the gpp. worker recruitment for skilled labor was carried out directly by the contractor and for unskilled labor, such as security workers and day laborers, recruitment was carried out by the hukumtua as a member of the working group in their respective villages. even though the village heads were involved, recruitment conflict always occurred. there are two kinds of conflicts occurring, namely between the village heads and the people who want to work and secondly between the contractor and pge lahendong and the people around the project. the village heads used their authority in recommending the workers who are only close to them. the contractor recruits people that they think can help protect their interests during the project. as a result, people who were not recruited revolted against the village heads and community leaders revolt against the contractor and pge lahendong. this is due to this fact that there were jealousies from the people and that only certain people were accepted. namely, people who were close to the working group and people related to the contractor and pge lahendong worked for the project. this conflict had encouraged people who were not included to demonstrate and rebel against the decision. during the gpp development projects there have been more than ten demonstrations carried out by the local community with various demands, such as asking for pge lahendong to socialize the project, requesting transparency about employment opportunities, and refusing workers from outside tompaso to work in the projects. in addition to that, the local workforce can only meet the needs of low and specialized skilled workers, who do not require skills. related to the conflict of the employee recruitment, the project needs to inform the community about the needs of the workforce, including the specifications of the needed workforce, involvement of community and religious leaders in the determination of workers, and should pay attention to community representation in the project. 3.2.3 working days and hours of operation in the process of the gpp project development in tompaso, the working days are monday through saturday. developers do not recognize holidays, especially sundays. the culture of the local community forbids people to work on sundays, especially during worship hours. having a working day on sunday led to protests from the local community. in addition, the noise and vibration caused from drilling wells are very disturbing during worship activities in the church. conflict about days and hours of operation can be solved by communication between community leaders, religious leaders and the developer. for example, there should be recess on sundays especially during church services. 3.2.4 settlement security the existence of the gpp project has resulted in two kinds of fears among the village community. firstly, local people worried about security and the entry of numerous workers from outside the community from different cultural backgrounds. secondly, the existence of the gpp project could bring misfortune to the community, such as mudslides or the 48 decline in land area. this is influenced by the recent lapindo mud disaster in east java that drowned several villages surrounding the lapindo geothermal plant (farida, 2013). also of concern are the results of research in units 1 and 2 in the lahendong gpp exploitation area, which had reduced the land surface level by three to four cm (kurniawan & anjasmara, 2016). the concern due to the incoming workers from outside of the area who live together within the village community can be reduced when there is a good interaction within the local community. public concern about the fears of lapindo's effect to the community can be overcome by public awareness that the lapindo mudflow incident was not caused by drilling but rather due to the natural disasters that happened in east java. 4. discussion the development of a gpp is intended to meet national energy needs by prioritizing the principles of sustainable and equitable development. to achieve this goal, we need to pay attention to issues that are developing in the village surrounding the gpp project and also learn from the many experiences that have occurred in other regions and countries. to solve these problems, the ci approach can provide solutions related to strategic programs and operational programs. the strategic program is under the authority of pge, as the person in charge of gpps throughout indonesia, while the operational program is a program that is mutually agreed with the local community and the local government. local people are those who produce geothermal energy or energy producers and outsiders are energy users. in relations between communities (environmental systems), in a state of nature, the more stable systems (cities, elite groups) will exploit less stable systems (e.g., villages, marginalized groups). energy and matter will flow from villages to cities (rambo, 1983). based on this fact, it is necessary for certain parties to intervene to create a balance between rural and urban areas, between the social environment and the natural environment, and between marginal groups and elites by providing incentives for villagers through national and local policies so that the principles of sustainable development and justice can be realized. national policies will be realized in the form of national strategic programs and local policies. this will be in the form of local strategic program policies (dou et al., 2020). strategic programs at the national level are programs built to maintain and improve the quality of the social and natural environment around gpps and geothermal wells. based on the results of this study, the national strategic programs that can be offered are making forests around gpps and geothermal wells, making wider reservoirs so that arsenic does not spread, reducing arsenic by planting plants that absorb arsenic, and paddy fields are the last option for location for the gpp and geothermal wells projects, gpps and geothermal wells are built far from settlements and improve the quality of community resources around gpps through education. the strategic program at the local level aims to improve the quality of human resources in the surrounding community. improving the quality of education can be done through education and training assistance. education is formal education, from kindergarten to higher education, while training is according to the needs of the local community. since the covid-19 pandemic in indonesia, the teaching and learning process from elementary schools to universities has been carried out by distance learning (online) since march 2020. the main problems faced by rural communities, including in the tompaso countryside around the gpp, in distance learning are the weak internet network, the absence of smartphone or computer devices, and funds to purchase data packages for students (amalia & sa’adah, 2020). based on this fact, the strategic programs at local level must provide an internet network, smart phones, and data quota assistance for students around the gpp. the absence or weakness of the current internet network must be anticipated by building satellite internet. satellite internet is one type of internet independent of a cable network which directly uses satellite as its transmission medium. satellite internet procurement is financed by pge through corporate social responsibility funds. with this satellite internet, the problem of internet access or internet network and data quota or data credit costs in distance learning can be resolved. some of the available providers include: karunia sinergy, viasat, hughes-net, and kacific. these providers provide satellite internet and telecommunications services to 49 customers in remote and rural areas. it can serve 100 networks with a distance of 1 km for 24 hours/day with an internet package cost of around rp. 2.2 million/month. through this program, the community, especially students, can participate in education through distance learning online. the role of the government, pge, and the surrounding community are very important in maintaining a balance between the social environment (social system) and the natural environment (ecosystem), as well as the balance between villages and cities. energy will flow from the village to the city, so to balance the two ecosystems, materials and information from the city must be conveyed to the village. for this reason, a collaboration platform between stakeholders is needed in order to support and accelerate the flow of information and materials from cities to villages. the platform is in the form of an information system (elitan, 2020) that allows all stakeholders to sit together to plan, implement and supervise programs to improve the quality of the natural and social environment around the gpp. tompaso gpp as an energy generator must be supported by all stakeholders. the existence of the gpp must be able to improve the quality of the natural environment (e.g., water, air, soil, sunlight, plants, and animals) and the quality of the social environment (e.g., education, health, economics, culture, law), particularly the local environment in which the project or business is located. gpps are part of a strategic renewable energy industry, and need to be supported by cooperation between the energy source community and energy users, the government, pge, and universities to create innovation (intelligence) in order to develop them (pique et al., 2018). with the cooperation of these stakeholders, gpp units 5 and 6 will be able to continue and the development of other gpp units can be carried out with more competitiveness and better quality by prioritizing the principles of sustainable development. the ci approach and method is used by companies, both national or multinational (prinsloo, 2017), and including small, medium, and large companies to be able to win the competition with similar companies (hassani & masconi, 2021; nte et al., 2020), but also by the government and local governments to advance their regions (ezenwa, 2018). ci is also used by organizations and communities to achieve their vision and goals. in this regard, this ci can be used to evaluate the implementation of gpp development and postgpp development. based on findings in this research, we can be concluded that the development of a gpp in rural tompaso, especially unit 5 and unit 6 in rural tompaso, is not in accordance with the goals and vision of pge and the local community around the gpp project. the vision for the community around gpps should be based on sustainable development principles, without jeopardizing quality of life and justice. this means that pge must operate efficiently in its development, not harm the community around the project, and not damage the social and natural environment. or in other words, the development of the gpp must prioritize the principles of economy, benefit, justice, and sustainability. thus ci can be used for the construction and development of projects for the public interest with a new vision (dou et al., 2020), that is not only based on economic aspects but also based on social and natural aspects. with the internet network, both through base transceiver station and satellite internet in the rural tompaso, it will make it easier for the community surrounding the gpp project to build an information system or smart village (andari & ella, 2019). this smart village will serve the community in relation to government administration as well as the information needs of the community and other stakeholders (syaodih, 2018). the development of this smart village can initially be realized through the cooperation of the village government, universities, and pge (imre, 2015). 5. conclusions and recommendations 5.1 conclusion problems with gpp development include: (i) natural environment: water pollution by arsenic, air pollution by sulfur, floods and drought, conversion of paddy fields to dry fields, (ii) social environment: conflicts of land acquisition, recruitment of workers, working days and hours of operation and security of local resident. some solutions to the natural environmental problems are (i) water pollution, such as exposure to arsenic in water can be overcome by increasing wastewater collection basins and wastewater treatment, (ii) air pollution and reduced crop production by sulfur can be overcome by desulfurization, 50 and (iii) floods and drought can be overcome by improving infrastructure and reforestation. solutions to social environmental problems such as (i) land acquisition, (ii) working days and hours, (iii) recruitment of workers can be overcome by a program of socialization with the community and involving local communities in decision making, and (iv) security of settlements can be solved by the development of gpp projects far from settlements. 5.2 recommendation recommendations that can be put forward are: (i) local communities should be included in decision making for location determination and recruitment of workers and should obtain benefits or incentives from energy produced through strategic programs from pge, central government, and local governments (ii) cooperation between government/ pge, universities and local communities should be carried out to find innovations, including plants that are resistant to sulfur, and (iii) 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(2019). geothermal power generation in china: status and prospects. energy science and engineering, 7(5), 1428–1450. https://doi.org/10.1002/ese3.365 vol9no2paper3 to cite this article: shaikh, s.a. & singhal, t.k. (2019) study on the various intellectual property management strategies used and implemented by ict firms for business intelligence. journal of intelligence studies in business. 9 (2) 30-42. article url: https://ojs.hh.se/index.php/jisib/article/view/407 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index study on the various intellectual property management strategies used and implemented by ict firms for business intelligence shabib-ahmed shaikha*, tarun kumar singhalb asymbiosis international (deemed university) (siu), pune, maharashtra, india, bsymbiosis centre for management studies (scms), symbiosis international (deemed university) (siu), noida, uttar pradesh, india *shabib.ahmed@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: making sense of the collective intelligence field: a review collective intelligence process to interpret weak signals and early warnings fernando c. de almeida and humbert lesca pp. 19-29 study on the various intellectual property management strategies used and implemented by ict firms for business intelligence journal of intelligence studies in business v ol 9 , n o 2 , 2 0 1 9 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 9, no. 2 2019 klaus solberg søilen pp. 6-18 shabib-ahmed shaikh pp. 30-42 and tarun kumar singhal a new corpus-based convolutional neural network for big data text analytics wedjdane nahili, khaled rezeg pp. 59-71 and okba kazar business intelligence using the fuzzy-kano model soumaya lamrhari , hamid elghazi pp. 43-58 and abdellatif el faker using open data and google search data for competitive intelligence analysis jan černý, martin potančok pp. 72-81 and zdeněk molnár the potential of business intelligence tools for expert finding mehdi dadkhah, mohammad lagzian, pp. 82-95 fariborz rahim-nia and khalil kimiafar study on the various intellectual property management strategies used and implemented by ict firms for business intelligence shabib-ahmed shaikha* and tarun kumar singhalb asymbiosis international (deemed university) (siu), pune, maharashtra, india bsymbiosis centre for management studies (scms), symbiosis international (deemed university) (siu), noida, uttar pradesh, india corresponding author (*): shabib.ahmed@gmail.com received 30 september 2019 accepted 25 october 2019 abstract software technology is seeing enormous growth as it is used in all fields of technology. it is continuously evolving at a rapid pace and has a short span of the technological life cycle. the use of the software is not restricted only to information and communication technology but is used in all fields of technology. in many cases, the inventive step of a product or service lies solely in the software. hence, the software plays a crucial role in all fields of technology. however, ease of copying poses a financial risk for the software industry, thereby creating major disincentives to the development of innovation. still, the technology is changing very fast and firms investing in this technology expect quick returns on their innovation investments. strategies for generating and managing intellectual property have subsequently taken center stage for information and communication technology companies, and patents have become an important feature providing maximum protection for any technology. hence, intellectual property rights strategies in general and patenting strategies especially play a crucial role in the information and communication technology industry to be globally competitive. firms never publish or disclose their intellectual property strategies; hence, this study makes use of the literature review to highlight various intellectual property management strategies used by information and communication technology firms for managing their intellectual property. these strategies can be offensive or defensive and may be used as proactive or reactive depending on various aspects such as market, territory, technology, or time. the insights provided in this work may help the research community from the it domain in industry and academia to learn and modify their strategies for patent acquisition. keywords business intelligence, competitive intelligence, ip strategies, organizational performance, patents 1. introduction 1.1 information technology information and communications technology (ict) is often used as an extended synonym for information technology (it). it is the application of computers and telecommunications equipment to store, retrieve, transmit, and manipulate data, often in the context of a business or other enterprise. it encompasses the inputting, storing, retrieving, transmitting, and managing data through the use of computers and various other networks, hardware, software, electronics, and telecommunication equipment (ipo, 2013). the core elements in the application of it are journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 30-42 open access: freely available at: https://ojs.hh.se/ 31 computers and their peripherals consisting of hardware and software. 1.2 intellectual property intellectual property (ip) is an intangible asset created from a human mind and having some value (kavida & sivakoumar, 2008; isa et al., 2009). intellectual property rights are the rights conferred on the persons for exploiting their intellectual property within a specified territory for a specific period. the intellectual property rights framework provides various alternatives for protecting the intellectual property generated from a business or required for a business to be globally competitive (wipo-b). the exploitation and management of this intellectual property is often linked with business sales, export quality and marketing needs, along with research direction strategies to ensure that a firm remains competitive in a business (zhang & yang, 2016; mahajan et al., 2015; debackere & veugelers, 2005; zahra & nielsen, 2002; torvinen, & väätänen, 2014). the full value of ip can be perceived as an information source derived from its technical details available in patent data, its uniqueness, and its volume as over 100 million patent documents that are freely available online for use as early as 18 months after the filing of a technology (khode & jambholkar, 2017). parr and smith (2016) point out that the commercialization of ip involves annual revenues of at least 5 trillion usd. managing ip in general and patents in particular, has thus become crucial for the it industry to survive. it is continuously evolving, has a short technological lifecycle, and is hit by many legal challenges towards its protection, litigations, and trolls (shaikh & londhe, 2016). 1.3 strategies strategies are futuristic plans conceived before execution, depending on a set of predefined rules or previous experiences. krig and sandra (2017) define strategy as “the determination of the basic long term goals and objectives of an enterprise, and the adoption of courses of action and the allocation of resources necessary for carrying out these goals.” the main aim of strategies is to sustain long term competitive advantage in business via means of building defenses against competitive forces (porter 1993). strategies can be proactively planned or reactive, based on situations and market places. 1.4 the need for ip strategies in it the it industry has rapidly globalized (cameron et al., 2006). as the software market started from the us, the us acts as a trendsetter for the protection of software via patenting. other countries follow the us in protecting software via patents (cameron et al., 2006) as this protection promotes a nation’s technological innovation (wang et al., 2012). a fundamental problem for the software industry is the ease of copying, which often poses a financial risk (rao, 2001). this even creates significant disincentives to the development of new and innovative software programs, hindering software development (mcgowan et al., 2007). robust r&d operations are undertaken if protection is provided, which leads to the start of profitable businesses. failure to protect software firms' developed products might affect a company’s ability to operate freely at the primary level in the global market (clarkson & dekorte, 2006), which in turn would threaten a firm’s own existence (dedrick & kraemer, 1993; jyoti et al., 2010). software innovations are usually incremental, fast-changing, and have a short lifecycle. software is becoming more complex and sophisticated daily, with value-added features. firms investing in this continually evolving and changing technology expect concrete protection for their ip and quick returns on their investments (shaikh & londhe, 2016). in the field of information technology, trade secrets, copyrights, and patents are mainly considered for protection. while each of these has its advantages and disadvantages, patents are considered to provide the highest protection in the ict sector, specifically for software (shaikh & londhe, 2016). patents qualify the protection of the functional aspect of a product, process, or service, along with its underlying idea. the idea behind this is that software can easily be copied and independently developed when it comes into the market, and hence trade secrets, as well as copyrights, prove to be weak in protection. additionally, copyrights are meant to protect the nonfunctional aspects and expression of ideas and not the functional aspects and ideas. hence patent protection in the field of it and mainly for software is gaining importance. at the same time, protecting software under patents also ensures that no one company can claim a monopoly under a particular innovation, thereby increasing competition (oecd, 2008; the united states. federal trade commission, 2003). many important 32 innovations have reached the marketplace with the help of the patent system (epo, 2013). different patent filing strategies are used by firms to gain a competitive advantage and survive and thrive in the market place (shaikh & singhal, 2018). this study focuses on patenting strategies of it firms and uses it interchangeably with the term ip strategy. 2. ip strategies for business intelligence an ip strategy is a subset of the business strategy (barrett, 2002) that can be used to apply business intelligence for decision making. ip strategy plays an essential role in defining, creating, and sustaining a winning business strategy enabling value creation and strengthening multiple aspects of an effective ip strategy (pargaonkar, 2016). in the current knowledge economy, intangible assets have gained more valuation, and hence a significant portion of enterprise value is presently governed by ip rights (fisher & oberholzergee 2013). these ip rights, when governed wisely, yield value, and put a firm in a competitively advantageous position. the ip creation, its possession, and utilization can bring practical, long-term, and direct economic interest to nationals (guo & li-hua 2008). ip strategies thus play an essential role in governing a firm’s ip and are mainly aligned with the overall business strategy to successfully survive and thrive in the market place. ip rights are used to create income, to defend the firm’s competitive status, and to address competitiveness (davoudi et al., 2018). ip is a valuable financial and strategic resource that needs careful management by every organization. without proper ip management, organizations may expose themselves to unnecessary risks and infringements as they may be unaware of the value and benefits of the ip they possess (spruson & ferguson, 2007). ip strategies refer to planning related to intangible assets. its management involves the formulation and execution of plans related to ip strategies. an appropriate ip strategy and its management enable smooth technology and knowledge transfer (guo & li-hua 2008). in general, an ip management strategy includes: 1. creating or acquiring intellectual property 2. governing the owned intellectual property, and 3. extracting value from the owned intellectual property amongst various ip rights, trade secrets, copyrights and patents can be used for protection in the ict domain, especially for the software; however, patents are the preferred choice of firms as they provide stronger protection for the functionality of a product, the process of service (shaikh & londhe, 2016). patent filing strategies can be to secure, enforce, exploit, or block, which depends on the level of innovativeness of the inventions (süzeroğlu-melchiors et al., 2017). hence, patenting decisions are seen as important strategic considerations. firms can gain maximum value from a patent depending on their ability to enforce the patent (arrow, 1962; holt et al. 2015; dornelles, 2016). to enforce patents, firms need to prepare well in advance and create strategies to embed their business strategies with patenting strategies to gain a maximum advantage in the long run. patent strategies encompass a set of resource allocation decisions and underlying “logic” of decision making about patents (somaya, 2012). firms seek patents to prevent copying, fence and build thickets, attaining licensing income, preventing hold-ups and rewarding r&d personnel, in addition to highlighting the innovativeness and competences of the firm (cohen et al., 2000; rudy & black, 2018; useche, 2014). firms with active and systematic patent management outperform those that remain inactive and non-strategic (soranzo et al., 2017) protection of ip does not happen automatically and may require active measures to enforce ip rights and at the same time, defend and preserve those (spruson & ferguson, 2007). patent filing strategies can be used to secure, enforce, exploit, or block competition, depending on the level of innovativeness of the inventions (süzeroğlumelchiors et al., 2017). firms that remain inactive and non-strategic for patent management are outperformed by firms that have an active and systematic patent management system in place (soranzo et al., 2017). the survival of the firms is based on how they perceive ip and patents, in particular, generate it and then utilize it further. it has become essential for firms to exploit their technologies internally as well as externally to avoid losing their value to competitors (chesbrough, 2003). firms can gain maximum benefit from a patent by their ability to enforce the patent (arrow, 1962; holt et al. 2015; dornelles, 2016). patent strategies include all decisions involving resource allocation along 33 with the logic of decision making about patents (somaya, 2012). firms also need to ensure that the ip they perceive and generate is aligned with their business needs and strategies to achieve long term objectives. a valid ip management strategy assists firms in capturing and protecting the outcomes of their investment in innovation. management of intellectual property involves: 1. an understanding of what intellectual property is, 2. when the intellectual property has been created, 3. the value of the created knowledge, 4. and how to protect intellectual property that has value. competitive advantage over rivals is achieved by firms depending on how well they align their ip strategies with business strategies. this paper highlights the various strategies used by firms for protecting and managing their ip as available in the literature of the work carried out by researchers. it also brings forth enablers, which may be the outcome of the strategies implemented by ict firms along with indicators of organizational performance. 2.1 intellectual property management strategies motohashi, (2008) defines a firm’s ip strategy as “strategic use of its technology pool, which is a firm’s capacity for innovation output, such as new products or processes, based on in-house r&d or acquired technology from external sources.” the core purpose of an ip strategy is to develop an ip economy (guo & li-hua, 2008). without appropriate strategies, firms that are not patenting will be unable to capitalize on their investments, and researchers may be prevented from conducting even the most basic research (clarkson & dekorte, 2006). hence, the role of patent management has changed from creating a purely legal barrier for competitors to a sophisticated utilization of patents to achieve maximum returns on innovation (süzeroğlumelchiors et al., 2017). ip management is the use of systematic processes to understand the intellectual property of others and to generate your own (spruson & ferguson, 2007). ip management strategy needs to address organizations' needs to achieve commercial goals successfully. the firms may use ip as a tool to: • block competing products • generate income from commercialization • deter potential infringers • defend an infringement action • attract investment • raise the organization’s profile, or • increase the sale price of the organization’s shares or business ip management strategies can be viewed as offensive or defensive, depending on where and how they are applied (spruson & ferguson, 2007; fisher & oberholzer-gee, 2013). an offensive ip strategy is generally to take action against an infringing party, while a defensive strategy is intended to obtain ip to minimize the risk of being sued by others for infringement. striking the correct balance between being offensive and defensive is a complex task. it may depend on the market place, market size, number of players, and the technology in question. new entrants in the markets, as well as old players, can exercise both these strategies. different strategies are listed under these two main categories are highlighted below. 2.1.1 defensive ip strategy defensive strategies seek to provide a firm the freedom to operate and commercialize its invention without hindrance from patents that belong to others (rudy, & black, 2018; somaya, 2012). they are helpful when there is high fragmentation in the market for patentees, and firms are unable to arrange licensing due to transaction costs (jell et al., 2017). defensive strategies are thought to be reactionary, focused on protecting the current value of ip (somaya, 2003; rudy & black, 2018). various defensive ip management strategies, as highlighted below, are implemented by business firms for enhancing their organization's performance. a) legal privilege: legal privilege can be asserted by firms that do not own ip in a technology (rudy & black, 2018). firms attempt to affect their competitors’ patent holdings by using opposition and re-examination proceedings (somaya, 2012). they can use legal suits to either defend the legality of the use of a technology or altogether challenge the validity of the patent holder’s claim on the technology. 34 however, defensive litigation is a rare option as there is a high cost of litigation, along with an emotional toll. even if a firm wins, other competitors in the market are also free to capitalize on the success, and if litigation is lost, damage awards can be huge (fisher & oberholzer-gee, 2013). b) invent around: firms mainly chose to commercialize their ip possessions using in-house development and supply of goods or services based on “inventing around” a said technology. inventing around a said technology provides an alternate way to tackle technology blockage (cohen et al., 2000; fisher & oberholzer-gee, 2013). it helps firms to increase their r&d capabilities, forms a basis for the investment in new products, a defense against others’ business strategies, and a competitive advantage in the market place (lang, 2001). however, it requires huge investments, manpower, and resources. the time taken to bring a product into the market is also longer. c) collaboration: instead of inventing around solely, firms can share r&d resources by collaborating with other firms via universities, intra, and interindustry partners who are seeking an alternative, complementing technology for the technology in question. collaboration helps firms benefit from external knowledge partners, which facilitates the blending of external and internal ideas into new products, processes, and systems (belderbos et al., 2014). it also helps reduce the financial burden and also distributes the risk in case of failures (fisher & oberholzer-gee, 2013; holgersson, 2012). firms also collaborate with competitors to infiltrate their intellectual knowledge and learn about their technological skill sets (krig & sandra, 2017). firms work with government and foundations in bringing out new manuals and standards in technological development. through such collaboration, firms may emerge as leaders in technology, which maintains those standards (krig & sandra, 2017). blocking patents are also common in the context of standard-setting, because once a standard is picked, any patents necessary to comply with that standard become truly essential and each patent can confer significant market power on its owner, and the standard itself is subject to holdups if these patent holders are not somehow obligated to license their patents on reasonable terms (shapiro, 2000). firms also collaborate to form alliances within the industry. collaboration is built for transferring, bifurcating, or reducing the consequences of potential risk via failure in r&d output. collaboration may also be formed in cases when there are fewer resources available for delivering technology. collaboration efforts trigger opportunities for value creation and at the same time, also present substantial challenges in seeking to appropriate this value (belderbos et al., 2014). d) license-in: licensing-in comprises procurement of required technologies under license from an ipr owner. licensing-in is a way to acquire products or technologies without expending the time and resources necessary to develop them independently. in some cases, licensing-in is required to gain access to technologies that are proprietary but standardized in products of interest. licensing-in reduces the time to market and might also be used to legalize infringement. for faster entry into the market place, it is recommended to license technology from the market leaders. it helps a firm to operate freely in the market without the fear of litigation. the difference in cost between acquiring knowledge from another person and originally creating that knowledge is substantial (lindberg, 2008). licensing can also be sought by companies for allied services required for the functioning of their product or service. by doing so, firms concentrate on the core product development and license the other dependencies from outside. firms also license-in technology for operational freedom even if they have developed a technology in-house in case its ip is held by others. a patent license is, in 35 such cases, seen as “a simple means of collecting money in exchange for agreeing not to sue” (feldman & lemley, 2015). licensing-in helps firms increase their business values and profits and also avoids litigation (krig & sandra, 2017). firms can also coordinate the acquisition of multiple related patents using licensing to create patent fences or thickets, which later can be used as a bargaining chip in cross-licensing negotiations (reitzig, 2007). 2.1.2 offensive ip strategy offensive patenting, on the other hand, is mostly exercised by firms having a broad patent portfolio or those owning patents of high quality. offensive ip management strategies are thought to be proactive, focused on protecting the future value of ip (somaya, 2003; rudy & black, 2018). the various offensive ip management strategies are highlighted below. a) exercising market power: as patents authorize the creation of monopolies, firms exercise market power by ensuring that no other firm infringes on its technology. the most valuable patents are not those likely to be used by the patent holder but those likely to be infringed upon by competitors because the primary role of the patent is as a bargaining chip to buy the freedom of action (hanel, 2006). although a patent provides its holder a right to commercialize or license its product, firms make use of enforcement mechanisms via litigation in pursuit of profits (nerkar et al., 2007). generally, the value of the patent right reflects the power of the patent to contribute to the profitability of the company in some manner (holt et al. 2015). firms employ patent litigation to detect imitation and aggressively enforce their patent’s rights against possible infringement (somaya, 2012; rudy & black, 2018). the use or threatened use of litigation helps a firm to protect its ip and at the same time gain competitive advantage (rudy & black, 2018) by enforcements with a desire to take out competition, encourage infringers to stop using patented inventions, pay higher royalties, or to build a fierce reputation (somaya, 2012). firms also make use of external attorneys to file patents while following a “maximization approach,” resulting in more claims, filing in more countries, and more pct applications (süzeroğlumelchiors et al., 2017). exercising market powers through litigation is high in the software industry compared to other sectors. patent litigation is undertaken by patent holders to both dissuade and economically punish the patent infringer (reitzig, 2007). however, patent infringement is often challenging to detect, and enforcing a patent through litigation can be extremely costly, disruptive, timeconsuming, and unpredictable (somaya, 2012). b) sell: instead of capitalizing on the value of innovation, firms may also need to make trade-offs in their patent strategies to allow their technologies to create greater value in the marketplace and out compete other innovative solutions (somaya, 2012). an outright sale is another option that can be exercised by the industry if the value of the technology is high in the hands of others (krig & sandra, 2017). this enables an increase in competition. inventors can transfer their technologies to other firms within the same industry that are better suited to make the application, production, and marketing investments that are necessary to turn inventions into commercially successful innovations, by enabling combinations of resources of different types (holgersson, 2012). selling can also be an attractive strategy for firms if the innovator firms lack manufacturing or marketing facilities (fisher & oberholzer-gee, 2013). c) license out: licensing-out requires that the owner of ip, licenses its ip to a licensee in return for royalties and/or other considerations. it allows maximizing license revenue, thereby fully exploiting a firm's r&d capabilities (parr & smith, 2016). many software vendors prefer to license the use of their product rather than sell 36 them, thereby retaining ownership. licensing-out is also an enabler to ensure that the competitive firm becomes dependent on a firm’s technology and does not invest in its r&d, thereby locking out the option of inventing around by competitive firms and impeding innovation (reitzig, 2007; krig and sandra, 2017; fisher & oberholzer-gee, 2013). licensing-out also helps reduce the transaction costs and at the same time, may also certify invention quality to potential technology partners, thus encouraging them to license the patented technology (somaya, 2012). most of the time, firms patent technology with a motive to improve its bargaining position in patent licensing (mihm et al., 2015). d) cross licensing: cross licensing is another form of barter of technology which may be royalty-free, or with a flow of royalties (hanel, 2006). cross licensing occurs when two competing firms with different r&d strengths take advantage of each other’s intellectual assets. cross licensing creates the same sort of synergy as a joint venture without the inconvenience and delay of setting up joint operations. these are relatively common in high technology and knowledge-led fields. cross licensing can be a remedy to cut through patent thickets. if two patent holders are the only companies capable of manufacturing products that utilize their intellectual property rights, a royalty-free cross-license is ideal (shapiro, 2000). cross licensing is the preferred means by which large companies clear blocking patent positions amongst themselves or settle outstanding patent disputes (shapiro, 2000). it is also seen as an alternative strategy for building large patent portfolios that helps to ward off patent infringement and gain access to rivals’ technology (motohashi, 2008; fisher & oberholzer-gee, 2013; rudy & black, 2018). patents can also be used to negotiate a cross-licensing agreement that helps in reducing the cost of acquiring the needed technology (lang, 2001; cockburn & macgarvie, 2011). e) donate: technology in the hands of a few helps personal gains, but when it is in the public domain it helps society. citing this example, software companies like ibm, google and redhat try to donate some of their patents in the public domain (wen et al., 2015). however, this is often done to understand how technology can be used and led further or is perceived by others. this also opens the doors of bigger firms to identify targets to acquire or collaborate in the future. innovators may also choose to provide their innovation freely in cases where there is low return from licensing of patents due to weak protection or involving high transactional costs (harhoff et al., 2003). it can also be disclosed freely to increase one's reputation in the market place. donations can also act as signals of a firm's r&d capabilities, which in turn may attract financial capitals (fisher & oberholzer-gee, 2013). f) signaling and disclosure: signalling technological advancements or disclosure of technology in the public domain sends signals to competitors about a firm’s commitment towards a technology. this influences rivals to exit r&d competition and redirect their r&d efforts (gill, 2008; somaya, 2012). this may also be done by firms to generate prior art, so rival innovative firms may find it harder to obtain patents in the same technology domain, and the focal firm may be able to catch up with competitors in the race to own critical patents (baker & mezzetti, 2005; somaya, 2012; reed & storrudbarnes, 2011). firms may patent “bad” inventions to mislead rivals in their efforts to build on the technologies disclosed in patents (somaya, 2012). specific patent actions may also be undertaken to signal the firm’s patent strategy and intentions credibly. signaling and disclosure can be done through article publication (holgersson, 2012) using a companies’ official website or web-based online publication portals such as ip.com or research disclosure. it is an efficient, effective, and inexpensive strategy to prevent competitors from patenting in 37 the technological space described in the publication disclosure (barrett, 2002). g) patent fencing: individual patents are often ineffective as others can build technology around them (jell et al., 2017). firms, therefore, file patents with the sole aim of blocking competitors, ensuring freedom to operate (hanel, 2006; guellec et al., 2012; weatherall & webster, 2014). firms try to patent not only the technology but also all related technologies of said technology, thus creating large patent portfolios (shapiro, 2000; lang, 2001; weatherall & webster, 2014; rudy & black, 2018). known as “patent fencing”, “patent pools”, “patent stacking”, “blocking”, “clustering and bracketing”, “blitzkrieg, consolidation”, “blanketing and flooding”, “fencing and surrounding”, “patent harvesting and ramping up”, “portfolio and network arrangements” (jackson, 2007) or “patent thickets”, the combination of multiple patents makes it costlier to invent around, and they block competitors thereby forcing competitors to license and pay higher royalties (cohen et al., 2000; jell et al., 2017). these patent pools help firms when threatened (or sued) over another firm’s patents, as the focal firm can threaten back with its patents, leading to a situation of mutual holdup that forces a faster resolution of the standoff (somaya, 2003; ziedonis, 2004). firms also use the “block to fence” strategy by acquiring a substantial number of patents not only for their core innovations but also for related processes and substitute products, hoping to drive up the cost of “inventing around” (fisher & oberholzer-gee, 2013). studies have also pointed out that the broader a firm’s patent portfolio, the more likely it is to develop new products (rudy & black, 2018). this private strategic value of patents may be increased in the presence of ‘thickets’ which can help in the growth of r&d activities by constraining the ability of firms to operate without extensive licensing of complementary technologies (noel & schankermann, 2013) and outsiders may consider that a company with additional patents in their portfolio will have a higher future performance than a company without patents. patent fencing is an expensive but powerful strategy to discourage or stop competitors as this tool makes it difficult for a competitor to expand on their patent portfolio without infringing on patents held by this strategy implementer (jackson, 2007). h) ip insurance: the need to address ip issues increases with the success of organizations as such organizations are increasingly monitored by competitors for possible infringements (spruson & ferguson, 2007). business needs to protect its ip risks in-house via a legal compliance program and also by outside means via insurance. apart from traditional insurance policies to manage risk, firms should effectively use other risk management devices, such as legal compliance programs, to ensure freedom to operate, new types of litigation insurance, and net loss insurance (simensky & small, 2000). legal compliance can be used by firms to avoid infringement of others' ip and at the same time to protect their ip from infringement by others to maximize their value. however, legal compliance is rarely used in offensive or defensive roles. the cost of ip enforcement in the software domain is too expensive, and hence it is suitable for firms to insure against the financial costs of enforcement proceedings considering the significant amount of time, effort, and resources spent in creating and protecting the ip. depending on the type of insurance and its cover, the ip insurance may cover the costs of bringing legal action to prevent or stop ip infringement by unauthorized users along with costs of legal expenses to enforce the ip right and costs of defending cross-claims brought by the alleged infringer. it may also cover the costs of proceedings brought against an organization for infringement of ip owned by a third party, including damages payable by the organization. ip insurance is advisable to firms in the early stages of ip creation, and it helps the firms to spread the risks and financial costs involved in ip lawsuits and at the same 38 time, acts as a deterrent to potential infringers (spruson & ferguson, 2007). an offensive ip strategy is generally to exercise market power and take action against an infringing party, while a defensive strategy is intended to obtain ip to operate freely in the markets and minimize the risk of being sued by others for infringement. having a correct balance between offensive and defensive strategies is a complex problem as it is dependent on the market place, market size, number of players, and the technology in question. industries are more inclined to undertake offensive or defensive strategies to enjoy positive performance outcomes (somaya, 2003; ziedonis, 2004; rudy & black, 2018). the patent strategy of firms is usually tied with its business strategies depending on its market place, market size, players involved along with the technology, and its protection. while the average patent may be a weak and porous instrument, carefully crafted patents and combinations of patents may become more effective tools for a firm’s strategy (somaya, 2012). firms’ ip strategies are evolving, and licensing decisions may be due to patent infringement, or a firm involved in a patent infringement case may adopt a serious view of ip management (motohashi, k. 2008). generalizing, it can be concluded that initially, when firms do not have patents or are new entrants in a technological market, they should use a defensive approach and follow generic patenting strategies while trying to accumulate a patent portfolio. when a significant patent portfolio is available in hand, firms should try to use a more proactive offensive approach with strategic patent management that could lead to a competitive advantage (figure 1). ip management strategy thus leads to an increase in a firm’s value and its performance. this study has several significant implications not only for it firms but also for academics and practitioners involved in ipr, specifically in r&d and patenting. an ip strategy is driving businesses to align their business strategy with ip strategy to survive and thrive in the market place and set future goals along with competitive advantage. the present research explores various offensive and defensive ip management strategies it firms are deploying to gain a competitive advantage in the market place. these highlighted strategies may provide the managers with an insight into various options they may deploy within their organizations to achieve a competitive advantage. 3. conclusion ip in the field of ict is gaining importance with the advent of new emerging technologies. creating and managing ip in the field of ict has become a key differentiator for the success of ict firms as the industry is moving with a rapid pace of innovations that have a shorter life cycle. the exploitation of ip and patents in particular is often linked with business sales, export quality, and marketing needs, along with research direction strategies to ensure that a firm remains competitive in business. figure 1 patenting strategies and firm’s value. 39 firms have started looking and opting for various ip management strategies to achieve success and competitive advantage. ip strategy has thus become a force for organizational performance, and businesses have begun aligning their ip strategy with their business strategy to successfully survive and thrive in the market place. amongst various ip rights, trade secrets, copyrights, and patents can be used for protection in the ict domain, especially for software; however, patents are the preferred choice of firms as they provide stronger protection for the functionality of a product, the process of service. it is also seen that firms with active and systematic patent management outperform those that remain inactive and non-strategic. various offensive and defensive ip strategies exist with the aim of attaining a competitive edge in the market place. defensive strategies seek to provide a firm the freedom to operate and commercialize an invention without hindrance from patents that belong to others. defensive strategies are thought to be reactionary, focused on protecting the current value of ip. offensive patenting, on the other hand, is mostly exercised by firms having large patent portfolios or those owning patents of high quality. offensive ip management strategies are thought to be proactive, focused on protecting the future value of ip. industries are more inclined to undertake an offensive or defensive strategy to enjoy positive performance outcomes. ipr in general and patents in particular serve as a barter system that helps promote innovation and research by putting innovation in the public domain in exchange for exclusive rights over the said technology for a limited period. the creation, protection, and enforcement of ip can bring direct, practical long-term economic interest to nations. firms seek to gain and maintain a competitive advantage by managing and protecting ip as they accumulate patent portfolios to gain market share or increase profits via multiple strategies. the study puts forth various ip strategies used by firms. many of these strategies are still evolving and are implemented proactively or reactively depending on various 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(2017) a new model for identifying emerging technologies. journal of intelligence studies in business. 7 (1) 79-86. article url: https://ojs.hh.se/index.php/jisib/article/view/202 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a new model for identifying emerging technologies stephanie f. hughesa adepartment of management, haile/us bank college of business, northern kentucky university, highland heights, kentucky, usa; hughesst@nku.edu journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies proposal of an assessment scale in competitive intelligence applied to the tourism sector gisela casado salguero, pedro carlos pp. 38-47 resende jr. and ignacio aldeanueva fernández key success factors to business intelligence solution implementation journal of intelligence studies in business v o l 7 , n o 1 , 2 0 1 7 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 7, no. 1 2017 josé manuel villamarín garcía and pp. 48-69 beatriz helena díaz pinzón business intelligence and smes: bridging the gap ekavi papachristodoulou, margarita pp. 70-78 koutsaki and efstathios kirkos klaus solberg søilen pp. 5-37 a new model for identifying emerging technologies klaus solberg søilen pp. 79-86 a new model for identifying emerging technologies stephanie f. hughesa adepartment of management, haile/us bank college of business, northern kentucky university, highland heights, kentucky, usa *corresponding author: hughesst@nku.edu received 1 january 2017; accepted 3 march 2017 abstract today, the complexity of so many emerging technologies requires an understanding of adjacent technologies often originating from multiple industries. technology sequence analysis has been used by organizations, governments and industries to help make sense of the many variables impacting the evolution of technologies. this technique relies heavily on the input of experts who can offer perspectives on the status of current technologies while also highlighting the potential opportunities in the future. however, the volume and speed at which scientific research is accelerating is making it nearly impossible for even the most knowledgeable expert to stay current with research in their own industries. today however, the use of big data search tools can help identify emerging trends around disruptive technologies well before many of the experts have fully grasped the impact of these technologies. despite the fear of many in the intelligence community that these tools will make their jobs obsolete, we expect that the value of the intelligence expert will increase given their unique knowledge of relevant data sources and how to connect the data in meaningful ways to derive value for the firm. we propose a new forecasting model that incorporates a combination of technology sequencing analysis and big data tools within the organization while also leveraging experts from across the open innovation spectrum. this new model, informed by current client engagements, has the potential to create significant competitive advantages for organizations as they benefit from expanded search breadth, search depth and search speed all while leveraging a range of internal and external experts to make sense of the rapidly changing technological landscape confronting their environment. keywords big data analytics, competitive intelligence, emerging technology, open innovation, technology sequence analysis 1. introduction recent technological innovations such as unmanned aerial vehicles (uavs) or driverless cars are hugely disruptive forces that have already, or soon will, dramatically alter the competitive landscape of markets from aerospace and the automotive industry to communication and defense. these innovations often involve technologies from multiple technological domains that can make a challenging environment for the experts tasked with staying on top of all the innovative activity. long established market leaders can be quickly undermined by start-ups who understand the potential value of a technology long before most of the rest of the market is even aware of its existence. clayton christenson (2000) in his landmark book, the innovator’s dilemma, coined the term “disruptive technologies” to describe innovations that create new markets by discovering new categories of customers. disruption, per christenson, can be achieved by harnessing new technologies, developing journal of intelligence studies in business vol. 7, no. 1 (2017) pp. 79-86 open access: freely available at: https://ojs.hh.se/ 80 new business models and/or exploiting old technologies in new ways. to achieve the kind of disruptive innovation conceptualized by christenson however, firms increasingly must look outside their own organizations and, often, outside their own industries to harness the innovative power of the crowd. these adjacent technologies are difficult for even the largest firms to uncover on their own. this innovation challenge is made even more difficult by the fact that so much innovative activity is taking place across the globe. chesbrough (2003) coined the term “open innovation” to refer to firms that actively engage with outside organizations to enhance their own innovative capability. while firms have been doing this sort of thing for a long time, the focus on the positive impact of these activities on firm performance helped to jumpstart a broader acceptance across industries to utilize different types of external research partners such as universities, competitors, and government agencies, among others (cohen and levinthal, 1990; parida, et. al., 2012). so, if firms want to take advantage of the wisdom of the crowd today, they must figure out how to become knowledgeable about all the activity occurring within their own industry, within adjacent industries and across the globe. they must also be able to identify and quantify the key researchers, associated organizations and the key technologies that would be most relevant to their own innovation processes. finally, they must be able to accomplish this in an efficient, and relatively cost-effective manner. scenario analysis is one type of methodology that can help companies deal with the uncertainty of a future disruption. bishop et al., (2007) suggested that “scenarios contain the stories of multiple futures” that are both creative and analytically feasible and help companies imagine a future world based on data and perspective grounded in the present. scenario analysis techniques include a broad range of possible methodologies including expert judgment, event sequence analysis, backcasting, technology road-mapping, trend impact analysis, matrix analysis and technology emergent pathways among others (bishop et al., 2007; smith and saritas, 2010). smith and saritas (2010) attempted to define the boundaries of these techniques a bit more specifically by suggesting that foresight analysis is a set of strategic tools that supports government and industry decisions by outlining multiple plausible futures over a 5 to 25 year horizon while highlighting emerging opportunities and threats along those various pathways. each of these techniques is generally characterized in the following ways: provides a set of scenarios based primarily on expert judgment, sometimes, but not always, obtained through group engagement, mostly working from the present day set of events forward and rarely, involves the use of computers to assist the development process (bishop et al., 2007). the utilization of external experts alone, or in a group, is rooted in the hope that they can provide a view of the future that is, ideally, not necessarily dependent on the company’s present-day reality. in the recent past, this type of analysis was mostly carried out by consulting organizations, working on behalf of big businesses, who accessed the expertise of key opinion leaders (kols) to share their insight on where they believed the market was going and what was necessary to achieve this future state. there are three main problems with this approach. first, the focus of these efforts was often within single industries and lacked the perspective of an across-industry analysis which might uncover the adjacent technologies that are often so necessary to successful disruptive products coming to market today. for example, major camera manufacturers likely never thought about the possibility of a major technological change coming from outside their industry that smart phone-enabled photography would have on their market and thus, were unprepared for the seismic impact this technology had on their core business. second, the use of consulting firms and kols to help make sense of the changing landscape of technology takes a long time to execute and produces a temporally-constrained view of what is happening with the technology. finally, the length of time to recruit kols and execute an analysis of technologies from across industries can turn into an incredibly costly endeavor often outside the reach of most firms. in this research, we propose the coupling of a big data analytics machine-learning capability with technology sequence analysis to offer an enhanced model for identifying emerging technologies. this approach can help firms deal with the huge challenge of initiating and managing disruptive innovation activities where success may depend on both the breadth and depth of the search as well as the convergence of varying maturation paths of different technologies. we also emphasize the importance of leveraging different kinds of 81 experts in this model including internal intelligence experts, data analytic experts and industry content experts as each of these groups plays a vital role in identifying, linking and contextualizing data to understand the evolution of specific technologies and their impact on the industry. 2. open innovation a recent headline in a july, 2016 edition of fortune magazine declared “data is the new oil” and projected that with only 20% of the world’s data open and available, data will soon become its own currency (vanian, 2016). even as more governments make commitments to open their data to the public, an estimated 2.5 billion gbs of new data is created every single day (schneider, 2016). in the united states, there are over 193,000 databases available to the public (data.gov, 2016) and within the european union, there are over 9,000 and counting (eu open data portal, 2016). the economics & statistics administration of the u.s department of commerce estimated that anywhere from $24-$221 billion is generated annually from using the data the government provides (useas, 2016). the open innovation model is premised on the idea that invention and innovation do not have to take place in the same place where they are turned into products and commercialized (inauen & schenker-wicki, 2012). largely, as a result, of the huge investments in research and development (r&d) efforts, government and academic institutions tend to generate a lot of the inventions and innovations that eventually do get commercialized. in 2016 alone, the federal government was responsible for approximately $138 billion in r&d efforts while academia invested another $18 billion (bernstein, 2016). researchers have touted the benefits of open innovation to include the lower cost of r&d activities (chesbrough, 2006), lower risk for the r&d efforts that can be shared by external partners (herzog, 2008) and, better innovation performance (hwang & lee, 2010; un et al., 2010). researchers further distinguished the nature of the flow of open innovation activities by focusing on inbound open innovation, which describes the one-way flow of external knowledge into a firm (sisodiya, 2013); outbound open innovation where the knowledge flows out of an organization to external research partners (powell, et. al., 1996) and coupled open innovation where knowledge flows are bi-directional and result in active collaboration between internal and external researchers and partners (cheng & huizingh, 2014; gassmann & enkel, 2004). research has also confirmed the positive impact on firm performance by assessing the type of collaborating firm (e.g. customer, supplier, competitor, academic institution) involved in a firm’s open innovation strategy (tether & tajar, 2008; un, et. al., 2010; wang et. al., 2015). while it is conceivable to imagine that opening a firm’s internal r&d efforts to outside knowledge would benefit from exposure to the diversity of thought and ideas, there appears to be a limit to the actual benefit due to the complexity and cost of establishing, maintaining and monitoring these external collaborative relationships. to understand that limit, greco et. al., (2016) looked at the effect of search breadth (how broad the search process is), search depth (how intensive the interaction is between external collaborative partners) activities and the volume of bi-directional collaborative relationships the firm is engaged in and their impact on firm performance and found diminishing marginal returns. the researchers found that the broader the firm’s search breadth and the higher the number of collaborative relationships, the more returns were diminished. the authors suggest that “a firm may be harmed by interacting with an excessive number of innovation channels, consequently reducing its effectiveness in bringing innovation ideas into implementation” (greco et al., 2016). these results did not hold on the search depth metric as relationships that experience repeated interactions between the partners tended to be more robust in general and did not appear to evidence diminishing returns. so, it appears that a firm’s open innovation activity could benefit from a more systematic and targeted approach to identifying technologies that will align with the organization’s research efforts if it wants to accelerate the innovative output arising from its open innovation efforts. 3. technology sequence analysis firms use technology sequence analysis to help them understand the extent, interdependence and likelihood of a wide range of emerging and adjacent technologies that are necessary to achieve a desired future state in their industry. sequence analysis breaks down broad patterns of overall processes into sequences of activities or events that produce specific outcomes 82 constituting change (isabella, 1990). so, the idea is to start with a future desired technology or product and work backwards by identifying the technologies or activities that must precede this future state. at each stage of the technology development process, there will be some assigned probability associated with their occurrence. probabilities are assigned by accessing expert judgment, usually in the form of a panel of experts, who review the details of the required technologies to assess technological fit and estimated time to “market ready” status. since we do not know exactly which event or events will occur, the probabilities assigned to later events will change as earlier events occur. this process produces a decision tree of nodes and branches with different outcomes listed along with assigned probabilities. van de ven and poole (1990) used sequence analysis to explain how and why innovations develop over time and which developmental paths lead to the success and failure of different kinds of innovations. subsequent applications of sequence analysis looked at how organizational outcomes are influenced by changing the order of steps in a process (pentland, 2003) or patterns of behavior (adair & brett, 2005) over some defined timeframe. each of these efforts focused on process activities related to firm-level innovation. technology sequence analysis can also be used to assist in understanding how to accelerate product innovation. abbott (1990) looked at whether and when certain events occur in the product development process as indicators of successful results. salvato (2009) used sequence analysis to uncover the way capabilities are developed through everyday activities involved in the new product development processes and found organizations that track innovative activity occurring at all levels of the organization and, sometimes, outside its boundaries are generally more successful at renewing their core capabilities. perks, et al., (2012) adopted sequence analysis to track the process of cocreation in the incremental development of a radical new service. using sequence analysis on an experiential simulation dataset, thatchenkery, et al., (2012) found that firms’ r&d performance and performance in new markets increased significantly when firms engage in a consistent time-paced competitive sequence whose sequences follow regular (i.e. continuous or periodic) patterns and whose sequences do not conform to what their competitors perform well. perks and roberts (2013) utilized technology sequence analysis to investigate the series of micro activities, involved in product innovation, which are carried out by individuals within and outside the organization that create change over a longer time frame. each of these applications of technology sequence analysis focuses on understanding the steps or processes involved in the innovation process, at a firm level, that can lead to more successful product outcomes. there has been little publicized use of technology sequence analysis at the industry or country level, likely due to the inability of researchers to accurately access and categorize research being done outside the boundaries of individual firms. however, the ability to incorporate a big data research capability that leverages significant search depth and search breadth into this process makes technology sequencing at an industry or country level a more realistic possibility. incorporating experts from outside the firm, across industries and from the furthest reaches of the globe is now possible due to the power of big data analytics, which can combine millions of records, aggregate search terms and, through the utilization of various machine-learning algorithms, identify the most relevant research and the companies and researchers most responsible for producing it. 4. expert judgment expert judgment is one of the most common forms of scenario analysis and is used often to support many other forms of forecasting. typically, expert judgment is accessed through panels convened for reviewing research or technology developed internally by organizations. the value of expert panels is that diverse ideas and alternatives can be examined especially by tapping into those outside the industry mainstream including “canaries”, iconoclasts and idea provocateurs (smith and saritas, 2011). while not inexpensive, the cost of empaneling experts from academia and government entities is far cheaper than hiring these people on as employees of the organization and the perspective that is offered is often free from organizational bias. functionally, expert opinion supports a wide range of firm activities from strategy and competitive intelligence through to research and development. competitive intelligence (ci) involves the collection of internal and external information to help companies predict the next 83 moves of their competitors, customers, and government entities (gilad, 1996). in the ci field, industry experts are a critical source of perspective and information used to inform a firm’s tactical and strategic activities. internal ci professionals are tasked with helping the company make sense of these activities and must be knowledgeable about where to find the most relevant data to answer the company’s most urgent intelligence needs. in many ways, these individuals act as translational experts for the organization by helping to frame research requests from internal constituents and then identifying the appropriate external data sources and experts to address these requests. most ci units will outsource their data collection efforts, including hiring or interviewing experts, to third-party research firms. these groups maintain lists of industry experts that they rely on for key insight into what is happening in the industry. a key limitation of this approach is that often the networks are not deep enough in their bench capacity, broad enough in their industry perspective or refreshed frequently enough with new perspectives to provide the kind of insight and foresight that can give an organization confidence about the magnitude of the changes that might lay ahead or how to respond to them. 5. proposed new technology sequence model with big data capability the proposed new model follows closely the suggestions of several researchers to augment existing forecasting models to include utilizing big data analytic capabilities in the process (kajikawa et al., 2010; vaseashta, 2014; park et al., 2016). in utilizing computer-assisted citation network analysis across a broad range of energy-related publications, kajikawa and his colleagues were able to efficiently build a technology roadmap for energy research that was incredibly effective at highlighting emerging areas of technology such as fuel cell and solar cell technology, despite the huge proliferation of readily available sciencerelated content. vaseashta (2014) combined three different methodologies, including technology foresight analysis, trend analysis and automated data analytics to demonstrate the potential of a new model for surveillance of emerging trends in science, technology and intelligence environments. park et al., (2016) used patent data as a source and, in employing various statistical measures, were able to map out where the market for 3d printing was in its technological evolution and where it might be heading into the future. as previously highlighted, most forecasting techniques rely heavily on expert feedback. however, as the proliferation of data continues to grow and the speed at which this data is produced accelerates, constructing a future technology roadmap based strictly on expert feedback is quickly becoming an obsolete approach. the fact that so much of this data production is also occurring globally makes figure 1 enhanced technology sequence model. 84 expert-focused forecasting models even more of a concern as the ability to capture, process and analyze huge troves of global data becomes almost impossible to achieve without the assistance of some powerful data analytic platform. the very real possibility of missing a significant technological milestone can become an unfortunate reality if the company’s network of experts does not stay up on the latest developments in their field of expertise. the model in figure 1 goes beyond merely augmenting existing foresight techniques with big data capability. instead it places a heavy emphasis on the role and timing of when to include different kinds of experts along with big data capability to help firms achieve significant differentiation in technological forecasting. we separate the role of experts in the process into “front-end translation experts” who are primarily company insiders such as strategists or ci professionals, “data scientists” who attempt to address the needs of the internal client by automating data capture and analysis using machine learning capabilities and “industry content experts” who generally come from outside the company and who provide a view of the industry or technology that is free of organizational bias. the role of the front-end expert is highlighted in this expanded forecasting model as someone who takes the requirements of internal departmental units and makes sense of them by identifying the appropriate data sources, metrics and internal experts to incorporate into the process to produce a relevant and targeted analysis. by leveraging the potential of the open innovation philosophy, the role of the data scientist expert is to enhance the search breadth, search depth and search speed by focusing on connecting relevant data sources (either open or proprietary) and utilizing machine learning to find underlying patterns between technologies, people and organizations. these tools help to quantify experts’ contributions to their scientific and technical disciplines and makes uncovering industry experts a much more scientific process. in this way, the role of the industry content expert can then be leveraged in a much more meaningful way because we can identify and quantify the expertise of researchers within and across technological disciplines by their specific areas of expertise. this opens the potential for a much richer analysis of the technological landscape by broadening the firm’s reach to those with very specific knowledge in technical domains and often from outside a single industry. these experts can provide insight and estimates of probabilities into the specific obstacles and opportunities around a broad range of core and adjacent technologies and help to develop a more sensitive and accurate technology sequence analysis. then recent emergence of many data analytic platforms provides organizations options for whether to “build”, “buy” or “license” to get into the market. obviously, the shortest path to implementation will be to license one of the many platform tools that are available today. the upside to licensing or leasing is the speed of implementation and lower upfront costs to participate. the downside is generally a lack of customization for both data sources and the algorithms that make sense of it all. the “buy” option provides some greater options for customization but with lower implementation speed than the license model and higher costs as well. finally, the “build” option provides the greatest amount of flexibility around customization but costs significantly more than the other two options and takes far longer to implement. 6. conclusions and future research traditional forecasting methods which rely heavily on expert guidance must begin to incorporate big data analytic capabilities in their process or risk soon becoming obsolete. this paper reinforces the important role of several different kinds of experts in technology forecasts but emphasizes the importance of adding big data tools to the process primarily because of the need in all industries to be “globally data aware” (kostoff & schaller, 2001), which is impossible to do today with the volume and speed of production of digital data. the choice of whether to build, buy or lease a big data analytic platform will be heavily dependent on the long-term vision of the organization with respect to the choice of data sources. if an organization possesses data that they believe provides a true leading view of the market, they may want to exercise greater control over that data and opt for a custombuilt platform tool. if they are unsure what data they want or need or are just getting started, they may want to consider leasing a tool early on. as they gain experience and better appreciation of the value of leveraging connected data, the buy or build approach becomes the more valuable option. one caveat to this choice is the fact that currently there is 85 a dearth of data scientists and visualization professionals so if a firm lacks the resources to attract and retain these type of professionals, they may face limited options regardless of interest or need. ci professionals who embrace the utilization of big data tools into their ci processes should find increased relevance and power within their organizations as they become crucial to the organization’s ability to leverage the power of these new tools. the role of the “translational expert” who can take the research problems and, by leveraging data and speed, generate advantages for the organization over its competitors becomes exponentially more valuable to the organization. ci professionals should seek out training and seminars to learn as much as they can about big data tools and the various business models associated with the utilization of these tools so they can begin to identify opportunities inside their organization where these tools may provide value. finally, ci professionals should begin to create a reference library for the automated data that the company currently produces, especially anything that highlights the behavior of its customers or market that can potentially be combined with external data to drive new and unique insights. the fact that ci professionals have responsibility for maintaining competitive and market intelligence oversight for entire product lines, divisions or for the firm makes them uniquely positioned to appreciate the research and data needs of their internal customers and able better translate these needs to the data analytic experts. the new battlefield of the future for strategy and ci professionals will be to identify the appropriate mix of datasets and algorithms that create a truly predictive big data intelligence tool. as more and more data become available to mine, it is the company’s knowledge of how to combine internal and external datasets utilizing proprietary algorithms and their access to industry experts that will become the new 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(2013). a review of longitudinal research in the product innovation field, with discussion of utility and conduct of sequence analysis. journal of product innovation management, nov. 2013, 30 (6), 1099-1111 parida, v., westerberg, m., & frishammar, j., (2012). inbound open innovation activities in high-tech smes: the impact on innovation performance. journal of small business management, 50 (2), 283–309 pentland, b. t. (2003). sequential variety in work processes. organization sciences, 14 (5). 528540. perks, h., gruber, t., & edvardsson, b. (2012). co-creation in radical service innovation: a systematic analysis of micro-level processes. journal of product innovation management, 29, 935-951. perks, h. & roberts, d. (2013). a review of longitudinal research in the product innovation field, with discussion of utility and conduct of sequence analysis. journal of product innovation management, 30 (6), 10991111. park, a., kim, j., lee, h., jang, d., & jum, s. (2016). methodology of technological evolution for three-dimensional printing. industrial management & data systems, 116 (1), 122146. powell, w.w., koput, k., smith-doerr, l., (1996). interorganizational collaboration and the locus of innovation: networks of learning in biotechnology. administrative science quarterly, 41(1), 116–145. salvato, c. (2009). capabilities unveiled: the role of ordinary activities in the evolution of product development processes. organization science, 20(2). 384-409. schneider, c. (2016, may 25). the biggest data challenges that you might not even know you have, ibm blog, retrieved from https://www.ibm.com/blogs/watson/2016/05/bi ggest-data-challenges-might-not-even-know/ sisodiya, s.r., johnson, j.l., grégoire, y., (2013). inbound open innovation for enhanced performance: enables and opportunities. industrial marketing management. 42(5), 836–849. smith, j.e. & saritas, o. (2010). science and technology foresight baker’s dozen: a pocket primer of comparative and combined foresight methods. foresight, 13(2), 79-96. tether, b. s., & tajar, a. (2008). beyond industry university links: sourcing knowledge for innovation from consultants, private research organizations and the public science-base. research policy, 37(6), 1079-1095. thatchenkery, s. m., katila, r. & chen, e. l. (2012). sequences of competitive moves and effects on firm performance. academy of management annual meeting proceedings. 2012, p1-1 u.s. federal government (2016). retrieved from https://www.data.gov/ u.s. economic & statistics administration. (2016). retrieved from http://www.esa.doc.gov/reports/fosteringinnovation-creating-jobs-driving-betterdecisions-value-government-data un, c. a., cuervo-cazurra, a., & asakawa, k. (2010). r&d collaborations and product innovation. journal of product innovation management, 27(5), 673-689. van de ven, a., & poole, s. 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(2015). the effect of inbound open innovation on firm performance: evidence from high-tech industry. technological forecasting & social change, 99, 222-230. vol11no3paper5 to cite this article: søilen, k.s (2021) book review: we never expected that – a corporative study of failures in national and business intelligence by avner barnea. journal of intelligence studies in business. 11 (3) 76-79. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 3 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index book review: we never expected that – a corporative study of failures in national and business intelligence by avner barnea klaus solberg søilena,* adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; *klasol@hh.se journal of intelligence studies in business please scroll down for article book review: we never expected that – a corporative study of failures in national and business intelligence by avner barnea klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se received 20 december 2021 accepted 25 december 2021 we never expected that – a corporative study of failures in national and business intelligence. by avner barnea. (lexington books, lanham, maryland, 2021) for jisib barnea has previously written about competitive intelligence in israel (2016), about israeli start-ups in cyber security (2018), and about how ai will change intelligence and decision-making (2020). the book, we never expected that – a corporative study of failures in national and business intelligence, is not on israeli intelligence per se. still, the best documented of the four cases presented come from the first intifada in 1993 when barnea was well situated to observe what was going on behind the scenes. for 27 years, until 1997, he was the senior official for intelligence in the prime minister’s office. since then, he has been a competitive intelligence consultant, a teacher and student of intelligence studies and sine 2016 a research fellow at the national security studies center, nssc. the book, which is a translation of a book in hebrew, which again builds on the author’s phd thesis, proposes an analysis of a series of intelligence failures. to study failures is a good way to learn. it is a good methodology, maybe the best. to present a book with both government and state failures is also a good idea from the perspective that there are bound to be fruitful parallels. so far so good. unless one speaks hebrew, it’s difficult to access experience gathered from within israeli intelligence as so little is translated. israeli intelligence relies very much on an oral tradition of knowledge transfer which makes this task even more difficult. when we learn about how israeli intelligence works and how the people working there think, the sources are often external, like in the classic book dangerous liaison by cockburn and cockburn (1991). the aim of the book is to classify events according to the type of risk they represent. this is highly laudable and much needed. the book starts with a claim: that intelligence methodology has reached a “glass ceiling,” meaning an unacknowledged barrier to advancement in the intelligence profession. this could be true as it corresponds to findings in the intelligence literature. barnea also argues that there have been too few parallels drawn between state and private experience of intelligence failures, which is also a fair claim. a weakness in the book is that it only builds on four cases, two from the private and two from the public sector. the empirical basis may, in other words, be limited. the outcome of the exercise of the book is the presentation of a new dichotomy, or model, dividing “risks,” or better “surprises,” into “concentrated” and “diffused”. the author claims that this will make a breakthrough in the intelligence field and the reader immediately wonders whether this claim can journal of intelligence studies in business vol. 11, no. 3 (2021) pp. 76-79 open access: freely available at: https://ojs.hh.se/ 77 be supported by the data presented. the notion of a “concentrated attack” refers to handel (2003) in the book, but it’s actually from an earlier article by handel published in 1984, described as a “deliberate and concentrated attack”. these attacks are planned by one actor carrying out plans (singer 1958), through concealment and disinformation. the other type of attack is a “diffused attack,” defined as “surprise attacks, spontaneous and unplanned”. so, they cannot be predicted. so, we have one group of attacks that is planned and one that is unplanned. it’s a weakness that there are not clearer definitions and that the dichotomy presented in the book is not discussed in greater detail compared to other existing theories that divide and try to understand the notion of risk. this goes back at least to what is called knightian uncertainty, a lack of any quantifiable knowledge about some possible occurrence, as opposed to the presence of quantifiable risk. knight’s risk is something that can be measured. that which cannot be measured is called “uncertainty”. so, following the knightian notion of risk, there would be no case of a diffused risk that cannot be measured. barnea’s “diffused risk” may remind some of the notion, popularized by rumsfeld, about “unknown unknowns,” or events we simply cannot know because even the idea of the type of risk is unknown to us. the idea is actually not rumsfeld’s but goes back to the psychologist joseph luft (1916–2014). in 1955 he created a useful tool for illustrating and improving self-awareness, and mutual understanding between individuals within a group with his colleague harry ingham. they called the model the johari window model and it is shown in figure 1. barnea’s unknown unknowns are of a special type: namely spontaneous and unplanned. we can also imagine nonspontaneous unknown unknowns and planned unknown unknowns. unknown unknowns simply mean that others know, but we do not. they are events that are not even on our radar. in many cases they often speak more to our perception of the world and what may happen, and to our cognitive abilities. barnea’s concentrated attack could be said to be a known unknown, a “deliberate and concentrated attack” planned by one actor through concealment and disinformation. it is what we can know if we had a more capable intelligence organization. the author uses the first intifada and the 2008 recession as examples of diffused attacks, meaning they are surprise attacks, spontaneous and unplanned. one could argue that the first intifada in december 1987 must have had a minimum of planning to be carried through, but the author does a good job at showing the complexity and uncertainty that led to this event, for example that riots broke out instantly without much plo direction. there was a string of events which led up to it, including the killing of a jewish person in gaza followed by the killing of palestinian workers in a civilian car. but there must have been a minimum of planning among those who came to the street. anyway, the question becomes one of the degrees of planning. the second example given by the author is the 2008 recession. this example is less clear. the recession was not deliberately planned of course, but it could have been foreseen as a result of reckless economic policies carried out in the us over decades. many analysts did foresee it and have received much acclaim as analysts for having done so. thus, it’s more difficult to see this example as a clear case of a “spontaneous” event. there were also many “surprises” in the recession, not the least the timing of the crisis, as is often the case with stock markets. it’s practically impossible to say exactly when they will unfold. you know something is brewing but it’s difficult to know at what date it will be disrupted. we are very much in a similar situation with the stock markets today, they could fall drastically in 2022. it’s more difficult to say in which quarter this may happen. as examples of concentrated attacks, the author uses the 9/11 attack and the collapse of ibm in 1993. 9/11 was not planned by one actor, but it certainly was a “deliberate and concentrated attack”, and it was concealed. it was planned by an organization, al-qaeda, not figure 1 the johari window model. 78 by an individual, even though khalid sheikh mohammed is often cited as the mastermind. thus, the example is not difficult to accept, but the definition given by the author at the beginning raises questions as to whether the example was well chosen. the last example presented by the author is ibm. ibm did not collapse in 1993 as it says in the introduction (“1993 collapse of ibm”), but in chapter 7 this is adjusted to the headline “almost collapse”, which is more correct. in the late 1980s and early 1990s, the company faced difficulty after decades of success. however, the difficulties of ibm were not caused by one person or cause, but a series of incidents. it’s not clear to what degree this was an intelligence failure. one reason is suggested as: “this was because ibm’s core mainframe business had been disrupted by the advent of the personal computer and the client server. ibm couldn’t compete with smaller nimbler less diversified competitors.” denning (2011). ceo thomas j. watson jr. suffered a heart attack and retired in 1971. after that the company had no less than four unsuccessful successors, until louis “lou” gerstner took over in 1993. gerstner, ceo of ibm from 1993 until 2002, turned the company around mainly by starting to listen to its clients, according to denning (2011). the intelligence effort this implied, for example starting an official competitive intelligence function and office at ibm, has been noted by many authors, for example behnke and slayton (1998) and prescott and williams (2003). at the end of the book the author suggests how methods/activities can be transferred from business intelligence to national intelligence and vice versa. the book consequently uses the term “business intelligence” (bi) as was common some decades ago before bi became all about software and not about “competitive intelligence” or “market intelligence” when appropriate. this can be confusing to some readers. the author notes that for bi it’s about sharing information internally, relying more on open source and measuring the value of information. for national intelligence to bi it’s about defining key intelligence topics and using competing hypotheses (“analysis of competing hypothesis, ach), as developed by richards (dick) j. heuer, jr., of the cia in the 1970s, building on abductive reasoning. these are probably good conclusions, but i expect that they come from a much larger amount of experience, which the author has not shown through the four cases presented in the book. the book is valuable more because of the collective experience that barnea brings into the conclusion in chapter 8 than because of what can be drawn out of the model, or the cases used. what makes barnea’s book especially interesting is how the author brings experience from the state sector to the private sector and vice versa, having worked in both sectors himself. references barnea, a. (2015). failures in national and business intelligence: a comparative study. phd diss., university of haifa, 66-129. barnea, a. (2016). study on competitive intelligence in israel: 2016 update. journal of intelligence studies in business, 6(2). barnea, a. (2018). israeli start-ups–especially in cyber security: can a new model enhance their survival rate? journal of intelligence studies in business, 8(1). barnea, a. (2020). how will ai change intelligence and decision-making? journal of intelligence studies in business, 1(1). barnea, a. (2021). we never expected that: a comparative study of failures in national and business intelligence. rowman & littlefield. behnke, l., & slayton, p. (1998). shaping a corporate competitive intelligence function at ibm. competitive intelligence review: published in cooperation with the society of competitive intelligence professionals, 9(2), 49. cockburn, a., & cockburn, l. (1991). dangerous liaison: the inside story of the us-israeli covert relationship. harpercollins. denning, steve (2011). “why did ibm survive”, forbes, jul 10th handel, m. i. (1984). intelligence and the problem of strategic surprise. the journal of strategic studies, 7(3), 229-281. kahana, e. (2006). historical dictionary of israeli intelligence. scarecrow press. knight, f. h. (1921). risk, uncertainty and profit (vol. 31). houghton mifflin. prescott, j. e., & williams, r. (2003). the userdriven competitive intelligence model: a new paradigm for ci. competitive intelligence magazine, 6(5), 10-14. 79 singer, j. d. (1958). threat-perception and the armament-tension dilemma. journal of conflict resolution, 2(1), 90-105. page 4 editors note vol 9 no 2 editor’s note vol 9, no 2 (2019) a deeper look at the collective intelligence phenomenon for the upcoming conference on intelligence studies at ici 2020 in bad nauheim, germany the focus of this issue of jisib is on collective intelligence and foresight. the first two papers by søilen and almedia and lesca deal with collective intelligence from an intelligence studies perspective. it may be said that the internet itself is a gigantic collective intelligence effort, the largest in human history. open source is a prerequisite for this system to work for everyone. the article by černý et al. is on open source. all other contributions are on the connection between the internet, software and intelligence. this issue consists of seven articles to compensate for two articles that were taken out by editors in the last issue. the first article by søilen entitled “making sense of the collective intelligence field: a review” is a historical review of the field of collective intelligence. the paper shows how collective intelligence is an interdisciplinary field and argues there is a flaw in the notion of “wisdom of crowds”. collective intelligence can be understood in terms of social systems theory and as such this approach has been fruitful for the social sciences, although so far not very popular. it also bares relevance for the study of business and economics. the second article by almeida and lesca is entitled “collective intelligence process to interpret weak signals and early warnings”. early warning and the detection of weak signals is a vital topic for any intelligence organization. two aspects are discussed in the paper, the importance of new technology and collective sense making or interpretation the third article by shaikh and singhal entitled “study on the various intellectual property management strategies used and implemented by ict firms for business intelligence” deals with intellectual property rights and patenting strategies. the authors identify a number of defensive and offensive ip strategies applied to ict companies. the results have a bearing on patent acquisitions. the fourth article by lamrhari et al. is entitled “web intelligence for understanding customer satisfaction: application of latent dirichlet allocation (lda) and the kano model”. customer satisfaction today is mostly measured with data from the internet, using different business intelligence techniques. the kano model is still valuablei,ii, but the way we gather information to assess the different levels in the model has changed. the authors use latent dirichlet allocation to analyze the voice of customer (voc) in online reviews. they suggest that bi techniques and a fuzzy-kano model can enable companies to better understand their customers’ online reviews. the fifth article by nahili et al. is entitled “a new corpus-based convolutional neutral network for big data text analysis”. companies need efficient ways to analyze everything that is said about them on the internet (reviews, comments). the paper suggests a convolutional neural network (cnn) as it has been successfully used for text classification. imdb movie reviews and reuters datasets were used for the experiment. the sixth article by černý et al. is entitled “using open data and google search data for competitive intelligence analysis”. taking the czech antidepressant market as an example, the authors show how competitive intelligence can be obtained using google search data, google trend and other osint sources. the seventh article by dadkhah et al. is entitled “the potential of business intelligence tools for expert findings”. the paper suggests a way for researchers to find experts using business intelligence tools. the same method may also be used by any business or person looking for experts on a specific topic. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. copyright © 2019 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 9, no 2 (2019) p. 4-5 open access: freely available at: https://ojs.hh.se/ 5 we hope to see you all at the ici 2020 on the 16-17 march, 2020. the deadline for the two-page abstract submission is march 1st, 2020. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2019 jisib, halmstad university. all rights reserved. i tontini, g., solberg søilen, k., silveira, a. (2013). how interactions of service attributes affect customer satisfaction: a study of the kano model’s attributes. total quality management & business excellence, 24(11-12), 1253-1271 ii tontini, g., söilen, k. s., & zanchett, r. (2017). nonlinear antecedents of customer satisfaction and loyalty in third-party logistics services (3pl). asia pacific journal of marketing and logistics, 29(5), 1116-1135. vol11no2paper1 to cite this article: maune, a. (2020) intention to use mobile applications in competitive intelligence: an extended conceptual framework. journal of intelligence studies in business. 11 (2) 6-29. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 2 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index intention to use mobile applications in competitive intelligence: an extended conceptual framework alexander maunea,b,* auniversity of south africa, pretoria, south africa; bbuse, bindura, zimbabwe *alexandermaune6@gmail.com journal of intelligence studies in business please scroll down for article intention to use mobile applications in competitive intelligence: an extended conceptual framework alexander maunea,b,* auniversity of south africa, pretoria, south africa; bbuse, bindura, zimbabwe; *corresponding author: alexandermaune6@gmail.com received 2 march 2021 accepted 24 september 2021 abstract this article aims at identifying the key antecedents to behavioral intention and use behavior of individuals regarding mobile applications that can support competitive intelligence of firms. attention was given to perspective antecedents in behavioural intention and use behaviour of mobile applications in competitive intelligence. a qualitative research based on a literature review of 21 peer-reviewed journal articles covering a period of six years from 2014 was used. these articles were collected from separate databases using search engines. all utaut2 constructs had a direct and significant influence on mobile application use. following significance factors were ease of use, perceived usefulness, perceived enjoyment, and trust. however, perceived risk, subjective norms, and self-efficacy were insignificant. an extended model was later developed with 15 constructs. this article highlights the key determinants of user behavior regarding mobile applications that firms should act on in order to foster the acceptance of these technologies despite the privacy risks that arise. previous research has largely ignored the influence of perceptive antecedents in the behavioural intention and use behaviour of mobile applications in competitive intelligence. this article covers this gap by drawing attention to the cognitive psychological perspective of the phenomenon. keywords behavioural intention, competitive intelligence, mobile applications, mobile apps, unified theory of acceptance and use of technology, use behaviour, utaut, utaut2 1. introduction competitive intelligence (ci) has become a global phenomenon in today’s environment of intensifying global competition because of big data analytics. this includes ai, iot, 5g/6g, cybersecurity, as well as the adoption and use of mobile applications such as whatsapp, facebook, instagram, twitter, and telegram that have enabled high-speed availability and transfer of large amounts of data collected and accumulated by individuals and organisations over the years. carlos and herrera (2021) argue that the business environment of today is complex and dynamic due to increasing global competition. people in business need to master and know all the information that has strategic value, and ci is positioned as the most appropriate tool to achieve this goal (carlos and herrera, 2021). organisations and individuals alike that can transform this data into information and knowledge faster remain at the top and thus achieve a competitive edge. the advent of mobile application technologies and the wider availability of internet connections have made it easier for individuals and organizations to access large amounts of data. singer and friedman (2014) argue that what constitutes the internet itself is evolving before us in an even more fundamental way. it journal of intelligence studies in business vol. 11, no. 2 (2021) pp. 6-29 open access: freely available at: https://ojs.hh.se/ 7 is simultaneously becoming bigger and far more personalized (singer and friedman, 2014). according to bulao (2021) and vuleta (2021), on average, every human created at least 1.7 mb of data per second in 2020. they predict cloud data storage around the world will amount to 200+ zettabytes by 2025. this will be up from 2019’s 4.4 zettabytes and 2020’s 44 zettabytes. the two further argue that by 2025, there will be 175 zettabytes of data in the global data sphere. they further argue that in 2020 2.5 quintillion data bytes daily were created and as of july 2020, the world had 4.8 billion internet users. that is a huge increase from the 2.6 billion internet users in 2013. mobile phones were more popular than other devices, with 4.28 billion unique users. by 2025 people will generate 463 exabytes of data and by 2030, nine out of every ten people aged six and above would be digitally active (vuleta, 2021 and bulao, 2021). rather than passively receiving this onslaught of online information, the individual users are creating and tailoring sites to their personal use, ultimately revealing more about themselves online. the amount of data is on the rise with the increase in smartphone subscriptions globally. this amount of big data is critical to decision-makers and data analysts. the use of ci has, however, become relevant now more than before. solberg (2019) argues that ci has developed and emerged with information technology (it) solutions over the past ten years. most advancements and developments are now about it solutions and applications. this has again given rise to a whole new world of intelligence-related problems and opportunities, not only for engineers but for users of these technologies (degerstedt, 2015 and solberg, 2019). it is probably fair to say that the intelligence perspective has never been as important for businesses as it is today, thereby refuting the notion that ci is dead or there is nothing new in the field. the use of mobile applications such as whatsapp, facebook, twitter, instagram, and telegram to mention just but a few have both increased and strengthened the role of ci globally. mobile apps have become big data mines for gathering intelligent information in this competitive environment. thus far, ci research has focused primarily on the same phenomenon, how to gather information to make better decisions (solberg, 2019). some research has begun to address ci from a business intelligence perspective, big data analytics, ai this time around using algorithms as a predictive tool. previously, ci research was more concerned with web and desktop applications but now there is a rapid shift towards mobile applications due to information available anytime, anywhere from everyone who has a phone. this sudden shift has also been influenced by an increase in the number of mobile apps and the number of active users per day. mobile intelligence has now combined bi, transactions, and multimedia. to singer and friedman (2014), facebook, twitter, google and all the rest are, in many ways the very definition of modern life though recently, issues around privacy, information security, mass surveillance, snooping, information theft through face recognition, cancel culture, and freedom of speech have been raised. a functioning internet with freedom of speech and a good connection to the social networks of one`s choice is a sign not just of modernity, but of civilization itself (singer and friedman, 2014). the two further argue that this is because the internet is where people live, do business, meet, and fall in love. it has become the central platform for business, culture, and personal relationships. other areas beginning to draw research attention are data mining, search engine optimization, social media marketing and digital marketing in general (solberg, 2019). accordingly, recent literature reviews have highlighted the need to further address mobile app users’ perspectives and psychology. these reviews acknowledge that the nature of users’ perspectives depends on the mobile app being examined, as motivations for use are driven by different antecedents. these notions are supported by the claims that understanding the users is fundamental to understanding ci, much like understanding the decision-makers’ needs is fundamental to understanding ci gathering. to singer and friedman (2014), to misunderstand the centrality of these services today is to make a fundamental error. the internet is no longer the luxury it was, for most people, knowingly or not, it is life. to address this gap, this article seeks to introduce a reasoning perspective into understanding ci through a literature review of the behavioural intention and use behaviour of mobile application users. this approach acknowledges that human behaviour is influenced by mental processes, and this is how people acquire, transform and use information (shneor and munimb, 2019). more importantly, the article seeks to examine and 8 understand the drivers, motivators, and influencers of acceptance and use of mobile applications in ci. given the availability of mobile applications across the globe, it is critical to appreciate the reasons behind the behaviour of users of these platforms in the ci process. this study uses the extended unified theory of acceptance and use of technology (hereafter, utaut2) developed by venkatesh, thong, and xu (2012). this theory can be used to capture the behavioural intention and use behaviour of users of mobile apps in ci and their antecedents. it also seeks to study mobile app acceptance and use in the ci process. venkatesh, thong, and xu (2012) developed the utaut2 as a comprehensive integrated model for better-understanding consumer acceptance toward new technology or system. to this end, the assumption is that due to the novelty of digital manifestation, privacy, information security, risk of mass surveillance, data theft, hacking, and cyberbullying, individuals involved in gathering ci through mobile apps are unlikely to engage in this behaviour without prior and preliminary consideration. previous research has largely ignored the influence of perspective antecedents in behavioural intention and use behaviour in mobile applications use in ci. this article gives attention to the cognitive psychological perspective of this phenomenon with the knowledge that personality affects behaviour. the underlying aim of this study is to identify the predictors of behavioural intention and use behaviour of ci professionals and experts in using mobile applications in intelligence gathering for decision-making. an extended framework, utaut2 is presented as the basis for identifying behaviour intention and use behaviour predictors in using mobile applications in intelligence gathering by ci professionals and experts. the starting point is appreciating these predictors of behaviour first since this behaviour has a strong bearing in the adoption and use of technology: in this case, mobile applications. the article follows a systematic literature review on mobile application use for ci through the lens of utaut2. an exploratory design was followed to confront utaut2 with extant studies on mobile application use for ci. the study focused more on the perspective antecedents in behavioural intention and use behaviour of mobile application use in ci. the study highlights the key determinants of user behaviour regarding mobile applications. identifying the determinants of user behaviour regarding mobile application use for ci enables firms to act appropriately in order to foster the acceptance and use of the mobile technologies despite the privacy risks associated with their use, thereby creating a virtuous cycle for the development of ci practices. the findings have both managerial and practical implications; their contribution is scientific, practical, societal, political, and educational. the remainder of this article is as follows. first a review of the literature regarding the mobile application acceptance and use, and users’ perspectives and psychological aspects in ci. a literature review is done to understand the reasons or influencers of mobile apps user behavioural intention and use in ci and how relevant the utaut2 framework is in this phenomenon. subsequently, the findings and discussions in light of prior research are presented. key contributions, limitations and implications for further future research are presented in the conclusion. 2. literature review ci research has focused primarily on how to gather information to make better decisions (solberg, 2019). researchers have concentrated on the ci process with little or no attention given to the cognitive psychological perspective of users. in most cases, the behavioural intention and use behaviour of mobile app users have been ignored. previous research on ci was more concerned with web and desktop applications but the focus has rapidly shifted towards mobile applications due to a surge in the use of mobile applications and digitalization of global economies. of current concern to researchers are issues surrounding big data, ai, iot, 5g, algorithms, and cybersecurity. with the rise in data censorship, risk of mass surveillance, data theft through face recognition, and victimization, users of mobile applications are unlikely to engage in ci gathering behaviour without prior and preliminary consideration. the acceptance and use of mobile applications in ci have become more of a planned behaviour. according to singer and friedman (2014), mobile applications have in many ways influenced the very definition of modern life. the two further argue that a functioning internet with freedom of speech and a good connection to social networks is a sign not just of modernity, but of civilization itself. however, recent developments in mobile applications have caused huge debates around data privacy, 9 and freedom of speech. data censorship, removal of accounts of users, and removal of platforms from networks has caused an outcry by users who feel that their rights are being infringed. examples include the case of donald j. trump, parler, and telegram to mention just but a few. these developments now have a serious bearing on the acceptance and use of mobile applications. motivators and drivers of user behavioural intention and use behaviour are now shifted towards risk, security, privacy, and freedom of speech. for example, telegram, surpassed 500 million active users on the 18th of january 2020 with more than 25 million new users from around the world joining the platform as a result of freedom and security issues in other platforms (for example, https://t.me/telegramtips/233). telegram argues that it stands for freedom and privacy and has many easy to use features (ibid). researchers have attempted to explain the acceptance and use of mobile applications with varied outcomes that range from social influence, utilitarian gratification, hedonic gratification of affection and leisure, website social presence, reasons linked to cost, sense of community, unlocking new opportunities for intimate communication, addictive behaviours as well as data gathering (ellison, steinfield and lampe, 2007; java et al., 2007; schneider et al., 2009; brandtzæg and heim, 2009; xu et al., 2012; church and de oliveira, 2013; cheung, 2014; sultan, 2014; pielot et al., 2014; bouhnik and deshen, 2014; narula and jindal, 2015; karapanos, teixeira and gouveia, 2016; and so, 2016). ci has played an important role in economic development and its factors (maune, 2017). the objective of ci has been to understand how the surrounding competitive environment impacts an organization – by monitoring events, actors, trends, research breakthroughs, and so forth – to be able to make relevant strategic decisions (degerstedt, 2015). degerstedt (2015) argues that a major trend in the world today is the increasing competition in global and digitalized markets where the speed of change and innovation is becoming faster than ever before. ci helps provide a better understanding of the global world. however, to søilen (2017), developments in new technology are also posing a serious threat to companies as today every individual is a potential spy. corporate espionage has also become a big problem with its consequences still underestimated. the current information/knowledge generation has placed ci at the centre stage of economic growth (maune, 2017). previously, factors such as capital, labour and natural resources were traditionally considered as the only factors which matter for economic growth. however, the technology explosion of the 1990s primarily stimulated the notion of ci as being something entirely new or even revolutionary (maune, 2014a). maune (2014b) argues that the emergence of the internet and online databases have offered an almost inexhaustible supply of information that has caused information overload in many instances. this has resulted in the development of social competitive intelligence by intelligence practitioners (maune, 2017). 2.1 unified theory of acceptance and use of technology according to benbasat and barki (2007) and venkatesh et al. (2007), understanding individual acceptance and use of information technology is one of the most mature streams of information systems research. several theoretical models were developed from psychology and sociology to explain technology acceptance and use (venkatesh et al., 2003). a review and synthesis of eight theories/models of technology use by venkatesh et al. (2003) resulted in the unified theory of acceptance and use of technology (utaut). to venkatesh et al. (2003), utaut has distilled the critical factors and contingencies related to the figure 1 the basic concept underlying the user acceptance model. adapted from venkatesh et al. (2003). 10 prediction of behavioural intention to use technology primarily in organizational contexts. figure 1 presents the basic conceptual framework underlying the class of models explaining individual acceptance of information technology that forms the basis of this research. according to venkatesh et al. (2012), venkatesh et al. (2003) developed utaut as a comprehensive synthesis of prior technology acceptance research based on a review of the extant literature. utaut has four key constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) that influence behavioural intention to use a technology and/or technology use. venkatesh et al. (2012) adapt these constructs and definitions from utaut to the consumer technology acceptance and use context. here, performance expectancy is defined as the degree to which using technology will provide benefits to consumers in performing certain activities. effort expectancy is the degree of ease associated with consumers’ use of technology, social influence is the extent to which consumers perceive that important others (for example, family and friends) believe they should use a particular technology, and facilitating conditions refer to consumers’ perceptions of the resources and support available to perform a behaviour (brown and venkatesh, 2005; venkatesh et al., 2003; and venkatesh et al., 2012). according to utaut, performance expectancy, effort expectancy, and social influence are theorized to influence behavioural intention to use technology, while behavioural intention and facilitating conditions determine technology use. also, individual difference variables, namely age, gender, and experience are theorized to moderate various utaut relationships (figure 2). based on the gaps in utaut (venkatesh et al., 2003) and the associated theoretical explanation provided, venkatesh et al. (2012) integrate hedonic motivation, price value, and habit into utaut to tailor it to the consumer technology use context later known as utaut2 (figure 2.). brown and venkatesh (2005) define hedonic motivation as the fun or pleasure derived from using technology, and it has been shown to play an important role in determining technology acceptance and use. van der heijden (2004) and thong et al. (2006) find hedonic motivation (perceived enjoyment) figure 2 utaut2 model. adapted from venkatesh et al. (2012). 11 to influence technology acceptance and use directly. brown and venkatesh (2005) and childers et al. (2001) also find hedonic motivation an important determinant of technology acceptance and use in the consumer context. thus, venkatesh et al. (2012) add hedonic motivation as a predictor of consumers’ behavioural intention to use technology. an important difference between a consumer use setting and the organizational use setting, where utaut was developed, is that consumers usually bear the monetary cost of such use whereas employees do not. the cost and pricing structure may have a significant impact on consumers’ technology use. for instance, there is evidence that the popularity of short messaging services (sms) in china is due to the low pricing of sms relative to other types of mobile internet applications (chan et al., 2008). dodds et al. (1991), cited by venkatesh et al. (2012), define price value as consumers’ cognitive tradeoff between the perceived benefits of the applications and the monetary cost for using them. the price value is positive when the benefits of using technology are perceived to be greater than the monetary cost and such price value has a positive impact on intention (venkatesh et al., 2012). thus, venkatesh et al. (2012) add price value as a predictor of behavioural intention to use technology. prior research on technology use has introduced two related yet distinct constructs, namely experience and habit. experience, as conceptualized in prior research (kim and malhotra, 2005 and venkatesh et al., 2003), reflects an opportunity to use a target technology and is typically operationalized as the passage of time from the initial use of technology by an individual. a habit has been defined as the extent to which people tend to perform behaviours automatically because of learning (limayem et al., 2007), while kim et al. (2005) equate habit with automaticity. although conceptualized rather similarly, a habit has been operationalized in two distinct ways: first, habit is viewed as prior behaviour (kim and malhotra, 2005); and second, habit is measured as the extent to which an individual believes the behaviour to be automatic (limayem et al., 2007). consequently, there are at least two key distinctions between experience and habit. one distinction is that experience is a necessary but not sufficient condition for the formation of habit. a second distinction is that the passage of chronological time, that is, the experience can result in the formation of differing levels of habit depending on the extent of interaction and familiarity that is developed with a target technology. 2.2 competitive intelligence ci is variously presented as a process, a function, a product, or a mix of all three (gilad and gilad, 1985 cited by bergeron and hiller, 2002). gračanin, kalac, and jovanović (2015) argue that there is no single and universal definition of ci and the most commonly used and cited definition was provided by the society of competitive intelligence professionals (scips) where ci is defined as the process of monitoring the competitive environment. ci is defined as actionable recommendations arising from a systematic process involving planning, gathering, analysing and disseminating information on the external environment for opportunities, or developments that have the potential to affect a company’s or country’s competitive situation (calof and skinner, 1999). ci has become a strategic business tool that has long been proposed to increase companies’ competitiveness (montgomery and urban, 1970; pearce, 1976; montgomery and weinberg, 1979; porter, 1980). ci enables managers in companies of all sizes to make decisions about everything, including marketing, research and development, investments and long-term business strategies. following the arguments of many different authors cited by pellissier and nenzhelele (2013) in the 50 definitions of ci, one is forced to conclude that there is no universally agreed definition of ci although there are common characteristics in each, and there are also unique characteristics identified. ci should stimulate an organization’s creativeness, innovativeness, and willingness to change (bergeron and hiller, 2002), in a continuing quest to create an evolving and intelligent organization. a more unified view of ci was recently provided by madureira, popoviˇc, and castelli (2021) as “… the process and forwardlooking practices used in producing knowledge about the competitive environment to improve organizational performance.” it is interesting to note how ci has developed over the years since the 1980s and 1990s when the founders jan herring, leonard fuld, and ben gilad built it. to solberg (2019) ci now consists of an interesting body of literature, though it was not the first term to deal with questions of intelligence in private organizations, and it is not the last. before ci 12 there was social intelligence, strategic intelligence and corporate intelligence, and now it includes terms such as market intelligence, marketing intelligence, business intelligence, collective intelligence, financial intelligence, scientific and technical intelligence, foresight, insight, and equivalent terms in other languages as well. maune (2019) argues that with the advent of globalisation, a term that was introduced in the 1980s, the role of ci becomes more visible and is strengthened by the increase in competition among nations and organisations. calof and skinner (1999) state that countries such as the usa, france, sweden, japan and canada have recognized the value of government and industry working jointly in the development of an intelligence culture. according to the strategic and competitive intelligence professionals website (scips), ci has spread to six continents with 53 international chapters distributed as follows; north america (28), australia (1), europe (10), asia (8), africa (3), and south america (3). scip now has overs 300 ambassadors, 280 certified professionals, and 480 thought leaders. ci is both a process and a product (intelligence) (bose, 2008). the process of ci is the action of gathering, analyzing, and applying information about products, competitors, suppliers, regulators, partners, and customers for the shortand long-term planning needs of an organization (kahaner, 1998). the ci process is a continuous cycle. even though the phases are shown in sequence, are all conducted concurrently. while available information is processed, additional information is collected, and the intelligence staff is planning and directing the collection effort to meet new demands. previously collected and processed information (intelligence) is disseminated as soon as it is available or needed. five phases constitute the ci cycle (kahaner, 1998, and mcgonagle and vella, 2012). the first phase, planning and direction, defines the company’s requirements in terms of what information is needed? why is it needed? when is it due? the collection activities include identification of all potential sources of information and then research and gather the right data legally and ethically from all available sources and put it in an ordered form. the analysis – a crucial step – activities involve analyzing collected data to identify patterns, relationships, or anomalies in it. dissemination – report and inform – is the finished product or the ci communicated back to the decision-makers in a format that is easily understood. feedback – evaluate – is the final phase in the cycle. it involves measuring the figure 3 competitive intelligence process. adapted from dishman and calof (2007, pp. 779). 13 impact of the intelligence that was provided to the decision-makers. these basic phases are linked to each other by a feedback loop (kahaner, 1998, and mcgonagle and vella, 2012). dishman and calof (2007) argue that the ci process identified in the literature includes the constructs of planning and focus, collection, analysis, communication, process and structure, and organisational awareness and culture as given shown in figure 3. barnea (2013) traces the ci roots to national intelligence. barnea (2013) argues that governmental decision-makers are aware that intelligence is an important and often critical tool to the national decision-making process. to him, ci is based on the "intelligence cycle". ci adopted the discipline of national intelligence and applies it to its needs, with necessary modifications. according to field manual [fm] 34-3 (1990), ci operations follow a four-phase process known as the intelligence cycle. the intelligence cycle is oriented to the mission (fm 34-3, 1990); this can be for the country or organisation. the fm 34-3 (1990) reports that "supervising and planning are inherent in all phases of the cycle. the intelligence cycle is continuous. even though the four phases are conducted in sequence, all are conducted concurrently. while available information is processed, additional information is collected, and the intelligence staff is planning and directing the collection effort to meet new demands. previously collected and processed information (intelligence) is disseminated as soon as it is available or needed.” mobile apps are becoming critical in the ci process given their perceived mobility and the limited functionality of websites (murphy, 2011). table 1 shows some of the ci resources from social media platforms. 2.3 determinants of mobile application use for competitive intelligence mobile applications are defined as software that can perform certain tasks for the users operating their mobile devices (islam and mazumder, 2011). mobile applications differ from websites, as the user downloads them from the mobile application store, which is a database that allows the mobile user to discover and install available mobile applications (wong, 2012). table 1 competitive intelligence type and resources. competitive intelligence type competitive intelligence resources people events news, company websites, social media platforms such as facebook, twitter, whatsapp etc. competitor strategies – technology investments etc. news, discussion forums, blogs, patent search sites, social media platforms. consumer sentiments review sites, social networking sites, social media platforms such as facebook, twitter, whatsapp etc. promotional events and pricing social media platforms such as facebook, twitter, whatsapp etc. related realworld events news, social media platforms such as facebook, twitter, whatsapp etc. the surge in the uptake and use of mobile apps has helped many organisations and individuals in making decisions. mobile applications have also played a very critical role in the ci process. why mobile applications? bulao (2021) and vuleta (2021) state that google, facebook, microsoft, and amazon store at least 1,200 petabytes of information. google handles a staggering 1.2 trillion searches every year. the two state that there were 71.5 billion apps downloaded worldwide in the first half of 2020. google play store had 52.3 billion total downloaded apps during that period while the app store had 18.3 billion. in 2020, roughly 306.4 billion emails were sent and received each day and in 2024, the number of emails will be about 361 billion every day (http://www.statista.com). bulao (2021) states that experts predict that google searches will amount to about 2 trillion in the whole of 2021. that equates to 6 billion searches a day. in terms of connection, for example, over 2 billion minutes of voice and video calls are made on whatsapp daily, and one billion people use this platform every day with more than two billion whatsapp users in 180 countries as of 2020. facebook had 1.82 billion daily active users and 2.7 billion monthly active users as of the 3rd quarter of 2020. facebook generated four petabytes of data every day in 2020. the total number of twitter users was 340 million as of october 2020 with 500 million tweets sent per day. these figures show how large these mobile applications are in terms of data repository. these numbers are 14 more likely to increase with the adoption of 5g technology. 5g has the ability to increase data transmission speed by up to 100 times and decrease latency from about 20 milliseconds to one millisecond (http://www.statista.com). the utaut2 has been widely used to examine the acceptance and use of it. for example through instant messengers, webbased learning, cellphone application adoption, acceptance of network by urban people, use of electronic public service innovations, electronic booking solutions, academic settings, mobile banking adoption, mobile commerce, and mobile shopping (lin and anol, 2008; chiu and wang, 2008; tan et al., 2010; and yuen et al., 2010). kang (2014) argues that researchers such as gefen and straub (1997), king and he (2006), schepers and wetzels (2007), and huang (2008) suggest that theoretical models of technology adoption and use encompass other important theoretical constructs such as motivations and functional aspects. in 2012 venkatesh et al. developed the utaut2 that combines diffusion of innovation theory (dit) (rogers, 1962, 1995), theory of planned behaviour (tpb) (ajzen, 1985; fishbein and ajzen, 1975), the technology acceptance model (tam) (davis, 1989), social cognitive theory (sct) (bandura, 1997), and unified theory of acceptance and use of technology (utaut) (venkatesh et al., 2003) to encompasses functional and contextual factors to increase the explanatory power in the adoption and use of information technology. the utaut2 specifically uses several key variables that lead to the intention of use and actual use. venkatesh et al. (2012) explain that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit are factors influencing behavioural intention or use behaviour of it. table 2 behaviour intention measurement items and sources. latent variable measurement items source pe (performance expectancy) pe1. i find mobile apps useful in my daily life. pe2. using mobile apps increases my chances of achieving things that are important to me. pe3. using mobile apps helps me accomplish things more quickly. pe4. using mobile apps increases my productivity. pe1-4 adapted and modified from “performance expectancy” in and venkatesh et al. (2003) and venkatesh et al. (2012). ee (effort expectancy) ee1. learning how to use mobile apps is easy for me. ee2. my interaction with mobile apps is clear and understandable. ee3. i find mobile apps easy to use. ee4. it is easy for me to become skillful at using mobile apps. ee1-4 adapted and modified from “effort expectancy” in and venkatesh et al. (2003) and venkatesh et al. (2012). si (social influence) si1. people who are important to me think that i should use mobile apps. si2. people who influence my behaviour think that i should use mobile apps. si3. people whose opinions that i value prefer that i use mobile apps. si1-3 adapted and modified from “social influence” in venkatesh et al. (2012) and venkatesh et al. (2003) for si1-2. fc (facilitating conditions) fc1. i have the resources necessary to use mobile apps. fc2. i have the knowledge necessary to use mobile apps. fc3. mobile apps are compatible with other technologies i use. fc4. i can get help from others when i have difficulties using mobile apps. fc1-4 adapted and modified from “facilitating conditions” in venkatesh et al. (2003) and venkatesh et al. (2012). hm (hedonic motivation) hm1. using mobile apps is fun. hm2. using mobile apps is enjoyable. hm3. using mobile apps is very entertaining. hm1-3 adapted and modified from “hedonic motivation” in venkatesh et al. (2012). pv (price value) pv1. mobile apps is reasonably priced. pv2. mobile apps is a good value for the money. pv3. at the current price, mobile apps provide good value. pv1-3 adapted and modified from “price value” in venkatesh et al. (2012). ht (habit) ht1. the use of mobile apps has become a habit for me. ht2. i am addicted to using mobile apps. ht3. i must use mobile apps. ht4. using mobile apps has become natural to me. ht1-4 adapted and modified from “habit” in venkatesh et al. (2012). bi (behavioural intention) bi1. i intend to continue using mobile apps in the future. bi2. i will always try to use mobile apps in my daily life. bi3. i plan to continue to use mobile apps frequently. bi1-3 adapted and modified from “behavioural intention” in venkatesh et al. (2003) and venkatesh et al. (2012). tt (trust) based on my previous experience in using mobile apps… tt1. i think they are honest. tt2. i think they are trustworthy. tt3. i think they provide good services to users. tt4. i think they care about their users and take their concerns seriously. tt5. i think they keep users’ security and privacy in mind. tt1-5 adapted and modified from “trust” in groß (2015). research has shown that performance expectancy (rogers, 1995; venkatesh et al., 2003; arya, 2011; pynoo et al., 2011; and venkatesh et al., 2012), effort expectancy (davis et al., 1989; bandura, 1997; agarwal and prasad, 1999; venkatesh et al., 2003; han et al., 2006; gupta et al., 2008; wang and wang, 2010; curtis et al., 2010; and venkatesh et al., 2012), social influence (ajzen, 1985; moore and benbasat, 1991; venkatesh and davis, 2000; venkatesh et al., 2003; yang, 2007; kijsanayotin et al., 2009; homburg et al., 2010; chong et al., 2010; and venkatesh et al., 2012), facilitating conditions (venkatesh et al., 2003; brown and venkatesh, 2005; and venkatesh et al. 2012, hedonic motivation (childers et al., 2001; van der heijden, 2004; brown and venkatesh, 2005; thong et al., 2006; and venkatesh et al., 2012), price value (zeithaml 1988; dodds et al., 1991; chan et al., 2008; and venkatesh et al. 2012), habit (ouellette and wood, 1998; ajzen, 2002; kim et al., 2005; kim and malhotra 2005; limayem et al., 2007; ajzen and fishbein, 2005; and venkatesh et al. 2012), and trust (gefen, karahanna and straub, 2003; luarn and lin, 2005; lin and wang, 2005; wei et al., 2009; joubert and van, 2013; vasileiadis, 2014; and groß, 2015) toward it predicts behavioural intention and use behaviour (figure 2 and table 2). in other words, the individual intention to use the technology depends on whether the technology is perceived as useful, easy to use, suggested by important others, the needed resources to use the technology are present, the technology is fun to use, the price value of the technology, and if the users have a habit of using the technology. 3. methods data were collected from published peerreviewed journal articles collected from electronic databases. a broad search strategy was used covering separate databases such as ebsco, emeralds, proquest, sage, sabinet, taylor & francis, and google scholar. articles on acceptance and use of it, specifically those that focused on mobile applications, were selected. also, articles that were based on the utaut and utaut2 by venkatesh et al. (2003) and venkatesh et al. (2012) respectively were targeted. the intention of reviewing these articles was to identify constructs that predict behavioural intention and behavioural use of mobile applications in ci. keywords such as, ‘competitive intelligence,’ ‘business intelligence,’ ‘tactical intelligence,’ ‘market intelligence,’ ‘corporate intelligence,’ ‘competitor intelligence,’ ‘social competitive intelligence,’ ‘technological intelligence,’ ‘product intelligence,’ ‘mobile apps,’ ‘mobile applications,’ ‘utaut,’ ‘utaut2,’ ‘unified theory of acceptance and use of technology,’ ‘behavioural intention,’ ‘behavioural use,’ and ‘strategic intelligence’ were used in search engines to find relevant articles. to ensure reliability, peer-reviewed journal articles were highly considered. the researcher skimmed through the text of the journal articles first, checking whether it was relevant for this research article. reviewing data from existing journal articles was necessary to enhance the generalisability of the findings. the purpose of this review was to identify the motivation for acceptance and use of mobile apps in ci as a way of enhancing the understanding and appreciation of human behaviour in the use of mobile apps in ci. criteria for inclusion of articles in the review also included that the articles must be written in english. for effectiveness, the author reviewed 21 articles (appendix 1). articles were strictly selected to achieve the desired objective. appendix 1 presents the distribution and articles that were used for this study. the researcher also brought in ideas from outside the traditionally defined field of ci and it and integrated different approaches, lines of investigation, or theories that had no previous connections. the researcher`s purpose was not only descriptive but also critical. the researcher used literature not as an authority to be referred to, but as a useful but fallible source of ideas about developments in the acceptance and use of mobile apps in ci. the review was done to serve as the basis for understanding the causal or correlational patterns of interconnections across events, ideas, observations, concepts, constructs, knowledge, interpretations and other components of mobile app acceptance and use in ci. 3.1 analysis first, the survey items were checked for measurement properties and sources (table 2) as given by venkatesh et al. (2003), venkatesh et al. (2012), and groß (2015). the estimation or proposed model was informed by studies by venkatesh et al. (2003), venkatesh et al. (2012), and groß (2015). this was followed by 16 a gathering of keywords and constructs used in the 21 reviewed journal articles. these words were analysed using the monkeylearn word cloud generator, a powerful ai visualization tool (figures 4 and 5). this tool scores words for relevance as shown in table 3 and table 4. the researcher had to use his discretion to determine the cutoff of the ranking. the keywords and constructs generated from the word cloud and survey items, measurement properties and sources in table 2 were used as a basis to formulate the proposed model of mobile applications intention of use and actual use in ci (figure 6). the constructs used in the model were supported by the studies reviewed (appendix 1). the researcher also found support from the following theories: tpb, tam, utaut, and utaut2. the only missing construct or variable from all the reviewed articles was ci. no articles that integrated ci with mobile application acceptance and use from a cognitive psychological perspective were found. this promoted the development of an integrated model to cater to the cognitive perspective (figure 6). the ci construct is very important given the nature of the business environment that has become very dynamic and competitive, driven by developments in it, ai, big data, algorithms, 5g, and cybersecurity. decision making has become a challenge due to huge amounts of data availability. ci has become a relevant strategic business tool. as a result, ci has developed and emerged with it to provide decision-making solutions over the years. perceived usefulness, perceived ease of use and perceived enjoyment were omitted as these were perceived to be the same as performance expectancy, effort expectancy, and hedonic motivation, respectively (van heijden, 2004 and thong et al., 2006). to avoid confusion and duplication, these constructs were omitted even though they were presented as separate constructs in some of the reviewed journal articles. see table 2 for specific details. in the end, the model in figure 6 was proposed as the final model with 11 predictors of behavioural intention and use behaviour of mobile applications for ci. table 3 rank, keywords and their relevance. rank keywords relevance 1 mobile application 0.994 2 structural equation modelling 0.745 3 technology acceptance model 0.559 4 mobile commerce 0.497 5 social influence 0.497 6 performance expectancy 0.373 7 effort expectancy 0.373 8 technology adoption 0.373 9 utaut 0.373 10 utaut2 0.311 11 hedonic motivation 0.248 12 mobile payment 0.248 13 behavioural intention 0.248 14 trust 0.186 15 use of technology 0.186 16 ease of use 0.186 17 perceived usefulness 0.124 figure 4 a visual representation of keywords. 17 table 4 rank, latent variables and their relevance. rank latent variables relevance 1 performance expectancy 0.997 2 effort expectancy 0.935 3 social influence 0.935 4 behavioural intention 0.623 5 hedonic motivation 0.498 6 ease of use 0.467 7 price value 0.436 8 perceived usefulness 0.374 9 perceived risk 0.249 10 perceived enjoyment 0.187 11 facilitating conditions 0.155 12 habits 0.129 13 subjective norm 0.125 14 social efficacy 0.063 15 trust 0.051 4. discussion appendix 2 presents the effects of selected predictors of behavioural intention and use in mobile applications. from the table, as developed from the 21 peer-reviewed journal articles, utaut2 predictors had a direct and significant influence on mobile application use with hedonic motivation, ease of use, and habits having 100% direct influence. latent variables including hedonic motivation, effort expectancy, price value, habits, performance expectancy, social influence, and facilitating conditions have proved to be significant in influencing mobile application use and acceptance (appendix 2). these are followed by ease of use, perceived usefulness, perceived enjoyment, and trust, though ease of use, perceived usefulness, and perceived enjoyment were omitted from the final proposed research model. as for perceived risk, abrahão et al. (2016) and khurana and jain (2019) find it to have a direct and significant influence on mobile application behavioural intention and use while liu and tai (2016) and chao (2019) find it insignificant, but due to recent developments in social media networks, perceived risk remains significant and having a direct influence on mobile applications user behavioural intentions. subjective norms and self-efficacy have been found to exert significant influence on behavioural intention (roy, 2017), but still uğur and turan (2019), chao, (2019), and tarhini et al. (2019) found them to have indirect insignificant influence. these two variables are borrowed from the theory of planned behaviour developed by ajzen (1991). these will be a good addition to the utaut2 model. three moderating variables were identified with varying effects: gender, age, and experience (kang, 2014, palau-saumell et al., 2019, and nawaz and mohamed, 2020). however, the role of moderators (gender, experience, and age) needs to be explored further in future research (barua et al., 2018). 4.1 implications for research the conceptual framework of mobile applications behavioural intention and use in ci found in this study has serious future figure 5 a visual representation of latent variables. 18 research implications. to validate the proposed research model (figure 6), a deductive research approach with a huge sample is required. this will help in the generalizability of findings with the potential of replication in different cultures, nations, age groups, and sectors. such a model and its replication are critical for ci analysts and practitioners given the current mobile technology penetration as measured by its acceptance and use. also, further studies catering for developed and developing countries as well as those looking at people with different income levels and age groups within the same society would be welcomed to understand the patterns and predictors of mobile application adoption and use in ci. these studies can then help with the replication of the model in different countries, cultures and sectors as well as shed further light on the generalizability of the findings. these findings will be critical for mobile application developers as well as users. more so, such studies will help validate the explanations given regarding the insignificant influence of perceived risk, subjective norms, and self-efficacy on user behavioural intention and use of mobile applications. this presents an interesting opportunity for empirically validating these suggestions. thus, researchers can evaluate different variable combinations to explore their relationships with behavioural intention. for example, research can combine tpb and utaut2 variables to predict their influence on behavioural intention and actual use. research may also focus on mobile application security and privacy and their impact on behavioural intention and actual use of mobile applications in ci. research needs to look at the best mobile application for ci practitioners and analysts. longitudinal and mixed methods research provides another important research paradigm in the area of mobile application user behavioural intention and actual use in ci given the dynamism in mobile technology and mobile platform user censorship, alienation and cancel culture. performancy expectancy effort expectancy social influence hedonic motivation price value perceived risk facilitating conditions habits subjective norm self-efficacy trust behaviour intention e1 use behaviour e2 age gender experience figure 6 proposed research model. 19 4.2 implications for practice the study developed a conceptual framework that is useful to mobile application developers and users alike. on one hand, developers will have a better understanding of users’ needs and intentions in using their applications and on the other hand users (ci analysts, decisionmakers, professionals) will make their needs and intentions fully known to developers. given the issues surrounding privacy and cybersecurity risks associated with mobile applications, the study will be critical to policy formulation and implementation as well as regulation of mobile applications or technology companies. this study will go a long way in helping businesses develop competitive strategies through ci. the combination of different predictors of behavioural intention and the use of mobile applications in ci from different theories provides an in-depth understanding of this phenomenon. particularly, utaut constructs turned out to have a well-established influence on acceptance and use of mobile applications. the current study therefore theoretically attempts to combine utaut2 constructs with other concepts or variables of cognitive behaviour to develop a robust conceptual framework that enhances the understanding of mobile application use in ci. this study contributes theoretically to the utaut2 model with particular emphasis on the role of cognitive behaviour in the use of mobile applications in ci. practically, there is no literature that has attempted to examine the relationship between utaut, mobile applications, and ci. this is still a grey area that requires more research, hence a follow-up is needed that will address this issue from an empirical point of view to establish the relationships that exists between constructs of utaut, mobile applications and ci. there is need to address the ci professionals as to the best mobile application to use. this entails ranking these mobile applications in terms of significance as a source of intelligence for decision making. an empirical survey will address this through involving experts and professionals both in mobile applications and ci. all these issues will be addressed in an empirical way as there is no current study that has addressed the issue. this has become more critical and urgent given the amount of big data created and stored by mobile applications on a daily basis as shown above. for ci professionals and analysts, mobile applications have become the biggest mines for intelligent data for decisionmaking. ci cannot avoid mobile applications and remain relevant given the amount of data that is created and stored by mobile applications. the predictions by vuleta (2021) and bulao (2021) that by 2030 nine out of every ten people aged six and above would be digitally active is just an example of how rapidly data production is growing each day. predictors of behaviour are very critical for ci professionals and experts in this competitive environment as a result of technological developments. understanding of behavioural intentions of users of technology has become more important than ever before. in this case research has shown that predictors such as performance expectancy, effort expectancy, social influence, ease of use, price value, perceived risk, and trust (see tables 4 and 5) are important in determining one’s behaviour in using mobile applications. this information is critical for players in ci and developers of mobile applications. what users need is more important than just imposing things on them. 4.3 limitations several factors limited this study. a qualitative research approach was used based on a literature review of 21 published peer-reviewed articles which to some might be viewed as a small sample but to develop a conceptual framework the sample was adequate given the nature and timeframe of the study. according to neuman (2014), doing an extensive professional summary review that covers all of the research literature on a broad question could take years for a skilled researcher. on the other hand, the same person could finish a narrowly focused review in a specialized area in a week. nevertheless, as noted by shneor and munimb (2019), a bigger sample may strengthen the generalizability of the findings and illuminate the potential roles of contextual factors in shaping the phenomena under investigation. this study builds on neuman’s (2014) arguments that, “as in other areas of life, it is wise to find out what others have already learned about an issue before you address it on your own. doing a literature review builds on the idea that knowledge accumulates, and that one can learn from and build on what others have done. the review rests on the principle that scientific research is a collective effort, one in which many researchers contribute and share results.” this approach, though subjective in nature, was critical in giving an in-depth 20 understanding and meaning of concepts under consideration. the articles used, however, were deemed trustworthy, authentic, and credible. this article forms an important base in analyzing the behavioural intention and use of the mobile application in ci. as stated by creswell (2009), the intent of this study is not to generalize findings to individuals, sites, or places outside of those under study: the value of this study lies in the particular description and themes developed in the context of a specific site. particularity, rather than generalizability (creswell, 2009), is the hallmark of this study. the dynamics in mobile application technology also constrain the generalizability of the present findings. this study, however, forms a strong base for more robust quantitative studies based on surveys and structural equation models using advanced analytical software, such as spss, stata, r, and python. prior limited research regarding behavioural intention and use of mobile applications in ci had a negative bearing on the review. this study followed a mono-method approach which results in a certain level of method bias. nonetheless, this was addressed by considering peer-reviewed published articles and reviewing different journal articles taken from different databases, countries, years and authors (appendix 1). the study could not, however, identify the ci construct in any of the analyzed articles. the final framework, therefore, presents a representation of the determinants of mobile application use. literature has failed to show the link between these determinants for mobile application use for ci. this gap in the literature needs to be filled with an empirical study that connects the identified determinants in the model above to ci. a literature review was useful to unpack this phenomenon and identify the gaps in the literature. 5. conclusion mobile applications are an important channel through which analysts, professionals, and businesses, as well as individuals, can gather ci for decision-making purposes. ci has become a global phenomenon in today’s environment of intensifying global competition as a result of big data analytics, ai, iot, 5g/6g, cybersecurity, as well as the adoption of mobile applications such as whatsapp, facebook, instagram, and telegram that have enabled high-speed availability and transfer of large amounts of data collected and accumulated by various individuals and organisations over the years. ci must not be confused with economic espionage which is unlawful and unethical: it is legal and is associated with a detailed code of ethics. the study has budded literature on ci and mobile application behavioural intention and use behaviour. the study focused on developing a conceptual framework based on the understudied role played by cognitive antecedents in influencing behavioural intention and use of mobile applications in ci. the study showed the usability of the utaut2 model in the acceptance and use of mobile applications in ci. this culminated with the development of a conceptual framework with 11 predictors of behavioural intention and use of mobile applications in ci. the framework was developed from utaut, utaut2, tpb, and tam. the articles that were reviewed made use of these theories in examining the predictors of behavioural intention and use of mobile applications. the missing element in all these studies was ci, which this study seeks to incorporate given its role in decision-making. the integration of utaut, utaut2, tpb and tam with ci is critical considering the role of technology in the current business environment. to ensure reliability and credibility of the study, articles covering several countries such as sri-lanka, jordan, greece, spain, india, turkey, taiwan, korea, oman, bangladesh, pakistan, egypt, malaysia, germany, vietnam, and brazil from 2014 to 2020 were considered for this review. a qualitative literature review of peerreviewed journal articles was used to explore mobile application user behavioural intention and use to develop a conceptual framework that forms a base for a more robust deductive research approach. the study reviewed 21 journal articles to understand the role played by cognitive antecedents in behavioural intention. the results of this study will have a bearing on the use of mobile applications in ci. articles were drawn from reputable academic databases such as ebsco, emeralds, proquest, sage, sabinet, taylor & francis, and google scholar. the findings of this study support the generally accepted views regarding the factors influencing the acceptance and use of technology with minor variations and considerations. all utaut2 predictors of behavioural intention and use had a direct and significant influence on mobile application use 21 with hedonic motivation, ease of use, and habits having 100% direct influence (appendix 2). following in significance were ease of use, perceived usefulness, perceived enjoyment, and trust which were later dropped from the final proposed model, except for trust. however, perceived risk, subjective norms, and self-efficacy were insignificant in influencing behavioural intention and use of mobile applications (roy, 2017; uğur and turan, 2019; chao, 2019; tarhini et al., 2019; abrahão et al., 2016; khurana and jain, 2019; and liu and tai, 2016). to summarize, this study presents several contributions. the study fills a gap in mobile application behavioural intention and use in ci though this needs to be validated using sem, efa and cfa. the proposed conceptual framework provides a theoretical base for the proposed model. this framework can be applied and tested in various contexts such as m-commerce, m-marketing, m-shopping, and m-banking. this model will go a long way in helping developers, analysts, policy-makers, regulators, and users of mobile applications understand the needs of each other. 6. references agarwal, r. and prasad, j. 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(1988). “consumer perceptions of price, quality, and value: a means–end model and synthesis of evidence,” journal of marketing, vol. 52(3), pp. 2-22. appendices appendix 1. articles reviewed by authors, title, purpose, methods, and keywords. author(s) title purpose context & nature method keywords nawaz and mohamed (2020) acceptance of mobile learning by higher educational institutions in sri lanka: an utaut2 approach the purpose of this study was to investigate the factors that might influence the intention and use behaviour of mlearning systems by students in higher education in sri lanka. 453 undergraduate and postgraduate students from sri lankan state universities. selfadministering and web-form questionnaire. the model was evaluated using cfa, efa & sem. data were analysed using microsoft excel 16, ibm’s spss 22 and amos 22. structural equation modelling, utaut2, mlearning systems, higher education, sri lanka gharaibeh et al. (2020) exploring the intention to adopt mobile commerce: integrating utaut2 with social media to predict the determinants that influence consumer expectation and intention to adopt mobile jordan, cross-sectional data was collected from 400 jordanian consumers. linear regression analysis. mobile commerce, utaut2, social media, customer intention, social influence, effort expectancy, hedonic 26 commerce in jordan. motivation, performance expectancy, habit, facilitating conditions saprikis, avlogiaris, and katarachia (2020) determinants of the intention to adopt mobile augmented reality apps in shopping malls among university students the study aimed at making substantial suggestions and investigating an integrative theoretical paradigm that attempts to establish the significance of specific factors which allow using mobile augmented reality apps in shopping malls. greece – university students. crosssectional 2300 equestionnaire sent, 405 responded & 381 retained. sem, cfa & maximum likelihood estimation. augmented reality; adoption; utaut; mobile commerce; shopping mall palau-saumell, forgas-coll, sánchez-garcía, and robres (2019) user acceptance of mobile apps for restaurants: an expanded and extended utaut-2 the paper examines the adoption of mobile applications for restaurant searches and/or reservations (marsr) by users, as part of their experiential quality. spanish who owned a smartphone and use marsr applications. cross-sectional. an online (netquest.com) questionnaire survey was sent to 1200 individuals. data that was analyzed using structural equation modelling (sem) – maximum likelihood estimation procedure (eqs6.1) statistical software. mobile applications; technology adoption; utaut; perceived credibility; social influence. khurana and jain (2019) applying and extending utaut2 model of adoption of new technology in the context of m-shopping fashion apps to recognize the factors that affect the adoption of mshopping fashion apps from the consumer perspective in delhi ncr delhi-ncr, india. cross-sectional structured online survey on the sample of 557 mobile app users aged 18-25. spss amos – sem & cfa used to analyse data. mobile fashion applications, mobile shopping, utaut2, technology adoption, india uğur and turan (2019) mobile applications acceptance: a theoretical model proposal and empirical test investigating the factors influencing the behavioural intentions to use mobile apps and find out what makes some apps popular. turkey, state university. crosssectional. structured questionnaire to collect data from 1852 college students. sem, pls smartpls software. mobile apps, model suggestion, structural equation modeling (sem), technology acceptance model (tam), uses and gratifications chao (2019) factors determining the behavioral intention to use mobile learning: an application and extension of the utaut model this study explored the behavioural intention to use m-learning from the perspective of consumers taiwan, cross-sectional a questionnaire sent to 2000 university students. partial least squares (pls) regression. mobile learning, mobile selfefficacy, unified theory of acceptance and use of technology model, trust, perceived enjoyment, perceived risk jeon, ali, and lee (2019) determinants of consumers’ intentions to this study examines customers’ korean, cross-sectional an invitation survey link to 4000 potential technology acceptance; utaut; innovativeness; 27 use smartphones apps for flight ticket bookings adoption and acceptance of smartphone apps to book their flight tickets. respondents, 440 followed the invitation link, 381 respondents were retained, the final sample of 369 respondents. pls-sem smartpls 3.0 involvement; trust tarhini et al. (2019) an analysis of the factors affecting mobile commerce adoption in developing countries towards an integrated model this study aims to investigate the factors that may hinder or facilitate consumers’ adoption of mobilecommerce in developing countries oman, cross-sectional 530 questionnaires were distributed of which 432 were returned, of which 430 were retained. sem & cfa -amos 21.0. servqual, developing countries, structural equation modelling, technology adoption, utaut, mobilecommerce, developed countries alam, hu, and barua (2018) using the utaut model to determine factors affecting acceptance and use of mobile health (mhealth) services in bangladesh to identify the critical factors affecting the adoption of mhealth in the healthcare system by extending the utaut model to include perceived reliability and price value. dhaka city of bangladesh, crosssectional. survey questionnaire to 323 participants from public and private hospitals. smart pls 2.0 was used to analyse data. mhealth, utaut, general users, developing countries, bangladesh mclean (2018) examining the determents and outcomes of mobile app engagementa longitudinal perspective. this research provides insight into the determinants and outcomes of consumer engagement with a retailer’s m-commerce application. longitudinal study an online questionnaire to 689 consumers over 12 months and sem amos graphics 24 (efa, cfa). mobile applications, mcommerce, human behaviour, determinants of engagement, outcomes of engagement. sair & danish (2018) effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among pakistani consumers to understand the relationships among performance expectancy, effort expectancy, personal innovativeness and behavioural intentions…. pakistan, crosssectional a questionnairebased survey of 320. sem-amos version 23. m-commerce, performance expectancy, effort expectancy, personal innovativeness, behavioural intentions bendary & alsahouly (2018) exploring the extension of the unified theory of acceptance and use of technology, utaut2, factors effect on perceived usefulness and ease of use on mobile commerce in egypt to examine the most relevant factors for mobile commerce adoption egypt, cross-sectional questionnaire survey to 200 participants. sem amos version 20 convenience, social influence, hedonic motivations, perceived usefulness, ease of use. 28 fadzil (2017) a study on factors affecting the behavioral intention to use mobile apps in malaysia to investigate the determinants of consumer behavioural intention (bi) to use mobile apps. undergraduate students at a malaysian local university. crosssectional. survey questionnaire sent to 200 respondents. regression analysis and equation modelling by using spss software consumer behavioural intention, gender, educational level, malaysia, mobile applications, utaut2 ibrahim et al. (2017) descriptive findings regarding factors influencing mobile application acceptance among millennial in malaysia factors influencing mobile application intention behaviour among millennial. university students in malaysia. crosssectional. survey questionnaire to 200 respondents. descriptive analysis using frequency and scoring techniques. technology acceptance, mobile application use, utaut2 kiat, samadi, and hakimian (2017) consumer behaviour towards acceptance of mobile marketing to investigate the enabling factors that influence consumers' behaviour to accept mobile marketing malaysia, crosssectional 140 questionnaires designed in google forms sent to online respondents. spss – pearson & multiple regressions. roy (2017) app adoption and switching behaviour: applying the extended tam in smartphone app usage the study examines (a) the adoption behaviour of mobile apps using the extended tam framework and (b) whether adoption leads to subsequent use behaviour and switching intentions. india – university. cross-sectional target survey 600 and usable respondents 549. sem, efa, cfa, cv (maximum likelihood estimation – amos 20). mobile applications (apps); app adoption; switching behavior; extended tam; structural equation modeling schmitz, bartsch, and meyer (2016) mobile app usage and its implications for service management – empirical findings from german public transport to explain consumers’ intentions to use mobile apps of service companies germany, crosssectional an online survey using questback’s efs to collect data from 197 app users of public transportation. focus groups of 18 people mobile apps; selfservice technologies; technology acceptance model; service quality liu and tai (2016) a study of factors affecting the intention to use mobile payment services in vietnam to spot out factors affecting the intention to use a mobile payment service plan vietnam, crosssectional 604 quantitative questionnaire, spss & amos software (sem, efa, cfa, & anova). the convenience of mobility, compatibility, mpayment knowledge, ease to use, usefulness, trust of safe to use, intention to use mobile payment, vietnam abrahão, moriguchi, and andrade (2016) intention of adoption of mobile payment: an analysis in the light of the unified theory of acceptance and use of technology (utaut). to evaluate the intention of adopting a future mobile payment service from the perspective of current brazilian consumers of mobile phones. brazil, cross-sectional 30,000 emails were generated randomly and sent to brazilian telecom operator mobile phone users. 750 responses were collected, of which 605 were mobile payment; innovation; adoption intention; acceptance and use of technology. 29 validated. sem partial least squares (pls), smart pls 3.0 software. kang (2014) factors influencing the intention of mobile application use the study examined factors that predict the use of intention of mobile applications. social networking sites in an online survey, a total of 1513, 755 responses were used. sem, mlp, amos 18.0 mobile communication; mobile applications; performance expectancy; effort expectancy; social influence; motivations; use intention. appendix 2. effect of latent variables on behaviour. latent variable influence on behaviour direct/significant indirect/no significant performance expectancy nawaz and mohamed (2020), barua et al. (2018), saprikis et al. (2020), palau-saumell et al. (2019), fadzil (2017), khurana and jain (2019), ibrahim et al. (2017), gharaibeh et al. (2020), hakimian et al. (2017), chao (2019), sair & danish (2018), jeon et al. (2019), abrahão et al. (2016), tarhini et al. (2019). uğur and turan (2019), kang (2014). effort expectancy palau-saumell et al. (2019), nawaz and mohamed (2020), barua et al. (2018), fadzil (2017), ibrahim et al. (2017), gharaibeh et al. (2020), hakimian et al. (2017), chao (2019), sair & danish (2018), abrahão et al. (2016), kang (2014). tarhini et al. (2019), khurana and jain (2019). social influence palau-saumell et al. (2019), nawaz and mohamed (2020), barua et al. (2018), fadzil (2017), ibrahim et al. (2017), gharaibeh et al. (2020), abrahão et al. (2016), bendary & al-sahouly (2018). tarhini et al. (2019), khurana and jain (2019), saprikis et al. (2020), kang (2014), hakimian et al. (2017). hedonic motivation palau-saumell et al. (2019), nawaz and mohamed (2020), fadzil (2017), khurana and jain (2019), ibrahim et al. (2017), gharaibeh et al. (2020), tarhini et al. (2019), bendary & al-sahouly (2018). ease of use mclean (2018), roy (2017), schmitz et al. (2016), liu and tai (2016). price value palau-saumell et al. (2019), fadzil (2017), khurana and jain (2019), ibrahim et al. (2017), tarhini et al. (2019). gharaibeh et al. (2020), barua et al. (2018). perceived usefulness mclean (2018), roy (2017), schmitz et al. (2016), liu and tai (2016). uğur and turan (2019). perceived risk abrahão et al. (2016), khurana and jain (2019). liu and tai (2016), chao (2019). perceived enjoyment roy (2017), chao (2019), saprikis et al. (2020). mclean (2018). facilitating conditions palau-saumell et al. (2019), nawaz and mohamed (2020), barua et al. (2018), fadzil (2017), ibrahim et al. (2017), gharaibeh et al. (2020), khurana and jain (2019), jeon et al. (2019), tarhini et al. (2019). saprikis et al. (2020), hakimian et al. (2017). habits nawaz and mohamed (2020), palau-saumell et al. (2019), fadzil (2017), khurana and jain (2019), ibrahim et al. (2017), gharaibeh et al. (2020), tarhini et al. (2019). subjective norm roy (2017). uğur and turan (2019). self-efficacy roy (2017). chao (2019), tarhini et al. (2019). trust liu and tai (2016), chao (2019), tarhini et al. (2019), jeon et al. (2019). saprikis et al. (2020). vol11no1paper3 to cite this article: alnoukari, m. (2021) a framework for big data integration within the strategic management process based on a balanced scorecard methodology. journal of intelligence studies in business. 11 (1) 33-47. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 1 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a framework for big data integration within the strategic management process based on a balanced scorecard methodology mouhib alnoukaria,* asyrian private university, syria; *mouhib.alnoukari@spu.edu.sy journal of intelligence studies in business please scroll down for article a framework for big data integration within the strategic management process based on a balanced scorecard methodology mouhib alnoukaria,* asyrian private university, syria *corresponding author: mouhib.alnoukari@spu.edu.sy received 18 december 2020 accepted 29 march 2021 abstract the purpose of this research is to study the impact of big data initiatives on strategic management processes. while the majority of strategic management disciplines have had research dedicated to the use of strategic management theories to understand how big data affect organizational performance, the body of research on big data lacks academic work capable of examining how to integrate big data into the strategic management process. the main contributions of this work are: (1) it highlights the strategic use of big data; (2) it analyses the main frameworks/models proposed by scholars that support the use of big data as a strategic management tool, and outlines this research gap; and (3) it proposes a new framework that integrates big data within the strategic management process based on a balanced scorecard methodology. keywords balanced scorecard, big data, big data analytics, big data framework, business intelligence, strategic management, strategic management process 1. introduction big data (bd) is considered a key corporate asset (court, 2015; polese, troisi, grimaldi, & romeo, 2019). the decision-making process was redefined in order to incorporate the new strategic effect of bd concepts (polese, troisi, grimaldi, & romeo, 2019). bd has become a source for innovation (soon, lee & boursier, 2016) and competitive advantage (shan, luo, zhou & wei, 2018) by transforming decisionmaking and leading to new strategic models (davenport, 2014; walls & barnard, 2020). moreover, strategic theorists raise the need to understand how bd influences functional decisions within organizations, in order to respond to new market innovated products and the new shape of digital markets (mazzei, & noble, 2020). two drivers were identified in the course of evaluating the decision-making process effectiveness using bd: the consideration of data as a strategic asset, and the needed operational skills to implement a bd businessoriented model. hence, big data analytics (bda) is the main player in the decisionmaking processes (polese, troisi, grimaldi, & romeo, 2019). furthermore, bischof et al. (2016) argue that bd still represents, for a large number of companies, a tool that can enhance their reporting and monitoring capabilities. for a limited number of companies, bd represents an opportunity to create an innovative business model. in the latter case, bd is integrated within the company’s structure, processes, infrastructure, technologies and mainly the corporate strategy (bischof, gabriel, rabel, & wilfinger, 2016; mazzei & noble, 2017). however, although bd efforts were focused on infrastructure, tools and technologies, many researchers highlighted the need to tackle the strategic incorporation of bd technological journal of intelligence studies in business vol. 11, no. 1 (2021) pp. 33-47 open access: freely available at: https://ojs.hh.se/ 34 developments and the link between bd and strategic management (sm) (falsarella, jannuzzi, & sugahara, 2017; mikalef, pappas, giannakos, krogstie, lekakos, 2016). while bd technologies have been developing rapidly, academic research on the integration of bd with sm is still in its infancy (al-qirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019; mikalef, pappas, giannakos, krogstie, lekakos, 2016; lin & kunnathur, 2019; shams, & solima, 2019; wang, kung, & byrd, 2018). polese et al. (2019) argue that the strategic use of bd in the organization strategy can be implemented through the integration of related processes and technological architectures. moreover, bd affects organizational culture; it converts firms to become data and evidence-based organizations (braganza, brooks, nepelski, ali & moro, 2017). hence, considering the importance of sm to better understand the implications of bd in an organizational context, the lack of a sm framework that integrates bd to improve corporate strategy process, and the emerging role of bd as a tool for corporate innovation and transformation, the research question that guides this work is: how can bd be integrated within the sm process to guide organizations to improve their competitive advantage? thus, in light of this, the main goal of this study is to provide a framework that fills the research gaps in the previous models and integrates bd within the sm process. this work is inspired by previous related studies tackling the strategic use of business intelligence (bi) and bd, including alnoukari & hanano (2017), holmlund et al. (2020) and wheelen & hunger (2008). the remainder of this paper is organized as follows. the next section looks at the fundamentals of bd and sm. then a section discusses in details some of the latest academic research that highlights the use of bd with sm. thereafter, the next section provides an overview of the frameworks/models that support the use of bd as a sm tool. then, the paper proposes a framework named “bd-bsc” that integrates bd within the sm process based on a balanced scorecard methodology. the final section ends this paper with some concluding remarks and future work. 2. research method this study reviews literature on bd and sm processes, and analyses how bd tools and techniques can be integrated into the sm process. the research method adopted was a semi-systematic literature review, as this approach is suitable for emerging topics such as bd. the main purpose of the semisystematic literature review is to provide an overview of the research area, as the research questions can be broad, the research strategy may or may not be systematic, and the analysis and evaluation phase can be quantitative or qualitative (snyder, 2019). this study uses this approach to evaluate the literature on the use of bd with sm, to understand this topic in a comprehensive perspective, and to discover the research gaps on this topic. the three steps of our literature review are presented in figure 1. the first step was the definition of the research question as presented in section 1. based on the research question, the search and selection for articles was conducted based on the recent related studies’ findings. the second step was to conduct an in-depth reading and analysis of the papers to identify the contributions and the gaps for future research. the third and last step was to suggest a new framework that fills the research gaps in the previous models and to provide a detailed description for each stage. 3. theoretical background 3.1 big data with the data explosion coming from clicks, sensors, and technological innovations, new fields become more and more necessary, especially in bd, and internet of things (iot) (alnoukari, 2020-a; mazzei & noble, 2020; porter & heppelmann, 2014; shin, 2016). figure 1 steps for this study’s semi-systematic literature. 35 every person is currently considered a “data generator” and organizations become “information processors” (mazzei & noble, 2020). bischof et al. (2016) argue that bd is a key technological component that can provide the basis for smart product. the key benefit of bd is that a high volume of very diverse data can be processed at a high speed (bischof, gabriel, rabel, & wilfinger, 2016). however, bd is currently generating more data than organizations are able to manage, store and analyze (walls & barnard, 2020). moving from 3 vs into 5 vs, and finally 7 vs, our work updates the definition of fosso wamba et al. (2015) of bd to incorporate all of the 7 vs as follows: “bd is a holistic approach to manage, process and analyze the 7 v’s (i.e., volume, variety, velocity, veracity, value, valence, and variability) in order to create actionable insights for sustained value delivery, measuring performance, establishing competitive advantages, and becoming a source of innovation.” (alnoukari, 2020-b). mazzei & noble (2020) argue that bd, with its capabilities in collecting, handling, analyzing and presenting huge amount of data, will be an evitable source for achieving and sustaining competitive advantages. however, bd can be seen as an extension to business intelligence and business analytics (mazzei & noble, 2020). bischof et al. (2016) argue that bd is not a single technological set that can be bought off the shelf. it is a wide range of technological components that in combination can provide the 7vs’ characteristics. according to sadovskyi et al. (2014), most scholars agree that bd enables organizations to create entirely new innovative products, and new business models. they also agree on the fact that bd helps achieving competitive advantages. suoniemi et al. (2017) noted that bd technologies provide the ability to generate customer insight that was not previously possible. furthermore, by analyzing finegrained data and identifying the subtle trends and patterns in the individual customer behavior and attitudes, bd is able to provide firms with the ability to understand their customers individually, in real time, rather than segmenting them demographically. moreover, lin & kunnathur (2019) argue that bd facilitates sensing by identifying market requirements and opportunities, then develops seizing by transforming these requirements and opportunities into innovative products and services, and finally supports reconfiguring by leading the organizational transformation into bd-driven firms and reorganizing firm’s resources and competencies to maintain a competitive advantage over competitors. the main constraint facing companies when applying bd analysis is the high volume of data collected from internal and external sources that can exceed the capacity of the company storage and tools (polese, troisi, grimaldi, & romeo, 2019). bda is defined as an innovative approach to deliver sustained value (xie, wu, xiao & hu; 2016), and enable competitive advantage by managing and analyzing the 5 vs that are bd related dimensions (volume, variety, velocity, veracity, and value) (fosso wamba, gunasekaran, akter, ren, ji-fan, dubey, & childe, 2017). bda allows firms to manage and analyze strategy through a data lens (fosso wamba, gunasekaran, akter, ren, ji-fan, dubey, & childe, 2017). holmlund et al. (2020) argue that bda are the approaches, tools, and methods that can help organizations to develop insights from bd initiatives in order to improve firms’ decision-making. hence, bda provides the organizations the ability to gain considerable value and competitive advantage. according to walls & barnard (2020), insights provided by bda can improve the efficiency of the whole organization operations, as well as the strategy. from a marketing point of view, saidali et al. (2019) argue that classical data analytics are unable to acquire valuable business insights. they propose combining bda and classical marketing analytics in order to gain valuable and real time insights, thus improve the marketing decision-making process (saidali, rahich, tabaa, & medouri, 2019). 3.2 strategic management a strategy is a fundamental framework through which an organization can maintain its continuity in the market, and maintain its adaptability to environment changes to gain competitive advantages (fries, 2006; porter, 1996; teece, pisano & shuen, 1997). traditionally, strategy can be seen as a coherent and integrative view for decisionmaking, or a long-term objective with action plans and priorities for the corporate resource allocation (wells, 1998). it can also be seen as a response to external opportunities, threats, internal weaknesses and strengths. it can be also seen as a logical system that differentiates between managerial tasks at the different corporate levels: corporate, business and functional (global intelligence alliance, 2004). 36 strategic management (sm) is a framework for decisions and actions that result in the formulation and implementation of plans to achieve a company’s objectives and setting long-term directions (alnoukari, 2009; kruger, 2010; fries, 2006; omalaja & eruola,2011). porter (1996) summarizes the sm basic elements as a strategy process, a strategy content and a strategy context. these elements provide four essential steps for the sm process (krishnakumar, 2015; nedelea & paun, 2009; wheelen & hunger, 2008) (figure 2 & 3). environmental scanning includes both internal and external scanning. strategy formulation includes the corporate vision and mission, as well as the corporate objectives, strategies and policies. strategy implementation drives the strategy into action (krishnakumar, 2015; nedelea & paun, 2009; wheelen & hunger, 2008). finally, the strategy carry out an evaluation and control, which monitors actual performance against desired performance, and the needed corrective actions (wheelen & hunger, 2008; wells, 1998). balanced scorecard is an important managerial tool that helps organizations to articulate their strategy into actionable initiatives and projects (alnoukari & hanano, 2017). in addition, it provides the roadmap for strategy implementation, execution, and monitoring and control (olszak, 2014). figure 2 basic elements of the strategic management process (wheelen & hunger, 2008). figure 3 strategic management model (wheelen & hunger, 2008). 37 moreover, balanced scorecard helps top management indicating the right strategic decisions to be taken (alnoukari & hanano, 2017). according to fries (2006), balanced scorecard translates corporate vision and strategy into action, information, and intelligence. balanced scorecard considers that a corporation has four main perspectives (kaplan, 2010): financial, customer, internal business process, and learning and growth. financial measurements are the most important driving factors for top management to evaluate the company position in the market. customer measurements including customer focus and satisfaction are used to evaluate the company image. internal business process measurements allow managers to monitor and evaluate business processes and whether they cover all required and predefined customer needs. employee learning and growth measurements are mainly used to evaluate the company commitment to its longterm strategy in terms of its human resources. 4. the use of big data with strategic management there is a strong relationship between bd and sm (şen, körük, serper, & çalış uslu, 2019). however, bd efforts are focused on infrastructure, tools and technologies (mikalef, pappas, giannakos, krogstie, lekakos, 2016). according to braganza et al. (2017), bd is more than a technology, and to be fully effective it should be incorporated into corporate strategy. many researchers highlight the need to tackle the strategic incorporation of bd technological development, and the link between bd and sm theories (mikalef, pappas, giannakos, krogstie, lekakos, 2016). wang et al. (2018) address the lack of understanding the strategic implications of bd by examining the historical development, architectural design, and component functionalities of bd analytics. new research confirms that bd will provide the opportunity to bring new theories and practices to organizational science and sm approaches. furthermore, mazzei, & noble (2020) argue that strategy scholars need to comprehend and create new theoretical approaches in order to provide integration between corporate strategies and bd, and reshaping strategic decision-making. mikalef et al. (2016) argue that decision makers do not have not enough thoughts on how bd strategy could be adopted and implemented to drive their business strategies. polese et al. (2019) argue that the strategic use of bd in organizational strategy can be implemented by the integration of related processes and technological architectures. however, according to bischof et al. (2016), technology, alone, is not sufficient to achieve a strategic impact that leads to a significant strategic performance. organizational adoption is an important factor to drive the use of bd across the entire organization (bischof, gabriel, rabel, & wilfinger, 2016). walls & barnard (2020) argue that bd in the lens of sm is the capability needed in order to gain organizational performance. they further argue that bda capability is becoming a sm tool that leads an organization to incorporate innovation into business. hence, it can be considered a business model for both innovation and a driver for innovativeness, and should be aligned with business strategy (walls & barnard, 2020). lin & kunnathur (2019) argue that organizational strategic orientation represents firms’ strategic willingness and preparedness. strategic orientation is divided into market, entrepreneurial, and technology orientations (lin & kunnathur, 2019). strategic orientation is shaped by the firm’s organizational culture, as it is rooted in the firm’s beliefs and values. strategic orientations contribute to organizational performance (lin & kunnathur, 2019). strategic literature recognizes that business strategy should be aligned with the organizational culture, core values, systems and processes, and resources and capabilities (barchiesi & fronzetti colladon, 2019). 5. an overview of the frameworks/models that support the use of big data as a strategic management tool in the following sub-sections, the paper provides an up-to-date overview about the frameworks/models that support the use of bd as a sm tool. the frameworks/models are presented according to their publishing year. 5.1 strategic framework for customer experience insights holmlund et al. (2020) built a strategic framework for customer experience (cx) management based on cx insights generated from bda. their framework is based on four stages including backtracking: cx and cx data, cx analytics, cx insights and cx actions. 38 the cx and cx data stage is based on the touchpoints within and outside the organization’s control in the digital, physical and social realms. the cx data generated ranges from highly structured cx data that can be represented numerically to highly unstructured cx data that is typically contained in hard-to-count formats such as multimedia data. furthermore, cx data can be categorized into solicited and unsolicited forms, according to the touchpoint interactions evaluation. the cx analytics stage is based on bda used to analyze and interpret cx data. the cx analytics stage has four levels of analysis: descriptive, inquisitive (or diagnostic), predictive, and prescriptive. the cx insights stage is classified into attitudinal/psychographic, behavioral, and market insights. attitudinal/psychographic insights provide knowledge about satisfaction, advocacy, and valuable efforts by organizations. behavioral insights help organizations with the knowledge about the behavioral aspects and consequences of the cx. market insights are extremely valuable as they are related to the knowledge about organizational performance in terms of the cx in relation to the marketplace. the holmlund et al. (2020) framework is developed for data-driven organizations, thus their cx actions stage is related to organizations’ capabilities that could be accomplished using bda-enabled cx insights. the dynamic system of cx actions is related to touchpoint monitoring, prioritization, adaptation, and journey design. according to holmlund et al. (2020), touchpoint journey monitoring actions use cx insight to collect a set of touchpoint performance indicators. for example, finning, a caterpillar dealer, has transformed from a traditional repair service to a provider of support for customers’ machines through predictive and prescriptive bda. cx insights enable finning to track a machine’s location, prevent premature failure, prolong service life, minimize downtime, increase operator efficiency, reduce the cost of repair, and recommend solutions. touchpoint journey prioritization uses cx insights to allocate/reallocate human, technical and monetary resources to direct the development and maintenance of any touchpoint without redesigning the whole journey each time. touchpoint journey adaptation relies on cx insights to generate suggestions to develop touchpoints. for example, spotify, a streaming provider, created a personalized experience for each customer. spotify capitalized on descriptive and predictive bda to generate cx behavioral insights (i.e. knowledge on listening habits) and design highly personalized touchpoints. spotify sent each customer a personalized email with information about their listening habits. these actions allowed spotify to create personalized touchpoints in each customer’s journey by generating custom playlists. touchpoint journey design uses cx insights to design potential journey offerings and distribute clear requirements across different organizational functions. for example, john deere, an agricultural equipment manufacturer, capitalized on bda and equipped its machines with sensors that allowed its customers to access and analyze their machine data, benchmarking it against other machines and combining it with historical data in real time and for free. thus, john deere introduced new touchpoint design that changed its customers’ entire journey. currently, the myjohndeere.com platform is opened to suppliers, retailers, and software developers. john deere transitioned from a manufacturing business model to a platformcentric model, and thus achieved innovation and revolutionized the agriculture industry. 5.2 a framework for business process data management based on a big data approach hassani & gahnouchi (2017) proposed a framework for business process data management based on a bd approach. it intends to combine the two perspectives of business processes and bd. the main goal of this framework is to ensure business process improvement using bd. in order to achieve the combination of business processes and bd, this framework provides the following fundamental steps. first, it starts with process (re)design based on bda by modeling processes to clearly describe the business scenario, then it carries out process configuration with bd generation tools in order to customize the process with external information systems. once the process has been designed and configured, it is deployed during the process execution. process analytics is required after the process execution to analyze process functionality. 39 5.3 conceptual research framework the conceptual research framework is based on the resource-based view and dynamic capability view sm theories, and management information system literature (mikalef, pappas, giannakos, krogstie, lekakos, 2016). the proposed framework provides managers and decision-makers with the basis on how to increase business value and competitive performance using bd and business analytics. according to mikalef et al. (2016), the it resources including infrastructure, human skills and knowledge, relational resources and data must be put into directed initiatives in order to get a competitive edge. hence, the firm must have the it competencies to transform individual it resources into it-enabled dynamic capabilities that include sensing, learning, coordinating, integrating and reconfiguring. it competencies are the sources used to transform bd it resources into competitive assets. thus, the conceptual research framework can help determining the business value of bd. 5.4 the marketing mix framework for big data management fan et al. (2015) proposed the marketing mix framework that relies on marketing intelligence. this framework identifies the data sources, methods and applications related to marketing’s most important perspectives: people, product, place, price, and promotion. the proposed framework provides guidelines for organizations aiming to apply marketing intelligence to meet their strategic marketing goals. this framework is based on the five marketing mix perspectives. the data is collected from various sources, then converted into actionable marketing knowledge using a variety of analytics methods, and finally utilized to support marketing intelligence applications. the data in this framework is collected using various methods including demographics, social networks, customer review, clickstream, product characteristics, product category, promotional data, transactional data, locationbased services, and surveys. the methods utilized in the proposed framework are based on data mining including association, classification, clustering and regression. different applications are applied according to each of the five marketing mix perspectives, including customer segmentation and profiling, product ontology and reputation, promotional marketing analysis and recommendation system, pricing strategy analysis and competitor analysis, and locationbased advertising and community dynamic analysis. product reputation management is a marketing intelligence tool that uses textbased reputation data from the web, in addition to the graphical images of products posted on the web. this tool is using an automated product ontology mining method that can build product ontologies based on textual descriptions of products extracted from social media. then, these product ontologies can be used to support product reputation applications. location-based advertising is an important marketing intelligence tool. it enables customers to get timely advertisements or product recommendations based on their current locations, and their future moves to other locations. community dynamic analysis provides firms with the ability to predict their changing product preferences. as a result, firms can develop an effective marketing strategy based on the time and location dynamics of a group of their customers (fan, lau, & zhao, 2015). 5.5 9s framework according to lake & drake (2014), the 9s framework (bd wheel) helps firms and managers to understand the impact of bd on business. furthermore, the 9s framework helps view the interplay between data and analytics from different technical and managerial strategic directions (al-qirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019). statistical thinking is at the center of the 9s wheel since it is the common perspective across all other aspects of bd. the remaining 8 ss are strategy, structure, style, staff, synthesis, systems, sources, and security. strategy and structure are tightly coupled to highlight the mutual impact of organizational structure on the organization’s strategy (alqirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019). 5.6 analytical discussion the holmlund et al. (2020) strategic framework is based on cx insights generated from bda. this framework includes four stages based on cx data: bd acquisition, bda, bd insights and bd actions. although the holmlund et al. (2020) strategic framework was built for cx management, it can be applied to other types of applications as well. hence, it can use any type of data including financial, talent and business process data. however, 40 hassani & gahnouchi’s (2017) framework’s intent is to analyze and improve business process functionality using bd. the mikalef et al. (2020) framework’s focus is to increase business value and competitive performance using bd and bda. it highlights the mutual effects of it competencies on organizational capabilities and business strategy. the mikalef et al. (2016) framework helps determining the business value of bd. fan et al. (2015) proposed a framework based on marketing mix and marketing intelligence. it can be considered a guideline for organizations aiming to apply marketing intelligence to meet their marketing strategic goals. this framework can be extended to use other types of data, and evaluate all their strategic goals including financial, talent and business processes. in the same vein, the 9s framework helps understanding the impact of bd on business. moreover, it highlights the mutual impact of organizational structure on the organization’s strategy (al-qirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019). although all these frameworks support the use of bd as a sm tool, the main research gap in this domain is that they are unable to integrate bd within the sm process. this issue provides reason to suggest the bd-bsc framework that is described in the following section. 6. bd-bsc: a framework for integrating big data within the strategic management process bd-bsc effectively integrates bd within the strategy development process. the main strategic themes are incorporated and improved in order to strengthen the organization’s long-term success (alnoukari & hanano, 2017). this could be achieved when the strategic themes deliver greater values to customers at lower cost. when these themes are properly implemented, organizations could increase their profitability results. therefore, strategic themes could be used to observe markets and competitors, and enable top management to continuously adjust their strategies when the environment changes (alnoukari & hanano, 2017). the following sub-sections provide detailed description about our proposed bd-bsc framework (figure 4). this framework is based on the sm model (wheelen & hunger, 2008) and bsc-bi framework (alnoukari & hanano, 2017). the bsc-bi framework was built to integrate business intelligence within the sm process (alnoukari & hanano, 2017). the bdbsc framework follows the four main phases of the sm process: environmental scanning, strategy formulation, strategy implementation, and evaluation and control. the bd-bsc framework integrates the bd process’s main stages including data acquisition, bd analytics and bd insights within the first phase to support environmental scanning and provide the four main inputs for balanced scorecard methodology, customer insights, financial insights, talent insights and business process insights. the bd-bsc framework includes a feedback/learning process. arrows coming out of each stage of the framework take information to each of the previous stages. framework users often must go back to revise or correct decisions made earlier (wheelen & hunger, 2008). for example, poor performance (as measured in evaluation and control) usually indicates that something has gone wrong with either strategy formulation or implementation. it could also mean that a key variable, such as a new competitor, was ignored during environmental scanning and assessment (wheelen & hunger, 2008). figure 4 bd-bsc framework. 41 6.1 environmental scanning phase the environmental scanning phase includes both internal and external scanning (global intelligence alliance, 2004). external scanning focuses on competitors, customers, and suppliers in addition to technology and political forces, whereas internal scanning focuses on the corporate structure, culture and resources (global intelligence alliance, 2004). the main purpose of the environmental scanning phase is to identify the strategic factors (wheelen & hunger, 2008). the traditional way to conduct environmental scanning is through a swot analysis (wheelen & hunger, 2008). however, the bd-bsc framework uses bda and bd insights to conduct environmental scanning based on the structured and unstructured data from the data acquisition stage. in the following sub-sections, a detailed description is provided for the three bd-bsc environmental scanning stages: data acquisition, bd analytics, and bd insights. 6.1.1 data acquisition stage according to jin & kim (2018), bi’s “raw data” has been expanded into “big data” due to advanced technology capability. bi focuses primarily on structured and internal enterprise data, overlooking valuable information embedded in unstructured and external data (marín-ortega, dmitriyevb, abilovb, & gómezb, 2014). this could result in an incomplete view of the reality, and biased enterprise decision-making (llave, 2018; ram, zhang, & koronios, 2016; marín-ortega, dmitriyevb, abilovb, & gómezb, 2014). hence, the bd 3vs definition tackles these concerns. the three vs are volume, variety, and velocity. the main source of this exponentially increased data is coming from the unstructured data of social networks, blogs, text messages, videos and audio (braganza, brooks, nepelski, ali, & moro, 2017). variety refers to the different types of data that can be manipulated using bd technologies (faroukhi, el alaoui, gahi, & amine, 2020). structured, semistructured, and unstructured data types are currently included under bd processes (faroukhi, el alaoui, gahi, & amine, 2020). unstructured data is the challenging key that allows bd to overcome the main deficiencies of the traditional methods. holmlund et al. (2020) employs solicited and unsolicited data for interaction evaluation. answering a survey, writing an invited review, or participating in a feedback workshop are some kinds of solicited data. however, customer feedback through emails, social media commands, or face-to-face interactions are examples of unsolicited data. 6.1.2 big data analytics stage bda can enhance the comprehension of business opportunities, and give better insight into customer behavior and services/products effectiveness (fan, lau, & zhao, 2015; polese, troisi, grimaldi, & romeo, 2019). fan et al. (2015) argue that analytical models based on single data sources may provide limited insights that consequently lead to biased business decisions. using multiple and heterogeneous data sources can provide a holistic view of the business and leads to better decision-making. furthermore, they argue that bda supports marketing intelligence by providing the ability to monitor customer opinions toward a product, service, or company using social media mining techniques. customer opinion mining is a key factor for strategic marketing decisions that can be based on multiple data sources including social media, transactions, surveys, and sensors, which can be applied to discover marketing intelligence. ram et al. (2016) listed five main advantages when applying bda: increasing data visibility, improving organizational performance, improving meeting customers’ needs, revealing valuable insights, and revealing new business models, products and services. bda helps executive managers to plan an organization’s short-term and long-term goals (palem, 2014). bda has been successfully used in many areas. different analytics have achieved a great success including in usagebased insurance, predictive maintenance, epidemic outbreak detection, and sentiment analysis (palem, 2014). bda adds additional characteristics to the conventional data analysis. these include innovated technologies and skills that enable organizations to use deep analytical capabilities, and integrate a wide range of data types from a large number of relatively unreliable data source in order to provide a meaningful and reliable source of business information (sadovskyi, engel, heininger, böhm, & krcmar, 2014). the bda stage in our bd-bsc framework has four levels of analysis: descriptive, inquisitive (or diagnostic), predictive, and prescriptive. descriptive bda is related to “what happened?” answers. these kinds of analytics help to further describe the situation 42 analysis. typical examples include descriptive statistics using charts, cross tabulation, or clustering graphs. inquisitive dba is related to “why did things happen?” answers. these kinds of analytics help validating research hypotheses, determining causation, and identifying variables to achieve desired results. typical examples include statistical inference techniques or factor analysis. predictive bda is related to “what could happen?” answers (waller & fawcett, 2013). these kinds of analytics help predicting future trends. typical examples include forecasting models, classification models, or neural networks. prescriptive bda is related to “what should happen?” answers. these kinds of analytics help providing quantifiable answers when solving a problem. typical examples include optimizations modeling, queuing modeling, or simulations (holmlund, van vaerenbergh, ciuchita, ravald, sarantopoulos, villarroelordenes, & zaki, 2020). after generating bda, the bd-bsc framework is able to generate different insights including market, behavioral and attitudinal insights. 6.1.3 big data insights stage bd insights refer to the value and benefits gained from bd (chen, mao, & liu, 2014). according to holmlund et al. (2020), bd insights can be developped using bda in order to improve a firm’s decision-making. similarly, walls & barnard (2020) stated that insights provided by bda could improve the efficiency of the organization’s full operations, as well as the strategy. due to its high importance, value is one of the new vs, most recently added to the bd definition (erevelles et al., 2016). wang et al. (2018) stated that the word “big” in bd does not only imply size, but rather the ability to produce insights, and manage complex types. hence, bd insights close the knowledge and time gaps of the traditional methods. walls & barnard (2020) highlight the need to structure and manage bd initiatives in order to have insights from data, and the ability to act quickly to achieve a positive impact on organizational performance. dubey et al. (2018) consider bda capability to be one of the organizational capabilities that provides organizations with the ability to produce insights that enable the data-driven decision-making process by analyzing its huge data with non-traditional methods using bd tools and techniques. moreover, akter et al. (2016) argue that bda capability provides organizations with the ability to deliver insights using data management, technology, and talent capability to transform business for a competitive advantage and gain business value. polese et al. (2017) noted that bda provides the ability to show behavioral insights about customers. these can be turned into strategic advantages (şen, körük, serper, & çalış uslu, 2019). moreover, saidali et al. (2019) suggest combining bda and classical marketing analytics in order to gain insights that are more valuable, and improve the marketing decision-making process. furthermore, suoniemi et al. (2017) argue that bd resources improve a firm’s ability to better innovate and optimize any marketing elements in the mix with bd predictive capability. hence, firms have the ability to get more insights into customer behavior, and also have the ability to tailor person-, contextand location-specific offers, and more in real time. holmlund et al. (2020) suggest a strategic framework for customer experience management based on customer experience insights generated from bda. holmlund et al. (2020) noted that the majority of organizations still face difficulties in generating relevant customer insights. they further argue that data and information cannot, themselves, provide customer insights. holmlund et al. (2020) found that customer insights could be generated by data transformation through analysis and interpretation: values are gained through the ability to drive actions. holmlund et al. (2020) classified customer experience insights as attitudinal/ psychographic, behavioral, and market insights. attitudinal/ psychographic insights provide knowledge about satisfaction, advocacy, and valuable efforts by organizations. behavioral insights help organizations with the knowledge about the behavioral aspect and consequences of the customer experience. market insights are extremely valuable as they are related to the knowledge about organizational performance in terms of the customer experience in relation to the marketplace. in contrast, other scholars argued that it is difficult for organizations to understand how to leverage bd insights in order to create value (erevelles, fukawa, swayne 2016; walls & barnard, 2020). even though an organization may extract bd insights successfully, there is no guarantee that they are able to utilize these 43 insights effectively (erevelles, fukawa, swayne 2016; walls & barnard, 2020). the bd insights stage in our bd-bcs framework is considered the core engine to deliver the insights needed for balanced scorecard implementation. customer insights (holmlund, van vaerenbergh, ciuchita, ravald, sarantopoulos, villarroel-ordenes, & zaki, 2020), financial insights (costa, dantas, santos, medeiros, & rebouças, 2018), talent insights (nocker & sena, 2019), and business process insights (al-qirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019; braganza, brooks, nepelski, ali, and moro, 2017; hassani & gahnouchi, 2017) are delivered in this stage. they are all considered inputs into the strategy formulation using a balanced scorecard in the next phase. 6.2 strategy formulation phase the strategy formulation phase includes defining the corporate mission, specifying achievable objectives, developing strategies and setting policy guidelines (global intelligence alliance, 2004; kaplan, 2010; wheelen & hunger, 2008). firms with mission statements containing the customers served explicitly and technologies have significantly higher growth than those firms without such statements (wheelen & hunger, 2008). bd insights provided in the previous phase support corporations defining better mission statements. fulfillment of the corporate mission could be achieved by developing corporate objectives (kaplan, 2010; wheelen & hunger, 2008). good corporate objectives should state what is to be accomplished and by when (kaplan, 2010; wheelen & hunger, 2008). quantified corporate objectives are better and could be measured in later phases. bda and bd insights help organizations specify quantified corporate objectives. corporation mission and objectives can be achieved by creating a comprehensive master plan or strategy (kaplan, 2010; wheelen & hunger, 2008). three types of strategies should be developed to provide an overall strategic direction: corporate, business and functional strategies. a corporate strategy provides an overall direction for the company and management of its businesses (wheelen & hunger, 2008). typically, the corporate strategy fits within the following three main categories: stability, growth and retrenchment (wheelen & hunger, 2008). the business strategy usually occurs at the business unit or production level. the business strategy emphasizes the company’s improvement in the competitive position of its products or services (wheelen & hunger, 2008). business strategies may fit within two main categories, the competitive and cooperative strategies (wheelen & hunger, 2008). business strategies provide companies with the ability to enhance their competitive advantages. functional strategy is usually taken by a functional area to achieve business and corporate objectives by maximizing resource productivity (wheelen & hunger, 2008). corporate, business and functional strategies form a hierarchy of strategy that complement and support one another. functional strategies support business strategies, which in turn, support the corporate strategy or strategies. bda and bd insights help organizations developing realistic corporate, business and functional strategies based on data mining and knowledge discovery algorithms. policy is a decision-making guideline that links the strategy formulation and its implementation (wheelen & hunger, 2008). the bd-bsc framework’s strategy formulation phase is based on a balanced scorecard methodology. using customer insights, financial insights, talent insights, and business process insights delivered from the previous phase, the bd-bsc framework supports organizations to formulate corporate missions, specify corporate objectives, develop strategies at all levels, and set policy guidelines for the implementation phase. 6.3 strategy implementation phase the strategy implementation phase is the process by which the strategies and policies are translated into actions, by developing programs, budgets and procedures (global intelligence alliance, 2004; kaplan, 2010; wheelen & hunger, 2008). strategy implementation may require overall changes in corporate culture, structure and management system (wheelen & hunger, 2008). the implementation phase is usually conducted by middleand lower-level managers under the top management’s review and guidance. hence, the implementation phase may involve day-to-day decisions in resources allocation (wheelen & hunger, 2008). the programs provide all the needed activities and steps to accomplish the operational plans (wheelen & hunger, 2008). budgets list the detailed cost of each program, and thus provide the basis to measure profit 44 performance (wheelen & hunger, 2008). finally, procedures provide all the necessary details to conduct a particular task or job (wheelen & hunger, 2008). the bd-bsc framework’s strategy implementation phase translates corporate strategies and policies developed in the previous phase into programs, budgets and procedures, based on the balanced scorecard’s four perspectives. strategic plans are executed to provide the necessary implementation’s activities. 6.4 evaluation and control phase the evaluation and control process measures performance results and compares them with the desired performance (global intelligence alliance, 2004; kaplan, 2010; wheelen & hunger, 2008). managers at all levels use the resulting performance measures to take corrective actions and resolve problems (wheelen & hunger, 2008). based on performance results, management may need to adjust its strategy formulation and/or implementation (wheelen & hunger, 2008). the bd-bsc framework’s evaluation and control phase is based on key performance indicators (kpis) to make comparisons between desired and achieved performance measures. kpis are used for the analysis of reaching goals and objectives (alnoukari & hanano, 2017). bda contribute to sm as they measure the organization’s performance. balanced scorecard is used to indicate whether bda match critical performance indicators. 7. conclusions and directions for future research our goal with this paper was to signal the importance of bd integration within the sm process. hence, we provided a comprehensive and integrative framework in which bd, bda and bd insights are used through balanced scorecard lenses to support strategy formulation and implementation. throughout this paper, we emphasized that bda and bd insights could provide the needed base for strategy development. traditional methodologies were based on swot analysis and other strategic tools to provide clear environmental scanning. bda and bd insights enhance the environmental scanning process, and provide accurate insights that help formulate better corporate strategies. in terms of implications, we integrated the literature on bd, sm and balanced scorecard and highlighted how an organization could apply these different technologies and methodologies to improve the development of corporate strategy. research at the intersection of bd and sm is in its early development phase (e.g., al-qirim, rouibah, serhani, tarhini, khalil, maqableh, & gergely, 2019) and we hope that our integrative framework can help both practitioners and researchers reflect on the growing complexities of using bd within sm. to conclude, we have outlined some avenues for future research in this area. we propose some opportunities for future studies in this promising research area. future studies could focus on the implementation of a bd-bcs framework in different areas including telecommunication, banking and education. other studies could tackle the use of other sm tools with bd. 8. references al-qirim, n., rouibah, k., serhani, m. a., tarhini, a., khalil, a., maqableh, m., & gergely, m. 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(2020) financial intelligence: financial statement fraud in indonesia. journal of intelligence studies in business. 10 (3) 80-95. article url: https://ojs.hh.se/index.php/jisib/article/view/590 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index financial intelligence: financial statement fraud in indonesia muhammad ikbala, irwansyah irwansyaha, ardi pamintob, yana ulfaha,* and dio caisar darmac adepartment of accounting, faculty of economics and business, mulawarman university, samarinda, indonesia; bdepartment of management, faculty of economics and business, mulawarman university, samarinda, indonesia; cdepartment of management, sekolah tinggi ilmu ekonomi samarinda, samarinda, indonesia; *yana.ulfah@feb.unmul.ac.id journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 3,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10,no.32020 opinion: a project management approach to competitive intelligence miguel-ángel garcía-madurga and miguel-ángel esteban-navarro pp. 8-23 an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukari pp. 24-37 the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry stefan zwerenz pp. 38-62 the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyen and nguyen phong nguyen pp. 63-79 financial intelligence: financial statement fraud in indonesia muhammad ikbal, irwansyah irwansyah, ardi paminto, yana ulfah and dio caisar darma pp. 80-95 financial intelligence: financial statement fraud in indonesia muhammad ikbala, irwansyah irwansyaha, ardi pamintob, yana ulfaha,* and dio caisar darmac adepartment of accounting, faculty of economics and business, mulawarman university, samarinda, indonesia; bdepartment of management, faculty of economics and business, mulawarman university, samarinda, indonesia; cdepartment of management, sekolah tinggi ilmu ekonomi samarinda, samarinda, indonesia *corresponding author: yana.ulfah@feb.unmul.ac.id received 18 may 2020 accepted 26 october 2020 abstract indonesia is currently in an honesty crisis, especially in financial governance, both in government and private institutions. our study uses the concept of financial intelligence to identify and collect information related to financial affairs in an organization. we use the opinions of 76 auditors regarding various fraudulent attempts, both with fraudulent financial statements and other corrupt practices in organizations in indonesia. our important finding is that small companies are more likely to commit fraud due to weak supervisors than listed public companies. this is also more likely than family-owned companies and government level organizations. it was indicated by some respondents that local government level organizations with weak supervision are more likely to commit fraud than local governments with close supervision from urban communities. the results of the non-parametric relationship analysis show that although there is a possibility that the more experienced the auditor is, the more able they are to detect fraud and manipulation in the organization, the relationship is relatively weak. other findings also show that auditors who have a cfe certificate find it easier to find fraud in the company. keywords bribes, financial intelligence, fraudulent financial statements, procurement of goods and services 1. introduction audit-based research has an important role in the effort to identify fraudulent attempts at both the scale of private company organizations and public organizations. the term that is widely used is financial intelligence, which is an attempt to identify various fraud in financial transactions including embezzlement, money laundering, or other fraudulent and illegal transactions (alavi 2016; scott and mcgoldrick 2018). many cases in indonesia lead to fraud involving parties related to the company. when viewed from a collection of numbers, fraud in company transactions is huge. the combined results of the acfe analysis amount to 800,000 usd. according to the fraud triangle theory, the opportunities for an individual to commit fraud are based on opportunities, abilities, pressures, needs, and lifestyle. the impact is enormous, at a time when this fraudulent opportunity can take place (suh et al. 2019; charlopova et al. journal of intelligence studies in business vol. 10, no. 3 (2020) pp. 80-95 open access: freely available at: https://ojs.hh.se/ 81 2020). investors and others have an impact on labor and company performance in the market (karpoff 2020). fraud can occur in any sector, including the private sector, public services, and both national and international organizations (lombardi et al. 2015; charlopova et al. 2020). indonesia has recorded massive cases of fraud since the government's efforts to eradicate corruption in the reform era (lewis and hendrawan 2019). fraud and criminal acts of corruption involve many parties, conglomerates, public officials, company employees, government employees, religious leaders, political figures and even the public in various aspects of life (jakimow 2018a). one of the cases involved the state company (bumd) pt garuda indonesia tbk. this airline was suspected of having released fraudulent financial statements. regulators—in this case, the ministry of finance and the financial services authority (ojk)—impose penalties on the parties involved, including the accounting firm, auditor, and pt garuda indonesia tbk. the results of the state auditor's examination showed fraud in the 2018 earnings report. the company inflated profits for certain purposes. from the audit findings, the company should have suffered a loss of 244.95 million usd, but they actually recorded a profit of 809,840 usd. we follow-up previous research, which only examines the fraud side of private companies (holtfreter 2005; lambsdorff 2002; jeppesen 2019), and we expand by adding data from facts that occur in governmental organizations. this study also broadens the perspective through the financial intelligence model in viewing financial fraud in indonesia. the role of financial intelligence is very important as a solution to various corporate frauds (dorrell et al. 2012; alavi 2016). this research is important for several reasons. as financial intelligence, this study will understand how fraud is committed within a company that can assist auditors in finding fraud from various sides in corporate governance. second, understanding the various forms and patterns of fraud will greatly assist company leaders in detecting losses due to fraud, to prevent the allocation of resources to fraudulent units. we hope this can contribute to the development of knowledge in the field of audit and fraud, and also be beneficial for auditing practices and good corporate governance practices. research in the field of fraud is currently of interest in indonesia. with the rise of corruption cases being revealed, more and more researchers are using the concepts and theories of fraud in observing the phenomenon of fraud and the issue of ethical and criminal violations. the interesting thing about this research is that most of the data were collected through in-depth interviews with selected informants and sources, although the survey results were used to present descriptive data. we chose auditors as informants. most of the research results look at the impact of fraud on the economy and moral violations (van ruth et al. 2017; kendall et al. 2019; roychowdhury et al. 2019; dungan et al. 2019). some researchers observe fraud motivation from the perspective of the fraud triangle theory (suh et al. 2019; malimage 2019; bujaki et al. 2019), which is not context-specific or based on empirical evidence as in this study. this paper’s structure is as follows. first, we review the relevant literature on financial intelligence and its relation to financial reporting fraud. in the next section, we discuss the methodology we use, which follows a data collection method that uses a combination of surveys and in-depth interviews. in the next step, we present the findings in detail for each item on the form and add context on fraud in financial reporting. finally, the conclusions are combined with a discussion of the research results and their implications for research and audit practice in future research. 2. theoretical framework 2.1 financial intelligence the concept of financial intelligence (finite) is an effort to identify and collect information related to financial affairs in an organization (alavi 2016; scott and mcgoldrick 2018). in addition to being used by the police department in australia and several european and american authorities, finite also applies to legal and audit researchers. the use of finite in the audit field can be applied in special studies to prove various fraudulent attempts by accountants or financial managers in corporate organizations (dorrell et al. 2012; alavi 2016). the existence of finite is intended to identify various irregularities in financial transactions including money laundering, tax evasion, deliberate misstatement, and violations of other accounting rules (dorrell et al. 2012; alavi 2016; scott and mcgoldrick 2018). the use of finite to identify suspects or victims in cases of fraud in corporate financial statements is an important challenge for 82 auditors in detecting corruption and fraud (rudner 2006; alavi 2016). generally, as in previous cases, the auditor or the police investigate after the case was reported, however by using finite, the investigation and observation could be carried out before the report. there are major obstacles to not reporting a case of fraud that is found, for many reasons. in many cases, this includes recognition from individuals that they are victims of fraud, and the stigma and shame associated with this (rudner 2006; thony 1996). 2.2 fraudulent financial statements the output of the transaction identification and recording process is financial statements. this involves many parties, especially experts in accounting, who assess the reasonableness of using external audit services so that the presentation of financial statements is reasonable (chychyla et al. 2019; el-helaly et al. 2018). many cases of fraud in financial reports are in the form of deliberate misstatement, inflating numbers, and manipulation of income, which have multiple purposes (zager et al. 2016). this fraud is mostly carried out by management who truly understand the condition of the company (habib et al. 2018; chychyla et al. 2020). there are various ways to fraudulently manipulate financial statements, including unreasonable revenue recognition, hidden costs for certain purposes, and asset valuation that is not in accordance with ifrs (west and bhattacharya 2016; chychyla et al. 2020). misappropriation of organizational assets and misstatement in revenue recognition is the most common means of fraudulent behavior. this includes revenue that is recognized but fictitious, premature income that is currently recognized, and incorrect income when adjusted (zager et al. 2016; habib et al. 2018; west and bhattacharya, 2016). however, creating fictitious sales appears to be the most common method of manipulating income (el-helaly et al. 2018; zager et al. 2016). various ways of manipulating income, reviewed in the literature, are presented in table 1. table 1 summary of the various modes of recognition of illegal income. technique source there is a sales discount, but it is not recorded rezaee (2005), coenen (2009), albrecht et al. (2006) consignment sales are recorded as a normal rezaee (2005), coenen (2009), albrecht et al. (2006) shift sales from a future period to the current period coenen (2009), hopwood (2008) early acknowledgment of legitimate sales coenen (2009) create a sales order invoice but the goods are shipped in the next period (bill and hold) lord and robb (2010), coenen (2009) hide the sales returns and deductions to increase sales and net income elder et al. (2010) minimizing the allowance for doubtful accounts, so that the debt burden is reduced rezaee (2005), albrecht et al. (2006), coenen (2009), elder et al. (2010) bad debts that are not written off rezaee (2005), albrecht et al. (2006), coenen (2009), elder et al. (2010) recognizes credit sales at the end of the accounting period, even though they have not been ordered, but the goods have been shipped. hopwood (2008) part or all of the goods have not been delivered, but are recorded as sales. coenen (2009) does not record the goods return transactions lord and robb (2010) the customer returned the item but it was not recorded rezaee (2005), albrecht et al. (2006), coenen (2009), elder et al. (2010) manipulate cash receipts from the consumer as if the transfer from the bank is a cash receiver rezaee (2005), albrecht et al. (2006), coenen (2009), elder et al. (2010) entering into additional agreements that change the terms of the previous agreement that do not qualify as sales under accounting principles lord and robb (2010), elder et al. (2010) transferring income between accounting periods, by determining an inappropriate cut-off period lord and robb (2010) returned goods are recognized after the period ends hopwood (2008), rezaee (2005), albrecht et al. (2006), coenen (2009) transferring the write-off of uncollectible accounts to the next period hopwood (2008), rezaee (2005), albrecht et al. (2006), coenen (2009) fictitious sales transactions discontinued at the end of the accounting period rezaee (2005), albrecht et al. (2006), coenen (2009) sales and delivery documents are required hopwood (2008) decrease the note on a percentage of misstatements on settlement coenen (2009), hopwood (2008) record gross income, not net income rezaee (2005), albrecht et al. (2006), coenen (2009), elder et al. (2010) record invalid earnings or shipments lord and robb (2010), elder et al. (2010), hopwood (2008) exaggerating real sales rezaee (2005), albrecht et al. (2006), coenen (2009), elder et al. (2010) 83 table 2 improper ways of valuing assets. concealment techniques and methods source and quoted from inventory manipulation of goods in the warehouse wells (2005), coenen (2008), albrecht et al. (2006) inflation of the unit cost used to increase the value of the inventory wells (2005), coenen (2008), albrecht et al. (2006) obsolete inventory or other assets are not recorded according to impairment value or collection issues wells (2005), coenen (2008), albrecht et al. (2006) the amount of inventory for the cost of goods sold is enlarged. usually creating fake documents such as sheet counts wells (2005), coenen (2008), albrecht et al. (2006) it is not appropriate to capitalize on the inventory and the cost of the beginning inventory wells (2005), coenen (2008), albrecht et al. (2006) should increase the discount on sales or the cost of inventory should not be reduced wells (2005), coenen (2008), albrecht et al. (2006) creating false records for the amount of inventory on hand to conceal it by fake shipments wells (2005), coenen (2008), albrecht et al. (2006) obsolete and slow-moving inventories are recorded as misstatements jones (2011) the method for valuing inventory is changed according to the importance jones (2011) the production overhead amount included in the inventory count is misstated jones (2011) inaccurate inventory recognition during the delivery process lord and robb (2010) obsolete or unsold inventory is recognized lord and robb (2010) inventory items are overbooked, without eliminating obsolete items or there is no provision for inventories whose value is reduced lord and robb (2010), coenen (2009) the existence of illegal accounting of receivables albrecht et al. (2006), wells (2005), coenen (2008) accounts receivable from bad debts are not written off albrecht et al. (2006), wells (2005), coenen (2008) accounts receivable added unilaterally albrecht et al. (2006), wells (2005), coenen (2008) there are several fictitious assets ordered to influence the total asset account on the balance sheet albrecht et al. (2006), wells (2005), coenen (2008) the depreciation cost of an asset is increased by increasing or decreasing its useful life jones (2011), albrecht et al. (2006) depreciation is not recorded properly albrecht et al. (2006), wells (2005), coenen (2008) the market price of fixed assets is recorded at a higher rate, supported by an asset valuation document albrecht et al. (2006), wells (2005), coenen (2008) the cost of acquiring assets is increased by cooperating with other parties albrecht et al. (2006), wells (2005), coenen (2008) intentionally misrepresenting securities information with the help of other parties albrecht et al. (2006), wells (2005), coenen (2008) manipulating the return of goods or purchases of goods in the previous period are recorded repeatedly albrecht et al. (2006), wells (2005), coenen (2008) increase the value of fixed assets albrecht et al. (2006), wells (2005), coenen (2008) there is an impairment of assets that are not recorded correctly albrecht et al. (2006), wells (2005), coenen (2008) manipulation of estimated fair market value of assets albrecht et al. (2006), wells (2005), coenen (2008) backup manipulated albrecht et al. (2006), wells (2005), coenen (2008) inaccurate investment appraisal by way of wrong investment classification coenen (2009) amounts attributable to the merger or acquisition are not recorded correctly jones (2011), coenen (2009) 84 table 3 various modes of manipulating against liability and expense. concealment techniques and methods source and quoted from improperly recorded current and long-term debt sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) there is no documentation of the agreement and repurchase commitment sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) contingent payables are carried at excessively lower than fair value sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) enlarge financial ratios by inconsistently presenting long-term debt with current debt sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) purchases of goods that are recorded fairly or materials are not recorded sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) purchase returns and purchase discounts returned to the seller sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) the cost of booking goods is not recorded sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) manipulating gross profit by attempting to change the cost of a sales item to another account such as other operating expenses sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) the value of strategic assets such as buildings, accounts receivable, work equipment or inventory are not recorded at their correct value sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) there are discounts, returns, and sales discounts, but these are not recorded as reduced costs sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) hiding expenses by manipulating the number of smaller expenses sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) shifting the amount owed in this period to the next period, or preventing employee debt in the next period wells (2005), elder et al. (2010), coenen (2008, 2009), sterling (2002) the amount of certain liabilities was not recorded correctly, including service payables or contingent payables sterling (2002), coenen (2009) bring up obligations that should not exist sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) transferring accruals in this period which should be recorded in the next period or another period sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) there is a net income that is recorded even though the income is received in advance sterling (2002), coenen (2008, 2009), wells (2005), aicpa (2007) in addition to income, assets are objects that can be manipulated in financial statements. efforts to manipulate asset values with the aim of increasing the value of assets on the balance sheet can be done so that certain ratios will be large (wells 2005). important ratios such as profit ratios, debt ratios, capital capacity ratios, and adequacy of funds are very dependent on the number of assets owned by the company. these actors usually use simple methods in presenting asset values, one of which is manipulating the physical inventory value of assets (coenen 2008), increasing the cost per unit of assets so that the cost can be determined by themselves (albrecht et al. 2006) and trying to restate the inventory of assets that are worthless, obsolete and almost unused (jones 2011). here are some opinions from experts on various ways of manipulating organizational assets (table 2). apart from income, another easy aspect of finances to manipulate is a liability. liability accounts have more openings for manipulation than faking sales transactions. many criminals conceal liability transactions. here are some opinions of experts in various ways to hide organizational obligations and expenses in table 3. fraud in the government budget includes not only fraudulent financial statements but many aspects that can be manipulated. this includes the procurement and purchase of goods and services, manipulation of financial reports, manipulation of official travel costs, manipulation of granting company licenses, fraud in the use of natural resources, and fraud by law enforcers. the following are a summary of some opinions of experts on various ways to manipulate state money and abuse of office (table 4). efforts to uncover illegal transactions usually include the following: hiding obligations, shifting transactions to the next period, transactions with related parties, and changes in accounting policies (charlopova et al. 2020; alavi 2016). if governance monitoring is weak, then many transactions with related parties will occur in the company, which results in fraudulent acts (dorrell et al. 2012). henry et al. (2007) revealed that there are 85 several weaknesses in the audit system, including the failure of the auditor to identify transactions of related parties that have special transactions. they also stated that notes on financial reports were intentionally misinterpreted or improper in order to influence financial policies issued by investors or report users (kuhn and siciliani 2013; lombardi et al. 2015; roychowdhury et al. 2019). table 4 ways of fraud on government organizations. concealment techniques and methods source and quoted from: purchase and procurement of goods or services mark-up price of goods miroslav et al. (2014), ameyaw et al. (2012) purchase of fictional items mamedova et al. (2017) making roads and bridges in the forest but fictional graafland and van liedekerke (2011) physical infrastructure development but not finished graafland and van liedekerke (2011) purchase of goods for one unit, but recorded for two or more units ameyaw et al. (2012), mamedova et al. (2017) purchase of goods for personal use, but paid for with government money ameyaw et al. (2012), mamedova et al. (2017) physical infrastructure development that is not important graafland and van liedekerke (2011) the existing physical infrastructure development was rebuilt graafland and van liedekerke (2011) waste of purchasing goods miroslav et al. (2014), ameyaw et al. (2012), mamedova et al. (2017) purchase of goods that do not match specifications miroslav et al. (2014), ameyaw et al. (2012), mamedova et al. (2017) financial statement manipulation lots of transaction evidence original but untrue kuhn and siciliani (2013) activity reports but no service activities othman et al. (2015) fictional official travel report kemp (2010) fake payroll signature othman et al. (2015), kemp (2010) purchase reports are not real mamedova et al. (2017) unreasonable asset report mamedova et al. (2017) state money reporting fraud in insurance investments kose et al. (2015) misstatement of regional company assets ameyaw et al. (2012), mamedova et al. (2017) deliberate misstatement of state revenue ameyaw et al. (2012), mamedova et al. (2017) manipulation on official trip expenses extending the period of official travel, even though it is less othman et al. (2015), kemp (2010) adding personnel for official travel, even though it is fictitious glancy and yadav (2011), othman et al. (2015), kemp (2010) take someone else on a trip, but at state expense glancy and yadav (2011), othman et al. (2015), kemp (2010) create a fake hotel bill glancy and yadav (2011), othman et al. (2015), kemp (2010) creating fake travel ticket invoices glancy and yadav (2011), othman et al. (2015), kemp (2010) creating a fake travel certificate glancy and yadav (2011), othman et al. (2015), kemp (2010) manipulation of granting business licenses asking entrepreneurs for a certain amount of money for the cost of obtaining a permit, even though it is illegal ferry and lehman (2018) give additional permits to entrepreneurs for illegal additional land meehan and tacconi (2017), ferry and lehman (2018) charging illegal fees for environmental permits meehan and tacconi (2017), ferry and lehman (2018) receiving money from companies that violate the environment meehan and tacconi (2017), ferry and lehman (2018) receiving bribes from companies that have experienced work accidents, so that they are not prosecuted meehan and tacconi (2017), ferry and lehman (2018) receiving money from entrepreneurs for social purposes, but illegal meehan and tacconi (2017), ferry and lehman (2018) cheating on the use of natural resources granting forest utilization permits on prohibited land huang and liu (2014), dincer and fredriksson (2018) granting forest utilization permits, by cutting trees and destroying forests huang and liu (2014), dincer and fredriksson (2018) received a certain amount of money to obtain mining business permits that destroy the environment huang and liu (2014), dincer and fredriksson (2018) give permits to use prohibited natural resources (timber) huang and liu (2014), dincer and fredriksson (2018) fraud by a legal officer police and prosecutors help fugitive state fugitives to escape michels (2016), gottschalk and rundmo (2014), ragatz et al. (2012) the police and prosecutors received a certain amount of money to lighten the case michels (2016), gottschalk and rundmo (2014), ragatz et al. (2012) the judge lightly decided the defendant, by receiving a sum of money michels (2016), gottschalk and rundmo (2014), ragatz et al. (2012) a court officer arranges civil proceedings and wins either party michels (2016), gottschalk and rundmo (2014), ragatz et al. (2012) court officials arrange the placement of prosecutors, judges, and other officers to receive leniency michels (2016), gottschalk and rundmo (2014), ragatz et al. (2012) 86 3. methods and objective we used semi-structured interviews and surveys to collect data. the respondents we selected included auditors at an accounting firm affiliated with big-4 in indonesia. we distributed approximately 200 questionnaires to the respondents. in the questionnaire, we included items that asked the respondent's willingness to be interviewed. the questionnaires we sent were received, but only 76 returned, making the response rate around 38%. only 21 out of 76 respondents who were willing to process the interview returned the questionnaire. sequential mixed research combines the methods of collecting interview and survey observation data in an effort to explore survey results with semi-structured interviews (subedi 2016). the interview process is used to deepen the information obtained from the survey data collection. this study requires in-depth technical assessment, which requires clarification from experienced auditors with at least two years of experience. many auditors are inexperienced and just guess when answering surveys, so they are not informative. twenty-one people were available for video calls. each interview lasted about 20-25 minutes, and we recorded the results of all interviews, except for three respondents who did not consent. all the data collected through our survey was tested for the relationship between the auditor's experience in the audit assignment and the ability to reveal fraud in the preparation of financial reports, both in the public and private sectors, using nonparametric statistical tests. the statistical analysis used was a phi-test. the phi-test is an associative test on a nominal data scale if the contingency table is 2 x 2. so, it can be said that the phi correlation coefficient is designed for dichotomized variables (loeb et al. 2017). 4. results and discussion 4.1 descriptive statistical analysis we have mentioned above that the respondents are auditors. the survey results related to auditors' perceptions are presented in the following descriptions including the experience of auditors, classification of public accounting firms, qualifications of public accountants, job public accountants who are willing to be interviewed, and audit experience of interviewees. based on the results of a survey of 76 auditors, the respondants predominantly stated that there was fraud in organizational governance, both in the public sector and in the private sector. from small to large-scale fraud, all reports related to manipulating financial reports and enriching oneself through illegal practices. however, even though they were aware of these practices, rarely did the respondents dare to reveal the incident for various reasons (64.47%, n = 49/76 respondents). these reasons include the fear of losing their job by clients, lack of protection for auditors, weak laws regarding the rights and obligations of auditors, and that the auditors have weak trust in indonesian law. this finding is in line with the expert's opinion that the law has not guaranteed the rights and obligations of auditors in acting to reveal crimes. there is evidence from research in africa, for example, that no lawsuits are made by accounting firms outside of the absence of a legal system that protects accounting firms. this is because of high fear and worry (salihu and berisha-hoti 2019; kawadza 2017). the result is that fraudulent acts will continue to flourish if the legal system does not fully protect accounting firm auditors who disclose fraudulent acts (cordis and lambert 2017). table 5 respondent audit experience. experience range frequency percent 0 2 years 3 3.95% 2 6 years 14 18.42% 6 8 years 28 36.84% over 8 years 31 40.79% total 76 100.0% table 6 classification of accounting firm. classification of accounting firms frequency percent big-4 7 9.21% domestic non-big-4 62 81.58% international non-big-4 7 9.21% total 76 100.0% 87 table 7 qualifications of the public accountant professional. dimensions frequency percent public accountant (ak.) no. 2 2.63% yes. 74 97.37% total 76 100.0% chartered accountants (ca) no. 17 22.37% yes. 59 77.63% total 76 100.0% certified public accountants (cpa) no 51 67.11% yes 25 32.89% total 76 100.0% certified fraud examiners (cfe) no 67 88.16% yes 9 11.84% total 76 100.0% weak law enforcement is one of the obstacles in eradicating fraud in doing business based on the results of the 2017-2018 global competitiveness report released by the world economic forum. even entrepreneurs feel dissatisfied when resolving business disputes in this condition (birhanu and wezel 2020; sharma and soederberg 2020). in some developing countries with weak legal systems, rulers develop legal systems and courts as a way not to ensure society is fair but to use law and courts as tools to justify and maintain the political status quo (sharma and soederberg 2020). conflicts of interest will be the main obstacle when auditors find irregularities in an organization's financial statements. on one hand. the auditor obtains an audit fee but on the other hand, maintains truth and independence (singh et al. 2019). one thing to remember is that the decision is with the top management of the accounting firm, not on the auditors (barua et al. 2020; singh et al. 2019). likewise, the decision by companies to use accounting firms depends on company management (barua et al. 2020). auditors face various challenges in dealing with fraud cases, in addition to risking professionalism as well as risking audit quality that is purely free from pressure (quick and schmidt 2018). the principle of auditor independence supports maintaining the reliability of financial statements. one of the public accounting services is to provide accurate and reliable information for user decisions. every profession must pay attention to product quality, including the quality of the audit produced by an auditor (barua et al. 2020; quick and schmidt 2018). the higher the quality of an auditor, the higher the client's trust in auditors, for example, investors, creditors, government, and the public to use financial reports (singh et al. 2019; quick and schmidt 2018). table 8 the job of public accountants who are willing to be interviewed. public accountant job frequency percent partner 1 4.76% manager 4 19.05% senior auditor 11 52.38% junior auditor 5 23.81% total 21 100.0% table 9 type of public accountant firm that was interviewed. types of classification of public accounting firms frequency percent big-4 6 7.89% non-big-4: domestic 12 15.79% non-big-4: international 3 3.95% total 21 100.0% table 10 audit experience of interviewed respondents. based on the results of our interviews with selected respondents, generally speaking, that fraud in organizational governance is considered normal. the first cause is due to the fear that employees will lose their positions, so whatever changes and wishes come from management must be followed. the company strives to report a good performance in public, due to intense competition. because of this, things can be done to preserve the company image, including manipulating financial reports. pressure from investors to get the maximum profit is one reason for fraudulent financial statements. many believe that because of the difficulty of getting a decent work position, an employee can easily be forced to commit fraud in order to keep his or her job, even in high positions. this is in line with research (ettredge et al. 2017; quick and schmidt 2018). the report from certified global management accounting (cgma 2015) mentions that many employees in the uk work under pressure from managers, then another study reports that around 78% of people in the uk agree that big businesses are more likely to prioritize profits than high ethical standards (ibe 2018). in 2019-2020, the supreme audit agency (bpk) finally revealed the results of an investigative audit of pt asuransi jiwasraya (persero). according to bpk, the financial statements of the stateowned insurance company, jiwasraya, are false financial reports (sulistiyanto and murtini, 2018). this has been occurring since 2006. jiwasraya's profit achievement recorded in the company's financial statements was due to the engineering of financial statements, sometimes called “window dressing.” for example, in 2017, jiwasraya received a profit of idr 2.4 trillion. this profit was unnatural because there was fraud in the reserves in jiwasrata's financial statements amounting to idr77 trillion. in general, financial statement manipulation or fraud is committed because of many motivations, such as the wrong opinion of an informant in an interview that: "… .. the manipulation in the financial statements is very high, many top managements are the main actors because of the many pressures, especially the pressure on obtaining bonuses and the pressure on high profits from shareholders ....". other informants also conveyed other things: "... many employees in the finance department feel obliged to follow orders from their superiors and are loyal, because the impact is that if they do, they will be fired, at least transferred to another department ..." this research is in line with kaseem (2018), which says that the strong pressure from owners increasingly encourages company management to cheat in an effort to provide the best information for the company's performance. the research by makhaiel and sherer (2017) also shows employees and investors increasingly encourage management to cheat in financial reporting. the results of our survey found that 53% of the external auditors interviewed in this study had encountered suspicions of reporting cases of financial fraud during an audit and management is almost always involved in these. this is in line with kaseem's (2019) study which found that financial reporting fraud is more likely to be carried out by management. the reason why management is most involved in fraud is the existence of highprofit pressure and bonus motivation. much of our in-depth study of informants is related to revenue recognition. income recognition is the easiest to manipulate and difficult to detect by outsiders, in this case, investors. the foresight of auditors is important because they can see if the revenue recognition transaction is reasonable or not (charlopova et al. 2020; alavi 2016). some developing countries have experienced cases of fraud, especially in the recognition of income, which is the area where most manipulations are made. research from dorrell et al. (2012) and charlopova et al. (2020) reported that there were many cases of fraud on income abuse. in march 2020, in indonesia, there was a hand-catching operation (ott) conducted by the corruption eradication commission (kpk) to one of the directors of pt krakatau steel experience range frequency percent 0 5 years 3 14.29% 5 8 years 6 28.57% 8 10 years 8 38.10% over 10 years 4 19.05% total 21 100.0% 89 tbk. the day after the ott, it was revealed that the director of technology and production of krakatau steel, wisnu kuncoro, was suspected as the recipient of a bribe in the case of procurement of goods and equipment at krakatau steel. the bribery was carried out by contractors, namely kenneth sutardja and kurniawan eddy tjokro (yudi) with an intermediary alexander muskitta. apart from bribery, this fraud case is also related to regulating company revenue. apart from increasing income, misstatement and manipulation of assets are also vulnerable for financial statement fraud in indonesia (jakimow 2018b). the name pt hanson international tbk has been sticking out for a while. this property company has been linked with the scandal of two stateowned insurance companies, pt asuransi jiwasraya (persero) and pt asabri (persero). both jiwasraya and asabri place their customers' funds with a large enough nominal value in pt hanson international tbk. apart from placement through shares, investment also flows through the purchase of mediumterm notes (mtn) or debt securities. in the records of the financial services authority (ojk), pt hanson international was proven to have manipulated the presentation of the annual financial statements (lkt) for 2016. the ojk also imposed sanctions, both for the company and its main director, benny tjokro. in the examination conducted by the ojk, manipulation was found in the presentation of accounting related to the sale of ready-to-build lots (kasiba) with a gross value of idr 732 billion, so that the company's revenue rose sharply. the results showed that some auditors agreed (n = 15 or 19.73%) that small companies have more opportunities for financial statement fraud than public companies on idx. meanwhile, at the government level, it shows that some auditors (n = 54 or 71.05%) agree that local government with weak supervision is more likely to commit fraud, compared to local governments with tight supervision from urban communities. for the case of private companies, however, our findings differ from studies in egypt and the middle east, and several other african countries, so their findings cannot be generalized that financial statement fraud is more prevalent in large companies (acfe, 2016). however, acfe only managed to collect evidence from five cases of fraud in egypt and several other african countries, so their findings cannot be generalized. meanwhile, for local governments, many studies show that when the government lacks supervision, the intensity of fraud is higher (puspasari 2015). in the process of government administration and development in the regions, is very important to improve supervision of regional financial management so that the regional revenue and expenditure budget can be managed effectively, efficiently, and achieve the expected goals (lewis and hendrawan 2019). this is in line with the mandate of laws in the field of state finance, which implies the need for a more accountable and transparent state financial management system (puspasari 2015). the results of our interviews with informants regarding corruption in the government: “…… the biggest thing is shopping and bribery, both of them are related. so if the government wants to buy or procure goods, there will be very thick with the practice of bribery and gratification to officials who determine partners. so it is dominant in the procurement of goods ………” the procurement of goods and services is still a source of corruption cases in indonesia. this is because one of the government expenditures has received a very large allocation of funds. therefore, many parties, both government and civil society, are consistent in continuing to highlight this area (mamedova et al. 2017). a researcher from transparency international indonesia (tii) said that the potential for corruption in several areas is dynamically changing, including the procurement of goods and services. the perpetrators also used different modes. the biggest megaproject is the electronic identity card (ktp) project, commonly known as e-ktp, which was started by the ministry of home affairs as the executor, in 2011-2012. the budget for this project reaches idr 5.9 trillion. however, the corruption eradication commission (kpk) said there were irregularities in the "(initial) budget discussion stage". in september 2012, the business competition supervisory commission (kppu) also detected irregularities in the tender process. the kpk has been investigating the alleged corruption case of the e-ktp project since mid-2014. over nearly three years, the agency examined 294 witnesses, named two suspects, and confiscated idr 247 billion. apart from the two defendants, the kpk also questioned 19 politicians who served as 90 people's representatives in the dpr in 20112012. among them were chairman harahap, who was then chairman of commission ii (dpr government commission), and setya novanto, who at that time held the position of chairman of the golkar party faction. perhaps most impressive in this case is the amount of funds that are suspected of being corrupt. of the project value of idr 5.9 trillion, the kpk said the funds that were corrupt reached idr 2.3 trillion. another megaproject case in indonesia, the hambalang project, initially only budgeted idr 125 billion. then, in the hands of andi mallarangeng, the project budget swelled to idr 2.5 trillion. andi mallarangeng served as minister of youth and sports at that time, as well as a member of the board of trustees of the democratic party. the recorded state losses from the misappropriation of the hambalang project were estimated at idr 243.66 billion. this is based on a financial audit conducted by the bpk. apart from andi mallarangeng, the corruption case in the hambalang project also involved the chairman of the national democratic party of urbaningrum. now because of the corruption committed by cadres of the democratic party, the hambalang project must stop. until now, the hambalang project has not made any more significant developments. 4.2 non-parametric statistical testing there is an important issue, namely the experience of auditors related to their ability to reveal fraud. we use alavi-tabulation of the phi-test to test whether there is a relationship between audit experience and fraud detection ability in the audit process. table 11 the method used to carry out a fraud scheme in indonesia. dimensions explanations improper asset valuation excessive inventory: § overbooking fixed assets § personal interests are capitalized § record excessive inventory balance § incorrect asset classification § borrowing costs for work-in-process projects are capitalized § some investments are not recorded § record low depreciation for less depreciation expense § there are expenses which are capitalized as assets § excess capitalization of fixed assets misstatement in revenue recognition manager to get a bonus, an increase in income: § manipulate estimates and associated receipt items § record premature income as normal income § accounts receivable manipulated § income is deducted to avoid paying taxes § income is deferred § there are fictitious discounts given on purchases § commission income is recorded in excess § there is a fictitious sale § accounts receivable that are recorded is greater § exaggerate income by hiding costs § manipulate the allowance for doubtful accounts hidden obligation manipulation in contingent liabilities and provision: § there are tax obligations and tax costs that are not recorded § misclassification of debt from long term to short term, or vice versa § underpayment of loan installments hidden costs avoid paying taxes by exaggerating expenses and costs: § does not record costs § there are expenses at the end of the period that are not recorded § there is a rental fee recorded as an asset incorrect disclosure doesn't reveal: § transactions with related parties § source of funds § director's remuneration cheating government officials doesn't reveal: § taking bribes for projects § accept bribes for sda business permits § inflated the price of an item § fictitious purchase § appoint incompetent associates table 12 alavi-tabulation of the relationship between audit experience and the possible ability to reveal fraud in financial statements. explanation audit experience total 0-2 year 3-5 year 6-8 year 8 year up likelihood of detecting financial fraud no 1 6 8 8 23 yes 2 9 15 27 53 total 3 15 23 35 76 table 13 phi test of the relationship between audit experience and the possible ability to reveal fraud in financial statements. explanations value approximate significance exact significance nominal by nominal phi cramer’s v .270 .134 .141 .270 .134 .141 number of valid cases 76 phi cramer's analysis shows that although there is a chance the auditor may find fraud if experienced, the relationship is relatively weak. the experience of an auditor is one of the factors that influence this ability because auditors who are more experienced can detect fraud in the financial statements (sulistiyanto and murtini 2018). research by corbella et al. (2015) also states that experienced auditors will have more knowledge of mistakes and fraud, which will result in better performance in detecting cases of fraud compared to inexperienced auditors. the results of this analysis also show that all auditors who have a certified fraud examiners (cfe) certificate find it easier to find fraud in the company. this shows the importance of special professional education that can increase the ability of auditors to find fraud (kassem 2018). continuous professional development must focus on developing strong analytical skills and abilities in using forensic accounting and efforts to warn companies that in the future some companies are likely to collapse (earley 2015). fraud is increasingly occurring in various ways that continue to develop so that the ability of auditors to detect fraud must also be improved. auditors are required to be able to detect fraud in carrying out audit tasks. the problem that arises is that auditors have limitations in detecting fraud (ulfah et al 2020, handayani et al. 2016). limitations by auditors will cause gaps between users of the auditor's services who hope that the auditor can assure them that the financial statements presented do not contain misstatements and instead reflect the actual situation. each auditor has different abilities in detecting fraud due to several factors, for example, the workload faced by auditors, different levels of experience, and different levels of skepticism (ettredge et al. 2017). there is evidence that most auditors do not understand fraud schemes well enough to understand the high risk of fraud and that in the quality of the audit process, knowledge of fraud, training, and experience are the most important factors in detecting fraud (othman et al. 2015). 5. conclusions various acts of fraud in organizations have happened around the world. in indonesia, for example, the cases of fraud happen mostly in companies where there is the recognition of income that is not acknowledged by ifrs, as well as fraud in asset valuation which results in the manipulation of financial statements. in contrast to government organizations, fraudulent acts mostly involve the purchase and supply of goods, which are followed by bribery and inflating the price of goods. similar results also occurred in japan, britain, egypt, and the united states. our findings also state that financial reporting fraud in indonesia is more common in small companies and is very common in companies that are not listed on the indonesia stock exchange (idx), and also in family-owned companies and companies that prepare consolidated financial statements. meanwhile, at the government level, we show that some auditors agree that local government levels with weak supervision are more likely to commit fraud, compared to local governments with tight supervision from urban communities. 6. future research 92 phi cramer's analysis shows that while the audit experience may increase the likelihood of detecting fraud, the relationship is relatively weak. other findings also show that all auditors who have a cfe find it easier to find fraud in companies. this shows the importance of special professional education that can detect fraud in increasing the ability of auditors to detect fraud. future research opportunities should explore the fraud profile on the recognition of revenues, expenses, and asset capitalization with an in-depth approach to specific informants. then it would be interesting to explore the reasons why auditors are not willing to disclose fraud. this will be useful for auditors in developing a good audit scheme to detect fraud. the implication of this research will be to develop a more sophisticated audit model in terms of plans, methods, sampling, and audit mechanisms. this research has identified the types of fraud, both in the private and government sectors. this study can be used as a reference in the initial process of identifying fraud in audit planning. the limitations of the study are related to the difficulty of moving to the field due to largescale social restrictions in several regions in indonesia, so the data we gathered is limited. 7. references alavi, m. 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(2019) a new corpus-based convolutional neural network for big data text analytics. journal of intelligence studies in business. 9 (2) 59-71. article url: https://ojs.hh.se/index.php/jisib/article/view/409 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a new corpus-based convolutional neural network for big data text analytics wedjdane nahilia*, kahled rezega, okba kazara alinfi laboratory, computer science, biskra university, algeria *w.nahili@univ-biskra.dz journal of intelligence studies in business please scroll down for article a new corpus-based convolutional neural network for big data text analytics wedjdane nahilia*, kahled rezega and okba kazara alinfi laboratory, computer science, biskra university, algeria corresponding author (*): w.nahili@univ-biskra.dz received 3 september 2019 accepted 27 october 2019 abstract companies market their services and products on social media platforms with today's easy access to the internet. as result, they receive feedback and reviews from their users directly on their social media sites. reading every text is time-consuming and resourcedemanding. with access to technology-based solutions, analyzing the sentiment of all these texts gives companies an overview of how positive or negative users are on specific subjects will minimize losses. in this paper, we propose a deep learning approach to perform sentiment analysis on reviews using a convolutional neural network model, because that they have proven remarkable results for text classification. we validate our convolutional neural network model using large-scale data sets: imdb movie reviews and reuters data sets with a final accuracy score of ~86% for both data sets. keywords convolutional neural networks, deep learning, natural language processing, nlp, user reviews, sentiment analysis, text classification 1. introduction the main purpose of sentiment analysis is analyzing and understanding expressed human emotion in text data. people are sharing daily thoughts and opinions about everything, and as a result, social media platforms have become the source of varied data, such as reviews of products, movies, and services. with the availability of this content a new type of information is harvested. understanding ‘what people think’ and the real meaning of this user-generated data is crucial. movie review sites such as imdb, rotten tomatoes and netflix represent an important source of information for researchers. the main reason behind this attention is the fact that valuable knowledge is often hidden behind this content and cannot be easily processed, which has gained increasing popularity among natural language processing (nlp) researchers. deep learning algorithms are useful when it comes to solving natural language processing problems, and the reason resides in the combination of a large sample of data and a general learning algorithm (collobert et al., 2011). several methods can do this with traditional algorithms such as naive bayes and support vector machine (svm). most of these methods consider the text word by word and classify a sentence as positive or negative by analyzing the words in the text. sometimes information can be lost by extracting a keyword without another word (shen et al., 2014). recently, sentiment analysis research successfully used deep learning. convolutional neural networks is one of the machine learning models that has archived remarkable results in image recognition and in natural language processing (collobert et al., 2011). in order to propose a text classification approach using deep learning, this work journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 59-71 open access: freely available at: https://ojs.hh.se/ 60 introduces a new convolutional neural network architecture for text classification, solving different natural language processing tasks, specifically sentiment analysis. our model’s strengths are its training time and accuracy. in our sentiment analysis model, we utilize convolutional neural networks because they have impressive results in image analysis and classification fields. with their convolution operation they can extract an area of features from global information, and are able to consider the relationship among these features (y. kim, 2014). for computer vision, such as image analysis, convolutional neural networks are able to extract pixel data information. this means they can not only extract the pixels one by one, but also the feature information can be extracted piece by piece, where the piece contains multi-pixel data information. thus, according to (krizhevsky et al., 2012) when text is transferred into a matrix, it can also be considered to be the same as an image-pixels matrix. as a result, we can do the same operation to the text data to make the input features to the model that can be trained in another effective way (yoon kim, 2014). in this paper, we propose a convolutional neural network (cnn) model to apply sentiment analysis on movie review data in order to predict sentiment orientation. firstly, as an input to our network model, we use the word2vec proposed by google to compute vector representations of words and reflect the distance between them. this step leads to initializing the parameters for our cnn model, therefore, efficiently improving the network performance in this particular problem. secondly, we propose a cnn architecture with three convolution layers with padding, a flatten layer followed by two dense layers. to the best of our knowledge, using this layer architecture in a cnn model with an embedding layer (word2vec) to analyze movie reviews sentiment has not been addressed before in the literature. and finally, to improve the accuracy of our model, we use normalization and dropout layers. the present work is organized as follows: section 2 presents a brief literature background with some related concepts used in our approach. section 3 outlines the related work on sentiment analysis and text classification, with an emphasis on deep learning methods. in section 4, we present our approach and provide the description for the proposed architecture. in section 5, the results and experimental setup are explained in detail along with the datasets used to train, test and validate our model and we present and elaborate on the performance using our model, and provide insight into the findings. finally, we conclude our work and discuss future directions in section 6. 2. background 2.1 convolutional neural networks convolutional neural networks, also known as convnets, are a deep learning tool that has gained traction in computer vision applications (s. srinivas et al., 2016). they were first introduced in y. lecun et al., (1989) to recognize handwritten zip code in 1989. they were later extended to recognize and classify various objects such as hand-written digits (mnist), house numbers (p. sermanet et al., 2012), caltech-101 (l. fei-fei et al., 2007), traffic signs (p. sermanet et al., 2011), and recently the work of a. krizhevsky et al. (2012) produced a 1000-category imagenet data set. the choice of using neural networks to create natural language processing (nlp) applications is attracting huge interest in the research community and they are systematically applied to all nlp tasks (y. kim, 2014). the fundamental idea of cnns is to consider feature extraction and classification as one joined task. the scope of using this methodology in text analytics has proven to be advantageous in various ways (d. santos et al., 2014; a. severyn et al., 2015; s. srinivas et al., 2016). in deep learning techniques, there is supervised learning, unsupervised learning, hybrid learning and reinforced learning (a. gibson and j. patterson, 2017), but supervised learning and unsupervised learning are the most common techniques. the main difference is: in supervised learning, the data is labeled and known prior to training. this technique is suited for classification and regression problems. in unsupervised learning, the data is not labeled, which makes it good for clustering problem where algorithms can find different types of patterns within the unlabeled data (m. mohri et al., 2012). with machine learning, there is deep structured learning, commonly known as deep learning. it can be used in different learning frameworks such as unsupervised, supervised and hybrid networks, in addition of different classification, regression and vision problems (l. deng and d.yu, 2014). a deep learning model can be described as a model of two nodes, where one is 61 an input, and the other an output. data is sent between these two nodes through the input layer. the data is examined at different levels and features once it is sent onto the hidden layers. recently, cnns have been adopted in natural language processing, sentiment analysis, text, topic and document classification for the following key reasons: cnn can extract an area of features from global information, it is able to consider the relationship among these features (y. kim et al., 2014), and text data features are extracted piece by piece and the relationship among these features, with the consideration of the whole sentence, thus, the sentiment can be understood correctly. 2.2 sentiment analysis there are a number of different problems that deep learning is trying to solve. from classification problems where the algorithms assign categories to items, for instance, news categories, and to regression problems where the algorithm gives predictions on real values like a prediction on the stock market (m. mohri et al., 2012). another problem is sentiment analysis, also known as opinion mining. sentiment analysis is an active research field in natural language processing, where people’s emotions, opinions, and sentiments towards different entities like products, services, and organizations are studied and analyzed. sentiment analysis is important for companies, organizations and individual persons (d. tang, 2018). companies want to know what people think about their products and services while on the other hand, individual people want to know what others think about a product they are considering purchasing. daniel angus stated: "this not only provides insight into what people think about your brand, but it can go a lot deeper. it can expose why people are thinking it.” in sentiment analysis, the goal is to determine whether a given piece of text is positive, negative or neutral. various work has been done in the field of sentiment analysis in recent years where text is analyzed in several ways. in general, there are three levels of sentiment analysis: document-level, sentencelevel and aspect-based level (a. kharde, 2016). document-level: at this level, the analysis takes in consideration that the entire document has only one opinion. sentence-level: this level takes in consideration each sentence as containing one opinion and thus, the polarity of the entire document depends on the polarity of the sentences. aspect-based level: is also known as featurebased sentiment analysis. at this level, each sentence can contain more than one aspect in order to determine the polarity of the document (a. kharde, 2016). the main advantage of deep learning approaches in sentiment analysis remains in the fact that networks train themselves on the same data to learn the structures and context of the data. the data can vary and is often in the form of electronic data collected and made available for analysis. the crucial aspects of the data are the size and quality of the information. the better the quality of the data used in training, the better the results of predicting data in the future (j. heaton, 2015). 2.3 natural language processing natural language processing (nlp) is an industry term for algorithms designed to take a document consisting of symbols and deduce associated semantics (russell. m, 2011). research in nlp deals with the application of computational models to analyze text or speech data. much work has been done in the field of nlp (mikolov et al., 2013; ouayang et al., 2015; houshmand, 2017; kalchbrenner et al., 2014) in order to allow semantic processing. sentiment analysis is the research area where nlp algorithms are most often used, due to the amount of available data resulting from shared information on different social media platforms such as facebook, twitter, amazon, yelp, imdb and netflix. until now, most sentiment analysis work has been done on short texts derived from social media sites. in this work, we analyze review texts because they provide sentiment about products or movies, therefore, when the result of this analysis is applied, it will help companies around the world to improve the decision-making process. further, to automate sentiment analysis, different approaches have been applied to predict sentiments of words, expressions or documents (mikolov et al., 2013; ouayang et al., 2015; houshmand, 2017; kalchbrenner et al., 2014). these include nlp and deep learning methods. in our attempt to analyze the sentiment of movie review data and topic classification, we propose a deep learning approach that combines the advantages of available techniques such as cnns along with nlp basic tasks. the following section reviews and discusses related work in the field of sentiment 62 analysis on reviews with emphasis on deep learning techniques. 3. related work recently, much work has been done in the field of sentiment analysis in natural language and social network posts. to determine whether a piece of text expresses a positive or negative sentiment, two main approaches are commonly used: the lexicon-based approach and the machine learning-based approach. in recent years, deep learning models have achieved remarkable results in computer vision (krizhevsky et al., 2012) and speech recognition (graves et al., 2013). in the area of natural language processing, research on deep learning approaches (bengio et al., 2003; mikolov et al., 2013; yih et al., 2011) has associated learning word vector representations. although originally invented for computer vision and image analysis, cnns have proven to be effective for nlp. these models have achieved impressive results in semantic parsing (yih et al., 2014), search query retrieval (shen et al., 2014), sentence modeling (kalchbrenner et al., 2014), and various traditional nlp tasks (collobert et al., 2011). ouayang et al. (2015) proposed a cnn and word2vec methodology for movie review sentiment analysis using a dataset from rottentomatoes.com. the data set contained 11,855 reviews with five different sentiment classifications (negative, somewhat negative, neutral, positive and somewhat positive). their cnn model used three different convolution layers with different kernels and each layer was followed by a dropout layer and normalization layers. to evaluate their results, they compared their model against other algorithms/models including naive bayes, svm, recursive neural network (rnn) and matrix-vector rnn (mv-rnn). the results show that performance is best when it comes to classifying every review into the five different classifications. their model achieved a test accuracy of 45.4% on the test data set. houshmand (2017) compared different neural networks architectures against the naive bayes algorithm to see how well they performed on movie reviews from the stanford sentiment tree bank dataset. the results of their study showed similar accuracy between the neural networks used (recurrent, recursive and convolutional neural networks) and naive bayes. one interesting thing about the result was the fact that their model’s accuracy improved significantly by adding a word vector from word2vec to the network. their model reached an accuracy of 46.4% on the test data while the cnn without a word vector had 40.5% accuracy (table 1). table 1 corpus-based related work. corpus accuracy semantic parsing (yih et al. 2014) cnn model 54% sentence modeling/sentiment analysis (kalchbrenner et al. 2014) dcnn model sst movie review trec text retrieval binary class 86.8% fine-grained 48.5% sentiment analysis (ouayang et al. 2015) cnn+word2vec model rotten tomatoes movie review five classes 45.4% sentiment analysis (houshmand, 2017) cnn model stt movie reviews 40.5% sentiment analysis (houshmand, 2017) cnn+word2vec model stt movie reviews 46.4% despite the strong empirical performance in (yih et al., 2014) and the good results in the work of (mikolov et al., 2013; ouayang et al., 2015; houshmand, 2017; kalchbrenner et al., 2014) we concluded that in (yih et al., 2014) their system has no room for improvement because the corpus derived from the wikianswers data and reverb kb does not contain enough data to train a robust cnn model. still, using word embeddings significantly improves the network’s performance (houshmand, 2017). we propose a corpus-based cnn model to do sentiment analysis on a large-scale dataset (imdb) in order to predict sentiment orientation. firstly, similar to (houshmand, 2017) as an input to our network model we use the word2vec as a lexical resource proposed by google to compute vector representations of words and reflect the distance between them. this step leads to initialize the parameters at a good point of our cnn model. secondly, the proposed sentiment analysis approach is done using a convolutional neural network architecture with three convolution layers with padding, a flatten layer followed by two dense layers with two dropout layers in between. to the best of our knowledge, using this architecture in a cnn model with an embedding layer to analyze movie reviews sentiment classification has not been addressed before in literature. our results with 63 the proposed model have better results compared to related work. 4. proposed approach with access to technology-based solutions and the rapid growth of social media platforms such as twitter, facebook, and online review sites such as imdb, amazon, and yelp, users are sharing daily thoughts and opinions about different entities. these entities can be products, services, organizations, individuals, events, issues, or topics. this exponential growth of user-generated content draws growing attention from data scientists, as well as research and industry communities. the issue remains that reading every piece of this raw text data is time-consuming and resource demanding, therefore, analyzing this huge amount of text automatically gives companies an overview of how positive or negative users are to specific subjects will minimize losses. in order to automate this process work has been done in different fields like semantic parsing, sentence modeling and sentiment analysis (mikolov et al., 2013; yih et al., 2014; ouayang et al., 2015; houshmand, 2017; kalchbrenner et al., 2014). despite the results of previous work (mikolov et al., 2013; ouayang et al., 2015; houshmand, 2017; kalchbrenner et al., 2014), in addition to the strong empirical performance in yih et al. (2014), their system has no room for improvement because the corpus does not contain enough data to train a robust cnn model. with the propose largescale corpus-based model, we are able to obtain better results. in this work, we use a cnn model to perform two tasks: binary-class sentiment analysis and multi-class text classification. in order to do so, first we analyze the sentiment of movie reviews using the publicly available imdb dataset, then we classify news/ topics using the reuters dataset. by using nlp, the computer can understand more than just the objective definitions of the words. this step includes using the word2vec model proposed by google, which is a way of extracting features from the text for use in modeling, also using a classifier module to identify if a given piece of text is positive or negative in the case of sentiment analysis, and which topic or category the given piece of text fits into (figure 1). in this case, we are using a new cnn model as our classifier. python libraries help the model learn with a faster curve, and the package “pandas” will help us read our csv files containing both datasets. a natural language toolkit (nltk) is used to remove unnecessary data from the data sets. figure 2 represents the process that takes place throughout the sentiment analysis process, which is divided into two sub-processes: the learning process where we train, test and validate our proposed cnn model and the classification process where new data is fed to the model. as illustrated in figure 2, before any further analysis of the input text data, text pre-processing is needed, followed by text vectorization. figure 1 general architecture for text classification problems. 64 4.1 data pre-processing it is necessary to normalize the text for any natural language processing tasks. since it is often represented in a cryptic and informal way, systematic pre-processing of reviews is required to enhance the accuracy of our sentiment classifier. in this work, we perform a corpus-based analysis on text from users’ movie reviews. since natural language is frequently used in reviews, this type of text data contains a lot of noise as shown in example 1, therefore, cleaning unnecessary information from raw comments (reviews) is needed. the movie review binary-class dataset used is imdb, which contains 50,000 movie reviews labeled by sentiment (positive/negative). similar to any nlp task, before any further processing, cleaning-up the data is crucial which involves the following steps: 1. remove numeric and empty texts 2. remove punctuation from texts 3. convert words to lower case 4. remove stop words as demonstrated in example 1, the datasets used contain non-relevant data (noise). therefore, basic cleanup needs to be performed. arbitrary characters and other useless information such as punctuation, stopwords, special characters and links/urls were removed, since we found no significance in our classification approach. then, text normalization was applied using regular expressions. when these nlp tasks are completed, the processed reviews are stored in a comma-separated value (csv) file for further processing. stemming and lemmatization are text normalization (or sometimes called word normalization) techniques. this step is very important in order to get better accuracy for the proposed cnn model, and it consists of preparing the text, words, and documents for further processing. in order to stem and lemmatize words, sentences and documents, we used the public python nltk package, the natural language toolkit package, provided by python for nlp tasks, as shown in example 2. example 1: ## [1] “i was blessed to have seen this movie last night. it made me laugh, it made me cry and it made me love life. this movie is a great movie that depicts a love of a father for his son. will smith did an incredible job and deserves every accolade available to him. his son also did a fantastic job. there is a great lesson that is learned in this movie and it truly shares the struggles of everyday life. this movie was heart felt and touching. it was truly an experience worth having. thank you for making this movie and i look forward to seeing it again.” ## [1] “blessed night made laugh made cry made love life great depicts love father son incredible job deserves accolade son fantastic job great lesson learned shares struggles everyday life heart felt touching experience worth making forward” example 2: “data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured,[1][2] similar to data mining.” 4.2 text vectorisation in order to convert string features into numerical features, one can use one of the following methods. one hot encoding maps each word to a unique id, it has typical vocabulary sizes. they will vary between 10,000 and 250,000. this method is a natural representation to start with, though a poor one due to several drawbacks such as the size of input vector figure 2 global architecture for the proposed system. 65 scales with size of vocabulary. there is the “out-of-vocabulary” problem (h. l. trieu et al., 2016) where there is no relationship between words (each word is an independent unit vector). also it is vulnerable to overfitting: sparse vectors which result in computations going to zero (t. ojeda et al., 2018). bag of words is an approach where we set all words in the corpus (t. ojeda et al., 2018). its main advantage is that it is quick and simple. but it is too simple and orderless, without syntactic or semantic similarity. n-gram model is a model with a set of all ngrams in the corpus. it tries to incorporate the order of words (t. ojeda et al., 2018), unfortunately it still has a very large vocabulary set and no notion of syntactic/semantic similarity. term frequency-inverse document frequency is a model that captures the importance of a word (term) to a document in a corpus. the importance of a word increases proportionally according to the number of times a word appears in the document; but is contrarily equivalent to the frequency of the word in the corpus (t. ojeda et al., 2018). the key advantage of this method is that it is easy to compute and has some basic metric to extract the most descriptive terms in a document. thus it can easily compute the similarity between two documents using it, but it does not capture the position in the text, semantics and co-occurrences in different documents because it is based on the bag-ofwords model. thus term frequency-inverse document frequency is only useful as a lexical resource, but it cannot capture semantics like topic models and word embedding. in our work we use word2vec published by google in 2013, which is a neural network implementation that learns distributed representations for words (mikolov et al., 2013). prior to word2vec, other deep or recurrent neural network architectures had been proposed (ouayang et al., 2015; kalchbrenner et al., 2014) for learning word representations. the major problem with previous attempts was the long time required to train the models, while word2vec learns quickly compared to these models. in order to create meaningful representations, word2vec does not need labels. since most data in the real world is unlabeled, this feature is very useful. if the network is trained on a large dataset, it produces word vectors with interesting characteristics. as a result, words with similar meanings appear in clusters, and clusters are spaced such that some word relationships, such as analogies, can be reproduced using vector math. 4.3 convolutional neural network classifier we propose a word-based cnn architecture for both binary-class and multi-class text classification. first, there is a sentiment analysis on the imdb movie reviews dataset, which contains 50,000 movie reviews labeled by sentiment (positive/negative), and second a text (topic) categorization for the reuters corpus, which contains 10,788 news documents totaling 1.3 million words, where the documents have been classified into 90 topics and grouped into two sets. as shown in figure 3, we train a cnn with an embedding layer and different convolution layers with padding. the purpose of using padding in every convolution layer is to conserve the size of the input data as it is; thus, no information is lost (shen et al., 2014). these convolution layers are followed by a flatten layer and two dense layers with two dropout layers. 4.3.1 sentence matrix instead of image pixels, the input to most nlp tasks is sentences or documents represented as a matrix. each row of the matrix corresponds to one token, typically a word, but it could be a character (krizhevsky et al., 2012). that is, each row is a vector that represents a word. typically, these vectors are word embeddings figure 3 the layer architecture of the proposed cnn model. 66 like word2vec or glove. for example in our work, a 10 word sentence using a 300dimensional embedding, has a 10×300 matrix as input. that’s our input sentence matrix (image) to the network (y. kim et al., 2014). 4.3.2 embedding layer as input to our proposed model, the first layer is an embedding layer which is defined as the first hidden layer and its role is to transforms words into real-valued feature vectors known as embeddings. these vectors are able to capture morphological, syntactic and semantic information about the words. it must specify the following arguments: top-words, embedding-vector-length, and max-reviewlength. in this work, we truncate the reviews to a maximum length of 1600 words and we only consider the top 10,000 most frequently occurring words in the movie reviews dataset, and we used an embedding vector length of 300 dimensions. this is an important step in the proposed network architecture because it initializes the parameters of our cnn model. the output of the embedding layer is a 2d vector (none, max-review-length, embeddingvector-length) with one embedding for each word in the input sequence of words. some modification is applied to the basic convolutional operation (layer) where padding is used to conserve the original size of the input sentence matrix, therefore, there is no loss of information (shen et al., 2014). to connect the dense layer (fully connected layer) to the 2d output matrix we must add a flatten layer in order to convert the output of the convolution layers into a single 1d vector to be used by the dense layer for final classification (figure 4). 4.3.3 fully activated layer (dense) in deep learning models, activation functions are used at the fully activated layer (dense) and they can be divided into two types: linear activation functions and non-linear activation functions (ml, 2018). in our work, the first experiment is binary-class sentiment analysis using the imdb dataset where we used the sigmoid activation function. we used a sigmoid function because it exists between 0 to 1. therefore, it is adequate for our model since we have to predict the probability as an output. in the second experiment we train, test and validate our cnn model on a multi-class reuters dataset. we used the soft-max activation function since it is a more generalized logistic activation function, which is used for multi-class classification. 4.3.4 dropout layer with approximately 7 million trainable parameters, the proposed cnn model is very powerful. however, overfitting is a serious problem in large networks, making them slow to use and thus difficult to deal with overfitting by combining many different predictions. dropout is a technique that prevents this problem and it refers to dropping out units (hidden and visible) in a neural network (lai. s-h et al., 2017). by dropping a unit out, we mean temporarily removing it from the network, along with all its incoming and outgoing connections. in our model we use two dropout layers with (0.2), and the choice of which units to drop is random. 5. results and discussion we propose a cnn model to apply text classification. we define a cnn model and we train it on publicly available data sets: th imdb movies reviews dataset and the reuters dataset. our model is word-based cnn with an embedding layer. at the embedding layer level, we tokenize text review sentences to a sentence matrix with rows where each row contains word vector representations of each token. in our work, we truncate the reviews to a maximum length of 1600 words and we only consider the top 10,000 most frequently occurring words in the movie reviews dataset. we experiment with the network model in two settings. the first experiment involves predicting sentiment classification of movie reviews and the second one is news/topic figure 4 total number of trainable parameters in our cnn model. 67 classification. the network performs well in both the binary and the multi-class experiments. 5.1 datasets as shown in table 3, to evaluate the performance of our proposed model, we used two large scale datasets, the binary class imdb dataset for sentiment classification (a. maas et al., 2011) and the multi-class reuters data set for news/topic classification (table 2). table 2 imdb and reuters datasets. imdb reuters #of sentences 50k #of positive reviews 25k #of negative reviews 25k # of documents 10788 # of topics 90 # of word 1.3 million we benchmark our cnn model on two different corpora from two different domains: movie reviews and news/topic classification. the movie review binary-class dataset used is imdb, which contains 50,000 movie reviews labeled by sentiment (positive/negative). reviews have been pre-processed, and each review is encoded as a sequence of word indexes (integers). this allows for quick filtering operations such as: "only consider the top 10,000 most common words, but eliminate the top 20 most common words" (a. maas et al., 2011). in our experiments, we focus on sentiment prediction of complete sentences (reviews). the second corpus we use is the reuters news wire topic classification. this dataset is a multi-class benchmark (e.g. there are multiple classes), multi-label (e.g. each document can belong to many classes) dataset (m. thoma, 2018). both datasets are used to validate our model, where the first dataset is the imdb movies reviews. the data was split evenly with 25,000 reviews intended for training and 25,000 for testing. moreover, each set has 12,500 positive and 12,500 negative reviews. we pre-processed the reviews, and each review is encoded as a sequence of word indexes (integers). and the second dataset is the reuters dataset for document classification; it has 10,788 news documents and 90 classes/topics. we conduct an empirical exploration on the use of the proposed word-based cnn architecture for sentiment classification on imdb movie reviews and the reuters corpus for text categorization, which contains 10,788 news documents totaling 1.3 million words where the documents have been classified into 90 topics and grouped into two sets. in the present work, we train a cnn with an embedding layer, convolution layers, a flatten layer and two dense layers with two dropouts. although cnns extract high-level features in image analysis, our model actually performs well in 2d problems and trains 50% to 60% faster as shown in figures 5 and 6. the proposed model has ~7m trainable parameters and is trained in a python environment which takes around 15 to 20 minutes on an intel (r) core (tm) i5-5200u cpu with 2.20ghz of ram. figure 5 loss function and accuracy values of the proposed model on the imdb dataset. figure 6 loss function and accuracy values of the proposed model on the reuters dataset. in the sentiment classification of movie reviews using the imdb dataset, in order to horizontally extract features, we used binary cross entropy loss because it is a binary classification problem. to avoid overfitting the training data dropout (0.2) was necessary. for reinforcing the generalization power, we disabled the network with holes during training. this way the network is forced to build new paths and extract new patterns. despite the satisfactory performance of our model, and in addition we were able to validate the proposed model on both imdb and reuters datasets. after 15 to 20 minutes of training, we obtain ~86% accuracy (table 3). 0 0,2 0,4 0,6 0,8 1 1,2 epoch 1/3 epoch 2/3 epoch 3/3 loss acc 0 0,5 1 1,5 epoch 1/3 epoch 2/3 epoch 3/3 loss acc 68 table 3 accuracy of the models on the imdb dataset for binary-class and reuters dataset for multi-class. fine-grained binary cnn model (yih et al. 2014) 54% dcnn model (kalchbrenner et al. 2014) 48.5% 86.8% cnn+word2vec model (ouayang et al. 2015) 45.4% cnn model (houshmand, 2017) 40.5% cnn+word2vec model (houshmand, 2017) 46.4% cnn model 85.95% 85.80% cnn+ lstm model 95% we tried to improve the accuracy of the model by conducting other experiments using a modified cnn and long short-term memory (lstm) architecture. the embedding layer is still the first hidden layer of our cnn-lstm model, we added the lstm layer followed by globalmaxpool 1d layer, and 2 dense layers with dropout. the main difference between the cnn model and the cnn-lstm model is at this level where we have the first dense layer with the ‘relu’ activation function instead of ‘sigmoid’ in the first cnn model. similar to the experiments with our cnn model, in order to avoid overfitting, a dropout layer (0.5) was necessary. this layer is followed by the second dense layer where a ‘sigmoid’ activation function is used. the same nlp tasks are applied to the reviews which involve the following steps: 1. remove numeric and empty texts 2. remove punctuation from texts 3. convert words to lower case 4. remove stop words 5. stemming only the imdb dataset was used to train, test and validate the proposed cnn-lstm model. the labeled dataset consists of 50,000 imdb movie reviews, selected for sentiment analysis. the sentiment of reviews is binary, meaning the imdb rating below 5 results in a sentiment score of 0, and ratings equal to or greater than 7 have a sentiment score of 1 and no individual movie has more than 30 reviews. 5.1.1 raw reviews • ‘with all this stuff going down at the moment...’ • ‘the classic war of the worlds by timothy hi...’ • ‘the film starts with a manager (nicholas bell)...’ • ‘it must be assumed that those who praised this...’ • ‘superbly trashy and wondrously unpretentious 8...’ 5.1.2 processed reviews • ‘stuff go moment mj ive start listen music watch...’ • ‘classic war world timothy hines entertain film...’ • ‘film start manager nicholas bell give welcome...’ • ‘must assume praise film great film opera ev...’ • ‘superbly trashy wondrously unpretentious 80 ex...’ the 25,000 review labeled as the training set do not include any of the same movies as the 25,000 review test set. in addition, there are another 50,000 imdb reviews provided without any rating labels. the labeled training set is tab-delimited and has a header row followed by 25,000 rows containing an id, sentiment, and text for each review. the test set is a tab-delimited file that has a header row followed by 25,000 rows containing an id and text for each review. the task of our cnn-lstm model is to predict the sentiment for each. an extra training set with no labels is provided that is a tab-delimited file with a header row followed by 50,000 rows containing an id and text for each review. one interesting thing about the results of the cnn-ltsm model is that the accuracy improved significantly compared to the first cnn model. the cnn-lstm model reached an f1 score of 0.95 on the test data while the figure 7 loss function and accuracy values of the proposed cnn-lstm model. 0 0,5 1 1,5 epoch 1/3 epoch 2/3 epoch 3/3 acc loss 69 cnn without the lstm layer got ~ 86% (figure 7). we conclude that both models perform well and show satisfactory results against state-of-the-art methods, which is quite respectable given: (1) the large size of the data sets and (2) the number of parameters in the network. 6. conclusion with an aim of classifying the sentiment of movie reviews into two classes (positive or negative) and applying text classification on news text in order to perform topic classification, our method has been implemented with an acceptable performance. as a next step of making use of a data driven model, cnn has been taken into consideration. in this work we present a new cnn architecture that jointly uses word2vec as an input layer to the cnn model and an lstm layer. the proposed model has yielded better results compared to previous methods with an accuracy of ~86 % for the first experiment and 95% for the cnn-lstm (mikolov et al., 2013; ouayang et al., 2015; houshmand, 2017; kalchbrenner et al., 2014). the main contributions of the paper are: (1) the short training time despite the large size of the data sets and the 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(2014). semantic parsing for single-relation question answering. in acl proceeding. zhang, y. and c. wallace, (2016). a sensitivity analysis of convolutional neural networks for sentence classification. cornell university library, computer science, computation and language 43 o p i n i o n s e c t i o n contribution to reduce risks related to strategic decisions in new uncertain competitive environments: the case of algerian state-owned firms abdelkader baaziz 1 and luc quoniam 2 1 irsic laboratory, aix-marseille university, france 2 university of sud toulon var, france email: kbaaziz@gmail.com, mail@quoniam.info, received may 7, accepted may 20, 2014 abstract: the aim of this paper is to show the complexity of the political, legal, social and economic environments where the algerian state-owned firms operate. these environments are qualified by “uncertainty” given the instability of the different parameters cited. since 1988, algeria has initiated deeper economic reforms supported by significant legislation and international agreements. in this uncertain environment, algerian state-owned firm cannot rely only on their internal capabilities. they should, create partnerships, both with suppliers, subcontractors, universities and even competitors. there is a need for these firms to: transform their organization to a new form improved for unexpected events and enough resilience to adapt to uncertain environments. build a strategic intelligence information system able to facilitate decisionmaking and reduce risks inherent to the strategic choices. find ways to reverse choice when unexpected events occur. this article shows there is a need to handle the following risks: inertia against the process of organizational transformation, wrong understanding of the received signals from the environment and poor reaction of the decision-maker to signals and events in the environment. keywords: strategic intelligence information system; knowledge management, competitive intelligence; business intelligence; decision-making under uncertainty, risk available for free online at https://ojs.hh.se/ journal of intelligence studies in business vol 4, no 1 (2014) 43-57 mailto:kbaaziz@gmail.com mailto:mail@quoniam.info https://ojs.hh.se/ 44 o p i n i o n s e c t i o n 1. introduction since 1988, algeria has initiated deeper economic reforms guided by two famous international agreements: signature on december 2001, the association agreement with the european union, effective since september 2005; (1) application for membership to the wto introduced on june 1987, considered by the algerian government as "a sovereign choice and necessity". (2) negotiations are still ongoing in 2014. these reforms are supported by a significant legislation. the most important are (3) : law 90-10 of april 14, 1990 on the money and credit, amended by ordinance 03-11 of august 26, 2003 on money and credit; the investment code promulgated on october 13, 1993, completed by ordinance 01-03 of august 20, 2001 on the development of investment and amended by ordinance no. 0608 of 15 july 2006; ordinance 01-04 of august 20, 2001 on the organization, management and privatization of state-owned enterprises; law 10-05 of august 15, 2010 on the competition, amending and completing ordinance 03-03 of july 19, 2003 and law 0812 of june 25, 2008; law 13-01 of february 20, 2013 on the hydrocarbons, amending law 05-07 of april 28, 2005 and ordinance 06-10 of july 29, 2006; various finance laws until 2014. it has resulted in an open economic market affecting almost all sectors in favor of new private and foreign entrants. this opening has not spared even some sectors considered strategic and largely protected until the end of the 1990s, such as mining and energy (baaziz, 2004). ( 1 ) official website of european union, «ue, instrument européen de voisinage et de partenariat – algérie document de stratégie», 2007-2013, available at: http://ec.europa.eu/external_relations/algeria/index _en.htm ( 2 ) official website of ministry of foreign affairs. available at: http://www.mae.dz ( 3 ) official wesite of ministry of industry, pme and promotion of investments. available at: http://www.mipmepi.gov.dz among the first effects of these reforms, we’ve observe deeper changes in the algerian economic landscape, including (baaziz, 2004): reorganization of state-owner’s firms called “economic public enterprises” to “corporations enterprises” or “limited liability companies”; bankruptcy or privatization of hundreds of state-owned enterprises (4) ; set up of many partnerships (such as joint venture, merger, acquisition, association and interest group) with foreign firms in various sectors such as consumer electronics, chemical and pharmaceutical industry and even the energy sector; market/customer orientation and new marketing practices. inapt to follow quick changes and uncertainty of the new environments, algerian state-owned firms are strongly shaken by deregulation of their market usually protected and acquired (baaziz, 2012). they find themselves in an aggressive competitive environment occupied by new emergent entrants. the algerian government has abandoned its protector role without providing a required regulatory role. in fact, the transition from a planned economy based on state monopole on all economics sectors to a market economy based on free competition and characterized by the emergence of local and foreign private sector implies radical changes both politically and institutionally (regarding algerian state) on the organizational, strategic and technological plans for state-owned firms. the classic business model within which the algerian state-owned firms was not confronted to market adaptation needs. the management approach was purely rules-based forecasting, planning and rationalization of tasks without unduly concern with the market itself. henri fayol in the 1920’s, described the five principles of this style of management still relevant in almost all algerian state-owned firms delaying the leap of change: planning, organizing, commanding, coordinating, controlling (fernandez, 2008). ( 4 ) official wesite of ministry of industry, pme and promotion of investments. available: http://www.mipmepi.gov.dz http://ec.europa.eu/external_relations/algeria/index_en.htm http://ec.europa.eu/external_relations/algeria/index_en.htm http://www.mae.dz/ http://www.mipmepi.gov.dz/ http://www.mipmepi.gov.dz/ 45 o p i n i o n s e c t i o n 2. method what organizational and technological leverages will grasp algerian state-owned firms to deal with the uncertainties of this new competitive environment? it is obvious that in such uncertain competitive environment, the algerian stateowned firm cannot rely only on its internal capabilities. it must look out of the box, create partnerships, both with suppliers, contractors, universities and even competitors (couture, 2000). on the organizational level, it is necessary to find new forms of organization that are more flexible, resilient and able to promote innovation and hold strategic positioning in such environments (baaziz & quoniam, 2013). on the technological level, a strategic alignment of an information system is needed and will be able to (baaziz, 2012): federate internally, its knowledge and critical skills; scan the environment in order to detect any positive signals to grasp desired strategic positioning; facilitate decision making and reduce its risks under uncertainty. hence the need for these firms to: transform its current organization to a new form of proactive organization improved for unexpected events and resilient enough to adapt to uncertain environments. build a strategic intelligence information system (siis), able to facilitate decisionmaking and reduce risks inherent to the strategic choices (baaziz, 2012). find ways to make the reversible choices if occur unexpected events (ao2008, 2012). 3. what are the risks linked to such changes? the risks are closely linked to three (03) sources of uncertainty: (i) environment; (ii) information and (iii) decision-maker. 3.1 risks linked to the environment: the major risk in the environment is "inertia" or resistance to fast and radical changes due to the transformation to the new form of organization (keen, 1981). 3.2 risks linked to information: the risk of information is a poor understanding and interpretation of signals received from the environment. 3.3 risks linked to the decision-maker: the risk to the decision-maker is poor reaction to signals and events in the environment. 4. literature review: environment and information. in the sixth century bc, sun tzu in "the art of war", describes how to recognize “a weak signal”. for him, an expert should be able to feel (touch, see, hear) what a common man cannot predict, so should be able to feel a weak signal. clausewitz (1832) raises the debate about the relationship between war and the economy. percepts of "military strategy". could be applied to the economic affairs (trade in particular) in this period. yet, it isn’t. it was only in the mid 1960s that it was used by alfred chandler in his book "strategy and structure" published in 1963, then in 1965 by igor ansoff, in his book "corporate strategy " (ducreux et al., 2009). we often attribute the authorship of "weak signals" to ansoff. however, as early as 1964, pierre massé, “ponts et chaussées” engineer, plan general commissioner of the french republic, in a famous prospective study “horizon 1985”, formulated the concept of " facts promising for the future". this fuzzy concept is paradoxical (because it can be verified only in the future) is considered one of the founders of prospective concepts. in 1967, massé finished his idea by saying that intuition and reasoning must be confirmed by the facts (rossel, 2012). although ansoff, who has borrowed the idea of weak signal from the theory of information, may be considered to have developed its own parallel approach mainly oriented towards business and management uncertainties, french futurists then treated essentially society and public policy questions (rossel, 2012). bright (1970) had already stated that companies undergoing an increasingly changing and turbulent environment. he was thus one of the first to talk about the importance of environment scanning and monitoring to anticipate technological changes that could give rise to opportunities and threats. he introduced at the same time new concepts such as "signs of change", "significant signal" and "early signals". 46 o p i n i o n s e c t i o n on the same assumptions of changing and turbulent environments, ansoff (1975) developed the concept of "weak signals" as an alternative to “the strategic planning” that in the 1970s and 1980s was a dominant future-oriented approach in firms and organizations. he declared that strategic planning is reasonable in the case of progressive development of historical trends, but it is not operative to deal with the unexpected or surprises. according ansoff (1975), strategic planning requires strong signals. the information available from the start must be sufficiently precise to enable appropriate responses (holopainena & toivonen, 2012). ansoff focuses on the responses of the company but also on the related statements of knowledge that is the result of external or internal interactions. according him, the best strategies are divided into three main options: those that improve awareness and understanding of the business, those that increase the flexibility of the company and those that allow the company to directly address threats or opportunities (rossel, 2012). porter (1985) introduced the concept of value chain (internal analysis of the firm with its strengths & weaknesses) and the concept of the five forces, that all affect the firm (external environment with its opportunities and threats). the combination of the two concepts provides strategic analysis leading to decisions. kaplan & norton (1992) by formalizing the balanced scorecard (bsc) concept through four perspectives (financial, customer, internal processes and growth), built a chain of causes and effects leading to the strategic success of an organization. it based on four assumptions, the first being: "innovation of creative people is the only insured source of long-term strategic success and every other aspect of the organization can be replicated by others". we understand that it is the knowledge held by the firm. cook & cook (2000) and hameed (2004) tried to explain similarities and differences between knowledge management (km) and business intelligence (bi). according to pesqueux (2004), km is an area that cannot extend beyond the firm’s boundary. as soon as we are interested in what happens outside, we move to another area than competitive intelligence (ci). in the strict sense, km is the process of internal knowledge creation (knowledge, skills, best practices, etc.), which is not the knowledge obtained from outside, via the internet, for example. it is rather the "environment scanning”. in this case, ci becomes a requirement for capturing and analyzing signals from the external environment and to deal with its threats and grasp the best opportunities available to the firm. jakobiak (2006) tried to explain the link between knowledge management and competitive intelligence and the contribution of km to support ci and its development. according to (jakobiak, 2006), km is not a main goal but a simple mean. the assessment of the links between ci and km provides a large overview of km techniques grant high interest for ci specialists. bretonès & said (2006) attempted to analyze the difference and complementarities between two important areas of research: ci and km, proposing an understanding framework of links between these two areas. goria (2006) described the merger, similarities and complementarities between km and ci domains. the same concerns were raised by (blondel et al. 2006). liebowitz (2006) introduced a concept of strategic intelligence (si). he defines it as the aggregation of other types of intelligentsia able to providing valueadded information and knowledge toward making organizational strategic decisions. the emphasis is on how best to position the firm to deal with future challenges and opportunities to maximize the firm’s success. he noted that the si forms the outer layer of the "onion", with the inside layers being artificial intelligence (ai), knowledge management (km), business intelligence (bi) and competitive intelligence (ci). 5. risks and uncertainties. knight (1921) suggests in "risk, uncertainty and profit", the distinction between risk and uncertainty. by expanding the scope of analysis to the general attitude of the actor facing these two concepts, without limited to economic aspects, then we can distinguish three situations: 1. certainty: each action is known to lead to certainly, to a specific outcome. 2. risks: every action leads to a specific set of possible outcomes and each outcome occurring with a known probability. 3. uncertainty: the actions may lead to a set of consequences, but where the probabilities of these outcomes are completely unknown. a risky situation where the outcome is unknown to the decision-maker who do not know what 47 o p i n i o n s e c t i o n the result will be. this uncertainty can lead to bad choices. for march & shapira (1987), decision making and risk are closely dependent on the context. it is therefore important to look at the context of the decision. a lot of research on attitudes to risk has informed our understanding of how individuals act to manage risk situations (baird & thomas, 1985) (maccrimmon & wehrung, 1986) (march & shapira, 1987) and (wehrung & al. 1989). for pablo & al. (1996), once the risky decision is made, the decision maker is likely to focus on how to achieve the best possible result when attempting to take more risks as favorable as possible, inherent in the selected target. this proposal is consistent with organizational research that argues that when firms are against a hostile environment, they act to improve and manage their environment (pfeffer & salancik, 1978). according to riabacke (2006), with the exception of studies by (maccrimmon & wehrung, 1986) and (shapira, 1995), empirical research has not enough focused on the conceptions of risk and risktaking held by managers. indeed, until now, no study has investigated the manager’s risk attitudes in parallel to their actual behavior when handling risky prospects. the area remains relatively open for new research. for riabacke (2006), managers often overlook the normative rules of decision-making in risky situations. they often rely on intuition that seems correct. they justify their inability to handle many situations at risk due to lack of information while affirming their fear of making poor decisions. the majority of managers insist that there are a lot of unwritten rules built into the culture that guide them when making decisions. using computerbased decision support could be one way to avoid these practices. weick & sutcliffe (2007) defined five principles for firms to deal with unexpected events and phenomena: 1. preoccupation with failure: small failure’s hunting is the responsibility of all actors in the firm. any deviation must be reported as a potential risk. 2. reluctance to simplify: everyone must resist to the temptation to simplify. 3. sensitivity to operations: all levels of the firm must be concerned with its activities and operations. 4. commitment to resilience: everyone must ensure the resilience of the system so that operations can continue. being able to learn from unexpected events to improve the ability to prevent, reduce or even contain future mistakes. 5. deference to expertise: the decision making process must be fluid, able to reconstruct different situations. the expertise prevails over hierarchical rank. 6. organizational transformation... the need to make decisions against uncertainty and randomness is a recurring source of risks that can push the firm to cooperate with others. risk management plays a key role in many strategic decisions (march & shapira, 1987). most managers spend nearly half their time in planning activities related. but in a complex and changing environment, planning is necessary but not sufficient (weick & sutcliffe, 2007). we agree the assumption that the alleged strength of organizations is not so obvious (weick, 2009) and that focusing on the lack of information to decide, managers try to take advantage of uncertain situations. in this perspective, uncertainty and risk are not necessarily a negative impact on firms. they can also create opportunities (weick, 2009). thus organizations should be proactive towards their environment, rather than reactive (weick, 2009). this shift (“mutation” or “transformation”) to a new form of resilient organization is needed to deal with the uncertain environment and support the strategic alignment of its information system (baaziz, 2012). political, socio-technical and economic aspects are crucial to overcome inertia and begin a transformation process (besson & rowe, 2011). transformation process should be achieved through several distinct phases (besson & rowe, 2011). it should be gradual and scalable (keen, 1981) that firms are very hierarchical, so that they can drive change and overcome the "inertia" inherent in this type of transformation (besson & rowe, 2011). a strategy of change management must be associated to the transformation in order to reduce risks and uncertainties of the mutation’s phases (besson & rowe, 2011). 48 o p i n i o n s e c t i o n 6.1 uncertainty in the decision making process decision is a set of processes to select an option among several alternatives. the decision-maker makes his choice by comparing the expected consequences of different options. the uncertainty in a competitive environment can come from three different sources: (i) environment: context of the environment; (ii) information: information captured from the environment; and (iii) decision-maker: interpretation of information captured from the environment. 6.2 environment uncertainties uncertainties linked to the environment are variables of environment where the decision is made. the uncertainty factors are either internal or external to the firm. 6.2.1 internal factors : these are internal factors that influence the decision and act both on upstream and downstream of the decision-making process (ao2008, 2011): information management: collection, storage, archiving and inefficient management of information are some probable factors that might disrupt the flow and sharing of the information within a firm. indeed, few algerian state-owned firms are not yet equipped with an electronic document management (edm) for the effective management of their important records and documents (baaziz & quoniam, 2013). hierarchical factors: main characteristic of the hierarchical organization that may have a big impact on the decision readability (baumard, 1997). majors proxy manager in algerian state-owned firms, don’t know the extent of their delegated powers of decision. to avoid any legal liability resulting from decision making, most of these managers turn to their superiors at the first difficulty they encounter. in this case, the instructions returned by the superiors are usually verbal thereby complicating decision-making process and finally, the legal responsibility falls on the proxy manager. 6.2.2 external factors: these are external contextual factors that may influence the firm's decision and the future of the firm (baaziz, 2012; ao2008, 2011): shareholder pressure: the corporate management is accountable to its shareholders. this pressure is higher when the exclusive shareholder (the owner) is the state as in case of algerian state-owned firms. power of political lobby: the political cooptation around a power lobby (group effect) implies the main manager’s profile is not the managerial competencies but simply that allegiance to the political group is the necessary condition for access to managerial positions in state-owned firms. therefore, these managers don’t have skills and attitudes of decision-makers; they systematically refer to the goodwill of the political lobby. this group effect is in fact a behavior pattern of a person bound to the status requirements and the group’s expectations. political affiliation is often preferred over the sense of belonging to the firm. pressure of social partner (syndicate): the weight of the social partners is more important in social and professional conflicts in the stateowned firms than in the private sector. in fact, the syndicates are deeply entrenched in the algerian state-owned firm and have a direct impact on major decisions. the pressures are generally focused on salary increases for sonatrach in the second half of 2011 (5) , and algerie telecom in december 2012 (6) , opposition to the privatization of stateowned firms and their consequences such as layoff plans result of the strike of workers following the acquisition of all shares of the engi by the german giant of industrial gas linde in july 2011 (7) . ( 5 ) el-watan, newspaper of june 09th, 2011, sonatrach : malaise sur les salaires, available: http://www.elwatan.com/economie/sonatrachmalaise-sur-les-salaires-06-09-2011138723_111.php ( 6 ) liberté, newspaper of december 13th, 2012, conflit algérie télécom, un conseil syndical prévu avant la fin décembre, available: http://www.algerie360.com/algerie/conflit-algerietelecom-un-conseil-syndical-prevu-avant-la-findecembre/ ( 7 ) le quotidien d'oran, newspaper july 9th, 2011, grève des travailleurs de linde gas algérie: les hôpitaux risquent de manquer d'oxygène. available: http://www.lequotidienoran.com/index.php?news=5155366 http://www.elwatan.com/economie/sonatrach-malaise-sur-les-salaires-06-09-2011-138723_111.php http://www.elwatan.com/economie/sonatrach-malaise-sur-les-salaires-06-09-2011-138723_111.php http://www.elwatan.com/economie/sonatrach-malaise-sur-les-salaires-06-09-2011-138723_111.php http://www.algerie360.com/algerie/conflit-algerie-telecom-un-conseil-syndical-prevu-avant-la-fin-decembre/ http://www.algerie360.com/algerie/conflit-algerie-telecom-un-conseil-syndical-prevu-avant-la-fin-decembre/ http://www.algerie360.com/algerie/conflit-algerie-telecom-un-conseil-syndical-prevu-avant-la-fin-decembre/ http://www.lequotidien-oran.com/index.php?news=5155366 http://www.lequotidien-oran.com/index.php?news=5155366 49 o p i n i o n s e c t i o n to curb a social climate in effervescence, managers tend to "calm the game", temper their actions and freeze critical decisions. anyway, in case of deterioration of the social climate (strike threat by the unions "social partner", for example), their hierarchies prefer sacrificing them in order to maintain a precarious equilibrium of social peace. given this state, managers prefer a status quo leading to inertia. threat of merger and acquisition / privatization: the potential grouping between two firms makes them unstable. this instability is most severe for state-owned firms planned for privatization under the ordinance 01-04 of august 20, 2001 related to the organization, management and privatization of “public economic enterprises” (baaziz & quoniam, 2013). a total of 417 state-owned firms were privatized between 2003 and 2007. (8) market trends: the pressure of new competitive environment brings much new information unexpected and incomprehensible. while a number of programs are in place to develop the non-petroleum economy, algeria remains heavily dependent on oil and gas exports, which represent 97% of total exports and roughly 30% of gdp. this dependency remains a real barrier to build a sustainable development. according oxford business group report about algeria: in recent years, stagnating investor interest has raised concerns about algeria’s ability to sustain current production levels, as a number of maturing fields will need to be replaced by new projects in the near term. following a number of lackluster bidding rounds over the past four years, the government launched a review of hydrocarbons law with the view to make the sector more attractive to foreign investors. (9) laws & regulations’ changes: unlike the national and foreign private firms that appeal to the international law firms, the algerian state-owned firms overlook the contents of the algerian legal arsenal in the continuing changes. (baaziz & quoniam, 2013). for ( 8 ) official wesite of ministry of industry, pme and promotion of investments. available: http://www.mipmepi.gov.dz ( 9 ) oxford business group, algérie: bilan de l’année 2012, january 16 th , 2013, available : http://www.oxfordbusinessgroup.com/economic_u pdates/algérie-bilan-de-l’année-2012 example, the hydrocarbon law was amended twice in less than ten years, the first occurred one year after the promulgation of the law. each year, the promulgation of the finance act is systematically followed by a substantial and significant revision. thus, the supplementary budget law "lfc 2009" was marked by the adoption of the letter of credit as the only mode of payment for foreign trade transactions, with an immediate effective date. this has caused serious disruptions in the supply chain and production of algerian firms. (10) criminalization of the wrong management act: long as the subject was taboo. decision leading to “bad business results” is not just a “wrong management act" but may be considered as an "economic crime" in light of the algerian laws. therefore, no range for error due to the undertaken risk is given to managers who prefer the status quo to make a decision that dragged him to court or even jail. the algerian president abdelaziz bouteflika has instructed the government to prepare appropriate legislation to decriminalize the management act. (11) the decriminalization of the management act will end the confusion that makes victims among executive’s managers. examples are numerous, we only mention: criminal trial of sider executive’s managers’ in 1997, cnan case in 2006, sonatrach case between 2010 to 2013, etc. for master zahouane (lawyer and human rights activist): “we should clear up the confusion between the management act which is the administrative responsibility and criminal act which is the penal responsibility (...) the penalty for the management error must be disciplinal not penal (…) releasing the management act without being assimilate that to impunity”. (12) legal context and partnership: the projects ( 10 ) le quotidien d’oran, newpaper of october 1st, 2009, pr. mebtoul a. (interview with.), situation du secteur financier algérien et problème du crédit documentaire (credoc). available: http://www.lequotidienoran.com/index.php?news=5127150 ( 11 ) el-moudjahid, newspaper of february 02 nd , 2011, selon des avocats : la dépénalisation de l’acte de gestion mettra fin à la “confusion” et libérera l’acte d’entreprendre. avalaible : http://www.elmoudjahid.com/fr/actualites/9007 ( 12 ) el-moudjahid, newspaper of february 02 nd , 2011, op-cited. http://www.mipmepi.gov.dz/ http://www.oxfordbusinessgroup.com/economic_updates/algérie-bilan-de-l'année-2012 http://www.oxfordbusinessgroup.com/economic_updates/algérie-bilan-de-l'année-2012 http://www.lequotidien-oran.com/index.php?news=5127150 http://www.lequotidien-oran.com/index.php?news=5127150 http://www.elmoudjahid.com/fr/actualites/9007 50 o p i n i o n s e c t i o n developed in partnership with several firms and the contracts concluded between them are liable to influence decisions or to hide information. the conflict between sonatrach and its partners anadarko and maersk is an edifying example this situation. the difficulty of interpreting the regulation on exceptional profits taxes (tpe regulation), forced sonatrach to pay compensation up to $ 4.4 billion for anadarko and $ 920 million for mearsk. (13) nasreddine lezzar (arbitration expert), says: “sonatrach erred on two levels; the first being of retiring on the aventine while the second evoked the choice to allocate the defense of the national company to an u.s. law cabinet (..) sonatrach, the algerian state company, was advised, in this case the volume of an affair of state, by an u.s. law cabinet, against an american company the size of a state. i would not presume to question the professionalism of the concerned cabinet, but at this level of interest, we must not allow the shadow of doubt”. (14) 6.3 information uncertainties uncertainties linked to the information are proprieties of this information in an environmental context where the decision is made (zio & pedroni, 2012; ao2008, 2011; zimmermann, 2000; armacosta & pet-edwards, 1999 and baumard, 1997): no information: lack of information. incompleteness: partial information due to the incapability to obtain certain information or to a problem at the time of knowledge capitation or to the existence of general information usually true but subjected to exceptions that we ( 13 ) el watan, newpaper of march 12th, 2012, roumadi m., fin du différend avec anadarko et maersk l’algérie paye cher la gestion opaque de sonatrach, available: http://www.elwatan.com/actualite/l-algerie-payecher-la-gestion-opaque-de-sonatrach-12-03-2012162499_109.php & http://lequotidienalgerie.org/2012/03/12/lalgeriepaye-cher-la-gestion-opaque-de-sonatrach/ ( 14 ) el watan, newspaper of june 29th, 2013, elles cumulent les procès à l’international, nos entreprises sont mal gouvernées juridiquement, available: http://www.elwatan.com/actualite/nosentreprises-sont-mal-gouvernees-juridiquement-2906-2013-219240_109.php & http://www.djazairess.com/fr/elwatan/419240 cannot enumerate or predict (bouchonmeunier, 1990). centralization: excessive centralization of strategic information (baumard, 1997). it is a common practice in algerian state-owned firms where many documents have confidential status. the information is not simply an intellectual product but a political instrument for lobbies. the replay through the information systems affects the interests of particular influential groups. significance: the information is only a tiny part of the decision-making process in the firm (keen, 1981). ambiguity: all languages have words that have different meanings depending on the context. this linguistic imprecision causes multiple conflicting interpretations, hence confusion and lack of understanding (thiry, 2002). subjectivity: this may be due to the subjective interpretation of little bits of available information. depending on their skills and cultures, different analysts may provide different interpretations or even contradictory to the same information. this source of uncertainty can be reduced by soliciting multiple views of different experts. contradiction: availability of abundant and conflicting information. multidisciplinary: information that affects both several areas, causing understanding difficulties. volatility: the propensity to variability of value over time. measurement error or bad estimation: measuring a quantity is always affected by the uncertainty due to the imprecision of the person taking the measurement or by the tolerance of the used instrument. 6.4 decision-maker uncertainties decision-maker may be a person or a group. each person reacts differently. the individual generators of uncertainty are not limited to his personality. their experiences, knowledge and skills also play an important role (baaziz, 2012). individual generators are either psychological properties of the person, a lack of skills or low experience that creates uncertainty (ao2008, 2011): doubt: state of mind which wonders in a kind of questioning. hesitation: lack of insurance and / or firmness. skepticism: state of mind of a person brings http://www.elwatan.com/actualite/l-algerie-paye-cher-la-gestion-opaque-de-sonatrach-12-03-2012-162499_109.php http://www.elwatan.com/actualite/l-algerie-paye-cher-la-gestion-opaque-de-sonatrach-12-03-2012-162499_109.php http://www.elwatan.com/actualite/l-algerie-paye-cher-la-gestion-opaque-de-sonatrach-12-03-2012-162499_109.php http://lequotidienalgerie.org/2012/03/12/lalgerie-paye-cher-la-gestion-opaque-de-sonatrach/ http://lequotidienalgerie.org/2012/03/12/lalgerie-paye-cher-la-gestion-opaque-de-sonatrach/ http://www.elwatan.com/actualite/nos-entreprises-sont-mal-gouvernees-juridiquement-29-06-2013-219240_109.php http://www.elwatan.com/actualite/nos-entreprises-sont-mal-gouvernees-juridiquement-29-06-2013-219240_109.php http://www.elwatan.com/actualite/nos-entreprises-sont-mal-gouvernees-juridiquement-29-06-2013-219240_109.php http://www.djazairess.com/fr/elwatan/419240 51 o p i n i o n s e c t i o n disbelief or distrust to opinions and received values. irresolution: personality trait of an incapable person to make decision whatever the context. indecision: mental state of a person who has difficulty with self-determination. pessimism: state of mind of a person who persists to see only the bad side of things, to find everything is or will go wrong. risk aversion: excessive afraid of risk whose result is an excessive distrust that paralyzes decision. thus, risk-taking is seen as a threat. regretfully: tendency to undermine the decision just taken by preferring an afterthought the not chosen option into the decision. lack of self-confidence: lack of assurance that one can have in one’s own resources or destination. other individual factors such as perception, reasoning mode, preferences, beliefs, convictions and emotions can amplify uncertainty. but we distinguish them of the cited generators because they play a dual role as they are both able to increase or decrease uncertainty. when the person is part of a group, it is in relation with the other members. interactions and exchanges alter his behavior and give him/her more or less knowledge or doubt and impacting the position that results the uncertainty making (ao2008, 2011): contradictory debates: the confrontation between divergent views. influences of expertise: the influence of expert opinion. subordinate relationship between persons: influence of a hierarchical superior on the views of its collaborators (baumard, 1997). this is common in the very hierarchical firms such as state-owned firms. cultural differences: existence of sub-groups with different visions of the firm’s strategy. group effects: behavior pattern of a person related to the needs of the status and expectations of his group (baumard, 1997). often ideological or political affiliation is prioritized over the sense of belonging to the firm. 7. reduce the risk linked to the uncertainty of the competitive environment in fact, the environmental parameters generate signals that directly affect the firm and therefore the manager who picks up an environmental signal, reconstructs an image of this signal (with information’s distortion) according to his/her own understanding (experiences, skills) and brings its own interpretation (behavioral psychology) and reacts to its own interpretation of the signal. the explained uncertainties can guide the knowledge production process. indeed, when they are explained, uncertainty is an impressive resource for decision-makers who are in a situation to reduce them without completely eliminate. there is probably a degree of uncertainty beyond which decision-makers becomes powerless and expose himself excessively to their management or their mandatory. the main actions allowing to manage uncertainty in order to reduce its risks (ao2008, 2011) are: correctly describe the unknown areas by establishing a new form of flexible organization, better prepared for unexpected events, enough resilient to adapt to uncertain environments. further investigate some of the unknown but plausible phenomena before making irreversible choices. it comes to organize trials upstream of decisive choices and avoid incurring their downstream effects. for this, there should be implemented a strategic intelligence information system (siis) able to maintain a permanent state of the environment scanning and monitoring to identify signals announcing unexpected effects (baaziz & quoniam, 2013). find ways to make reversible choices that can interfere with the lesser known areas and provide the means to return to these choices, if there are unexpected effects. 8. of the transformation to a new form of organization to deal with uncertainty so dare to take the risk of transforming the organization towards models enabling enough proactivity, such as the “extended enterprise” model. the major risk would be an inertia which is a kind of resistance to fast and radical changes resulting from the transformation (keen, 1981). we identify several sources of inertia (besson & rowe, 2011): psychological inertia related to the preference of the status quo; 52 o p i n i o n s e c t i o n cognitive inertia related to patterns of interpretation of the actors, resulting from their past experiences; sociotechnical inertia related to the coherence and interdependence of technical systems between them of the one part, technical systems and skills to run them, on the other part; political inertia related to the sharing of authority, the governance form and the alliances; economic inertia related to the required investments and the existence of sunk costs. for the firm, the political, socio-technical and economic aspects are crucial to overcome inertia and begin the process of transformation (besson & rowe, 2011). indeed, decision-makers must be willing to accept the declination and sharing power. this is a major policy decision sine qua non condition for initiating the process of transformation towards a new form of resilient organization. the transformation process must inevitably pass through four distinct, gradual and scalable phases (besson & rowe, 2011): 1. phase of uprooting that allows them out of the old organization; 2. phase exploration / construction of the new organization; 3. phase stabilization / institutionalization of the new organization; 4. phase optimization / routinization. a strategy for driving the transformation helps to reduce risks and uncertainties associated with the phases of the process (besson & rowe, 2011). 9. of the need to rebuild a strategic intelligence information system to deal with uncertainty 9.1 strategic intelligence information system in such competitive environment, it is necessary to provide a tool for management of resilient ownedstate firms, allowing the conception and monitoring the strategies with an improved visibility for piloting their activities according to their abilities "intramural" and "extramural" considering the influence of signals sensed in the environment where they operate. hence the need to implement an information system strategic intelligence, able to (baaziz & quoniam, 2013): federate their knowledge and critical skills; ensure the rapprochement with firms that may have conjugated interests and complementary skills; organize and prepare internal and external information for improved visibility and decision-making; facilitate the exploitation of external knowledge bases such as patent databases in order to find practical alternatives of development coupled with a creative vision "out of the box" (quoniam, 2013); scan external environment to detect the favorable signals for its positioning; facilitates decision making and reduce risks due to uncertainties inherent in its strategic choices. the strategic intelligence information system cannot create a synergy for decision-makers, only if it is able to create this synergy between the own knowledge and critical skills of the firm (knowledge management), the ability to decrypt signals and changes in the environment where the firm operates (through a competitive intelligence system) in order to claim to relevant decisions in a timely manner (by using the decision support tools known as business intelligence). here, the concepts of knowledge management (km), competitive intelligence (ci) and business intelligence (bi) operate at different levels of management: from strategic to operational (baaziz, 2012). 9.2 the empirical model of "synergy of the triptych" the decision cannot be relevant only if it is taken in a context of intelligent learning organization where both internal km and external ci information are available, up to date, analyzed and contextualized enabling the synergy of the triptych: km, ci and bi. the decision support system (bi) can be based on the outcome of km and ci in order to constitute hypotheses, analysis of alternatives for helping to lead the decision. the decision (outcome / output) becomes a component of organizational learning and enrich the knowledge base of the firm (based case study / input) (baaziz, 2012). we propose an empirical model of decision making, as follows: 53 o p i n i o n s e c t i o n this process is apparently simple but in fact more complicated: 1. first, relative to the prerequisites for this process, with the following assumptions: an environment conducive to a learning organization where the asset "knowledge" should be the focus of managerial concerns (pesqueux, 2004), in order to get a return on investment visible operated on intangible assets. a firm knowledge should be managed as a single focal point, control of knowledge and skills. 2. then, there is the operation of other complex production processes of managerial knowledge: quest for information, interpretation and learning. we could say that with organizational knowledge, one is facing the production of organizational routines, hence the importance of the modification of routines to generate new knowledge. this transformation of knowledge obtained from external information that becomes an internal knowledge as a result of learning and ownership. (pesqueux, 2005) 3. the third hypothesis is the "non-linearity" of this process due to the uncertainty listed, mainly the "decision-maker" which is an integral part of this process (baaziz, 2012). indeed, it is obvious that with the same environmental deals, the same informational database and the same decision-making tools, it is unlikely that two people with different experiences can produce convergent decisions. each person reacts differently. its culture, experiences, knowledge and skills also play an important role (baaziz, 2012). the individual generators are either psychological properties of the person, or a lack of skills or experience that creates uncertainty (ao2008, 2011). so, it is important to involve the human dimension, see psychological aspect of the decision-maker who constitutes the catalyst of the desired synergy. 4. the traceability of decisions’ actions is granted by the strategic intelligence information system (siis). hence the possibility of reviewing the success factors or failures by checking the knowledge base describing the cases: subject, context, environment description, profiles of the decision-makers, taken decisions and actions, etc. 9.3 towards the integration of triptych km, ci & bi customer satisfaction through innovation, efficiency and performance of business processes requires upgrading the actors’ skills, hence the need to use a km system for the knowledge capitalization of the firm. indeed, knowledge is a combination of information (or observations) and their interpretations by persons who, based on their beliefs, thought patterns, theories and personal or collective experiences, make sense of this information (prax, 2000). km and ci are two activities that allow firms to be innovative, efficient and competitive by monitoring the one part, the external environment to decrypt weak signals, in order to go faster than its competitors and on the other, by following and monitoring internal changes they must operate in order to adapt, grow and innovate (jakobiak, 2006; goria, 2006). the goal of both is taking relevant decisions in a given context in order to grasp an opportunity or avoid a threat (baaziz, 2012). in front of the environmental and organizational constraints of enterprises and the strong similarity of used tools of competitive intelligence and knowledge management, we cannot practically be in one of the domains without practicing the other. 54 o p i n i o n s e c t i o n the strong similarities characterizing km and ci tools lead us to combine efforts to set up for an improved synergy. we quote (goria, 2006): building networks and communities of practice, guidance of the firm toward a learning organization, a logic-oriented innovation by building a sustainable competitive advantage, strategic management of skills and human resources, management of intangible assets (including those of its partners) implication of the top management for the success of km or ci project. common it infrastructure (servers, databases, web 2.0, etc.) in point of view of information technology, this similarity is extensible to decision support systems (bi) which link the results of the km and ci domains in order to constitute the assumptions, analysis of situations to lead to better decisionmaking. this is true if we consider that the ci as the “external” km (pesqueux, 2004), because: first, the tools, as well as terminology (web 2.0, mapping, search engine, information management tools , presentation, data warehousing, storage, statistics, correlation, data mining, big data, analytics, etc.) are reused in the context of km, ci and bi; a good command of the internal knowledge management depends on the external knowledge, especially for the km-oriented business skills and marketing (pesqueux, 2004); the focus towards the client has greatly intensified in recent years. (pesqueux, 2004). this is a significant economic asset as investments in infrastructure; applications’ platforms and a part of the study are common. then just develop for each domain, its specificities. the main contribution of this paper is the construction of the empirical model for the integration of the triptych km, ci and bi to create synergies needed for suitable decision-making in an uncertain competitive environment and also enrich the strategic knowledge base for organizational learning. this model is applicable to the overall strategic analysis as follows: fig.02. enhanced lcag model to triptych synergy model describing the strategic review process 55 o p i n i o n s e c t i o n conclusion in conclusion, the algerian state-owned firm must undergo deep changes at the organizational level by adopting a new form of organization resilient like "extended enterprise" in order to combine skills and resources to ensure a competitive advantage to local and foreign private firms whose "culture of networking and collaboration" is well anchored. it must rebuild its information system accordingly, extended to its partners in order to exploit existing synergies "intramural" and "extramural". this gives the firm, the ability to innovate and reach the needed objectives of competitive advantage in an uncertain environment. by using benchmarking tools and best practices with private and international firms operating in algeria (like cevital, henkel, sanofiaventis, etc..), the leaders among algerian state-owned firms such as sonatrach, sonelgaz and their respective subsidiaries, can demonstrate the efficiency of their process in continuous improvement following the transformation of the firm and the extension of their information systems by: better visibility of the political, economic, socio-cultural and technological environments in which they operate; mapping knowledge and skills of the firm but also those of their partners contributing to its extended value chain; mapping knowledge and skills of new key competitors in their main economic perimeter and / or geographical in order to achieve improved benchmarking; the easy identification of sensitive information "weak signals" and key skills for innovation, performance and competitive advantage; creating favorable conditions for innovation by extending the partner network and building communities of practice; anticipating customer requirements and alternative solutions to potential competitors. references ansoff, h. i. 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(2020) intelligent information extraction from scholarly document databases. journal of intelligence studies in business. 10 (2) 44-61. article url: https://ojs.hh.se/index.php/jisib/article/view/570 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index intelligent information extraction from scholarly document databases fernando vegas fernandeza* adepartamento de ingeniería civil: construcción, universidad politécnica de madrid, spain; *fvegas@ciccp.es journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 2,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10, no. 2, 2020 thinking methods as a lever to develop collective intelligence ursula teubert pp. 6-12 big data analytics and international market selection: an exploratory study jonathan calof and wilma viviers pp. 13-25 atman: intelligent information gap detection for learning organizations: first steps toward computational collective intelligence for decision making vincent grèzes, riccardo bonazzi and pp. 26-31 francesco maria cimmino on the relationship between competitive intelligence and innovation jonathan calof and nisha sewdass pp. 32-43 intelligent information extraction from scholarly document databases fernando vegas fernandez pp. 44-61 intelligent information extraction from scholarly document databases fernando vegas fernandeza* adepartamento de ingeniería civil: construcción, universidad politécnica de madrid, spain *corresponding author: fvegas@ciccp.es received 4 january 2020 accepted 5 may 2020 abstract extracting knowledge from big document databases has long been a challenge. most researchers do a literature review and manage their document databases with tools that just provide a bibliography and when retrieving information (a list of concepts and ideas), there is a severe lack of functionality. researchers do need to extract specific information from their scholarly document databases depending on their predefined breakdown structure. those databases usually contain a few hundred documents, information requirements are distinct in each research project, and technique algorithms are not always the answer. as most retrieving and information extraction algorithms require manual training, supervision, and tuning, it could be shorter and more efficient to do it by hand and dedicate time and effort to perform an effective semantic search list definition that is the key to obtain the desired results. a robust relative importance index definition is the final step to obtain a ranked importance concept list that will be helpful both to measure trends and to find a quick path to the most appropriate paper in each case. keywords business intelligence, concept map, information extraction, knowledge management, literature review, natural language process, nlp, semantic search 1. introduction according to the cambridge dictionary, knowledge is “understanding of or information about a subject that you get by experience or study, either known by one person or by people generally”. it could also be defined as “the state of knowing about or being familiar with something” or “the creation of information from structured or unstructured data” (upadhyay and fujii 2016). in other words, knowledge is the result of settling information. “the general purpose of knowledge discovery is to extract implicit, previously unknown, and potentially useful information from data” (matsuo and ishizuka 2004). information can be contained in a lot of documents available in several kinds of formats (mitra and chaudhuri 2000), as can be seen in figure 1. nowadays there is no distinction between electronic and printed formats given that any printed paper can be easily converted to an electronic format with scanning and ocr technologies that are commonplace. a large amount of available information on the internet has made it easier to reach a constantly increasing number of documents but it has caused the problem of finding the most relevant ones for the specific purpose that the user addresses. information retrieval (ir) has attracted scientists' attention since the 1960s (allan et al. 2002). allan uses salton’s definition in 1983 for ir: “information retrieval is a field concerned with the structure, analysis, organization, storage, searching, and retrieval of information”. recent publications define ir as “a system to identify a subset of journal of intelligence studies in business vol. 10, no. 2 (2020) pp. 44-61 open access: freely available at: https://ojs.hh.se/ 45 documents in a large text database or a library scenario a subset of resources in a library” (grishman 2019). an information extraction system identifies a subset of information within a document to extract relevant information from documents. information extraction (ie) should not be confused with the more mature technology of information retrieval (ir) (gaizauskas and wilks 1998). to sum it up, ir retrieves relevant documents from collections and ie extracts relevant information from documents. the relevance of extracted information is always related to the interests, goals, and specific information requirements of the researcher and, then, once it has been internally processed, information becomes knowledge. extracting knowledge from big databases and document databases has long been a challenge because of the large number of documents that make it hard to select the most relevant data. for that reason, a lot of retrieval algorithms have been developed (ahmad and ansari 2012; boden et al. 2012; karol and mangat 2013; koval and návrat 2012; wang et al. 2013) applying distinct sophisticated techniques: fuzzy, artificial neural network (ann), clustering, machine learning, and hybrids. there is a specific scenario where the challenge is not to find the right documents but to extract usable information from them: it is the literature review that every researcher faces when addresses a new research project (nasar et al. 2018). this is a case of unstructured typed text written information (see figure 1). in that situation, ir can be easily solved with the available search engines on the internet. however, it is much harder to extract and manage information because a very high accuracy is needed and information about many distinct concepts should be extracted from documents depending on the researcher’s requirements. in that scenario, knowledge management involves not just information about keywords, tags, and meta-data, but a structured and even quantitative structure of all the concepts that can be relevant for the researcher's objectives. the document database size that researchers use in each specific research project is very small, typically 30 to a few hundred documents, and this situation is far from big data scenarios. for that reason, most of the time and effort should be dedicated to clearly defining specific user information requirements before thinking of a better way to extract information. this article addresses the case of the literature review. researchers do a literature review, create a document database, and must manage that source of knowledge. there are several tools to manage that kind of document (e.g., endnote, mendeley, word), but they just provide a catalog management functionality, when it comes to extracting knowledge, there is a severe lack of functionality. this case is a “little brother” of the general problem of extracting information from pdf files, but the approach, methodology, and principles used in this case are the same as those used in bigger cases. however, the it tools required are much simpler. before searching for concepts in a document database (e.g., ideas, topics) it is necessary to perform a previous concept analysis to define the semantic framework that will be used later (lópez-robles et al. 2019; sarwar and allan 2019). sometimes this analysis can be easily performed because it merely consists of defining words to be found in the text (e.g., to achieve a list of possible risks) and other times figure 1 distinct information formats. 46 it is harder. this article proposes a simple and effective way to extracting information from research document databases depending on the researcher’s predefined breakdown structure, obtaining a ranked list of concepts and items to define priorities or to make decisions. these results are relevant for researchers and are an example of what companies could do to organize and use their stored information simply and effectively. 2. problem description researchers use literature review as a relevant part of their research studies to know the state of the art and to give a sound basis to the statements they include in their papers. each new research project leads to a new tailored document database creation with a few hundred documents that, although possibly partially overlapping with previously used databases, is a fully new one from which researchers will take references to include them in their new papers. in fact, they create a library that could be seen as their business intelligence document warehouse (tseng and chou 2006), because researchers do not use their document database just to cite previous works but also to extract knowledge from those documents. scholarly documents address a specific subject and give a conclusion. researches can read abstracts and even write a summary for each document. but there is much more information there, related to the main subject and related to marginal topics that might concern researchers, for which they might need to keep a record by annotating statements, methods, algorithms, author’s position about specific issues and techniques (rostami et al. 2015). to do that, researchers could think of a predefined information breakdown structure and a list of premises, concepts, ideas, issues, and techniques that they would like to confirm or refute with the database information. in the end, that’s knowledge (sirsat et al. 2014), and that sort of virtual list containing a reduced number of entries (typically 20 to 50) is itself a handy knowledge reference. researchers need tools to efficiently carry out that task, but they usually do it by hand or with the help of desktop cataloging tools such as endnote, mendeley, or word. a survey conducted in universidad politécnica de madrid with a selected group of ph.d. candidates and researchers confirmed this statement. sophisticated algorithms are not always the right answer to extract information and knowledge, and most researchers are not opened to them because they do not have enough time to try them. furthermore, most of the scholarly algorithms proposed require manual training, supervision, and tuning (sirsat et al. 2014; upadhyay and fujii 2016) and, in the end, it is faster and more efficient to do it by hand. researchers need to retrieve information from scholarly papers and transform it into knowledge. a possible way is to create a list of concepts or items that are representative of each document concerning what researchers are looking for in their research projects. that list of concepts can be weighted later on to achieve a ranked list of relevant concept elements with the overall reviewed literature. 3. objective this article addresses the literature review and the knowledge extraction that researchers carry out using scholarly document databases in their research projects and aims to give an affordable solution to improve that situation. scientific document databases are much more than a collection of papers that need to be managed and cataloged: a task that several commercial solutions can do. scientific document databases are a relevant source of information and researchers need to extract knowledge from them and rank results according to their relevance. 4. research method this study analyzes the state of the art in intelligence information extraction from scientific document databases. to do that, a systematic literature review and interviews with researchers at universidad politécnica de madrid were carried out. that way, requirements and available resources were identified. this study also takes advantage of my personal experience as a researcher and as a chief information officer in multinational companies. advances in linguistic structure definitions were studied in depth to try to find the most efficient way to analyze text and to use it for specified purposes. novelty proposed algorithms were considered to evaluate their adequacy for the objectives proposed. a previous author’s experience related to a competitive intelligence innovation project studied in 2015-2016 to predict risks in projects is a significant reference as to what actual technical solutions can provide and their 47 possibilities to satisfy the requirements proposed in this study. 5. literature review a systematic literature review was performed to know the state of the art related to intelligent information extraction following the searching method by bettany-saltikov (bettany-saltikov 2012; kasperiuniene and zydziunaite 2019; snyder 2019). a systematic search, unlike a narrative search that could yield a subset of haphazard and biased documents, achieves a neutral collection of documents to obtain an objective view of the state of the art. to carry out the information retrieval, the initial idea of using the string “intelligent information extraction” linked to scholarly and scientific documents was completely dismissed because it hardly gave any results; a search for the concept “intelligent information extraction from document databases” was performed in several sources (renault and agumba 2016; xia et al. 2018), with and without quotation marks and sometimes splitting that string into smaller fragments to achieve complementary results. as some sources retrieved more than 313,000 documents (e.g., google scholar), the first 400 hits were selected in each source, given that their search engines are supposed to show the most relevant results first. that outcome was filtered screening titles, keywords, and abstracts to rule out documents that did not meet the subject proposed and those that were unreachable. the results obtained prove that distinct sources do not always contain distinct databases; their search engines are different, and, for that reason, their first documents retrieved were distinct. it is possible to find in google scholar almost any document found in the other sources. however, by using distinct sources it is possible to get more results. the number of remaining documents, after filtering and deleting duplicated results, was 58. concepts such as natural language processing, semantics, and ontologies frequently appear in the documents reviewed. a linguistic approach to the ontology concept could be helpful to clarify its meaning with several distinct definitions (schalley 2019): “an explicit specification of a conceptualization”, “the study of the categories of things that exist or may exist in some domain”, and “catalog of the types of things that are assumed to exist in a domain of interest d from the perspective of a person who uses a language l for the purpose of talking about d”. some documents address only ir (allan et al. 2002; barde and bainwad 2018), others only address ie (lee 1998; saik et al. 2017), and most of them address both ie and ir. although ie and ir have been studied from the 1960s, there is a lack of scholarly documents addressing ie and ir from scientific publications: only 7 out of the 58 documents retrieved address them (esposito et al. 2005; marinai 2009; nasar et al. 2018; rodríguez et al. 2009; saik et al. 2017; upadhyay and fujii 2016; wang et al. 2013): esposito addresses a semantic-based tag extraction by using their system dominus, and they achieve accuracies from 93% up to 98% (esposito et al. 2005). however, those tags are title, author, abstract, and references, and nowadays it is easier to retrieve those tags with google scholar and tools such as endnote and mendeley. marinai aims to extract administrative meta-data from digital articles (marinai 2009). the paper uses the term “administrative metadata” to describe details such as title, authors, and publisher (named hereinafter “administrative tags” to avoid confusion). their outcome is, thus, a file card, the sort of data that tools such as endnote and mendeley can provide. nasar et al.’s article distinguishes metadata extraction and key-insights extraction and says that “the amount of time that is required to conduct a quality review can take up to 1 year” and that a “systematic literature review can take up to 186 weeks with single/multiple human resources”. in the survey, they talk about an average accuracy of 92% in retrieving meta-data when the document includes a report document page and 64% when it does not. when it comes to key-insight extraction, the precision is 42% and the recall is 52% (nasar et al. 2018). rodríguez et al. wrote in 2009 a promising article trying to classify software engineering publications with a three-step method using natural language processing (nlp), mainly focused on (but not limited to) html documents. no information is provided about their results, precision, and recall rates (rodríguez et al. 2009). saik et al.’s article addresses the agricultural biotechnology field to automatically extract medical and biological knowledge from the pubmed texts using semantic analysis and the relational database 48 mysql. they propose the use of an adapted version of their andsystem solution that “involved the creation of a subject domain ontology and semantic linguistic rules (templates) for analyzing natural language texts and extracting knowledge formalized according to a given ontology”. it requires “dictionaries of the objects” that must be first created using templates (saik et al. 2017). upadhyay and fujii propose “a practical sentence extraction procedure and supporting system which we intended to call knowledge extraction system” by applying rules to identify and extract keywords, discourse keywords, and sentences, but human expert support is required and no precision nor recall rates are provided (upadhyay and fujii 2016). wang et al. focus on information retrieval (document retrieval) based on word concepts and text clustering. they apply the cosine algorithm to classify documents (wang et al. 2013). natural language processing (nlp) is a constant reference in most publications (hassan and le 2020). sometimes their proposals ask for structured documents and, when not, they need to transform documents into structured data (dezsenyi et al. 2007; oro and ruffolo 2008). other times they need to convert the original pdf files into html and text format files to be able to proceed (hassan and baumgartner 2005a; rizvi et al. 2018; seng and lai 2010). the methods and algorithms proposed frequently require the involvement of experts and manual training and tuning of the system (chen and lynch 1992; koval and návrat 2012; lambrix and shahmehri 2000; sirsat et al. 2014; upadhyay and fujii 2016). the documents analyzed propose algorithmbased systems and agents with rules to query document databases, although it is common to find unsolved problems when there are heterogeneous data sources (seng and lai 2010). sometimes the solution proposed is just a query with boolean logic (lambrix and shahmehri 2000; lee 1998; rahman et al. 2017; sarwar and allan 2019) and other times they propose sophisticated techniques such as an artificial neural network (al-hroob et al. 2018; matos et al. 2010), machine learning (fan et al. 2015; hassan and le 2020; seedah and leite 2015), and artificial intelligence (ansari et al. 2016; gupta and gupta 2012; matsuo and ishizuka 2004), even though artificial intelligence is usually related to nlp (kim and chi 2019; lee 1998). some documents address information extraction from multimedia contents and files (srihari et al. 2000; wolf and jolion 2004). other works are intended for specific purposes such as biological knowledge extraction from biomedical web documents (hu et al. 2004), medical document summarization (afantenos et al. 2005), and software testing (lutsky 2000). some studies aim for “automatic keyword extraction” by considering cooccurrence and frequency to extract keywords (matsuo and ishizuka 2004), but do not consider the researcher’s interests. clustering and classifying techniques are often used, such as nearest neighbor classifier, bayes, and support vector machine (shrihari and desai 2015; song et al. 2007). attempts to intelligently split unstructured pdf files into segments have been made by using ontologies and queries to generate an xml output with understandable data, trying to simulate how human readers would analyze a page (hassan and baumgartner 2005b). that “human visual” approach has also been addressed by other authors trying to make text visual, although there is a generalized lack of references and there are strong limitations (nualartvilaplana et al. 2014). there are many proposals although sometimes they have not been fully tested (inui et al. 2008) and are just experimental proposals (fan et al. 2015; karthik et al. 2008; li et al. 2015; milward and thomas 2000; xie et al. 2019). the most frequent situation is that the systems proposed need human training, supervision, and tuning (fan et al. 2015; sirsat et al. 2014; upadhyay and fujii 2016), and even with that, the outcome is not always as good as desired, with poor precision and recall values (adrian et al. 2015; al-hroob et al. 2018; milward and thomas 2000). 6. proposed approach in this section, several relevant components of the whole problem are analyzed, creating a breakdown structure to address them separately. the typical path that researchers follow in their literature review process has several stages (xia et al. 2018). according to xia, there are three stages: stage 1 includes review planning and searching for relevant articles using electronic databases; stage 2 involves deleting all duplicates according to the title and author and excluding irrelevant papers by reading their titles, abstracts, and keywords; and stage 3 refers to content analysis. we 49 propose a more effective procedure with four stages (figure 2). 6.1 stage 1: planning and computer search in stage 1 an electronic search is performed using databases and search engines on the internet. to do that, a previous selection of databases is done considering the research subject, e.g., google scholar, web of sciences, scopus, or researchgate. some of those databases share documents: that means that they could have the same content, although the result of the search performed can be quite different because of their different search engines. it is relevant to notice that google scholar contains almost every reference included in the other databases, and stage 3 will take advantage of this fact to automatically obtain document tags. after having selected the desired databases, it is necessary to define the keywords and patterns that will be used with the search engines selected. as it is very easy to perform search operations, it is possible to use several keywords and patterns, with and without quotation marks and sometimes splitting search strings into smaller fragments to achieve complementary results. with each search operation, the outcome is a list of documents that match the query. when the number of results is too high it is necessary to refine the search by changing the keywords and patterns or to select just the desired number of results. those outcomes can be easily copied and pasted into a spreadsheet, proceso.igx s ta ge 1 p la nn in g an d co m pu te r s ea rc h s ta ge 2 fi lte rin g an d fil e re tri ev al s ta ge 3 fi le re ad in g an d ta gg in g s ta ge 4 in fo rm at io n ex tra ct io n steps outcome objectives definition search patterns & keywords t arget databases information retrieval outcome process document list document list filter duplicates final list download files document files final list document files t agging reading summarizinghighlighting reviewed files catalog catalog concept definition concept annotation relative importance index knowledge catalog figure 2 process stage description. 50 like excel, to transform them into easy to use reports. depending on each database, those lists could contain a variable number of identification fields such as title, authors, date, and even abstract and other tags (“administrative tags”). all that information can be used in stage 2 for filtering purposes. the feasibility, agility, and flexibility of modern search engines lead to dismissing, in general, any other possible sophisticated algorithm proposed in the ir literature. 6.2 stage 2: filtering and file retrieval in stage 2 a filtering operation is performed to refine the results obtained in the previous stage. excel filters are used to select or unselect document titles to exclude irrelevant documents. for instance, a possible exclusion rule could be to find in the title the words “image”, “video”, and “media”. additional available information, e.g., keywords, abstract, or other data, can be used to exclude, for instance, documents corresponding to patents: in this case, the filtering rule would be to find the word “patent” close to the title line. if necessary, documents can be downloaded to check their content and decide whether they fit the subject proposed. when the filtering operation is completed, duplicate results are detected according to the title and authors and then deleted. finally, the documents are downloaded, and all unreachable documents are excluded. the outcome of this stage is a final list of documents and a database with downloaded pdf files. 6.3 stage 3: file reading and tagging in stage 3, documents retrieved should be tagged and reviewed. meta-data in scientific documents is information commonly associated with administrative properties, such as author names, title, publication date, or journal (esposito et al. 2005; marinai 2009; tseng and chou 2006), and many researchers have tried to find ways to retrieve them automatically, even recently (nasar et al. 2018). however, tagging files is very easy now because it can be done using free tools. for this reason, other possible equivalently sophisticated algorithms proposed in the ir literature were dismissed for this purpose. the most direct way to do it is to look for the document title on google scholar and to export the reference obtained to mendeley, endnote, or another catalog tool (not all of them are free). both mendeley and endnote are desktop tools to catalog references and to allow researchers to include citation and a reference list properly formatted in their papers. with those tools it is also possible to edit tags and update them automatically. tags considered in this step are only administrative properties, not other content-related tags (lópez-robles et al. 2019; xie et al. 2019). all documents are read at this stage and researchers begin to achieve knowledge. according to xia, “the technique of content analysis is employed for compressing many words of text in an organized manner, identifying the focus of subject matter, and diagnosing emerging patterns in the current body of knowledge” (xia et al. 2018). the researchers interviewed in universidad politécnica de madrid had distinct ways and tools to carry out paper revision, but highlighting and summary elaboration are a constant for all of them. at this stage, the action proposed is a revision of the papers with highlighting of parts of the text using different colors and even writing a short summary (about 150 words) with keywords, tips, and short sentences. this summary is not an abstract summary, but a cue to help them to recall document content later on. 6.4 stage 4: knowledge extraction according to hobbs, “information extraction is the process of scanning text for information relevant to some interest” and “it requires deeper analysis than key word searches” (hobbs 2002). natural language process goes beyond the exact term-matching technique (rahman et al. 2017) and focuses on concepts, semantics, and relationships between terms to try to retrieve most of the original ideas expressed by document writers. it is a hard task for algorithms and programmers to handle entities, relationships, and events to process them automatically with a high level of both precision and recall, and they frequently require human-supervised help (grishman 2019). however, that task is the daily work of the human brain: every time a person reads a paper, they unconsciously create a mind map which connects the most relevant concepts with their interests to generate knowledge. that virtual mind map could be explicitly created by defining key concepts corresponding to the concepts identified after having analyzed the relevant syntagmas, ontologies, and keywords existing in the text studied (buzan 2004). the criteria to define those key concepts is not the frequency-based traditional model (fan et al. 2015; matsuo and ishizuka 2004), but a 51 tailored definition that researchers can make according to three factors (sirsat et al. 2014): 1) the overall contribution of the documents studied to the research project, with concepts that attract researcher’s attention because they appear in several documents of the database studied; 2) the researcher’s previous knowledge that makes them search for specific concepts to clarify authors’ position about them; and 3) the researcher’s experience, which helps them find concepts that could become relevant according to their perception. some authors call them “keywords” and “discourse words” (upadhyay and fujii 2016). this step affects the final outcome and is directly related to the research project purposes (see figure 3). the aim of defining those concepts is not to summarize documents but to summarize their contribution to the research project, making it possible to characterize documents as a sort of layout and schematic summary in the same line followed by some proposals for document image layout analysis (oliveira and viana 2017). according to this, several distinct possible concept types are shown in table 1. in this table, “type” refers to the way the concept is found in the text reviewed and how it is annotated. regarding the way to find them (“trigger”), there are two main possibilities: to be a word (or group of words) or to be a sentence. it is a word (or group of words) when their occurrence undoubtedly means a concept expression, e.g., “ann”, and it is a sentence when concepts are expressed in a more complex way so that no single word is enough to summarize those concepts. regarding the way concepts may appear (“variation”) they could be specific words and groups of words or an opened or closed name list. regarding the way concepts are “annotated” in each document, they can be registered just with an “x” mark (they meet the required keyword, idea, or condition) or they can be labeled with a descriptive list element or name. last, concepts can be numeric values; in that case, the value is annotated. to fully understand table 1 a detailed description of the types is included in table 2. researchers can define as many concepts as needed to cover each detail that is relevant for their research and that they will want to include in their papers. semantic analysis is an undeniable requirement to achieve a good annotation that is the basis of a key concept definition (malik et al. 2010). once the concept definition has been done, a new document review would be needed to identify them in all the documents and to annotate their occurrences. this operation becomes shorter than it could be thought by using desktop tools that make the use of complicated algorithms and programs unnecessary. there are free solutions, such as adobe reader and docfetcher. docfetcher creates and uses an internal index (the same table 1 concept types. type trigger variations annotation keyword word word, group of words “x” idea/opinion/statem ent sentence n.a. “x” position sentence n.a. list element use case sentence / table / figure list list element name sentence list name numeric sentence / table / figure n.a. value condition sentence list “x” figure 3 key concept definition. 52 table 2 type definition. type definition keyword applies to the undeniable meaning of a word and group of words in a specific context, e.g., information retrieval, cosine, query, machine learning, ontology, ann, or nlp. idea/opinion/statement applies to a conceptual meaning that could be expressed with distinct words and sentences, e.g., “need for improvement”, “knowledge extraction”, “lack of objectivity”, or “biases”. position applies to statements, case of use, and others where authors show whether they approve, reject, or just cite a particular subject, e.g., in regards to a specific technique, they “use or recommend”, they “criticize”, or they “cite”. use case applies to distinct options researchers might want to keep track of, such as kind of technology, type of chart, or type of scale. name applies to concepts that can be registered with their names, e.g., system, country, or activity. numeric applies to concepts that can be quantitatively measured so that it is possible to register their value, e.g., precision or recall. condition applies to specific conditions that document scope could accomplish to meet the researcher’s interests, e.g., specific industry or country, or specific field. way as adobe acrobat does) that allow users to perform quick boolean searches for any word and string in a document databases. for instance, to find whether documents indicate that further improvement is needed (an idea/opinion/statement type concept), it would be possible to look for “improve” and “limitation” and retrieve the texts “improving the performance of nlp-based tools” and “there are also practical limitations in rule generation …” (kim and chi 2019). however, the text “their sometimes low recall may be compensated by adjusting” (adrian et al. 2015) and “is prone to several limitations that, in turn, offer opportunities for future research” (li et al. 2015) would not be retrieved. this manual process is similar to li et al.’s, which consists of an automated method to retrieve meta-data (li et al. 2015). their process lexicon extraction and task identification method for process mining requires manual task annotation to train a statistical model and yields over 75 % classification accuracy, 70 % precision, and 95% recall. the method proposed here improves accuracy, precision, and recall up to 100%, and it is not more manually time-consuming than most of the automated methods proposed in the literature. to efficiently register those knowledge tags, the use of a spreadsheet is suggested. this practice allows for an additional feature: a quantitative measure of the relevance of each concept, i.e., the use of a relative importance index (rii). this idea can be found in many works (alashwal and al-sabahi 2018; jarkas and haupt 2015; nagalla et al. 2018) and for this research project, the solution proposed by vegas-fernández was used (vegas-fernández 2019; vegas-fernández and rodríguez lópez 2019). this method applies a weight to each document that considers the document type (standard or regulation, doctoral thesis, book, indexed journal, lecture source, unindexed journal, master thesis, a website run by a renowned organization, or a standard website). the date and their scope are also considered by adding +0.5 to documents after 2010 and by subtracting 0.5 when they are intended for a specific activity or a particular country. the final score is the weight assigned to each document, which is considered when the document matches a concept (regardless if the annotation is an “x”, a name, or a value). the rii is the ratio between the weighted count of documents matching a concept and the maximum value that that weighted count takes for a concept. the outcome at this stage is a ranked list of key concepts, which is a quantitative outcome of knowledge extraction. 7. knowledge extraction example using the proposed system 53 the process of knowledge extraction carried out for this study is explained next to make it easy to understand the scope, possibilities, and limits of the proposed system. each one of the distinct steps at each stage is described here with data that will allow readers to make their guess about this system. 7.1 stage 1: planning and computer search each researcher is used to searching in scholarly databases, and they choose them according to their preferences. their previous experience and their knowledge of previous publications related to their research project subject give them the required orientation to select the search strings and the best databases. searching documents in google scholar is a must, but the number of possible retrieved documents can be too high. in this case, the chosen search string was “intelligent information extraction from document databases” without quotation marks to be able to achieve results. that search yielded 313,000 results in google scholar, but that outcome was truncated to select just the first 400 most relevant titles. that systematic search process was conducted in eight sources and 974 documents were originally retrieved from google scholar, web of sciences, scopus, sciencedirect, researchgate, asce, elsevier, and mendeley. outcomes were post-processed in an excel workbook to manage each database report; that process consisted of converting the html information yielded by each search engine into understandable and easy to use excel rows. this step took less than 3 hours. the number of documents retrieved is displayed in table 3. table 3 information retrieval initial summary (number of documents). source initial outcome google scholar 383 web of sciences 2 scopus 85 sciencedirect 26 researchgate 350 asce 20 elsevier 3 mendeley 105 total 974 7.2 stage 2: filtering and file retrieval this stage involves a heavy task because often it is not possible to know whether a document will be useful without reading it. according to their titles, keywords, and abstracts, it is possible to perform an initial filter to reject those that do not meet the requirements. some search engines do not provide abstracts and keywords in their outcomes and the filter can only consider titles. in those cases, a first filter was applied removing unwanted documents according to their titles, and the remaining were downloaded to check by skim-reading whether they met expectations. each downloaded document finally accepted was saved in the computer library labeling it with the author-title format. this step took about 60 hours and the number of documents finally selected was 58, after adding manually three more documents. table 4 shows the number of remaining documents after removing duplicates. there were three types of documents in the list: 62% were journal articles, 36% conference proceedings, and 2% books. journal article impact distribution is shown in figure 4. table 4 information retrieval final summary (number of documents). source initial outcome resulting outcome google scholar 383 24 web of sciences 2 2 scopus 85 6 sciencedirect 26 0 researchgate 350 8 asce 20 4 elsevier 3 0 mendeley 105 11 others 3 summary 974 58 figure 4 impact distribution of the retrieved journal articles (q factor). 54 7.3 stage 3: file reading and tagging two relevant tasks were done at this stage: reading and tagging documents. google scholar and its citing tool were used to find each document and to create an entry in the mendeley catalog (figure 5). most tags are automatically saved, and mendeley, endnote, and other tools can find reference updates, although sometimes it is necessary to look for a specific missing tag, such as the doi, publisher, or the url for the document (see figure 6). figure 5 tag retrieving with google scholar. figure 6 tag management with mendeley. 55 this process does not take long (5 hours for 58 documents), and researchers can perform this part while retrieving and reading documents. reading documents takes much longer and highlighting and writing the summary proposed in section 6.3 does not account for any significant extra time. 7.4 stage 4: knowledge extraction at this key stage, 25 concepts were defined using the types defined in table 2 (see table 5). an excel table was used to annotate documents when they met specific criteria, according to table 5. a part of this work could be done when reading and highlighting documents. to complete this annotation task, the free program docfetcher was used. its outcome is a list of the files that meet the search criteria, showing the number of matches in each file, the context paragraph where the keywords were found, and a direct link to the files. these features make it possible to review any concept presence in 5-10 minutes when all the documents have been read, and it becomes extremely easy to carry out efficient searches. it is necessary to reject documents whose matches belong only to the “references” section. the total time dedicated to the 25 concepts defined was less than 4 hours. the outcome of this step is a table with the list of documents, their tags, summary, and concepts (figure 7). figure 7 shows the concept map where most of the values are “x”, there are values for precision and recall concepts, and there are names. the bottom line displays the count for the number of documents that meet each concept requirement. the use of the relative importance index (rii) method assigns distinct importance to the hits obtained in each document. this way, a weighted count is obtained for each concept. “semantics” is the most important concept and is the basis for calculating the rii in every other concept. in this case “semantics” is a sort of wide concept because almost every document talks about semantics without a specific purpose, but that is not a problem as is shown in the next section. table 5 key concepts for knowledge extraction. concept type explanation scientific papers condition the document addresses scientific papers ie keyword information extraction is considered ir keyword information retrieval is considered improvement idea need for improvement of current ie/ir techniques concepts keyword concept as an entity, related to semantics and ontologies cosine keyword algorithm intended to evaluate the similarity nlp keyword natural language process is cited knowledge keyword knowledge extraction concept is cited ann keyword artificial neural network is cited fuzzy keyword fuzzy techniques and fuzzy logic are cited bayes keyword bayes decision function (classification method) is cited semantics keyword semantics is cited ontology keyword ontology is cited query keyword query is cited, usually related to boolean operations rule-based keyword rule-based and rule are cited related to queries clustering keyword clustering technique is used to classify documents machine learning keyword machine learning is cited artificial intelligence keyword artificial intelligence is cited manual idea manual operation is needed for supervision, training, etc. system keyword a system is proposed, although different in each paper precision numeric percentage of precision yielded by the proposed system recall numeric percentage of recall yielded by the proposed system tags keyword administrative tags are used and retrieved specific activity name the document addresses some specific kind of papers specific country name the document addresses some specific country 56 8. results and discussion the results of the knowledge extraction performed according to the proposed method can be expressed by using the concepts defined and their rii. a ranked list of concepts using the rii gives an accurate view of how scientists address information extraction as a gate to knowledge extraction (table 6) and a pareto diagram gives a better understanding of the relative importance of each concept (figure 8). table 6 ranked list of concepts. # concept rii 1 semantics 100% 2 knowledge 81% 3 ie 78% 4 query 74% 5 improvement 69% 6 ir 69% 7 manual 66% 8 tags 63% 9 rule-based 61% 10 machine learning 55% 11 ontology 49% 12 concepts 47% 13 clustering 45% 14 system 44% 15 precision 40% 16 recall 38% 17 specific activity 33% 18 nlp 30% 19 cosine 23% 20 fuzzy 17% 21 artificial intelligence 17% 22 bayes 14% 23 scientific papers 12% 24 specific country 11% 25 ann 11% it is remarkable that “knowledge extraction” is the second most cited concept, after “semantics,” whose presence is compulsory in this kind of documents. “information extraction” is placed third in the list and “information retrieval” is sixth, although the search string was “intelligent information extraction”. this proves how close both concepts are in the literature. figure 8 proves that the results obtained do not follow the pareto rule. it is possible to differentiate three groups according to concept relevance: 1 to 9, 10 to 18, and 18 to 25. the first group includes basic concepts related to automatization, e.g., “query” and “rule-based”. however, this group contains concepts indicating that there are strong limitations in the state of the art: “need for improvement of current ie/ir techniques” is placed fifth and “manual operation is needed for supervision, training, etc.” is placed seventh. “tags” is placed eighth (administrative tags) and this fact proves that the solutions proposed to extract information frequently address tags, less relevant than insights information. the second group includes concepts related to the technology applied to retrieve and extract information (machine learning, ontologies, concepts, and clustering). it also includes the concept “system” that represents all the systems proposed. all of them are different and, for that reason, they were grouped in that concept to make it possible to give them some visibility. the concept “specific activity,” placed seventeenth, shows that a significant part of the documents studied are intended for a specific purpose, and that fact makes them less applicable to this study. this group includes the concepts “precision” and 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text document cl us teri ng approach bas ed on parti cl e s warm opti mi zati oncl us ter. cl as i fi caci ón documentos con técni cas fuzzy. informati on retri eval ir. propone dos técni cas híbri das : kpso y fcpso. prueba con 3.000 documentos .x x x x x x x x x x x x proceedi ng karthi k, m., mari kkannan, m., and kannan, a. 2008 an i ntel l i gent s ys tem for s emanti c i nformati on retri eval i nformati on from textual web documentsextraen i nformaci ón. us an al gori tmo compl ej o en fas es . mej oran res ul tados de xml. experi mental .x x x x x x seminret x journal arti cl e ki m, t., and chi , s. 2019 acci dent cas e retri eval and anal ys es : us i ng natural l anguage proces s i ng i n the cons tructi on i ndus tryie con regl as y condi ti onal random fi el d crf. extraen i nformaci ón de i nformes de acci dente. ie con okapi bm25. nlp. semánti ca. tokeni zaci ón. li mi taci ones . poca i nformaci ón.x x x x x x x x x x x x x system (python) 85% 68% cons tructi on acci dent journal arti cl e koval , r., and návrat, p. 2012 intel l i gent s upport for i nformati on retri eval of web documents informati on retri eval . ie. obtenci ón documentos en l a web que cumpl an con requi s i tos . intervenci ón manual . cl us teri ng.x x x x x x x x x x tree clustering 80% x web journal arti cl e lambri x, p., and shahmehri , n. 2000 queryi ng documents us i ng content, s tructure and properti es bús queda en propi edades y conteni do. bus ca palabras. cons ul ta manual y query. toma deci s i ones . creaci ón índi ce. bús queda adaptada al conoci mi ento previ o. al tavi s ta.x x x x x x x x x query x proceedi ng lee, r. 1998 automati c i nformati on extracti on from documents : a tool for i ntel l i gence and l aw enforcement anal ys tssi s tema con querys para obtener i nformaci ón. no l a cl as i fi ca, s ól o l a al macena. enti dades . ie i nformati on extracti on. revi s i ón manual .x x x x x x journal arti cl e li , j., wang, h. j., and bai , x. 2015 an i ntel l i gent approach to data extracti on and tas k i denti fi cati on for proces s mi ni ngextracci ón i nformaci ón ie. cons i guen metadatos . experi mental . machi ne l earni ng. preci s i ón 90%. fal s os pos i ti vos 30%.x x x x x x x x x method 70% 87% journal arti cl e lópez-robl es , j.-r., gual l ar, j., otegi -ol as o, j.-r., and gamboa-ros al es , n.-k.2019 bi bl i ometri c and themati c anal ys i s (2006-2017) anal i za evol uci ón revi s ta epi. sci mat para anál i s i s . local i za l os temas (conceptos ). interconexi ones .x x x x x x x journal arti cl e luts ky, p. 2000 informati on extracti on from documents for automati ng s oftware tes ti ng us o de l enguaj e natural nlp. comprobaci ón de s oftware. val i daci ón. si s tema s peci fi cati on i nformati on from text (sift).x x x sift x software journal arti cl e mal i k, s. k., prakas h, n., and ri zvi , s. 2010 semanti c annotati on framework for i ntel l i gent i nformati on retri eval us i ng kim archi tecturesi s tema. entorno web. semánti ca. ontol ogías . lenguaj e natural nlp.x x x x x x x x x x kim proceedi ng mari nai , s. 2009 metadata extracti on from pdf papers for di gi tal l i brary i nges t extracci ón metadatos de pdf. convi erten pdf a xml. us an greens tone.x x x x x x pdf2gsdl 23% 74% proceedi ng matos , p. f., lombardi , l. o., pardo, t. a., ci ferri , c. d., vi ei ra, m. t., and ci ferri , r. r.2010 an envi ronment for data anal ys i s i n bi omedi cal domai n: i nformati on extracti on for deci s i on s upport s ys temsori entado a bi omedi ci na. anemi a de cél ul as fal ci formes . informatoi n extracti on ie. datos numéri cos . documentos no es tructurados .x x x x x x x x x x x x x x bi omedi ci na journal arti cl e mats uo, y., and is hi zuka, m. 2004 keyword extracti on from a s i ngl e document us i ng word co-occurrence s tati s ti cal i nformati onextrae pal abras con al gori tmo. no val ora el s enti do. obti ene l os que más aparecen. co-occurrence.x x x x x proceedi ng mi l ward, d., and thomas , j. 2000 from i nformati on retri eval to i nformati on extracti on ie, ir. nlp. hi ghl i ght. query con operadores bool eanos . experi mental . res ul tados pobres y l i mi tados .x x x x x x x x 77% 55% x journal arti cl e mi tra, m., and chaudhuri , b. 2000 informati on retri eval from documents : a s urvey encues ta es tado arte en bús queda e i ndexaci ón. ti pos documentos . des es tructuraci ón. mul ti -domi ni o de ori gen. model o bool eano. al gori tmos . ocr.x x x x x x x x journal arti cl e nas ar, z., jaffry, s. w., and mal i k, m. k. 2018 informati on extracti on from s ci enti fi c arti cl es : a s urvey extracci ón i nformaci ón artícul os académi cos . al gori tmos hmm, cora, crf, svm. extrae metadatos (datos artícul o) y key-i ns i ghts (mens aj es dentro del texto).x x x x x x x x x x x x x 42% 52% x journal arti cl e nual art-vi l apl ana, j., pérez-montoro, m., and whi tel aw, m.2014 cómo di buj amos textos : revi s i ón de propues tas de vi s ual i zaci ón y expl oraci ón textualvi s i ón mul ti di mens i onal del texto. mi nería de datos . textos i ndi vi dual es y col ecci ones . anál i s i s vi s ual de es tructura. intentan es tructurar.x x x x proceedi ng ol i vei ra, d. a. b., and vi ana, m. p. 2017 fas t cnn-bas ed document l ayout anal ys i s si s tema uni di mens i onal anál i s i s automáti co. cnn (convol uti onal neural networks ). anal i zan i mágenes .x x x x cnn proceedi ng oro, e., and ruffol o, m. 2008 xonto: an ontol ogy-bas ed s ys tem for s emanti c i nformati on extracti on from pdf documentsextracci ón de pdf. ontol ogía. ontol ogy-bas ed s ys tem for s emanti c ie from pdf documents xonto. convers i ón de documentos no es tructurados a es tructurados .x x x x x x x x x xonto x proceedi ng rahman, n. a., soom, a. b. m., and is mai l , n. k. 2017 enhanci ng latent semanti c anal ys i s by embeddi ng taggi ng al gori thm i n retri evi ng mal ay text documentslatent semanti c indexi ng (lsi). apl i caci ón a l engua mal ay. mej ora de lsi. términos y conceptos. definiciones. us a eti quetas (tags ).x x x x x x x lsat 65% 70% x mal ay l anguage proceedi ng ri zvi , s. t. r., merci er, d., agne, s., erkel , s., dengel , a., and ahmed, s.2018 ontol ogy-bas ed informati on extracti on from techni cal documents extracci ón de i nformaci ón de tabl as . convers i ón de pdf a html. bas ado en ontol ogías . automáti co.x x x x x x 88% 100% tabl es proceedi ng rodríguez, a., col omo, r., gómez, j. m., al or-hernandez, g., pos ada-gomez, r., juarez-marti nez, u., gayo, j. e. l., and vi dyas ankar, k.2009 a propos al for a s emanti c i ntel l i gent document repos i tory archi tecture li teratura académi ca. ie. ir. sidra s i s tema híbri do. ori entado a html. ontol ogía. query. keywords . ranki ng por rel evanci a en cuanto al número de ci tas .x x x x x x x x sidra x software irel and journal arti cl e ros tami , n. a. 2014 integrati on of bus i nes s intel l i gence and knowl edge management – a l i terature revi ewdefi ne knowl edge management. rel aci ón con bi. x x x journal arti cl e sai k, o., demenkov, p., ivani s enko, t., kol chanov, n., and ivani s enko, v.2017 devel opment of methods for automati c extracti on of knowl edge from texts of s ci enti fi c publ i cati ons for the creati on of a knowl edge bas e sol anum tuberosumci ta s i s temas de extracci ón ori entados a temas bi ol ogía. us a bas e datos mysql. semánti ca.x x x x x x andsystem agri cul tural bi otechnol ogy proceedi ng sarwar, s. m., and al l an, j. 2019 a retri eval approach for informati on extracti on si s tema search ie. informati on extracti on. query. cas o de pocas apari ci ones de un concepto. lenguaj e natural nlp.x x x x x x x searchie x journal arti cl e schal l ey, a. c. 2019 ontol ogi es and ontol ogi cal methods i n l i ngui s ti cs defi ne ontol ogía. li ngüís ti ca. x x x x proceedi ng seedah, d. p., and lei te, f. 2015 informati on extracti on for frei 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for mul ti -di mens i onal model i ng of textual -bas ed bus i nes s i ntel l i gencedefi ne metadatos meta-data como endnote. 80% i nformaci ón no es numéri ca. mul ti -di mens i ón. data warehous e. document warehous e. pl antea xml.x x x x x x x x x tai wan proceedi ng upadhyay, r., and fuj i i , a. 2016 semanti c knowl edge extracti on from res earch documents combi nati on of s emanti cs of s entences and natural l anguage proces s i ng techni que over the s entences . rul es . keywords . query. apoyo manual .x x x x x x x x x x x proceedi ng wang, q., qu, s. n., du, t., and zhang, m. j. 2013 the res earch and appl i cati on i n intel l i gent document retri eval bas ed on text quanti fi cati on and subj ect mappi ngdocument retri eval . ie. word concept. bus ca pal abras por s u s emánti ca. cl as i fi caci ón de documentos por temas . keywords para cl as i fi car. correl aci ón entre pal abras . al gori tmo cosine.x x x x x x x x x x journal arti cl e wol f, c., and jol i on, j.-m. 2004 extracti on and recogni ti on of arti fi ci al text i n mul ti medi a documents referenci a para bús queda en documentos mul ti medi a. ocr.x x x x x x x x system (ocr) 88% 76% mul ti medi a journal arti cl e xi e, x., fu, y., ji n, h., zhao, y., and cao, w. 2019 a novel text mi ni ng approach for s chol ar i nformati on extracti on from web content i n chi nes esi s tema experi mental para extraer i nformaci ón de web en chi no. extrae atributos expertos . bas ado en pal abras y regl as . x x x x x 44% 47% x chi na 58 58 58 7 42 35 35 23 10 16 42 6 9 8 52 26 38 31 21 27 9 34 26 20 19 32 20 6 figure 7 reference list with concepts. 57 “recall”: the average values for precision and recall in the literature review performed are 64% and 70%, respectively, which are very far from a comfortable confidence level. the third group contains the least relevant concepts and they are related to the most sophisticated techniques, e.g., “artificial intelligence.” this seems to prove that they are far from a mature state that would allow them to be commonplace. the concept “scientific papers” is placed twenty-third because only seven out of the 58 documents studied address this subject. the specific field of knowledge extraction from scholarly documents asks for affordable solutions that are easy to work with. nassar says that “manual analysis is not scalable and efficient” and cites other authors who state that a systematic literature review could take 1 to 3 years (nasar et al. 2018). this study has used a manual method to extract knowledge starting with a systematic literature review, and the whole process took less than one month. the results presented in this study prove that knowledge extraction can be efficiently performed manually with the help of desktop tools that are commonplace. it does not matter that manual analysis is not scalable because researchers usually face a scholarly library with only a few hundred documents in each research project. the method proposed was also used in a distinct research project with a library that held 300 documents (vegasfernández 2019). in practice, document reading takes up most of the time dedicated to literature review in a research project, much more than retrieving and organizing documents. this paper proposes a feasible way to optimize knowledge extraction, giving up, for now, the option of a fully automatic information retrieval and extraction system, and proposing “concept definition” as the most relevant task. 9. conclusions technique algorithms are not always the answer to efficient extraction of information from scholarly document databases and sophisticated automatic systems do not seem to be the best fit to solve the researcher’s needs. any possible automated solution that requires manual training, supervision, and tuning is not worthwhile because it requires too much time dedicated to those tasks and it is shorter and more efficient to do it by hand. the relevance of concept definition has frequently been underestimated and this paper proposes and proves that proper concept definition is key to achieve outstanding knowledge extraction. the results of the analysis conducted with a scholarly document database confirm the suitability of the approach and the method that has been explained. this paper has presented a simple but efficient method that takes advantage of free desktop tools that are commonplace. by following this method, it is very easy to carry out a systematic literature review, in order to figure 8 pareto diagram of concepts using their rii. 58 retrieve, filter, and organize results, and to extract information to transform it into knowledge. the conceptual basis is a semantics-oriented concept definition and a relative importance index to measure concept relevance in the literature studied. the detailed explanation of the proposed procedure in four steps shows that most of the tasks require mental activity that cannot be helped by automated systems. the method 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(2017) the impact of supply chain management on business intelligence. journal of intelligence studies in business. 7 (2) 51-61. article url: https://ojs.hh.se/index.php/jisib/article/view/223 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index the impact of supply chain management on business intelligence audrey langloisa and benjanmin chauvala ala rochelle university, france; audrey-langlois@hotmail.fr and benja-chauval@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: integration of business intelligence with corporate strategic management patent bibliometrics and its use for technology watch björn jürgens pp. 17-26 why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company journal of intelligence studies in business v o l 7 , n o 2 , 2 0 1 7 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 7, no. 2 2017 klaus solberg søilen pp. 27-39 an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france sophian gauzelin and hugo bentz pp. 40-50 mouhib alnoukari and abdellatif hanano pp. 5-16 the impact of supply chain management on business intelligence audrey langlois and benjamin chauvel pp. 51-61 the impact of supply chain management on business intelligence audrey langloisa and benjamin chauvela ala rochelle university, france *corresponding authors: audrey-langlois@hotmail.fr and benja-chauvel@gmail.com received 4 march 2017; accepted 3 june 2017 abstract this conceptual paper investigates the impact of the supply chain on business intelligence (bi) in private companies. the article focuses on these two subjects in order to broadly understand the concept of business intelligence, supply chain and characteristics implement such as olap, data warehouse or data mining. it looks at the joint advantages of the business intelligence and supply chain concepts and revisits the traditional bi concept. we found that the supply chain includes many data samples collected from the first supplier to the last customer, which have to be analysed by the company in order to be more efficient. based on these observations the authors argue for why it makes sense to see the bi function as an extension of supply chain management, but moreover they show how difficult it has become to separate bi from other it intensive processes in the organization. keywords business intelligence, information systems, real-time business intelligence, supply chain management 1. introduction customers’ demand for high quality products and services is rising. they want the right product at the right place and on time. modern companies have to be more efficient to match customers’ needs while reducing the time and cost of the production process. thus, a company can’t be viewed as a single entity, but as a part of the supply chain if they want to gain a competitive advantage. as christopher (1998) says, a supply chain “is a network of organizations that are involved, through upstream and downstream linkages in the different processes and activities that produce value in the form of products and services in the hand of the ultimate consumer”. additionally, supply chain management is viewed as the best way to reduce costs and to increase the optimization of the production process. yet, since the early 2000s, technologies have increased and the collection of data has deeply changed. for example, “walmart handles more than a million customer transactions each hour and imports those into databases estimated to contain more than 2.5 petabytes of data.” (ittmann, 2015). today, as companies are drowned in information which doubles every two to three years, they have to find the best way to understand it and gain a competitive advantage. it is more important to know what information the company needs, how and when to match the customer needs. therefore, software has been created in order to answer these questions. one of the most used practice is business intelligence (bi) which integrates and analyses various software. bi provides a set of technologies and products for supplying users with the information they need to answer business questions, and make tactical and strategic business decisions (stefanovic et al., 2006). the bi field is growing over the years because as said by gartner (2012), “the global spending on bi systems, including analytics and performance management applications, journal of intelligence studies in business vol. 7, no. 2 (2017) pp. 51-61 open access: freely available at: https://ojs.hh.se/ 52 has risen from $10.5 to $12.2 billion in 2011”. given the increase in data, competition and customers requirement, it is vital for a company to have rapid access to its information in order to take the best decision and reduce its cost. bi, consequently, is also appropriate for supply chain management (scm) which needs to be functional. thus, it can provide real-time data of this supply chain. before using bi in the supply chain it is important to understand and to know how to use it. in this respect, some questions must be asked: • what is business intelligence? • why do supply chains need business intelligence? • what is the impact of the business intelligence on the supply chain? a supply chain provides information from the supplier to the client and has to be processed. more information means more competition. in the age of the information explosion, executives, managers, professionals, and workers all need to be able to deliver their product on time and make better decisions faster. because now, more than ever, “time is money” (reinschmidt and francoise, 2000). the creation of bi revolutionized business and is bringing a new way for business to thrive and manage its supply chain at reduced cost. however, it was often difficult to understand and very expensive, so much so that companies don’t really used it. it is only for a few years that its uses have been facilitated and its cost is now lower. today, bi is an important factor for a company’s success. however, no articles that we found discuss the relationship with supply chain (research gap). 2. empirical findings: a literature review 2.1 business intelligence, data gathering, competitive intelligence the importance of a good intelligence systems has become increasingly apparent during the past few decades for two reasons, the abundance of information now available due to new technologies, and, as a consequence, the need to be able to distinguish between “need to know” and “nice to know” (soilen, 2012). businesses collect enormous amounts of data every day: information about orders, inventory, accounts payable, point-of-sale transactions, and of course, customers. businesses also acquire data, such as demographics and mailing lists, from outside sources. unfortunately, based on a recent survey, over 93% of corporate data is not usable in the business decision-making process today (reinschmidt & francoise, 2000). to put order in all these data, some companies use business intelligence. it is difficult to give a clear definition of bi when many of them can be used. business intelligence is seen as a concept of conscious, organized, continuous, legal and legitimate gathering, analysing and using data and information for strategic and tactical marketing decisions according to šerić et al. (2014). adelman et al. (2002) describe bi as a term that “encompasses a broad range of analytical software and solutions for gathering, consolidating, analysing and providing access to information in a way that is supposed to let an enterprise’s users make better business decisions”. malhotra (2000) points out that bi benefits facilitate the connections in the newform organization, bringing real-time information to centralized repositories and support analytics that can be exploited at every horizontal and vertical level within and outside the firm. according to partrige (2013), bi is the use of computing technologies for the identification, discovery, and analysis of business data such as sales revenue, products, costs, and incomes. however, bi can also be viewed as more technical and integrate several software for extraction, transformation and loading (etl), such as data warehouse (database where data is collected for the purpose of being analysed; it collects, organizes, and makes data available for the purpose of analysis), database query and reporting (berson et al., 2002). we also find multidimensional/online analytical processing (olap) and data mining (used to solve different kinds of analytical problems, olap summarizes data and only makes forecasts, data mining discovers hidden patterns in data and operates at a detailed level instead of a summary level). bi is a system designed to support decision making, it finds information from many other systems (figure 1). some of these terms have briefly been explained in order to understand the bi dimension. bi helps to create knowledge from a world of information, get the right data, discover its power, and share the value. bi transforms information into knowledge. (reinschmidt & francoise, 2000). 53 consequently, bi is the application of putting the right information into the hands of the right user at the right time to support the decision-making process (reinschmidt & francoise, 2000). the business success factor for any enterprise is finding ways to bring the vast amounts of data that are flowing within and across the business processes together and making sense out of them (sahay & ranjan, 2008). for those reasons, bi is not business as usual. it’s about making better decisions easier and making them more quickly (reinschmidt & francoise, 2000), thus improving the timeliness of input to the decision process, and facilitating managerial work (negash, 2004). in addition, bi gives an overview of the competitors thanks to competitive intelligence (ci), which could be defined as a special branch of the bi literature. ci is the process of ensuring your competitiveness in the marketplace through a greater understanding of your competitors and the overall competitive environment (solomon negash, 2004). in consequence, it’s the practice of “defining, gathering, analysing and distributing need-toknow information to the organization’s decision makers” (soilen, 2013). much of information obtained by ci comes from easy sources (imhoff, 2003) such as government websites and reports. for example, it could come from: • online databases, interviews or surveys, • special interest groups (such as academics, trade associations, and consumer groups), • private sector sources (such as competitors, suppliers, distributors, customer) or • media (journals, wire services, newspapers, and financial reports). soilen (2010) points out that trade shows represent another opportunity to gather information about competitors, whether for their products or services in order to obtain a competitive advantage. however, it is important to collect useful information, staff training has to be done in order to gather the right information by the team. companies can also access books and articles in journals dedicated to these issues like this one or previous journals like the journal of competitive intelligence and management (jcim) or the competitive intelligence review (cir) according to soilen (2013). 2.2 supply chain management, software and data creation through big data first of all, it is important to have a clear definition of what logistics and supply chains are, as these two terms can often lead to confusion. logistics is a term which has been used for many years, it has a military origin and was born during the preparations in anticipation of a battle, to make available the means of transport, the equipment or all that concerning the foodstuffs. according to dictionary.com, there are two definitions for the term logistic: “the branch of military science and operations dealing with the procurement, supply, and maintenance of figure 1 information systems used by bi. 54 equipment, with the movement, evacuation, and hospitalization of personnel, with the provision of facilities and services, and with related matters” and one definition based on the actual logistic: “planning, execution, and control of the procurement, movement, and stationing of personnel, material, and other resources to achieve the objectives of a campaign, plan, project, or strategy. it may be defined as the 'management of inventory in motion and at rest”. the concept of logistics is a rather recent and appeared in the 1960s. the concept of supply chain was born some time later, towards the 1990s. supply chain could be explained by the logistics management corresponding to a part of the supply chain management that provides, sets up and controls upstream and downstream flows efficiently, storage, services and information exchanged between the actors of the chain from their point of departure to the final customers in order to satisfy them, in other words, logistics is only one (important) element of supply chain management (figure 2). as stated previously, lambert et al. (1998) defines a supply chain as the alignment of firms that bring products or services to market. it is important to know that the final or end consumer is included as an element of the supply chain. differentiated from the supply chain, supply chain management (scm) is “the task of integrating organizational units along a supply chain and coordinating materials, information and financial flows in order to fulfil customer demands with the aim of improving competitiveness of the supply chain as whole” (stadtler, 2005). the main objective of scm is to meet the customer needs by sending the right product at the right place, time, and price. besides, scm is a multidimensional approach which integrates product development, manufacturing, logistic, customer service, performance measurement, and information sharing (surbhi, 2015). consequently, the supply chain is a part of the scm, it transforms resources into a product and delivers it to a customer whereas the scm is a broader area which aims to cut costs and to add a value for the customer and the shareholder. the supply chain is only a way to help the scm to execute the operations. nowadays, scm is a factor of differentiation, especially for the competitors and for the customer service. to make a scm work efficiently, different types of software and actors are included in the process. some software will be used for strategic planning, others for the execution. the software is classified according to the three different functions of the scm: the first one is the scp (supply chain planning), it is about planning the production, the distribution, the transport and realizing forecasts. the software related to scp is an aps (advanced planning system), it analyses the capabilities of the resources in order to propose a detailed schedule for a better production (http://www.catlogistique.com/supply_chain.ht m). the second function is the sce (supply chain execution) and this function integrates the data related to the operational activities management of the supply chain. software like tms (transport management systems) and wms (warehouse management systems) are associated with sce. the last function is the scem: the supply chain event management. another type of software to take into consideration is erp (enterprise resource planning). it is a software that integrates all the functions of a company. it is constituted of several units named business objects (bo) (for example: supply, sell, production, finance, hr, or stock). these units share the same database, so it facilitates the control of the company (http://www.logistiqueconseil.org/articles/new -tech/scm.htm) even if “traditional erp players are now facing competition from cloud providers” (trebilcock, 2016), the leader in the erp software market remains sap with €2.67 billion in revenue in 2014. there are many figure 2 logistics as part of every step in a supply chain. 55 actors participating with supply chain software, therefore it is important for companies “to find the system that best suits their business” (nyblom, 2012) and they have to know what are the software and techniques used by the companies. this software is generating tons of data which is called big data. in fact, “millions of shipments are tracked daily from origin to destination, indicating information such as the content, weight, size, location, route” (watson et al., 2012). this huge amount of data is then exploited. with the enormous amount of data created every day, companies are under pressure to make smart use of the data, and take advantage of it. the nature of the scm environment is changing, and two major trends will impact the scm in the future: big data and analytics (ittmann 2015). ittmann is not the only one to argue this. cooke (2013) points out that “the increased use of big data analytics is one of the three trends in scm to watch” (cooke, 2013). big data and analytics are becoming increasingly important for many reasons. first of all, storing data is becoming cheaper and data is available everywhere thanks to the anytime connectivity. plus, the tools are easier to use because it is simpler to make the analysis, there are techniques to show and present huge volume of data, and the processing power is faster (deloitte & mhi, 2014). in fact, extracting and analysing the values from big data can have a huge impact on businesses and help them to succeed. analytics, which is considered a subset of bi is defined as “the scientific process of transforming data into insights for making better decisions” (ittmann, 2015). there are many ways to extract data in order to create business intelligence, for example “statistical and quantitative analysis, explanatory and predictive models” (ittmann, 2015). therefore, big data and analytics can directly be related to bi because it can help firms to make decisions and improve their businesses. as mentioned by partridge (2013), “being able to find, understand, and use that data to make strategic decisions that improve supply chain effectiveness is crucial.” figure 3 the different kinds of software. 56 2.3 the importance of business intelligence strategy when a company decides to take advantage of bi and use it for its own supply chain, it is important to set up a supply chain business intelligence strategy. having a reliable strategy is essential for every business to succeed, the same holds true for the implementation of bi in a supply chain. as reported by sangari and razmi (2014), the supply chain bi competence is seen as a multidimensional construct competence. the company has to build a full strategy, including three competences: the managerial, technical and cultural competence. the managerial competence aims to relay the right information to the right people at the right time (bose, 2009). the technical competence represents the tools and the technologies (like data warehousing) used to gather information in a supply chain in order to make business decisions. the cultural competence is defined as the ability to develop a strong bi culture, including the quality of the information and the quality of the communication flows. all of these three competences prove that having a strategy can have a positive impact on the performance of the supply chain, especially on the customer satisfaction and the cost reduction. 3. method this article is conceptual and built on a literature review. when reviewing a number of articles within bi that link with software, competitive intelligence, and strategic planning a gap was identified with supply chain management. the authors found definitions for the keywords, such as business intelligence, logistic, supply chain, supply chain management, and competitive intelligence. afterward, they extracted key elements from the articles in order to analyze and compare content. the last part of the research was conceptualization and synthesis, building models to sum up the analysis. 4. analysis 4.1 business intelligence in scm the concept of supply chain and bi is nothing new, but, until recently, only few companies had these solutions at their disposal. as seen above, the supply chain allows a company to gain a competitive advantage on their competitors. however, it is not easy to lead a supply chain. it requires having a good relationship with suppliers and customers as the supply chain represents the chain of a product from the supplier to the final customer. this is done in order to be efficient and reduce costs. these can be procurement costs, production costs, financial capital and possession costs, transfer costs, breaking costs, product design costs and insurance costs. to reduce these costs, companies are used to employing supply chain management defined as the execution, the conception, the control of the supply chain activity in order to create value for the company, to achieve greater efficiency and gain a competitive advantage. consequently, supply chain management is a priority and essential challenge for the company, in order to optimize its productivity. however, there are many steps before selling a product on the market; they concern purchases, inventory management, handling, storage, and transportation. supply chain management aims to improve administrative management and thus reduce a significant number of errors. it contains many tools developed by companies in different fields: • planning (mrp, jit, drp, etc.). • manufacturing (opt, crp, etc.). • stock optimization: endogenous method (historical analysis) or exogenous (market research approach) etc. • transport and warehousing (rfid, tracking, etc.). • information management (erp, crm, srm, plm, edi, etc.). • quality (tqm, etc.). all of these software collect data, so that companies can read them to have an overall view of the company and to make decision despite obstacles such as arrivals in disorder, and delays in organizing and interpreting data. formerly, companies had to hire specific technical employees in order to read and understand this data. today, companies use bi in order to collect data quickly, efficiently and to make it available immediately. it provides decision-making support to professionals through reports and dashboards to monitor both analytical and forward-looking business activities. bi collects data from erp (enterprise resource planning), tms, and crm that it then stores in the data warehouse as a central data repository or in data marts via etl (extraction, transformation and loading) 57 processes which are responsible for retrieving data from all existing operational sources and loading them to the decision-making system. then bi distributes this data and finally analyses them through data mining, olap charts and reporting. as seen above, bi is made up of several components. the following are the major components: a data warehouse is a database dedicated to the storage of all the data used in decision making and decision analysis. the data warehouse is exclusively reserved for this purpose. data marts are a smaller version of the data warehouse. they focus on a topic, a theme or a job. in olap, within an olap database, the data is stored according to a principle of dimensions closely corresponding to the user's search axes, its structure can be seen as a "cube". “olap provides multidimensional, summarized views of business data and is used for reporting, analysis, modelling and planning for optimizing the business” (sahay and ranjan, 2008). data mining is able to find original structures and informal correlations between data. it allows us to better understand the links between apparently distinct phenomena and to anticipate trends that are not yet discernible. as a consequence, bi is a part of business, it allows the company to make decisions clearly and quickly. the faster the stores send information about what customers buy, the faster the information can be passed on to manufacturers and designers, the faster the supply chain can react and contributes to the optimization of supply chains which are the issue in the search for competitive advantages. stock reduction and optimization of the supply chain cannot be conceived without good information management. beyond the traditional operational systems that automate processes, it is without doubt necessary to rely on an appropriate decision-making system like bi. the latter must be based on a data warehouse that integrates all internal and external logistics data and provides all stakeholders with the historical, operational, forecasting or simulation visions they need. consequently, bi in management of scm contributes to the differentiation of a business entity. 4.2 real-time business intelligence bi is important in order to make appropriate decisions. as part of this, the concept of realtime bi is starting to attract companies’ attention. real-time bi consists of reducing time and collect instantaneous data. it not only supports the traditional strategic functions of data warehousing, but also provides tactical real-time support for generating corporate actions to respond immediately to events as they occur. manh et al. (2005) propose an “event-driven it figure 4 creating business intelligence in the supply chain management. 58 infrastructure to leverage bi applications that enable real-time analysis in all business-tobusiness processes, notify actionable recommendations, or trigger business operations automatically, and allow to effectively bridge the gap between bi systems and business processes.” for example, if a company sells clothes online then the company's web site and the company's call centre representatives must have the same updated information on inventory levels, so that, if a customer makes an order and the size or colour is sold out, the customer can be notified and redirected to another similar item. sahay and ranjan (2008) point out the realtime bi system is to provide information on business operations with minimal latency. this means providing information a few seconds after the business event. while traditional bi presents historical information to users for analysis, realtime bi compares current business events with historical models to detect problems or opportunities automatically. not all departments of a company need real time bi, because of the high cost compared to traditional bi, companies should use the real time bi only when it is necessary and needs to focus first on specific business needs. 4.3 real time business intelligence in the supply chain traditional bi systems are used by several varied sectors like manufacturers, airlines telecommunication providers, retailers, financial services, health systems and hotels and consist of a back-end database, a front-enduser interface, software that processes the information to produce the bi itself, and a reporting system. it produces for these companies customer support, market research, segmenting, product profitability, statistical analysis, inventory and distribution analysis. however, bi requires a complex technology usable only to technical specialists. moreover, bi takes a long time to yield correct analyses and companies want this analysis in real time for short-term projects. traditional bi cannot do this and in consequence real time bi is seen as a rescue. real time bi detects early situations for planning and coordination of logistics such as delay of freight, stocks alert, and failure of delivery. real time bi reacts in near real time to changes in the business environment. it analyses data minute-tominute in various time zones and helps firms move to what is called as “zero latency” or real time enterprise. according to hackerthorn (2003), a business is operating with three latency periods: data latency, analysis latency and decision latency. the aim is to reduce the latency to the minimum to be more efficient and this is one of the purposes of real-time bi. sahay and ranjan (2008) noticed that it means “delivering information in a range from milliseconds to a few seconds after the business event”. take the example of flixbus, a bus is stuck in the traffic jam, the real time bi automatically discovers the problem, analyses it before a decision is needed. from there on the bus route will be adjusted or the customers will be notified of the shipment delay. according to sahay and ranjan (2008) a global real time data warehouse, real time data mart for storing historical and summary data at different levels is required, as well as an efficient olap interface with secure real time architecture for such efforts to succeed. 4.4 the impact of using bi in the supply chain management after having explained how bi and scm are related and how software help to create bi especially with the real-time bi, the focus here is on the benefits for companies to use bi in their supply chain. there are many positive consequences in each function of a supply chain (warehouse management, transportation management, marketing and sales, financial management) that can lead to the success of a company. first of all, bi tools are helpful in the supply chain because they can help to detect and solve problems. chen et al. (2012), “consider business intelligence and analytics as an important area of study and research to solve data-related problems in companies”. if there is a problem with transportation, the idea is that bi will detect the problem first and it will help by changing the transportation route or the mode of transport, in order to reduce negative consequences. if there is a failure of delivery or a delay in the shipping, real time bi can directly send a message to customer and let them know about delay in shipping (ramish babu, 2010). some software has a strong ability to monitor and predict low in-stock items in advance (krupnik, 2013), this reduces the amount of incomplete shipments, reducing complaints from customers and avoiding new a problem. as an example, amazon developed an algorithm to analyse clicks on the website to 59 solve the problem of stocks. this analytic tool helped amazon track sales on many kinds of products allowing them to manage inventories (ittmann, 2015). when a firm succeeds in avoiding problems which could arise on any part of the scm, it obviously saves costs. tools help to reduce waste, they show which part of the supply chain is not efficient, and if managers are taking this into account, they will make changes to reduce and save costs. ibm optimized their supply chain by using analytics tools (dietrich et al., 2014) and they implement a system which can detect problems earlier. as a consequence, the company increased productivity, revealing opportunities to cut costs and saved money. another positive consequence of bi is the efficiency and the performance of the supply chain, which is also a logical consequence of cost savings and problems solving. as mentioned previously, firms include mobile devices and barcode scanners to store the information for every item, such as location, stats, and method of transportation (ramesh babu, 2010). this way of tracking the information enhances monitoring and optimizes process flows. for example, gap implemented ways to keep the supply chain as efficient as possible through bi solutions. they carried out the seamless inventory to improve its performance and they build the “reserve in store” on the e-commerce website. moreover, all of the functions of the company are affected by bi, even the support functions such as human resources or financial management. for example, as for the human resources, reports can analyse the movement and the performance of staff, tools can measure the need of the workforce (rao p. and swarup, 2001). hr managers are able to know which employees are efficient, they also see how many people they need to hire for each new project or implementation. concerning financial management, budgets can be analysed and financial viability can be assessed (profitability per kilometer of distance covered or labour cost, for example) through financial report or data warehousing. this helps take strategic decisions and directly participates to the efficiency and the performance of the firm. through the analysis of data, bi helps to find what is providing value. as mentioned by soilen et al. (2010), “a value chain analysis focuses first on the firm's core competences from an inside perspective”, and this analysis aims to identify the competitive advantage of the firm. in this sense, tracking the information and analysing it increases the efficiency and the performance of the supply chain but also provides a competitive advantage. firms can be more competitive on the market. firms can find a differentiation approach faster than usual. as stated by sangari (2004), “businesses are still struggling to achieve competitive advantage.” nowadays, organizations noticed that they need to use effective tools for decision making, in order to create bi. to prove that a company can be more competitive with data analysis, the example of a baseball player will be used. lewis (2003) performed research on a baseball team and used data-based analysis on one of the players’ performance. it turned the club into a very competitive team. lidl is one of the many firms that used bi in their processes. they used the software sap (an erp software) to analyse a large amount of data, to understand and react to the customer behavior. this allowed them to have a better understanding of the customer and to target the right market. targeting the right market also means they will have better chance to improve the success of the company. all of the elements stated previously are participating together towards the common and final goal, customer satisfaction. through profitability analysis of the services offered to the clients, firms are able to know what to offer to each customer. it allows them to provide more value-added services to exactly meet their needs. to sum up the ideas mentioned previously, a citation stated by ngai et al. (2011) can be used: “supply chain agile capabilities help to sustain competitive advantage and improve performance through reducing manufacturing costs, enhancing customer satisfaction, and removing non-valueadded activities.” 5. conclusion data has been used for critical decisions since the beginning of globalization. new opportunities and choices have been given for both consumers and companies. a competitive pressure has forced companies to lead their sourcing and manufacturing on a global scale resulting in a significant increase in product offerings. when a company grows, it needs a bigger and more sophisticated supply chain with tools that generate the insight that leads to smarter it solutions. bi systems are part of this effort to provide technology in order to 60 collect information to improve business potency and give easy access to the information that partners, suppliers, and employees need to do their job. it facilitates scrutinizing every aspect of business operations to find new revenue or squeeze out additional cost savings by supplying decision support information. as such it has become increasingly difficult to separate bi from other it intensive efforts, like the supply chain. robison (2002) points out that bi uses technology-related complexities and can be useful only with technically savvy specialists. robinson argues that bi is expensive due to its complexity and that bi can take long time to yield correct analyses when companies need to get a perspective in the short-term. given that bi is hard to set up, there are other ways to provide bi, such as sql (structured query language). sql is a domain specific language designed for managing data held in a relational database management system. as discussed previously, the focus of supply chain management is to optimize tools and methods in manufacturing, sourcing and distribution sectors in order to reduce delivery times, inventories and costs. applying the concepts of bi to scm systems provides strategic information to decision makers in organizations. besides, real-time bi has an impact on business decisions and current business processes. ittmann (2015) summarized the situation well with the following statement: “organisations need to understand forces in their marketplace better and respond faster to changes in their environment in order to remain competitive. the proper use of any tools and methodology to assist in this is essential.” using bi tools has become essential in the current business environment because there are many advantages for companies to use bi in their strategies because it allows them to be more competitive on the market and manage customer relations in the easiest and best way. 6. references adelman, s., moss, l., & barbusinski, l. 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(2010). boosting innovation and knowledge through delocalization: market intelligence at trade shows. problems and perspectives in management, 8(3), 200-207. søilen, k. s. (2012). geoeconomics. bookboon. søilen, k. s. (2013). an overview of articles on competitive intelligence in jcim and cir. journal of intelligence studies in business, 3(1). stadtler, h. (2004). supply chain management and advanced planning––basics, overview and challenges. european journal of operational research, 163(3), 575-588. trebilcock, b. (2016). top 20 supply chain management software suppliers: the market for conventional solutions continues to rise, even as innovative variations help the industry chart a new course. logistics management (highlands ranch, colo.: 2002). 29 intelligence in the oil patch: knowledge management and competitive intelligence insights helen n. rothberg 1 and g. scott erickson 2 1 marist college, poughkeepsie, usa 2 ithaca college, ithaca, usa email: hnrothberg@aol.com, gerickson@ithaca.edu received october 10, accepted 25 december 2013 abstract: the fields of knowledge management and competitive intelligence have been joined in the literature for over a decade, as scholars recognized the emphasis in each field on developing knowledge, albeit of different types. while knowledge management is often limited to the human, structural, and relational capital of the firm, competitive intelligence is more outward looking, building a broadly sourced knowledge base concerning competitors. in fact, practitioners are one step ahead of academia in this application as many organizations have a connection between their knowledge management and competitive intelligence functions. in extensive depth interviews to ascertain the state of intelligence work of all types in contemporary industry, we found such an inclination to be prominent in a number of specific industries. one of these was oil and gas. while exploration, recovery, refining, transportation, and retail are all separate aspects of this broad field, it is collectively of interest, in large part because of this extensive scope. in this paper, we compare and contrast knowledge management and competitive intelligence practice in oil-based industries. in doing so, we draw upon an extensive database including financial returns of thousands of companies in a broad range of industries over a five-year period. looking specifically at industries related to oil and gas, we review data concerning the level and importance of knowledge assets in each industry. included in the database is additional information on competitive intelligence activity in each industry. we add these figures to the analysis, allowing us to assess the relative competitive intelligence threat levels. finally, we discuss the results from the depth interviews we conducted with practitioners in these industries, sharing their perspective on the nature of knowledge management, competitive intelligence, and the interplay between them in this complex industry. keywords: knowledge management, competitive intelligence, strategy, tobin’s q available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2013) 29-36 mailto:hnrothberg@aol.com https://ojs.hh.se/ 30 introduction knowledge management (km), intellectual capital, and competitive intelligence (ci) are all fields that grew up together over the past twenty-five years. a full review of all three disciplines in a short paper is almost impossible, so this literature summary will focus on some major concepts in km and ci, similarities and differences, and how the fields interact. km and its related field, intellectual capital, evolved out of an interest in determining how and why firms are more competitive in the marketplace. as an extension to the resource-based theory of the firm (wernerfelt 1984), scholars suggested that one unique, sustainable resource of the firm might be knowledge (teece 1998; grant 1996) and, indeed, this might be the only unique source of competitive advantage in the modern economy. interest grew in what an organization’s people might know and how that could be assessed, managed, and employed to best effect. intellectual capital theory and practice made up one side of this effort, specifically directed at defining and measuring the knowledge assets of the organization. these assets went beyond traditional intellectual property (patents, copyrights, etc.), including less well-defined, softer knowledge. firms like skandia (edvinsson & malone 1997), the general business press (stewart 1997), and scholars (bontis 1999) all worked at developing definitions and metrics. these and related efforts resulted in the familiar categories and concepts of human capital, structural capital, and relational capital we know today. while intellectual capital is chiefly concerned with the stock of knowledge assets, knowledge management has more to do with effectively managing and growing them (zack 1999; grant 1996). km typically focuses on the nature of knowledge assets, organizational differences, and systems to best handle these differences while gaining participation from individuals throughout the firm. regarding knowledge, the distinction between tacit and explicit knowledge (polanyi 1967) is a critical one, particularly in terms of how to best develop those knowledge assets (nonaka & takeuchi 1996). depending on the extent of tacitness or explicitness, different approaches and techniques have been developed to aid person-toperson sharing or use of more digital approaches (choi & lee 2003; schulz & jobe 2001; boisot 1995). additional knowledge characteristics that may matter include complexity and specificity/stickiness (mcevily & chakravarthy 2002; zander & kogut 1995; kogut & zander 1992). organizational variables include aspects such as the absorptive capacity (cohen & levinthal 1990) and the social capital (nahapiet & ghoshal 1998) of an individual firm. depending on the circumstances of a given organization, particular approaches to km can be chosen, including communities of practice, mentoring, and knowledge markets (brown & duguid 1991; matson, patiath & shavers 2003; thomas, kellogg & erickson 2001). each also poses its own issues with workability, including how variables such as motivation and trust can influence participation. it’s really a matter of choosing the right approach for the circumstances of the firm and can be a complex decision. competitive intelligence practice and study also grew during the past quarter century. the legal and ethical side of economic espionage, ci is the practice of collecting data and information about a competitor and/or its activities, processing and analyzing it for competitive insights, and acting on the results. as is the case with km, ci also developed around practice (gilad & herring 1996; fuld 1994) as it was being noticed by the academic community (prescott & miller 2001). scholarship on ci, much like km, has focused on sources of information/knowledge (mcgonagle & vella 2002) and techniques for using it (fleisher & bensoussan 2002). the nature of the knowledge and organizational characteristics have been less of a concern but one could certainly see the field moving in that direction for future research. of more interest to researchers are characteristics of ci teams or operations. maturity appears to matter, with ci groups expanding their human intelligence networks and adding to their own analytical capabilities (wright, picton & callow 2002; raouch & santi 2001). one place where ci has already arrived is in deeper analysis of knowledge assets. looking for 31 actionable intelligence, ci teams are charged with understanding a competitor, its current strategies, and possible future strategies and actions (gilad 2003; bernhardt 1993). km is likely headed in this direction, especially as the advent of big data and business intelligence work widens the view of valuable intangibles to include analyzable data and information. even so, km has yet to reach the same analytical level as ci. so km and ci have a number of similarities in terms of the identification and gathering of valuable intangible assets and the use of specific tools and techniques to manage them (rothberg & erickson 2005; 2002). one other important interaction is in the likely increased ci vulnerability that comes from expanded km efforts. one of the key aims of km is to make more of a firm’s knowledge stock available for use by many more employees. the result is more access points inside and outside the core company for competitors’ ci operations, with access to a greater proportion of the firm’s knowledge or information, in hard-to-monitor digital form. greater dispersal of valuable proprietary assets can make them more at risk (liebeskind 1996). as a consequence, there is a balance to be struck between development of knowledge and its protection, a balance that has only recently begun receiving scholarly attention (liebowitz 2006; rothberg & erickson 2005) this paper reports on a study to examine more closely the relationship and interplay between km and ci in practice. looking at both objective results from a substantial database of financial returns and competitive intelligence activity and more subjective responses from practitioner interviews, we can more deeply study how km and ci are managed in these closely related industries. methodology and results in looking to analyze knowledge development and protection across a number of firms and industries, one needs a tool capable of a certain amount of scope. past work (erickson & rothberg 2012; rothberg & erickson 2005) has established that differences exist on the national, industry, and firm level that impact knowledge, so using industry and firm as the level of analysis, paired with an appropriate metric, can yield the kind of information we’re seeking. indeed, by following the strategic protection factor framework, we can organize industries (and firms) by whether km is important or not to industry success and whether ci is prevalent or not. measuring the knowledge development in a firm can be done in any number of ways (sveiby 2010). micro approaches tend to add up knowledge asset components in the firm to get a sense of the total intellectual capital. given the difficulties in accessing such data, however, these approaches are usually limited to analysis of a single firm or a small group of related firms. this is how they have been used in practice (lev & radhakrishnan 2003; marr & schiuma 2001). by taking a more macro approach and using more available financial data, many more firms can be analyzed at one time, allowing comparisons across industries (tan, plowman & hancock 2007; firer & williams 2003). such metrics are more appropriate in this case. in particular, we apply a variation on tobin’s q (tobin & brainard 1977) that has been used previously in such applications (erickson & rothberg 2012; 2009). tobin’s q assesses the level of intangible assets of the firm, largely overlapping with the concept of the intellectual capital. the original value proposed by tobin was market capitalization versus replacement value of assets. replacement value of assets can be difficult to obtain, however, so a common variation is market cap to book value. for our purposes, we use market cap to asset value— the difference being that book value subtracts out liabilities giving debt levels an impact on the measure (this makes a difference for industries like financial services with huge levels of borrowed capital). we just want to know the productivity of the firm given a certain tangible asset level, borrowed or owned, so we tend to prefer the market cap to assets approach. but both are included here for context. we also employ the metric as a ratio, eliminating firm size as a potential source of bias. financial data were obtained from the i/b/e/s service, including all firms trading on north american exchanges with at least $1 billion in annual revenue. data from 2005-2009 were included with over 7000 observations from over 2000 firms. the overall average for the market cap to asset ratio for the database was 1.02. the overall average for the alternate market cap to book value metric was 2.68. firms were grouped by industry (according to standard industrial classification 32 number) and industries with at least twenty observations were included in the analysis. for this paper, we looked at industries involved in oil and gas exploration, drilling, refining, and transmission/delivery. competitive intelligence metrics were taken from a benchmarking database constructed by fuld & company, a major ci consultancy. these data were collected over a similar five-year period (20052009) and include over 1,000 worldwide respondents. we used a specific question on the maturity/professionalism of the ci function in the respondent’s organization as our indicator. ci professionals included in the results rated their group’s proficiency along a four-point scale, with 4 designating a highly developed capability and 1 suggesting a more ad hoc function. again, we could group these by industry, using the same sic codes and including specific organizations in the same place/industry in the data set. depth interviews were conducted with practitioner contacts, participants solicited from training programs conducted by the authors, and other outreach efforts. no particular targeting by industry was done, participants were selected who participate in km or ci (often both) at a senior level and with some substantive experience in at least one of the fields. semi-structured interviews were conducted focusing on km practice in their organization, ci practice, and any relationship between the two. significant probing was done to provide additional depth. results are presented in table 1. these include both tobin’s q metrics to assess the level of knowledge development required to compete in the industry (cap/assets, cap/book), our km measures. competitive intelligence activity is shown by the number of firms at each level of proficiency. a single firm at level 2 was the midpoint for the overall database, below that suggested low ci activity while multiple firms at 2 or at least one firm reporting 3 or above shows high ci activity. we also included the spf (strategic protection factor) from rothberg & erickson (2005) illustrating the competitive conditions facing each firm in terms of the combination of km and ci results. we’ll talk more about these shortly. cap/book cap/assets cap/book competitive intelligence (#firms,# respondents) spf category 1311 crude petroleum and natural gas exploration 0.85 1.85 4 (0) 3 (0) 2 (4) 1 (0) spf 30 low km high ci 1381 drilling oil/gas wells 1.37 2.25 4 (1,6) 3 (0) 2 (0) 1 (0) spf 45 high km high ci 291 petroleum refining 1.93 2.42 4 (0) 3 (1) 2 (1,2) 1 (0) spf 45 high km high ci 4922 natural gas transmission 0.58 1.82 4 (0) 3 (0) 2 (1) 1 (0) spf 5 low km low ci 4923 natural gas transmission & distribution 0.80 2.25 4 (0) 3 (0) 2 (0) 1 (0) spf 5 low km low ci 4924 natural gas distribution 0.58 1.92 4 (0) 3 (0) 2 (0) 1 (0) spf 5 low km low ci table 1: oil & gas industries, knowledge management and competitive intelligence status 33 discussion there are a number of interesting things in the data, especially when paired with some of the insights from the interviews. but, as a first pass, let’s focus on the nature of the data. the cap/asset ratio shows a range of knowledge development in the industries, some well above the overall average (drilling and refining), some below (exploration, transmission/distribution). cap/book has a similar range of results but all the numbers are below the average of the full database. so this is an application where the choice of km metric does matter and there is obviously something in the data leading to the differing results—probably the drilling and refining industries have substantially higher levels of debt, especially when compared to the transmission/distribution industries. as debt is not an important part of what we are trying to analyze, we believe the cap/asset result is the more reliable and preferred option. the ci metric shows the number of firms and individuals within the firms reporting on their level of proficiency. exploration, drilling, and refining all have higher than average levels of ci activity. in exploration, multiple firms (four) are all operating at a fairly organized level. drilling only shows a single firm reporting a ci operation but it is at the highest level and included six team members independently responding to the benchmarking study, something very unusual in the dataset. even if only a single firm, when you have someone in the industry operating at that level, it has major implications for the vulnerability of information and knowledge for everybody (as well as for the need for protection and counterintelligence). in refining, there are again multiple firms active in ci, at the second and third levels, and one of those firms again has more than one respondent. once more, this is in the upper half of ci activity for the full database. such metrics, on their face, may not seem to illustrate substantial ci operations, but the people reporting in the survey are competitive intelligence professionals, generally managers of the group. so a single responder can be indicative of a much bigger operation, particularly when reporting above the lowest level of proficiency. the three transmission/distribution industries show less activity. only one individual reports an active operation in the three industries, and that is at the next to lowest proficiency level. taken individually, all three industries are below the overall average for ci activity. in terms of the strategic protection factors represented here, the main point is that there are different industry conditions. in some industries, there is clear evidence of substantial development of intangibles or knowledge assets. firms would probably need to aggressively grow their knowledge in such industries in order to keep up with competitors. in other industries, there is no indication of significant knowledge development and so no such mandate for investment in knowledge by member firms. similarly, there are industries with heavy ci activity, industries with no ci activity, and a range of other results in between. what the spf categorization does is indicate these conditions—where km investment is important (or not) and where ci activity and/or protection is needed (or not). such evidence leads to a logical conclusion that km decisions may be more strategic than we often think (many km scholars would recommend ever more investment into development) and that a better understanding of these types of conditions could lead to better spending decisions on both km systems and ci offense and defense. depth interviews included conversations with four practicing managers working for oil and gas companies, chiefly in competitive intelligence. as might be expected, size of ci operations varied dramatically across such a small sample, from virtual teams formed for specific purposes to core groups of 30-40 to loose networks of up to 100 contributors. budgets also varied dramatically, when individuals were willing to report them, from a couple hundred thousand dollars to $75 million at one large integrated multinational. key commonalities across the interviews included the distributed nature of many of the operations, being both task specific (information on joint ventures, mergers and acquisitions, market conditions, market entry, competitor strategies) or group specific (country, function, etc.). at the same time, there was a recognition that ci functions tend to become more centralized as they matured and senior management become more convinced of their value. all of the respondents noted the often close relationship between ci and km, even if all efforts 34 to integrate the two functions weren’t successful. both functions, often managed though the same office, seek to gather information and knowledge from throughout the firm and its larger network. respondents noted a desire to incorporate the km network into ci information-gathering and also using techniques such as communities of practice to good effect in both areas. there were comments about protecting knowledge, noting that these industries tend to be leaky. as a result, although knowledge might be gathered from throughout the firm and its extended network, it was not necessarily shared back out through the whole structure. key knowledge was kept internal. what can we conclude from the data and the interviews about these industries and their wider implications? knowledge has different levels of importance at various points along the value chain, both in the firm and across the industry-wide chain. firms that have a mandate to aggressively develop knowledge will often have key knowledge present in several places along the value chain, not just in a single spot (e.g. operations). that is seen clearly in this example. the industry value chain includes exploration through drilling, refining, and eventually transmission/delivery. one could include retail as well, though separating out gas stations in the data is difficult. across this chain, the really valuable knowledge, at least from a knowledge development perspective, is in drilling and refining. this was reiterated in the interviews where those were the functions often mentioned by the respondents as being the key areas of attention for their offices. not all knowledge is equally valuable or manageable, and this is true across industries and even across an individual firm. firms integrated across several distinct functions or industries, as a number of the major oil and gas majors are, should expect to face different conditions in these different arenas. again, the value of the knowledge may differ. the range of competitive intelligence operations and activities may differ. the interplay between km and ci may differ. once more, there is strong evidence that a strategic approach is best, examining the knowledge development and protection conditions as they apply in each setting. part of that task would be understanding the type of knowledge involved. in some parts of the oil industry, the valuable knowledge is more tacit, potentially more valuable but also harder to manage effectively. tacit knowledge is also harder for competitors to take by standard ci techniques. similarly, if knowledge is more sticky or specific, it can have implications for sharing or competitive infiltration as could the complexity of the knowledge. the maturity of the industry comes into play and how much new, proprietary knowledge is being developed that is not easily available to everyone in the field. so drilling or refining, where tacit know-how can be extremely important but also quite personal, complex, and perhaps sticky poses a very different knowledge development/protection scenario than does something like transmission, where much knowledge is explicit, well-known throughout the industry, and complex but manageable using readily available logistics programs. the bottom line is, again, conditions differ, and strategists would be well-advised to understand the full conditions surrounding their knowledge development and knowledge protection decisions. conclusions this paper has looked at knowledge practices in various oil and gas industries, specifically addressing the question of whether decision-makers should take more strategic decisions regarding knowledge development and protection. while the natural inclination of most of us working in the fields of km and ci is that more is always better, both theory and practice suggest that sometimes a more measured approach may be better. knowledge has different levels of value in different industries included under the oil and gas designation. development is critical in order to compete in industries such as drilling and refining while it may be less a priority in areas like exploration and transmission/distribution. similarly, competitive intelligence can be a major threat, or not. ci activity levels are high in exploration, drilling, and refining but almost nonexistent in transmission/distribution. these industries also demonstrate an increasing integration in the km and ci operations, according to respondent reports. as a result, what we see in these industries helps to make the case for the more strategic approach to knowledge development and protection. evaluating circumstances can help in determining 35 when making larger investments in km will pay off. similarly, such strategic planning can better focus investments in ci offense and defense. taking such a wider view can help increase the odds that km and ci initiatives will actually pay off, providing greater opportunities for the disciplines to make a true contribution to modern business success. acknowledgement the authors gratefully acknowledge the generosity of fuld & company in providing some of the data used in this study. references bernhardt, d. 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(2017) integration of business intelligence with corporate strategic management. journal of intelligence studies in business. 7 (2) 5-16. article url: https://ojs.hh.se/index.php/jisib/article/view/219 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index integration of business intelligence with corporate strategic management mouhib alnoukaria and abdellatif hananoa adamascus university, syria; mnoukari@scs-net.org and d.hanano@damascusuniv.edu.sy journal of intelligence studies in business please scroll down for article integration of business intelligence with corporate strategic management mouhib alnoukaria and abdellatif hananoa adamascus university, syria corresponding authors: mnoukari@scs-net.org and d.hanano@damascusuniv.edu.sy received 2 april 2017; accepted 20 june 2017 abstract integration of business intelligence and corporate strategic management has a direct impact on modern and flexible organizations. this integration helps decision makers to implement their corporate strategies, adapt easily to changes in the environment, and gain competitive advantages. this paper extends the studies in this domain, and clarifies the relationships between business intelligence and strategic management. it highlights also the role of business intelligence in corporate performance management and strategic intelligence. this paper proposes a bsc-bi framework that facilitates the integration of business intelligence with a balanced scorecard methodology. the bsc-bi framework implementation is demonstrated using a case study on the telecom field. keywords balanced scorecard, business intelligence, competitive intelligence, corporate performance management, corporate strategic management, strategic intelligence 1. introduction dresner introduced business intelligence in the year 1989, as an umbrella term that “describe a set of concepts and methods to improve business decision making by using fact-based support systems” (power, 2007). business intelligence is an environment in which ‘marrying’ business knowledge and data mining provides great results (anand, bell, and hughes, 1995; cody, kreulen, krishna, and spangler, 2002; weiss, buckley, kapoor, and damgaard, 2003; graco, semenova, and dubossarsky, 2007). alnoukari considers business intelligence as "a framework that helps organizations managing, developing and communicating their information and knowledge. thus, it can be considered as an imperative framework in the current knowledge-based economy arena" (alnoukari, 2012). other researchers consider business intelligence as an umbrella that combines: architectures, tools, data bases, applications, practices, and methodologies (turban, aronson, liang, & sharda, 2007; cody, kreulen, krishna, & spangler, 2002; rouhani, asgari, & mirhosseini, 2012). weiss et al. 2003 define business intelligence as the “combination of data mining, data warehousing, knowledge management, and traditional decision support systems” (weiss, buckley, kapoor, & damgaard, 2003). business intelligence systems can have multiple benefits including: faster access to information, particularly big data complexes, increasing revenue, better customer satisfaction and generating or improving competitiveness of enterprises (brinkmann, 2015). knowledge management emerges in part from the thinking of the “intelligence approach” to business (marren, 2004). dedijer thinks that “intelligence” is more descriptive than knowledge. “knowledge is static, intelligence is dynamic” (marren, 2004). intelligence is "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal" journal of intelligence studies in business vol. 7, no. 2 (2017) pp. 5-16 open access: freely available at: https://ojs.hh.se/ 6 (alnoukari, 2012). the main challenge in any business intelligence solution is in its intelligence ability. this can be found in the post data mining phase where the system has to interpret its data mining results using a visual environment (alnoukari, 2012). the capability of any business intelligence (bi) solution can be measured by its ability to derive knowledge from data (azevedo & santos, 2009). the challenge in any bi solution is to meet with the ability to identify patterns, trends, rules, and relationships from volumes of information which are too large to be processed by human analysis alone (alnoukari, 2012). in summary, bi is “the use of all the organization’s resources: data, applications, people and processes in order to increase its knowledge, implement and achieve its strategy, and adapt to the environment’s dynamism” (alnoukari et al., 2008). competitive advantage has shifted from companies that focus on implementing new technologies to those that employ technology to share, manage, and increase the level of knowledge inside the organization (brinkmann, 2015). bi and analytics evolution started by dbms-based and structured content, evolved into web-based and unstructured content, and currently is based on mobile and sensor contents (chen, chiang, & storey, 2012). the business intelligence solution has three layers (azvine, cui, & nauck, 2005; baars, & kemper, 2007; shariat, & hightower, 2007). each data layer is responsible for storing structured and unstructured data for decision support purposes. structured data are usually stored in operational data stores (ods), data warehouses (dw), and data marts (dm). unstructured data are handled using content and document management systems. data are extracted from operational data sources, e.g. scm, erp, crm, or from external data sources, e.g. market research data. data are extracted from data sources that are transformed and loaded into dw by etl (extract, transform and load) tools. the analytics layer provides functionality to analyze data and provide knowledge. this includes: olap, data mining, and aggregations. data mining is a core component of this layer. data mining is the search for relationships and distinct patterns that exist in a set of data, but they are “hidden" among the huge amount of data (jermol, lavrac, and urbancic, 2003; turban, aronson, liang, & sharda, 2007). the data mining application has important results in many areas (alnoukari, and alhussan, 2008; watson, wixom, hoffer, anderson-lehman, and reynolds, 2006) including: marketing (direct mail, cross-selling, customer acquisition and retention), fraud detection, financial services (srivastava, & cooley, 2003), inventory control, fault diagnosis, credit scoring (shi, peng, kou, & chen, 2005), network management, scheduling, medical diagnosis and prognosis. there are two main sets of tools used for data mining (corbitt, 2003; baars & kemper, 2007): discovery tools (wixom, 2004; chung, chen, & nunamaker jr, 2005), and verification tools (grigori, casati, castellanos, dayal, sayal, & shan, 2004). discovery tools include data visualization, neural networks, cluster analysis and factor analysis. verification tools include regression analysis, correlations, and predictions. knowledge discovered from data mining can enhance and improve an organization’s decision making capabilities (kerdprasop, & kerdprasop, 2007). the third layer is the visualization layer realized by bi applications or portals. strategic management is a framework for decisions and actions that results in the formulation and implementation of plans to achieve a company’s objectives and setting long term directions (kruger, 2010; fries, 2006). porter (1979) summarizes strategic management basic elements as: strategy process, strategy content and strategy context. these elements provide four essential steps for strategic management. environmental scanning includes both internal and external scanning. strategy formulation includes corporate’s vision and mission, corporate objectives, strategies and policies. strategy implementation drives the strategy into action, and finally strategy evaluation and control lead monitor actual performance against desired performance, and the needed corrective actions (porter, 1979). a strategy is a fundamental framework through which an organization can maintain its continuity in the market, and maintain its adaptability to environment changes to gain competitive advantages (fries, 2006; porter, 1996). traditionally, strategy can be seen as a coherent and integrative view for decision making, or long term objectives with action plans and priorities for the corporate resource allocation. it can also be seen as a response to external opportunities and threats and internal weaknesses and strengths as well as a logical system that differentiates between managerial tasks at the corporate different 7 levels: corporate, business and functional (global intelligence alliance, 2004). lastly, different research tackles the use and importance of business intelligence in the strategy development process, and its effect in improving corporate performance in order to gain strategic capabilities (brinkmann, 2015; zoumpatianos, palpanas, & mylopoulos, 2013; seitovirta, 2011; alnoukari, 2009; bogdana, felicia, & delia, 2009; albescu, pugna, & paraschiv, 2008; elbashir, collier, & michael, 2008; pirttimaki, 2007; fries, 2006; viitanen & pirttimaki, 2006). one of the new terms that best describes the alignment between strategic management and business intelligence is strategic intelligence. it can be defined as “a systematic and continuous process of producing needed intelligence of strategic value in an actionable form to facilitate long-term decision making” (global intelligence alliance, 2004). strategic intelligence focuses mainly on supporting strategic decision making by introducing intelligence to the strategic values. it provides a big picture about the business environment and benchmarks corporate operations. strategic intelligence can contribute in strategic management by collecting, analyzing and distributing of information (seitovirta, 2011). kruger considered strategic intelligence as a combination (in terms of information) between business intelligence, competitive intelligence, and knowledge management and it acts as a powerful input to strategic management. strategic management can assist in identifying opportunities, and add value to the organization’s decision making capabilities (kruger, 2010). strategic management requires many indepth analyses including: impact analysis, what-if analysis, business driver analysis, and critical strategic themes analysis. different roles were identified for strategic management, such as defining and providing a forecast for the competitive environment, underlying management assumptions which may impact strategic thinking, identifying and assessing the company weaknesses against the market opportunities and threats, implementing and adjusting the strategy in response to the changes in the competitive environment, and determining when the strategy is no longer sustainable (global intelligence alliance, 2004). thus, strategic intelligence covers many concepts from business intelligence, competitive intelligence and competitor intelligence. the aim of this paper is to make a significant contribution to the research in this domain. first, it extends previous business intelligence studies by providing a framework that can integrate research solution with strategic management using an exploratory approach. our systemic overview builds on prior research within this domain, but recognizes the evolution of business intelligence to include analysis and strategic management. this study builds on previous research that highlights the use of business intelligence solutions for achieving organizational strategies (alnoukari, 2009). 2. the integration between business intelligence and strategic management business intelligence as a strategic framework is becoming increasingly important in strategic management and in supporting business strategies. it can be considered as one of the most important technologies that allows managers and end users to convert masses of non-transparent data into useful information that provide companies with huge capabilities. these technologies help coordinating projects, and schedules, and provide the roadmap to align with the corporate strategy. business intelligence as an analytical tool changes internal and external data into an appropriate knowledge that supports the decision making process. business intelligence combines operational data with the analytical tools to provide corporate planners and managers with competitive information. for this reason reserachers consider business intelligence as a competitive differentiator (brinkmann, 2015). strategic management addresses the it role in the strategy formulation and implementation processes (tang & walters, 2006; shadid, 2012; zoumpatianos, palpanas, & mylopoulos, 2013). strategic management theories are largely geared towards gaining competitive advantages. porter proposed a five-forces model of competition, value chain and generic competitive strategies between many of very influential strategic analysis models (porter, 1979). flexible organization is based on it alignment with business strategy. as a result of acceleration in the rate of innovation and technological changes, markets evolve rapidly, products’ life cycles get shorter and innovation becomes the main source of competitive advantage (järvinen, 2014). it alignment with the business strategy to enhance corporate 8 strategy was highlighted by many researchers (boddy, boonstra, & kennedy, 2005; sabherwal & chan, 2001). the strategic alignment model was one of the first models that described in an explicit way the relationship between business strategies and it strategies (grembergen, haes, & guldentops, 2004). the strategic alignment model is based on the strategic fit that recognizes the need to position the firm in an external marketplace where growth can take place, and the functional integration, which addresses how to best structure internal systems to execute the business strategy of the firm (katz, 2002). it alignment is not only formulating it strategy to fit business strategy. it has to consider external forces and the environmental uncertainty. therefore, organizations seek flexibility to meet market demands. flexibility-based perspectives were evolved from schumpeter’s concept of creative destruction (drnevich, hahn, & shanley, 2006). operationalization of these perspectives in strategic management can be achieved through dynamic capabilities and real option views. a dynamic capabilities view refers to a firm’s abilities to maintain and adapt its internal resources to environmental changes to maintain sustainability of the competitive advantages. it refers to the capability of acquiring new modes of competitive advantage. it involves continuous searching, innovation and adaptation of firm resources and capabilities to uncover and tape new sources of competitive advantages. the real options view is effective in dealing with issues of uncertainty. it allows the firm to defer investment decisions until uncertainties are resolved (drnevich, hahn, & shanley, 2006). business intelligence facilitates the transition into flexible organizations as it is becoming a source of competitive advantages and differentiation (herring, 1988; pérezvalls, ortega-egea, & úbeda, 2006). there are many reasons for organization to adopt business intelligence in order to improve organizational strategy. it is considered as an extension to corporate strategy activities (herring, 1988; viitanen & pirttimaki, 2006). zoumpatianos et al. (2013) argue that a complete business intelligence problem begins with the modeling and analysis of corporate strategies and objectives (zoumpatianos, palpanas, & mylopoulos, 2013). business intelligence dashboards and reports can easily provide strategic management with important strategic information such as trends, production evolution over time, historical evolution of market share, demads forecast, and market segmentation (fries, 2006). data analytics and data mining could be used effectively to build future business strategy, and could reveal hidden reasons for some deficiencies as well as possible high-yielding new investments. corporations need to be sure that they are receiving the right information related to their long-term strategy. in conclusion, business intelligence helps organizations in supporting their strategic decision making process, including corporation swot analysis and strategic planning (herring, 1988; zoumpatianos, palpanas, & mylopoulos, 2013). all the mentioned benefits should provide organizations with sustainable competitive advantages. zoumpatianos et al. (2013) propose an integrated system based on swot analysis findings and a query engin that can monitor and evaluate the corporate strategic objectives and goals. a data warehouse based query is used to coninously monitor the corporate strategic acheivement. this system can provide answers to a trend query like the following: "will the current sales trend that we observe up to now, within a time window w, in the market segment s help us to achieve the goal of increasing our market share by 5%?" zoumpatianos et al. (2013) argue that this system is able to find objectives trends and monitor the expected and unexpected threats and opprtunities in the data warehouse as well as their causes (zoumpatianos, palpanas, & mylopoulos, 2013). corporate performance management is considered as one of the strategic management tool that includes: planning, measurement and analysis steps. business intelligence contributes to corporate performance management and especially to measurement and analysis practices by enhancing access to performance information, and supports decision making in each step of the corporate performance management cycle. the effectiveness of business intelligence implementation would affect the effectiveness of corporate performance management related planning and analytic practices (richards, yeoh, chong, & popovič, 2014). bogdana et. al (2009) propose a framework for integrating corporate performance management with business intelligence. the framework integrates corporate objectives using scorecards and dashboards using business intelligence tools at a strategic level, with the 9 aim to support business measurement at the tactical and operational level (bogdana, felicia, & delia, 2009). corporate performance management is thus considered as the combination of business intelligence, scorecards, and profiling. vuksic et al. (2013) demonstrated using a case study on the croatian telecommunications industry the importance of implementing corporate performance management and business intelligence initiatives together in order to achieve better firm performance. they demonstrated the importance of the alignment between corporate performance management and business intelligence initiatives in order to resolve any data problems by creating one integrated data architecture; which would make business more effective (vuksica, bacha, & popovic, 2013). business intelligence tools could be integrated into an operational process, or monitor the output of a process or series of processes (elbashir, collier, & davern, 2008). business process outputs are often linked to business objectives that are usually aligned with an organization’s strategy. the main role of business intelligence is to provide the information on the accomplishment of the corporate objectives, thus allowing the managers to analyze performance gaps, and improve their understandings of organizational outcomes (watson, et al. 2006). according to the performance gaps, managers can take corrective actions. they might update the related objectives, or take special steps to improve the processes to better achieve the objective. in conclusion, business intelligence could be integrated in some situations into a process to automate certain type of decisions, or could be used in other situations to provide the needed information to monitor the output of a process (elbashir, collier, & davern, 2008). business process management and business intelligence are highly connected for the purpose of improving corporate performance (vuksica, bacha, & popovic, 2013). although business process management focuses mainly on business process while business intelligence focuses on business performance, they can together provide better results for corporate performance management. business intelligence improves corporate effectiveness by focusing mainly on sales, marketing and customer information, while business process management improves corporate effectiveness by focusing mainly on improving corporate processes as they generate most of the cost of any business. business intelligence provides the business process management with the detailed data needed for information consistency and data quality. thus the integration of business intelligence and business process management initiatives are vital for improving corporate effectiveness (vuksica, bacha, & popovic, 2013). the most important component for the success of any modern organization is its ability to take the benefits of all the available information, internally and externally, using structured data management systems (business intelligence) or unstructured content management systems (knowledge management). both hybrid technologies, business intelligence and knowledge management, are widely known as competitive intelligence (albescu, pugna, & paraschiv, 2008). competitive intelligence is the analytical process of collecting, selecting, and interpreting all the information related to business competitors in order to emphasis their positions, capabilities, performances and results and in the market. the society of competitive intelligence professionals defines competitive intelligence as: “timely and fact-based data on which management may rely on decision-making and strategy development. it is carried out through industry analysis, which means understanding the players in an industry; competitive analysis, which means understanding the strengths and weaknesses of competitors; and benchmarking i.e. the analysis of individual business process of competitors” (olszak, 2014) the core advantage of any competitive intelligence system is to extract the knowledge needed about competitors’ opportunities and threats. in this context, competitive intelligence provides external environment scanning, whereas business intelligence provides internal environment scanning. the cross analysis of information provided can be used efficiently in many strategic analysis tools including: swot analysis, industry analysis, and competitor analysis (albescu, pugna, & paraschiv, 2008). different types of tools can be used to build competitive intelligence including: data mining, text mining, web mining, dashboards, balanced score cards and others (olszak, 2014). 10 the integration of business intelligence and competitive intelligence can be used to formulate a corporate mission, long term objectives, strategies and policies. business intelligence technology can be used effectively to provide corporate performance results (figure 3). corporate performance management is used to evaluate program or project evolution, and also to monitor and control them. 3. bsc-bi: a framework for business intelligence integration with strategic management balanced scorecard is an important managerial tool that helps organizations to articulate their strategy into actionable initiatives and projects. in addition, it provides the roadmap for strategy implementation, execution, monitoring and control (olszak, 2014). balanced scorecard is an important tool that helps top management to indicate the right strategic decisions to take. balanced scorecard translates corporate vision and strategy into action, information, and intelligence (fries, 2006). balanced scorecard considers that corporations have four main perspectives: financial, customer, internal business processes, and learning and growth. financial measurements are the most important driving factors for top management to evaluate the company’s position in the market. customer measurements such as customer focus and satisfaction are used to evaluate the company image. internal business process measurements allow managers to monitor and evaluate business processes whether they cover all required and predefined customer needs. employee learning and growth measurements are mainly used to evaluate the company commitment to its long term strategy in terms of its human resources. knowledge management is the main pillar in building such corporate capacity. business intelligence reports can track the number of relevant trainings undertaken by each worker. results of such reports can be matched with the predefined corporate objectives via balanced scorecard (fries, 2006). most strategic analysis tools, such as scenario analysis, swot analysis and demands forecasts, can be easily supported by a combination of data mining tools such as regression analysis, decision trees, and neural networks. many types of analysis such as customers’ buying behaviors, inventory slow turn, and product market share could support discovering internal strengths and weaknesses. data mining helps detect new customers or competitors. such data provide inputs for opportunities and threats. in conclusion, business intelligence, and especially data mining can reveal important inputs to swot analysis. olap (online analytical processing) functionalities facilitate detecting problem areas, and focus more on the problem’s root causes. neural networks could detect the relationship between trends and huge amount of external data. forecasting can be more accurate to define more possible scenarios. decision trees could classify relevant future situations in order to be able to calculate the risk of any scenario. all these business intelligence tools, techniques and applications could contribute efficiently to the design of a scenario analysis. they can specify the realistic and relevant scenarios in many cases. business intelligence results should be matched against predefined and measurable objectives. kpis (key performance indicators) are used for the analysis of reaching goals and objectives (fries, 2006). business intelligence reporting tools and olaps contribute to strategic management as they measure the organization’s performance. balanced scorecard can be introduced to indicate weather business intelligence reporting matches critical performance indicators. figure 1 presents an overview of the corporate challenges of an organization on the basis of its business strategy using the four strategic themes, based on the balanced scorecard methodology. although strategy plays an important role in modern organizations, it is a process in nature and has become more customer-focus. modern organizations are seen as knowledge-based enterprises in which proactive knowledge management and strategic business intelligence are important for competitiveness (brinkmann, 2015). strategic business intelligence technologies support or change the enterprise’s strategy in which they are utilized to increase the reaction time to environmental changes and to assist the company to achieve its capability (alnoukari, 2009). business intelligence integrates information utilities and a decision support system that can help organizations to manage, develop, and communicate their intangible assets such as information and knowledge. thus, it can be considered as an imperative framework in the current knowledge-based 11 economy arena (alnoukari, 2009). business intelligence implementation and enhancement will evolve as the organization becomes more competent in process and technology. changes in the positioning in the market and the organization’s strategy will be implemented more effectively in such flexible and modern organizations (brinkmann, 2015). business intelligence should be embedded within the organization and its objectives and strategies, and their benefits should be clarified and communicated. the bsc-bi framework clarified in figure 1 is based on previously suggested frameworks (brinkmann 2015; gonzales 2011, albescu et al. 2000). it combines and integrates an organization’s success factors in order to maximize both its users’ and corporate performance. the framework incorporates different types of business intelligence techniques including: planning, predictive, explorative, and standard applications in order to provide the main requirement and installation to back up an efficient strategic and operational reporting. business intelligence excellence can be achieved when organizations properly define their strategies, implement learning for their people, put their processes in track, and provide the needed technologies. business intelligence excellence would have significant results on business impact, value and effectiveness (brinkmann, 2015). bsc-bi effectively integrates business intelligence technologies into the strategy development process. the main strategic business intelligence competitive intelligence internal scanning external scanning market position value chain cost structure core competences specific assets industry attractiveness market development customer segmentation consumer behavior competitor comparison strengths weaknesses opportunities threats customer finance internal business processes learning & growth balanced scorecard programs & projects – finance & budget – process & procedures km key performance indicators implementatio n evaluation analysis: predictive explorative planning standard bsc-bi figure 1 bsc-bi framework, the integration of strategic intelligence with balanced scorecard methodology 12 themes are incorporated and improved in order to strengthen the organization’s long term success. this could be achieved when the strategic themes tend to deliver greater value to customers at lower cost. when these themes are properly implemented, organizations increase their profitability results. therefore, strategic themes could be used to observe markets and competitors, and enable top management to continuously adjust their strategies when the environment changes. the use of business intelligence for corporate objective-setting is based on the tools that provide historical data that directly inform the setting of objectives for subsequent planning periods. business intelligence tools conduct internal environmental scanning activities, whereas competitive intelligence tools are used to conduct external environmental scanning activities as part of the planning practices. the bsc-bi framework is able to test past activities against planned results and use the findings for setting objectives. cause-effect analysis tools help to find the processes that most significantly impact organizational outcomes, thus allowing for process improvement. 4. bsc-bi framework implementation – syriatel case study syriatel is one of the largest telecommunications companies in syria. the company started using the balanced scorecard approach in 2008. the company relies on setting general goals approved by the board of directors, to construct its strategic objectives. these objectives are created to achieve sustainability, excellence in services, optimal performance, and building people. the strategic objectives are linked to the corporate objectives, then build up the unit objectives at each department, then cascading them to the employee-objective level. most successful companies seek to change their strategies to move from the current position in the market to a better one. this transition usually requires taking administrative procedures. it is customary to take these procedures after the measurement and evaluation. the evaluation process is based on answering several questions, including: • what is the current position of the company in the market? • what daily operations are implemented to achieve the desired goals? • what is the future plan to achieve more of the desired goals? the corporate strategic plan is built according to the organizational structure. syriatel strategic objectives are managed using a system named the objectives cascading management system (ocms). the company's departments share most of its corporate objectives, each department has a set of units, and each unit comprises sections that include a group of staff objectives. the strategic plan is built on a set of objectives to figure 2 bi dashboard for the power source losses in all sites. 13 be achieved at all levels. these objectives are smart, this means that the set of objectives should be specific, measurable, achievable, realistic, and set within a specific time. each department sets its objectives, which are combined with the objectives of its units, and achieve hierarchically the goals of all subdivisions. key performance indicators (kpis) are used to measure objective performance. business intelligence is a crucial system in the company. it helps to identify problems and weaknesses. applying the bsc-bi framework provides the company with the capability to integrate between business intelligence and its strategic management system (ocms). one of the fruitful results of this integration is identifying the losses that result from the interruption of electric current for each of the company sites, and the alternative solutions used to reduce this interruption (figure 2). the system registers the sites where frequent feeding breaks occur, and exceeds the predefined number of hours, then classifies it as a new weakness point at the corporate level according to predefined performance indicators. then, the system registers a set of actions to follow up in order to achieve the goals that have been generated, and monitor them periodically. in addition, it identifies the kpis to help monitor the level of performance until achieving the set objectives completely (figure 3). as a results of applying a bsc-bi framework, the number of stop hours decreased in all sites from 59,000 hours during february 2016 to less than 3,000 hours during august 2016. this decrease helps in achieving the company's "network sustainability" kpi. 5. conclusion business intelligence activities and their intentional use are considered to constitute a relatively young discipline. they have connections with several functions in organizations, especially finance, marketing, and strategic management. it was clear that business intelligence has does much more than simply refining raw data into reports and dashboards that could be provided to top management with the ability to take the right decisions. information and knowledge provided could have a direct impact on several factors related to intangible assets such as know-how, innovativeness, and market properties. business intelligence tends to provide the basis for continuous and proactive control, and for the optimization of a company’s shortand long-term success in a dynamically changing business environment. business intelligence has a direct impact on business strategies, and provides top management in modern and flexible organizations with the needed tools and technologies to formulate corporate strategies, implement, and monitor them using corporate performance management tools. in this article, we explored the relationships between business intelligence, competitive intelligence, and strategic management. then we explained the impact of business intelligence on corporate performance figure 3 corporate objective created using the bsc-bi framework. 14 management, operational business process, and strategic intelligence. we proposed a new framework "bsc-bi" that uses business intelligence and competitive intelligence capabilities to build corporate swot analysis, and develop corporate objectives using the balanced scorecards methodology. validating the bsc-bi framework was done using a case study on one of the biggest mobile telecom company in syria. direct results were achieved using this framework that integrates business intelligence tools with a balanced scorecard methodology used for strategic planning. 6. references albescu, f., pugna, i., & paraschiv, d. 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(2013). strategic management for real-time business intelligence. in m. castellanos, u. dayal, & e. a. rundenst, enabling real-time business intelligence (pp. 118-128). springer. issn: 2001-015x v o l 3 , n o 1 ( 2 0 1 3 ) c o n t e n t s a. fatti and a.s.a. du toit competitive intelligence in the south african pharmaceutical industry pp. 5-14 p. jenster and k. solberg søilen the relationship between strategic planning and company performance – a chinese perspective pp. 15-30 a. momeni and m. mehrafzoon critical factors of competitive intelligence in the power plant industry: the case study of mapna group pp. 31-43 k. solberg søilen an overview of articles on competitive intelligece in jcim and cir pp. 44-58 o p i n i o n s e c t i o n magnus hoppe the intelligence worker as a knowledge activist – an alternative view on intelligence by the use of burke’s pentad pp. 59-68 ~ 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2013 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : way chen, china institute of competitive intelligence (cici) raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden dr. sofiane saadi, directeur général du laboratoire en organisation et gestion des entreprises (loge) algeria. managing director nt2s consulting inc. north vancouver, bc, canada javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/3') 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pleased to offer another series of research articles within the area of intelligence studies in business. the articles represent as always a number of different approaches and problems. the article by fatti and du toit on competitive intelligence in the south african pharmaceutical industry confirms the idea that ci by now is a well-established field of interest in companies. the article goes on to propose a series of suggestions for how to improve the ci function for these companies. the article by jenster and solberg søilen is a quantitative paper on the correlation between strategic planning and company performance for chinese companies. the research confirms that the ci function is more important for company performance than the other variables and functions that were measured. the article by momeni and mehrafzoon identifies a number of key success factors for the ci function in the power plant industry in iran. seven factors are identified in the study. the article by solberg søilen is an overview of articles published in the journal of competitive intelligence and management and competitive. the article shows where articles are from, what topics are most popular, what background authors have and to what extent they define future research. the article by hoppe is about the methodological direction of intelligence studies, and is placed in the opinion section. by using burk’s pentad the author brings a series of new perspectives to intelligence studies in general. we hope you will enjoy these quite different contributions. on behalf of the editorial board, sincerely yours, dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 page 4 editors note vol 7 no 2 editor’s note vol 7, no 2 (2017) how companies work and fail to work with business intelligence most papers in this issue deal with different sides of business intelligence systems. empirical data from a number of countries and companies are gathered to illustrate how companies work and fail to work with competitive intelligence. the paper by alnoukari and hanano, entitled “integration of business intelligence with corporate strategic management,” deals with the relationships between business intelligence and strategic management. the paper proposes a bsc-bi framework that facilitates the integration of business intelligence with the balanced scorecard methodology using an example of a case from the telecom industry. the paper by jürgens, “patent bibliometrics and its use for technology watch,” is on the topic of technology watch and statistical analysis of patent information and proposes patent indicators for technology watch activities, which are classified into four categories: performance, technology, patent value and collaboration indicators. the case of nanotechnology for a whole country is applied as example. the paper by søilen, “why care about competitive intelligence and market intelligence? the case of ericsson and swedish cellulose company (sca),” tries to answer that question with an example of two swedish companies. the history of the intelligence function in private companies is compared to that of state and military organizations. the most interesting question turns out to be why more companies don't pay attention to ci and mi when so many arguments speak to their advantages. the paper by gauzelin and benz is entitled “an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france”. this empirical study examines the impact of business intelligence systems on organizational decision-making and performance. they found that when bi systems are deployed in smes, they facilitate timely decision making, improve organizational efficiency, enable a company to meet client’s needs appropriately and lead to more satisfied employees. the paper by langlois and chauvel is entitled “the impact of supply chain management on business intelligence”. the authors argue for why it makes sense to see the bi function as an extension of supply chain management, but moreover they show how difficult it has become to separate bi from other it intensive processes in the organization. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles and to the swedish research council for continuous financial support. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2017 jisib, halmstad university. all rights reserved. journal of intelligence studies in business vol. 7, no 2 (2017) p. 4 open access: freely available at: https://ojs.hh.se/ vol6no3paper5 kss to cite this article: søilen, k.s. (2016) economic and industrial espionage at the start of the 21st century – status quaestionis. journal of intelligence studies in business. 6 (3) 51-64. article url: https://ojs.hh.se/index.php/jisib/article/view/179 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index economic and industrial espionage at the start of the 21st century – status quaestionis klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: geospatial analysis of census data for targeting new businesses using geoeconomics business intelligence through patinformatics: a study of energy efficient data centres using patent data nishad deshpande, shabib ahmed and pp. 13-26 alok khode cross-cultural strategic intelligence solutions for leveraging open innovation opportunities journal of intelligence studies in business v ol 6 , n o 3 , 2 0 1 6 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 6, no. 3 2016 alexandru capatina, gianita bleoju pp. 27-38 and kiyohiro yamazaki business intelligence evaluation model in enterprise systems using fuzzy promethee mansoureh maadi, mohammad javidnia pp. 39-50 and malihe khatami sushant k. singh pp. 5-12 economic and industrial espionage at the start of the 21st century – status quaestionis klaus solberg søilen pp. 51-64 economic and industrial espionage at the start of the 21st century – status quaestionis klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se received 2 october 2016; accepted 15 december 2016 abstract this article is a literature review where the aim is to define a status quaestionis for the field of economic and industrial espionage. history shows how those who engage in these activities often are the scientifically and industrially weaker party, the party that is learning or trying to catch up. on a global scale economic and industrial espionage can be seen as a form of involuntarily sharing that has a series of positive results for economic development. on the scale of the individual businesses attacked, and for tax authorities in those countries, it is a troublesome phenomenon that must be regulated and punished. governments must prepare society for systematic and frequent cyberattacks. private companies are wise to move to stricter security controls, which must include encryption. a number of specific research projects are suggested throughout the article. in the literature we have identified the following agent motives: the employee who needs money, has split loyalties, leaves angry, the occasional thieve and the professional spy. keywords economic espionage, hacking, industrial espionage, literature review, signal intelligence 1. introduction about ten years ago in 2005 i defended a doctoral thesis on industrial espionage in germany (solberg søilen, 2005). now the question arises: what has changed in this field over the past decade? a quick look shows that the capabilities and practices have seen a degree of change that is nothing short of a revolution. in the late 1990s, when i did most of the literature research, government institutions were lagging far behind in technology. private companies were dominating the field with customer relation management (crm), business intelligence (bi) and what was to become data mining (dm). the important technical contributions all came from different private actors, but it was made possible by massive government funding. it is a myth that the internet was created within the military. espionage companies were suddenly doing what only states had done previously. after the cold war thousands of spies had been dismissed and were seeking jobs in the private sector, a reason why there is still a concentration of corporate espionage consultancy around langley, virginia, usa. this was a period of private intelligence gathering. many of the ideas about gathering large amounts of data on users grew out of the marketing field and were related to customer loyalty programs, bonus cards and in-depth customer segmentation. my dissertation was about industrial espionage in trade negotiations. negotiations are still a primary target for agents but the field has been vastly expanded. just like then, companies today are still poor at detecting and stopping attacks, preferring to simply fire the alleged culprit hoping to avoid negative journal of intelligence studies in business vol. 6, no. 3 (2016) pp. 51-64 open access: freely available at: https://ojs.hh.se/ 52 publicity (schultz, 2001, p. 202). there is always a fear that admission of breach may lead to loss of confidence and lower share price. so the stories seldom become public, if they are not leaked by state intelligence organizations or spread as anecdotes by retired executives at cocktail parties. spying on allies for economic gains has been normal practice within europe for many years, especially ahead of major european summits (corera, 2016, p. 361). german intelligence can detect increased activities before commercial negotiation with the chinese. most of the attacks are traced back to the same cities: beijing, shanghai and guangzhou (corera, 2016 p. 242). at other times, hacking attempts have come from hainan, which is the headquarters of signals intelligence for the people’s liberation army (pla). other attacks come from chinese universities and may be just for practice. western adversaries are engaged in many of the same practices. for spies, the use of the computer is far safer and less risky than snooping around in person. when we copy from a personal computer instead of stealing a briefcase we do not leave a trace if we are good, so it’s an attractive form of espionage. it’s also difficult to separate good from bad guys on the internet, which makes the place a natural environment for deception schemes. our computers are faced with possible hacking (mainly fishing) attacks every day. this has become normal. computers are simply not safe. even though safe email services exist, like phil zimmermann’s prettygoodprivacy (pgp), created in 1991, which caused no end of panic in the us government and the us naval research laboratory’s tor, companies are slow to adopt it, maybe because they find it difficult to use or are afraid that the messages cannot be opened by the receiver or will arrive much later (schultz, 2001, p. 206). before we look to the literature and the discussion it’s necessary to give some background to the field of economic and industrial espionage to describe current capabilities. 1.1 definitions capabilities for economic and industrial espionage economic espionage (also government espionage) is a government’s efforts to collect information, appropriate trade secrets, and steal knowledge (nasheri, 2005). industrial espionage is the same, but without direct government involvement. information warfare (also cyberwar) on the internet, as conducted by the military, is a version of economic espionage where the primary aim is first of all to destroy vital infrastructure in another country, not to steal company secrets or help companies become more competitive. private companies gather their data either from the traces we make when we engage on their sites or by active searches on the internet, such as when we look up a name on a site. governments gather their data by controlling the entry points where the internet is brought into a country, by setting up black boxes inside of telecom companies and by tapping data directly from the databases of private companies like microsoft or facebook by forcing them to build side doors (in the us this is controlled by the 2008 foreign intelligence surveillance act). fisa says the government has the right to collect any data that comes through your software program and that you are obliged to facilitate this gathering. they also get data through a system of information exchange with other countries. private telecom, internet and software companies cooperate with their national intelligence organizations because they know they have to in the end, or because the government is a major customer or out of some feeling of patriotism. the public at large is unaware of these deals and forms of cooperation. in the end, the internet is a physical infrastructure consisting of cables and routers. more than 90% of the world’s data pass through fiber-optic cables (corera, p. 306) and the us (most of the rest pass via other ukusa member states). foreign powers can now break into anything that is connected to the internet. with the help of traditional agents (carrying malware on a usb stick) they can also break into closed systems. of concern to private organizations is that this knowledge is just as easily available to their competitors. an important strategic advantage is related to who can supply the cables and internet infrastructure. today there are only two companies that are suppliers of complete telecoms networks in the world: huawei and ericsson. the us has made a point of not letting huawei in to the us due to allegations that it’s a spying tool for the chinese government. the only evidence so far is that the nsa has spied on huawei since at least 2007 (corera, 2016, p. 373). huawei may soon 53 be the only major supplier that can set up and run a telecoms network from scratch if ericsson is outcompeted, as is indicated by recent sales figures and economic results. we do not know what huawei will be like in the future, once it has established its role as the dominant supplier. all this raises a number of questions as to how companies can protect their secret information. the aim of this paper is to try to define a number of these questions for future research based on a literature review of scientific papers and books published during the past ten years (the research gap) followed by a lengthy discussion on some key issues. 2. method how does one perform research into economic and industrial espionage? is it even possible? most sources are based on interviews with employees of western intelligence services and will naturally be skewed in that direction, for example showing how they never engage in economic espionage themselves but try to stop it when it comes from other, unfriendly nations. the us-and-them rhetoric is strong in these sources (mainly books). all services systematically exaggerate the dangers coming from other countries to obtain larger budgets and employ more staff. the assumption here is that one party is predominantly good. compared with current as well as historical events of aggression between states since the second world war it’s difficult to make this claim stick. thus, this method can at best be seen as telling one side of the story. the companies themselves do everything in their power not to tell stories about when they are hacked or cheated as it is considered negative publicity. when authors or researchers do get access to information about industrial espionage inside of companies they have typically had to sign hefty confidentiality agreements. thus the names of real companies and people are hidden and the stories are one-sided. one solution to these biases is to set up laboratory experiments where the subjects do not know what is being measured (contrived study setting). laboratory experiments can be set up as a role play with case studies indicating different roles. the easiest way of running such experiments is with graduate students, but they are not representative of the population we are trying to measure. to strengthen the reliability of the findings such studies can be supported by running the games inside of real companies. a further layer of extending redundancies in method can be done by comparing these results with interviews of executives (solberg søilen, 2005). using the laboratory experiment, a multiple crosssectional study with constructs measured at multiple points in time and the use of different samples may be imagined. the method is far from perfect when it comes to eliminating biases but relatively good given the nature of the object studied. when writing on a sensitive issue there is often a considerable delay in the empirical data presented: a story is often first leaked many years after an incident happened. thus publications today typically reflect a reality that is no longer existent. the more technology that is involved in the problem statement the more prone the answers are to be outdated by the time of publication. in general, however, a number of research strategies are possible: experiments, survey research, observation and case studies. for this paper a combination of literature review and discussion is chosen to try to define a status quaestionis for the field. the aim is to identify a series of new and interesting research problems. as such this paper may be seen as a first step in hypothetic-deductive research. the nature of the subject is more open for exploratory and descriptive research. web of science renders 104 references on the topic of industrial espionage. forty of these are articles, and, most (8) are written for the study of history. from these the author selected and read little more than two dozen articles based on their relevance for business studies. these and related topics are discussed and future studies defined. 3. literature review thorleuchter and poel (2013) confirm that government and industrial espionage has become an increasing problem for governments and corporations. an article in the journal of professional engineering (2007) describes how the international bar association has warned that businesses are more at risk than ever. this development has been facilitated by users having weak passwords for their systems, a problem identified more than fifteen years ago by schultz, (2001) and still a major culprit. thus there are several articles that confirm the existence, the degree and some of the causes of the problem. other articles focus on solutions. lee (2015) attempts to show how criminal profiling can be used to prevent industrial 54 espionage. an empirical analysis from south korea published by the national intelligence service (nis) shows that leaks from big companies come from current employees and from ex-employees in 47.8% of the cases each. for small and medium sized companies the numbers are 5.1% and 71.8% respectively (p. 1693). this means that for small and medium sized companies the problem is basically exemployees, but that in big companies there problem is evenly spread. it means that for small and medium sized companies the problem of leakages is so small that it may not require our attention. if this data is reliable and applicable to other countries the findings are of great interest. meyersson and glitz (2016) are interviewed in hbr about a large empirical analysis done with data from the ddr during the period 1969-1989, which found that east germany enjoyed significant economic returns from its government espionage. more interesting, the authors suggest that the ddr was so successful with industrial espionage that it may have crowded out standard forms of r&d (p. 30). for example the ddr was able to reverse engineer the ibm 360 in 1970 so that a company from dresden was able to make 100 computers per year three years later (p. 31). the authors suggest that this strategy may lead to less r&d by a group’s own efforts and therefore an industrial decline in the long run for nations faced with free competition. this raises a strategic question as to which countries, and maybe more interesting for business studies, which industries and companies, are to gain the most by espionage. economic and industrial espionage finds interest among a variety of schools of economics, and solutions are suggested using different scientific methods and approaches. for example barrachina et al. (2014) make an elaborative attempt of a game theoretical approach to economic espionage that show in which case espionage can make the market more competitive. another highly analytical paper is presented by ferdinand and simm (2007). they analyze industrial and economic espionage as a form of learning. for example chinese students come to the west to learn as much as possible. the work of ferdinand and simm (2007) builds on greve (1998), kraatz (1998), and baum et al. (2000), who describe how organizations learn from their competitors. following the work of bapuji and crossan (2004) ferdinand and simm (2007) analyze espionage as a form of external learning (el) without collaboration, what they also call larcenous learning (ll). this may be a fruitful approach as it gives insights into the motives of much industrial espionage. it is also a constructive conceptual way to avoid the complicated moral discussions which tend to go nowhere (not that they are not important). as argued by polanyi (1967), stealing knowledge may in itself be insufficient if we do not have the ability to apply it. attempts of theft are therefore often followed by attempts to hire key personnel and make other prearrangements. sometimes in history this has even come to include kidnapping (decamp, 1974, cipolla, 1993). from a strategic perspective this means that espionage should not be seen as an isolated phenomenon, but as a plan for r&d that includes other elements in conjuncture. the question is what elements do you need in addition to the secret information? according to cotte (2005) technological eve is a precondition for innovation and therefore also for efficient espionage, the importance of which the author considers to be exaggerated, almost a quasi-mythical phenomenon. according to a study by sivanesan (2011) agents are normally recruited from science and technology academia. today preparations for identifying and locating potential agents are normally done on the internet. as an example, linkedin is frequently used for this purpose. an initial contact and follow ups are often made on this and similar sites. in the old days recruiting agents used to be a risky and time consuming exercise (instructions though classified ads in a newspaper, etc.). intelligence services are patient and can spend months cultivating a relationship before they find a way to persuade the agent to hand over valuable information, but this is also a more costly process. often agents contacted in this way do not know that they have been recruited as spies, but think they are part of a normal market research or consultancy job outsourced to some entity. again the internet shows itself as an arena for deception. universities are an especially attractive target, as they, by definition, contain a concentration of knowledge workers with access to cutting edge research. a question that arises is which countries are pointed out as economic spies in the literature? sivanesan (2011) claims they come from russia, china, and more generally from the middle east, asia and north africa. another approach is to define who has the capabilities to perform economic and industrial 55 espionage and assume that these are being or will be used sometimes in future, for example under another head of state. new political leadership can lead to increased economic and industrial espionage. but the internet can also help a new group of politicians get elected. a reoccurring topic today is whether false information and disinformation threatens the political model of democracy. companies operating on the internet pay little attention to if information is true for false. instead they tend to put all focus on internet traffic; that is how many users they have. false stories are spread just as quickly as and sometimes even quicker than true stories. for example facebook has been criticized for facilitating spreading false information as news during the last political election in the us between hillary clinton and donald trump. agents of false news use twitter and other networks to create fake accounts that spread untruths or inject fraudulent chatter into the conversation. dictatorships have been known to create fake videos and images and upload them to youtube and other websites in the hope that news organizations and the public will find them and mistake them for real (silverman, 2012). the companies themselves refer back to the freedom of press and argue that censorship is not something they can or will engage in. at the same time never before in the history of journalism have more people and organizations been engaged in fact checking and verification. never before has it been so easy to expose an error, check a fact, crowdsource and bring technology to bear in the service of verification. a politician or public figure who publicly asserts a falsehood is likely to be called out by fact-checking organizations such as factcheck.org. the problem is that rumors and falsehoods spread just as quickly, if not faster than, facts. in many cases they prove more compelling, more convincing, and more are more clickable. this development threatens democratic values and the electoral outcome of political elections, the argument goes. research by nyhan and reifer (2015) suggests the internet may be ineffective at reducing public misperceptions about controversial issues. that is, once a false perception has rooted itself it is difficult to correct it. thus the argument of legislation for more restricted use of the internet against such practices becomes important not only to guarantee a higher degree of truth in the information that is spread but also for political stability. china and other countries that were early to regulate the internet see this as a victory for their approach. from the above a number of issues are identified and presented as a discussion in the next section where the aim is to present a series of theses based on arguments. 4. discussion by looking at the different cases of economic and industrial espionage used as examples in the literature through history some patterns become clear. the first is that those who engage in economics of industrial espionage are often the scientifically and industrially weaker party, the party that is learning or trying to catch up. at the turn of the 19th century the usa was the student. in 1811 an american by the name of francis cabot lowell almost singlehandedly stole the knowledge of how to build a textile industry from britain (mendell, 2003). england a few generations earlier wanted to learn how to make their own tea instead of buying it from china. in 1789 robert fortune smuggled thousands of tea plants and seeds to darjeeling in british imperial india. also the french stole secrets from china. the process of making true porcelain was also stolen from the chinese and introduced in europe by père francois xavier d’entrecolles (bergier, 1975). the jesuit travelled to china in 1698 and the theft can be seen in letters dated 1712 and 1722 (bergier, 1977). for early self-educated industrialists travelling was the standard way of learning. actually, learning by travelling has been a well-used method for acquiring a competitive advantage throughout history (solberg søilen, 2016). a classic is charlers dupin’s six volume “voyages dans la grandebretagne (1821-22). in the late 1960s and early 1970s when the japanese were trying to gain a competitive advantage, a government sponsored system of industrial espionage was set up through the japanese external trade organization (jetro) partially funded by the government. jetro train people to look for new technologies (fialka, 1997). japan is one of the few well documented cases of a country that was systematically spied upon by the us, especially before and during trade negotiations (solberg søilen, 2005). american disrespect for the privacy of japanese citizens and companies makes an interesting case as both the us and japan are dependent on good relations in asia to counter chinese dominance in the region. it may be because the us considers japan to be 56 the weaker part and that they are entitled to treat japan in this way due to atrocities committed by japanese soldiers during the second world war. japan has few alternatives to american cooperation as they have not even apologized for the atrocities they committed in china during the same war. today it is not the japanese as much as chinese who fill the role of student in many industries in countries like england and the us. one of the well-known examples of chinese espionage is tenhong lee from taiwan (also called the glue man) who worked in an american company making glue-based products. he performed industrial espionage for a taiwanese competitor (ferdinand and simm, 2007). one of the reasons the case is well know is that it went to court where we learned about the complex motives behind lee’s actions. thus we have come full circle when it comes to industrial espionage within a few centuries and there is nothing to suggest that these alternating roles of who stand to profit from spying and who stand to lose will remain static. instead we may assume that this will continue to change with the alternations in the competitive advantage of nations, unless a better set of international laws and agreements can be established. 4.1 the moral dimension and regulations are economic and industrial espionage theft? or, is it simply learning, as some of the literature suggests? larcenous learning (ll) is adapted in organizations and countries in early stages of development. it’s a rational strategy as it is faster than developing your own r&d capabilities, and it’s also cheaper. can economic and industrial espionage be justified when one considers that many of those companies holding secrets are monopolies and that the spread of industries to new countries helps fight poverty and prepares the way for a large middle class in those countries? throughout history it can be shown how industrial espionage has helped fight poverty. china is only the latest example, bringing 500 million people from the poor classes to the middle class. how much is due to economic and industrial espionage is difficult to say, but we can assume that it has had a positive effect. learning countries often start by making cheap copies of established brands and products. as their sales increase they are able to improve the quality of their products which again raises the possibility of charging a higher price. this is the way for japan, china and all of the four asian tigers. in addition we have seen that research also suggests that certain forms of espionage can make the market more effective. when the information system (is) quality is the private information of the entrant, the incumbent is better off with an is of high expected precision while the entrant benefits from one of high quality (barrachina et al., 2014, p. 127). there are several arguments for why economic espionage is improving both markets and societies. we suggest here that economic and industrial espionage can be seen as a form of involuntarily sharing, which can be good on the macro scale but is devastating on the micro scale. for the individual company and the country where that company is taxed, economic and industrial espionage is an economic loss. it is a crime and it is an intrusion on individual life. all nations try to protect their own secrets by making laws that protect them, laws that are difficult to enforce outside of their own sovereign territory. there are no written rules in espionage between countries and foreign services, at best an understanding and form of balance. for some offenses there is a logic of guaranteed retaliation, a bit à la mutual assured destruction (mad) to use a parallel from the cold war. we see this in examples of cyberwarfare. moral and legal questions should be discussed further within the framework of moral philosophy and the study of international law. it is a dangerous moment for man when we accept the premises that stealing and treason are just the way of the world. it may be a part of human nature, it most certainly is a part of our history and as shown here it can have positive effects on the macro level, but agreements about conduct are necessary and countries can show political will by standing behind international laws and agreements. if we are to catch agents we must know what motivates them. the “glue man” was motivated by ego and power not money, and he also suffered from divided loyalties, as he wanted to help both companies. to assume that agents simply look for the money then is an oversimplified view of reality which can make us look in the wrong directions. if companies can better understand the agents’ motives they can also more easily stop them, or persuade 57 them to act differently. risk profiles can be identified in any company. even the term agent needs to be broken down into subcategories as it has been suggested that most industrial espionage is carried through by employees already employed or leaving a company (in large companies). they may or may not be working with a foreign state or a competitor. many employees simply take information because it is easy and they know it is valuable, but without knowing what they will do with it. others, like mr. martin who worked for booz allen hamilton, major contractor to the nsa, knew what to do with it before he was caught, but had not made the contact with competitors yet. it was the opportunity, or the occasion, that made him a thief. thus we can speak about the following motives in economic and industrial espionage: the employee who needs money, has split loyalties, leaves angry, the occasional thieve and the professional spy. for cases of economic espionage where foreign states are involved in hacking the situation is different and clearer. most spies here have a monthly salary. they are employed by the state to spy and are simply doing their job. others are contractors or subsuppliers. we must assume that fewer spies are motivated by political conviction today as the political divide (ideologies) between countries play a less significant role, but this may of course change. a general problem in the literature, as briefly discussed in the methods, is the onesidedness of the perspectives presented, especially when it comes to dealing out blame. when a book on industrial espionage is written in the uk today, then everyone else is considered to be the bad guys, for example the chinese and russians. the people interviewed in these books (and more worryingly, the author) want us to believe that the world’s largest surveillance systems developed in the western world are never used aggressively, but put in place only to defend our information and freedom. the same sources that are interviewed have no reservations about lying to elected politician in our national assemblies, and not only in the us. leakages by edward snowden and others have confirmed suspicion. for example, the heads of american intelligence have all been caught lying before the senate about spying on americans. obama lied when he said that prism was only used to spy on foreigners (or he too was seriously misled, which is not less worrying). prism showed that state organizations have a side door to the software we buy and how private data that is gathered about us on the internet is used. snowden showed that the us is a major aggressor. after these leakages much of the trust between state and citizens was broken, to say nothing about the trust between the american state and other nationals. after a series of unjustified wars in the middle east, america is now close to moral bankruptcy in the sphere of international politics, discredited from outside and more worryingly from within. that is not a good thing for world stability. a major problem with much of the existing literature on economic espionage is not only the one-sidedness but also the obvious extent of “moralism”, blatant and uncritical condemnation of what other countries are doing. for example it is said that only china and russia are engaged in economic espionage, how it was china who pioneered the use of computer espionage to target western companies for economic gain or we are given excuses such as that the difference between intelligence and information is less clearly defined in china. another approach is to recognize that all major services are engaged in economic and industrial espionage, but that some are more active than others. we may assume that countries that have the most to gain by economic espionage are more active and that those espionage capabilities that are being built will be used. there is no evidence that suggests otherwise. stories of moral superiority are spread to strengthen the conviction that one side has the moral high ground. once citizens are convinced that their own state has that high ground they can do all sort of things and get away with it, like engaging in economic espionage or starting wars. the intelligence apparatus is part of this logic that spread stories of us-and-them, also for their own advantage to get larger intelligence budgets. experience so far has shown that good books on economic and industrial espionage are based more on leaked sources than on interviews with people under oath who have signed secrecy papers. we should always listen to the executive or politician who has nothing to lose, who has been fired or suffered from injustice. in the quest for objective information open source will continue to play an important role here. technology is both an opportunity for better information and a threat to the same development as we have seen. going from 58 surveilling our computers to mobile phones is a great leap for intelligence organizations and private organizations alike. we can now follow people (targets/customers) in real time. for example with the help of beacons we can see when a customer is in the store and what he looks at. this information can later be used to send highly targeted advertising. the same technology can be used to gather information about terrorists’ whereabouts. for intelligence organizations planting bugs in homes was always risky. now we carry those bugs around with us all of the time and our microphones and video cameras can be tuned on and operated remotely by others. as a species we have taken a major step into the total surveillance state, so it is surprising that more citizens are not reacting. the reason for why more are not reacting should be studied by psychologists. the increase in false information is a product of this new technology. as we have seen it now spreads rapidly on the internet and is difficult to correct. voters are willing to disregard more serious and objective news sites when they make up their mind about whom to vote for and why. at the same time it has never been easier to find good and reliable information. the problem is that correct information takes so much training and demand that we are more critical as readers. this has put a new layer of responsibility on our learning institutions which they have not been able to handle so far. if we as societies do not develop a more critical ability towards what is published on the internet then manipulators will get the upper hand. we have been there before in history, when demagogues ruled and it never ended well. that in itself is a reason to regulate publications on the internet. how this is different from censorship is a challenge for scholars to show before policies are decided and implemented. the principle of freedom of press works only as long as there is someone responsible and is therefore a poor parallel for the world of the internet. it seems clear that a solution will have to include more legislation, policing and enforcement. our companies are just as vulnerable as the general public to misinformation and internet attacks. they don’t normally know when they are being attacked, when a part of their own network traffic is due to intrusions. foreign states continuously look for intelligence in connection with companies’ mergers and acquisitions activity, joint venture intentions, and strategies. companies surveille each other or their customers like when auction houses look for signs that art collectors are getting older and may be willing to sell. criminals try different scams to get access to credit cards and other valuables. in the end they are only protected by the expertise they have developed within their own organization. 4.2 cyberwars and challenges faced by government institutions for signal intelligence in 2014 sony corporation was attacked to the point where servers and computers were all cleaned of data. the company had to pay its employees in paper checks and there was no contingency plan. in this case the company got some help, at least afterwards. a few months later the nsa shut down the entire internet and mobile phone data in north korea for a short time as a direct retaliation. cyberwar is a threat that can strike any private organization, not only suppliers of infrastructure, but any company that infuriates another country or its rulers. moreover the companies attacked do not know if they are been harmed because of something they have done or something they could have done as many attacks are mere exercises. these exercises can be initiated by a foreign country’s intelligence apparatus, but may also come from universities, even from within their own country. economic and industrial espionage over the internet (preventing it, and even carrying it out) is the business of signals intelligence (singint). in the us this means the national security agency (nsa), in england the gchq and in sweden the fra. information warfare has become very real. the cyberarmy is to the 21st century what the air force was to the 20th century. it is now the fourth army group next to the army, navy, and air force. as a consequence militaries all over the world are building their own cyber-armies, some of them like iran after having suffered from massive attacks by other countries (us, israel and uk primarily). the us, england and israel showed that they can take control of a country’s nuclear facilities even in a closed computer system not connected to the internet by getting an agent to put in a simple usb drive with an operation known as “olympic games”, but better known after the name given to the malware: styxnet. 59 what they did not foresee was that this triggered a massive response by iran. iran answered with two major attacks, one against aramco and another against american banks. in 2012 iran took down the computer network of the saudi oil giant aramco for 8 days. a few weeks after they showed they can take down customer services offered by the bank of america (corera, p. 280-1). this led to an american-iranian deal of de-escalation that left israel infuriated and the uk uncertain that they should have entered the cooperation in the first place, according to corera’s sources. cyberwar and cyber armies are a reality after styxnet, and this and similar codes have since spread to many countries. a problem is that we do not know the extent of other countries’ capabilities for cyber warfare as they have not been fully tested. in a worst case scenario countries and companies must assume that all they do online can be stolen and stopped if they do not have a vigorous security system in place, which also takes into account the possibility that an employee may be used as a vehicle, even involuntarily. needless to say this degree of security is hardly found in any organization. the problem with cyberattacks is that it’s difficult to know who is attacking you, whether it’s your own state, another state or another company. michael hayden defined the types of attackers as states, criminals and a third groups consisting of “hactivists”, “anarchists” and “nihilists” (corera, p. 301). during the last american presidential election we witnessed how russian intelligence was able to influence the outcome of the election by hacking the email account of clinton’s campaign manager and leaking the information, bluntly exposing the clinton campaign’s strategies but also portraying the candidate and her staff as cynical and unconcerned about voters’ interests. the real damage of these intrusions is still being evaluated. their significance is still difficult to oversee aside from the obvious fact that they may have helped donald trump win the american presidential election. on one side there is nothing new with these intrusions. both russia and the us have been interfering in other countries’ elections for more than a century, as other great powers have done before them. however, this may be the first time russia has succeeded with such an operation in the us and the first time the us got a taste of some of its own medicine, after having meddled systematically in political election all over the world since the second world war. hacking is all about getting access to source code, so the attacker can identify how a system is made and where the weaknesses or hacking opportunities are. hindering spying is about checking the source code for backdoors, which can be used by foreign governments. for example microsoft has to show at least some of the code for its products to be sold in china as china knows that microsoft is obliged through american law to alter their software to allow for american spying. these episodes are often portrayed as a conflict between states and private companies, like when facebook’s mark zuckerberg lashed out against the american president for prism. in reality many private technology companies live in a form of symbiosis with national intelligence organizations. they exchange employees/expertise and do business with each other. both are also in much the same business, in the information industry, where the primary aim is the gathering and exploitation of data. they also cooperate. in the first half of 2014 google received 15,000 government request for user data from different countries. they complied in 65% of the cases (corera, p. 380). social media and google are themselves in the spying business, selling private information to companies for advertising. the main difference is that it is done by consent (at least formally, but no one reads the fine print) and that customers can opt-out. further research should aim to show the extent to which this cooperation is done. for those citizens fearing a total surveillance state, it is sometimes argued that intelligence organization are selling security. the privacy debate exists but is not strong today. instead states do what they can and lie about the rest. for example they claim that they are not surveilling their own citizens, but in reality they cannot separate this data from other foreign data. instead all is collected. the nsa are wiretapping the whole world and we as world citizens are to believe that this is for our own best interest as america will protect us all. it is a hard sell today. the major reason why other nations and their elites comply is that the nsa is also sharing a part of this information, with other countries like germany and france that do not have the same technological capabilities. the intelligence that is passed on by the nsa to other countries is sometimes invaluable for catching terrorists. 60 sometimes the intelligence is passed on as part of intelligence swaps (getting access to data the other party does not have) and sometimes it is simply goodwill. of course they only swap between friends. it would be of interest to know what other countries think about these issues and the extent to which new intelligence alliances are formed. the nsa was the result of a need for a more centralized intelligence system after the disaster of pearl harbor and failings in the korean war (corera, 2016, p. 51). in the shadow of what president eisenhower called the ‘military-industrial complex’, there emerged a spy-industrial complex centered in washington, dc and northern california. by the early 1960s, over 50,000 americans were involved in signals intelligence (corera, p. 6264). today the us has a total dominance of the infrastructure of the internet. bluffdale ohio is the strategy to gather and save it all, every piece of digital trace a person leaves; not only surfing, but financial records, tickets, photos, chats, phone calls and gps data. the major security risk with this project is that it is done by non-military and private contractors. at the nsa less than 50% of staff today is military and much has been out sourced to a few big contractors of which booz allen hamilton is the best known. it was the employer of edward snowden and more recently harold thomas martin. spy-hunting has been outsourced to private firms and private employees are receiving top security clearance: “booz allen is one of five corporations that together employ nearly 80 percent of the private-sector employees contracted to work for us spy and surveillance agencies. booz itself deploys an intelligence workforce of 12,000 personnel with security clearances, a figure i found is equivalent to nearly 27 percent of the 45,000 contractors employed in us civilian and military intelligence” (shorrock, 2016). martin was recently arrested, suspected of taking the highly classified source code developed by the agency to break into computer systems of adversaries like russia, china, iran and north korea. we started the introduction of this paper by saying that governments were lagging far behind in technology. today governments have built up their technological abilities, but these rely heavily on private contractors. this has given rise to a new problem and a new level of risk. what is more worrying for businesses is that it is just as easy and natural and often more lucrative for the same nsa staff to take on assignments for a private company, and the risk is not exclusive to the us. the same competence is found among it consultants in many countries around the world. companies will need to push for more security and encryption. in extreme cases it has meant going back to the typewriter and holding meetings while going for a walk in the park. for that which cannot be protected it means companies should not write it down, at least not on anything that is connected to the internet. this is a radically different world from the one i started to study only a decade ago when i wrote a dissertation on industrial espionage. 5. future studies it would be interesting to see if findings from the national intelligence service (nis) referred to in lee (2015) about who leaks (employees, former employees) and in what size companies (small, medium and large) are applicable to countries other than south korea. if they are, spy catchers’ attention at small and medium sized companies can be put mainly on ex-employees and mainly larger and multinational companies need focus on leakage among current employees. based on meyersson and glitz (2016) study of the ddr it would be of interest to define which countries and which industries and companies are better served by espionage economically. following from polanyi (1967) we want to know what else an organization needs to acquire to become competitive besides the secret information and hiring key personnel who know how to use it. there is capital and the material component as in the case of the iranian nuclear project, but other ingredients may have been overlooked that are essential for making use of the secret information that the organization has come across. in other words, it seems too narrow to only focus on the information itself when we want to understand the process by which secret information is turned into a competitive advantage. one suggestion is made by cotte (2005), namely technological eve. how is technological eve performed effectively? what besides reengineering, buying the products of competitors and picking them apart to find out how each part is made and how it brings value to the end-product, are essential for this 61 operation? in the french literature there has been a keen focus on eve more in general (“veille”) during the past decade. in sweden universities still give courses in “omvärldsanalys”, meaning “surrounding world analysis”. building on the research of sivanesan (2011) we want to know more about how spies are recruited from universities, but also what motivates them. how much of the information passed on is open source and published material? academics on the cutting edge of a technical or natural science field can sometimes refrain from publishing to avoid coping and in order to prepare for patents. studies should continue from the research of ferdinand and simm (2007) that use external learning (el) without collaboration, or larcenous learning (ll) to describe this process. it may be different in different cultures and the perception of ll may also be different. the difference between ll and el, like attending a foreign university, may then be one of time: ll is fast while el is slow. from a strategic perspective this raises the question of what mix is optimal for the competitive advantage of a rising nation, or any nation. there is a need to gather data through interviews from non-western intelligence organizations, like the russians and chinese, to balance and check the numerous stories coming from the western world. there is also a need to create case studies with individual stories of economic espionage. a number of these stories already exists in other forms and need to be extended. the great challenge in a case with two counterparts, two companies or countries, is to get the story from both sides. from the discussion and syntheses it would be good if a historian could gather the examples we have of economic and industrial espionage through history and present them as unsentimentally as possible. a similar project for a broad discussion based in moral philosophy and international law does not exist either from what i can see. the consequences of cyberwarfare for companies are not sufficiently described and understood. more generally, the danger that the intelligence services can be used more intensively for economic espionage is real and should be addressed. how can companies protect themselves in this reality? how are state intelligence services going to solve the situation they have gotten into with the hiring of private contractors who leak information about us and how are internet companies going to convince customers that they are the good guys when they very much are locked into a symbiosis with the services, forced by law and otherwise persuaded to cooperate? will we see new (national) systems of internet and will this make business less global and less efficient? 6. concluding remarks much has changed since i defended my doctoral thesis in industrial espionage at the university of leipzig some ten years ago. we have moved from break-ins à la watergate to theft by hacking. this period has also seen the beginning of cyberespionage even though the notion of information warfare was well known before. the conclusions of the empirical work in my thesis has stood the test of time and since then been confirmed regularly: companies do not disclose when they have been attacked as that only makes things worse. instead they take the break-ins as a fait accompli and move on, unless they are the dominant player in the industry and the intruder is a smaller player, then they may decide to punish. the dissertation introduces the theory of diversification of moral risk (dmr) built on the principle agent problem and the notion of portfolio risk diversification, showing how companies hire agents to perform actions they deem immoral to reduce the risk and consequences of being caught. for example oil companies outsource bribery to other companies to facilitate the handling of loading oil in high risk harbors. weapons manufacturers hire other companies who hire other companies for their sales activities. observations of these phenomena have only increased with new technology due to increased opportunities, lower risk of being caught and smaller consequences when caught. spying and snooping has become an activity that engages everyone today, on all levels. state intelligence organizations and internet and technology companies work much in symbiosis. for example facebook is an indispensable starting point also for intelligence organizations that look for suspects as they will typically cross index our friends list with our financial transactions and flight itineraries over the past years. the same goes for individuals. a major motive for anyone to turn on facebook is voyeurism, which is a form of snooping on people we know or even don’t know but whose information we can get access to. we install cameras to keep track of 62 our kids and place trackers on our spouse’s car. it is all part of the same phenomenon. there is a risk that western intelligence organizations will turn to economic espionage to help their major corporations gain a competitive advantage as the technology and the facilities are already put in place. it very much depends on the country and who is head of state. the strategy of those countries who can afford to build these systems will be to catch it all and store it all, all data, and forever. the us is the first country to achieve this, but they are not going to be the only one. with the new complex at bluffdale the us can not only search in all metadata, but also go down in detail and search all data (deep packet inspections). metadata is simply the best way to start a search because otherwise you would get too much. it is not where the search stops. this system is already giving the us an information advantage today, but responses are to be expected. china for one is bound to follow. the internet, the ultimate symbol of freedom and knowledge, has become the ultimate surveillance tool. we as citizens have accepted walking around with a mobile phone, which is the spy’s dream tool. can the internet be recreated in its former self or was it naïve to think that the state would let it be uncontrolled? for companies it will have to mean a more encrypted reality. no company secrets that are 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(2017) a bayesian approach to developing a strategic early warning system for the french milk market. journal of intelligence studies in business. 7 (3) 25-34. article url: https://ojs.hh.se/index.php/jisib/article/view/242 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a bayesian approach to developing a strategic early warning system for the french milk market christophe bissona and furkan gurpinarb akadir has university, mis department, istanbul, turkey bbogazici university, computer engineering department, istanbul, turkey journal of intelligence studies in business please scroll down for article a bayesian approach to developing a strategic early warning system for the french milk market christophe bissona* and furkan gurpinarb akadir has university, mis department, istanbul, turkey bbogazici university, computer engineering department, istanbul, turkey *corresponding authors: cbisson@khas.edu.tr and furkan.gurpinar@boun.edu.tr received 11 july 2017; accepted 27 october 2017 abstract a new approach is provided in our paper for creating a strategic early warning system allowing the estimation of the future state of the milk market as scenarios. this is in line with the recent call from the eu commission for tools that help to better address such a highly volatile market. we applied different multivariate time series regression and bayesian networks on a pre-determined map of relations between macro-economic indicators. the evaluation of our findings with root mean square error (rmse) performance score enhances the robustness of the prediction model constructed. our model could be used by competitive intelligence teams to obtain sharper scenarios, leading companies and public organisations to better anticipate market changes and make more robust decisions. keywords bayesian networks, competitive intelligence, forecasting, milk market, strategic early warning system 1. introduction as globalisation, deregulation and the big data phenomenon (bendler et al., 2014) are rendering our economy gradually more complex and uncertain, the interest in competitive intelligence (ci) is growing (bisson, 2014; hugues, 2017). calof and skinner (1998, p.38) define ci as “the art and science of preparing companies for the future by way of a systematic knowledge management process. it is creating knowledge from openly available information by use of a systematic process involving planning, collection, analysis, communication and management, which results in decision-maker action.” however, day and schoemaker (2008) report that only 23% of ceos use scanning, which is the upstream part of ci allowing the transfer of information from the environment to the organisation (see for example bisson, 2013). by using scanning, managers detect most of the time weak signals (thereby allowing to anticipate) through using their intuition (cahen, 2010) and too often decisions are made on the basis of heuristics (bisson et al., 2012). therefore, in order to address challenges such as big data, highly volatile and uncertain environments, an era where anticipation is more important and more difficult than ever, “traditional” ci systems based on scanning appear to be limited (accenture, 2013; gilad, 2008). when trying to overcome these limitations and strengthen strategic planning and governance, the importance of strategic early warning systems (sews) has been raised (fuld, 2010). sews can help decision-makers anticipate market changes, and allow organisations to have a strategy that fits the market reality and avoid industry dissonance. sews integrate scenario techniques which aim to “create alternative ‘pictures’ of the future and to challenge mental models” (schwarz, 2005). the general framework of sews (bisson, 2013; gilad, 2008) for a market is: 1) define the scope, i.e. journal of intelligence studies in business vol. 7, no. 3 (2017) pp. 25-34 open access: freely available at: https://ojs.hh.se/ 26 the time frame, analysis to be done and participants; 2) determine the drivers of change; 3) generate scenarios; 4) explore strategic implications, options and decisions; and 5) implement the system by watching the drivers of change (through scanning), which could lead to the appearance of a predetermined scenario, then launch an alert to anticipate either a threat or opportunity. sews requires updates to maintain its performances as inputs might change with time (bisson et al., 2012). these updates regarding variables as well as other data/information must be provided by the competitive intelligence team. our research focuses on the first three steps of the framework as we do not intend to implement it here. although several qualitative methods of sews were developed which demonstrated their importance for governance (gilad, 2003), there is room for improvements for sews based on quantitative methods (fuld, 2010). thus, we aim to address this scientific gap by applying for the first time different multivariate time series regressions and bayesian networks following the three first steps of the general frame of sews to predict the impacting scenario(s) that would help to be better prepared for the future. for our experiment, we chose the milk sector in france in line with the call from the eu commission (european commission, 2010) for more robust tools to better predict the milk price and anticipate changes in this market. indeed, the milk price is highly volatile. for instance, french farmers’ incomes can vary by over one third from one year to the next (momagri, 2012). for example, a 1% or 2% discrepancy between supply and demand can trigger a variation of 50% to 100% change in income (momagri, 2012). yet, the european union’s milk market is currently in crisis as the new common agricultural policy, which went into effect in 2015, ended quotas for milk (robert, 2015). moreover, quotas will eventually end for other products as well (e.g. sugar in 2017). the remainder of our paper is organised as follows: we first present the necessary theoretical background and provide an outline of the approaches used in the quantitative analysis of time series data. next, we build the bayesian model, apply it to our data, and we discuss the results obtained through bayesian analysis. we conclude with comments on limitations and future research to be undertaken. 2. theoretical background 2.1 strategic early warning systems although the development of sews is common among international companies, such as shell (gilad, 2003), the experiments and their details are rarely disclosed. indeed, sews are central to governance, and their implementation can result in a competitive advantage synonymous to market share and profit increases (bisson, 2013). sews can help to anticipate rather than react, and to detect strategic opportunities and risks (gilad, 2003), reduce cognitive bias and intuition in the decision process, and allow for more effective contingency plans. several types of sews have already been used, particularly in industry. sews are nowadays deemed to be compulsory for private organisations to survive and/or thrive (fuld, 2010; gilad, 2008). it can be argued that public organisations are also facing growing international competition, compelling them to most efficiently utilise tax funds. as a result, public organisations would benefit from implementing sews as well (bisson et al., 2012) as demonstrated by the steel sector in the north american region of pittsburgh (2008). companies were closing one after another in 2008 (e.g. seagate), due to the worst financial and economic crisis since 1929, and the sharp decline of the american automotive industry: “the steel valley authority (sva) is an intermunicipal economic development agency incorporated by the city of pittsburgh and eleven riverfront municipalities all within the mon river region. the sva has been managing industrial retention for the commonwealth of pennsylvania. the authority, through a strategic early warning network (sewn), has made significant contributions to the retention and revival of industrial enterprises, has saved and created nearly 8,000 jobs, and has impacted many more workers and communities indirectly. the sewn network has saved companies from pittsburgh to erie to altoona, and has become a model state and nation-wide” (www.steelvalley.org). thus, a sews that is well developed and implemented can help private and public organisations succeed by allowing them to make better and faster strategic decisions in comparison to their competitors. 27 2.2 time series forecasting financial time-series forecasting is considered to be one of the most difficult challenges of modern time-series forecasting. as explained by abu-mostafa and atiya (1996), financial time-series data is usually noisy, nonstationary and deterministically chaotic. the term “noise” here actually represents the unavailability of data to capture the complex and non-linear relationships between market variables from past data. the non-stationary nature of data arises from the fact that the structure of relations between variables tends to change over time. the data is said to be chaotic because it usually behaves randomly in the short-term. however, under the assumption that there is a deterministic component in the long-term financial timeseries data, we proceed to analyse and build a forecasting system, where the parameters are learned from the past data. the accuracy of time-series forecasting methods plays a crucial role in the economic and social benefits of competitive intelligence systems (bisson, 2013). for building accurate forecasting systems, there are two main methodologies employed by researchers, namely, neural networks and support vector machines. each of these methodologies has advantages and weaknesses, as explained below. the area of time-series forecasting is influenced by linear models such as autoregressive integrated moving average (arima) and non-linear models such as the threshold autoregressive model, the bilinear model and the autoregressive heteroscedastic (arch) models (engle, 1982). the linear arima model, however, is clearly shown to be too weak to adopt in real-life scenarios (de gooijer and hyndman, 2006). given that the traditional statistical forecasting methods lack the power of explaining the underlying structure, attention has been drawn to machine learning models, especially in the last two decades (ahmed et al., 2010). machine learning models are also called “data-driven”, or “black-box” models due to their nonparametric and nonlinear operation, which only requires the past data to learn the structure, and therefore perform future forecasting. for instance, artificial neural networks (anns) are shown to outperform their traditional opponents (such as linear regression) in the task of market forecasting (lapedes and farber, 1987; werbos, 1988). following anns, other machine learning models such as decision trees, nearest-neighbour regression and support vector machines emerged for the task of future value forecasting (alpaydin, 2010). support vector machines are still widely used for classification and pattern recognition tasks, and they are shown to be a desirable alternative for classical learning methods for the task of time-series forecasting (muller et al., 1997). statistical methods to analyse the structure and/or predict the future of the milk market have been implemented using a variety of methods in the previous works in the field. reed (1992) studied the structure of the market by optimising the parameters of different equations that are used to estimate the supply response from changes in demand and producer expectations. another work by saravanakumar and jain (2009) proposes an econometric approach for determining the price of milk based on other variables of the market such as technology and input costs, by analysing the individual households of a local market. other research addresses the issue of better prediction for the milk market by using statistical learning methods. one example was done regarding the estimation of the entry and exit conditions to the milk market, based on quota and other policies regarding this market, by using the discrete variable of farm size in relation to other variables in a markov chain analysis (rahelizatovo and gillespie, 1999). markov chains are also employed in a recent work that studies the effect of trade quotas on milk, analysing the dairy sectors of germany and netherlands, again using categorical variables such as discretized milk production and firm size (huettel and jongeneel, 2008). more than a decade ago, a research project funded by the european commission resulted in the development of an economic model called common agricultural policy regional impact (capri), and aimed to deal with the complexity induced by the cap reform in 1992 (heckelei and britz, 2000). a study based on capri analysed the effect of removing milk quotas, and it obtained a prediction that the milk price would drop with respect to a reference scenario (jansson and britz, 2002). another framework developed by the food and agricultural policy research institute (fapri) examined and projected several variables related to agricultural markets. a study that utilised this framework to analyse the effect of removing milk quotas in the industry of the uk and the eu predicted a significant fall in milk 28 prices, as well as a recess in the expansion of milk production by 2016 (patton et al., 2008). 2.3 bayesian networks bayesian networks are data structures that represent the relations between multiple parameters of a system. bayesian networks, sometimes termed belief networks, causal networks or influence diagrams, are probability distributions factorised over a directed acyclic graph (dag). although bayesian networks were first introduced in the literature by wright in 1921 to analyse the failures in crops, they are still widely used in dealing with uncertainty in knowledge based systems. bayesian networks, as structure learning tools, are usually constructed with directed acyclic graphs where the leaf nodes are the observed variables and the lower-order nodes are the hidden (or cause) variables. most of the time, the set of relations between the variables are given a priori. an example by kiiveri, et al. (1984) analyses causal relations using a probability distribution factorised over a dag. there are also variants of bayesian networks to analyse dynamic systems such as hidden markov models (hmms) (durbin, 1998) and dynamic bayesian networks, as introduced by murphy (2002). although we analyse a more complicated graph structure representing the relations of the major variables of our market, we also construct a dag in order to represent a subset of variables, which have available time series data, by establishing the strength of relations using an expert evaluation, and we further investigate the data using this bayesian network to get future value estimations, as described in section 3.3. 3. methodology in this section, we apply bayesian analysis in order to estimate and evaluate future scenarios for the milk market. next we discretise the data and use the k-means clustering algorithm to classify the data in terms of amounts of change. this is followed by obtaining the prior probabilities needed to construct the bayesian model. finally, we evaluate the performance of our forecasting system and measure the probability for each scenario. to establish a broader understanding, we present our work in figure 1 system pipeline. figure 2 raw data. 29 the form of a work flow diagram, as shown in figure 1. 3.1 data a questionnaire was first sent to a french milk expert (we were asked to keep his/her name confidential) to obtain all the drivers of change of the milk price which are macro-economic indicators. thereafter, we started the quantitative analysis by collecting time series data for various price change drivers related to milk, which are world milk demand and production, the consumer price index for milkrelated products, livestock and input costs (e.g. energy). we collected time series data for the period from january 1990 to february 2015, and normalised each time series vector by mapping its values between 0 and 1. annotating the time t = 0 at the beginning of our observations, we have t = 319 time points where observations are recorded (see figure 2). the time series data can be found at the website of insee (the french public official statistic organisation), an example data link is in the national institute of statistics and economic studies (2015). we also visualised the data and the autocorrelation function in figures 3 and figure 4, respectively. since the time series data for various indicators mentioned above came from different sources, some of them were measured in different units of time, such as monthly, quarterly and yearly. therefore, to establish a consistent data set, we used linear interpolation and extrapolation to convert all the time series to monthly-observed variables. in order to impute the missing samples, we used least-squares approximation from applicable input variables, and thereby obtained the best linear unbiased estimation for the missing samples. figure 3 reconstruction with different algorithms. km: kmeans clustering, em: expectation maximization. 3.2 clustering next, we simplified the learning problem by converting the time series signals to discrete classes, then any given signal x is transformed to f(x)=𝑥". in the new form 𝑥", every element 𝑥#$ could have a value between 1 and v , where v is the number of states. so, intuitively, the values of xd represent changes in the data (1: big drop, 2: smaller drop , ... v: big rise). in figure 4, we show that a higher number of cluster centres reduce the reconstruction error, however this means increasing the complexity of the classification system. therefore, to avoid overfitting and to be consistent with the 5-point likert scale, we chose to set v =5 in our experiments. in order to find a reasonable set of changes, we used a k-means clustering algorithm which performs vector quantisation by finding optimal sets of clusters, and assigned each member of the vector to a cluster centre (macqueen, 1967). we used the vl feat library (vedaldi et al., 2008) for the parallelised k-means implementation, which uses lloyd’s algorithm (lloyd, 1982) and l2 distance measure for optimisation. we started with a random initialization, repeated the clustering 10 times and chose the solution that gives the minimum energy. we found that k-means clustering provided better classification and forecasting accuracy than expectation maximization clustering. in our application, we converted the signal to a format 𝑥& where this represents changes in the data such that: 𝑥&$ = xi − 𝑥$ −1. we applied clustering on this change vector 𝑥& , to find the v most observed change values in the samples, and assigning each sample to one of the v cluster centers, we obtained the discrete vector 𝑥" as defined above. figure 4 reconstruction with k-means algorithm and different number of clusters. km: k-means clustering, em: expectation maximization. 30 3.3 bayesian analysis since our aim is to estimate the future values of dependent variables, we first needed to obtain prior probabilities to feed our bayesian decision system. to this end, we used two different probability definitions, which can then be combined in a single set of matrices. two different probability estimations are explained below. we started by finding the probability distributions of single variables over different time lags. in other words, we constructed probability distribution function (pdf) tables to establish the prior probability of observing variable i having the value k1 ∈ [1: v] when observed that it has the value k2 ∈ [1: v], on time (t − lag). thus, we established a seasonal model where we have an estimation of probabilities of observing a single variable. after normalisation, this yields a (vxv) pdf table t. where t(,*,$ = p(x(\x(-.), in other words the probability of observing x = j when we know that x = i [lag] periods before. similar to the intra-variable approach, we construct prior probabilities which represent the effect of indicator variables on the dependent variables over different time lags, more formally p(𝑦0| 𝑥.,(0-.), 𝑥3,(0-.), . . . , 𝑥45,(0-.)). finally, we obtained a set of v−by−v probability distribution matrices from the collected set of data. for the representation of pdfs, assuming that each variable depends on each other (a complete graph), we have a data structure of size 𝑁3by𝑉3 where n is the number of variables in the model, and v is the number of classes. we compute the prior probabilities as described above, and use the posteriors to forecast the time series vectors and evaluate scenarios, which will be described next. having collected all the data and the prior probability distributions, we used our system for simulation, to determine the probability of a scenario happening 𝑇9 time periods after the last observation. therefore in our case, a scenario s is simply represented as an n by 1 vector where each member 𝑆𝑖 represents the numerical value of variable i, at the time period designated by t +𝑇9. since we cannot measure the accuracy of our system’s prediction with a large 𝑇9 value, we make validation tests with forward chaining, as we explain next. 3.4 performance evaluation in order to measure the accuracy of our forecasting system, we ran validation tests using the forward chaining strategy, which means for each data point, we use the previous observations to construct our model, and measure the out of sample rmse of the prediction on the point of interest. we use all five variables as explanatory variables and price of milk as the output. averaging the results over all folds, the classification accuracy was 80.94% and the average rmse was 0.0189. we also provide the performance with each input variable in table 1. here we keep the autoregressive component and compare the contributions of each explanatory variable. therefore, the first row corresponds to estimation with only previous values of price. table 1 forward chaining estimation accuracy of price with different input variables. 3.5 scenario assessment using the prior probabilities explained in section 2, we used bayes’ decision theorem to forecast the future values of our time-series signals. we represented our system’s state by n discrete time-series signals of length t, hence a t-by-n matrix. we fed this matrix into our simulation code and we obtained a new scenario of size (t +1) x n. the process is repeated until we reach time 𝑇9, and converting the discrete signals back to the numerical values, we estimated the final values of variables. to analyse the probability of scenarios, we repeated this process many times, hence we obtained a probability distribution function for the scenario at time 𝑇9. 3.6 simulation since our aim was to obtain a probability density function for the final values of the variables, we ran 1,000 simulations to forecast the values of the discrete time series vectors, and converting them back to continuous signals, we obtained one final value per parameter for each turn. collecting all the final 31 values, we obtained a data distribution. by fitting a normal distribution on this data, we obtain a probability for a given scenario. 4. results and discussion to evaluate the accuracy of our framework, we ran some tests on different parts of the machine learning system, and we report performance scores in the following. 4.1 signal reconstruction accuracy here, we analyse the accuracy of our signal conversion system. as explained above, we convert our time series data into discrete values. hence we need to reconstruct the signal back to a “continuous” time-series form, which inevitably causes information loss. intuitively, increasing the number of cluster centres, k, in k-means clustering should decrease the reconstruction error. here, we present a chart for a sample signal (namely the usd/eur parity) which shows the relationship between the number of cluster centres and the root mean square error (rmse) for signal reconstruction, in figure 5 (an example signal reconstruction for 5 and 10 cluster centres are shown). as expected, the reconstructed signal converged to the original one as the number of cluster centres increases. as is shown, there might still be room for improvement, but increasing the number of cluster centres is equivalent to increasing the complexity of the learning algorithm, and with a fixed amount of data, a high number of cluster centres might lead to over-learning. in order to evaluate the accuracy of our prediction system, we again used the rmse error measure, with a performance test similar to a machine learning application. in this test, we used the parameter τ ∈ [0, 1] which is the ratio of training set size to the data set size d. in other words, we used the first τd number of observations for the learning (see section 3.3), and we ran a simulation for the remaining (1 − τ) d unobserved time periods, and thus constructed a scenario which is of size d. after obtaining a large (∼10>) number of scenarios, and taking the mean of them, we estimated the signal 𝑆? for the variable of interest. since we already knew the original signal s, we represented our system’s performance with the root mean square error rmse(s,𝑆?). below in table 2 are some results for different variables and different values of τ. table 2 forecast error vs. τ. 4.2 scenario probability evaluation finally, we used our framework to estimate the probability of different scenarios relevant to the milk market. two scenarios were given in terms of milk price, and another one about the milk demand in the european union (pole economie & prospective normandie, 2014). we tested these scenarios by propagating the market’s state up to the year 2020, with the method explained in section 3.6. the results for the 3 scenarios are shown in table 3. we tested our algorithm with different scenarios for the variables of price and demand. as expected, the likely scenario resulted in a high probability value, whereas figure 5 reconstruction with: (a) 5 and (b) 10 cluster centres. 32 the probability of the pessimistic scenario (price decreases by 15 % scenario) resulted in a low probability value. however, the highest probability is for the optimistic scenario. hence, we observe a difference between the results obtained with the prospective (or foresight) approach (which is purely qualitative and for the long term) and the approaches obtained with our simulation for sews. table 3 scenario probabilities. about the milk market, although prices are currently lower compared to before the end of quotas on the first of april 2015, our optimistic scenario might occur in 2020, as after a price drop the market will certainly concentrate and price might increase again. a competitive intelligence team could use, feed and update this model by entering new variables, new inputs such as new prices and production levels among others and see the most probable scenarios in the coming months and years. therefore, it would help organisations to be better prepared for the future and lead toward stronger decisions. 5. conclusion we applied for the first time different multivariate time series regression and bayesian networks to predict the impacting scenarios which are the heart of sews. our model could inspire competitive intelligence teams in order to seek more accuracy regarding scenarios, leading to better anticipate opportunities and/or threats, and to more robust decisions. 6. limitations our work models both small and big changes, but to create better scenarios, we need more data for such complex relationships. experts in the field together with competitive intelligence experts could make further searches to get a stronger understanding of the underlying procedures. 7. further work our regression is learned in one shot, so there are no iterations, and therefore there is no correction. thus, by using machine learning algorithms, we could get automatic corrections and potentially proffer toward better accuracy of scenarios. 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(1921). correlation and causation. journal of agricultural research, 20(7), 557– 585. eg-uk conference paper style guide 12 how to adapt a tactical board wargame for marketing strategy identification stéphane goria université de lorraine, crem laboratory, département informatique, iut nancy charlemagne, 2 ter boulevard charlemagne – cs 55227, f-54052 nancy, france stephane.goria@univ-lorraine.fr abstract: this research paper investigates some fundamental principles of marketing warfare to see specifically what kinds of maneuvers can be used to defend or take control of a certain market. we present military wargames and its history to ease the understanding of the fundamentals in this area of study. since we did not find a visual business wargame solution for our problem in the literature, we decided to develop one, based on the french market of game consoles between nintendo and sony in the period between 1994 and 2010. our experiment confirmed the value of wargaming. it showed that a parallel could be made between tactical maneuvers on the map and the statistics of sales for this market during the time interval. keywords: wargames, marketing warfare, board wargames, competitive intelligence, game consoles 1 introduction in order to be competitive or simply to survive, companies have to choose strategies which incorporate development. innovation is a common solution for many of them (trot 2008, 77-78) (lundvall 2010, 328). but innovating is always risky, because one can’t know if strategic orientation of innovation will be good before the new product or service will be on market. another approach concerns quality methods which often propose some solutions to perform a company process (weaver 1991) (pyzdek and keller 2003). but, these take a long time for implementation and need organizational involvement. in addition, they work in a homogeneous way and consequently their impact is homogenous too and easily predictable. another choice is proposed by marketing warfare (kotler and singh 2001). with this approach called war analogy, the authors propose to elaborate company strategic planning, according to war laws and the position of the company in its markets. but till now, marketing warfare is reduced to abstract analogies and it is not easy for the most part to envisage a company strategy with only abstractions. a partial response to this is proposed by a business wargame approach. from war and battle models for military strategies development, some researchers have tried available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2012) 12-28 https://ojs.hh.se/ 13 to fit them to markets (herman et al. 2009) (gilad 2009). this approach gives some keys about how to simulate a competitive environment and shows the first interest for competitive intelligence (kurtz and schuller 2008) and economic intelligence (besson et al. 2010). nowadays it is also considered a marketing intelligence analysis tool (jenster and søilen 2009, 165), for a warning system (gilad 2003, 93) or as an accelerator for decision-making processes with the capability to anticipate the future (fuld 2003) (cares and miskel 2007). however, in our opinion this approach has a drawback: it doesn’t propose, as its military cousins, visual systems to identify and consider marketing warfare maneuvers. for some time the competitive intelligence community has also been interested in information visualization tools for their applications (shaker and gembicki 1998, 130) (bose 2008) (besson et al. 2010, 122). we can assume that visual application for wargaming will improve the use of competitive intelligence. with this assumption, the wargames become tools for more creative competitive intelligence, i.e. a kind of competitive intelligence where we use creative techniques to stimulate the imagination of decision-makers and analysts with the aim to identify opportunities and threats. in this paper, we try to solve this problem of how to display information to propose a solution for marketing warfare maneuvers with visual presentation in real competitive context. we base our work on information clarifying in relation to, first marketing warfare theories, and second, on wargame history and solutions and, in third, how to propose a visual representation of war analogy with visual tools already developed for this purpose with board wargames. finally, we present our methodology to transform market or product information in a tactical board wargame. to illustrate this, we created a map using home video game consoles battles, with sony and nintendo from 1995 to 2007. 2 marketing warfare by analogy with the war, marketing warfare is based on the idea that many competitive situations can be interpreted in terms of war strategies. in the beginning of 1980s (kotler and singh 2001) and (ries and trout 2006, 44) researchers proposed to consider the mind of a consumer as a battleground. then, they interpreted the company strategies possible in four categories: (1) defensive, (2) offensive, (3) flanking attack and (4) guerrilla. in the case of (kotler and singh 2001) there are two flank/flanking attacks 1 (figure 1): simple and bypass (a bypass attack wins the battle by attacking 1 in marketing warfare, it seems the “flanking attack” expression is preferred to “flank attack”; but for military terminology, it seems different. in this paper, when we talk about marketing warfare, we use “flanking attack” and when we talk about military battle we use “flank attack”. not defended zones). for (ries and trout 2006, 83) bypass attacks are not accurate and encirclement attack is included in the flanking option. they also add which strategy is good for which company:  defending option suits the market leader. it implies than all strong competitive moves should be blocked and the best defensive strategy is the courage to attack oneself.  direct offensive option suits the number 2 company on the market. it implies that we consider the strength of the leader’s position to find a weakness in the leader’s strength and attack at that point. we then launch an attack on a front as narrow as possible.  flanking option suits smaller companies. it implies tactical surprise, an oriented attack into an uncontested area. we follow the pursuit attack to its end.  guerrilla option suits local and regional companies. it implies that these companies try to find a market segment small enough to defend. they will never act like the leader and be prepared to run away at any time. 14 figure 1: attack alternatives in marketing warfare (kotler and singh, 2001) however, these propositions seem to be lacking on strategic and tactical attack and defence warfare levels. for example, guerrilla warfare is a type of warfare and not really kind of attack. to respond to this problem (james 1985, 7) proposed 4 kinds of strategic maneuvers: deterrent, attack, defence and alliance: “deterrent strategies in business attempt to induce stability by encouraging prudence on the part of competitors” (james 1985, 31). attack and defence strategic manoeuvres contain each a set of tactical maneuvers. attack includes (kotler and singh 2001) alternatives and isolation and unconventional offense. unconventional offense is a kind of interpretation for guerrilla tactics when guerrilla forces look for a local superiority to strike the enemy and retreat. isolation alternative is a specific proposition (james 1985, 60). with this tactic, the enemy’s strong points “are bypassed by main forces and mopped up by later waves of troops or left to surrender”. tactical defence maneuvers include: position defence (intensification of its positions), mobile defence, pre-emptive strike, flank positioning (reinforcing flanks), counter offensive and withdrawal. but, for all of these propositions, marketing warfare doesn’t suggest a less metaphoric interpretation of maneuvers. the only system proposed is a reference to market segmentation. it is interesting, but too abstract to interpret a situation in terms of attack or defence alternatives. to apply this idea people need to imagine battleground and armies’ positions. in fact, at a tactical level, marketing warfare seems have no solution to guide our interpretation of clash actions and battle orders. at this level, marketing warfare is a kind of philosophy to consider as we see to manage a market situation. another criticism of marketing warfare is the frequent use of some innovative solutions to illustrate it without a real place for innovation in the strategy. for ries and trout (2006, 58) attacking yourself is an innovative element in a manoeuvre to attack or defend a position (examples used are starbucks coffee, gillette razors and ipod). however, they don’t give any information to identify a kind of efficiently in these cases. to find this information, to include innovation with more guidance in marketing warfare strategy, we looked into the innovation literature and specifically into the buyer utility map (see 4.1). 3 wargame proposition wargame is a tool made to consider a war situation with many possibilities of development. it helps the decision-maker to envisage his choices and those of the opponent. “the object of any wargame (historical or otherwise) is to enable the player to recreate a specific event and, more importantly, to be able to explore what might have been if the player decides to do things differently” (dunnigan 2000, 1). its recent history can already look back at two centuries of military applications and around sixty years of applications in business. wargames propose different options to consider war situations from the skirmish level to strategic level including the tactical level. 15 3.1 a brief history of wargames it is difficult to date the origin of wargames. most authors give an origin around the 7th century bc. the two traditional ancestors of wargame are the game of go and the chess, respectively: wei hei from china and chaturanga from india. personally, we add to these two ancestors three other forgotten abstract games with similar rules: petteia 2 (greece), seega (egypt) and latrunculorum (rome), which appeared around the 5th century bc. from these very abstract war or battle representations, other kinds of war game appeared. one was metromaxia, a chess evolution which presents around 1578, a medieval battle simulation between two armies and two castles, and a resolution of the battles based on mathematics (boutin and parlebas 1999). some years later, a battleground simulation appeared in prussia. in 1644 c. weickhmann created the koenigsspiel (king’s game). it's a game derived from chess: a first “war chess” model including a board bigger than usual and thirty tokens for each player. one century later, in 1779, j. clerk proposed a simulation of naval engagement, perhaps the first naval wargame (perla 1990, 20). this game used small wooden tokens to represent combat actions between warships with rules including geometry and mathematics to solve firepower effects, ship maneuvers and wind effects. admiral g.b. rodney tested new tactics studied with clerk’s wargame and validated them with his victory in the battle of saintes (1782). we may say that modern wargame history begun at this time. in 1780, c.l. helwig modified war chess to transform them into a modern wargame. he extended the game board to a 1666 squares board, using coloured squares to represent ground variations (forests, rivers, mountains, …) which have an impact on the tokens’ movements. he also proposed the aggregation concept: “employing a single playing piece to represent a large body of soldiers or organized combat units” (perla 1990, 18) and, he included an umpire to supervise the play (to decide in case of ambiguities). right after, in 1797, georg venturini adapted clerk's game with topographic maps (battleships were removed and replaced by battalions). we can say that modern wargame matured in prussia with the invention of kriegspiel (literally wargame) with the contributions of von reißwitz, father and son, between 1811 and 1824. the game used a map like 2 http://www.di.fc.ul.pt/~jpn/gv/petteia.htm venturini's game and rules included a calculation system to quantify the combat effects of different types of units (perla 1990, 28). after a first failure to propose this game to teach war principles to young prussian officers, the game modified by the son was later adopted by the prussian army. we notice than some years later, in prussia, two conceptions of kriegspiel (wargames) are defended: the rigid kriegspiel, based on statistics and calculations for movement and engagement resolution with lots of detailed rules, and the easier and faster free kriegspiel, where troops’ capacities are based on umpire interpretations according to the context. prussian and german victories of the second half of 19th century contributed to develop both wargame systems in others countries (for example usa, uk, japan). later the evolution of wargames continued to be made in the usa. first, lieutenant c.a.l. totten published in 1880, strategos: a serie of american games of war based upon military principles. this game was designed for history fans and is one of the first wargames dedicated to civilians. totten contributed in wargame development with the reintroduction of squares on the board with a topographic square grid map to simplify movement calculation (patrick 1977). second, major w.r. livermore edited in 1882 the american kriegspiel, a game for practicing art of war upon a topographical map, a translation of the rigid german kriegspiel. from livermore, tokens are often counters with specific informations marked above (see figure 2). this solution helps the facilitated use of rigid wargames. after totten's works, civilians quickly adopted wargames for their own use and special problems. the hobby of wargame was developed in two types: board wargames (with counters and a map) and wargames with miniatures (little tin soldiers or vehicles) initiated by h.g. wells's game: little wars in 1912. however, the true wargame hobby development first appeared after the second world war. in 1958 avalon hill created a company dedicated to wargame edition for civilians. the company’s creation was followed by many others during the years 1960-1990. concerning the application of wargames to business, it seems that its beginning is linked to military electronic wargaming development. during the second world war, computers and electronic calculators were developed. in 1958, the navy announced the development of news figure 2: two counters for a board wargame (great battles of alexander, gmt games) http://www.di.fc.ul.pt/~jpn/gv/petteia.htm 16 (navy electronic warfare simulator). then, the same year (andlinger 1958) proposed a kind of business wargame to the consulting firm mckinsey & company (faria and nulsen 1996). 3.2 wargame applications to business from the application to markets and business, wargames are generally called or known as “business wargames”. in these variations (kurtz 2003) (gilad 2009, 17) (oriesek and schwarz 2008, 22), the business wargame is a kind of role-playing game applied to a competitive environment. from the 1970s (kalman and rehnman 1975) the business wargame is thought of as played by a set of teams (2 to 6), often associated with a complex computing simulation of a market and a set of scenarios. the role-playing simulation in competitive business situations with a computing model can be linked to either a rigid business wargame and those without a simulation, which are simplest to manipulate, can be linked to the free business wargame (gilad 2009, 19). a business wargame takes around 6 weeks to 12 weeks to play for the rigid versions (herman et al. 2009, 15) and 1 to 2 days for the free versions (gilad 2003, 90). the phases in a business wargame often follow along the lines of this model (oriesek and schwarz 2008, 119): 1. design: objective and requirement definition, interview with senior management; 2. preparation: game book conception, market and control models development, pre-tests; 3. execution: team motivation, run the wargame; 4. debriefing and documentation: documentation about lessons learned and implications for next steps strategy realizations. unfortunately, in these cases of wargames used for a market, we didn't find a real visual map to identify competitive maneuvers. the only option used seem to follow along the lines of a monopoly board (schwartz and teach 2002). this type of presentation leaves much to be asked for as compared to the more advanced military wargames. this is why we in this research turned to the wargame hobby and in particular to board wargames, in order to find a more interesting and useful presentations for our problem which could include a more dynamic play. 3.3 a board wargame presentation a board wargame usually includes five types of elements: (1) a map, (2) counters or other pieces representing units, (3) rules, (4) a few player aid cards and (5) a set of scenarios. nowadays, there are essentially three kinds of maps for board wargame: geomorphic, geographical and point-to-point. geomorphic maps are mostly hexagonal grid maps (an avalon hill company creation). these maps are generally used for tactical level games. geographical area maps are maps where counters are put on areas identified with others by a frontier. point-to-point system maps use mostly some intersection, generally communication ways to put the counters on. on a map some particular context elements can be shown, like ground variations. geographical and point-to-point maps are generally used for strategic level games. size of map depends on the game, but generally is displayed on a sheet around 17*22” to 22*34” (43.2*55.9 cm to 55.9*86.4 cm or ~a2 to a1 page format). shape of the counters (like in figure 2) is mostly square or double squares. simonen (1977) specified that the standard counter size is 13.86 mm (~0.54”) for a map with standard hexagons of a diameter of 16 mm (~0.63”). counters are designed to present important information for the game. on each counter, a set of data is displayed according to its relative importance. an order and a code (position on the counter and a specific colour) to represent items on counter is chosen to identify one from another. simonen (1977) presents a list of questions to display items on a counter: 1. who owns the counter? 2. what type of counter is it? 3. what is the primary value(s) of the counter? 4. what historical or functional information not included in above categories is necessary for the play of the game? 5. what historical information not included in categories above is desirable to display on the counter even though the information is not functionally necessary? 17 figure 3: great battles of alexander (gmt games) board wargame map with armies to represent the battle of granicus river counters represent most of the time military units or others special elements like unit leaders. to help identification of units, units of the same origin (country or army) are represented with counters of the same colour. in addition, to solve ambiguities in case of a large set of counters, their origin is written on the counter. for the same consideration, the type of unit or leader is displayed with an abbreviation associated with an image representing the unit or the personage. rules explain the historical considerations, the representation scale chosen, items displayed on a counter, sequences of play, and a system to solve engagements and movements (notably, in function of units, types and terrain variations). rules usually include charts to help players solve most of situations in the game. these charts are often offered in the shape of player handouts. finally, a set of scenarios propose some ways to play the game and to consider the historical vision of the game designers. a scenario includes army battle orders (i.e. the positions of units on the map at the beginning of the game), objectives of each army, the duration of the game (or number of game rounds), and a system (victory point calculation) for how to know who has won at the end. 4 method: from marketing warfare to board wargame representations after some discussions with managers and others decision makers, we noticed that marketing warfare notions are too abstract for many. even though, they accept and approve some of the marketing warfare considerations, it is difficult for users to apply them easily to their business. in fact, we had a problem to visually represent marketing warfare concepts. another problem with marketing warfare applications seemed to be the development of how to support attack or defend the strategy of a company. at this moment, we looked for tools and we were interested in the buyer utility map (see chapter 4.1). but, with this tool to help orientate a strategy, we had no solution for the other marketing warfare concepts. as marketing warfare is a war analogy for marketing, we looked for solutions in the field of board wargames. without a real solution, but with some idea of board representation, we then developed our own solution. following the order in which elements included in a wargame were presented, we began with the map. in marketing warfare the prospect or consumer mind is the battleground. we have proposed a very simple solution that anybody can use, understand and modify according to the context or point of view. with tactical board wargames we have considered which elements permit us to understand a battle in terms of maneuvers. board wargames seemed to be the best for this problem (figure 3). like in marketing warfare, we decided that the battleground is the consumer’s mind, from his point of view, as he interprets a product or a service value\interest. 18 4.1 tactical wargame considerations we considered all components of a current tactical board wargame to transform it into a product or service board wargame presentation. first, we decided that tactical wargame maps (geomorphic maps) make a good representation of the objectives. these maps (square grid maps or hexagon grid maps) are practical to define the positions of units and to calculate movements. but, with maps it is à priori difficult to determine the front line. this is why we thought that, like in chinese chess, a river can be very practical for delimitating the front line (figure 3). we also had an idea of the shape of the battle maps that we wanted. second, we tried to define counters. in a wargame, counters represent army unities. in marketing warfare, armies are companies. for our objective, counters should represent a company unit for a particular market from a consumer point of view. thus, we opted to make counters with a particular colour and a representation relatively to each company. then there is the question of what these counters can represent and how they can be placed on the board and move on the map. in wargames, this is developed in a scenario at units scale, along with the order of battle and the rules for movements. this implied that we have some equivalent consideration for marketing warfare representations. with a classical market segmentation grid, most parameters chosen are not ordered except for some of them, like age categories. we want units to be able to move on the map. with a counter corresponding to a classical interseption in a market segmentation grid, it is difficult to simulate few coherent movements with regard to time. however, if we consider à priori a counter movement and link it to the consumer mind, we can have some idea of what a counter movement is. a counter movement is a translation of a value variation of something in the consumer’s mind. reduced to one dimension we linked this to a consumer interest indicator. then we can use a dimension to move our counter and another one to help to put it on the map. if age categories can be ordered, they are not the only element. another alternative was proposed by kim and mauborgne (2000) with the buyer utility map. kim and mauborgne (2000) proposed a solution to identify where and how to present a new product or service. their idea is to consider an innovation according to consumer utility. this map is based on six stages of buyer experience cycles and six utility levers (a set of variables) from the consumer’s point of view. the crossing of these two sets forms the buyer’s utility map (figure 2): “by locating a new product on one of the 36 spaces of the buyer utility map, managers can clearly see how the new idea creates a different utility proposition from existing products” (kim and mauborgne 2000). for this we borrowed fundamental elements of the buyer utility map. for the six stages of buyer experience, we put them in connection with the purchasing process (tyagi and kumar 2004) and we added two stages: know and first use. now we have at least eight stages of consumer experience cycles: (1) know and found, (2) purchase, (3) delivery, (4) first use, (5) use, (6) renew and reload, (7) maintenance and stowage, (8) disposal. figure 4: part of blank square grid map for board wargame the eight stages of the buyer experience cycle are a set of ordered parameters, and the consumer’s interest for something is the second set of ordered values. consequently, from the buyer’s utility map, we transformed the user utility levers into consumer interest indicators and associate these with army unities. then, we suggested estimating the value of one product or service utility by a user/consumer on a likert scale from 0 to 4. 0 represents the non19 existent lever of the user or consumer perception. 4 represent the best satisfaction from the point of view of the user. to get symmetry, we can make 8 columns (from the 8 stages of consumer experience cycle) in which each company unit can be put in relation to a competitor unit. to use a set of consumer interest indicators by column, we divide them in functions of situations studied into 5 to 8 sub-columns and, for more visibility; we insert 1 or 2 columns between the 2 sets of sub-columns. to separate armies, we use 1 line between them, a line in the shape of river and we propose to board this line with 2 others, 1 for each camp. at the end we obtain a standard map on which army units can be put (see figure 4). then, we need to define some rules for the placement of the units and their movements. to be simple, in the point of view of one camp, we put a unit in a sub-column from left to right by beginning with the highest line, after we go to the second highest line, etc., with a displacement of some spaces to complete most of sub-columns with other lines. for the movement, we consider it as a result of a position phase and a combat resolution phase. a position phase is the phase in which a company puts its units on the map and proposes a rearrangement of them. a combat resolution phase is the phase in which we see the difference, for each column, between the total value (i.e. its strength) of a group of units of one army (put them in the sub-columns of the column) with the group of units of the other army in the same column. according to the result, the best group advances from 1 to 4 squares and the lesser group retreats symmetrically from 1 to 4 squares along the column. if the difference between two army groups is null or very weak there is no attack and retreat movement in this column. we propose this engagement resolution table (for 6 to 11 potential counters by column):  4 squares displacement if one group of units has a strength 4.1 or more higher than the competitor's group;  3 squares displacement if one group of units has a strength 2.4 4 higher than the competitor's group;  2 squares displacement if one group of units has a strength 1.5 2.3 higher than the competitor's group;  1 square displacement if one group of units has a strength 1.2 1.4 higher than the competitor's group.  no displacement if one group of units has a strength 1-1.1 higher than the competitor's group. in function of the peculiarities of the situation (ground variations) and the value gap between the two groups of units, the umpire adapts his rule and decides how many squares the movement is. as for free kriegspiel, we can play the role of umpire or we can resort to an expert to play this role. the umpire estimates from the positions of units and other information like the importance of the interest lever vis-à-vis the supposed result of the engagement. this result can have three forms:  each group of units doesn’t move (equal fight);  one group of units moves forward and the opposing group steps back;  one group of units moves forward without opposition. for a product clash map elaboration, the same thing could be asked to the umpire about specificities of the battleground. the question can be asked for each column if movements on it are slower (a 1.6 superiority could be necessary to move from 1 square in place of 2, for example). finally, we need to do a hypothesis about the sequence of events. in fact, in classical board games, each gamer player moves his pieces and calculates potential effects. when the game turn is finished and a new one begins, this is repeated until the end of the game. this is easy, but if we want to transpose some variables for a market with the aim of having a better understanding of competition for a specific type of product, this supposes an equivalent sequence of events. thus, when we consider a battle for a product, we need to consider what the events are and if it seems logical that they form a sequence. position and movement phases are realized with regard to the last position for each column. then the product value scale is moved in function to the movements previously realized. finally, we obtain a system which allows us to confront estimations of two products or services equivalent of the consumer’s points of view to a representation which results a board wargames analogy. even though we only have linear movement by column, we can try to consider attack and defence warfare manoeuvre alternatives with this system. 4.2 inspiration from attack and defence manoeuvres the marketing warfare analogy was made from a war analogy and in some cases from battle analogies. to propose a wargame map of marketing situations, we thought that we would have to realize it in the same way. we looked for some historical battles in order to base our consideration on a visual analogy system. in fact many known battles have begun with a river separating two armies. we have found eight of them which illustrated eight kinds of marketing warfare attack or defence manoeuvres. the battles selected are: granicus river (334 bc), trebbia (218 bc), the sabis (57 bc), mohi (1241), yamazaki (1582), leuthen (1757), austerlitz (1805) and shiloh (1862). of course features of 20 unconventional attack or guerrilla warfare for maneuver considerations are such that we won’t treat them with our proposition. the same problem arises for isolation attack and pre-emptive strikes. thus, we have tried to consider a typical example for each one, attack or defence:  frontal attack: at the battle of granicus river (334 bc), in a narrow passage where the persian army couldn’t deploy its numeric superiority; alexander the great army charged with a bigger quality of cavalry and heavy phalanx infantry and initially defeated the persian center after which the persian army retreated.  flank attack: at the battle of yamazaki (1582), with as front line the enmeiji river, toyotomi hideyoshi (the japan's second great unifier) blocks his enemy akechi mitsuhide, fights adverse right flank with a local superiority and after this maneuver surrounds him.  bypass attack: at the battle of mohi (1241), separated by sajo river, the mongol army attacks the hungarian army at the bridge of mohi. meanwhile many others mongol troops directed by subutai cross the sajo river to the south of the bridge of mohi where nobody waits them. after they attacked the hungarians’ rear flank.  encirclement attack: at the battle of trebbia (218 bc), after some provocations and having hidden some of his cavalry in the upstream to the trebbia river, hannibal waits the assault of the roman army which crosses the river. then hannibal's cavalry which isn't hidden attacks the roman army flanks and his hidden cavalry charges the roman rears.  counter offensive: at the battle of the sabis (57 bc), caesar strengthens his camp to stop the frontal assault of belgium tribes. afterwards he counter-attacks, defeats his enemies and takes their camp.  mobile defence: near leuthen (1757), an important austrian army crosses the schneidnitz river to fight the prussians. frederic the great with half as important an army, but with a better mobility, divides his army in two groups, north and south, to fight the austrians. after a withdraw feint, he brings his north army quickly to the south to get a superior position and then, repels and defeats the austrian army.  flank positioning: at austerlitz (1805), napoleon’s army leaves the pratzen plateau heights to align back to the goldbach brook apparently exposing a weak right flank to his enemies. but, when prussians and russians leave the pratzen heights for attacking, the right flank of their army is exposed to all of the french army. then, the great army reinforces its right flank and engages in a general assault and defeats the enemy.  tactical withdraw: at the battle of shiloh (1862), the union army is surprised by the confederate army and moves back to a second line to defend itself, leaning on two gunboats on its flank. the confederates are stopped at this level and after a day of confrontations, general grant reinforcing forces cross back to the tilman creek and push away the enemy. the major part of this development could be represented with a simple map. first, frontal attack, counter offensive and tactical withdraw can be represented with no modifications. second, flank attack needs to establish the superiority for a group of units and an oblique or rotational movement directed to an enemy group of units adjacent to their column. for this, it seem necessary that the aggressor's group of units is superior to his opponent's group of units in its column and that a link between its column and the adjacent column including the target group for flanking attack can be establish in the consumer’s mind. third, the bypass attack needs a surprise effect on the battleground. to make it possible, we have added another particular stage between two columns. from the consumer point of view, we estimated a new column: divert and propose others functionalities, could be a solution to represent the bypass attack. at the moment, we have chosen to put it between stages (6) renew and reload and (7) maintenance and stowage. this particular stage creates a space in the battleground of the shape of a lake. for our consideration, for a company developing a product from a standard, innovation by addition of new functionalities is always a possibility but risky endeavour. if our complementary solution is not appreciated by customers, our army can’t cross the lake. the lake underlines this risk and shows explicitly where a bypass attack can be realized. fourthly, the encirclement attack and flank positioning defence are from our point of view variations of combinations between the attack and the defence above. we propose according to the case and the context to move units from 1 to 3 squares of movement. all of these movements are good. later, if a relation can be established between two buyers’ experience where a group of units is in the opposite camp, then one has to be afraid of a flank movement in the invaded camp. some units can then be turned to signal the flank movement. 5 a product study: example of market battle by board wargame display to illustrate our proposition, we show a possible interpretation of a home video game console battle between sony and nintendo. this illustration can 21 help to explain our methodology. the battle began in 1989 when nintendo breaks the home console game development partnership with sony. in december 1994 sony answers back with playstation 1 on the japanese market. from this moment, the battle between sony and nintendo implied 7 game consoles: super nes (nintendo entertainment system), playstation1 (sony), nintendo 64 (nintendo), playstation2 (sony), game cube (nintendo), playstation3 (sony) and wii (nintendo). for this information we did a deep interview with 4 people who bought at least 4 of the consoles and know the others. in this specific case, only the battle for the french market could be interpreted. 5.1 map and counter elaborations we know that it is the situation of a market which we have to represent: the french market of game consoles between 1994 and 2010. first, we adopt the consumer experience process to determine columns of the map. we add the column: divert and propose other functionalities. we have at this moment 9 columns. we know which shape of representation we are going to obtain. then, we begin to design counters. second, we need to determine which consumer interest parameters are relevant for this product study. from the list of user interest levers, we did some brainstorming and identified 9 consumer interest parameters: (1) simplicity and facility, (2) autonomy and adaptability (in the variations of context), (3) risk perception, (4) emotions and sensations, (5) well being, (6) cost, (7) trend or tradition, (8) quality and reliability, (9) variety of choice. with these 9 consumer interest parameters, we propose 6 sub-columns by column plus one other sub-column between each column to reduce visibility problems. correspondingly, to obtain the value graduation and the symmetry between the two armies, we separate them for the first turn by the front line river. third, the question of the ground variations is posed. has each column the same importance for the french game console consumer? after a discussion, we decide that columns: (1) know the product, (2) purchase, (3) delivery, (8) maintenance and storage and (9) disposal are less relevant. we colour them in grey and the others in green to mark the differences. now, we need to design counters. we know that there are two counter owners: nintendo and sony. we propose to use a square counters type. the first information on the counter is its owner, and the second one is the consumer interest parameter linked to it. the owner will be represented by its name, a colour and a specific image. nintendo's colour will be white and that of sony, red. for the images, we take the playstation logo for sony and for nintendo the most known personage for nintendo, i.e. mario (figure 5). the consumer interest parameter will be represented by its abbreviation in capital letters (for instance: sf for simplicity and facility) followed-up by its complete expression with a smaller font size. about ground variations, we need to ask about the consumer interest parameters, as some of them are more important than others. the response is yes for: (4) emotions and sensations and (9) variety of choice. we decide that these two parameters are twice as important as the others. now, we have three choices from which to design these particular counters:  write a strength indicator to show its double value (figure 6);  use a double size counter to indicate its double value (figure 6);  double the counter number for these parameters. we make the third choice. then, we ask ourselves if some other information should be displayed on the counters. one could be the value at a given moment of this parameter, but we decide that it is not necessary for the battle representation. our choices of counter design are then completed. figure 5: information display on two counters linked to simplicity and facility parameter figure 6: two others possibilities to indicate the double value of a parameter (size * 1.5) 22 5.2 information gathering when we have determined counters and columns for the game, we can develop some complementary rules and scenario or directly collect important information for the progress of the game. in our case study, we need to have, for each of the 7 game consoles, an evaluation on a scale from 0 to 4 and 9 points of view (our column categories) and 9 parameters (counters categories). we have at the moment 7 charts to complete. we could develop other charts for the estimation of one console at a moment vis-à-vis the competitors' consoles, but we think it's already implicitly present in our 7 charts. thus this reduces the number of questions to ask. then each player completes his charts. an average estimation is calculated by rounding off. 5.3 rules and scenario development first, we must decide on the sequence of events. we make the decision that each battle event is linked to the introduction of a new game console on the market. we suppose that it is reasonable to consider that these types of events can form a sequence. these events will help us determine the number of game turns. from information retrieval, we identified on french market, 5 turns for this battle: 1. 1995, sony presents playsation1. 2. 1997, nintendo responds with nintendo64. 3. 2000, sony proposes playstation2. 4. 2001, nintendo responds with gamecube. 5. 2006, playsation3 and wii are on the market. each turn includes a game sequence. for our development we adopt a game sequence in 3 steps: (1) companies put their counters, (2) by column, unit’s strengths are compared, (3) movement phase is realized in relation to the strength estimation. next, two questions can be asked, at the first turn who has the initiative and is one of the two competitors in a defence position? if the answer to the last question is yes, must we have some special rules for this turn? in our example, we decided that there is no real initiative. but, concerning the defence position, we think that nintendo occupied the ground some time before sony and this is why nintendo has some advantage at the first turn. then, for each group attack by the competitor, as strength estimation, we add implicitly the equivalent of one level 4 counter. at the end one technical problem must be solved. what can we do if the number of counters on the same line of a column is up to 6 (number of sub-columns)? first, we can use one subcolumn to separate columns. second, since we have two counters in double numbers, so we can pile them up in this case. in this last case, a small interval between the counter in the background and the counter in the foreground will indicate two counters in this position. now we can run the battle game representation. 5.4 representation of the home video console battle turn after turn, we can display information in the shape of a tactical board wargame. figure 7 presents a global map with an initial position of the competitor in the mind for the test group. to present other turns and game sequences, we just focus on 4 green central columns: (4) first use, (5) use, (6) renew and reload and (7) divert and propose others functionalities (figure 8). let's form ours charts; the other columns bring no modification in the battle situation. in addition, the size of the real map is too big to clearly display all information in this paper. so figure 8 represents a counter position after the movement resolution at the end of turn 1. 23 figure 7: first turn, first game sequence, sony attack playstation 1 against nintendo super famicom (before movement, map scale 1/5) 24 figure 8: first turn, third game sequence, sony attack playstation 1 against nintendo super nes (after movement, map scale 1/2) figure 9 displays the arrival of the nintendo64 console versus playstation1. in this figure, the movement sequence is completed. we can see the failure of the counter attack and the retirement of nintendo64 units. in figure 10, we note progressive losses of ground for nintendo confronted with playstation2. we see the units of sony crossing the lake to bypass the attack, linked particularly to the possibility for this console to read dvd. figure 9: second turn, third game sequence, nintendo 64 response to playstation (after movement) 25 figure 10: third turn, third game sequence, playstation 2 against nintendo 64 (after movement) figure 11 shows nintendo’s response to playstation2 with gamecube. again we see the defeat of nintendo's units against sony's solution. this figure also shows the sony encirclement attack on the group of nintendo. units in column “renew and reload”. figure 11: fourth turn, third game sequence, game cube against playstation 2 (after movement) finally, figure 12 represents the simultaneous arrival on the market of playstation3 and the wii con soles. we see the nintendo counter offensive for each column. the occupation of column seven by 26 nintendo is explained by the possibility to use wii for fitness. for sony, this column is a continuation of the playstation2 solution with the integration of a blue-ray/dvd reader in playstation3. we can now also see the potential risk for sony, to suffer a flank attack on the column: divert and propose other functionalities. figure 12: fifth turn, third game sequence, playstation 3 against nintendo wii (after movement) 27 5.5 possible interpretations of the home video game console battle with some statistics from the year 2001 on game consoles sales on the french market 3 and in function to the marketing warfare maneuver link, we can propose some interpretations based on this information visualization method. first, we can see, with figures 8 and 9, the mutual frontal engagement between sony and nintendo game consoles. with playstation2, we can see a bypass maneuver by sony. figure 10 illustrates it and the statistics of the year 2001 in france for market shares show: playstation2, 19%, nintendo64, 2%. the nintendo response with gamecube doesn’t try to stop the sony bypass attack. the statistics for these consoles on the french market for the years 2003 are: playstation2, 30% and gamecube, 8%. the real counter attack by nintendo is realized with wii. as for playstation in front of the nintendo64; for each central column implied by the sony assault, nintendo is the better option. french market shares in 2009 for playstation 3 are 20.8% and for wii, 27%. this is a general counter attack. the reduction of nintendo’s response delay with this last console persuades us that the gamecube was introduced on the market as a tactical withdrawal or a flank positioning. we also notice that at this moment and in a similar situation, consecutive failures of the sega consoles (megadrive, segasaturn and dreamcast) in front of the playstation1 and 2, sega choose a strategic withdrawal. the company stopped game console development and now proposes video games for others consoles instead. consequently, and with this example, it seems that according to the logic of marketing warfare, the flanking attack has a more important impact than frontal attack, even though the difference between the forces used is significant. indeed for bypass threat (figure 10 and 11), differences between the french market shares are respectively 17% and 22 % for playstation2 vs nintendo64 and playstation2 vs gamecube. by comparison, when the nintendo wii counter attack is realized, it is similar to a frontal attack and the french market difference is 6.2% for the year 2009. 7 conclusions and perspectives we have investigated some fundamental principles of marketing warfare to see specifically what kinds of maneuvers can be used to defend or take a certain market. in parallel, we have presented military wargames and its history to ease understanding of the fundamentals in this area of study. the reason is that tactical wargames propose some solution to recreate a specific battle with the use of army maneuvers. since we did not find a visual business wargame solution for our problem in the literature, we decided to develop one. for this, our approach 3 agence française pour le jeu vidéo: http://www.afjv.com is based on current tactical board wargames for civilians. we have presented all components to be found and an equivalent for each component in order to generate a product clash map. then we introduced the tokens of the game, as they are important variables for the product’s potential consumers. to define battle orders, we used an ordered set of process steps in correlation with an estimation scale of consumer interest for the product concerned. with these elements, we reconsidered a classical tactical maneuver as defined by a market warfare situation for our battle map system. we concluded than most tactical maneuvers could be interpreted with this system. finally, we have shown how to interpret a market battle with this kind of information display. to prove this we built a wargame to represent the battle of a home video game console on the french market from 1994 to 2009. it showed that a parallel could be made between tactical maneuvers on the map and the statistics of sales for this market at a given time. thus the usefulness of the game seems to have been confirmed. future research: we now continue ours experimentation to make board wargame in order to simulate other market examples. we hope to develop a software dedicated to this, with an additional possibility to transform a square grid map into a hexagon grid map to improve the connection with tactical wargame maps. in our opinion, this information visualization tool permits one to perform competitive intelligence with the possibility to add substantial value to the organization. another advantage of this methodology is to extend the question about the company environment to identification of threats and market 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(2017) why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company. journal of intelligence studies in business. 7 (2) 27-39. article url: https://ojs.hh.se/index.php/jisib/article/view/221 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: integration of business intelligence with corporate strategic management patent bibliometrics and its use for technology watch björn jürgens pp. 17-26 why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company journal of intelligence studies in business v o l 7 , n o 2 , 2 0 1 7 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 7, no. 2 2017 klaus solberg søilen pp. 27-39 an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france sophian gauzelin and hugo bentz pp. 40-50 mouhib alnoukari and abdellatif hanano pp. 5-16 the impact of supply chain management on business intelligence audrey langlois and benjamin chauvel pp. 51-61 why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se received 15 april 2017; accepted 22 may 2017 abstract this article tries to show the importance of the competitive intelligence (ci) and market intelligence (mi) function by describing developments in two quite different swedish multinational companies. we see how top management can become the problem when the company is struggling to compete and how this affects the intelligence function. in the analysis we compare the intelligence function in private companies with those of state and military organizations and draw historical parallels. moreover, the cases show what an important role competitive and market intelligence continue to play in the age of information, especially during the past decade. keywords competitive intelligence, defensive position of top manager in distress theory, high salary theory argument of top managers, market intelligence, organizational theory 1. introduction why should anyone working in a private company care about competitive intelligence (ci) or market intelligence (mi)? why is it that these areas of study are not more widespread in companies today, despite the fact that the literature has existed for almost 60 years? (alden1, 1959; keegan, 1974; dedijer, 1975; porter, 1980). were the ideas a failure or were they underestimated for a long time? other management practices and bodies of literature, such as strategy or leadership, are more established both as a practice in companies and as theory in the academic literature. why is that? is it because competitive intelligence and market intelligence work is being done by others whose job descriptions have other names, such as marketing research, business intelligence or 1 alden studied under professor georges frederic doriot at harvard, a frenchman who later founded insead. doriot like stevan dedijer, who was 12 years younger, fought for the us army during the second world war. strategy? or is it the haunting association to espionage that so many have been trying to disassociate from competitive intelligence? these questions are frequently raised at ci and mi conferences, especially by professionals who work in the field. in this article i try to find an answer to these questions with the help of two cases, looking at ci and mi practices at two swedish multinational companies: ericsson, a swedish multinational networking and telecommunications equipment company with more than 100,000 employees and the swedish cellulose company (sca), a swedish consumer goods company and pulp and paper manufacturer with 44 000 employees worldwide. during the past decade i have been able to study ericsson from different perspectives, mapping the company’s value chain (søilen et journal of intelligence studies in business vol. 7, no. 2 (2017) pp. 27-39 open access: freely available at: https://ojs.hh.se/ 28 al., 2012) and their innovation benchmarking (søilen and tontini, 2013). in an article from 2010, i describe seven organizational placement models for ci, where ericsson was the model for one of them: the special department model of intelligence. a decade ago the company placed the ci function as an advisory function to top management. the advisor had the title of “director” in swedish meaning he was a part of the top management. he was a senior staffer who enjoyed considerable trust and authority in the company. in the other companies i looked at the ci function was placed differently. the other models described are the special department model of intelligence, the professional model of intelligence, the topdown model of intelligence, the integrated intelligence model, the down-up model of intelligence and the departmental model of intelligence. ericsson chose the advisory model of intelligence as a direct response to problems with the special department model of intelligence: “the major problem with this model is isolation and its consequences. special intelligence departments tend to close themselves in and develop projects they think but do not know will be useful for the company. their more or less self-initiated projects will only be useful to the extent that the special department know exactly what intelligence is needed. if they do not communicate well with top managers their work will build too much on guess work, and the output will be less relevant.” p. 54 søilen (2010) six years later ci work at ericsson does not fit into any of the above mentioned organizational models. a new diagnostic is needed. this raises some further questions, like what has happened in ericsson in general and with the intelligence function in particular? why did they leave the previous model and choose the current one? another swedish multinational company, the swedish cellulose company (sca) has organized their ci activities around the special department model of intelligence. it has worked in this way for more than a decade and a half without any drastic changes. the ci function at sca has today about ten employees and regular and formalized contact with top management, much as described in earlier research. how come these companies, who in part have the same owners, think so differently when it comes to ci and mi work? 2. method the research strategy is a case study. the purpose of the research has been exploratory, but concentrated around the initial questions. the extent of researcher interference has been minimal as i try to keep my own opinions back and let the other person speak to the very end. the study setting is non-contrived, meaning the people were interviewed in their normal environment, either coming out of work for a lunch or meeting at a conference. the unit of analysis is individuals. the data collection method is interviews and the analysis is qualitative. to answer the research questions i use interviews conducted with key employees in ericsson over a fifteen year period, some of whom have become acquaintances over the years. most of the twenty-six employees interviewed at ericsson have had key roles in ci. others have worked with technical intelligence and with value chain and marketing issues. some of them worked in the previous organization sony-ericsson and at ericsson mobile platforms (emp), which ceased operations in 2009. the time horizon for the research can therefore be said to be longitudinal. for the current research a new set of interviews were conducted between november 2016 and march 2017. five key employees engaged in different sides of ci and mi work in the company were interviewed for about half an hour informally (over lunch), separately and independently, meaning they had no knowledge that colleagues were interviewed on the same topic. conversations with sca employees are more recent and serve here first of all as a comparison to current practices at ericsson. two employees were interviewed. one is the head of the ci unit and the second is a top manager who is a receiver of ci and mi products. conclusions are not drawn directly from what any one employee has said, but are the result of analysis of conversations with multiple people over time. in the analysis i compare the development of the ci and mi fields to other business studies. a historical analysis is attempted and a comparison between the private and the public sector intelligence carried out. 29 3. theory in the theory part we are interested in the kinds of literature, cases and examples from the companies sca and ericsson (1) and theory about the problems raised in the article (2). we shall start with the first. there are no cases on sca and ci published as scientific material to my knowledge. practically all papers related to sca are on natural science topics, like storing, transport and processing for a forest-fuel supplier and pulp products. as i will not discuss these papers i am not going to cite them. the number of case studies on ericsson are numerous but less relevant here, so not cited either. what is relevant are articles were ericsson is used as an example for ci and mi. the first is an article by doz et al. (2001), where ericsson is mentioned as one of the companies threatening american industry, “companies as nokia and ericsson, with roots on the edge of the arctic”. it is the realization that competitive advantage is primarily based on knowledge and that that knowledge can be found anywhere. the perspective is that “tomorrow’s winners will be companies that create value by searching out and mobilizing untapped pockets of technology and market intelligence that are scattered across the globe”. the same year there was an article by rouach and santi (2001) where ericsson is mentioned as the first example of companies with a warrior attitude who take an offensive stance in the market; “the intelligence analyst is very pro-active in managing the competitive intelligence process, and continuously on the look-out for opportunities”. the year after, herring (1992) wrote a case about business intelligence in japan and sweden. he criticized senior managers in the us for not taking business intelligence seriously, for “not adopted intelligence as a strategic management discipline”. japan and sweden are mentioned as examples of countries that do take this discipline seriously. ericsson is mentioned as a primary example. crane (2005) told the story of how ericsson was a victim of industrial espionage in 2002 related to products for the aircraft industry: “the events of the industrial espionage case centered on the alleged leaking of company information from ericsson to a foreign intelligence service”. two ericsson employees were caught and suspended and two russian diplomats accused of being involved were expelled. in 2011 gilad criticized executives for not focusing on ci. he argues that they see it simply as competitor-watching and therefore of no real value to executives. this has left their companies vulnerable to disastrous blindsiding, he concludes. as for the second type of theory related to specific problems addressed in this paper, it is discussed in connection with each issue or argument as they appear below. 4. empirical today five ci people at ericsson work more or less independently from each other in different parts of the world. they work on different projects, many of their own choosing, and have only occasional contact with each other. there is no list of specific reports that they turn in at regular times of the year, but some types of demands are reoccurring and more frequent. it is a combination of push and pull intelligence. i shall call this the consultancy model of ci as it enjoys independence, freedom and autonomy but as the function and job is uncertain. efforts have been made to bring ci staffers together, but this has taken more effort and time than is expected. the status of the employees’ positions in the company is not given and they continuously have to defend the value they bring to the company and to higher management. access to higher management is not a given but is decided on a case by case basis. sometimes their reports receive attention and are read by top management and passed along, sometimes and more often the are not. ci work in ericsson deals with convincing top management of the value of ci. mi is a term used to a lesser degree at present. a first conclusion is that the work is more about social intelligence, not in the sense that stevan dedijer gave it in the 1970s, but in the sense of ‘social skills’. it is about selling ci to top management, about trying to present ci in a way that is appealing to top management. another way to say this is that it is more about how than about what is being delivered. as an example, one staffer found that it is much easier to be heard and kept in the loop when he asks questions instead of providing answers to specific problems. when he provided specific answers in the past he found that he was often being questioned. the more specific he was in his answers the more critical they tended to be. top managers reacted particularly negatively towards receiving exact numbers. they often thought they knew better. this would lead to arguments and 30 disagreement. as a consequence the staffer soon felt excluded and the importance of his function or contribution was weak. at a certain point in time he started asking questions instead, so instead of saying “the market in brazil looks to weaken by 15% annually over the next three years”, he would ask “how confident are we about increased sales volumes in the brazilian market over the next three years?” the new ci focus was on defining the problem area, but not the actual problem. he was now part of the analysis, but left the answers to top management. the latter approach opened the way for influence in the organization. the next question then is why didn’t the managers appreciate the more accurate answers? one reason suggested by staffers is that top managers feel threatened by exact numbers. the reasons for this may be two; for one it is often assumed that managers know best. top managers in private companies are paid very high salaries for their knowledge and decision making skills. these decisions basically consist of two parts, one is the information set or the intelligence at hand, the other is the analytical abilities of the manager. if the actual intelligence for a decision is provided by another party, this only leaves the decision making part to the manager. in theory both parts could be made transparent, that is, it is possible to show clearly the most important pieces of intelligence needed to make a decision and it would be possible to show the analyses used for making the decision, for example a swot or pest. if both elements are transparent it is possible to go back and evaluate decisions and the decision making process of each manager in a way that is not done today. it would then be possible to see which pieces of intelligence were not used or used incorrectly and it would be possible to point to mistakes in the analyses or critique could be raised as to the analysis that was selected for the given data and the problem at hand. in other words the managers’ abilities and performance would be stripped naked in a way that is rare in organizations today. owners would better be able to see what they are paying for. they could then discover which top managers are overpaid. the argument is that this is not something that the manager wants so he (it is often a he) does everything to keep the process hidden or muddled. if this is true it becomes obvious that effective ci and mi procedures can only be imposed by the owners, not by top management itself. these observations though do not explain why ci work is so different in sca and ericsson. the second reason is that when the company is under considerable financial pressure due to heavy competition, like the case is today in ericsson with huawei continuously breathing down their neck and potential new entrants in the ip technology sector threatening to disrupt the industry, employees in general and managers in particular become more concerned about keeping their jobs. this means that they become risk adverse about their own position and more concerned with showing that any success or progress made in the company is their own doing. top managers who find themselves in this situation do not want to admit that someone under them, a subordinate like a ci staffer, knows more about what is going on than they do themselves. as a result they become more defensive towards subordinates who think they know better. this is a confirmation of another problem: that ci deals directly with knowledge and as we know knowledge is power. by asking questions instead of delivering answers the ci staffer becomes less of a threat. the top manager can then take the information given and the credit for the decision to show that he has the knowledge needed for the job, that he is indispensable. this view of organizational life based in critical theory is not pessimistic, but realistic and can be found in the writings of alvesson on organizational culture (alvesson , 2012; alvesson, & sveningsson, 2015). it is a view that is opposed to instrumentalist and constructionist contribution in organizational theory, as developed in the neoclassic paradigm. i will call the first reason for lack of ci efforts the high salary theory argument of top managers. the second argument i will call the defensive position of top manager in distress theory. in ericsson both phenomena are making the work of ci and mi less efficient and more difficult. what was then the reason why ericsson left their previous model of ci, according to ci staffers, one may ask? for decisions or changes of roles and functions in large knowledge intensive organizations we expect good reasons. for the question why ericsson left the advisory model of intelligence and adapted what i have called the consultancy model of ci there does not seem to be any clear answer, at least not when ci staffers are asked. from the 31 interviews it seems the advisory model was left when the person who filled that position left the company and retired. no clear effort to continue the function seems to have been made. ci staffers currently at ericsson do not remember the previous model or how they worked, nor do all remember the person who used to head it, even though he was well-known in the company only ten years ago and had worked there for more than two decades. part of the reason may be that most ci staffers today have held the role for less than five years and came from other functions and other countries and markets before they entered into their current positions working with ci and mi. in many respects we see that current ci staffers started ci work from scratch, organically, seeing an opportunity for ci assignments and taking them, only then realizing it is a developed academic field. knowledge of ci and mi was not passed on from one employee to another. is this then a defeat of the professionalization of ci, or just a new more flexible version and model? it seems clear that ericsson has been losing competitive strength for a number of years. the failure of sonyericsson was just a step in this development. the growth and strength of its competitor, huawei, continues. in addition the threat of new entrants is becoming ever more likely in what could be a technology shift. ericsson used to be the preferred partner in western countries for security reasons (as they are not chinese), but also this advantage has disappeared it seems everywhere except for in the us market (where huawei is still blocked from major infrastructure projects). it is a contradiction of organizational life that companies in trouble perform worse exactly at a time when they need to perform better. i shall call this the contradictory organizational theory of companies in trouble, but not pretending that i am the first observe such a phenomenon in organizational life. there is also some strength to the existing consultancy model at ericsson. it appears to be more flexible and can easily be adapted anywhere and everywhere in the organization. it is easy to set up and to dismantle, builds on continuous evaluations and it invites the use of external consultants or anyone with the right knowledge. as such it could be a ci model for companies in trouble. from a methodological perspective the question is if we are measuring the actual importance of the ci function as such or if we are seeing a ci model in a company struggling to survive in a very competitive market. in other words, is the ci model at ericsson a result of the situation they are in, or is the situation they are in a result, at least in part, of the way they have set up the ci function? comparisons to other companies like the sca suggest that it could be the latter case as the ericsson model of ci deviates from practice in other swedish multinational enterprises (mnes), but more studies are needed. sca is a company in rapid expansion and growth, partly through new acquisitions, but also though reorganization. none of this has altered the ci function in the company, which follow an old established model. a few years ago the ci department had to cut staff by two employees, but increased efficiency in the department has led to even higher output and more professional standards. the structure of the ci department is the same and they deliver the same standard reports each year more or less. their work is defined by regularity, stability and mutual trust. the question for the analysis is: is the consultancy model a good choice for ericsson in their current situation? should ericsson and other companies put more emphasis on ci? in other words, does ci matter? 5. analysis companies in difficult situations tend to be a bit like mediaeval rulers, who will decide to execute the messenger. this resembles the role of the ci specialist in ericsson. by changing his role from one of being a bringer of facts to one who asks questions instead the ci specialist managed to save his life, but only to find himself turned into another medieval figure, the court jester. the court jester is focused on pleasing his superiors, not on delivering need to know information and telling the truth. when a company is in a difficult situation the organization tends to becomes more political, and therefore less concerned with facts. managers become occupied primarily with defending their own positions and existing perks rather than with keeping the company alive. if everything goes wrong financially managers can jump ship and find another company to work for. with the high salaries they are given they can afford to take their time when looking for new opportunities. as long as they do not make any outright mistakes that lead to disasters for the company they will be able to leave the company with 32 good references. those who stand to lose the most in this are the owners. thus it is in the interest of the owners, more than the managers, that a good ci function is put in place. the problem is that this is not a decision normally made by owners, but by the managers. this then is a catch 22 situation in management theory, a problematic situation for which the only solution is denied by a circumstance inherent in the problem. owners could realize this and play a more active role, for example by giving directions from the board, making the company implement an active and extensive ci model in the organization, given that it can be made to lead to better decisions. 5.1 managers’ unrealistic expectations of the intelligence function another problem that was raised in the conversations with ericsson employees is that managers often have expectations of the ci function that are too high. they expect to be able to “see into the future”, what unfortunately is promised in much of the academic literature, for example on the topic of “foresight” and by consultants eager to sell business intelligence solutions. as agrell (1998) reminds us, there is much talk about breakthroughs in this area, but it is still much about guessing and making mistakes (p. 118). not much has changed in this area. it does not mean that studies of ci are useless. on the contrary, what we have developed in the study of the scientific method in the social sciences gives us more information than if we did not do any analysis at all. this then should be the first insight. instead of waiting for the next management guru, managers should assure that their analysts are well trained on the topic of science and the scientific method and not duped by promises of theoretical revolutions in other disciplines. managers often take in consultants when they want to make changes but do not want to stand for the consequences. for example, sacking employees is then the result of an external report and “was not what the management wanted”, it is argued. in somewhat the same way management gurus are brought in to spread uplifting ideas in any area where enthusiasm is needed regardless of whether it’s true or not. instead these services are often a simulacrum of doing something or of looking like the organization and top management are up to the task. managers take in ci specialists to talk about the future and what will happen in the future, thinking that by talking about it the organization stands a better chance at an actual prediction. predictions of the future can be correct when the future is a close function of the past and current events, when there is a pattern and a clear logic to follow, but not when there is a break with normal logic. we can classify different types of differences that break with this logic and therefore are almost unpredictable; innovation is one example (1). a sudden unexpected innovation that leads to a new product like the touchscreen on mobile phones was what drove sony-ericsson out of business. another group of changes is disinformation (2), when we chose to believe something that is put out there that is willingly and misleadingly false; as when companies stack great piles of empty boxes in front of a store to signal that they are successful. a third type is natural catastrophes (3). trends are less of a game changer as they are easier to predict. for example, duffel coats seem to come back in fashion every 5 to 7 years. we can often tell a year in advance, but the logic here is commercial: the time it takes a consumer to throw away his old coat. so, are there no advances when it comes to foresight since agrell made his observations? yes, there are, but not in the field of management or the social sciences. with the development of big data, data mining and business intelligence application companies are now able to make better predictions that can be derived from historic data. for organizations who own very large sets of information like amazon, google or facebook, data mining can reveal detailed patterns about our behavior and general preferences. however, artificial intelligence (ai) as discussed today, mainly builds on the historical method, assuming the customer will do as he has done. this method is far from perfected today. as an example amazon can still not guess what i will buy next, even though they are trying very hard to do so (basically assuming that i want more of the same or combining it with something i wrote in an email or searched for). the internet giants know what my interests are and when i type ‘malaga’ in the browser or somewhere it can access or exchange data with, but they assume i want to go there and offer a rental car, which is a fair guess, but wrong (i was just corresponding with a colleague at the university there). and still, these new 33 intelligence techniques built on what i type are more useful when it comes to questions of customer purchases than what will happen in world politics. the technology works fine for selling targeted or tailor made advertising, but will not answer our question about what ericsson should do in the brazilian market in the next three years. another problem for ericsson and all companies that are not in the big data business is that they do not have access to this kind of information, as it is not shared by the internet giants. our behavior becomes their property which they do not share with others, not even with us. our data becomes their currency; what we pay them with when we access their services “for free”. instead of money we have given them pieces of our lives, even our private photos. for business intelligence software to be valuable, larger amounts of data are needed. companies like ericsson can buy a lot of data or rent it, for example with data as a service (daas), but it will not come cheap. consequently, the results of the exercise of implementing these systems for companies, even for larger companies, are often a disappointment when it comes to the broader questions, which are relevant for the ci function. another problem is that managers tend to be uncritical towards the answers coming out of or from these systems. in other words, there is an over-belief that foresight is possible with new technology, a view that is pushed forward by managers and consultants alike of reasons i have tried to show. 5.2 the problem of the ci job description participants at ci and mi conferences often complain that intelligence work is not defined as a proper position in the company. they would like it to be so, or are even promised that it will be so by their superiors, but end up doing a whole range of other tasks in the company instead or in addition, like more general marketing and sales. so those interested in ci work often express a feeling of disappointment vis-à-vis the specialization. this has been the case for the past 17 years that i have participated at conferences and probably much longer. the question we must ask is if it is a failure of ci and mi that it does not correspond to a proper full time job description. the two cases give little insight into this question as employees at both ericsson and sca are labeled something with “ci”. in the case of ericsson the ci specialists have job descriptions that say ci specialists or similar, for example “director of competitive intelligence”. this is also the case at sca and in numerous larger swedish mnes. however, in most companies employee’s engaged in ci have different titles, liker sales manager, director of hrm or key account manager. ci is not a major part of their job description and does not occupy most of their time at work. there is no indication that companies who do not have full ci positions perform any worse. it seems, at least in sweden, to be more a question of the size of the company. performance seems to be more related to how they work with ci, but future studies should look at this. there is a wish by many ci professional and larger companies to develop departments of intelligence. those working with ci at ericsson for example seem to favor this. in sca this is already the case. in ericsson such a department was never developed, as they followed another model, but it has existed at companies like seb for more than 100 years. so, established ci functions are far from a new idea and far from uncommon. part of the reason why employees focus on positions is the way we think of departments. most disciplines in business started from the perspective of departments that exist in companies. there is a human resource department, so there must be a study of human resources or human resource management (hrm). in the same way there is an accounting department and there is a marketing and sales department and we study those fields with their proper subjects and courses. there may also be a finance department or employees working with finance and controlling. managers deal with strategy, leadership and decision making, so those are other welldeveloped areas of study but without a proper department. then there is the sociological perspective as in the study of organizational behavior, a sort of from-outside-perspective by sociologists or academic outsiders. ci can be its own department, but it can also be something mangers do, just like leadership or strategy. ci and mi as a working process are not typical for any one department, but may occur in different areas such as finance or in marketing. this may also explain why organizations must reach a certain size before it makes sense to turn the ci or mi function into a proper department or position. it does not mean that these functions are any less relevant than accounting or hrm. it will be suggested next 34 that it means that the intelligence function in private organizations is lagging behind its equivalent in the public sector. 5.3 the intelligence function in private and state organizations we have entered a new phase of the information age when the average private organization can access the amount of data and information that was previously only available to state and military organizations. we easily find facts with google, facebook or linkedin. we study detailed geographical images with details for buildings and trucks on google maps or use gps tracking devices. we leave reviews on tripadvisor and set up cameras for surveillance that are linked to face recognition. in addition we now all publish and we can read what others publish, for example on twitter. this leaves an abundance of information about everyone and everything which resembles the capabilities that only states used to have. what used to be accessible to state intelligence is today within the reach of everyone with some basic internet resources. the notion of competitive advantage builds on knowledge and knowledge in turn builds on reliable information, facts or intelligence about the world and all the things in it. a private organization today with a small intelligence department can gather more data than what the state could do only a decade ago. thus the idea of a professional intelligence model in private organizations has never been more convincing. strategy builds on the assumption that managers today have or know how to find information needed to make good decisions. this assumption must be questioned. managers in the private sector, unlike their counterparts in the public sector—such as generals, ministers or heads of states—get most of the information they need themselves, either by what they know, by whom they know and can ask or from reports they buy and read. the logic in private organizations is that it is assumed managers are well informed and make the right decisions without much assistance because that is what they are paid to do. in the running of the state, where pay is considerably lower, ministers are surrounded by advisors, special departments that can do research, and call in the best experts. besides they have a large intelligence organization at their disposal for both internal and external information. it has been suggested in this article that the high pay is a reason why the manager does not like to listen to advice, especially not that given by people further down the hierarchy. what we have to ask is why the situation for ministers or generals is so different? why is it that generals are dependent upon support and value and appreciate intelligence and the help from the intelligence department while most managers do not? when we look at history we find that the generals were in the same situation as managers are today. during the napoleonic wars the general ruled all by himself, as he was considered a military genius, he simply knew what to do. he had spies out looking for what was happening in different directions, but no intelligence unit helping with coordination and processing information to make decisions. instead he stood on a hill a bit away from where the main action was taking place and sent out his orders. when the army won everyone thought he was brilliant and he would ride down from his hill and make a spectacular entrance into the city like a roman military leader. in some sense the practice of management today is not that different. when managers succeed they are rewarded with salaries that are many hundreds of times higher than those of an average worker, they get bonuses and their portrait on the front page of fortune magazine. it was first later with the development of the prussian and russian military command that a second department was formed, one engaged with special responsibility not for engaging in war that was the responsibility of the first department of “the general command” but of strategy and intelligence. in this way a superior army was produced and the organizational model soon copied by other nations. from then on intelligence organizations became standard in the military and have been so ever since. sometimes the army will experiment with mixed, shared or integrated models of intelligence, but so far these versions have not been convincing. as an example, in sweden it is accepted by many that the air force has the best intelligence organization because they have been organized in their own separate department for a longer time and have more experience as specialists. in the next stage the military intelligence model became a standard for the way the state was run, to assist ministers and heads of states. the logic was that if the military can make better decision with an intelligence 35 organization so can the state. later this function was again divided into a domestic and a foreign branch, which made sense as these are two very different specialties or domains. it’s easy to forget that the professionalization of the intelligence functions in the military and the state is less than a century old. the cia was mostly built up around the experience the us had working with the british during the second world war. the nsa was mainly built as a response to the failure of pearl harbor. the number of intelligence personnel working for the state today runs into the millions. no one in the military and no heads of state today will seriously question the importance of having an intelligence organization or department. it is more a question of its size, efficiency and what priorities the organization should have. the question we have to ask is if the private sector is so fundamentally different that it can ignore these developments? is business life not also basically about gathering information and about decision making in a race for a competitive advantage and ultimately for the survival of the firm? after we entered what is called the information age the answer seem to be clear, especially when we consider how information and the internet has come together during the past decade. just like the 1980s and 1990s were about logistics with ikea, dell and walmart, the early 21st century is about data. facebook is not about friends and amazon is not about books. they are both about reaching as many potential customers as possible to gather as much data as possible. the basic human need for friends just happens to be a way to achieve that. amazon started to grow by selling books, but soon discovered that they can now sell almost anything. their data centers are not that different from those of the nsa or equivalents in other countries, gathering data about people 24/7. both the public and private sector are run according to the principle of competitive advantage. states need annual increases in gdp to guarantee their citizens a higher standard of living, so they compete economically with other nations. a failure to bring about economic growth on a continuous basis will lead to a weakening of the state when compared to other states. for their citizens, this means a lower standard of living. economically weak states are prone to social instability and poverty, and in the end to dictatorship and revolutions as we have seen several times in modern european history and which we will see again. we remember that the modern study of economics started with the notion of competitive advantage with adam smith in 1776. the question was what makes a state prosper. ceos are concerned with the same question, how they can compete with other organizations, and eventually how they can make enough money to satisfy investors and owners. right now ericsson is wondering how they can compete with huawei. if they fail to achieve this, ericsson employees will lose their jobs, and in the worst case the company will go bankrupt or cease to exist, like st ericsson, its daughter company, did. like states, companies today have to take advantage of the great amount of information available to them. the existing business literature and the study of economics in particular have not drawn the right conclusions from this paradigm shift. on one side the amount of data available for making good decisions has increased beyond the wildest expectation. on the other side the costs of this information have become so low that it’s available to almost any company and any person with some data equipment and an internet connection. competitive advantage today is to a large extent defined by how companies access this information and what conclusions they draw from it. this is an impossible task for a manager to succeed with by himself. he does not have time to read and digest the amount of information needed, in many cases he does not even know where to start looking. this is a situation that resembles that which the state and military organizations found themselves in not much more than a century and a half ago. good information or intelligence has been assumed in the study of economics and later in business studies and the management literature. there is also the assumption given by vendors in particular that computers will do it all for us, that it’s enough for the manager to buy the right software (business intelligence) and the machine will give the answer. instead, as we have seen, the software is only as good or helpful in decision making as the quality of information we put into it, according to the formula garbage-in-garbage-out (gigo). consultants today say they have an answer to this problem with daas, the idea that if you do not have the data to put in to the machine yourself then you can buy it, or rent it, but today this mainly works for certain questions 36 and problems, what we could call “library questions”, where the clue is to look up something (søilen, 2016). for more typical intelligence questions, of things we do not know, dealing with future scenarios, we need data input that comes through a comparison of current events with a broad reading (not so much management literature as literature, history and philosophy) and extensive travelling (understanding other cultures, which includes learning other languages). this you can only get through a good general education, extensive reading and experience. our computers are not there yet. instead computer systems are good at delivering one kind of data (søilen, 2016). new technology is also a threat to companies. today every individual is a potential spy. corporate espionage has become a big problem, its consequences still underestimated. hackers can easily be hired to break into competitors’ data systems and security systems are often weak. companies are closing their eyes to encryption afraid that it will make business communication more cumbersome. those industries that are being hacked, like banks, keep quiet about their losses and do not report about the hackers successful entries into their systems afraid that it will scare customers to withdraw their money and move to another bank. the next development in technology will be perfect voice recognition which will make counterintelligence an even a bigger problem. a competitor can then call an employee pretending to be someone from his work. this technology has again triggered new counterintelligence technology, like programs that can detect if the voice is real or not, but adaptation of such systems will lag behind for a long time. with internet technology corporate espionage has become massive as it has become easier and less risky to break in to corporations and steal assets such as money or intelligence. private organizations are facing many of the same threats that used to be the problem only for states and military organizations. this is yet another indication of how relevant the intelligence parallel is for both worlds. to deal with these new threats companies need to catch up and start to think of themselves more as intelligence driven organizations. they are already living in an intelligence reality but they are lagging behind in its implementation. one reason companies do not think of themselves as such is that they use other terms for the same activities. for one thing we say information instead of intelligence even though all organizations make a distinction about the quality of the information gathered. for facebook the information that a customer opens the application is less valuable than actually clicking on specific posts and some posts give more valuable information than others, for example a customer clicking on a specific advertisement. another example of the use of different terms is human intelligence (humint), gathering information from people we talk to in person. it is such a natural way of doing business that business people hardly ever think much about it as such. sending out agents to gather information on customers and markets is not spying but what the marketing department does when it talks about market research. we do not talk about interrogations but deep interviews. sometimes the notion of an agent is used in theory, but it is rare. the relationship between the intelligence provider and the decision maker, or the ci person and the manager can be understood with the help of principle agent theory. the relationship between the agent and the principal is one of mutual dependency, where the principal is best served by the ordering and delivering of good information over time, slowly. the agent must learn what kind of information is needed and the principal must learn to trust the agent and the information that is given. it should be a professional relation built on mutual trust and as such the logic is quite similar in the public and private spheres. these are just some examples. avoiding the intelligence lingo is a deliberate effort by companies to avoid the stamp of being brutal, aggressive, or of being spies, with all the negative associations that brings. the ethical dimensions within the phenomena are very similar. the separate sets of terms may in part explain the reason why ci and mi have been late to develop in private organizations. in ericsson the ci function is lacking today. the company may still survive and prosper as most measures of success are not related to this question. the current ci model in ericsson may also be part of a transitional phase, but it is more likely to be a symptom of an organization that is struggling uphill, a company losing its competitive advantage. it is symptomatic that the organization does not remember how the company used to do ci only a decade ago, who the people who worked there were, to say nothing about how they worked. what is worse, ericsson seems to have limited 37 knowledge about their competitors. ci people have not even been to schenzhen to study their biggest competitor and are more often than not unfamiliar with chinese culture. as such they remind me of western students in sweden who prefer to stay in town and party when there is a school break, while as the chinese students hire a cheap car, fill it with staple food and drive to the north cape. competitive advantage is just as much a question of mentality. the ci problem is not solved by throwing lots of money at it either. expensive ci is not the same as good ci. few american companies put more emphasis on ci than motorola inc. the company failed and it all happened quickly, as it did for st-ericsson. in the case of motorola inc. the company’s production costs were too high and overestimated the value of their high end products. ironically it was later bought by a chinese counterpart and continues as motorola mobility. as competition intensifies the speed by which huge companies are brought down surprises everyone. these examples are not exclusive to private organizations, but are also familiar to nation states. in june 1967 the egyptian army was knocked out by a superior israeli air force and, as they had no information about what was going on at the front, the war ended abruptly. stasi, the intelligence organization of eastern germany, was known for knowing everything about everyone in the ddr. still they were taken by surprise when the revolution broke out in 1989. over a few nights there was no stasi, not even a ddr. from a theoretical perspective it is the social sciences that are failing (søilen, 2017). the social sciences are still in their infancy, struggling to find their guiding paradigm and a common project. as such they in the same positionas the study of biology was at the start of the 19th century: highly fragmented and rather unscientific (mayr, 1942). the discipline of intelligence studies in business is a part of an attempt to change the focus and paradigm for the socials sciences by trying to study a phenomenon that is relevant in a way that is relevant (method). until it gets more recognition it is a discipline and a profession that will have to accept a place in the background. it does not mean that these areas and the people and what they do are less relevant, on the contrary. 6. conclusion in this article we started with the question of why anyone should care about ci and mi by looking at theory and practices in two swedish multinationals, ericsson and sca. the short answer is that data or intelligence is the future of success for all companies that rely on computers systems as part of their business idea or model, not just big data, data mining and business intelligence but ci and mi. this is something companies have known for a long time, but which few have been able to implement. so, the interesting question is not why it is important or why anyone should care, but why it has not happened. this then is the real question which this paper tries to answer. when seb started its intelligence unit more than 100 years ago in 1903 the head of the bank markus wallenberg sr. sent a young lawyer by the name of richard julien out to travel and to read, to learn french and figure out how the french banks managed to be competitive. when he came home julien established an intelligence unit within the bank, camouflaged as “the statistical department”. it basically dealt with what we should call financial intelligence today, trying to understand different industries and the creditworthiness of specific customers. since then many swedish mnes have followed and have developed formal ci functions within their organization. sca has a well-oiled, well proven and systematic ci function today. the way they are organized fits with what is called the intelligence department model. about ten ci specialists work to produce mostly standard and timely ci reports. the ci unit is now also involved in the upcoming splitting of the company into two independent units each with their own ci capabilities. sca follows more closely a typical ci and mi development than does ericsson. ci work at ericsson seems to be effected by the difficult competitive position the company is in. to describe the current intelligence model used in the organization we could not use any of the existing models, but defined a new one: the consultancy model. this model does not have to be inferior to the other models in terms of performance and efficiency, but ci function is struggling. the company does not seem to understand its competitors. employees seem more concerned about job security than finding out what needs to be done. ci staffers use much time to try to sell their analyses to top management. instead of leading to necessary changes in competitive, the current crisis in ericsson has led to the organization and its 38 managers to become more political. employees are putting their own interests above those of the company. in times of crisis when the demand for intelligence is the greatest the company is not succeeding with ci. a decade and half ago there were serious discussions in ericsson as to where to put the intelligence function. ericsson was following in the footstep of other great swedish companies who understood the value of good intelligence, like seb. today’s ci staffers in ericsson do not remember that process, or the names of the people who led it or how they used to do it. this does not mean that ci staffers do not do a good job, but the conditions have deteriorated. seb and ericsson have more or less the same owner, the wallenberg family. the family is the largest single owner of seb with about 20% and of ericsson with about 22% of shares. the second largest owner of ericsson is the lundberg family, who controls industrivaerden ab. sca is a minority owner of the same investment company. the companies that the wallenberg family control seem to follow quite different ci practices, but future research needs to confirm this. one reason may be that the owners are less involved with ci questions. i have argued that management theory and practices are living in a napoleonic logic where the manager is seen as a genius, much like the military genius. it was an idea that developed in the 1980s. i argue that this is harmful for the interest of the company, as napoleon was harmful for the state. i also try to show how the private organization can learn much from state and military organization when it comes to intelligence work. it is the status of genius or guru that allows the manager to claim such a high salary or special perks—remunerations that are many times higher than what is accepted in the public sector. an efficient intelligence system could make the job of the top manager more transparent. how the manager gathers intelligence, and makes decisions as a result of concrete analyses can show what contribution he actually makes to the organization. further studies are needed to look specifically at how these processes unfold. the whole problem should be interesting to study from a psychological perspective. it will be argued that management theory has not been sufficiently critical when it comes to the managers’ contributions to the organization. it shows that intelligence studies in business and other areas of studies have an important role to play to uncover the mechanisms that lie behind good decisions. another way to say this is that much management theory builds on a wrong assumption, that of the all-knowing manager. 7. references alden, b. h. (1959). competitive intelligence. ci associates. alvesson, m. (2012). understanding organizational culture. sage. alvesson, m., & sveningsson, s. (2015). changing organizational culture: cultural change work in progress. routledge. agrell, wilhelm (1998). kosten att gissa rätt. studentlitteratur, lund crane, a. (2005). in the company of spies: when competitive intelligence gathering becomes industrial espionage. business horizons, 48(3), 233-240. doz, y., santos, j., & williamson, p. (2001). from global to metanational. ubiquity, 2(40), 2. dedijer, s. (1975). social intelligence: a comparative social sciences approach to an emerging social problem. darmouth, newhampire. gilad, b. (2011). strategy without intelligence, intelligence without strategy. business strategy series, 12(1), 4-11. herring, j. p. (1992). business intelligence in japan and sweden: lessons for the us. journal of business strategy, 13(2), 44-49. porter, m. (1980). corporate strategy. new york. new york, ny. keegan, w. j. (1974). multinational scanning: a study of the information sources utilized by headquarters executives in multinational companies. administrative science quarterly, 411-421. rouach, d., & santi, p. (2001). competitive intelligence adds value:: five intelligence attitudes. european management journal, 19(5), 552-559. sonnecken, e. h. (1960). competitive intelligence. journal of marketing (pre1986), 24(1), 129c. søilen, k. s. (2010). management implementation of business intelligence systems/gestion de la implementacion de sistemas de intelligencia de negocios. inteligencia y seguridad, (9), 46-67. søilen, k. s., kovacevic, m. a., & jallouli, r. (2012). key success factors for ericsson mobile 39 platforms using the value grid model. journal of business research, 65(9), 1335-1345. søilen, k., & tontini, g. (2013). knowledge management systems and human resource management policies for innovation benchmarking: a study of st ericsson. international journal of innovation science, 5(3), 159-172. søilen, k. s. (2015). a place for intelligence studies as a scientific discipline. journal of intelligence studies in business, 5(3), 35-46. søilen, k. s. (2017). why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies. journal of intelligence studies in business, 7(1). vol11no2paper5 to cite this article: poblano-ojinaga, e.r. (2021) competitive intelligence as a factor of the innovation capability in mexican companies: a structural equations modeling approach. journal of intelligence studies in business. 11 (2) 69-79. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 2 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive intelligence as a factor of the innovation capability in mexican companies: a structural equations modeling approach eduardo rafael poblano-ojinagaa,* atecnológico nacional de méxico, campus la laguna, departamento de ingeniería industrial, torreón, coahuila, méxico; *pooe_65@hotmail.com journal of intelligence studies in business please scroll down for article competitive intelligence as a factor of the innovation capability in mexican companies: a structural equations modeling approach eduardo rafael poblano-ojinagaa,* atecnológico nacional de méxico, campus la laguna, departamento de ingeniería industrial, torreón, coahuila, méxico *corresponding author: pooe_65@hotmail.com received 23 january 2021 accepted 24 september 2021 abstract in today's world markets, where rivalry is increasingly intense, companies face pressure to deliver better results in a shorter time. the continual technological change produces more efficient equipment, processes and products, new business relationships due to emerging and unexpected substitute products, as well as changing consumer preferences. in this constantly changing environment, companies need useful information to develop strategies, make decisions and implement them throughout the organization to increase their competitiveness and market share. this is not easy or straightforward, it begins at the company's strategy level and ends with the creation, development, and deployment of the technological capabilities necessary to provide agile and flexible responses to customers, market situations, and technological changes. the innovation capability of companies plays an important role, as it is a critical strength, technology-based and strategic in nature, with the purpose of creating and developing new products and improved processes. this is a continuous source of competitive advantage, and a necessary element for companies that operate in highly competitive environments and under growing rivalry, in order to improve technological innovations and developments. this information is essential for decision-making and one way to generate it is through methodologies, among which competitive intelligence stands out. this article presents an investigation using a structural equation modeling methodology to evaluate the relationships between competitive intelligence and innovation capability of mexican companies. the empirical results show that competitive intelligence has an important indirect impact on three main functions of innovation capability: creation of new concepts, innovation and technological development, and development/improvement of ideas for products, processes, and equipment. the indirect effect is through knowledge management as a mediating factor. keywords competitive intelligence, innovation capability, structural equations modeling 1. introduction business environments are characterized by their high volatility, turbulence and uncertainty. some industries pose extreme dynamism, under increasing rivalry the emergence of technologies are the source of important disruptions. in such conditions, analysis and decision making are highly complex. therefore, making the right decision depends on the analysis of the available information. but this is just the first problem, collecting data and producing useful information, adequately and on time, are difficult tasks. nonetheless, the processes for data collection, and information and knowledge management, are not as effective as needed. this is even though it is clear that companies journal of intelligence studies in business vol. 11, no. 2 (2021) pp. 69-79 open access: freely available at: https://ojs.hh.se/ 70 do not take advantage of the knowledge obtained by their experience, nor do they track environmental and competitiveness variables. in the search for explanations, the theory related to knowledge is developed in three fields of knowledge: competitive intelligence (ci), knowledge management (km), and intellectual capital (ic). ci is a process or practice that produces and disseminates actionable intelligence by planning, collecting, processing and ethical and legal analysis of the internal and external or competitive environment, in order to assist decision makers and to provide a competitive advantage to the company (pellissier and nenzhelele, 2013). application of ci has increased in the last decades and it has become more formalized (sewdass & calof, 2020). ci is defined as a systematic effort with specific, ethical and timely objectives for the gathering, analysis and synthesis of relevant information regarding competitors, markets and the economic environment, which also constitute a good source of competitive advantage (fleisher, 2009; rodríguez & chávez, 2011). this information leads to better business planning, including research, marketing and development projects. ci is a common practice because of the importance of tracking technology trends, the reduction of associated risks and the acquisition of the right technologies (brody, 2008; fuld, 2006). km research shows how the important role of good knowledge management contributes significantly to improving organizational performance (sundiman, 2018). it has an utmost interest for information and business management, communication, industrial engineering, and psychology because of the contributions to the organization (rodríguez gómez, 2006). among other functions, km is dedicated to the development of the capabilities and activities required for the design and improvement of goods, process, and production technologies (díaz, 2007). two of the most important sources of competitive advantage are the knowledge and the capabilities to learn and execute plans. ic can be defined as the sum of all of the intangible and knowledge-related resources that an organization is able to use in its production processes in the attempt to create value (lerro et al., 2014). it is the set of intangible assets that, when well-managed, can be a source of sustainable competitive advantages. it is useful knowledge for the creation of value and increased profitability (alama et al., 2006). ic has three widely accepted elements: human capital integrates attitudes, abilities, experiences of the people; structural capital includes intellectual property, such as patents, results of research and development, policies, strategies, and information, closely related to innovation capability; and relational capital deals with the value of the business relations with its environment, such as customers and suppliers (hormiga et al., 2011; díez et al., 2010). innovation capability (inc) is a firms’ fundamental strategic asset to sustain competitive advantage (ponta et al., 2020). it is the ability to continuously transform knowledge and ideas into new products, process, and system for the benefit of the firm, and is a set of organizational capabilities and resources. these are highly dynamic in nature with the purpose of managing and deploying innovation strategies, searching for the creation and development of the sustainable competitive advantage required for adequate and flexible responses to market challenges. robledo et al (2010) includes the people abilities and their best organization (lugones et al., 2007) in this as well. although the purposes and the specific study are different, the factors that explain the creation and development of innovation capacities could be affirmed that they are common, but their relative importance is not conclusive. as for ci, it is less frequently applied because it is a newer field and its strategic focus and more specialized functions reduce the widespread use. still, it is considered an important task because it has a great effect on the economic environment. this is because it has a continuous flow of innovations and technological developments that exert pressure on all competitors, driving innovation throughout the system (fagerberg & srholec, 2008). this article presents an evaluation of structural relationships between ci, km, and ic as influencing factors of inc of mexican companies established in torreon city, located in northeast mexico. the economy of the region is based on agricultural, textile, metallurgical, chemical, commerce, and services industries. the sector of maquiladoras, international companies, is devoted to textile, electronics, and automotive production. similar research was done in 2018 in companies from the juarez city, mexico-el paso, texas, usa, region (poblano et al, 2019). ciudad juárez is an industrial city in northern 71 mexico on the banks of the rio grande, and it is the largest city in the state of chihuahua. it has an economy based on the manufacturing industry made up of more than 380 companies, which are located strategically at border bridges and in fast access areas. bases on the review of related studies, the hypotheses to be tested empirically are: h1: competitive intelligence influences the innovation capability, h2: competitive intelligence influences knowledge management, h3: knowledge management influences innovation capability. the factors are discriminated by their impact on innovation capabilities through structural equation modeling (sem), so that companies can benefit from the knowledge of their current state and the possible measures for improvement. statistical analyses begin with the identification of outliers using the mahalanobis distance method. the internal reliability of the questionnaire, the kaisermeyer olkin test, is measured for the suitability of the sample, and bartlett's sphericity test for the correlations to determine the suitability of the model. subsequently the regression weights and factor correlations are determined by means of the principal components extraction method and the rotation is performed by promax. then the convergent and discriminant validation is carried out, as well as the estimation of the adjustment indices for the validation of the questionnaire constructs. the sem uses a confirmatory approach for the analysis of theories that present relationships between observed variables (items) and latent variables or factors. byrne (2010) begins with the specification of the model. for the specification of the model, lomax & schumacker (2012) recommend the definition of relationships with the variables of the theoretical model and for the determination of the best model, capable of producing the sample covariance matrix. to determine the differences between the real model and the data, all the parameters are considered free, restricted, or fixed and by their combination, the implicit variance-covariance matrix of the model is constructed. this is followed by identification, estimation, testing, and modification (lomax & schumacker, 2012). statistical analyses were performed with minitab v17, spssv.22, and amos v.22. table 1 dimensions and their critical factors. dimension critical factors item code references competitive intelligence ci activity planning the collection of environmental information the analysis of information to generate intelligence, the administration of useful information (intelligence), decision-making based on intelligence, ci staff talent management. ci01, ci02, ci03, ci04, ci05, ci06, ci07 stefanikova et al. (2015); dishman y calof (2008); rodríguez y tello (2012); fleisher (2009); nenzhelele (2014); calof, (2014); peyrot et al. (2002). knowledge management information system, human factor management, employee empowerment, organizational structure, knowledge sharing. km01, km02, km03, km04, km05 salojärvi et al. (2005); ghannay et al. (2012); du plessis (2007; tzortzaki y mihiotis (2014); martins et al. (2003). intellectual capital hc: professional level, training and development, attitude to share knowledge; sc: information system, staff participation, ability to innovate; rc: relationship with customers and suppliers, strategic alliances, relationship with organisms (public & private). ic01, ic02, ic03, ic04, ic05, ic06 ic07, ic08, ic09 díez et al. (2010); díaz (2007); sveiby (2001); boekestein (2006); santos-rodríguez et al. (2011); huang et al. (2010); kianto et al. (2017). innovation capability generation of ideas, generation of new concepts, generation of new products, generation of new processes, intellectual property. inc01, inc02 inc03, inc04 inc05 robledo et al. (2010); lugones et al. (2007); güemes y rodríguez (2007); dodgson et al. (2008); tidd y bessant (2009). 2. methods and discussion the methodology has a quantitative focus, used data gathered and statistical analyses to test hypotheses and obtain an enhanced understanding of the phenomena (malhotra, 2008; hernández et al., 2014). the scope was correlational with the purpose of determining the relation between two or more factors and variables in their specific context. the design was non-experimental and transversal, correlational-causal, collecting data in a single trial (hernández et al., 2014). in the literature review of the four dimensions (latent variables), the most frequent critical factors mentioned were selected, subsequently, for each of the factors. items were established for their measurement, yielding a set of 26 items for ic, km, ic and inc (table 1). data collection was carried out through a questionnaire, which was previously validated in content, reliability, and construct (poblano ojinaga, 2019). the questionnaire used five likert scale categories, ranging from 1, which means "strongly disagree" to 5, "strongly agree". the sample size was 195, table 2 presents its demographic characteristics. the collection of sample data was carried out through non-probabilistic convenience sampling. the sample elements were selected because they were determined through a census and willingness to participate (malhotra, 2008). the questionnaire was given characteristics frequency percentage accumulative % gender male 148 75.8 75.8 female 47 24.2 100.0 age less than 25 76 38.9 38.9 range 25 35 65 33.4 72.3 older than > 35 54 27.7 100.0 experience in related position < 1 77 39.5 39,5 2 7 55 28.2 67.7 > 7 63 32.3 100.0 table 2 sample characteristics (n=195). ci01 ci02 ci03 ci04 ci05 ci06 ci07 km01 km02 km03 km04 km05 in01 inc02 inc03 inc04 inc05 ci01 1.000 ci02 .694 1.000 ci03 .530 .667 1.000 ci04 .430 .492 .733 1.000 ci05 .419 .549 .592 .684 1.000 ci06 .403 .523 .652 .587 .600 1.000 ci07 .494 .513 .536 .491 .502 .650 1.000 km01 .351 .398 .453 .377 .407 .524 .432 1.000 km02 .282 .285 .296 .285 .336 .357 .471 .473 1.000 km03 .306 .433 .419 .410 .419 .433 .462 .379 .520 1.000 km04 .288 .360 .414 .400 .429 .423 .449 .384 .331 .470 1.000 km05 .261 .367 .494 .492 .461 .483 .409 .435 .370 .446 .598 1.000 inc01 .220 .345 .331 .246 .251 .269 .229 .299 .248 .340 .537 .413 1.000 inc02 .141 .297 .313 .277 .304 .287 .183 .338 .126 .288 .490 .376 .710 1.000 inc03 .049 .156 .265 .208 .124 .273 .149 .188 .151 .233 .249 .284 .407 .585 1.000 inc04 .073 .188 .275 .269 .193 .288 .244 .194 .245 .315 .307 .378 .405 .464 .522 1.000 inc05 .025 .172 .206 .146 .067 .222 .164 .093 .053 .248 .232 .281 .274 .401 .479 .401 1.000 s.d 0.567 0.522 0.523 0.522 0.511 0.545 0.521 0.553 0.536 0.504 0.589 0.556 0.580 0.570 0.666 0.569 0.861 means 4.545 4.449 4.383 4.449 4.449 4.377 4.371 4.425 4.503 4.401 4.341 4.377 4.395 4.257 4.120 4.210 3.868 table 3 sample correlation matrix for data (n = 167). 73 to 195 people (managers and supervisors) from 14 multinational companies that produce auto parts, textiles and electronics (lloret-segura et al., 2014). the mahalanobis distance method eliminated 28 questionnaires. using the remaining 167 questionnaires, the cronbach alpha gave a 0.91, indicating it is reliable (tavakol & dennick, 2011). the kaiser-meyerolkin test gave 0.880, indicating low partial correlations, measuring as a common factor. chi-square = 1466.491, df = 136, and a pvalue = 0.000 meaning that the correlations matrix is not an identity one, with high correlations, which is acceptable (levy et al., 2003). in the initial factorial analysis, the ic was eliminated because the items do not comply with the convergent validity criteria, although in the literature report an impact of intellectual capital on competitive intelligence (santos-rodrigues, 2011; wang y chen, 2013; sivalogathasan & wu, 2013). a correlation matrix of the data are presented in table 3. the correlations and factor loading (fl) were determined using the principal axes method to extract the factors and the promax method for their rotation. the fl indicates the correlation between the factor and the variable, observing that for all the items it was greater than 0.60, exceeding the recommended level (lin, 2007). convergent and discriminant validity was measured with the above information. convergent validity is the degree to which multiple attempts to measure the same concept agree (table 4). the composite reliability values (cr) show the degree to which the indicators explain the latent construct, where values in a range of 0.85 to 0.92 were obtained. in all cases this exceeded the recommended level of 0.70. likewise, the average variances extracted (ave) reflected the total amount of variation in the indicators, explained by the latent construct. values ranged between 0.53 and 0.62, exceeding the recommended level of 0.5 (lin, 2007). discriminant validity is the degree to which the measures of the concepts are different, for which the squared correlations of the construct are compared between the mean variance extracted for the construct. discriminant validity occurs when the elements on the factor loading ave cr cronbach's alpha item ci01 .731 ci02 .822 ci03 .869 ci04 .806 ci05 .781 ci06 .775 ci07 .707 0.62 0.92 0.90 knowledge management item km01 .695 km02 .815 km03 .748 km04 .680 km05 .679 0.53 0.85 0.80 item inc01 .732 inc02 .842 inc03 .783 inc04 .715 inc05 .666 0.56 0.86 0.80 dimension competitiva intelligence innovation capability table 4 convergent validity. ci inc km ci 0.62 inc 0.16 0.56 km 0.39 0.21 0.53 table 5 discriminant validity. 74 diagonal (ave) are greater than the elements below the diagonal (matzler & renzl, 2006). the results show that the square correlations for each construct are less than the mean variance extracted (table 5). the analyses show that the results met the criteria of convergent and discriminatory validity. therefore, the confirmatory factor analysis (cfa) was carried out with the three factors and their 17 corresponding items (figure 1). the cfa results for the measurement model show a chi-square = 224.274, p-value = 0.000 and cmin / df = 1.985 value less than the recommended value of 3. given agfi = 0.82, greater than 0.80; the comparative adjustment index, cfi = 0.92, is higher than the recommended 0.9 (chau & hu, 2001). the root of the mean square error of approximation, rmsea = 0.077, was less than the proposed 0.08 limit (browne & cudeck, 1993), and since the variance-covariance data fit the structural model well, the construct is valid. the hypothetical model has three latent variables (or factors) and 17 observed variables (items). it shows three structural relationships: competitive intelligence influences innovation capability (h1); competitive intelligence influences knowledge management (h2) and knowledge management influences innovation capability (h3). for the model identification, the number of free parameters to estimate must be equal to or less than the number of different values in the matrix s. since the number of estimated values (153) was greater than the number of free parameters, the model was identified and the estimation of the parameters followed. for the estimation of the parameter, the regression weights and the structural coefficients of the hypothetical model indicate that, with the exception of the ic inc, they were significant because the p-value was less than a = 0.05. this was run with amos v.22 with a maximum likelihood method for normally distributed, ordinal, or moderately abnormal data. for the model test, given the set of fit indices used and the values presented in table 3, the degree to which the variancecovariance data fit the hypothetical structural model was acceptable. the fit seemed reasonable, although modification could improve the model fit. for modifying the model to improve its fit, additional parameters were included such as modification indices, with three covariances between errors, e3-e4, e11-e12, and e13-e15. in the maximum likelihood method, the factorial loads are statistically significant, different from 0.00 (p <0.05), except for the path between competitive intelligence and innovation capability. furthermore, given that chi-square = 224.74, the p-value = 0.000 and cmin / df; agfi; rmsea, meet the corresponding criteria, presented in table 6. finally, figure 2 presents the hypothetical structural model, which shows three factors figure 1 measurement model of ci, km and inc. 75 with their structural coefficients and the smc (r2) for the endogenous variables km and inc. assuming that the estimates are an effect of the latent variables of the three hypotheses raised in the study, h2 and h3 have significant structural coefficients, which indicate that there is enough evidence to accept that ci influences km, and km also has an influence on the inc. ci has a positive effect on km, and the latter has a positive effect on the inc, results coinciding with sundiman, (2018) and le & lei (2019). there is also evidence that the real effect is enhanced with careful km (de almeida et al., 2016) in addition, h1 is rejected for not having sufficient statistical evidence that ci has a significant direct effect on the inc in mexican companies. in this case, the empirical results coincide with those reported by güemes & rodríguez (2007) that ci activities are not formally carried out in mexican companies to improve the innovation of products and services. poblano et al., (2019) report the same in plants located in ciudad juárez, mexico, mainly because ic is still a relatively young discipline (alnoukari hanano, 2017) in most mexican companies. however, although there is no direct effect of ci on inc, there is a significant indirect effect through km (table 7). this means that it becomes the mediating variable between ci and inc. these results support the importance of integrating km and ci with the intention of obtaining better results and being a source of competitive advantage for companies (dhujahat et al., 2017; sundiman, 2018; sharp, 2008; gonzálezgutiérrez, 2011; rothberg and erickson, 2013). on the other hand, when analyzing the results of the total direct and indirect effects, high values are observed in the indirect effects, with the value of 0.698 between ci and inc. table 7 presents the standardized effects between factors and the corresponding regression weights. the indirect effects (estimated with the bootstrap method) come from the use of ci and km practices. ci has a significant impact on three functions of km: the activities for the shared use of knowledge and the learning obtained by experience (km05, 0.600); the system for the management of innovation(km04, 0.588); and the measures taken for people empowerment (km03, 0.507). also an important indirect impact of ci on inc is observed in three functions. the production of new concepts (inc02, 0.384); analysis and decision making for innovation and technology development (inc01, 0.339); and on the development and improvement, ideas for products, processes and equipment (inc03, 0.276). these effects were statistically significant at a level of 0.05 finally, the factor loadings indicate a high correlation between ci and inc, specifically, of the ci factors. the ones with the greatest impact are the collection and analysis of information from the environment, formally and systematically, for strategy purposes. 3. conclusions although ic was discarded and a relationship with inc couldn’t be verified, the contents of the former and reports in the literature indicate there has to be a direct effect, mainly with relational capital. this has a close relation with ci, since people have to have a deep understanding of the competitive environment, strategy formulation and deployment, and the management of knowledge. a relationship of structural capital with innovation is also observed, although it might be explained by the management of research and development, intellectual property such as patents and the learning obtained by experience. this focus also might explain the elimination of ic. for the people interviewed, there was no evident relation of its theoretical contents with innovation. table 6 fit indexes of the measurement model. fit index chi-square df cmin/df cfi rmsea agfi initial model 290.264 116 2.502 0.875 0.095 0.77 modified model 224.74 113 1.985 0.920 0.77 0.817 criteria <3.0 >0.90 < 0.08 >0.80 figure 2 hypothetical structural model (pv < 0.001*). it seems that a formal integration of ci and km and the description of the mediating effect of ci on inc is pertinent. this opens another research possible for the development of a system tracking competition variables such as emergent products and technologies and competitiveness, and feed them in an effective way to the functions that use them, such as design, engineering, marketing. the characterization of the indirect effects of ci on inc is also important. this could be through km as an intermediate variable (mediator), which helps to explain how or why an independent variable influences a result (glunzler et al., 2013). this assumption needs to be verified, including the mediating effect to gain a better comprehension of this phenomena. in this sense, it is suggested that future studies may consider the use of analytical and statistical methods to test relationships and measure ic practices, and move towards causals models (calof & sewdass, 2020), such as sem which has proven to be a powerful tool for this purpose. likewise, these results may justify continuing with studies that evaluate the effect of ci on the inc of organizations considering the possibility of including a greater number of measurable variables than those considered in this study for the latent variables analyzed. however, in studies where a wide variety of variables are used only some of the ci measures had statistically significant correlations greater than .30, and it may not be enough to advance in the theory. still, this could indicate that looking for a midpoint in the number of variables would be adequate. even so, these studies indicate that further research in this direction is needed. this paper constitutes evidence that sem is a powerful tool for the determination of total or partial effects, direct or indirect, between a measurable variable and a latent variable, as in the effects between latent variables or constructs. 4. future research although the main limitation of the study is the size of the sample, several aspects indicate that the study is still valid. these include the internal consistency of the questionnaire (cronbach's alpha) and kmo greater than the recommended of .70; compliance with cases of convergent validity and discriminant validity; and compliance with the model fit criteria. on the other hand, to validate and generalize the results obtained, it is necessary to carry out the study with a larger sample of mexican companies. it could also be a line of research to compare the results obtained from mexican companies with transnational exporting companies located in mexico. the study of the effect of ci on inc, through the mediating effect of km, in organizations that have developed an efficient system, raises another possible line of research 5. references alama salazar, elsa; martín de castro, gregorio; lópez sáez, pedro; (2006). capital intelectual. una propuesta para clasificarlo y medirlo. academia. revista latinoamericana de administración, segundo semestre, 116. http://www.redalyc.org/articulo.oa?id=716 03702. alnoukari, m., & hanano, a. 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(2013). does intellectual capital matter? high-performance work systems and bilateral innovative capabilities. international journal of manpower, 34(8), 861-879. issn: 2001-015x v o l 2 , n o 1 ( 2 0 1 2 ) adis sabanovic and klaus solberg søilen “customers’ expectations and needs in the business intelligence software market”, pp. 5-20 eloïse loubier “interactive methods for graph exploration”, pp. 21-31 kaïs khrouf, jamel feki and chantal soulé-dupuy “multiversion document warehouse: an approach to multidimensional analysis”, pp. 32-40 xie xinzhou, wang qiang and chen anqi “analysis of competition in chinese automobile industry based on an opinion and sentiment mining system”, pp. 41-50 marisela rodríguez salvador and mario alberto tello bañuelos “applying patent analysis with competitive technical intelligence: the case of plastics”, pp. 51-58 o p i n i o n s e c t i o n christian bourret “standards, evaluation, certification and implications for the study of competitive intelligence”, pp. 59-67 2 journal contact: mailing address: jisib halmstad university box 823 301 18 halmstad sweden principal contact: dr. klaus solberg søilen school of business and engineering (sbe) email: klaus.solberg_soilen@hh.se copyright © 2011 jisib, halmstad university. all rights reserved. 3 e d i t o r i a l t e a m founding editors prof. henri dou (france), goupe escem prof. per jenster (china), nimi honorary editors prof. john e. prescott (usa), university of pittsburgh prof. bernard dousset (france), toulouse university editor-in-chief dr. klaus solberg søilen (sweden), halmstad university regional associated editors america: prof. g. scott erickson (usa), ithaca college europe: prof. sahbi sidhom (france), nancy university asia: prof. xie xinzhou (china), beijing university africa: prof. adeline du toit (south africa), university of johannesburg t h e e d i t o r i a l b o a r d : dr. mark xu, university of portsmouth, uk dr. subir ranjan das, university of petroleum & energy studies, india assistant professor dirk vriens, radboud university, netherlands professor karim baina, école nationale supérieure d'informatique et d'analyse des systèmes (ensias), morocco professor uwe hannig, fachhochschule ludwigshafen am rhein, germany dr. klaus solberg søilen, halmstad university, school of business and engineering, sweden dr. eduardo flores bermudez, bayer schering pharma ag, germany professor kingo mchombu, university of namibia, namibia professor adeline du tout, university of johannesburg, south africa professor pere escorsa, school of industrial engineering of terrassa, politechnical university of catalonia, spain assistant professor per frankelius, örebro university, sweden professor malek ghenima, l'université de la manouba, tunisia professor blaise cronin, indiana university, united states dr. john e. prescott, university of pittsburgh, united states dr. michael l neugarten, the college of management, rishon lezion, israel professor mika hannula, tampere university of technology, finnland professor kamel smaili, université nany 2, france professor henri jean-marie dou, atelis competitive intelligence work room of the groupe escem, france professor bernard dousset, toulouse university, france professor g. scott erickson, ithaca college, united states professor sahbi sidom, université nancy 2, france professor xinzhou xie, beijing science and technology information institute, china associate professor jonathan calof, telfer school of management at university of ottawa, canada professor per v. jenster, nordic international management institute, china professor alfredo passos, fundação getulio vargas, brazil professor brigitte gay, esc-toulouse, france professor sophie larivet, ecole supérieure du commerce extérieur (esce), paris, france t h e m a n a g e r i a l b o a r d : arik johnson, chairman aurora wdc, united states raíner e michaeli, director institute for competitive intelligence gmbh, germany philippe a. clerc, director of ci, innovation & it department at the assembly of the french chambers of commerce and industry, france alessandro comai, director of miniera sl, project leader in world-class ci function, spain pascal frion, director acrie competitive intelligence network, france hans hedin, vice president business development at global intelligence alliance group, sweden dr. sofiane saadi, directeur général du laboratoire en organisation et gestion des entreprises (loge) algeria. managing director nt2s consulting inc. north vancouver, bc, canada javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/49') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/18') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/20') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/19') javascript:openrtwindow('https://ojs.hh.se/index.php/jisib/about/editorialteambio/21') 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halmstad, april 30 2012 e d i t o r i a l n o t e v o l 2 , n o 1 ( 2 0 1 2 ) jisib here presents six new articles. as in the first issue these contributions come from scholars all over the world; from africa, north america, asia and europe. we are very pleased about the diversity of these contributions, also with the fact that we have a good number of female authors. the subject they all have in common is problems related to how private organizations work with information to gain a competitive advantage. more precisely they are occupied with a particular kind of information, the need-to-know, or intelligence. some of the articles are, as before, more technical, others more qualitative. they are all focused on management practices, that is, solving real life problems. as more technology is being implemented in our corporations, the ability to understand and use new applications distinguishes the skilled from the unskilled, be it in the it department, the marketing department, in accounting and finance or in human resource management department, where most of those working with intelligence tasks are found. for the first time the journal has opened an opinion section, allowing for contribution which does not fit the format of empirical studies, but offer critical perspectives on the subject studied in this journal. we believe these are important contributions. a discipline should always question what it is doing and it must be able to welcome other methodologies, be it from critical theory, post modernism or the historical school. it is with great interest that we have noticed the attention paid to open access journals recently, in particular by an editorial in the newspaper the economist and by the decision at harvard university to demand that all research from the institution be published in this format. right now many other universities are thinking about demanding the same thing from their researchers. this will give open access journals a great boost in the time to come. we welcome this development. the journal works in symbioses with a number of conferences. it relies heavily on the contributions of scientific papers presented at these conferences, in particular for these first issues. among these we would in particular like to mention the more scholarly conferences, like vsst, ecis, icticti and siie. in the near future we also hope to receive contributions from inosa and eckm. we also receive support from members in the more professional conferences related to intelligence studies like ici and scip. we are most grateful to the organizers and contributors at all of these conferences. as always, we would first of all like to thank the authors for this issue. on behalf of the editorial board, sincerely yours dr. klaus solberg søilen halmstad university i box 823 i s-301 18 halmstad, sweden i tel: +46 35-16 71 00 vol7no3paper4 kss et al to cite this article: søilen, k.s., tontini, g. and aagerup, u. (2017) the perception of useful information derived from twitter: a survey of professionals. journal of intelligence studies in business. 7 (3) 50-61. article url: https://ojs.hh.se/index.php/jisib/article/view/244 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index the perception of useful information derived from twitter: a survey of professionals klaus solberg søilena, gerson tontinib, and ulf aagerupa adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden, bfurb, brazil; klasol@hh.se journal of intelligence studies in business please scroll down for article the perception of useful information derived from twitter: a survey of professionals klaus solberg søilena,*, gerson tontinib and ulf aagerupa adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden bfurb, brazil *corresponding author: klasol@hh.se received 23 august 2017; accepted 28 october 2017 abstract in this study we gathered data from 220 professional users of information via a survey. twitter is perceived as a service for useful information but not for the reason one may expect, not because the content of the tweets give valuable information, but because of what can be derived and extracted from the information that is being tweeted and not tweeted. professional users are aware that tweets are being manipulated by communication departments so they adjust for this in their understanding of the content that is being delivered. for the same reason “fake news” is not seen as a problem either by professionals. twitter is seen as valuable alongside other social media software (additional software solutions) and used directly together with other software (integrated software solutions). as a stand-alone service it is found to be of less value to experienced users and there are no signs that twitter is a valuable tool for learning. keywords bots, business intelligence, competitive intelligence, consumer opinion mining, sentiment analysis, social media, twitter 1. introduction for this research project we wanted to know if the online news and social networking service twitter is a source of useful information, as useful information, or intelligence, is the core of what makes companies thrive. previous studies have shown how information leads to a competitive advantage (porter and millar; 1985) and the importance of strategic planning for company performance (jenster & søilen, 2013). an early study by java et al. (2007) suggests that people tweet because they want to share daily activities and information, so it would be a natural next step to ask what the value of this information for business purposes is. this question is also important for the public company twitter as its share price depends much on the value or perceived value of the information it makes available, which is inseparable from its product. if twitter delivers valuable information the service is an important source of intelligence and maybe even learning. in the worst case it is a marketplace for gossip. that the service offers a large amount of information or data is reflected in the numbers: in 2016 twitter reported that they had 319 million active users. when we do some statistics, we see that images are posted more than videos, but that videos get more likes. most retweets are given to texts with links/urls. humor seems to be the most frequent type of content, but politics, (pop) culture, food and travel are other popular categories and the categories are not mutually exclusive, either. those accounts with the most followers are pop-stars (60% of the top 50), followed by tv-stars and other celebrities. only journal of intelligence studies in business vol. 7, no. 3 (2017) pp. 50-61 open access: freely available at: https://ojs.hh.se/ 51 five out of the top fifty are big news outlets (two accounts for cnn, bbc, espn and another sports channel) and three are politicians (trump, obama and modi). previous research has shown that twitter has an effect on political outcomes, such as the arab spring movement (kassim) or the 2012 us presidential election (mills, 2012). the focus in this article is on valuable information for business. research in marketing has shown how twitter can result in people not seeing a movie as a result of poor reviews through microblogging word of mouth (mwom) (hennig-thurau et al., 2015). the phenomenon is called “the twitter effect” and has strong economic implications for products that are sensitive to immediate success, such as movies (hayes, 2002), music (asai, 2009) and electronic games and it affects early adoption of new products. information diffusion on twitter occurs through the process of retweeting. suh et al. (2010) analyzed 74 m tweets and found that best chances of being retweeted occur with the use of urls and hashtags. it is also affected by the number of followers and followees, as well as the age of the account. naveed et at. (2011) found that retweets occur when the topic is general and public instead of narrow and personal. this is an argument for twitter as a news platform, the authors argue. their research also confirms the existence of the twitter effect, that bad news travels longer and faster. hong et al. (2011) show, in a highly cited poster paper, some of the mechanisms for getting many likes on tweets. the likelihood of being retweeted increases with the number of followers a person has and the extent to which the tweet has been retweeted by others before, but the paper also goes into more detail. turning to studies more closely related to information, haustein et al. (2016) show how twitter can be used effectively to spread scientific information. they show how automated twitter accounts, known as twitterbots, which are small software programs that are designed to mimic human tweets, schedule posts automatically when the engagement and potential reach are higher, allowing for repetition of tweets. tools like tweriod can tell what day and times followers are most active. with a ifttt recipe like buffer it is possible to automatically reschedule the content posted in social media. with twittercamp tweets can be displayed in large-format displays. with chir.ps, audioboo, or twaud.io users can send voice messages via twitter, which is also a way of getting around the 140 characters limit. castillo et al. (2011) look at the information credibility of news on twitter. the authors explain why it is so easy to be misled on twitter, especially for inexperienced users. newsworthy tweets tend to include urls, have deep propagation trees, come from users with many tweets and have many retweets. kim et al. (2016) conducted a competitive intelligence (ci) exercise comparing consumer opinions and sales performances between an iphone and samsung mobile phone. the analysis confirms the value of twitter for ci. the authors found that the volume of tweets revealed a significant gap between the two products. this was confirmed by the purchase intention data and the social opinion gap. other authors have studied how twitter and ci are relevant for specific industries, like the film industry (kim et al., 2015), hotels (ye et al., 2011), restaurants (lu et al., 2013), retail (chen, 2010) and the food industry (kim and jeong, 2015). text data about end users are analysed using opinion mining and sentiment analysis. both are a part of social media analytics. social media analytics is about finding software or business intelligence solutions to gather, monitor, analyze, summarize, and visualize social media data such as that from twitter. an evaluation of business intelligence systems along similar lines has been conducted by amara et al. (2012), sabanovic & søilen (2012), søilen (2012 b) and fougatsaro (2009). it gives a more accurate assessment of customer responses, enabling companies to improve their market strategies (chen and zimbra, 2010; liu et al., 2010; lusch et al., 2010). li and li (2014) show how social media marketing is effective in increasing brand awareness of existing or new products, and can help to build a strong brand community. most studies using social media analytics suggest that it is a powerful tool for marketing purposes. in conclusion, many studies have dealt with a single case or a specific phenomenon. what is missing is a critical study about what perceived value twitter has for ci and business intelligence (bi) professionals in general. there is another gap in the literature regarding the receiver of the tweets, i.e. the readers who evaluates that information. the problem is interesting for the scope of intelligence studies as outlined in søilen (2015). 52 when it comes to intelligence, most research papers are of a more technical nature. data mining, artificial intelligence and data learning technologies have come a long way when it comes to identifying and classifying the information in tweets according to names of people, organizations, locations, dates and times in what is sometimes called named entity recognition (ner): findings that are highly useful in marketing and segmentation. inkpen et al. (2017) show how it is possible to go deeper into location and identify not only countries, but province and cities. another related body of research looks more at alert functions for national and military intelligence. for example with large scale tweets, some events may be predicted. alsaedi et al. (2017) propose to that an end-to-end integrated event detection framework which was tested and confirmed using a large-scale, real-world dataset from twitter, using the august 2011 riots in england as an example. the same technology can be useful for private companies to predict new trends. 2. method and research design the purpose of this study is exploration, hypothesis testing and description. we have the following research questions: rq1: is twitter a source of useful information for companies? rq2: to what extent do managers use twitter? rq3: what do managers think about twitter in general? to answer the first question a number of hypotheses were formulated (hypothesis testing). to answer the second question, a number of specific questions were asked (descriptive method). for the third question an open-ended question was created (exploratory method). 2.1 hypothesis testing the following hypotheses were defined for this study: hypothesis 1: twitter is useful for competitive intelligence (q1) hypothesis 2: those who post on twitter have valuable information (q2) hypothesis 3: those who post on twitter whom i follow have valuable information (q3) hypothesis 4: i get my most valuable information from twitter (q4) hypothesis 5: the most valuable information i get on social media is from twitter (q5) as humans we tend to overestimate our own abilities. thus, we think that we know more than others and that the people we know and follow on twitter are more knowledgeable. this assumption is tested with the difference in answers from h2 and h3. we also want to see and compare any difference of what people understand as ci and useful information in general by comparing h1 to h4. it may be valuable to compare the information gathered on twitter to the information we get from other social network services, such as facebook. to make a distinction possible we split the hypotheses in two, allowing a comparison with all information sources (h4) and other social network information sources (h5). a likert scale of 1-5 was used, including the five categories: i completely agree, i agree, neutral, i disagree and i completely disagree. this method can only give a perception of what users think, not say what they actually think. as such, this empirical study is in a tradition of perception studies. the reason for choosing this method is primarily one of economy, as other studies demand more time and resources (direct observations and experiments). 2.2 description a number of specific questions were formulated to find out to what extent managers use twitter: how often do you think you check twitter each day? (minutes) (q6) how many minutes do you think you spend on twitter each day? (q7) how often do you tweet? (number of times per day/week/month) (q8) what percent of your time on twitter is for professional use (not private use) (q9) questions were asked in a survey with the option to add comments and explanations to 53 each answer. as it can be difficult (almost impossible) to know how many minutes we use on twitter we ask what managers think they use (q6, q7). it is assumed that it is easier to remember how many tweets we send (q8). the answers show we should have used “think” in the last specific question, too (q9). initial answers also show that it may have been wrong to use several measures as options in one and the same question, like day/week/month as respondents used different measures, which demanded unnecessary recalculations for direct comparisons. 2.3 exploration for the last part of the survey we wanted to know what managers think about twitter in general. “please give your personal comments about the importance of twitter for competitive intelligence” (q10) an open ended question was given with enough space for comments. 2.4 research design the extent of researcher interferences was moderate. all questions were sent in networks online in the form of a link to a survey using the service surveymonkey. the online networks defined as the population were eight groups related to business intelligence in linkedin with from 7 000 to 1.8 million members in each group, and a mailing list of more than 900 members for the jisib journal, as shown in table 1. table 1 population defined. these users are defined as experienced users, thus less likely to be manipulated by false information on twitter (castillo et al., 2011). there was less than a minimum of manipulation and/or control and/or simulation. the study setting must therefore be said to be contrived as it is an artificial setting and we are not studying a natural environment where the phenomenon occurs normally. the research strategy is survey research. the data collection method is a questionnaire. the unit of analysis is individuals. the measurement is scaling for the hypotheses. items in the descriptive part are measured (times, minutes). the exploration part is based on text analysis. the study is partly longitudinal with two measures in time, with a time difference of 6 months between each. we used the same sample/survey. sampling size: n = 220. the sample was 0,012% of the population, which reflects the increasing difficulty of getting users to fill in complete surveys with the increased number of users seeking attention on the internet. this gives us a confidence interval of about 7 with a 95% confidence level. for the text analysis from the open-ended question, we use a synthesis process by which opinions are classified according to relevant dimensions identified in the process (1), narrowed down to key words (2), and analyzed for the least common denominator/meaning (3). this allows for a test of validity and accuracy as readers can largely redo the analysis from the same raw data and the empirical test can easily be replicated. 3. empirical data table 2 summarized the responses to the first questions. in q6 and q7: most respondents misunderstood this question, something that was missed in the pre-test. respondents treated q 6 as if it was the same as q7, asking only for the number of minutes, not the amount of time spent. the average answer was 16 minutes, but answers varied too much for the average to have much meaning. many respondents do not check twitter at all and the minutes used on twitter vary from 1 minute to 180 minutes per day. the most frequent answer was 10 minutes (15.5%), followed by 60 minutes (12.0%), 1 minute (10.3%), and 20 minutes (6.9%). only 3.4% of respondents never use twitter. nr. group’s name members 1 software and technology 1,800,000 2 business intelligence professionals 206,000 3 microsoft business intelligence 120,000 4 software as a service (saas) 101,000 5 scip 26,000 6 market intelligence professionals 25,000 7 ci professionals 12,000 8 competitive intelligence professionals 12,000 9 jisib membership list 900 table 2 the hypotheses (q1-q5). i completely agree i agree neutral i disagree i completely disagree qi 23.33% 46.67% 18.33% 10.00% 1.67% q2 5.00% 43.33% 36.67% 15.00% 0% q3 18.33% 46.67% 26.67% 5.00% 3.33% q4 1.67% 20.00% 23.33% 36.67% 18.33% q5 6.67% 15.00% 28.33% 33.33% 16.67% q8: number of tweets per day/week/month varied even more than the number of minutes spent on tweets. so again, an average makes little sense. some respondents answered in days, others in weeks and others again in months. this was not an optimal way of framing the question but luckily it could easily be solved by recalculating all numbers as “tweets per day”. this is shown in table 3. table 3 tweets per day. day week month 3, 1, 2, 1, 3, 3, 1, 2, ,1 10, 2, 10, 5, 2, 2, 5 30, 1, 2, 3, 30, 1 average 2.7 4.3 per week 11.2 per month day equivalent 0.6 0.3 those who answered in tweets had an average of 2.7 per day, in weeks they had 4.3 per week or the equivalent of 0.6 per day. those who answered in months had an average of 11.2 tweets per month and the equivalent of 0.3 per day. the answers suggest that it may be that this division of days/weeks/months catches a more nuanced understanding of users’ habits than if we had only written days. those who answered in weeks have a far lower range of tweets than those who answer per day and those who answer per month have a far lower number of tweets than those who answer in tweets per week. the total average is 1.2 tweets a day, which for example is below the limit of 3 tweets recommended by the service buffer. their statistics suggest that the engagement of your followers drops first after the third tweet. see http://follows.com/blog/2016/04/times-daypost-twitter. a large percent answered that they send 0 tweets per day (27.6%). q9: on average, respondents use twitter for work purposes 50.1% of the time. answers vary greatly and often, from 0-100%. the most frequent response (mode) was 100%, which was answered by 17.6% of respondents. 15.7% answered 50% of the time. 7.8% answered 90%, 5.9% answered 1%, and 5.9% answered 0 times. q10: often it is the open-ended question that brings the most meaning to the empirical work. from the 220 respondents we have taken away blank answers, irrelevant comments or pure opinions without arguments or backing. these represented 56% of comments, or 123 comments. we also took away double comments, comments with content that was too similar. these represented another 23% of comments, or 50 comments. this left 46 comments, or 21%, as shown in the tables below. these are deemed significant and worth analyzing further. looking at the comments, four dimensions (d) were identified as relevant for further analysis: advantages (1), potentials (2), limitations (3), and warnings (4) as shown in table 4. table 4 the comments (q10). d/ nr advantages potentials limitations warnings 1-4 strongly important especially when it comes to extracting knowledge and insights from social data. not so useful for ci but for marketing and consumer insight teams. twitter may provide competitive information for some industries. relying completely on it would be futile for most. 55 5-8 twitter's immediacy means you can get quick updates on a range of topics, products and news. in ci we can get info regarding bigger changes in consumer attitudes and know if rivals do pilot tests with new products somewhere in the world. sometimes data may be available from only one category of users. mostly its content (which is followed, viewed and commented on by many) is banter and selfpromotion by individuals. 912 it lets you keep up-to-date and allows you to capture the zeitgeist of your target. twitter is one source of new signals in the competitive environment. twitter is one of many resources, not a primary source. some try to use it for marketing of products or services, which by itself does not provide anything useful. 1316 you can find the latest news posted by companies involved in a competitive landscape. the most authentic opinions on twitter are from politicians (they use it in a very straightforward way), it is one more source of information, but not focused, in near real time. corporate accounts are mostly controlled by communication departments. i remember once a group i worked with tried to analyze twitter content to understand what people wanted for valentine's day. they ended up only with information from marketers on things people could buy for valentine's day. all the plans of providing new insights into the client vaporized into thin air. 1720 the instantaneity of information, in particular "alerts" on events. i do sometimes use it to id human sources who we could speak with on various topics with authority. it really depends on the industry. if none of the competitors or customers are using it, it will be useless. twitter is certainly not a ci tool. ci should be focused on building outside-in perspectives. 2124 twitter is the best source for recent/actual information (fastest social media). it’s a gap filler. one of many resources, but not exclusive. i think twitter more often misleads than informs for ci work. 2528 i think it is important but i rarely tweet. large potential though for text analysis and network analysis, etc. to be integrated, but limited by itself. i find it not worth the time required to scan all of the pointless stuff. 2931 twitter is useful for identifying relevant sources for ci tasks, their messaging and their networks. twitter can be useful because it contains very different information about the environment. there’s a huge variation in quality of content and difficult to assess these differences. 3234 it is useful real time news in relation to surprise events such as terrorist attacks, military moves, uprisings, disease outbreaks, [...] and for geopolitical and catastrophe monitoring. the importance of twitter for competitive intelligence requires sifting through the noise. i don't regard it as important. it is merely a tool that can guide you towards leads. 3537 it’s an indirect tool. assess what people know, value or say. to use twitter, you should also use tools like tweetdeck or hootsuite so you can manage the twitter stream and put key people into columns and lists. in the age of information overload and disinformation it is as much what people don't say or omit on twitter. 3840 when used seriously i think it is very valuable. follow the group rather than the individual. for tweeting use tools such as buffer to schedule tweets. i prefer fb. 4142 i believe twitter is a platform where people are spontaneous. only for selective accounts and filters need to be applied. 4344 it is possible to spot trends early but you need to be following the trend setters. identifying true trendsetters is difficult. interesting but like any secondary source offers guidance at best. 4546 depends on who you follow and who follows you. it is simply a source of information in which public opinion may be manipulated. from the classification of relevant dimensions a number of keywords could be extracted from each group of answers: 1. keywords for advantages: extracting knowledge and insights from social data, fastest social media, quick updates on a range of topics, up-to-date and allows you to capture the zeitgeist, latest news posted by companies, "alerts" on events, identify people and networks, assess what people know, value or say. 2. keywords for potentials: not useful for ci but for marketing and consumer insights, consumer attitudes and know if rivals do pilot tests, only one source among several, authentic opinions from politicians, id human sources who could speak on various topics with authority, potential for text analysis and network analysis, different information about the environment, requires sifting through the noise, requires use of other tools (tweetdeck, hootsuite, buffer), follow the group rather than the individual, a platform where people are spontaneous, but you need to be following trend setters, identifying trendsetters is difficult, depends on followers and who you are following 3. keywords for limitations: corporate accounts controlled by communication departments, sometimes data maybe available from only one category of users, not a primary source, value depends on customers, if they use it, limited by itself, difference in scope and quality, difficult to assess, at best for leads, tells you what people are not saying, fb is better for ci work, a secondary source, easily manipulated 4. keywords for warnings: futile to rely on, mostly self-promotion by individuals, a marketing tool for companies, reflects the market, not a ci tool, for inside-out perspectives, misleading, not worth time for scanning. a look at the data shows that respondents think the advantage of twitter is that it is a fast social media, quick with updates and alerts, on a range of topics and events. it’s good for identifying people and their networks, not necessarily for finding the truth, but what individuals and institutions value and say. twitter is not a ci tool as such, but more valuable for marketing and consumer insights, potentially easily to manipulate and controlled by communication departments. it’s largely a place where individuals and corporations promote themselves and their products. in the figure 1 results for h1. 57 next part we conduct an analysis to see what this may mean. 4. analysis 4.1 the results from the empirical work on the hypotheses the first hypothesis is “twitter is useful for competitive intelligence” (q1). 46.7% answered “i agree” and 23.3% “i completely agree”. this makes 70%, thus we can accept hypothesis 1 with 95% certainty even though we have a high confidence interval of 7 (figure 1): h1: accepted the results for the other hypothesis were: h2: those who post on twitter have valuable information (q2). 43.3 % answered “i agree” and 5% “i completely agree”. this makes 48.3%, thus we cannot accept hypothesis 2: h2: rejected this may at first seem like a contradiction. if twitter is useful for intelligence is it then possible that those who post on twitter do not possess any valuable information? it may be that intelligence professionals can find valuable information about markets, industries, and products without the person tweeting having any valuable information. it would mean that the value comes from the analysis of the data, not the data itself. we find this in some of the answers above, it may be that the value of the information lies in the things that are not said. if we have knowledge about an industry we can draw our own conclusions that are not the same as what is being tweeted. in the comments above we find an emphasis on “extracting knowledge and insights” and “opinion mining and sentiment analysis”. this suggests that it is not so much the raw data that is valuable as the analysis of the data. intelligence professionals know that corporate tweets come from communication departments and professionals. they may know how to read what they see or what is between the lines, so to speak. in that lays the valuable information. for h3 we asked “those who post on twitter whom i follow have valuable information” (q3). 46.7% answered “i agree” and 18.3% “i completely agree”. this makes 65%, thus we can accept hypothesis 3: h3: accepted here the respondents are saying that there are also those who tweet who possess valuable information and the individuals that i follow belong to this group. again it may be seen as a contradiction that there is no valuable information for ci on twitter (h1), but those i follow have valuable information, but by the same logic respondents could be saying that most of those who tweet do not have valuable information, but those i follow do. regarding, the fourth hypothesis “i get my most valuable information from twitter” (q4), 20% answered “i agree” and 1.7 % “i completely agree”. this makes 21.7%, thus we cannot accept hypothesis 4: h4: rejected there are other sources that are much more valuable in terms of intelligence for professionals than twitter. those who disagree are 36.6% and those who strongly disagree 18.3%, in total 54.9%. it is a surprise that the percentage rejected is not even higher, as the comparison here is with all other sources. it may be that respondents thought of social media only, which is h5. in hypothesis 5 we claim “the most valuable information i get on social media is from twitter” (q5). 15% answered “i agree” and 6.7 % “i completely agree”. this also makes exactly 21.7%, thus we cannot accept hypothesis 5 either: h5: rejected respondents gave similar answers to questions 4 and 5. there was a possibility to go back and changes answers in the survey, but respondents may have ignored this. it is tempting to treat the answers given in 5 and 6 as if both were comparing with other social media only. from the other questions, we know that users check their twitter for 16 minutes per day on average (q7), send 1.2 tweets (q8) and use twitter for professional use 50.1% of the time (q9). we did not get any reliable data about how many times a day users check their twitter account (q6). from q6-9 we see that twitter is only one of several social media channels used by respondents and only attracts limited attention. this is also confirmed in the comments (q10). 58 4.2 no stand-alone application twitter is not a good stand-alone application, but is best used with other software. this can take two forms, either beside and/or alongside other software (additional software solutions), for example together with facebook and linkedin or in conjunction with other software, like tweriod and buffer (integrated software solution). twitter is an ineffective software when used alone. when using other software in conjunction with twitter the supportive software helps to render twitter more effective. as an example, below we used tweriod to find what day and times my own followers are most active, as shown in figure 2. the graph presents times for weekends in general, sunday, monday and weekdays. if we are to choose one day we should tweet on monday at 6 pm or 9 pm. the lowest chances of tweets being seen is on sundays. if we choose one time to tweet, monday at 3 pm is the best. using buffer we can then schedule automated tweets, for example on the coming monday at 6:00 pm. in the example in figure 3 we schedule extracts from my book “geoeconomics” (søilen, 2012c). followers and tweet readers cannot see that the tweet comes from a bot. integrated software solutions allow me to use my working days more effectively and better plan what is to be communicated. without it, social media services like twitter, where we are always asked to check what just happened, tend to steal too much of our time. 4.3 fake news we see that users did not find “fake news” to be a problem in general on twitter. users expect the information from companies to have a certain angle, to be manipulated or come as propaganda so they analyze the data based on this assumption. we may assume that professionals and experienced users know what to look for to avoid being tricked (for example, number of followers, number of retweets, links/urls, likes). those who are being tricked tend to be more inexperienced users. this does not mean that experienced users cannot be tricked with false data, but they themselves do not see “fake news” as a problem for the value of the information they get from twitter. it may be that they have a low self-criticism ability, we do not know. for twitter as a company this is good news, as figure 2 analysis in tweriod. 59 professional users are not concerned about being tricked or bombarded with fake news and are not considering leaving twitter for this reason. even though the biggest accounts (most followers) are connected to pop stars and celebrities, the fact that bbc and cnn rank high is a sign that there are also those searching for more objective news and content that have a broader bearing on life. among the smaller accounts there are many examples of valuable information coming from experts and professors like richard dawkins (2.5 million followers), yanis varoufakis (1 million), joseph stiglitz (200,000) michael porter (151,000) niall ferguson (127,000) and steve keen (46,000). thus valuable information is very much a question of whom we chose to follow. this again assumes that we know who knows and who we can trust. 4.4 comparing findings to theory much existing theory is confirmed. professionals find twitter valuable for alerts, breaking news and events. when compared to theory, respondents in the sample miss part of the deeper insights of social media analytics for its value to market intelligence. in comparison with traditional data, social media content is much richer and contains a diverse range of information. in this regard, business intelligence gleaned from social media can enable business analysists and decision makers to develop market insights into consumer behavior, discover new marketing ideas, improve customer satisfaction, and ultimately increase returns on business investments (chau and xu, 2012; chen et al., 2012). 5. future studies i always find conclusions to be of less value in papers as they just repeat what is said elsewhere. for the same reason we do not like introductions because they do not get to the point. most tweeting happens “on the go” with people using smartphones (mcgee 2012). does this affect the quality of the information conveyed? or does it make the information figure 3 example of twitter scheduling. 60 more actionable, more up to date with what is happening in the market? most studies are on likes and retweets, but it would also be interesting to see what value comments have on tweets as the third active possibility to give a reaction. what is more effective: using time on commenting, retweeting or liking a post? a study by chu et al (2012) found that 10.5% of twitter accounts are bots, with an additional 36.2% classified as “cyborgs” (defined as a “botassisted human or human-assisted bot”). future studies should find out how much of this is pure spam, thus less valuable information. bots are also used to spread viruses. there is a risk that social media is being filled not only with more information but less valuable information not only in the us but also in other countries like russia (kelly et al., 2012) and that the valuable information is getting harder to locate. to avoid manipulation it is important to separate between and identify what information comes via human, cyborg, and bot accounts. twitter as a microblogging platform has vast potential to become a collective source of intelligence that can be used to obtain opinions, ideas, facts, and sentiments. but, what are the incentives for sending valuable information out for free unless in anger or as a revenge? those 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(2011), “the influence of user-generated content on traveler behavior: an empirical investigation on the effects of e-word-of-mouth to hotel online bookings”, computers in human behavior, vol. 27 no. 2, pp. 634-639. doi: 10.1016/j.chb.2010.04.014 eg-uk conference paper style guide 48 factors shaping vendor differentiation in the business intelligence software industry klaus solberg søilen*, anders hasslinger **(corresponding author), halmstad university, sweden klasol@hh.se revised version accepted december 5 2012 abstract: this paper is investigating, through a mixed-method research combining interviews and an online survey, how bi vendors differentiate themselves when it comes to application integration, security issues and pricing strategies. the conclusion is that bi vendors differentiated themselves mainly by having individual definitions of what bi is. buyers are therefore advised to compare vendors through the vendor’s definition of business intelligence. security issues were mainly user centric and pricing strategies implied that vendors approach buyers in a similar way where they offered standardized software bundles that would require some degree of customization in order for the buyer to derive the maximum benefit from the applications. it can be deduced from the obtained results that most competitive bi vendors are acting more homogenous towards buyers when they offer their products and handle customers, compared to niche bi vendors. keywords: business intelligence, software production, application integration, pricing strategies, security issues, definitions 1. introduction making the right decisions has always been the major concern in the strategic field. businesses are constantly under pressure to make the right decisions. having the right information timely at hand is crucial for maintaining a competitive position in the market. in this paper we study business intelligence (bi) vendors. the core of the study focuses on vendor differentiation, although implications may be drawn for clients. furthermore, as most of the larger vendors cover a huge area of softand sometimes even hardware applications, as well as associated products, it is difficult to overlook these aspects and solely focus on bi. business intelligence is a discipline which overlaps with other subjects such as business performance management (bpm), customer relation management (crm), decision support systems (dss) and knowledge management (km). the overall objective of this paper is to account for how vendors chose to differentiate themselves in what has evolved into a homogenous business environment. the focus of the industry lies in distinguishable differentiation in terms of pricing available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2012) 48-54 https://ojs.hh.se/ 49 strategies, application integration and security issues. this paper does not intend to identify the individual differentiation strategies of single vendors. the aim is rather to generalize the findings across the bi market. 2. method data collection in this research is conducted partly through one deep interview with oracle, followed by eight completed online-questionnaire from vendors. the questions asked in the interview are the same as in the questionnaire, but leave more room for discussion and depth. the interview was possible, using a digital recording device. hence, the data collected through the online-questionnaire and the interview is considered to be primary sources of data. secondary sources of information for this study come in form of books and journals. the bi vendors that were included in the research are presented below: table 1: list of participants the statistical population was defined as a result of an internet based research on business intelligence vendors. the magic quadrant for business intelligence platforms report issued by gartner inc., an american based it research and advisory firm, also provide insights into the bi market to give an idea of which vendors are relevant. the program used to create the questionnaire was eval. the research questions will provide answers to the title and are limited within the context. they are as follows: q1. how versatile in respect to data exchange and integration are bi products today? q2. what are the major information security issues associated with bi products today? q3. how do bi vendors chose to differentiate themselves from their main competitors? q4. what pricing strategy do bi vendors pursue? q5. what are the main reasons for customer rejection? q6. what clients, servers and databases does the bi platform support? q7. how importantly do vendors view customer needs for a complete solution? q8. where do bi vendors see their competitive advantage? q9. where do bi vendors see their future opportunities and threats? 3. theory and problem discussion according to howson [2008] business intelligence is a set of technologies and processes that allow people at all levels of an organization to access and analyze data. loshin [2003] uses the definition of the data warehousing institute to define bi as “the process, technologies, and tools needed to turn data into information, information into knowledge, and knowledge into plans that drive profitable business action. business intelligence encompasses data warehousing, business analytic tools, and content/knowledge management.” [loshin 2003, 6]. business intelligence may however be defined in many ways. often vendors “craft” their own definition to show their tools in the best possible light [langit 2007]. there are often not only different definitions of bi, but different terms are used to describe business intelligence. thus bi is often wrongly referred to as competitive intelligence (ci), business performance management (bpm), executive information systems (eis), management information systems (mis), business information system (bis) or decision support system (dss), just to name a few of the more common forms. it is vital to distinguish between the differences in terminologies. e.g. according to clifton and sutcliffe [1990], dss support the decision-making process and is most effective at calculating risk, as for example probability situations, where the manager is faced with a number of alternative choices. dss enables managers to retrieve information ad hoc and as straightforwardly as possible in order to facilitate decision-making. executive information systems (eis) are a function of a dss, as they provide decision support to management, with information retrieval powerful display capabilities for business graphics, and communications. thus the term eis may be vendor participant country method oracle director bi sales consulting emea ger interview sap product management ger online survey micro strategy emea marketing director usa online survey tibco european manager, technical sales usa online survey traction software president and cofounder usa online survey astragy marketing director ned online survey sas institute academic sale swe online survey qliktech country manager swe online survey microsoft marketing manager bi swe online survey 50 seen as an old fashioned term to describe today’s digital dashboards, which are also often described under management information systems (mis). an enterprise resource planning (erp) system could be described as the backbone and perhaps basic it system in an organization. the creation of erp-systems integrates all the functional areas of an organization. although erp-systems can integrate all business transaction data, it is not a system for data analysis. these transactional systems, however, do not meet management’s needs to discover trends and patterns for performing optimized and effective decisionmaking. erp-systems are designed to record and manage business transaction data. if bi and erp are integrated, they contribute with additional value to the organization, which may be used to enhance erp-systems. in contrast, analytical bi systems are designed to examine large volumes of data as a foundation for decision-making [chou, tripuramallu, & chou 2005]. business performance management (bpm), also known as enterprise performance management (epm), is a framework for automating, organizing, and analyzing business processes and systems that drive business performance to achieve maximum value [blansfield 2003]. indart [2006] concludes that performance management solutions are more process-orientated. lee & dale [1998] conclude that bpm could be considered a customer-focused approach to the systematic management, measurement and improvement of all company processes through cross-functional teamwork and employee empowerment. bose [2005] claims that bpm is a combination of planning, budgeting, financial consolidation, reporting, strategy planning and business scorecard tools. specifically, bpm helps operational bi decision making become more proactive and timely, and support a wide range of business users [ballard et al. 2005]. therefore with regards to the analytical capabilities, one could argue that bi is a part of bpm. as bose [2005] points out, menninger concluded that “most vendors do not offer the full set of these components, so they adjust their version of the definition to suit their own product set” [bose 2005, 50]. it could also be argued that mbp is so wide a term it risks to become equivalent to terms like management, which at the end can come to mean all that managers do within the private organization. an overview of the definitions is presented below: abbr. term definition bi business intelligence a umbrella term referring to the technical side within private intelligence and the process of collecting, processing, analyzing and disseminating intelligence bpm business performance management a framework for automating, organizing, and analyzing business processes and systems that drive business performance to achieve maximum value ci competitive intelligence a umbrella term referring to the managerial side of private intelligence dss decision support system computerbased information systems that support decisionmaking activities by presenting alternative choices eis executive information system computer-based information system providing easy access to both internal and external information relevant to meeting the strategic goals of the organization on a graphical user interface. sometimes referred to as to digital dashboards epm enterprise performance management see bpm erp enterprise resource planning enterprise-wide information system designed to coordinate all the resources, information, and activities needed to complete business processes such as order fulfillment or billing. table 2: list of definitions the two most related terms are bi and ci. defining the differences between bi and ci has caused considerable debates between practitioners and academics [wright & calof 2006]. the term has become clearer now that the impact of the technology side has become more evident. e.g. solberg søilen [2005] points out that business intelligence now relates to the technical side whilst competitive intelligence relates to the managerial side within private intelligence. a logic overview of the most important terms is presented in a venn diagram below (white background indicates it based): 51 figure 1: logic of terms another question which often arises is about knowledge management (km) and how it should be treated in respect to bi. knowledge management deals with the process of creating value from an organization’s intangible assets [liebowitz 1999]. bi has more practical problem solving features, whilst km encompasses the realization and preservation of knowledge. solberg søilen [2005] argues that all subjects dealing with information and knowledge may be gathered under the term information management. marketing is also an area into which bi often finds its way, especially when gathering data about customers such as through crm. at the end what should decide what term is used for each study or specialization is if it can be clearly defined and thereafter its usefulness. 4. critical differentiations defined 4.1 application integration within the context of enterprise systems, there is no single definition what integration entails. general consensus lays within the description that integration makes applications work together that “were not intended to work together by passing information through some form of interface” [gulledge 2006, 5]. companies that implement a bi solution often have an existing erp-system from which they obtain the transactional data which is used for analysis. it automatically becomes an important issue how well the systems work together. howson [2008] states that, historically, companies had to buy multiple bi front-end tools from different vendors, because no single vendors offered the full spectrum of tools. according to howson [2008], as an example microsoft office excel is sometimes referred to as the leading bi tool for creating spreadsheets. hence, the importance of offering integration to applications such as the microsoft office series or similar products with widespread usage. from a customer’s point of view bi projects should be funded based on a projected return-oninvestment (roi) [hedgebeth 2007]. on the other hand, fuld [1991] argue that companies should not make an intelligence program a strict roi issue. yet, bi is often roi driven. companies that implemented erp solutions and that were unable to justify roi for erp implementation, were sometimes implementing bi software since bi enhanced the utilization of the enterprise data [chou et al. 2005]. 4.2 security there are several threats to computer security which of course influence the security of bi systems. sanderson and forcht [1996] show that there are a number of intruders that poses threats for a number of different reasons. examples are foreign intelligence services, organized crime, terrorist organizations, industrial espionage agents, private investigators, and information brokers who illegally sell information as well as hackers. security threats to system structures are constantly being added as the overlapping of computers, resources and industries, referred to as convergence, integrates it infrastructures to provide more customers through established lines. sanderson and forcht [1996] argue that, “threats to companies through convergence have a great range” [sanderson & forcht 1996, 33], involving anything from fraud, unauthorized disclosure of information, and unauthorized modification of sensitive information, to information brokering. computer fraud and abuse may involve the accessing of computers without authorization or exceeding that authorization to perform malicious acts against computing resources. generally regarded as the biggest threat to an organization’s information resources, however, are insiders employees and others in trusted positions with an organization that have great access to information within the organization [denning 1999]. regarding bi, there are typically two major security areas discussed in the literature: role-based access and internet security. the first deals directly with the employees and the second more generally with computing. the two terms role-based access and internet security are explained with greater detail below. the weakest spot in a bi system may also vary. the information in olap structures is often very sensitive. the sensitivity can range from highly confidential internal data to data that has a high level of intellectual capital investment [rasmussen et al. 2002]. however, it security in general and bi security, are much broader topics than what has been suggested here. role-based security usually has roles defined for different levels of responsibility within an organization. rasmussen et al. [2002] describe role-based access as associating a user id with a role which has certain restrictions for information 52 visibility. employees that fall into certain areas of responsibility then become members of those roles. vendors often offer two types of licenses: named-user licenses and concurrent licenses. named-user licenses are purchased and assigned to specific end-users, whilst the concurrent user licensing structure provides a specific number of licenses that may be shared amongst a group of users [bontis & chung 2000]. for example, a business with two concurrent licenses to an application that are set to three workstations can have two employees using the application simultaneously. a third user is not allowed and has to wait until one of the two users logs-off. some vendors also offer different classes of users, for example a standard user and a light user license. the standard user is given full application access, whilst the light user is given a restricted set of features [bontis & chung 2000]. it may also be a great advantage to businesses making bi information available to its employees across the internet. it may range from information that is running on a secure connection to information that businesses wish to make public. the advantage of using the internet is that it offloads all the infrastructural responsibilities of an it department, which could stand for significant savings. the downside is associated with security issues as the growing success of the internet, make it easier to invade corporate privacy [wright & roy 1999]. 4.3 pricing strategy in terms of b2b software pricing strategies, there is not a single perfect generic pricing model. in a case study, bontis and chung [2000] conclude that “vendors must understand the value they provide to customers and create a price structure that aligns pricing with value realization, but more importantly facilitates their business objectives of the product and service.” [brontis & chung 2000, 246]. thus, it depends on the need of the buyer that vendors align pricing with the buyers product goals. originally, as software ran on mainframes, it was priced according to cpu speed. this pricing method, based on processing usage, did not consider the needs of neither buyers nor vendors [bontis & chung, 2000]. as software architectures evolved through time, pricing models moved towards named and concurrent user licenses. named-user licenses are purchased and assigned to specific end-users, whilst the concurrent user licensing structure provides a specific number of licenses that may be shared amongst a group of users. bontis and chung [2000] explain that the price structures, associated with concurrent licenses, charge customers according to their peak user predictions. a software vendor is, therefore, looking for both revenue maximization as well as market share as concurrent licenses are accessibly from a corporate site. additionally the license time is of importance. the possibility to offer a perpetual license, that is one that continues indefinitely [bennet & kosc 2002], or a term license, one which is limited in time and can be renewed are important and common possibilities for vendors to charge its buyers. other possibilities are for example rental or leasing, where there are no boundaries set to the payment or pricing options. hence, as concluded by bontis and chung [2000], software development is an output of a programmer’s intellectual capital, the pricing of software often requires a more subjective approach. a recent study [pricewaterhousecoopers 2008] shows that software vendor revenues are shifting from license fees to maintenance fees. the study explains that a consistent trend is the transition from large perpetual licenses to alternative models that stretch payments over a period of time. other vendors are finding greater success by generating more revenue from maintenance and support instead. another trend that has emerged within the software industry are software-as-a-service (saas) solutions. saas is web-based software which is purchased on subscription basis and allows an organization to shift almost all their technological responsibility to the vendor [lashar 2008]. the saas model is an objective pricing model based on transactions volume and usage. the adoption of a saas model, however, eliminates most of the challenges that occur with product installation and allows firms to optimize their resource allocation. [bhingarde et al. 2008] lashar [2008] also states that saas can be a compelling option especially for larger business if the need for standardization, data centralization and bi exists as opposed to the need for differentiated functionality within the organization or specialized functionality; in which case, saas would not be an option. 5. results the overall objective of the paper was to account for how vendors chose to differentiate themselves in terms of pricing strategies, application integration and security issues. nine research questions were set of which eight could be answered. one research question could only be answered partially, but is viewed upon as not answered. the study collected data from a bi vendor population that what was set to one deep interview and 27 vendor questionnaires. out of these 27 a total of 9 vendors completed the questionnaire, which can be said to have been expected given that no financial remuneration was offered. 53 the areas of application integration (q1), security issues (q2) and pricing strategy (q4) can be summarized within this research to the bi market as that application integrated easily. the research question, what clients, servers and databases does the bi platform support (q6), could only be answered incomplete. the reason for this is that the received answers could not be organized to support any general conclusions. due to the way the question was phrased, the research question remains unanswered. security issues (q2) were mainly user centric and pricing strategies (q4) implied that vendors approach buyers in a similar way where they offered standardized software bundles that could require some degree of customization in order for the buyer to derive the maximum benefit from the applications. it can be deduced from the obtained results that the most competitive bi vendors are acting more homogenous towards the buyers in the way they offer their products and handle customers, compared to niche bi vendors. one implication that can be drawn for buyers from the obtained results is that buyers should carefully look at what they want to do with a bi system and find a vendor that has a definition of bi similar to the buyer’s vision. more importantly bi vendors chose mainly to differentiate themselves (q3) through their individual definition of how they define bi, as also stated by howson [2008], to create a definition that best suits their products. we could call this the selling theory of the business intelligence label, even though i am sure it related to many other forms of software and services as well. hopefully a clearer difference as to the meaning of the terms used, as suggested in the table and the venn model above, can help avoid this problem in the future. there was no clear reason to why potential customers, such as customers that are in negotiations with several vendors, would reject (q5) a vendor. one reason was that the vendor perhaps did not fulfill the client’s needs, but not what the underlying reasons were. due to the received answers, it can be said within this context, that vendors generally did not know the specific reasons. most vendors saw that their competitive advantage (q8) was that they were able to offer the customer a complete bi solution (q7) within the entire spectrum of bi applications, or that they were focusing on niche areas such as traction software. not many vendors chose to answer the question where they saw their future opportunities and threats (q9). those that did, however, delivered some interesting market insights. the bigger bi vendors clearly saw their advantage in working with the full spectrum of bi tools and possibilities. most vendors did not see any threats, or at least did not state them. one stated that it did not see any threats, but rather opportunities, whilst another feared low-end competition from generic tools such as offered from google and microsoft. most opportunities were seen in making bi available across an entire company and thereby moving more towards operational bi. oracle saw huge opportunities for bi for the future as the demand for decision making based on intelligence obtained from data is increasing. further oracle points out the possibilities that are emerging within rfid. regulatory changes make it possible for data to be stored even longer and be used for analytics. tibco saw opportunities within pervasive bi, by optimizing today’s bi environment and responding to the emerging demand from this convergence to make decision making available in real-time within the right context to any specific business process. traction software looks towards a web 2.0-style integration with erp software, in the context of product development and manufacturing, with bi through human analysis, dissemination and issue tracking. astragy saw possibilities within saas and sas institute within analytics while microsoft expected future opportunities are to be found in making bi available to everyone 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(2019) using open data and google search data for competitive intelligence analysis. journal of intelligence studies in business. 9 (2) 72-81. article url: https://ojs.hh.se/index.php/jisib/article/view/410 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index using open data and google search data for competitive intelligence analysis jan černýa, martin potančoka*, zdeněk molnára afaculty of informatics and statistics, department of information technologies, university of economics, prague, czech republic *martin.potancok@vse.cz journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: making sense of the collective intelligence field: a review collective intelligence process to interpret weak signals and early warnings fernando c. de almeida and humbert lesca pp. 19-29 study on the various intellectual property management strategies used and implemented by ict firms for business intelligence journal of intelligence studies in business v ol 9 , n o 2 , 2 0 1 9 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 9, no. 2 2019 klaus solberg søilen pp. 6-18 shabib-ahmed shaikh pp. 30-42 and tarun kumar singhal a new corpus-based convolutional neural network for big data text analytics wedjdane nahili, khaled rezeg pp. 59-71 and okba kazar business intelligence using the fuzzy-kano model soumaya lamrhari , hamid elghazi pp. 43-58 and abdellatif el faker using open data and google search data for competitive intelligence analysis jan černý, martin potančok pp. 72-81 and zdeněk molnár the potential of business intelligence tools for expert finding mehdi dadkhah, mohammad lagzian, pp. 82-95 fariborz rahim-nia and khalil kimiafar using open data and google search data for competitive intelligence analysis jan černýa, martin potančoka* and zdeněk molnára afaculty of informatics and statistics, department of information technologies, university of economics, prague, czech republic corresponding author (*): martin.potancok@vse.cz received 23 september 2019 accepted 28 october 2019 abstract open data are information entities that are of significant importance for many institutions, businesses and even citizens as the part of the digital transformation within many fields in our society. the aim of this paper is to provide a competitive environment analysis method using open source intelligence within the pharmaceutical sector and to design the optimal data structure for this purpose. firstly, we have described the state-of-the-art of open human medicine data within the european union with a focus on antidepressants and we have chosen the czech republic as the primary research territory for demonstrating competitive intelligence analysis. secondly, we have identified the competitive intelligence and open source intelligence relationship with a new possible contextual analysis method using open human medicine data and google search data. finally, this paper shows the potential of open deep web data within competitive intelligence activities, together with surface web data entities as a lowcost approach with high intelligence value focused on the pharmaceutical market. keywords competitive intelligence, data structure, digital transformation, open data, open source intelligence, osint 1. introduction open data plays a significant role in our present society and is one of the most important digital transformation trends. moreover, it has become a solid part of the activities of business units that are charged with business analyses, insights and strategy plans (janssen et al. 2012). the reason can be found in a very broad spectrum of industries and areas where open data has started to be a rational form of result output. as the number and scope of such open datasets has grown enormously to include in the areas of transportation, public services, natural science, education, demography, and last but not least the health sector, it has also become a significant part of many national information policies, shifting from governmental down to local levels. in the usa, a growing trackable significance was evident during the obama administration after the official data.gov site was launched (kostkova et al. 2016). data is also an essential part of the eu’s digital single market strategy, as “the eu needs to ensure that data flows across borders and sectors and disciplines. this data should be accessible and reusable by most stakeholders in an optimal way.” (european commission 2018). moreover, massive digitalization and increasing information system/information and communication technology (is/ict) usage have brought big data challenges and demands for non-traditional analytical methods to uncover global and regional trends (gandomi and haider 2015). journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 72-81 open access: freely available at: https://ojs.hh.se/ 73 this means, therefore, that open data appears to be a strong tool for a spectrum of competitive intelligence (ci) and open source intelligence (osint) methodologies at all levels of different industries and organization types. ci can be defined at its basic level as the process of planning, collecting and disseminating data, information and knowledge for the purpose of better decisionmaking, eliminating risks and uncovering of business opportunities, primarily in an external company environment (grèzes 2015). the first phase identifies particular business information needs through key intelligence topics (kit), and then key intelligence questions (kiq) which analysts use for the collection process as they define information requests (herring 1999). osint consists of a very similar cycle as ci, but it also consists of an open data and information source mining process through the collection phase. in addition, osint end-users do not come primarily from business, but from government, military, intelligence services and from the security service sector. in the present paper we have focused on open human medicine data from two perspectives: government and business. in both cases we wanted to design open data intelligence analysis methods for the public sector, e.g. policy makers, ministers, commissioners and other key persons. our governmental direction is directed towards setting up the optimal open data structure, and our business direction is directed towards complex business environment analysis. to demonstrate our intent, we have chosen open human medicine data focused on antidepressants. to increase specificity, we have added a google search data perspective to gain a territorial dimension for our analysis. our two main research questions are: could open data provide significant ci insights within the pharmaceutical industry? and could the surface web search data deliver a territorial perspective to anonymous open human medicine data? 2. literature review there are several studies of how open data could help in the health sector. for example, bernard et al. (2018) seek possible open source solutions that could be used for the detection, reporting and control of disease outbreaks, and analyze the previous use of similar tools in ebola and sars epidemics. one part of this work also considers the ethical level (oubrich 2011) of these intelligence activities within the context of data ownership. this question is also discussed by kostkova et al., (2016). brownstein, et al. (2008) find the power of public information sources in the signal intelligence scope for outbreak-oriented detection activities to be at the local level of information sources such as discussion sites, disease reporting networks, and news outlets (with regards to a very detailed verification process). google search data played an important role in the past within the google flu trends project. as cook, et al. (2011) show in their evaluation, this tool was highly accurate in the prediction of influenza activity in the united states based on user search queries. akhgar, et al. (2016) demonstrate the complex usage of osint methods, however the critical issue is also focused on an early warning system for health hazards. open innovations (hughes 2017) and open data (european commission 2019) initiatives are also more visible in the health sector over recent years. for example, cantor, et al. (2018) developed a dataset for community-level social determinants of health and strengthened the decision-making process for care planning. farber (2017) discusses whether data repositories can help find effective treatments for complex diseases. his suggestions for informatics communities consist of methods concerning the provision of an effective data infrastructure with the inexpensive method of data accessibility from different datasets, monitoring the growth of biomedical datasets and finding ways to link data in different repositories. perer and gotz (2013) and hu, et al. (2016) have illustrated how data-informed and datadriven decisions can be supported by data visualization in the health sector. to achieve appropriate data visualization several principles should be followed (e.g. simplify, compare, explore) (few 2012). 2.1 survey and preparations the quality of open datasets is an aspect of many discussions at all levels of the policymaking process. policy makers put high pressure on the availability and frequency of the “update” aspect, but we would like to raise concern over the poor open data structure concept with regards to quality. within this context, we highlight our recent study directed toward open human medicine data in the european union (cerny et al. 2018). during the first three months, we made a large survey 74 of national medicine control offices and their open data policies. the results showed significant differences. further, we have designed a method for the new ci approach and demonstrated the context for open human medicine data and google search data. there were a number of reasons for this step. to begin with, according to our secondary survey, five billion google queries are conducted per day, and even a small sample of this amount could lead to significant insights. the second reason is that national control offices provide datasets strictly anonymously, with no territorial information. and, through the google trends application, we were able to mine the information-seeking behavior of surface web users and get the following data entities: • the searcher interest rate • the territorial origin of the searchers (region, city) • trend keywords connected to our desired terms 3. key intelligence questions after we defined the research questions, we continued and narrowed our information needs through the following key intelligence questions (kiq): • kiq1: is antidepressant use increasing in the czech republic? • kiq2: what is the most prescribed antidepressant on the market? • kiq3: who is the key player in the specific market? • kiq4: what is the market share of antidepressants on the specific market? • kiq5: how can google search data help to determine territorial information seeking behavior regarding antidepressant-oriented queries? 4. material and methods 4.1 medicine data structure we have analyzed data accessibility from national control agencies that are in charge of regulatory and distribution policies in the european union, switzerland, norway and turkey. when we contacted each agency, we collected information about time response, level of content relevancy feedback and the human factor based on their ability to help regarding the requested data collection. we were aware that the results from this primary research are strictly qualitative and could be misleading, so we broadened the timeframe of the research to three months. e-mail communication has been chosen as the first method of contact, however, in specific cases phone communication was also needed. secondly, we went through all the possible information sources, e.g. official websites, repositories and ftp servers, and monitored whether the open human health datasets are available and how they are handled with respect to their format. if the datasets did not exist online, we concentrated on a search system interface that could be used to generate datasets with the required data fields. if there was no evidence of the existence of open data, we contacted the person in charge of communication to gather information about the state of the open data policy. as our aim is to gain market insights regarding antidepressants, we have focused on the specific data entities that could lead to quality business analysis. table 1 suggests the fields we have monitored and that, in our opinion, could uncover specific market trends. here we explain why our suggested data fields should be considered to be key information elements for advanced ci business analysis. table 1 designed data field for a complex business analysis. atc anatomical therapeutic chemical classification system code_med specific code of the medicine name name of the medicine additional_ information additional information to the name producer registration holder country_origin_ producer country of a registration holder number_of_ packages_year number of packages / year price_nosur charge_excl_vat price per package excl. a surcharge and vat total_sum_nosur charge_excl_vat total sum / all packages / excl. a surcharge and vat price_surcharge_ incl_vat price per package incl. a surcharge and vat total_sum_surch arge_incl_vat total sum / all packages / incl. a surcharge and vat number_ddd defined daily doses / package total_ddd defined daily doses / total ddd_1000inh_day defined daily doses / 1000 inhabitants 75 firstly, the atc code (who 2018) is the internationally respected classification in the pharmaceutical field. we can demonstrate its role in our case study. as shown below, we have chosen the n06a group, but if the specific active component is needed for analysis, we could narrow it down and be more specific. • n nervous system • n06 psychoanaleptics • n06a antidepressants • n06aa non-selective monoamine reuptake inhibitors • n06ab selective serotonin reuptake inhibitors • n06af monoamine oxidase inhibitors, non-selective • n06ag monoamine oxidase a inhibitors • n06ax other antidepressants the lowest level of the classification is further divided into specific medicines and this could be a crucial factor for resolving the situation when the datasets do not include commercial medicine names. for example, class n06aa (non-selective monoamine reuptake inhibitors) covers subclass n06aa01 (desipramine) along with information about the daily defined dose (ddd). in this scenario we would use mesh browser (u.s. national library of medicine 2019) to uncover commercial names, e.g. pertofran, norpramin among others. the specific code of the medicine supports atc codes as the existence confirmation identifier of the specific medicine. the name of the medicine, its additional information and the producer, together with the country of origin, are the basic identifiers of any possible commercial entity analysis. the significance of the market activity of a given producer, or possibly of a specific medicine, uncovers the total number of prescribed packages with their total cost with no surcharge and excluding value added tax. additional price fields are used for the price comparison of individual medicines. 4.2 google data structure further, our intention was directed towards the process that could verify our open human medicine data ci market analysis results. if we were able to get detailed market data about pharmaceutical companies, we would also need to add territorial information, which is crucial because of the strict anonymity of open human medicine data. through the google trends application data, we were able to mine the information-seeking behavior of surface web users and obtain the following data entities: • the searcher interest rate with retrospectivity to the year 2004 • the territorial origin of the searchers (region, city) • trend keywords connected to our desired terms • we have structured the google search data sets as follows: • country • search term (the keyword antidepressant in a given national language and in english) • week (in a specific year) • number of searches in given country • region • number of searches in given region 5. results 5.1 open human medicine data analysis results the data collected reflect the present level of open human health data quality and accessibility. we went through all three levels of the collection process and found significant differences. the biggest issues we faced could be identified as the different data structure in each of the countries together with language barriers leading to difficulties as to when data should be used in a whole-region analysis. some datasets were complex (e.g. the czech republic and slovenia), while others provided only simple insights into specific medicines, e.g. wales or slovakia, and others, e.g. bulgaria or greece, had no data. although some countries had neither open repositories nor data files accessible, a few of them did provide a specific search interface that could be used for searching, filtering and exporting open medicine data. this approach is advantageous because the exported files already include the requested class of the medicine. excluding france, we could define the classes in the search forms with the specific atc code. poland, croatia and lithuania especially have powerful search interfaces. the third level of the data collection phase found significant differences between the information services of the agencies. table 2 summarizes the response time, with comments. where references are mentioned, the agency provided links to repositories, or to search interfaces. 76 table 2 survey of agency information service time response. r = days until response. entity r institution remarks austria 1 ages (1 day), basq did not respond bulgaria 5 bda (no data availability) croatia halmed (no response) czech republic 1 súkl (reference to the czech datasets) estonia 5 ream (did not provide datasets with requested fields) finland fimea (no response) france ameli (no response) hungary 20 ogyéi (references) germany 7 several institutions contacted. only paid datasets italy aifa (no response) latvia 5 zva (reference to the search interface) malta 3 medicine authority malta (limited data availability) netherlands 4 cbg-meb (do not provide requested data publicly) norway 7 norpd (references) poland 5 urpl (no requested data availability) portugal 17 infarmed (provided data only for study purposes) romania 5 anm (references) turkey 6 titck (references) slovakia 2 šúkl (only paid datasets) slovenia jazmp (no response) spain 3 aemps (no cooperation) sweden 15 lmf – läkemedelsverket (references) switzerland 2 interpharma (only limited data) united kingdom 18 mhra (contacted several times, references) during the collection process, we dealt mainly with data structure and data quality obstacles and did not get relevant support for our open data ci analysis research. the file formats and structure field values were different in every country. moreover, the data quality implied high time costs in preparation for data analysis, especially when we dealt with the company and medicine name differences in each of the analyzed countries. for the purpose of this paper we have chosen the open data ci analysis possibilities in the dataset from the czech republic. firstly, the czech dataset structure and quality was the most complex of the monitored countries and it is a great example of what can be achieved by open data. secondly, we were able to make valuable market insights, even though the complexity of the data from the czech republic provided a powerful example of what can be achieved regarding competitive business intelligence. however, then we added the comparison possibility between the states with less structured content to demonstrate the minimum analysis context. the requested class of medicine was antidepressants, according to research question two. we have used tableau (2019) to create an interactive visualization which can be shared and analyzed (datig and whiting 2018). by focusing on the czech republic, we can gain very detailed insights. to begin with, we wanted to analyze the antidepressant consumption trend among czech citizens (kiq1). we used an open dataset covering the time period from 1991 to 2018. figure 1 demonstrates the increase in antidepressant consumption during this period. figure 1 czech antidepressant consumption 1991-2018. table 3 czech antidepressant medicine leader market insights through open data 2009-2018 with prescribing information. producer medicine name total packages percent packages treatment (from prescribing information) h. lundbeck cipralex 5 891 747 23.29 depression and anxiety disorders (panic disorder with or without agoraphobia, social anxiety disorder, generalized anxiety disorder and obsessive-compulsive disorder) zentiva citalec 4 976 308 22.19 depression and anxiety disorders pfizer zoloft 3 881 554 15.34 depression with or without anxiety, panic disorder and obsessive-compulsive disorder and the treatment of posttraumatic stress disorder krka asentra 3 843 125 15.19 depression and prevention of depression (adult), social anxiety disorder (in adults), post-traumatic stress disorder (in adults), panic disorder (in adults), obsessive compulsive disorder (in adults and children and adolescents aged 6-17) angelini trittico 3 763 352 14.88 anti-anxiety, tension, restlessness, sleep disturbance, and sexual function in the context of this trend, our further point of interest was to uncover the most prescribed antidepressants (kiq2, kiq3) and their market share in the country. we have narrowed the time period, as demonstrated in table 3, to get the most accurate market data. this step was necessary due to significant market changes, e.g. prothiaden was de facto the most prescribed antidepressant medicine until the year 2005, and then its popularity fell rapidly. as we can uncover the main medicine representatives in the czech republic, we can connect these with the types of the mental disorder as shown in table 3. this is used to predict mental health trends in a particular area. however, thanks to open data, we can monitor the whole market share of antidepressants (kiq4) and compare whether the producer of the main medicine representatives is similar to the whole antidepressant market share (table 4). table 4 czech antidepressant market share 2009-2018. producer total antidepressant packages percent of all packages sold zentiva 12 193 957 19,46 krka 9 838 079 15,70 h. lundbeck 7 680 389 12,25 angelini 4 006 332 6,39 pfizer 3 974 158 6,34 5.2 google search data results to analyze the context between open human medicine data and information seeking behavior we have used google trends (nuti et al. 2014) including google search data (the context description is given above). the aim of the analysis was to confirm a correlation between google search data and market information about specific antidepressant consumption. google trends (available on trends.google.com) providing google search data in an available form and as confirmed by (nuti et al. 2014) and (nuti et al. 2014) is used by the health sector. the identified set of related keywords (general antidepressant terms and specific names of the medicine) was gradually inserted into google trends, all data was downloaded into a csv file and aggregated. it is important to emphasize that data was downloaded at the regional level for the period of analysis. consolidated csv files were used as a basis for the following analysis (figure 2). the conversion per capita was used for the analysis to ensure comparable results between countries with different population sizes. the overall analysis done in number of searches per capita shows an increase in searches since 2011 and confirms the increase in consumption based on the analysis above. as the analysis shows, the relationship between the number of searches and the number of searches per capita is not affected only by size of the country, but also by other factors. norway, estonia, switzerland, netherlands and austria are among the countries with the largest number of searches per capita. both number of searches 78 and number of searches per capita are above average in the czech republic. it is important to analyze the correlation between czech market trends and czech searching trends. we have chosen the two most prescribed medicines in the czech republic, cipralex and citalec, and compared their market performance with google search performance (figure 3 and figure 4). we demonstrate with these analyses that there is a significant similarity between market data and google data. to sum up, if the state control office does not provide open human medicine data with territorial dimension, we can use google data (kiq5) to narrow our market analysis (table 5 and table 6). 6. conclusions open human health data can be considered to be crucial information entities for competitive environment analysis and for showing particular health trends across a large geographic area. there are two conditions that figure 2 search per capita analysis. figure 3 cipralex and citalec market comparison (no. of packages sold) 2009-2018. 79 could lead to this possible usage. firstly, the data must follow a consistent structure with clearly defined variables. secondly, the datasets have to include the classification codes to uncover specific medicines or active ingredients. we faced significant obstacles with data synthesis during our three-month collection period across the eu member states mainly caused by poor information services with significant differences regarding open human medicine data structure and quality. finally, we were able to demonstrate open data ci analysis with a focus on the czech antidepressant market. moreover, the czech datasets provided us with the possibility of showing insights into specific medicine and company market performance thanks to rich data quality including the atc classification, name of the producers, consumption and pricing data, as well as reliable retrospectivity. we have used the atc classification to filter out the antidepressant class during the time period from 1991 to 2018 for the consumption trend, and then from 2009 to 2018 to provide actual market insights. afterwards, we were able to identify key antidepressant market players and the main antidepressants used in the czech republic, together with consumption data (daily doses, number of packages, etc.) and finally to uncover total antidepressant consumption. our first research question is therefore confirmed: open data and its contextual analysis bring intelligence for a specific country. table 5 google search data territorial analysis with the keyword cipralex 2009-2018. czech region cipralex keyword interest pardubický region 100 region vysočina 80 prague 78 ústecký region 71 moravskoslezský region 69 středočeský region 58 jihomoravský region 58 zlínský region 55 olomoucký region 54 královéhradecký region 50 jihočeský region 45 plzeňský region 43 table 6 google search data territorial analysis with the keyword citalec 2009-2018. czech region citalec keyword interest moravskoslezský region 100 středočeský region 55 jihomoravský region 54 prague 51 zlínský region 33 figure 4 cipralex and citalec google trend comparison 2009-2018. 80 our second research question focused on geographical aspects of open medicine data. firstly, medicine data are strictly anonymous. none of the institutions provided datasets with geolocation. we have decided to use information-seeking behavior data and show possible geographical context to antidepressant consumption. we have used the google search data together with related keywords that consisted of ‘antidepressant’ as the general term and the specific name of the medicine. the analysis has shown that google search data correlates with market trends uncovered by open data analysis, but the territorial insights were not significant in this case due to the small google search data sample and provided only a general regional overview. however, this method would be effective in the analysis of a larger western country (e.g. united states, united kingdom) where it is possible to work with a more significant and detailed search data sample, e.g. on a city by city level. for this reason, we consider the second research question to be confirmed. our future work is directed towards finding possible intelligence links between the open human medicine market data and innovation processes with the perspective of using patent data. 7. discussion our aim in this paper was to provide possibilities for working with open data as a tool for hard-to-get intelligence insights within the pharmaceutical sector. not only did our results provide significant and relevant market context, but they also confirmed that open human medicine data can serve as a trend analysis information commodity for a wide range of public entities, e.g. governmental bodies for decision-making processes aimed at increasing the level of public health. our case with antidepressants has demonstrated the trend analysis possibility within a reliable time frame. thanks to the atc classification system we are able to determine specific health problems within the whole population of a specific country. more importantly, we can compare countries afterwards regarding their health condition. our collection phase regarding the data structure and quality led us to the conclusions that open human medicine data initiatives should be considered more seriously across the eu. we have designed optimal data fields as a common base. this could determine another quality level across the whole of europe and use open data in the most reliable way: to strengthen public health. still, open human medicine data in our designed structure plays an important role for intelligence studies. based on our results, we could get insightful market information in any selected geographical area on pharmaceutical companies, medicine brands and the active ingredients of drugs together with their therapeutic, chemical and pharmacological properties. acknowledgements this paper was written thanks to the long-term institutional support of research activities by the faculty of informatics and statistics, university of economics, prague. this paper has been supported by the iga grant “using open data within competitive intelligence” vse igs f4/32/2018. we also would like to thank dr. james partridge for his academic support. 8. references akhgar, b., bayerl, p. s., & sampson, f. 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(2018). atc/ddd index 2018. retrieved may 29, 2018, from https://www.whocc.no/atc_ddd_index/ 41 applying competitive intelligence: the case of thermoplastics elastomers marisela rodriguez salvador* and luis francisco salinas casanova** *instituto tecnológico y de estudios superiores de monterrey (itesm), **exa-tec campus monterrey, mexico marisrod@itesm.mx and 00casanova@gmail.com received february 2, revised form may 20, accepted december 18 2012 abstract: the objective of this article is to investigate and identify drivers to compete in the industry of plastics through the application of the methodology of competitive intelligence. practical implications: this article provides a practical case of the competitive intelligence methodology applied to the thermoplastics elastomers industry, specifically within the styrenic block copolymers category. the output of this research helped support a mexican company in their decision-making process. keywords: competitive intelligence, thermoplastics elastomers, styrenic block copolymers, hydrogenated styrenic block copolymers 1. introduction thermoplastics elastomers (te) are a class of polymers with rubber-elastic behavior and a processing system typical of thermoplastics. te has the property of being reprocessed when heated above the melting temperature. the capacity of being reused is an advantage regarding the limitation of recycling thermoset rubbers, and with little waste when processing. moreover, te provides significant benefits to reduce pollution impact in the environment, and it has an important role in the economic aspect. styrenic block copolymers (sbc) are high performance thermoplastics elastomers designed to improve a wide range of products and applications. the sbc consist of at least three blocks, two of them are hard polystyrene blocks and one a middle block soft (polybutadiene or polyisoprene); they may or not be hydrogenated. (nandini consultancy center, 2011). the asian continent has now become the main market for sbc, due to a great demand from china. the country is the largest producer of footwear in the world, followed by india; both available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2012) 41-47 mailto:marisrod@itesm.mx https://ojs.hh.se/ 42 consume large quantities of rubber and elastomers, including sbc (löchne & mori, 2011). however the current overcapacity of sbc’s in manufacturing plants in china has caused this product to become a commodity for other uses. the industry presents (löchne & mori, 2011):  a high volatility of raw materials (butadiene, isoprene and styrene);  overcapacity production in china.  some effects from the global economic crisis of 2008-2009; under this context the main goal of this research is to identify new opportunities to compete in the industry of thermoplastic elastomers (te) in the category of "styrenic block copolymers (sbc)", through the application of the methodology of competitive intelligence. the main aim is to identify opportunities to exploit. the research started with the interest of the authors in the competitive intelligence field and in particular how this facilitates the process of decision-making to innovate. it was decided to implement the method in the case of thermoplastic elastomers as a part of a conacyt (national council of science and technology) project between a mexican company (for confidentiality reasons for now the company will be called “xyz”), and the competitive intelligence unit of the center of quality and manufacturing at tecnológico de monterrey (tec), campus monterrey. 2. competitive intelligence methodology as kahaner (1997, p. 16) established competitive intelligence (ci) is "a systematic program to collect and analyze information about competitors' activities and general business trends to achieve the goals of the company". moreover, ci comprises identification of intelligence needs within an organization, collection of data from primary and secondary sources, evaluation and analysis. the main objective is to provide information for the decision making process in order to add value to the organization. the basic model that the ci methodology follows involves a cycle where intelligence can be viewed as a process and as a product – the intelligent result (bose, 2008). the following figure shows an adaptation of the approach proposed by murphy (2005): the principal objective of this model is to support innovation. innovation involves a process to create new knowledge and ideas in order to achieve improvements in processes and organizational structures, creating new products and services focused on market’s needs (bareghehs, 2007) and (rowley, & sambrook, 2009). moreover, innovation could be seen as the implementation of ideas to create value (patterson 2009 in vega, 2010). from this perspective ci is a valuable methodology that helps companies to generate those ideas that are important for the company, searching and analyzing key pieces of information from the competitive environment of the organization. planning data collection data evaluation analyze conclusions consolidate results communicate findings decisionmaking figure 1: competitive intelligence model (compiled from murphy, 2005) 43 3. the case of study: thermoplastics elastomers. as we mentioned earlier, this research was developed to analyze the thermoplastics elastomers industry. the scientific method was applied during this research as part of a master thesis entitled “application of competitive intelligence methodology: case of thermoplastic elastomers” written by luis salinas. it was developed for the engineering school of tecnológico de monterrey, campus monterrey. the objectives pursued were: contribute to increase the practice of ci methodology in mexico; identify market growth rates in this industry; identify lead competitors; to finally support the strategic planning of the company "xyz” based on the evidences obtained. for this purpose we followed the model proposed by murphy (2005) as it is explained in next paragraphs. 1. definition of the initial problem the first stage in the process was to define the problem, in this initial phase the company "xyz" expressed their intelligence needs personally. the company pursued to obtain relevant information regarding new market opportunities or new applications aligned to their core business, in this case the thermoplastic elastomers. 2. identification of the key intelligence topics (kit’s) during this phase of the process, the following kit’s were defined to start the research activity:  thermoplastic elastomers  styrenic block copolymers  styrene block copolymers 3. initial review of the literature a deep revision of literature on the subject of thermoplastic elastomers was conducted. this activity was complemented with interviews with industry experts. this stage was useful to build a theoretical framework for this research. 4. preliminary identification of information sources after reviewing the literature, the next step in the methodology was to define the sources of information to be applied, trying to limit the search to sources that would provide the most relevant information to the project objective. for this task, databases from tecnológico de monterrey, campus monterrey were initially evaluated doing a preliminary search. as a result databases selected were:  datamonitor 360. country statistics, market data analytics, and product launch analytics which also provides market, companies and industries analysis.  isi emerging markets company profiles, news, macroeconomic indicators, financial markets, industry behavior and reports which generally considered emerging countries, including mexico. 5. initial information research once it was defined the databases to be used for the project, an initial research of information was made in order to know the amount and quality of the information that could be obtained. 6. preliminary evaluation these results allowed us to validate both the preliminary databases as the collection strategy applied. they were presented to the company "xyz" to have an assessment of the information obtained. with this activity, we closed gaps between the company requirements and preliminary results, so it was possible to properly focus the efforts of the research. 44 7. final project scope definition and delimitation of key concepts once we had concluded the initial assessment of information with the company "xyz" it was agreed to limit the research on the specific market of "styrenic block copolymers" emerging as the most attractive area to the company. under this approach the following key intelligent topics were selected:  thermoplastic elastomers  styrene block copolymer  styrene-butadiene-styrene  styrene-isoprene-styrene  hydrogenated styrenic block copolymers 8. information research this process began with a collection in the database isi emerging markets delimiting the searches from year 2009 to year 2012. in total 3600 results were obtained but many of them were not relevant for the project. an exploration in the database datamonitor 360 was made with the same criteria obtaining about 550 results. in the next stage of the project, a segregation of items was made according to specific topics of interest for the company. 9. selection of relevant documents the initial information research resulted in about 4000 documents from both databases: isi emerging markets and datamonitor 360. as many of these results were repeated and valueless for the research, it was necessary to do a selection of the most useful information. for this purpose a segregation of reports, news, and data was made considering particular research axes established by the company in terms of: materials, technologies, final products, and strategic actions (mergers, acquisitions, alliances, etc.). 10. information analysis driving forces analysis technique proposed by fleisher & bensoussan (2007) was applied in this stage. driving forces are elements with the capacity to change the industry structure. this tool was selected as it was the most suitable to get insights requested for the company involved in the study. 11. ic report development once the analysis of the information found in the research was completed, the next step in the process was to develop a ic report with the main findings including recommendations established. 12. dissemination a personal presentation was made to the experts and decision makers at the company “xyz” with the objective of disseminating the findings, conclusions, and recommendations developed. 13. validation of information during the application of the methodology different presentations of the results were made to the company "xyz" in order to guide the research according to the main purpose established. validation of information was made with experts from the company and with external people (industry and academy) maintaining confidentiality of information. 14. decision-making process the final stage of the methodology, the decision-making process is the job of the senior management of company “xyz” as we delivered the recommendations of the ci report. 4. findings of the analysis as it was mentioned before the “driving forces analysis” technique of fleisher & bensoussan (2007) was applied during the analysis stage. an identification of the driving forces for the industry of thermoplastics elastomers was made 45 according to: economic, social and technological factors. here we present some interesting findings (for confidential reasons not all results could be shown): i. economic factors the economic factors of the thermoplastic elastomer industry, in specific sbc were divided into two important points. the first one was the up-to-date market situation including demand and consumption, and the second one was the industry’s competitors. market condition after the recovery from the economic crisis of 2009, sbc consumption in all regions increased, although the rate of growth is slow due to per se market maturity. it is important to point out that the footwear market decline has affected most western europe. on the other hand, china has a growing demand in this industry but at a slower pace (löchne & mori, 2011). the following figure shows the percentage of world consumption of the different classifications of sbc: currently, within the classifications of styrenic block copolymers, the styrene-butadienestyrene (sbs) is the highest category of consumption with a total of 75% of sbc's market share, followed by styrene-isoprene-styrene (sis) with a consumption rate of 15%, and hydrogenated styrenic block copolymers (hsbc) with a 10% share, according to zhang li china national petroleum and chemical planning institute (2011). the demand for the category of hydrogenated styrenic block copolymers (hsbc) which include styreneethylene/butylene-styrene (sebs), styreneethylene/propylene-styrene (seps) and styreneethylene/ethylene-propylene-styrene (seeps), is growing faster than other categories of sbc's, at rates of 8% to 10% in certain regions (nandini consultancy center, 2011). moreover, it is expected that there will be an increment in global consumption of sbc to an average annual rate of about 4.5% during 20102015. in developed regions, consumption will be driven by the use of sbc for the market of adhesives and sealants. in asia (excluding japan) polymers and asphalt modified will drive consumption, as the growth rates for footwear has considerably decreased. on the other hand, central and eastern europe have become an interesting market, the total demand growth is forecasted to be at 8-10% per year until 2015, developing even faster than in china (löchne & mori, 2011). styrenic block copolymers (sbc) competitors currently, 70% of the global production capacity of the sbc market is dominated by key players, in particular:  kraton performance polymers, inc., united states of america.  tsrc corporation, taiwan  lee chang yung, taiwan these companies play a key role in the industry due to their large investments in asia, their manufacturing capacity, and current research on new developments related to hydrogenated styrenic block copolymer (hsbc). 75% 15% 10% global consumption of sbc styrenebutadienestyrene (sbs) block copolymers styreneisoprenestyrene (sis) block copolymers hydrogenated styrenic block copolymers (hsbc) figure 2: distribution of global consumption by classification styrenic block copolymers (compiled from zhang li china national petroleum and chemical planning institute, 2011). 46 recommendations the first recommendation for the company “xyz” is to invest more in research and development, mainly in the hsbc category but considering also: sebs, seps, and seeps. secondly, it is important to carefully analyze the participation of the companies in china, because of the saturation of the market and the overcapacity of their plants up to 50 % (löchne & mori, 2011). for this reason they must consider other developing regions such as eastern europe. central and eastern europe represents an interesting opportunity to explore as their demand has interesting growth which is forecasted at 810% per year until 2015 (löchne & mori, 2011). ii. social factors this section is divided into two major points. first: the sbc's relationship with the natural environment. second: the involvement of the government in the industry. styrenic block copolymers and environment during the 12th five-year development guidelines for the petroleum and chemical industry, one of the main issues that were analyzed was to strengthen the chemical sector on energy saving and environmental protection (changjin, 2012). in this respect a significant trend in the industry of elastomers is one called "green technology". the case of goodyear and its biotred technology in tires is a good example. organic products replace conventional raw materials and the product gets the additional benefit of reduced friction and weight. it is clear that companies in the industry of sbc should not only pay attention to elements such as design, production and operation costs, but they should also follow changes in environmental regulations and pressure from customer groups, as these are demanding products that are more environmental friendly. regulations for handling and disposal in the industry styrenic block copolymers according to changjin (2012), in recent years the chemical and petroleum industry in china has increased concern about environmental issues related to energy consumption, recycling and pollution. china in fact, announced in early 2012 a plan to reduce emissions of carbon dioxide (co2) by 2020 to a level of 40-45% lower than in 2005, which would be the equivalent of saving 670 million metric tons of coal. recommendations it is expected that international regulations become stricter regarding the environment, health, and security issues related to the industry of plastic and petroleum. a recommendation for the company “xyz” is to develop a specific group to manage this issue, trying to anticipate changes in environmental laws. in particular it is important to detect any compound that could produce a negative effect on peoples’ health. iii. technological factors development of new products in the industry styrenic block copolymers during the research one remarkable product we identified was k resin which is a synthetic resin with properties of transparency and high impact resistance. it is a product composed by a copolymer butadiene / styrene with a high content of styrene (70 85%). it has a substantial potential in the medical and food package industry (zhang li china national petroleum and chemical planning institute, 2011). moreover, applications that k resin can have are focused on elaborate food containers, packaging, medical devices, toys, footwear, and household appliances, among others. it is important to remark that construction of production facilities of k resin in china is at an early stage. units with a capacity of 25,000 tons have already been built. the consumption in china of k resin was for 50,000 tons in 2009. china's demand is mainly satisfied by imports as it can only produce locally 20% of its consumption (zhang li china national petroleum and chemical planning institute, 2011). it is 47 expected that the demand in china for k resin reaches 80,000 tons in 2015. this product has a an important market potential. recommendations the company “xyz” should integrate k resin into its business. according to zhang li china national petroleum and chemical planning institute (2011), this is the right time to exploit this product. the demand of k resin is anticipated to grow to 80,000 tons in 2015, and the current capacity in china is not able to satisfy that requirement. finally, it would be interesting to conduct a deep benchmarking process of key competitor's like those mentioned before. 5. conclusions through the application of a competitive intelligence methodology, it was possible to obtain valuable insights into the plastics industry. from the results obtained, it is clear that the industry of styrenic block copolymers is currently growing to develop more specialized products. innovations in adhesives, sealants, medical, and compounds applications are the most prominent areas of development. the company “xyz” should compete with a product differentiation strategy in these categories, rather than high-volume products (commodities) or low cost strategy. it is also important to combine the differentiation strategy with niche strategy, considering in particular the region of eastern europe which market is estimate to grow between 8 and 10% by 2015. in addition, research and development efforts in the styrenic hydrogenated block copolymers (hsbc) represents an interesting opportunity to undertake, provided that the market will grow faster than the other categories of sbc's, at rates of 8% to 10%. finally the company should increase its efforts to be aware of environmental issues, for example it could strengthen its strategies to reduce co2 emissions. references. baregheh, a., rowley, j., & sambrook, s. 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(2010). propuesta de integración de la inteligencia competitiva con la innovación abierta. monterrey: itesm. zhang li china national petroleum and chemical planning institute. (2011). new changes in styrene downstream market opportunities. china chemical reporter , 16-18. vol9no3paper4 to cite this article: palilingan, v.r. and batmetan, j.r. (2019) how competitive intelligence can be used to improve a management vocational high school: a case from indonesia. journal of intelligence studies in business. 9 (3) 56-61. article url: https://ojs.hh.se/index.php/jisib/article/view/477 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index how competitive intelligence can be used to improve a management vocational high school: a case from indonesia verry ronny palilingana and johan reimon batmetana* ainformation technology and communication education department, universitas negeri manado, indonesia; *john.reimon@unima.ac.id journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: empirical evidence from a connectivist competitive intelligence massive open online course (ci cmooc) proof of concept competitive intelligence as a game changer for africa’s competitiveness in the global economy alexander maune pp. 24-38 integration of textual voc into a cx data model for business intelligence use in b2c lucie sperkova pp. 39-55 how competitive intelligence can be used to improve a management vocational high school: a case from indonesia verry ronny pailingan and pp. 56-61 johan reimon batmetan journal of intelligence studies in business v ol9,n o 3,2019 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 9,no.3,2019 gianita bleoju, alexandru capatina,valter pp. 7-23 vairinhos, rozalia nistor, and nicolas lesca effect of competitive intelligence on innovation capability: an exploratory study in mexican companie eduardo rafael poblano-ojinaga pp. 62-67 how competitive intelligence can be used to improve a management vocational high school: a case from indonesia verry ronny pailingana and johan reimon batmetana* ainformation technology and communication education department, universitas negeri manado, indonesia *corresponding author: john.reimon@unima.ac.id received 8 december 2019 accepted 30 december 2019 abstract vocational high school needs professional management in order to increase competitiveness. this requires easy, efficient and comprehensive management techniques to maximize potential. the purpose of this study is to improve vocational high school competitiveness by applying competitive intelligence methods. this study uses competitive intelligence methods that are divided into two steps: the competitive intelligence circle in formulating problems and the competitive framework of intelligence as a management model. the results of this study show that problems can be mapped using different competitive intelligence tools. the use of a competitive intelligence framework produces a prime management model and strategies. this applied framework enhances the competitiveness of the vocational high school in our case. keywords competitive intelligence, management, vocational high school 1. introduction vocational high schools are primary producers of workers in developing countries. this skilled labor industry is needed in developing countries to supply laborers for industries and other sectors that need skilled labor. schools should produce professionals that are instructed by teachers who are professionals in their fields [1]. it takes a superior vocational high school to realize this goal, which shows it is a quality school. the characteristics of quality are high competitiveness and strong competitive advantage. another feature is that vocational high schools can provide public education and training services for students. the indonesia central bureau of statistics shows that there are 13.68 million people, making up 11.03% of the skilled workforce, that came from vocational high schools in 2018 [2]. the data are an increase from the 2017 numbers, which show only 10.40% of the workforce came from these schools. the majority of graduates from vocational high schools work as employees at a company (49.23%), 23.62% are self-employed, and the rest are in other jobs. based on the field of work, the majority of workers (56.84%) work in the informal sector. on the income side, the average vocational high school graduate receives a wage of idr 2.23 million. this shows that the majority of vocational high school graduates do not work in relevant jobs and are instead working according to the opportunities available at that time. the unemployment rate in 2018 is dominated by vocational high school graduates, making up 11.24% of the 7 million people who are unemployed nationally in indonesia [3]. these data indicate that the competitiveness of vocational high schools is journal of intelligence studies in business vol. 9, no. 3 (2019) pp. 56-61 open access: freely available at: https://ojs.hh.se/ 57 still low in order to be able to compete in the fields studied at the school. a school management model is needed which is directed at increasing competitiveness [4]. good managerial skills influence schools in managing their resources and opening up opportunities for stakeholders. technology will make schools more competitive [5]. this management is not only limited to the school curriculum and human resources available, but also complete and massive complete management. this study aims to improve the competitiveness of vocational high schools and is supported by applying competitive intelligence. this research is expected to produce a way to improve the competitiveness of vocational schools that are significant and able to improve the management of vocational secondary schools professionally. 2. literatur review competitive intelligence encourages competition to utilize all the resources needed to win the competition by paying attention to its competitors [6]. related to that, competitiveness can be increased by overcoming the shortcomings raised and being prepared for each challenge that arises. in order to be more competitive, you can also use other competitive model tools [7]. institutions can use information technology to build strength and take advantage of the opportunities they have [8]. information technology support enables vocational schools to reach an agreement and increase competitiveness. technology has become a driving force for vocational high schools that provide high-quality training [9]. information technology can be used as the main enabler for all business processes that it has. information technology has encouraged vocational secondary schools in a fast and unlimited era of globalization [10]. there is support for information technology as an enabler, a finding that can be achieved in a way that is easily obtained from the results, with highly competitive power in accordance with industry and society. the competitive method of intelligence with the support of information technology will produce quality graduates. therefore, vocational high schools needs to make improvements in terms of professional human resources [11], reliable management, quality teaching and learning activities, access to quality domestic and foreign higher education institutions and the availability of equal facilities with international standard education [12]. the increasingly difficult challenge in the world of education, especially for planning and management, education policymakers, is that, in this case, the government must have a tool or device to evaluate the extent to which education development, especially the performance of educational services for the community can be achieved [13]. the best way to ensure an organization (school) has the durability and viability of the present and sustainability in the future is to create a new strategy using several analyses, such as swot analysis, potter five force analysis, key of success analysis or analysis patent. a swot analysis of factors determines all systematic factors to formulate organizational strategies for both business enterprises and social organizations [14]. strength analysis can maximize strength (opportunity), opportunity (weakness) and weakness (threat). strategic decision-making processes consider the vision, mission, goals, and policies of an organization. thus the strategic planner (strategic factor) must analyze the organizational strategy factors (strengths, weaknesses, opportunities, and threats) in the current conditions [15]. five forces porter’s analysis is a simple but very useful tool for where the strength of our company lies in competition in the business world [16]. by using this five strength analysis, we can find the current competitive position and position competition in businesses that are fighting. the key success factor (ksf) was the implication of the process of matching the company, which was used to support the company's internal factors. the ksf has the potential to gain a competitive advantage in a particular industry, especially in matters that figure 1 competitive intelligence method. 58 are important for companies and who challenge successful companies [17]. analysis of intellectual property rights (ipr) is divided into two types: copyright and industrial property rights. based on indonesian law number 19 of 2002 concerning copyright, copyright is the exclusive right for the creator or the right to announce or reproduce work permissions for it by not allowing it to improve with the regulations requested [16]. industrial property rights are based on patents, brands, industrial designs, layout designs of integrated circuits, trade secrets, and plant varieties. 3. method this research was conducted by collecting formal and informal data. formal data is obtained from various scientific sources such as school performance reports, scientific journals, and books. informal data is obtained from various observations of the institution, surveys, and interviews with respondents. this data collection contains human resources, learning methods, achievements, financial data, and school curriculum data. data is collected from direct observation and interviews with school principals, teachers, students, and school administrators. the method of research is a competitive intelligence method which is divided into two main steps: a competitive intelligence circle in formulating the problem and an intelligence framework as a management model. this study uses swot analysis to produce a competitiveness strategy, and the researchers used competitive intelligence analysis techniques as shown in figure 1. competitive intelligence methods start with the question of how the company vision can be realized with the best strategy. thus the three basic questions are asked, namely: where are we now? where do we want to go? and how do we get there? the competitive intelligence method will formulate a four-step company strategy as shown in figure 1. the first step is to gather information from various sources, both formal and informal. the second step is management. the information should be managed successfully in the form of databases and intranets so that it is easy to analyze. the third step is analysis. the information is analyzed both automatically and manually with various tools available. the result of this process is a strategy. the fourth step, is to understand. the results of the analysis are then extracted into a strategy that will be applied as a way to increase competitiveness. the results of the strategy are then recommended to the cio and top executives as a strategy that will be implemented to achieve the company's vision. 4. result and disscusion 4.1 profile: indonesian vocational high schools the average vocational high school vision covers a certain period of time. in the vocational high schools that were sampled, they have a vision of "being a faithful vocational secondary school, being honest, courteous, intelligent, cultured, achieving, disciplined, diligent, nationalist and holding on to pancasila and the 1945 constitution". this vision is still difficult to realize. while its mission is, 1) educate and train students to be safe and polite, 2) educate and train students to be smart and trained in the fields of nursing, pharmacy, automotive, and graphics preparation, 3) educate, train and encourage students to be able to perform according to competence, 4) educate and train students so that they can be diligent, faithful, national, based on the pancasila and the 1945 constitution. vocational high schools require buildings, facilities, teachers, administrative staff, and all students need to be improved and developed. the location is supportive to improve the learning process. schools have a principal, deputy principal, teachers, employees, students and also school guards/security guards. the conditions for productive learning are sufficient to carry out vocational learning. the learning process uses guidelines that are in accordance with the governmentdetermined curriculum. there are two curricula that are applied in vocational high schools: the 2013 curriculum for class x and ktsp 2006 for class xi & class xii. the school curriculum is a series of activities arranged in accordance with the needs of the school carried out in vocational high schools. the curriculum includes the division of teachers’ tasks, preparation of lesson schedules, preparation of learning units, preparation of kbm tools, implementing the teaching learning process (kbm) and evaluation. second, extracurricular programs include: homework (development of learning materials), sports and competitions, line training, worship, regional arts training, skills, arts and scouts. this has an impact on students because 59 students no longer accept material that can be understood. financial requirements are met as all vocational secondary schools receive funding from the government in accordance with the number of students approved at the school. in addition, sources can also be obtained from subcommittee payments with fees determined by the school. from these various sources, vocational secondary schools are able to finance all costs obtained in school management. the school is able to manage various things to realize its vision, be able to survive and be able to compete well. 4.2 swot analysis of vocational high schools swot analysis is used as a basis for discussing work strategies and programs. an assessment of the factors of strength (weakness) and weakness (weakness). meanwhile, external analysis limits opportunities (challenges) and challenges (threats). there are two types of information that are equipped with boxes, namely the top two are external factor boxes (opportunities and challenges). the two adjoining boxes are internal factors (strength and weakness). the other four boxes are boxes of strategic issues that emerge as a result of points related to internal and external factors (figure 2). table 1 result of the swot analysis of a vocational high school. external factor internal factor opportunity 1. local government assistance in completing facilities & infrastructure 2. demands from the surrounding community for a quality collection 3. parental support 4. get support from bos funds from the government threat 1. similar educational institutions 2. progress on health & automotive technology 3. competition to enter vocational school strength 1. having a student teacher who is confirmed and obeyed by students 2. the motivation of teachers & students 3. student's scare, they still have a good relationship with the teacher 4. the learning process is done adjusting to the circumstances & willingness of students strategy strengthopportunity 1. continue to motivate teachers & students in teaching and learning with government support in completing infrastructure facilities 2. doing learning for students by applying interesting learning methods and having optimal learning outcomes. strategy strength-threat work to improve what must be the best in all fields, both teachers and students in the context of competition with other schools weakness 1. the salary of the teaching staff is too small 2. does not have complete learning facilities 3. does not have complete laboratory facilities 4. most teaching staff cannot overcome student delinquency 5. there is a no teacher acceptance test 6. there is a no student acceptance test 7. only 1 teacher is a civil servant, the rest are honorary teachers 8. most teaching staff are not in accordance with teaching time 9. school buildings need a lot of improvement 10. school equipment is old and needs to be replaced strategy weaknessopportunity 1. increase the wages of the teaching staff, so that the teaching staff will become more professional and succeed maximally by using government assistance 2. replacing & repairing school equipment with government assistance 3. facilitating laboratories with government assistance 4. trust 1 staff for school finance 5. utilizing improvement support with joint service work to improve the school building 6. submit requests to the government to procure qualified teaching staff strategy weakness-threat 1. receiving teaching staff by conducting tests according to their respective fields, especially teaching the staff of productive subjects 2. accept students' test so that each student enters guaranteed quality and character 3. conduct special training for teaching staff 4. conduct character coaching for students 5. conduct a joint evaluation every week to discuss learning methods & integration of teaching staff as well as everyone involved in the school figure 2 matrix swot kearns. in figure 2, cell a is the comparative advantage where you can develop faster. cell b is mobilization, where the cell is the interaction between threat and strength. here, resource mobilization must be carried out, which is the strength of the organization to be the threat from outside, the event then turning the challenge into an opportunity. cell c is divestment/ investment. this cell is an opportunity between organizational weaknesses and opportunities from outside. a situation like this provides an option for an escape location. the opportunities available are guaranteed but cannot be used because of insufficient strength. the choice of a decision taken is issuing opportunities available for other organizations to use or forcing them to work on opportunities (investment). finally, cell d is control damage, this is the weakest condition of all cells because it is a meeting between the weaknesses and the resolution of decisions that will bring a great disaster to the organization. the strategy of returning losses is so that it doesn't become more severe than expected. the results of swot analyses are possessed by vocational high schools. on the external side, there are many opportunities that can be maximized by vocational secondary schools, but there must also be questions about the challenges that arise in competition (table 1). some of the strong strategies that need to be built in vocational high schools are conducting innovative learning using various projectbased learning methods, based on problems, learning to find discoveries and other students who take more and increase higher interest. a targeted apprenticeship program and appropriate scientific competition can also be applied in the step of increasing the competitiveness of secondary school graduates. the internal strategy that can be applied is the improvement of visionary leadership patterns and strong and resilient managerial capabilities. vocational secondary school is supported by leaders who drive competition, develop good technology, have strong leadership abilities and are able to move all the components in front. calculated strategies can maximize organizational strength. in addition, organizations also need special attention. calculated strategies are needed to reduce and overcome organizational weaknesses. for example, a strategy to get new students who are qualified and meet basic standards for vocational school students is needed. external-based strategies must be built on the strengths of the organization. vocational high schools must formulate strategies to take advantage of their competitors. this strategy must be solved by considering the strategies that can be generated after making a strategy. continuous evaluation is needed to develop a strategy that is sustainable over a long period of time. vocational high schools need to carry out strategies to implement sustainable service improvements for the provision of quality services available in the long term. the strategies needed for invitation requirements arise. this threat can come from other competitors, regulatory changes and social events phenomena that arise in the community. this is a strategy to anticipate. one strategy that can be applied is to increase the human resources needed. competent human resources can significantly improve the competitiveness of secondary schools so they are able to compete with various challenges. 5. conclusion strong competitiveness can be built with strategies that are good and feasible to implement. competitive intelligence techniques are proven to be able to significantly improve the competitiveness of vocational high schools, in our case from indonesia. the application of competitive intelligence can formulate various strategies for managing vocational secondary schools that can be applied by utilizing various strengths they have and utilizing opportunities that are available and fast ways to produce competitive work. minimizing weakness 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(2021) nexus between strategic thinking, competitive intelligence and innovation capability: managerial support as a moderator. journal of intelligence studies in business. 11 (3) 27-41. issue url: https://ojs.hh.se/index.php/jisib/article/view/jisib vol 11 nr 3 2021 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index nexus between strategic thinking, competitive intelligence and innovation capability: managerial support as a moderator banji rildwan olaleyea,*, mustapha bojuwonb, raed ibrahim mohamad ibrahima, betty oluwayemisi alimomohb adepartment of business management, faculty of business & economics, girne american university, north cyprus, turkey; bdepartment of accounting, faculty of management science, federal university oye-ekiti, nigeria; *banji.olaar@gmail.com journal of intelligence studies in business please scroll down for article nexus between strategic thinking, competitive intelligence and innovation capability: managerial support as a moderator banji rildwan olaleyea,*, mustapha bojuwonb, raed ibrahim mohamad ibrahima, betty oluwayemisi ali-momohb adepartment of business management, faculty of business & economics, girne american university, north cyprus, turkey; bdepartment of accounting, faculty of management science, federal university oye-ekiti, nigeria *corresponding author: banji.olaar@gmail.com received 24 november 2021 accepted 25 december 2021 abstract in a rapidly changing milieus, great support for innovation by top management team allows firms to sustain high market competitiveness both in the present and in the future. in actualizing this pursuit, strategic thinking and competitive intelligence are seen as drivers for innovation capability. this study investigates the nature of relationships between competitive intelligence, strategic thinking, and innovation capability. it also explores the moderating role of managerial support on these associations. in this study, a sample of 327 top and middle-level managers’ responses to a survey was obtained from nigerian information technology firms, using a judgmental sampling technique. the data were analyzed with partial least square structural equation modeling (pls-sem), using the smartpls software. the findings revealed that competitive intelligence and strategic thinking have an imperative direct and positive impact on innovation capability, and managerial support impacted positively, by meaningfully strengthening the relationships within the nigeria context. the study mades significant contributions to the literature in terms of model development, which depicts the joint influence of competitive intelligence and strategic thinking with a moderating effect of managerial support. if deficient, this may result in inefficiency in achieving innovation capability among it firms. keywords competitive intelligence, innovation capability, managerial support, pls-sem, strategic thinking 1. introduction in today’s innovation-driven economy, understanding how to generate prodigious ideas is a pressing managerial priority. initiating innovations is mostly a task handled by senior managers within an organization. strategic thinking (st) and competitive intelligence (ci) are used in creating novel and rational decisions relating to the past, present, and future, in areas of value addition and overall performance. strategy aids the discovery and execution of novel ways of stimulating innovation capacity and sustaining competitiveness. in an intricate, widespread competitive environment, the uncertainty and turbulence of the contemporary world of business demands that organizational leaders and managers think strategically by responding to changes and developing an innovative model for business survival and sustainability (haycock, 2012). st and action have become increasingly journal of intelligence studies in business vol. 11, no. 3 (2021) pp. 27-41 open access: freely available at: https://ojs.hh.se/ 28 important within a new global environment, in which successful leadership requires a vision (bouhali, mekdad, lebsirc and ferkhad, 2015). st is among the expertise needed by managers. if it is not applied, there is a missing link in a business’s performance (srivastava and d’souza, 2019; emereole and okafor, 2019; bonn, 2001). st is a modern and fundamental strategic management tool used in handling, forestalling, and proffering solutions to corporate challenges (kettunen et al., 2020; nickols, 2016). it can also be seen as the ability to examine and analyze the organizational external and internal environment, by foreseeing future opportunities and risks, as well as formulating alternatives and possibilities. it thereby organizes programs by absorbing opportunities and preventing risks (olaleye et al., 2021; hunitie, 2018). in addition, st can also help a firm in discovering new strategies that can help in shaping competitive strategies (dixit, singh, dhir, and dhir, 2021) meanwhile, ci is a corporate strategy that assists firms in the managerial course of increasing performance via enhanced knowledge, internal communications, and strategic plans quality. the society of competitive intelligence professionals (scip, 2009) defines ci as a systematic and ethical program for gathering, analyzing, and managing any combination of data, information, and knowledge vis-à-vis the business milieu in which a company functions, and accommodates a substantial competitive advantage and enabling profiting decisions. ci's real value is to provide managers with the organizational tool to learn what the competitor will do, not what the competitor has already done. innovation capability is the “firms’ ability to absorb, adapt and transform a given technology into specific operational, managerial and transactional routines that can lead to a schumpeterian profit, that is, innovation” (zawislak et al., 2012). consequentially, innovation accrued benefits from intelligence processes, accrued to newlyprovided knowledge, recognized novel opportunities, and enlarged technological paths of the external environment (cainelli et al., 2019). among existing firms, innovation performs vital roles as it strategically strengthens the technology-based prospect of the enterprise, with the sole aim of evolving and taming new products and processes. innovation is delineated as the espousal of ideas or conduct that is novel to an organization (olaleye et al., 2021; daft, 1978; damanpour & evan, 1984). innovativeness is a procedural launching, with idea generation and development, towards extemporizing new products, services, and processes (olaleye et al, 2020; ainul, hasliza & noor, 2015; bates & khasawneh, 2005). all types of organizations are incapacitated with innovation, irrespective of their sizes since it is proven that innovative organizations tend to realize higher profits and market share (prajogo & ahmed, 2006). hence, innovation capability (inc) is a firms’ fundamental strategic asset to sustain competitive advantage (ponta et al., 2020). various studies have examined st as an antecedent (kula and naktiyok, 2021; olaleye et al., 2020; adelekan, 2020; emereole and okafor, 2019; ibrahim and elumah, 2016; zahra and nambisan, 2012), while few studies have analyzed the role of st as a mediator or moderator (bani-hani, 2021; alqershi et al, 2021; fahmi et al., 2020) and even fewer studies have examined the impact of st on inc (rastgar, arefi, and hizji, 2017). equally, studies have examined the role of ci on competitive advantage (dixit et al., 2021), bani-hani, 2021), organizational performance (irenaus, ikechukwu & ndubuisi, 2021), innovativeness (olaleye et al., 2020; hussein, farzaneh, & amiri, 2011), innovation performance (poblano-ojinaga, 2021; caloof and sewdass, 2020) and strategic human resource management (alomari, 2020). in response to gaps in research, this study proposes a new model on connection linking st and ci to nigerian it firms’ innovation capacity. since the joint connection between st, ci, and firms’ inc is yet to be widely investigated, the study will attest to situational strengths that affects the relationship of the variables, and equally, add the moderating effect of managerial support (mgs) to the framework. following the prior discussions, this study attempts to answer the following research questions: rq1. does st impact inc among it firms? rq2: does ci impact inc among it firms? rq3: does mgs moderate these relationships? 2. theoretical background and hypotheses development 29 2.1 strategic thinking and innovation capability strategic thinking is a crucial module in the change management process, where alternate strategic methods are combined, bearing in mind vital decisions on the organizational value-creating process. bonn (2001), stated that st is seen as the cognitive process, preceding designing of strategies, whereby an individual contemplates organizational longrun developments, considering its historical and extant qualities, and the external veracities of its operations. alqershi et al. (2021), defined st as the “organization’s ability to create and develop a strategic vision by exploring all potential future organizational events and challenging traditional thinking to promote sound decisionmaking in record time”. nuntamanop et al. (2013), described st as managerial required competency comprising conceptual thinking, visionary thinking, creativity, analytical thinking, learning, synthesizing, and objectivity. garratt (2003), cited st as an organizational procedure established by executives in meeting daily contests of managing and providing cogent alternatives into a dynamic business environment in actualizing managerial efficiency. st is an inevitable capacity procedure to support managers in evolving better strategies and inspiring employees to collaborate in innovative tactics which aid a firm’s survival (olaleye et al., 2020). also, st is a process that encourages creative and innovative thinking to overcome the dynamic and often unpredictable difficulties encountered in today’s economy (haycock, cheadle & bluestone, 2012; kula and naktiyok, 2021). st helps businesses to understand the present and be prepared for the future through scenario planning. thus, it harmonizes various premises related to the future, which might be challenging. st can offer innovative solutions to complex problems in a turbulent and hypercompetitive environment, which has the potential to change the rules of the competition and depict the future (zahra and nambisan, 2012). st can be described as a dynamic and innovationoriented process, which aids in developing a clearer vision for managers, while responding to external changes. therefore, decisions led by st are expected to be creative, original, and change the rules in the competitive game (heracleous, 1998; tovstiga, 2013). as such, st often requires reconciling competing premises about the future and the integration of differing views into a coherent unit. this integration requires creativity and intelligence. nowadays, st should not be assigned solely to top-level managers, since some inventions are traceable to middle and lower-level managers, as well as employees who relate with customers, suppliers, and other stakeholders. since st is viewed as a synthesizing activity that can be integrated into the formal organizational strategic planning process, it is developed in individuals across all levels of an organization. emereole and okafor (2019) conducted a study on the impact of st using strategic planning as a proxy on organizational effectiveness, as well as examining the effect of strategic leadership on organizational performance. this study centered on the telecommunication industry, where 64 employees were questioned. the chi-square result showed a tie between strategic planning and organization effectiveness at 0.05 significant level. however, it was concluded that strategic leadership has a significant and positive effect on organizational performance, indiciating that organizations needed to define their visions when engaging in the st process. olaleye et al. (2020), explored the mediating role of absorptive capabilities on the relationship between st and innovation performance of it firms in nigeria. 182 seniorlevel and mid-level managers were questioned, and pragmatic evidence revealed that top-level managers in the it industry in nigeria are familiar with and implement st. this enables them to understand the dynamic nature of firms in this ever-changing business era. however, it was concluded that improved innovative performance is attributable to st competency among it firms but the mediating role of absorptive capabilities was insignificant. ibrahim & elumah (2016), examined the effect of st on firm performance within nigeria’s business milieu. data was analyzed and it was found that a positive relationship exists between st and firm performance, whereby managers were expected to be thinking strategically in order to obtain a large market share or competitive advantage in the market. therefore, the study presents the following hypothesis: h01: strategic thinking is assumed to have a positive influence on innovation capability 30 2.2 competitive intelligence and innovation capability in designing a strategy of recognizing emerging trends and sustaining competitive advantage over rivals, the development of ci is a key management tool for corporate chief executives and policymakers. it is necessitated in the system, which tends to provide companies with new ideas in predicting the future, and also accepting changes more readily. thus, due to increased competition, competitor intelligence has become a valuable analytical tool in the strategic planning process. ci is defined as actionable recommendations arising from a systematic process, involving planning, gathering, analyzing, and disseminating information on the external environment for opportunities, or developments that have the potential to affect a company’s or country’s competitive situation (calof and skinner, 1999). ci focused primarily on how to understand the surrounding competitive environmental impacts on organizations, by gathering information to make relevant and better decisions (maune, 2020). hence, ci enables managers in companies of all sizes to make decisions on marketing, research, investments, and longterm business strategies. ci assists businesses in numerous ways, ranging from the creation of new concepts, products, opportunities, and markets, as well as the positioning and launching of new products, processes, or services. it also includes the generation of new ideas, the tracking of trends, mergers, and acquisitions and the formulation of strategies. meanwhile, this conforms to a study conducted in iran on the effect of ci on innovativeness, which revealed that ci usage leads to innovation and organizational survival (hussein, farzaneh, & amiri, 2011). this finding is also corroborated by a study on small establishments in canada, showing a clear relationship between ci usage and innovative performance (tanev & bailetti, 2008). caloof and sewdass (2020) explained that among studies conducted on ci and innovation, theoretical studies surpass empirical studies. they explored literature using a review approach that established significant relationships between various ci processes and structure variables, mostly related to innovation. from this, researchers were guided to conduct future work on causal statistical approaches to this relationship. rastgar et al. (2017) used questionnaires for the first time in measuring organizational innovation in iran based on a survey made by the organization for economic co-operation and development (oecd). results depicted those features of ci on organizational innovation. st has also been effective as a mediator in 66 percent of their relationships. it is well established within management practice and among relevant scholarly communities that ci is a skillset crucial to the success of organizations and individuals (olaleye et al., 2021; michaeli and simon, 2008; global intelligence alliance, 2007a; wright et al., 2002). furthermore, irenaus, ikechukwu, and ndubuisi (2021) researched ci and organizational performance among smes in the southeast of nigeria. the degree of the relationship between technology intelligence, strategic partnership, market intelligence, and financial performance indicators such as return on investment, return on sales, and market share was examined with a sample size of 318. all the hypotheses they tested had a positive significance on financial performance, and a recommendation was put forward that all employees should have rudimentary values and an understanding of ci. tanev and bailetti (2008), focused on the nexus between intelligence activities and innovation in technology firms and concluded that ci results in the creation of innovativeness in small businesses. both small and large organizations in the western hemisphere and east asia deeply applied ci as a basis for competitive advantage and innovativeness (adidam, banerjee, & shukla, 2012; smith & kossou, 2008; wright, 2011). a review by hussein, farzaneh, & amiri (2011) showed a positive relationship between ci and innovative performance. consequently, on the assumption of understanding ci's role in promoting inc, the following hypothesis is proposed: h02: competitive intelligence positively influences innovation capability 2.3 moderating role of managerial support and innovation capability managerial support is viewed as a commitment from organization administrators, considering some pressing and uncontrollable circumstances of their employees that require attention towards their development in achieving better performance. it can also be 31 defined as “the degree to which employees form general impressions that their managers appreciate their contributions, are supportive, and care about their subordinates’ well-being” (eisenberger, stinglhamber, vandenberghe, sucharski and rhoades 2002). nowadays, business administrators categorially put in place ci activities, whether performed formally or not. ci could be viewed as either a process or a product, which is acquainted with creating innovation of any manner. meanwhile, firms with welldeveloped innovation capabilities stand a better chance to sustain their competitiveness. additionally, managers who have st skills need the information to interpret the dynamics of the competition correctly, to predict their competitive positions, and to determine their competitive positions correctly. these innovative ideas make them distinct. innovation in it inventions has immensely contributed to the enhancement of organizational performance and the feat of competitive advantage for organizations within developed and developing countries (niebel, 2018). besides the dissimilar needs of studies, factors elucidating the creation and development of innovation capacities could be common, but their relative importance is inconclusive. ci is less frequently applied due to its newness. it is strategically focused, requiring an expertise role in reducing its prevalent usage by top-level managers. ci is considered an imperative based on its positive impact on the economic environment, to retain its continuous flow of innovations and technological advances in exercising pressure on all competitors (fagerberg & srholec, 2008). in a study conducted by kula and naktiyok (2021), the impact of st skills on ci by executives was examined. the idea of st epitomizes a knowledge of st dimensions: system thinking, creativity, and vision dimensions. in contrast, ci was evaluated based on its context and process. data were obtained from 628 executives from the automotive and communication industries. based on the results, st has a positive and significant effect on ci. hence, the study greatly contributes to the literature on the connection between ideas of strategy and competition through the interaction of st and ci. however, studies in the literature do not address if managerial support plays a moderating role in the relationship between st, ci, and inc. therefore, the following hypotheses are proposed: h3a: the relationship between strategic thinking and innovation capability is positively moderated through management support h3b: the relationship between competitive intelligence and innovation capability is positively moderated through management support a research model for all testable hypotheses stated above is depicted in figure 1. figure 1 research model. 32 3. methodology 3.1 study area, research design, population, and sample size this study centered on nigerian it firms, since the sector has promising contributions to the nations’ gdp, as declared by the federal government of nigeria (pantanmi, 2021). it companies were assembled using the directory of recognized sectoral and national bodies including: the nigeria computer society (ncs), the information technology association of nigeria (itan), and the national it development agency (nitda). the study involved a quantitative cross-sectional research design. all-inclusive information and understanding regarding the prevailing subject of discourse was elicited from ceos and senior managers occupying top and midlevel managerial positions in the it firms, using a well-structured instrument adapted from the extant literature. a combined nonprobability sampling technique using purposive and convenience was used since the criteria for selecting sample units and participants was already known. the study proposed a sample size of 260 for a population of 800, using the program g*power, version 3.1.9.2, with an error probability of 0.05 (faul et al., 2009). 3.2 measures inc encompasses a firms’ skills, knowledge, and procedures to transform identified knowledge into technology and business (zawislak et al., 2012). a five items scale was adopted from robledo et al. (2010) and lugones et al., (2007). st was captured using a ten items scale derived from three dimensions: system thinking, divergent thought, and reflection (liedtka, 1998 and napier and albert, 1990). meanwhile, ci and management support were modeled and captured with seven and five items, respectively (stefanikova et al., 2015; dishman and calof, 2008; allen and meyer, 1990). responses to all items were measured on a five-point likert scale ranging from 1 “strongly disagree” to 5 “strongly agree”. 3.3 data analysis the analytical procedure deployed in this study comprises both descriptive and inferential statistics. spss was used in describing the sample population frame in terms of frequencies and percentages. the proposed structural model was subjected to strings of psychometric and multi-collinearity tests, with confirmation by the partial least square structural equation modeling (pls-sem) using smartpls version 3.0. significance levels and their path coefficients were examined using the bootstrapping method. 4. results 4.1 response rate and descriptive analysis out of 800 surveys administered within 16 months, 401 were returned, 74 responses were deleted, while 327 were valid for the study, implying a 40.8 percent response rate. descriptive statistics described the socioeconomic characteristics of the respondents, and also defined whether or not the selected respondents are appropriate for the study. table 1 demographic profile of the respondents. source: computations from survey data, 2020. demographics parameters sample (n=327) frequency percentage gender male 214 65.4 female 113 34.6 educational qualification working experience job position bachelor 106 32.4 masters (mba/mpa/msc) 193 59.0 doctorate 28 8.6 below 5 years 5-10 years above 10 years chief executive officer (ceo) director supervisor 41 129 157 211 67 49 12.5 39.5 48.0 64.5 20.5 15.0 33 table 2 measurement model. note: *** = p < 0.01. –* discarded items during confirmatory factor analysis. constructs and indicators loadings (λ) mean std. deviation skewness kurtosis competitive intelligence ci1 0.825*** 3.548 0.836 -0.411 -0.478 ci2 0.820*** 3.469 0.816 -0.275 -0.387 ci3 0.815*** 3.557 0.880 -0.590 0.274 ci4 0.828*** 3.648 0.806 -0.388 -0.094 ci5 0.807*** 3.622 0.825 -0.362 -0.368 ci6 ci7 strategic thinking system thinking st1 0.819*** 3.598 1.075 -0.655 -0.407 st2 0.824*** 3.660 1.219 -0.507 -0.899 st3 0.857*** 3.557 1.286 -0.476 -0.973 st4 0.868*** 3.648 1.164 -0.642 -0.502 divergent thought dt1 0.876*** 3.469 1.183 -0.311 -0.919 dt2 0.876*** 3.768 1.084 -0.667 -0.238 dt3 0.821*** 3.712 0.993 -0.644 0.167 reflection rx1 0.841*** 3.331 0.866 -0.070 -0.435 rx2 0.867*** 3.455 1.031 -0.401 -0.655 rx3 0.840*** 3.481 1.035 -0.587 -0.266 managerial support ms1 0.889*** 4.012 1.149 -0.932 -0.251 ms2 0.888*** 3.669 1.178 -0.522 -0.763 ms3 0.818*** 4.076 0.984 -0.970 0.202 ms4 ms5 innovation performance inc1 0.784*** 3.349 1.063 -0.130 -0.879 inc2 0.841*** 3.243 0.936 -0.072 -0.735 inc3 0.806*** 3.543 0.979 -0.695 -0.106 inc4 0.809*** 3.208 1.028 -0.247 -0.764 inc5 the study sample comprises 327 top-level and middle-level managers of it firms in nigeria. out of this sample, male respondents accounted for 65.4% of total responses obtained, while 34.6% are female, this indicates that there is gender equality among it firms’ administration in nigeria. distribution based on academic qualification evidenced that majority (59%) possess a master’s degree, closely followed by those with bachelor certificate (32.4%) and the least were those with their doctorate (8.6%). on average, the majority of the respondents are highly knowledgeable and experienced with 48% having served for more than 10 years, next was 5-10 years with 39.5%, and the least proportion (12.5%) had less than 5 years of experice. finally, the job position indicates that 64.5% are the ceos (sole owners), closely followed by 20.5% occupying the position of director and the lowest number (15%), employed as supervisors. 4.2 measurement model the results of the measurement model are presented in table 2, using the partial least square structural equation modeling (plssem) to the evaluation of the psychometric properties of the constructs: st, ci, managerial support, and inc. in assessing the measurement model as hypothesized, all constructs associated with latent variables are subjected to a psychometric test. the test entails the outer loadings, average variance extracted (ave), composite reliability (cr), cronbach’s alpha (ca), rho_a values, and convergent validity of items related to their constructs (hair et al. 2017). to improve the best model fit indices, scale items with poor loadings below 0.4 were deleted. this included one item from inc, and two items each from ci and ms. thereafter, all retained items documented outer loadings above 0.5, as suggested by lin & wang (2012), while values of cr, ca, and rho_a exceed the 34 0.7 threshold. this affirms the presence of convergent validity in the measurement model (dijkstra & henseler 2015). since all the aves are above the threshold, the entire measurement shows an acceptable fit and high predictive power. the discriminant validity among the variables is also recognized following the fornell-larcker criterion (1981), the square root of ave (represented diagonally in bold format) for each latent variable is higher than the inter-construct correlation for each construct in the measurement model depicted in table 3. furthermore, critiques made on the reliability of fornell-larcker’s (1981) criterion led to the alternative proposed technique, the heterotrait-monotrait (htmt) ratio of correlations to demonstrate its superiority over the fornell and larcker (1981) approach (henseler et al., 2015). as observed in the table, the htmt values shown in italics right above the square roots of ave in diagonal that all the constructs in our measurement model are below the thresholds of 0.9, as recommended by kline (2005). this affirms a definite discriminant validity existence among variables in our model. 4.3 structural model assessment in assessing the hypothesized relationship between constructs as depicted in the model in figure 2, r-squared values, the beta (β) coefficients, and t-values obtained from bootstrapping using 2,000 subsamples and effect sizes (f2) are being examined as recommended by hair et al. (2019). firstly, the direct effect of the predictor on the dependent variable is analyzed and the result showed that st had a positive effect on inc (β = 0.231; t = 2.771). it also proved the second hypothesis is significant, showing that ci positively influences inc (β = 0.366; t = 7.085). to test the moderation effect contained in hypothesis three, the result of the moderation analysis shows that ms positively moderate the relationship between st and inc (β = 0.155, t=3.002, p< .001), likewise, the path between ci and inc (β = 0.123; t = 2.442). however, all hypothesized paths in the study model are supported and the coefficient of determination (r-squared) shows the combined effects of exogenous latent variables were considered to be moderate with an r2 value of 0.310. subsequently, to observe the beta coefficients (β), statistical significance (p-value), and variance explained (r2), sullivan & feinn (2012), recommend that the substantive significance (f2), be reported to reveal the actual magnitude of the observed effects. the effect sizes of the direct and indirect paths are recorded in table 4. relying on the magnitude of effect sizes, three paths including the moderating path (str→inc; mod_ms*str→inc; mod_ms*ci→inc) recorded low effect sizes, since the f2 fell within the limit of 0.02 0.15 as suggested by cohen (1988), while the effect size of ci on inc was moderate (f2= 0.173), hence none had insignificant magnitude. considering the overall goodness-of-fit (gof), which can be accessed via tests of model fit or the use of fit indices, indicators like the srmr and normal fit index (nfi) become significant, if the srmr is less than 0.08 and nfi fell within the range of 0 and 1. hence, the study model is said to be statistically fit (srmr= 0.072; nfi = 0.907) as evidenced by henseler, hubona, and ray (2016). table 3 inter-construct correlations, convergent and discriminant validity. notes: a= diagonal values in bold are the square root of ave, b= italicized values above the square root of ave are htmt ratios. constructs ca rho cr ave ci inc ms str competitive intelligence 0.877 0.879 0.911 0.671 a0.819 b0.526 0.225 0.309 innovation capability 0.826 0.830 0.884 0.657 0.454 0.810 0.385 0.435 managerial support (ms) 0.832 0.835 0.900 0.749 0.191 0.325 0.866 0.886 strategic thinking (str) 0.921 0.922 0.934 0.586 0.278 0.385 0.772 0.765 table 4 results of the path analysis. note: ***p < 0.05 (based on two-tailed test). hypothesis model fit indices: srmr= 0.072; nfi = 0.907 d_uls = 3.928 direct effects std. beta t-value p-values f 2 r2 decision h1: str→inc 0.231 2.771*** 0.006 0.038 0.310 supported h2: ci→inc 0.366 7.085*** 0.000 0.173 0.310 supported interaction effects (moderation) h3a:mod_ms*str→inc 0.155 3.002*** 0.003 0.029 supported h3b: mod_ms*ci→inc 0.123 2.442*** 0.015 0.023 supported 35 table 5 latent construct prediction summary. note* rmse = root mean squared error, and mae = mean absolute error. rmse mae q²_predict innovation capability 0.522 0.403 0.108 strategic thinking 0.237 0.182 0.952 finally, the predictions of the outcome variable in the study model were examined, using the pls predict functionality in smartpls. the predictive validity involved cross-validation and generation of predicted errors and error summary statistics, which include the root mean squared error (rmse), the mean absolute error (mae), and the mean absolute percentage error (mape) (shmueli et al., 2016). the pls predict analysis yielded q2 values for each of the constructs: inc (0.952), str (0.108). hence, the positivity of the q2 value denoted that the model is adequately established, and valid in predicting the exogenous latent construct. 5. discussion and theoretical contributions today, managerial precedence focuses on idea creation, which is a result of an innovationdriven economy, especially within the business world. this study provides empirical evidence for the proposed theoretical relationships in the framework, confirming the significant relationships, both direct and indirect. the evidence highlights the role that mgs plays as a moderating variable on the relationships between the str, ci, and it firms’ inc. first, the question of the relationship between st and inc is addressed with the three dimensions of st: system thinking, divergent thought, and reflection. the findings show a significant relationship between str and inc, supporting kalu and naktiyok (2021) and zahra and nambisan, (2012). consequently, it can be deduced that managers engaged in it organizations possess st skills since the industry involves originations which tend to satisfy demands in the changing environment. st competency has been shown to also contribute to the positive outcomes on inc. a firm’s innovation performance solely depends on hypothetical intellects and strategic plans made by visionary and strategic leaders in predicting the future, and implementing figure 2 structural model (direct path). 36 planned scenarios in gaining a competitive advantage over rivals. strategic thinkers have diverse obligations, ranging from creating strategic plans, monitoring market trends, and continuously outwitting competitors in market performance, using tools such as pestle analysis, porter's five forces, mckinsey 7s model, and swot analysis. secondly, the result revealed that ci is directly related to, and had a positive impact on, inc. this result validates caloof and sewdass (2020) and ainul et al. (2015), who established a strong effect between ci and innovation. in support of the findings, hussein et al. (2011) and tanev and bailetti (2008) reported that ci results in innovativeness, thereby enhancing innovative performance among smes. also, strong support was given to the reasoning by petrişor and străin (2013), jaworski, macinnis, and kohli (2002), and krücken-pereira, debiasi, and abreu (2001) that ci serves as a strategy to develop and innovation capacity. meanwhile, poblanoojinaga, (2021) mentioned that no direct effect exists between ci on inc, emphasizing the repute of integrating an intervening variables, such as knowledge management, to obtain better results in serving as a source of competitive advantage for operating firms the significance of ci’s influence on inc conforms to the definition of wright, fleisher, and madden (2008) in muritala and ajetunobi (2019), viewing ci as a process in which an organization amasses information about competitors and the competitive environs, to be used in forecasting decision makings with the intent of improving performance. hence, this is actualized with actionable intelligence made through critical thinking, reflection, and principled evidence gathered from the competitive environment. this in turn is processed and further analyzed to aid decision making. hence, ci is empirically proven to increase innovative performance in nigerian it firms. from the result presented, figure 3 shows an r-squared value of 0.279, while the inclusion of the moderator (mgs) caused a change in the r-squared value to 0.310 (see figure 4). hence, this implies that an upward shift in the value of r-squared is accounted for by the combined effects of exogenous latent variables, in which the intervening variable, mgs, is strongly embedded through its positive co-efficient. several studies explore the ci effect on innovation performance, as well the effect of st on innovation performance. a study on the dual figure 3 final pls structural model (with moderator). 37 effect of ci and st on innovation was carried out by rastgar, arefi & hizji, (2017). the novelty of this study owes to factors including the industry type, continent (country), and intervening variable, which is the “managerial support” playing a moderating role. such moderating effect is one of the unique contributions of this study, as it supports the proposal that smgs has a role in the relationship between st and it firms’ inc, confirming that management support to the firm enhances innovation. the study found ci to influence innovation capacity through the moderating role of mgs, this creates an irreplaceable input to it firms, as evidence showed that managers who exhibit st skills have a keen interest in depicting future situations and, as such, they tend to steer competition. since business is driven by profit, to sustain competition, interests are not only protected but rather expanded in the area of outsmarting competitors with innovation capacity (botha and boon, 2008). this study gives support to the proposal made by rastgar et al. (2017) on the need to develop competition in business-driven companies, in awareness of environmental changes and innovation. hence, ci is a basis of the innovation process, but a lack of st in organizations causes inefficiency and ineffectiveness in achieving organizational innovation. following debates on the significant and positive influence of st on the capability of organizational innovation, management greatly supports this. this is done by encouraging all managers in charge of decision-making, as well as employees with satisfactory resources and strategies on developing, and implementing competencies on foresight and intelligence in the marketing conduct of the organizational not minding cadres of personnel. 6. conclusion the study establishes positive relationships between the st competency and its subconstructs of systemic thinking, divergent thought, and reflection, as well as one of business capability with ci to stimulate inc with support from top management teams of it firms in nigeria. notably, in the literature, academia has dealt with the relationship between st and innovation performance, as well as ci influence on innovation performance. there has been less focus on the nexus between these constructs, via a best of fit research model, figure 4 t-test statistic. 38 including the feat of management support on this strategy for developing organizational capacity. thus, this remains an novel contribution to scholarly discourse. overall results of the present study proved that the management team's support for st and careful intensification on ci serves as an imperative strategy to achieve increased organizational inc. the conclusion is drawn that through support from the management team, and influence on the link between st and ci, nigerian it firms, and their dynamic economy will be innovation-driven. 6.1 policy implications for management a few practical implications are deduced from this study, which remains valuable to managers and the top management team in place of rationale decision on the aptness of innovation type and capacity, to enhance performance. ci is relevant in today's global environment since it entails the creation of a thoughtful idea, which level managers strategically make future predictions upon. in this study, it is implicitly stated that managers who have st skills can use their ci skills more effectively, as this tends to increase the innovation capacity and performance of the organization. the present study provides consistent results with the st and ci literature on innovation capacity. this owes to the fact that managers can create a supportive competitive culture at a certain level by giving importance to st, by ensuring their contributions to the long-term goals of the enterprise and to the extent of convincing workforces in actualizing the need for innovativeness and viewing it as a corporate objective to be realized. finally, results depict that innovation benefits from intelligence processes and the proactiveness of management in support for this tactic. this can be done through periodic strategic training and orientation of employees and better diffusion of innovation capacity as a core capability. connecting with systemic thinking and divergent thought will keep the creative vision of operations alive, and result in better performance. 6.2 limitations and future research despite the theoretical and empirical contributions presented by this study, some confines should be acknowledged. first, the study results may not be generalized with other industries and should be interpreted in the context of the industry and changing business dynamics. future research using multiple industries will provide a fruitful comparison of the relationship between st, ci, and inc. it will also help in understanding the relationship between st and types of intelligence such as market intelligence, technological intelligence, corporate and strategic intelligence. the study is crosssectional, which made use of a survey in obtaining information from the respondents. therefore, future research could also supplement the data collection method sections of the interview, making a mixed-method study, which could compensate for the strengths and weaknesses associated with particular methods. future research must assess whether the alignment between st and ci changes over time given a specific innovation capacity of the firm through, for example, a longitudinal study. research could also be expanded to identify any leadership style that strengthens this association since st is further allied with leadership obligation. finally, since no strategy is required in an environment where there is no rival, the identified variables could be investigated as an antecedent of sustainable competitive advantage. 7. references adelekan, s. a. 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(2012). innovation capability: from technology development to transaction capability. journal technology management of innovation, 7(2), 14-27.s 15 the relationship between strategic planning and company performance – a chinese perspective per jenster* and klaus solberg søilen** *nordic international management institute (nimi), china per.jenster@nimichina.com **halmstad university, sweden klasol@hh.se received february 10 2012, revised form march 3, accepted february 13 2013 abstract: what is the relationship between strategic planning and company performances in chinese companies? is there a correlation between company performance and the strategies adopted by these companies, using the miles and snow model for aggressiveness strategies? and is it possible to say something more about what kind of strategic planning gives better company performances? we wanted to separate here between the planning which is related to what is called competitive intelligence and other activities related to planning. the idea was to be able to say something about the importance of competitive intelligence. we also wanted to use more extensive statistical analysis with more variables in light of the criticisms that has been raised about the methodology of previous studies. we found that better planning had a positive effect on a number of key business performance measures. we found that there was indeed a distinction between the different strategies selected and company performance. the strategy type named reactors performed systematically less well than companies who choose one of the other strategies. moreover we found that there were differences between different planning activities and company performance and that activities related to competitive intelligence were on the average more important for company performance than other planning activities. keywords: strategic planning, company performances, competitive intelligence 1 introduction there are seemingly no ends of studies on strategic planning and company analysis. why then another one? for one thing the problem has not been solved satisfactory yet. previous studies have shown quite different results and their methodologies have been seriously questioned. besides that all studies are to our knowledge on western companies. we wanted to see the effects on chinese companies to be able to make some sort of comparison. we also wanted to focus on a special type of long range planning, available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2013) 15-30 https://ojs.hh.se/ 16 namely the competitive intelligence (ci) function. is the ci function more important for company performance than other types of strategic planning? furthermore, is it possible to see what kind of strategies companies that perform better have chosen? to find out we needed to select a well acknowledged strategic model and test it against the correlation between strategic planning and company performance. this would already imply a more advanced statistical analysis. much criticism has been directed to the methodology of these studies. we found that the number of variables tested in previous studies were quite limited in numbers. this is an issue because company performance, but first of all strategic planning encompasses such a wide range of activities. the variables testing company performance are less controversial and often the same in different studies; sales growth, return on capital, cost of production, quality of products, innovativeness, profits etc. the variables used for strategic planning are not only potentially more numerous and therefore less obvious, but often not shown in the actual studies. the multiple regression analysis tables are often just summaries of the actual research where strategic planning is reduced to one variable. if the reader of these studies is to be critical he or she needs to see all of the calculations however cumbersome, so we added appendixes ag. brody has shown that there is often a misconception as to what exactly ci is. ci is the practice of defining, gathering, analyzing and distributing need-to-know information to the organization’s decision makers. as such it is a vital part of strategic planning. even though its process is simple, following the so called intelligence cycle, each stage in the cycle is relatively complex. this means that any study that wants to capture its significance needs to test a large number of different variables. the logic for the study can be expressed as follows: figure 1: a model for including competitive intelligence in the study of the correlation between strategy types and successful performance each company chooses or can be defined according to at least one strategy. after all, if the company does not have a strategy that can be defined as a strategy too. the chosen strategy again defines the company’s competitive intelligence activities, explicitly or implicitly, along the same logic. the result of these activities will again and to a large extent define the relative success of the company, or its performance. is there reason to believe that chinese firms should be different, or that the dynamic chinese business environment might call for different approaches? or do chinese companies react and function in much the same way as western companies when it comes to strategic planning and company performance? these were the questions and considerations which started this research. 2 literature review there is much empirical research on planning and performance in general, but no major research on ci and performance. tianjiao (2008) looks at the effects of proactive scanning on performance. others have studied the reverse relationship, how ci is a precedent to marketing strategy formulation (dishman and calof, 2008). in the general literature it is a problem that results from research performed on strategic planning and company performance differs greatly, even over time, and so much that it has spurred a debate about the rigor and value of different methods used in these studies (e.g. ruud, greenley, beatson and lings 2008). along this line, rhyme (1986), miller strategic types competive intelligence successful performance 17 and cradinal (1994), brews and hunt (1999), andersen (2000), delmar and share (2003) have found a positive association between planning and performance. shrader et al. (1984) and pearce et al. (1987) found that there is no such relationship. falshaw, glaister and tatoglu (2006) found there was no such relationship among uk companies. boyd (1991), greenley (1994) and hahn and powers ( 1999) has shown how this has hindered the progress of research for this problem. schwenk and shrader (1993), leilich (1993) and leilich and marcus (2006) have suggested that other factors will impact on the relationship between strategic planning and performance. strategic planning is an old topic of interest in management science. early research on strategic planning has been carried out by steiner (1963, 1979), learned et al. (1965), ansoff (1965), steiner and cannon (1966), ackoff (1970), mintzberg (1979), ansoff et al. (1976), armstrong (1982), pearce et al. (1987), ansoff (1991), miller & cardinal (1994), mintzberg and lampel (1999) and falshaw and tatoglu, (2006). the findings of this research have also been inconclusive, as suggested by the book by mintzberg “the rise and fall of strategic planning” (1994). again critique has been raised against the rigor in the methodology used (greenley, 1986 and 1994). greenley (1994) found that a number of differences were found among the methodologies of the studies so that each study is deemed limited. consequently, the results cannot be legitimately combined, and it cannot be concluded that an association is evident (greenley, 1994). mintzberg has also described other problems areas; the adhoc way of forming strategy in state departments (1985), and the difficulties that strategy imposes on entrepreneurial firms (1982). the idea of trying to identify a finite number of important strategic choices for any organization starts with chandler (1962) and child (1972). a major contribution is made by miles and snow (1978), who develop the theory of strategic equifinality, the idea that within a particular industry or environment there are a finite number of ways to succeed. this research again inspired porter’s (1980) generic strategies, of cost leadership, differentialization and focus, developed further in porter (1987). since then research on miles and snow (1978) have been carried out by hambrick (1983 & 2003), jenster (1985), mcdaniel and kolari (1987), ruekert and walker (1987), mckee, varadarajan, and pride (1989), conant, mokwa, and varadarajan, (1990), shorel and zajac (1990), matsuno & mentzer (2000), desarbo, benedetto, song and sinha, (2004) aragonsanchez & sanchez-marin (2005), and pleshko & nickerson, (2006). parnell & wright (1993) confirm earlier results where reactors are outperformed by prospectors, analyzers and defenders. prospectors tend to have more market research competence, key personal involvement, innovativeness also greater implementation planning (veliyath & shortell, 1993). others have claimed that prospectors outperform other types in dynamic markets (shorel and zajac, 1990). hambrick (1981), segev (1987) and james and hatten (1995) have confirmed the value of the miles and snow typology. 3 the empirical study to simplify all the different strategy types possible then we used the above discussed model presented by miles and snow. it describes four main types of strategies; defenders (a), prospectors (), analyzers (c) and reactors (d). they are explained in more detail below. http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib93 http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib84 http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib84 http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib18 http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib47 http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib50 http://www.sciencedirect.com.miman.bib.bth.se/science?_ob=articleurl&_udi=b6v7s-4p83hkd-1&_user=644585&_coverdate=02%2f29%2f2008&_rdoc=1&_fmt=full&_orig=search&_cdi=5850&_sort=d&_docanchor=&view=c&_acct=c000034638&_version=1&_urlversion=0&_userid=644585&md5=b74855d4a481a38da5394491d363806f#bib50 http://elin.lub.lu.se.miman.bib.bth.se/elin?func=basicsearch&lang=se&query=au:%22greenley,%20g.e.%22&start=0 http://elin.lub.lu.se.miman.bib.bth.se/elin?func=basicsearch&lang=se&query=au:%22greenley,%20g.e.%22&start=0 18 figure 2: the miles and snow (1978) model for aggressive strategies in business to be able to test chinese companies per se we selected a wide variety of different companies; joint ventures, privately owned, state owned etc. category frequency percent joint-venture 21 8.7 private-owned enterprise 69 28.6 shareholding 53 22 state owned enterprises 27 11.2 wholly foreign-owned 67 27.8 others 4 1.7 sum 241 100% table 1: types of companies included in the study we also made sure that we had companies representing all of the four different strategy types. 19 type frequency percent a 61 25.3 b 45 18.7 c 90 37.3 d 44 18.3 undefined 1 0,6 sum 240 100% table 2: number of companies across the different strategy types next we set up a number of hypotheses or questions to be answered. the first was to confirm or reject previous research in the field by repeating the standard hypothesis used in other studies on strategic planning and company performance. the only difference would be that our general hypothesis tested for chinese companies operating in china, not for western companies. h1. there is a strong, positive correlation between the level of formal strategic planning and the degree of satisfaction of performance we then wanted to find out whether or not companies perform differently depending on their different aggressiveness strategies. the limited strategies selected are those of miles and snow (1978); divided into reactors (no proactive strategy), prospectors, (have programs to expand into new markets and stimulate new opportunities), analyzers (are in between the defender and prospector), and defenders (maintain a secure and relatively stable market). these strategies were tested across 13 selected performance criteria. h2. companies perform differently depending on their different aggressiveness strategies. more importantly we wanted to see if certain planning practices have a more significant effect on the performance model. it would be possible to see this directly by comparing the results from the statistic analysis. h3. certain planning practices have a more significant effect on the performance model in a continuation of this we wanted to be able to say something about the correlation of those planning practices which may be defined as a competitive intelligence. to distinguish ci planning practices from other activities we divided all our questions into three types, x, xx and 0. where o means there is no special relationship with ci activities, x means there is a relationship and xx means there is a strong relationship. these assessments were made based on the definition of what ci is. based on our findings we would be able to answer the next hypotheses: h4. competitive intelligence practices have a significant effect on performance. at the end we also wanted to be able to say something about the importance of competitive intelligence practices as opposed to other strategic planning processes or variables. h5. competitive intelligence practices have a higher significant effect on performance than other planning activities our hypotheses were subjected to an empirical investigation. 241 valid questionnaires were collected among students attending an mba executive program representing chinese medium and large size companies. the 13 performance criteria were selected (appendix a). 33 questions were asked on strategic planning (appendix b). 20 two questions were later redrawn on suspicions of misunderstanding on the part of the subjects. a likert scale from 1-7 was used to indicate the degree of response, where 1 was very poor and 7 very good. the questions were asked about their recent experience as to avoid any differences in what experiences were measured and to make sure the experience was up to date. this was particularly important in our case as the chinese companies have gone through and are going through periods of great change, also in terms of strategic planning and company performance. the companies were largely from the major industrial areas of china but spread about the whole country. the actual interviews were done in the form of questionnaires in connections with lectures. to obtain the maximum of objectivity in the answers all participants were able to answer anonymously. the questionnaires were pretested by 25 students or about 10% of the actual sample. this allowed for some alterations of the actual questions. a t-test was performed to assess whether the means of two groups performance and strategy types were statistically different from each other. 4 results and analysis overall response rate was 100%. the sample was tested for non-response biases and differences between those who had returned the questionnaire early and those who were late. no significant difference was found. the results across the four strategy types for the 13 measures used were as follows: table 3: average score we see that d type has the lowest average score of all the performance criteria (except k-social responsibility). does that mean d type of companies have lower performance than the other three types of companies? to find out more precise we did a t-test. for the t-test, if the p-value associated with the t-test is small (usually set at p < 0.05), there is evidence that the mean is different from the hypothesized value (which is set to be 0). if the p-value associated with the t-test is not small (p > 0.05), then the null hypothesis is not rejected, and we can conclude that the mean is not different from the hypothesized value. we’re run pair wise ttest between the four types: a vs. b, a vs. c, a vs. d, b vs. c, b vs. d, c vs. d, on each of the 13 performance criteria: a-m. the p-values showed whether or not the four types are significantly different from each other. by performance 21 table 4: the t-test we found here that type a and type b have same means on each of the 13 performance criteria. type b and type c have same means on each of the 13 performance criteria. type a and type c have same means on most of the 13 performance criteria, except iability to attract, develop and keep talented manpower. type a and type d have same means on performance criteria f-m. type b and type d have same means on performance criteria d-i, k, l. type c and type d have same means on performance criteria f, g, i, k. thus we conclude that type a, b and c do not have much difference from each other on the 13 performance criteria. more interestingly we conclude that type d has a difference from the other three types on the performance criteria, which are lower than others. thus we confirm the second hypothesis: h2. companies perform differently depending on their different aggressiveness strategies. to solve the first hypothesis we use a two -way analysis of variance, using general linear model (glm). glm allows us to analyze categorical variables as well as numerical variables in the same model. in the model we use each performance criterion (a-m) as the dependent variable, all the planning practice (q1-q33) and q36 (strategy types a, b, c, d), as the independent variables to do general linear model analysis. then we find out if the planning practice and different strategy types both have an effect on the company performance. the p value of the model shows if the model is significantly valid. it also shows the significant effect of the independent variables contributing to the model. as an example for the first company performance criteria (sales growth for the past 5 years) we get the following formula: formula 1: the model in this case “a” is the dependent variable. q1-q33 & q36 (a, b, c, d) are the independent variables. we define the total effect of a, b, c and d, to see if the different strategy types of the companies matters in the company performances. 22 table 5: factor ii analysis we list some key indicators of the analysis. since our sample is big, the r square will not be significant. we mainly looked into the p value, which shows the significant effect of the model and the variables. for the model: p<=0.05 – the effect of the model is valid. p>0.05 – the effect of the model is not significantly valid. for the variables: p<=0.05 – the effect of the variable is significant or the coefficient is not zero. p>0.05 – the effect of the model variable is not significant or it’s very probable that the coefficient is zero. table 6: performance a sales growth for the past 5 years. where: y means (p<=0.05) the effect of the model (variable) is significant n means (p>0.05) the effect of the model (variable) is not significant for a list of all the p values see appendix c. a conclusion from the statistical analysis is summarized in appendix d. based on this we were able to say identify among the dependable variables which have a significant effect on the performance criteria. the overall information of the analysis is shown in appendix e. the number of valid models with independent q1-q33 is shown in appendix f. we found here that most of the planning practices have significant effect on the model except q3, q8, q10. this suggests that the fact that the planning is provided by the president or ceo is not of vital importance. this supports previous research that the engagement of top management is not a prerequisite for strategic planning. more surprising is the results that the regularity of these activities is not of importance. and its’ success does not seem 23 to depend on earmarked funds for strategic analysis and planning. when we look at the number of valid independent variables q1-q33 (appendix g), we see that q2, q4, q5, q7, q14, q15-q23, q25-q33 have more significant p values on the model. we then conclude that: h3. certain planning practices have a more significant effect on the performance model the hypothesis is accepted. for the fourth hypothesis: h4. competitive intelligence practices have a significant effect on performance. we recall that q16-20 got a xx mark for strongly relevant to ci practices. so did q26-28 and q31. the average score for these questions were (10+11+13+12+12+12+9+11+12+9) 11,1. this suggests that ci practices have a significant effect on performance. the hypothesis is accepted. for the last hypothesis: h5. competitive intelligence practices have a higher significant effect on performance than other planning activities if we take out q3 as an out-layer the average for the whole set is 8,9. this suggests that ci activities are the more relevant part of strategic planning when it comes to its effect on company performance, even though the difference is not substantial. the hypothesis is accepted. 4 findings our findings support a large part of previous research done on strategic planning and company performance. strategic planning does have a considerable impact on company performance. moreover, it confirms that chinese companies seem to follow the same model as western companies. whether or not our findings about the competitive intelligence function is the same for western companies is still to be researched. furthermore, we have tested only one side to ci. it would also be of value if other studies could look at the use of the different stages of the intelligence cycle and company performance. in today’s world where ever more information technology is used it would also be interesting to know if there is a relationship between the use of business intelligence (software) and company performance. references ansoff, h.i. 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(1993), “strategic orientation, strategic planning system characteristics and performance”, journal of management studies, vol. 30 no. 3, pp. 359-81. http://elin.lub.lu.se.miman.bib.bth.se/elin?func=basicsearch&lang=se&query=au:%22greenley,%20g.e.%22&start=0 http://www.emeraldinsight.com.miman.bib.bth.se/0309-0566.htm http://www.emeraldinsight.com.miman.bib.bth.se/0309-0566.htm http://www.emeraldinsight.com.miman.bib.bth.se/0309-0566/42/7/8 http://elin.lub.lu.se.miman.bib.bth.se/elin?func=jortoc&issn=01482963&lang=se http://www.emeraldinsight.com.miman.bib.bth.se/0309-0566.htm http://www.emeraldinsight.com.miman.bib.bth.se/0309-0566.htm 25 appendixes a sales growth for the past 5 years b average return of equity for the past 3 years c ability to gain market share d achieve low cost production e quality of your management f quality of your products or services g innovationess/new products & services h stability of profits i ability to attract, develop and keep talented manpower j record of avoiding major mistakes k social responsibility l productivity m how would your competitors rate your overall performance relative to the rest of the industry appendix a: performance criteria question number questions asked competitive intelligence indicators 1 to what extent do top executives support a formal strategic business planning process? (0-100% optimal) x 2 to what extent is there a clear idea of this organization's strategy that was set some time ago and has changed very little? (0-100% optimal) x 3 to what extent is the strategy of your organization primarily provided by the president/chief executive and a few of his executives? (0-100% optimal) 0 4 to what extent is your organization continually adapting by making appropriate changes in its strategy based upon feedback from the marketplace (0-100% optimal) x 5 to what extent is there a set of clear and consistent values of this organization that governs the way you do business? (0-100% optimal) 0 6 to what extent is long-term potential valued over short-term performance? (0100% optimal) x 7 to what extent is the way you do things in this organization well suited to the business you are in? (0-100% optimal) 0 8 to what extent is strategic dialogue a top priority activity, performed on a regular x 26 basis, e.g., each year? (0-100% optimal) 9 to what extent does the president/chief executive of this organization insists on placing his mark on virtually every major initiative? (0-100% optimal) 0 10 to what extent does the organization provide resources (managers' time, money, staff support, etc.) earmarked specifically for strategic analysis & planning? (0100% optimal) x 11 to what extent does the organization follow a defined set of procedures in its strategic planning process? (0-100% optimal) x 12 to what extent do all managers, whose work might be affected significantly by strategic issues, participate in the planning process? (0-100% optimal) x 13 to what extent does the organization have a written and well communicated mission statement? (0-100% optimal) 0 14 to what extent are all managers and higher-level staff aware of the mission and understand it? (0-100% optimal) 0 15 to what extent does the organization systematically measure actual performance vs. goals? (0-100% optimal) x 16 to what extent does the organization systematically gather and analyze data about market and other external factors which affect the business? (0-100% optimal) xx 17 to what extent do managers evaluate the organization's performance and operational characteristics systematically compared with those of competitors? (0100% optimal) xx 18 to what extent does the organization systematically assess the industry as a whole in terms of new competitors and concepts, new technologies, procurement practices, price trends, labor practices, etc.? (0-100% optimal) xx 19 to what extent does the organization have knowledge of and access to sources of information about the industry, markets, and other external factors? (0-100% optimal) xx 20 to what extent does systematic internal analysis identify key strengths and weaknesses in the organization? (0-100% optimal) xx 21 to what extent does systematic internal analysis include profitability factor trends, e.g., aftertax earnings, return on assets, cash flow? (0-100% optimal) x 22 question withdrawn as it may have been misunderstood 23 to what extent does systematic internal analysis include pricing strategy and its effects on customer behavior? (0-100% optimal) x 24 to what extent does systematic internal analysis include quality of customer service and customer satisfaction/ loyalty/ defection data? (0-100% optimal) x 25 to what extent does systematic internal analysis of the organization assess its human resource development and management programs? (0-100% optimal) x 26 to what extent does the organization's management information system provide relatively easy access to the internal data discussed above? (0-100% optimal) xx 27 after completing its external and internal analyses, to what extent does the organization review the mission and goals in light of the apparent threats/ opportunities and strengths/ weaknesses? (0-100% optimal) xx 28 to what extent does the organization make strategic decisions (implementation action plans) based upon the strategic plan? xx 29 to what extent does the organization clearly assign lead responsibility for action plan implementation to a person or, alternately, to a team? (0-100% optimal) 0 30 to what extent does the organization set clearly defined and measurable performance standards for each plan element? (0-100% optimal) x 31 to what extent does the organization develop an organized system for monitoring how well those performance standards were met? (0-100% optimal) xx 32 to what extent are individuals responsible for strategic planning and implementation rewarded for successful performance? (0-100% optimal) x 33 question withdrawn as it may have been misunderstood appendix b: questions asked on strategic planning 27 appendix c: f values question nr measure results a sales growth for the past 5 years a clear strategy and value, good internal and external analysis, transparent responsibility among the organization members and clear performance measurement will increase the sales growth of the organization. the strategy planning process seems to have no significant effect on the sales growth. b average return of equity for the past 3 years (…) will increase the return of equity. (…) no significant effect on the return of equity. c ability to gain market share (…) will increase the ability to gain market share. (…) no significant effect on the ability to gain market share. d achieve low cost production (…) will achieve low cost production. (…) no significant effect on the achieve low cost production. marketing and advertising can’t help the organization to 28 achieve low cost production. different type of companies have significant difference on achieving low cost production. e quality of your management (…) will increase quality of your management. different type of companies have significant difference on quality of management. f quality of your products or services (…) will increase quality of your products or services. doing things well suited to the business, this factor do not play significant effect on increasing the quality of your products or services. this may give us a hint that all the business follows the same principle. g innovationess/new products & services (…) will enhance innovation. internal analysis does not have significant effect on innovation. different type of companies have significant effect on innovation. h stability of profits (…) have significant effect on the stability of profits. i ability to attract, develop and keep talented manpower (…) have significant effect on the ability to attract, develop and keep talented manpower. a defined set of procedures in its strategic planning process, knowing your customer those factors may have no significant effect on your ability to attract, develop and keep talented manpower. j record of avoiding major mistakes (…) have significant effect on avoiding major mistakes. top executives’ strategy decision may have no effect on avoiding major mistakes. k social responsibility (…) have significant effect on social responsibility. different type of companies have no significant difference on social responsibility. l productivity (…) will increase productivity. m how would your competitors rate your overall performance relative to the rest of the industry (…) will affect how would your competitors rate your overall performance relative to the rest of the industry. the strategy planning process may have no significant effect on how would your competitors rate your overall performance relative to the rest of the industry. appendix d: conclusions from statistical analysis 29 appendix e: summary of depended and independent variable results appendix f: the no. of valid model 30 appendix g: the no. of valid independent variable q1-q33 that has significant effect on the models. . vol10no1paper5 to cite this article: barnea, a. (2020) how will ai change intelligence and decision-making? journal of intelligence studies in business. 10 (1) 75-80. article url: https://ojs.hh.se/index.php/jisib/article/view/521 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index how will ai change intelligence and decisionmaking? avner barneaa* aschool of business, netanya academic college, national security studies center, university of haifa, israel *avnerpro@netvision.net.il journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: technology intelligence practices in smes: evidence from estonia the effects of cross-functional coordination and competition on knowledge sharing and organisational innovativeness: a qualitative study in a transition economy nguyen phong nguyen pp.23-41 market intelligence on business performance: the mediating role of specialized marketing capabilities hendar hendar, alifah ratnawati, pp. 42-58 wan maziah wan ab razak and zalinawati abdullah implementation of business intelligence considering the role of information systems integration and enterprise resource planning farzaneh zafary pp.59-74 v ol10,n o 1,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10,no.1,2020 akhatjon nasullaev, raffaella manzini pp. 6-22 and tarmo kalvet how will ai change intelligence and decision-making? avner barnea pp.75-80 how will ai change intelligence and decision-making? avner barneaa* aschool of business, netanya academic college, national security studies center, university of haifa, israel *corresponding author: avnerpro@netvision.net.il received 5 april 2020 accepted 20 april 2020 abstract the world is facing a rapid pace of changes with a heightened sense of uncertainty, ambiguity, and complexity in both government and business landscapes. new threats and major changes in the world order are creating an external environment that demands closer monitoring and greater anticipatory and predictive skills. deeper analysis and speed of action are becoming more important for agile organizations and governments. the needs to upgrade the capabilities of intelligence analysts, mostly in strategic intelligence, have been known for quite a long time. scholars who are looking into intelligence failures1 and other major national security2 and business3 events when decision-makers were not warned in time, seek expert tools and methodologies to avoid these failures4. management is constantly concerned, aspiring to receive better decisions by relying on solid analysis in order to better understand the challenges ahead5. the current direction is in the same direction, while new emerging technologies enable theory and practice to move forward. artificial intelligence (ai) capabilities definitely are jumping two stairs up. it looks that through new ai tools, the value of humans will not become redundant but rather improve its outcomes by relying on better intelligence for their decisions. keywords artificial intelligence (ai), competition, competitive advantage, decision-making, intelligence failures, prediction, strategic surprises 1. introduction many corporations are allocating significant resources to gathering and analyzing massive amounts of information about their rivals and disruptive phenomena in business. nevertheless, too often these companies face strategic surprises, usually when their competitors make moves that were not anticipated. such surprises frequently force 1 bar-joseph, u. and mcdermott, r. intelligence success & failure, the human factor. oxford university press. 2017. 2 marrin, s. "evaluating cia's analytical performance: reflections of a former analyst", orbis, 326 (2013). 3 gilad, b. early warning, ny amacom, 2004. 4 betts, r. k. "two faces of intelligence failure: september 11 and iraq’s missing wmd." political science quarterly, 122, 4 (2007): 585-606. 5 bisson, c., and barnea, a. “competitive intelligence: from being the “eyes and corporate senior management to react under intense pressures, often leading to poorly informed, hurried and sub-optimal decisions6. it happens similarly in governments’ decisions on national security in events of military surprises or other national threats like the recent covid-19 pandemic. numerous inquiry commissions in western democracies7 have pointed towards the phenomenon of governments' looking to make the ears” to becoming “the brain” of companies”, competitive intelligence magazine, vol 23, no. 4, fall, 2018. 6 barnea, a. "failures in national and business intelligence: a comparative study", a thesis submitted for the degree "doctor of philosophy", university of haifa, faculty of social sciences, school of political sciences (2015). 7 betts, r. "analysis, war and decision: why intelligence failures are inevitable", studies in intelligence, journal of the american intelligence professional (2014). journal of intelligence studies in business vol. 10, no. 1 (2020) pp.75-80 open access: freely available at: https://ojs.hh.se/ 76 improvements on intelligence failures. different programs have been established to address this challenge, mainly by actions such as further training of analysts, team building efforts, diversity of analysts, and using expert tools. there is also a need to train decision makers on how to collaborate with intelligence and strategic units for better intelligence outputs. it looks as if using ai can help to make a change8. in this paper, there will be an attempt to predict the new direction of ai in influencing decision-making, and mostly on the prospects for it to lead to better analytical capabilities, which can have an immediate impact on the quality of management judgment. 2. about ai according to a pwc report9, it is widely accepted that ai technologies will be the most disruptive phenomenon over the next decade. growing interest in ai is reflected in the pwc global ceo survey, which found that 85% of ceos agreeing that ai will significantly change the way they do business in the next five years, even if ai’s penetration into the senior echelon of companies is not yet impressive. one definition of ai is that it is “a collective term for computer systems that can sense their environment, think, learn, and take action in response to what they are sensing and their objectives.”10 another definition is that ai “…is intelligence displayed by machines, in contrast with the natural intelligence (ni) displayed by humans and other animals.”11 according to mckinsey, "ai is typically defined as the ability of a machine to perform cognitive functions we associate with human minds, such as perceiving, reasoning, learning, and problem solving".12 there are already new tools in use that offer an ai-enabled solution that tracks over 200,000 online sources on competitors, customers, and industry segments. it enables users to collect, curate, and share information across the organization. these capabilities make ai a powerful tool, which can radicalize decision making and 8 colson, e. “what ai-driven decision making looks like”, harvard business review, july 08, 2019 9 pwc, “artificial intelligence may be a game changer for pricing”, 2019 10 ibid. 11 russell, stuart j.; norvig, peter (2003), artificial intelligence: a modern approach (2nd ed.), upper saddle river, new jersey: prentice hall, p. 4. 12 chui, michael and mccarthy brian, “an executive guide to ai”, mckinsey, october, 2018. completely change the way we do business. the same may happen to decision making in national security issues, that are also in need of better analysis capabilities to be shared with the decision makers. 3. the manner of decision making however, it looks like actually there is no change, and no further significant progress has been made so far in the analysis of information to become intelligence. intelligence manuals and a few good books13 on intelligence analysis are not helping to change the course while do not embed ai into the process of absorbing information to become useful intelligence. the best information obtained is not the key to the best analysis and to be able to create significant insights. always there will be a gap between the need to know and the information in hand, so the assessments remains the core of the problem. it is a mistake to put all the responsibility for failures of analysis on the analysts' shoulders14. it is time to consider that the quality of analysis will become a shared responsibility of the senior managements both in business and in government. for example, regarding one of the well-known failures of intelligence analysis was that the israeli intelligence did not correctly assess egypt’s intentions before the yom kippur war (1973). there are scholars15 who call for the responsibility of the heads of the israeli state who could have assessed the situation differently based on the information they had and not solely on the heads of the military intelligence. since the recent progress of ai, it looks as if new opportunities are coming up. using the latest capabilities of ai seemed to be an outstanding opportunity to upgrade the quality of analysts' reports and thus to better support the decision-makers. ai capabilities that can provide intelligent learning algorithms, analyze data, draw some conclusions and even recommend the best solutions are already part of our reality. 13pherson, k. and pherson, r. critical thinking for strategic intelligence, cq press, 2017. 14 bar-joseph, u. & kruglanski, a. (2003). "intelligence failures and the need for cognitive closure: on the psychology of the yom kippur surprise", political psychology 24: pp. 75-99. 15 shalev, a. israel’s intelligence assessment before the yom kippur war: disentangling deception and distraction, sussex academic press, australia (2010). 77 another goal is to provide predictions based on incomplete information. for instance, predictive analytics can be used to map a complex decision tree of all possible outcomes, which will then simplify human decisionmaking. ai can already perform tasks such as identifying patterns in the data more efficiently than humans, enabling businesses to gain more insight out of their data. intelligence agencies in the us, uk and israel have already started to look carefully into these new ai opportunities. however, officials say they will not lose sight of the importance of the human analyst. “as we’re looking at algorithmic analysis, artificial intelligence, machine learning, we’re finding [that] we’re having to examine what the role [is] of the human and the analyst,” melissa drisko, the defense intelligence agency's deputy director added: “it’s kind of scary … but what’s the role, what do we look like in 10 years … and even as we try to define it does that make [the role of the analyst] obsolete."16 dawn meyerriecks, the cia’s deputy director for science and technology, says regarding the use of ai: "what do i need in order to make a really good assessment on the back-end because that tells me what sort of collection i need to raise confidence to go address national leadership?"17 she added that: "the cia currently has 137 pilot projects directly related to artificial intelligence". what are the expectations of these intelligence organizations in the coming age of ai? in april 2020, there were 40 ai start-ups in israel, with a few focused on information for decision making18. as can be seen from this list, a few israeli start-ups will develop the use of ai in the intelligence analysis, both for business and government, based on the information gathered. it can give a strong support to predict future moves by competitors and enemies, and significantly improve analysis of information if the outputs produce better intelligence reports presented to the decision-makers. senior executives desperately need new tools to help them systematically analyze their own and other players’ competitive positions in hypercompetitive markets as well as in global changes in the aspects of security and threats. often, they need a fast, yet reliable, way of capturing changes that were emerging in the 16 goldstein, p. "why intelligence agencies are so interested in ai?" fedtech magazine, oct. 13(2017), 17 tucker, p. "what the cia's tech director wants from ai", defense one, september 6, (2017), market so they could finalize a strategy quickly. it is already possible to foresee a circumstance when decision makers are more beneficial with the help of the new ai capabilities entering the markets, becoming valuable. this can be a real breakthrough. 4. how much will the decision makers benefit? the buzz around ai has grown loud enough to penetrate the c-suites of organizations around the world, and for a good reason. investments in ai tools are growing and are increasingly coming also from organizations outside the tech space19. however, so far, very few senior executives think practically about how ai will impact their decision-making performance. it’s hard to say how much of a leader’s success comes from know-how and how much comes from a combination of expectations, accumulated experience, and access to information and tools that aren’t readily available to subordinates. it looks as if ai will become a supplement and enhance human thinking and help to avoid human cognitive biases. if this is the direction, we must start discussing its possible effects on how companies and other organizations such as governments operate and, just as importantly, on how they’re run. when highquality information and tools for decisionmaking will be accessed at every level within the business and in government, top executives will be under increasing pressure to use ai solutions to deliver extraordinary value. it is already visible that ceos will leverage the ability of ai to turn massive amounts of information into answers to complex strategic questions. ai will let them ask questions that they didn’t even know to ask. as other top executives also turn to ai to inform their input into corporate strategy, the effect will be amplified across the entire senior executives’ teams. it appears as if ceos will need to combine strong strategic thinking skills with increasingly sophisticated analytic tools to help them run the organization. they will have to learn carefully, first what the right questions are. senior executives who use instinctive leadership skills or past successes to make decisions, will have to become evidence 18“top 40 ai startups in israel”, april 2020 19 bughin, j., chui, m. and mccarthey, b. (2017). "how to make ai work for your business", harvard business review, august. 78 enthusiasts, as ai tools will influence strategic thinking to emphasize inquiry over gut thinking. this can be a major change in their set of activities and routines, and they will have to be informed about the capabilities of ai in order to use them effectively. still, ai is a long way from even approximating the human ability to solve problems that aren’t well defined. one can’t simply inquire of an ai platform: “what is the next move of my key competitor?”, "predict decisions of my strategic customer", or alternatively, "what is the decision dna of my competitor’s management?" ceos or their close assistants especially in strategy and intelligence must teach the algorithm all the criteria to use to define performance, capabilities and intentions of competitors such as m&as decisions, new-product introductions, and entering into new disruptive technologies. the same goes for customers. once it knows what it’s looking for, though, ai is excellent at identifying patterns in masses of data and using those patterns to build the kinds of complex insights humans can use to inform their decisions. companies invest significant resource in business intelligence and other data gathering systems. however, without identifying the “cognitive algebra” of how these competitors make decisions on m&as, tenders, new technologies, and new product introductions, data and information alone almost always lead to errors in decisions and predictions. “cognitive algebra” considers some of the interrelations between attribution theory and theory of information integration. both integration theory and attribution theory have been concerned with personal perception, but there has been little interaction between them. 20 this has had huge financial consequences for companies. by doing “reverse engineering” of a series of decisions by your competitor or rival in a particular area (for example, marketing, sales, m&as, tenders) it is possible to identify the decision rule of each decision. analyzing these rules supports the process of identifying a dominant pattern of the decision of your competitor. the outcome can provide the improvement of understanding of how your competitor/rival not only makes decisions, but the way it arrives to a choice. 20 anderson, n. (1974). "cognitive algebra: integration theory applied to social attribution", advances in experimental social psychology 26:1-101. most senior management decisions aren’t one-offs: they recur over time. and as they do, ai will compile a vast amount of past data that will inform decisions about critical issues in business, like competitive intelligence, strategic planning, finance and supply chain optimization and also in governmental intelligence. for example, today’s heads of marketing are waiting weeks or months for the marketing department to field and analyze a customer survey before accurately learning about the success of a new product. with ai constantly monitoring inputs such as purchase data, search traffic, and social media, cmos will be able to track and respond to customer sentiment in real time. this is a major competitive advantage. it can similarly work promptly in government and especially in intelligence agencies, especially when they are looking into strategic issues. ai will also be highly practical when the need is for timely and relevant data analysis. many intelligence organizations struggle with long lead times for analyzing data as demands for fast decisions increase or conducting analysis based on partial information as a result of needs to supply quick responses. ai is also capable of giving key factors indicators that place that metric into different contexts so management and analysts can see what is happening, what might happen and what has happened? then it is possible to act on those intelligence vectors. ai may be used to help anticipate what will happen in the future and thus help decision makers to shape the company’s actions accordingly. companies will need to identify and provide ai with all the relevant variables, as well as guidance on how to prioritize and rank those variables to determine which option is best. otherwise, it risks results that tell the company its best choice is to do what it has always done and get the same outcome it has always had. it’s not always possible to know whether a question that can be addressed by ai is worth asking. as ai becomes more available and sophisticated, though, these inquiries will become possible in many more cases. ceos and senior managements in business and in government will be able to ask more questions that were once too complex to answer and to determine questions that might not previously have been answerable in the "old" world. 79 once we understand the "cognitive algebra" of our competitors’ and rivals’ decisions, it will be able to better predict, using ai algorithms, their next move or decision. this gives a tremendous advantage in a competitive environment. these ai products are designed for top executives to de-bias their important decisions, by giving them objective understanding of their key competitors and rivals. it is quite similar to the use of newly non-invasive technologies in medicine, enabling doctors to treat patients successfully without using surgical systems. when senior management has improved tools, they will have to learn how to better use them. this will be different than what they are used to with the frequent use of ai tools. most large corporations have functional units (strategic planning, competitive intelligence) that monitor the external environment, including capturing intentions and actions of their competitors. most of these companies, even fortune 500s, use simple tools, primarily designed to gather information. such tools analyze competitive information, primarily from open source intelligence (osint) and from internal information (through internal strong it tools, known as business intelligence), but the resulting analysis and the added value are quite limited. there is an urgent need to find the next layer that will enable companies to generate insights tailored for strategic forecasting by utilizing technology that was specifically designed to analyze available competitive information. such insights are invaluable assets for senior managers who are facing vital decisions regarding the strategic direction of their companies or of their governments. ai that uses past data to make recommendations about possible alternatives will let top managers and others on lower levels test many different scenarios and determine how best to adapt business processes to manage risk across functions for any or all of those potential outcomes. it is hard to say yet what the precise added value of ai at the executive level will be. until it is implemented, we won’t know what new patterns it will uncover in existing data or how those patterns might lead to improved data analysis and thereby decisions. it looks as if in quantity issues like productivity, greater efficiency, or 21 mckinsey & company, “enduring ideas: the 7-s framework”, march 2008, cost savings, the contribution of ai will be easier to trace. however, ai will likely influence almost any decision a decision maker can make. it won’t just deliver more data and informed predictions about how new initiatives might influence the organization. it will let senior executives see how those ai capabilities might have a more positive impact. far from simply being another layer of technology, ai tools will guide in a new era of leadership. leaders and other decision-makers and also analysts working closely with them will need analytic skills rather than just accumulated knowledge. they’ll need an ability to inspire rather than control and they will use ai-driven inputs to create a long-term vision and purpose for the organization rather than a short-term strategy. we’ll start to see a move towards a trend of relying on ai capability where what matters most is not the individual responsible but what all senior executives can do with the information at their disposal, with the close support of their strategic and intelligence teams. it is possible that in the near future, measuring the quality of ai tools, organizations using it will be measured as a capability which will identify if companies are effectively aligned and allow organizations to achieve their objectives. maybe ai capability needs to be added to the key internal elements in the famous mckinsey 7-s model that analyzes a firm's organizational design by looking at seven key internal capabilities: strategy, structure, systems, shared values, style, staff and skills, in order to identify if they are effectively aligned and allow an organization to achieve its objectives. 21 5. to what extents will ai make a difference? it is possible to assume that ai will be valuable to upgrade the quality of analysis. however, it is worth remembering porter's22 views that a robust strategy requires a tailored value chain—it's about the supply side as well, the unique configuration of activities that delivers value. strategy links choices on the demand side with the rare choices about the value chain (the supply side). you can't have a competitive advantage without both. so, there are other difficulties with the capabilities of analysis 22 margretta, j. (2011). understanding michael porter: the essential guide to competition and strategy, harvard business press. 80 either by analyst who delivers them to decision makers or while the latter are actively involved in the analysis process, especially in the ai era. another challenge is how to avoid overestimating strengths, as we are aware there is an inward-looking bias in many corporations. it is also similar with overestimation of strengths over enemies that often are later found to be wrong. senior executives might perceive their customer service as a strong area. so that becomes the "strength" on which they attempt to build a strategy. but how you reach to such conclusions? what is the basis for them? a real strength for strategy purposes has to be something the company can do better than any of its rivals. and perceiving being "better" is because you are performing different activities than your key competitors perform, because you've chosen a different configuration than they have. all these are often based on cognitive biases rather than analysis. these difficulties lead to the conclusion that in order to make the right decision, senior executives will need to analyze not only their competitors’ moves and other alarming changes in the external environment, including their future goals, but also to look carefully into their own performance. although porter23 gives priority to the following capabilities to know better what is the right direction: future goals, assumptions, current strategy (of your competitor) and (their) capabilities, this still is not sufficient. clearly, although better intelligence, through ai, of a competitor’s goals can identify disruptive trends and technologies to support the prediction about the likelihood, the competitor will change its strategy, so there is a still a critical need to develop ai capabilities inside the corporation systems as not to be mistaken by biases that give outputs on a company’s own capabilities. this is related to a company’s products, distribution, marketing, overall costs and other capabilities. so, the other side of the equation is to be able perform an excellent estimation of the competitors’ reactions to a company’s move and be able to ensure that this will give a sustainable competitive advantage. here we expect to use ai, based on data gathered from multiple sources and stored internally. corporations are not there yet but are starting to develop these new capabilities. using ai capabilities for analyzing both the external environment together with the internal area are expected to give great value. 6. conclusions it is quite difficult to expect senior executives to dive into the nature of ai tools. it will be more reasonable to assume that they are more concerned with how to decide better and what the added value of ai is, if any. regarding the future of ai in israel, both in corporations24 and the security establishment25, it looks that there are a lot of expectations but organizations are still unsure of how much it is relevant for better decision making. this is also my perspective, after discussing this issue with numerous israeli directors in senior positions. for example, it is possible to see the advantage of ai in running and optimizing many scenarios regarding “go to market” decisions instead of just the typical handful of scenarios, usually leaving them unimpressed. discussing applications of ai in retail, i.e. marketing and sales, was more promising, especially demonstrating marketing forecasting and expected customer behavior. senior executives who realized the potential of ai may be starting points for implementing it systematically. in the future, ai will be highly significant for analysis and predictions in advance of competitors’ moves and in delivering early warning signals of threats in national intelligence. research looking into the interrelations between decisions to avoid strategic surprises in governments and business shows that usually businesses are leading in absorbing new tools and technologies before governments26. it appears that as intelligence communities have an urgent need for better tools to prevent emerging terror threats, they implement these highly advanced ai tools for these needs more quickly than businesses, and lessons will be drawn from this and extended into business. 23 porter, m. (1998). competitive strategy: techniques for analyzing industries and competitors, free press. 24solomon, s. (2019). “israel needs national vision for ai or risks falling behind, tech authority says”, the times of israel, 14th. january 25 israel, d. (2017). “the future of artificial intelligence in the idf”, israel defense, 2nd. july 26 barnea, a. (2020). “strategic intelligence: a concentrated and diffused intelligence model”, intelligence and national security, doi: 10.1080/02684527.2020.1747004 vol9no2paper2 to cite this article: de almeida, f.c. & lesca, h. (2019) collective intelligence process to interpret weak signals and early warnings. journal of intelligence studies in business. 9 (2) 19-29. article url: https://ojs.hh.se/index.php/jisib/article/view/406 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index collective intelligence process to interpret weak signals and early warnings fernando c. de almeidaa*, humbert lescab auniversity of são paulo, brazil blaboratoire cerag umr 5820 cnrs université de grenoble, france *fcalmeida@usp.br journal of intelligence studies in business please scroll down for article collective intelligence process to interpret weak signals and early warnings fernando c. de almeidaa* and humbert lescab auniversity of são paulo, brazil blaboratoire cerag umr 5820 cnrs université de grenoble, france corresponding author (*): fcalmeida@usp.br received 10 october 2019 accepted 15 october 2019 abstract the treatment of weak signals is identified as a method to identify strategic surprises in a firm’s environment. many researchers address the problem of anticipation of movements that have an impact on a firm’s environment. weak signals are considered in some approaches and presented in the literature, but also other methods are explored. this article tries to deepen the discussion of how to treat and interpret weak signals collected in a firm’s environment. the concept of a weak signal is explained and the discussion about how to collect and interpret them is presented. two important aspects are distinguished in the article: the usefulness of information technology in collection and treatment of weak signals and the concept of collective sensemaking in interpreting weak signals. two cases of weak signal interpretation are presented as illustrations. keywords collective sensemaking, competitive intelligence, weak signals 1. introduction there is an ongoing lack of understanding of the notion of weak signals and few methods exist to explore them. some researchers developed methodological procedures to explore them (lesca and lesca, 2014) and produced methods for collecting and interpreting weak signals in a competitive intelligence process. the traditional competitive intelligence process (herring, 1988) considers key intelligence topics (kit) to “provide the focus the prioritization needed to conduct effective intelligence operations and to produce the appropriate intelligence” (herring, 1999, p.6). kits are comprehended in the first step of planning and direction of competitive intelligence cycles. this step defines an organization’s intelligence needs and orients the search of a firm in the competitive environment. many organizations considerer the environment as analyzable and that it has the information needed to obtain correct answers to their questions. it is just a matter of searching for this information through “discovery”, one of the four scanning methods that may be assumed by an organization in an environmental scanning process (daft and weick, 1984). there is no reflection and hypothesis of what may or may not exist in the environment. the information is there. the intelligence needs and kits identified in the “planning and direction” step, conducted in the competitive intelligence search process. some organizations may consider the environment unanalyzable and adopt “enacting” as a strategy to approach the interpretation of the environment. “the organization in some extent may create the external environment. the key is to construct, coerce, or enact a reasonable interpretation that makes previous actions sensible and suggests some steps. the interpretation may journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 19-29 open access: freely available at: https://ojs.hh.se/ 20 shape the environment more than the environment shapes the interpretation” (daft and weick, 1984, p.287). weak signals suggest interpretation and sensemaking (shoemaker and day, 2009) as the environment is considered unanalyzable. weak signals through an inductive process stimulate the hypothesis generation and sensemaking of the competitive environment. it is not a matter of finding the right answer, as in a discovery scanning processes, but creating perspectives and possibilities that outline how the future environment and competitive may move (gilad, 2011). whatever future is considered, the future does not exist yet and the perspective of today may not happen in the future. for example, possible competitive moves identified today may not happen if the environmental scenario changes as a consequence of economic change, competitive moves or any other unexpected environmental change. in this article ansoff ’s concept of weak signal and an operational process of treating this weak signal is discussed. it allows us to create hypotheses and perspectives about future moves in a competitive environment that may impact an organization. weak signals are considered here to be an inductor of collective sensemaking about what may or may not come in a future environment. 2. theoretical background 2.1 weak signal information of an anticipatory nature is a weak signal. the notion of weak signals, a type of metaphor (ansoff, 1975), has proven interesting on account of its orientation toward attention given to surprises and ruptures that may occur in the business environment. “for the first time, the idea of a need to be ‘early’, or rather as early as possible in anticipating change, was expressed and translated into a complete methodological proposal” (rossel, 2012, p.230). however, the weak signal definition lacks precision and does not constitute actionable knowledge (argyris 1996), despite the fact that ansoff (1975) clearly attributes an anticipatory character to weak signals. according to the author, these fragments of information have a propensity to trigger, in the entrepreneurs that observe them (provided they pay attention), a sensation that something important may happen in the general environment. “for ansoff, any change taking place is preceded by some form of ‘warning’, which the analyst has the role of capturing and making good use of. this is what he called a signal, based on the information theory work of shannon and weaver in the 1940s” (rossel, 2012, p.230). this sensation approaches that of intuition, triggered by data that is perceived and then examined attentively. such information plays a triggering role, inducing the stimulus of an interrogation followed by an interpretation. next, an inquiring entrepreneur will wish to know more about the question and obtain further information to refine this sensation. before the interpretation through a weak signal, the decision maker had probably not asked for anything concerning the subject as his/her attention was not activated. this notion of a weak signal does not have an operational definition. in practice it can be seen that expressed weak signals are misinterpreted in companies and generate contradictions (lesca, 2011). 2.1.1 meaning of the word weak: contradiction and propositions our experience through numerous companybased action research projects leads us to verify that the expression of weak signals is misinterpreted by most entrepreneurs due to the adjective weak. we often hear: “we don’t want to capture weak signals, but strong ones!” evidently, the word “weak” leads entrepreneurs in the wrong direction. indeed, a signal can be weak in its appearance and thus discrete in terms of meaning but potentially very rich in meaning; in this sense it can “announce” something very important for the individual that is able to capture and interpret it. in our view, ansoff (1975) meant that a signal can be classified as “weak” if it bears the following characteristics: a) fragmented: for example, there is only a fragment of information from which it can be attempted making inferences in a holistic procedure. it is expect that the number of weak signals is very small. it is not a context where the amount of information is high and it is not a matter of treating a huge amount of data. b) submerged amidst myriad bolder data: it is weak because it is submerged, mixed with a myriad of useless information that creates noise. it appears thus, with weak visibility, 21 most people pass over these signals, barely noticing them. c) meaning not evident: it is weak because of an apparent weak meaning and ambiguousness. information such as a weak signal does not bring a visible interest. on the contrary it is equivocal or ambivalent. this information is of little significance by itself, and does not have an evident connection with other information. d) unexpected, not familiar, non-repetitive, and it risks not to be noticed: the concept of non-familiarity of this kind of information makes it difficult to distinguish. cognitive biases may also distort its identification or interpretation and analysis in competitive intelligence processes (memheld, 2014). e) the operational utility of a weak signal is not immediately evident and it seems not to be very useful. the very same information may be of importance for one person and of no interest for another. it is not evidently interesting, the consequences of the event identified are not evident. f) the detection of a weak signal is difficult. because of this the opportunity to use information technology or big data techniques to search for weak signals on the web, or on a newspaper’s site is high (lesca, buitrago and casagrande, 2016, buitrago, casagrande and lesca, 2015). the technology can select news with potential weak signals to be evaluated. nevertheless, weak signals are at the core of anticipatory, strategic intelligence because they are of potential use to managers, if the managers are able to perceive and interpret them. this type of information can range from indicators of disruptions (ansoff, 1975) to larger events, and they clarify the intentions of external actors (competitors, clients, suppliers, and various signs of changes in general). individual differences may also influence the interpretation and importance perceived of information (stanovich and west, 2012). 2.1.2 definition of a weak signal as posited by ansoff (1975), a weak signal is a “datum,” often with an insignificant appearance and submerged in myriad other data, the interpretation of which can warn that an event (perhaps not yet initiated) is about to occur and is likely to have significant consequences in terms of risks or opportunities. it has an anticipatory feature (lesca 2003). weak signals have the following characteristics presented by lesca (2001): • fragmented: to which information can it be related? • isolated • uncertain reliability: is it possible to relate it to something else? • imprecise • unpredictable: where to look, when to pay attention to the information? • ambiguous • apparently little or no utility: how to avoid ignoring it? • anticipatory • no standardized key words: how to access it? • unusual, singular, unfamiliar: when to pay attention to it? • possibly intentional on the part of the signaler • submerged amidst a large quantity of data: how to notice it? • subjective • often qualitative 2.1.3 characteristics of a weak signal (adapted from lesca 2001) weak signals originate from two types of sources. contacts with the field: personal relationships, visual observations, etc. these are the richest sources of anticipatory information, but significant human aptitudes are needed to exploit them. databases, the internet, websites, etc. these sources have been causes of data overload (edmunds and morris 2000; lesca et. al. 2009, sherkock, 2011). lately, efforts at using new technologies are helping to deal with large data sources on the web to identify weak signals (buitragouitrago, 2014, casagrande, 2012), and to limit the information overload (lau et al., 2012). one should not use anticipation and prediction interchangeably. prediction is mainly the calculation of the trends in the quantitative database collected over a period. the calculation does not include singletons or outliers, and computers are of great use. it is more related to daft and weick’s (1984) discovery processes. prediction may be 22 expressed by a curve integrating a significant part of the data (for example, 80% of the observations), extrapolating to the future what was learned from the past. the 20% of the observations not integrated in the predicting curve are considered to be less important or outliers. anticipation concentrates singular information or outliers left aside by predictionmakers. it is interested in the 20% of the data left aside by the predictions. though considered outliers by the statistics, this is possibly where weak signals can be detected early, as well as possible surprises, discontinuities or disruptions. these weak signals should be stimuli for strategic management (reinhardt,1984; starbuck and milliken, 1988; gilad, 2004; marrs 2005). consequence 1: the first question to be presented is: “what is one’s objective: to predict or to anticipate?” if it is to detect surprises, ruptures, or breakthroughs, then weak signal treatment is a appropriate method. consequence 2: information like weak signals are the one considered by a process that daft and weik (1984) called enacting, where a process of sensemaking and interpretation is induced by the weak signal. the treatment of weak signals stems from interpretation through collective sensemaking, and not an algorithm with information technology (daft and weick 1984). 2.2 detection/ acquisition of weak signals strategic scanning information systems (scis) is the way by which a firm seeks to detect signals as early as possible, before the occurrence of changes in the environment, so as to secure sustained competitiveness. it is a collective, transversal, proactive, and continual process through which a group of individuals collaborate to pursue, capture, and use information of an anticipatory nature concerning the external environment and changes that can be produced there (strategic surprise), including disruptions (lesca, 2003, p10). a conceptual scis model is shown in figure 1. figure 1 scis conceptual model. 23 over successive experiments in different organizations, it was possible to distinguish two types of strategic monitoring processes. there are those including a phase of collective sensemaking that is particularly important in recognizing and exploring weak signals. it can be referred to as an anticipatory collective intelligence processes in the sense of daft and weick’s enacting process. the second is those that do not include the collective sensemaking phase. this type of process is currently the most-used by companies. daft and weick called it a discovery process. according to daft and weick (1984, p291), there are four different ways to interpret the environment, leading to four different modes of organizing processes for scanning the environment (four quadrants). daft and weick (1984) suggested a model to categorize organizations according to the way top management interprets the collected information to make a decision and to define actions. they suggested the existence of a relation between strategic orientation and the way firms monitor the environment, based on aguilar’s (1967) and miles and snow’s (1978) models respectively. daft and weick (1984) used two dimensions to explain how organizations approach environmental knowledge. the first one is how much top management considers the environment stable and the second one is how actively the organization searches information allocating resources. from these dimensions, four ways of interpreting the environment are derived: undirected viewing for reactive organizations that obtain information randomly; conditioned viewing for defensive organizations that frequently use information that once in the past was helpful; discovery for analytical organizations that intend to formally search and structure environmental knowledge; enacting for prospective organizations that intend to transform the environment through innovation and are characterized by informal searches of information. daft and weick (1984) suggest two different dimensions concerning the scanning strategy and firms environment perception. the first is intrusiveness. the firm exhibits proactive behavior, searching for business opportunities, and strives to prevent all types of threats. to this end various sources of information are accessed (formal and informal, documented and field-based). it seeks several types of information (field-based, formal, and digital information). people in charge of collecting information belong to different parts of the organization. exploiting the information, mainly weak signals, is done through interpretative processes, considering the characteristics of weak signals presented above. the results of the interpretations aim to assist in strategic decision-making. the second is the unanalyzable dimension. the enterprise is in an unanalyzable environment. the sources of information are diverse, but the richest are also the least formal: human contact is essential. information collection is not done by a bureaucratic “cell,” but is entrusted to collaborators with main activities other than scanning. perception processes are essential. exploring information is not automated: it is mainly based on human and heuristic cognitive processes. people interpret information individually and then collectively. collective learning is important. understanding weak signals advances by trial and error, or “learning by doing”. 2.3 a collective sensemaking of weak signals weak signals are of little interest per se. they start to become useful if it is known how to exploit them to create a useful meaning for strategic management (haeckel 2004). the treatment of weak signals lies in the resulting interpretation (daft and weick 1984). information technology is becoming more and more effective in detecting weak signals automatically (lesca, buitrago and casagrande, 2016, buitrago, casagrande and lesca, 2015). however, interpretation can only be made by individuals, alone or in groups (almeida, 2009), as interpretation is also a matter of a decision maker’s perspective (gilad, 2011). it was shown that the characteristics of weak signals create a number of difficulties when considering its features. lesca (1995) suggest that the exploitation of weak signals could be accomplished with heuristics. the conceptual model for the application of the heuristics was illustrated in figure 1 and agrees with the works of daft and weick (1984) and nonaka (1991, 1994). lesca and lesca (2014) suggest that heuristics must be used within a collective working group of people chosen according to their involvement in the subject and their knowledge. the work of collective interpretation is called “collective intelligence” (lesca and caron 1996; blanco 24 and lesca 1998; blanco et al. 2003; lesca, 2003). collective sensemaking is the operation of collective interpretation thanks to which meaning and knowledge are created from weak signals (input) that have the role of inducing stimuli, and through interactions among participants (mamykin, nakikj and elhadad, 2015, lesca, 1995). the result of collective sensemaking (output) is the formulation of plausible future views capable of orienting entrepreneurs (lesca and caron 1996). the collective sensemaking accomplished according to lesca’s (1995) heuristics is in line with schoemaker and day (2009). collective sensemaking cannot be understood as “organizational sensemaking,” because experience shows us that it is not possible to mobilize all people within a firm to interpret information. the process of collective intelligence arises from a group of individuals when the signals coming from the competitive environment are collected, selected, interpreted, and compared through collective work so as to make sense. it is a process in which group members interact in different ways, subject to behavior rules of collective work (lesca, 2003). a weak signal must be examined from different points of view, by different people holding different positions within a firm (starbuck and milliken 1988). the discussion of collective sensemaking appears in the academic literature in different domains like teaching (coburn, 2001), on-line services (mamykin, nakikj and elhadad, 2015) and competitive intelligence (soilen, 2017, lesca, 1995). the discussion of weak signals in a collective way is in line with the idea that in a competitive intelligence process, it is not effective to deliver reports and answers to managers as they tend to ignore them or to consider them threatening to their position (soilen, 2017). in a collective process around a group of individuals, they debate and discuss the environment. the role of the competitive intelligence staff is to conduct and help the discussion process. decision makers then may have insights about the market, have their own perspectives about what is going on and take decisions based on their own perspectives (gilad, 2011, rohrbeck and bade, 2012). 3. two cases of weak signal interpretation and sensemaking two examples are explored here to access the concept of weak signals as follows. these two examples were treated by the team involved in this research in order to analyze weak signals for to companies. the first is the abb case (lesca, h., buitrago-uitrago a. f. ,casagrande, a., 2015). let’s consider a company with a strategic intelligence process that is interested in abb as a target of the process. the information to be treated in the following paragraphs was presented as follows: “abb wins the energy prize at the arabian united emirates.” why can this data be considered a weak signal? it is fragmented (less than a line). it was taken from a newspaper that contains over thirty pages per day. it is submerged in a huge volume of data. how can this be seen a warning sign in this weak signal? • pertinence. considering abb as an example of a target, this is a fragmented piece of information. • surprise. this data was not expected, caught someone’s attention, and triggered a process of collective reflection. as of that moment, this data gained the status of information for us. • importance. considering abb as a target and the motivations justifying a process of strategic intelligence, it can be raised the hypothesis that abb relations could suggest business opportunities for the company interested in it. a manager considering this information observed: "the information thus began to be potentially useful to us. we could enter the arabian market through abb.” • anticipation. is this information anticipative? it is clear that abb prize is already a past event. on the other hand, it could be estimated that there still may be initiatives not known of abb in saudi arabia showing opportunities. the set of collective reflections by a group in the company dealing with the information, led it to see in the weak signal as a warning sign. thus, it was possible to exploit a weak signal and trigger the concrete action of contacting abb. this procedure gives rise to a positive 25 output beyond the company’s initial expectations. this example shows that, in certain cases, detecting weak signals and transforming them into early warning signals fully exploited by the firm’s leadership generates benefits that may be far superior to costs. the second example is the azuly case. the information was presented as follows: “p. azuly goes to the x group”. why consider this data to be a weak signal? it is very fragmented, qualitative data. at first it was captured through oral communication, talking with a work associate. later it was found printed in a recent issue of a professional magazine. the information occupied only two lines—a piece of news submerged in a 150-page magazine, bound to go unnoticed. the utility of this information leading to action was not evident. furthermore, this data is ambiguous and open to multiple interpretations. it was a surprise. it caught the researcher’s attention almost by chance. the piece of information started to have a meaning for the team. the information is probably anticipative: the strategic operation of the x group is only in the initial stage of its preparation. a field expert that was contacted informs us that this sort of operation and a communication campaign related to the strategic topic possibly identified requires around 12 months of preparation. in conclusion, in this example one moves from a weak signal to an early warning signal (gilad, 2003). clearly, the latter is based on hypotheses (lesca, 2014) that are formulated and are able to be verified. such interpretation of the weak signal is not the only one possible. it allows the decision maker to be placed in an “alert mode”. from then on, it is up to him/her to accomplish what is necessary to further explore the situation and reduce the uncertainty if it is judged useful. but what type of usefulness does this weak signal represent to the x group? the strategic operation was revealed to be of great importance, both for the x and y groups. group y had available to itself of a sufficiently long term of anticipation to create plans to consider an offensive vis-à-vis x. 4. a strategic intelligence method in order to organize the detection, capture, and exploration of weak signals, lesca (2003) suggests the lescanning (learning environmental scanning) method. figure 1 indicates the different blocks that make up the entire process of anticipatory strategic intelligence. 4.1 domain delimitation approaching the scis (strategic scanning information system) device: a company can have various scis devices. in a large company, for instance, there are devices at the company level, together with the ceo, or at the group level when the company comprises a number of autonomous units or “business units.” perimeter delimitation of the scis device: perimeter refers to the list of people included in the device, each of whom will have to contribute and will experience some benefit. 4.2 scis target targeting is the operation of delimiting the portion of the environment-of-interest to the members of the perimeter of the future scis device. focusing means expressing in an explicit and formal manner who/what can serve as a common interest for the different participants of the scis process. 4.3 collecting/surrounding the information by designated people this phase requires human and formative qualities. it is an elementary form of the perception filter (starbuck and milliken 1988). 4.4 information selection this consists of retaining, from the collected information, only that which is of interest to potential users within the scis perimeter. this is a crucial operation: lack of selection leads to data overload and suffocates the scis process, whereas too restrictive a selection impoverishes and empties the scis process. selection (or filtering) is the separation of raw data from potentially weak signals. it is conducted by taking the target into account. 4.5 collective sensemaking this is the process of exploring weak signals to create sense. the interpretation of weak signals cannot be valid if conducted by just a single person. it requires plurality and competing viewpoints from people with different knowledge, experience and points of 26 view. but it requires a certain familiarity with the subject. interactions among people are very important. it can be suggested that heuristics creating links between the pieces of information (weak signals) used during the collective work session can map fragments of isolated information into a more significant and reasoned visual (or other) representation. figure 2 shows an example of a puzzle, referring to the carrefour example in brazil. the collective interpretation of weak signals may imply resorting to a single or several external specialists. lesca and kriaa (2007) conceived and tested a method of remote monitoring to help the leader of the collective sensemaking sessions using the puzzle method. 5. conclusion ansoff (1975) distinguished the importance of treating weak signals to identify strategic surprises. the point was to identify disruptions and strategic surprises, not tendencies projected from past data. his article comes after some decades of a stable environment and continuous growth where long-range planning was still possible. however, the stable environment from the 1950’s and 1960’s changed and the environment became turbulent and the experience and projections from the past were not enough to anticipate the future. formal search is questionable in its ability to predict the future, since it is strongly associated with analyses and statistical predictions that may divert the attention from strategic surprises or disruptions (ansoff, 1975). data from the past may be interesting to identify future outcomes only in a stable environment. in this case quantitative data analysis may be of use. ansoff suggested the importance of paying attention to weak signals that might preannounce changes in the future environment. kahaner (1997), sharing the same reasoning, comments that one of the most difficult tasks of monitoring the competitive environment is to predict what will happen in the future and that quantitative information, in general, describes the past and therefore suggests that even unstructured information such as rumors and comments should also be part of the scope of monitoring. rumors may be weak signals of future events. decades after ansoff’s proposition, the discussion about weak signals and early warning was extended. different authors figure 2 example of puzzle: the carrefour case. 27 reinforced ansoff’s preoccupation with this kind of information. they proposed useful approaches to increase firms’ attention to not so clear events that might suggest important moves in the environment. rossel (2012) identified different “neo-ansoffian contributions” (p.232), considering them diverse and rich. the author considered classificatory maps the richest one, for example, where morrison and wilson (1996) made cross references to probabilities of occurrence with impact concerning weak signals. this kind of approach is particularly interesting as it suggests ways of interpreting weak signals. day and schoemaker (2005) proposed to scan the periphery in order to identify events not in the main stream of the decision maker’s attention. treating weak signals requires methods that enable one to identify and interpret them. because the characteristics of weak signals make them difficult to be identified and interpreted, there is still a considerable opportunity concerning new ways of working on them. the present study intends to bring some methodological propositions and suggestions. one important aspect of treating weak signals to be further explored is the use of information technology. it may help in identifying and treating weak signal interpretation. it also requires intuition, imagination, and sensitivity in their interpretation, a task that cannot be fully accomplished by information technology, though it is increasingly helpful in the first steps of collection and interpretation of weak signals. it is also importance to distinguish the collective reflection on the eventual meaning of the weak signals, as different persons bring different knowledge and 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(2017) key success factors to business intelligence solution implementation. journal of intelligence studies in business. 7 (1) 48-69. article url: https://ojs.hh.se/index.php/jisib/article/view/200 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index key success factors to business intelligence solution implementation josé manuel villamarín garcíaa,* and beatriz helena díaz pinzóna a universidad nacional de colombia, gistic research group, bogota, colombia *jmvillamaring@unal.edu.co journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies proposal of an assessment scale in competitive intelligence applied to the tourism sector gisela casado salguero, pedro carlos pp. 38-47 resende jr. and ignacio aldeanueva fernández key success factors to business intelligence solution implementation journal of intelligence studies in business v o l 7 , n o 1 , 2 0 1 7 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 7, no. 1 2017 josé manuel villamarín garcía and pp. 48-69 beatriz helena díaz pinzón business intelligence and smes: bridging the gap ekavi papachristodoulou, margarita pp. 70-78 koutsaki and efstathios kirkos klaus solberg søilen pp. 5-37 a new model for identifying emerging technologies klaus solberg søilen pp. 79-86 key success factors to business intelligence solution implementation josé manuel villamarín garcíaa,* and beatriz helena díaz pinzóna auniversidad nacional de colombia, gistic research group, bogota, colombia *corresponding author: jmvillamaring@unal.edu.co received 6 february 2017; accepted 27 february 2017 abstract business intelligence (bi) solutions have been adopted within organizations as a mean to achieve a more grounded decision making process that results in better organizational outcomes. nowadays, about 70% to 80% of business intelligence implementation projects fail due to both technological and managerial issues. multi-methodology proposed by mingers (2006) was followed to develop the research in four phases: appreciation, where documental search was conducted through a literature review; analysis, where hypothetical structures related with the key success factors were proposed; assessment, where key success factors were assessed along with experts; and action, where research results discussion was shown. as a result, 13 factors that affect the business intelligence solution’s success were identified. those factors contribute to improve planning and implementation of business intelligence projects, accomplishing in a greater extent the purposes of these projects. keywords bi projects, bi success, business intelligence, critical factors, key success factors 1. introduction for companies and institutions to survive in the economy and in the business world, decisions must be accurate and made on time (karim 2011; olszak 2016). to have trusted, accurate and timely decisions, information needs must be ideally satisfied (rajterič 2010) since the amount of time between making a decision and its feedback (which requires a new decision) is shorter every time (folinas 2007). for companies to remain competitive in the new economy they must dynamically respond to both environmental changes and customer requirements (velicanu and matei 2008). in practice and despite the facts mentioned above, it has been noticed that a great proportion of bi projects fail. according to gartner inc. about 70% to 80% of bi projects fail (ortega 2013; sap 2013). pham et al. (2016) estimated a rate of failure approximately between 65% to 70%. castelán et al. (2010) claim this proportion is about 40% to 50% for systems based on data warehouses, such as bi systems, because of issues that were not considered early on. this is consistent with another study that reveals that in addition to failing, they are also abandoned at the same rate (herrera, 2011). failures in the use of bi implemented solutions are significant as well. in a few cases this type of solution tends to be discarded or fails to be implementations. about 10% to 20% of projects that did not fail in the preimplementation stage are executed result subutilization by those users that were supposed to use them (arnott 2010; yeoh and popovič 2016). however, existing problems in the bi project field can be seen from different perspectives. from a general point of view, there are two groups that summarize the presented failures: managerial obstacles and technological obstacles (sakulsorn 2011). from a specific perspective there are problems related to the project leaders, sponsorship, journal of intelligence studies in business vol. 7, no. 1 (2017) pp. 48-69 open access: freely available at: https://ojs.hh.se/ 49 solution requirements, designs, training, tools, tracing, posted objectives, estimated time to execution, data, data sources, problems with the technology handling, user needs, and investments, among others (ahmed 2014; castelán et al. 2010; emc consulting 2010; gurjar and rathore 2013; herrera 2011; sap 2013). those failures produce problems within organizations such as wasted of resources, time, and costs of opportunity of invested capital, as well as an inability to achieve expected benefits (ortiz 2014). taking into account the given failures when thinking about bi solutions and the problems that arise at the time of sharing information at an organizational level, this research aims to give a conceptual framework of key success factors to improve bi solutions success within organizations. all of these take contributions from several authors, validate those contributions at an organizational level and generate factors or specific characteristics that allow organizations to get greater effectivity rates in the adoption and implementation of these type of projects. 2. theoretical background given the high failure rates, sub-utilization and the withdrawal of bi solutions, the need to approach issues that encourage good planning, use, implementation and holding of these type of solutions is evident. for that, researchers have attempted to identify those factors that could contribute to bi solution success, and are linked to benefits that could be potentially achieved (ramamurthy and sen 2008; srikant 2006; solomon 2005; shin 2003; hwang et al. 2004 cited in hawking and sellitto 2010). these factors have been called “key success factors”. issues such as solutions adoption, complexities in implementation, and business purposes justify a more focused study of key success factors for bi solutions (yeoh et al. 2008). the challenge for organizations is to identify factors that have the greatest influence over their bi systems (sangar and iahad, 2013), which is why the topic of key success factors becomes a useful concept to understand the events during a bi project. further, it becomes a construct easy to understand by managers, executives, technology information professionals and other people from areas that can carry theory into practice (arnott 2008). 2.1 key success factors “the theory of ksfs gives good basis for stating what criteria should be followed during implementation of bi applications” (olszak 2016, 112). key success factors are defined in the literature as those critical areas where everything has to work correctly for business to flourish (umble and umble 2003, cited in sangar and iahad 2013). equally, they are seen as high level considerations that differ from a set of deliverables at the end of a project (yeoh et al. 2006). the definition made by olszak and ziemba (2012) goes further and claims that they are seen as a set of tasks and procedures that must be approached to secure the bi systems achievements during their formulation and promotion. this is used as the definition in this research. 2.2 key success factor in bi solutions literature presents different key criteria to ensure bi solution success (table 1). in turn, these factors present key characteristics that describe in a detailed way the meaning and composition of each factor. 2.2.1 directives and top management the engagement of the key members of the management team relates to the bi project (table 1). according to cidrin and adamala (2011), a high level of top management support is associated with a high level of bi project success. likewise, it helps to manage the change process and battle the resistance against project (arnott 2008). leadership figures have important influence since if these executives exert a significant influence, they will be seen as leaders, and, employees will tend to follow them (hobek et al. 2009). 2.2.2 business linking according to an interviewed person from the study by yeoh et al. (2007, 1362), “a bi system that is not business driven, is a failed system”. also salmasi et al. (2016, 26) stated that “for bi success in an organization, information systems must meet the business needs”. a solid business model must incorporate all strategic proposals that the project will approach, needed working resources, possible risks, costs to take on and deadlines to execute the project (table 1). thus, the model will provide justifiable motivations by which the adoption of a new solution changes the existing practices (yeoh et al. 2007). 50 table 1 collected key success factors (characteristics) based on the literature review. factor key characteristics references directives and top management committed support and sponsorship from top management continuous support and support from directives directive sponsor, informed and committed active participation from actionist well-qualified managers and managerial teams project that fulfil with the sponsor needs arnott 2008; chan et al. 2013; cidrin and adamala 2011; dawson and van belle 2013; hawking and sellitto 2010; olszak and ziemba 2012; sangar and iahad 2013; yeoh et al. 2006; yeoh et al. 2007; yeoh et al. 2008; yeoh and koronios 2010; olszak, 2016; pham et al. 2016; yeoh and popovič 2016. business linking to have well defined business process and problems strategic bi vision linked to company initiatives align business needs to have well defined business requirements related to information to have well defined business model identify key performance indicators (kpi) involve business affairs with the technical side establish metrics and classifications handled by business side to govern the information handled by business to formulate a methodology and a project management handled by business side to have a theoretical and upgradeable framework managed by business side to formulate a project approach handled by business side well-stablished business case arnott 2008; cidrin and adamala 2011; hawking and sellitto 2010; sangar and iahad 2013; olszak and ziemba 2012; yeoh et al. 2007; yeoh et al. 2008; yeoh and koronios 2010; yeoh and popovič 2016. project leader or “champion” set-up high-level person with business knowledge business oriented champion project champion sangar and iahad 2013; dawson and van belle 2013; hawking and sellitto 2010; yeoh et al. 2006; yeoh et al. 2008; yeoh and koronios 2010. strategy clear mission and vision strategical vision of the bi project business vision clear business plan strategic and extensible technical framework cidrin and adamala 2011; dawson and van belle 2013; sangar and iahad 2013; olszak and ziemba 2012; yeoh et al. 2008; yeoh and koronios 2010; olszak, 2016; pham et al. 2016; yeoh and popovič 2016. change management suitable and effective change management due to bi project user-oriented change management hawking and sellitto 2010; olszak and ziemba 2012; sangar and iahad 2013; yeoh et al. 2008; yeoh and koronios 2010; pham et al. 2016; yeoh and popovič 2016. project project planning to define and manage project scope project that delivers “quick wins” effective project management solutions design solutions design based on the end user clear link between business objectives project methodology project performance competent bi project manager respond to lack of flexibility and answer to user requirements to build a project pilot which introduce incremental changes iterative development handled by business part arnott 2008; cidrin and adamala 2011; hawking and sellitto 2010; olszak and ziemba 2012; sangar and iahad 2013; yeoh et al. 2007. people and human talent teams support from an external consultant in the start phase formal an interactive engagement with participation of the end user during project life cycle. appropriate mixed skills team well defined user expectations balanced skills and composition of the team arnott 2008; dawson and van belle 2013; olszak and ziemba 2012; sangar and iahad 2013; yeoh et al. 2006; yeoh et al. 2007; yeoh and koronios 2010; pham et al. 2016; yeoh and popovič 2016. learning and skills education and suitable and formal user learning easy learning solutions in-site education, learning and support team knowledge and skills committed experience from the business side chan et al. 2013; sangar and iahad 2013; yeoh et al. 2006; yeoh et al. 2007; olszak, 2016. 51 information and technology suitable technology and tools technologies development evolving development set a strategic, extensible and upgradable technical framework contents according to the business high data quality and confident sources sustainability tests interaction with other systems report strategies date government data security effective data management source data systems data and information integrity and accuracy partners for implementation friendly bi system use sustainability quantity and quality of data hardware and software sustainability system confidence, upgradability and flexibility friendly user-oriented technologies solutions fit to user expectations dimensional model of data and metadata use of a test prototype source systems stable in site availability of information department customization devices security authentication device independency usability accessibility connectivity to networks flexibility consistency re-usability functionality support of interactive systems timely reports arnott 2008; chan et al. 2013; cidrin and adamala 2011; hawking and sellitto 2010; olszak and ziemba 2012; sangar and iahad 2013; yeoh et al. 2006; yeoh et al. 2007; yeoh et al. 2008; yeoh and koronios 2010; pham et al. 2016; yeoh and popovič 2016. resources intellectual suitable resources technological suitable resources suitable budget strategic human and financial resources arnott 2008; olszak and ziemba 2012; yeoh et al. 2006; yeoh et al. 2007; chasanlow 2009 cited by salmasi et al. 2016 metrics current system use perceived system utility net benefits obtained user satisfaction use intention service quality system quality information quality nemec 2011; sangar and iahad 2013. environment organizational culture solving of non-technical issues cooperation with bi suppliers based on past experiences cidrin and adamala 2011; olszak and ziemba 2012; sangar and iahad 2013. the project must have a clear link to the business, this way it will be economically supported in terms of its economic value (arnott 2008). according to yeoh and koronios (2010), the main cause of bi solutions failure is not technological but a poor alignment with the business, its vision and objectives. this result in the impossibility of satisfying both the business and the costumers’ needs and objectives. 2.2.3 project leader or “champion” set up this makes reference to a team leader appointment, in a few cases it is the same chief information officer (cio) (table 1). this person must have enough technical and functional knowledge and at the same time he/she must have excellent interpersonal 52 abilities to solve organizational conflicts (yeoh et al. 2006). this makes choosing a leader a challenge as that person will carry the project baton, and foresee organizational challenges and course changes on time (yeoh and koronios 2010). he/she will see the solution from an organizational and strategic perspective, not only technological. if he/she understands both business and technology, he/she could translate business requirements in the technological architecture and vice versa (yeoh et al. 2007). 2.2.4 strategy the fixed strategic vision is summarized in the results obtained by yeoh et al. (2007). their findings suggest that a long-term strategy results in a continuum improvement at an organizational level, and the impact of the solution and the expected results depend on its understanding (table 1). top management must be committed and give the needed support for project success (yeoh et al. 2006). the project must have a vision of bi as well, it must provide needed resources to fulfil it and must insist on the use of information at the decision making process (watson and wixom 2007). equally important are the goals or objectives. it is a fundamental input to have a clear way to which the organizations want to reach. it also works to dispose the resources, actions, processes and everything needed to reach a desired state. although the company may fix it, sometimes there is doubt about their use from the employees in their daily operations (popescu 2012). 2.2.5 change management a change management program is important in the sense that it reduces implementation resistance and in the way that it favors its adoption (hawking 2013) especially when technologies are ongoing, because it is the moment in which there are greater possibilities for changes to happen (hobek et al. 2009; fourati-jamoussi et al. 2016) (table 1). communication is an important factor for the change management. it must appear in the project formulation step so employees can prepare on their own to receive change (hobek et al. 2009) and for them to know first-hand the impact it will have at individual level (hawking 2013). 2.2.6 project the bi project is one of the most important factors, considered to be a key one. the authors (arnott 2008; hawking and sellitto 2010; yeoh et al. 2006; yeoh et al. 2007) claim a marked emphasis in the scope is an important issue for the success of the bi project. with that, the main objective of its formulation, deadlines, advances and final results can be achieved, framed and aligned with the business purposes strategically posted early by the top management (table 1). 2.2.7 people and human talent teams individuals as project members must have appropriate experience, knowledge and skills (arnott 2008; rouhani et al. 2012; salmasi et al. 2016). according to interviews made by yeoh et al. (2007), they showed that experts agreed that team conformation and the skills of people engaged in the project greatly influenced its implementation success. it is ideal that participant teams are composed of people from diverse areas, who have technical expertise and a deep business knowledge (burton et al. 2006 cited by yeoh et al. 2007) (table 1). 2.2.8 learning and skills it is important that organizations provide workers with the skills and knowledge to use the bi solutions (mccalister 2012; arnott 2008; wixom and watson 2001, cited by chan et al., 2013). taking into account that this kind of project demands high technical engagement, it must dispose a team that gives support and more precisely training in order to educate and shape everyone about the bi project (adamala and cidrin 2011; olszak 2016.) (table 1). that team can be shaped by people supporting both the technical and human parties. based on this training it is important that people give feedback about their experience since they will continue to use the bi solutions (bălăceanu 2007; muntean 2007). learning tools enter here to mediate. they must be offered and disposed to acquaint people with the new solution environment, since human behavior related to decision making is not generally aligned with tools capacity (feng et al. 2009). 2.2.9 information and technology this key success factor is one of the most used in bi research, since it is focused on 53 architecture, software and tools development and tangible elements whose impact is reflected in practice by its operative characteristics (loshin 2013). according to yeoh et al. (2007) the first step is to do a requirements analysis whereby a solution can secure the shape of organizational conditions over the time. as second step that analysis must conclude in a match between organizational needs and their alignment in the company’s strategic framework whereby it fulfills the proposed objectives and posted vision (knoben and oerlemans 2006). a third step is related to information management, established sources and articulation of needed means, for instance strategic and tactical integration with other tools like bpm (business process management), which offers innovative solutions to decision making (linden et al. 2011), policies for processing and processing information. not estimating the magnitude of unsolved information problems generally resonates in a project failure (rosado and rico 2010). choosing a solution is the last step; it should be matched to the organization’s needs (arnott 2008). it must require a detailed plan formulation. if the organization is supported only by tools without a plan, purchasing solutions will become a distraction to the proposed goals (loshin 2013) (table 1). 2.2.10 resources generally, this factor is seen from a clearly economic view, mainly for the top management which assess this kind of project through costbenefit relations. while it is not a mistake, is clear that intellectual, economic and physical factors have equal weight within a bi project since suitable handling and engaged management are key to real and verifiable benefits (hobek et al. 2009; yeoh et al. 2007) (table 1). 2.2.11 metrics metrics are always important to know projects results and in this case, it is not an exception. following the research proposal of nemec (2011) based on a literature review focused on delone y mclean studies, dimensions posted by these authors in their information systems success model can be seen as key factors when a bi project is assessed (table 1). nemec (2011) formulates issues like benefits, utility, quality and satisfaction, which are perceived by users as influencing elements in a bi solution’s success. it will result in relevant information about acceptance and real use that could be obtained by the project. 2.2.12 environment organizations that do not have information to process, need information systems that can improve that situation and give them a better understanding about environment forces, with which they can improve their performance by producing and using useful information (sangar and iahad 2013). based on results from a big survey, watson and haley 1997 (cited by yeoh et al. 2008), stated that critical factors for bi project success are organizational by nature. with a key success factor framework, engaged stakeholders can identify those necessary elements to improve efficacy and efficiency of planning and implementation activities, understanding the background, which is conducive to bi project implementation to success (yeoh et al. 2008) (table 1). 3. research methodology the methodology used is the multi-methology proposed by mingers (2006), which follows the phases: appreciation, where document search is conducted through a literature review; analysis, where hypothetical structures related with the key success factors are proposed; assessment, where key success factors are assessed along with experts; and action, where research result discussion is shown. 3.1 literature review bibliography and references search were conducted in: scopus and web of science and in a small amount in google scholar. indexed journal articles, conference proceedings, book sections and corporate reports on bi were collected. it was conducted by equations restricted to databases: ebscohost (business source complete and academic source complete), jstor, emerald, ieee, science direct, springer journal, springer books and taylor & francys. once documents were obtained, a detailed check of abstracts and keywords was done to corroborate the material’s relevance to the research. table 2 shows the process outcomes. a total of 12 documents that explicitly treat the topic key success factors on bi solutions were found. 54 table 2 search and document outcomes. table shows the equations used to retrieve important information to gather documents on the topic: “key success factors” in business intelligence which were applied to the database search. search equations ((critical (or) (+) key (or) (+) csf (or) (+) ksf) and (success (or) (+) factors (or) (+) success factors) and (information systems (or) (+) business intelligence (or) (+) competitive intelligence (or) (+) information (or) (+) bi (or) (+) ci (or) (+) it)) documents finally worked academic corporate total 11 1 12 3.1.1 document codification according to serbia (2007), a topics analysis was conducted. by using the nvivo10 software, it was structured as: a primary node with the topic key success factors on bi and twelve secondary nodes, ten of which are matched with the referred authors. similarly, twelve tertiary nodes that represent the main identified factors according to a systematic literature review on this topic were formulated. this structure was established taking as reference the topics analysis conducted by fernández núñez (2006), referring to free text analysis through key words in context (kwic) to proceed to codify the contents on those nodes. next, this node structure is presented (figure 1). the discontinuous line refers to contributions and its complement of author and exposed factors. 3.2 information collecting interviews of seven experts in the field who have participated in research or figure 1 node classification of key success factors on bi articles. this shows the node structure that is presented for the topic “key success factors on bi”. the discontinuous line refers to contributions and its complementarity of each author to every exposed factor. 55 implementation of bi solutions were conducted (table 3). according to morse (1994) and kuzel (1992) cited in guest et al. (2006), a suitable number of interviewed participants in a qualitative study ranged from 6 to 8 people. other studies (fairer-wessels and malherbe, 2012; fusch and ness 2015; mason 2010) argued that despite not having an ideal number of participants, saturation of information is a good stop index. each interview was made up of 30 questions (appendix 1), two general questions to begin and end with a closer and conclusive conversation and 28 more focused on key success factors identified on literature that was exposed early on. based on the application, interviews duration ranged from 35 minutes to 82 minutes. six were conducted in person and one on skype. table 3 experts participating in the study. this summarizes the main information about the experts who participated in the research. it contains basic information like degrees and practical and academic experience. note: the distribution number is based on the order in which experts were interviewed, so this is not an important or significant factor in this research. no. position education experience means 1 director information technologies and communications dntic un systems engineer and master in systems engineering he has worked in the bi solutions industry for more than 25 years, 10 of which he worked as businessman and partner of a firm with which bi projects were designed and implemented in colombia and central america. he has been consultant and lecturer (outliner) in bi graduate courses. personal 2 professor national university of colombia mechanical engineer, telecommunications engineering specialist and master in systems engineering. 20 years of experience in bi. he has worked with companies like latino bi with the product cognos in both, academic and industrial fields. he teaches bi subjects and works jointly with bi vendors like ibm and oracle, developing events of presentation of solutions and consultancy by those vendors in the university. personal 3 professor konrad lorenz university economist, statistical specialist, master in administration and phd in industry and organizations bi analyst for ‘casa editorial el tiempo’. also, bi and marketing research director in the ‘new means and transactional portals unit’ in the same organization, bi consultant and professor. personal 4 professor university of the andes systems engineer, master in systems engineering and phd in informatics more than 20 years of experience in bi topics, data warehouses, physical designs and etl in different sectors. she has served as project intervener, consultant, adviser and professor mainly in subjects like bi and business analytics. personal 5 bi manager philips mexicana business administrator, marketing specialist and master in multinational administration she has worked in the bi field since 2011 in worldwide companies like jhonson & jhonson and philips mexicana in data analysis as specialist and manager. she jointly works data analysis and financial analysis topics. skype 6 senior analytics architect cross unit ibm colombia s&d systems engineer and master in systems engineering latino bi partner jointly with cognos corporation and procalidad, working on bi projects for companies in colombia. cognos partner for spanish companies. he worked with cognos corporation developing projects in latin america. since 2008 he served as specialist and architect in bi solutions, statistical and predictive solutions, operative and financial risk solutions and fraud solutions at ibm. personal 7 business intelligence project director on data s.a. systems engineer, emphasis in organizational information systems. certificate in management of information systems she has served in bpm and bi as well as software quality insurance. software quality leader and bi project director for on data. she focuses in planning, development and implementation of bi solutions for important companies both national and international located in colombia in different sectors. personal 56 3.3 information analysis interview processing was done with the nvivo10 software based on a word frequency query applied to the seven documents of the interviews. it was a primary landscape of terms and keywords that were important in context, which were coincident with the early identified factors in the literature on key success factors in bi. with those terms a node structure was generated to classify and group information obtained from interviews. table 4 shows the node classification and denomination that was used in the interviews processing. table 4 node classification to interviews analysis. this shows the node classification and denomination that was used to the interviews processing with the nvivo software. name resources references 1. directives and top management 7 20 2. business linking 7 25 organizational structure 7 12 central control entity 5 7 3. project leader or “champion” set up 7 24 4. business strategy 7 13 5. change management 7 17 6. bi project deployment 7 25 requests 4 6 7. people and human talent teams 7 22 people 7 14 trust 5 9 collaboration 2 8 communication 5 8 coordination 4 5 engagement 3 4 cooperation 3 4 8. learning and skills 7 33 9. information and technologies 7 45 10. resources 7 35 economic 7 9 intellectual 7 9 technological 7 17 11. metrics 2 2 12. environment 3 7 argumentations 6 19 table 4 shows the number of resources that were linked to the codification, which range from 0 (when no resources allude to each factor) to 7 (the maximum number of documents of experts interviewed). likewise, it shows the number of references (codifications) made for each considered node. almost all of the factors achieve the maximum number of resources, which means that most factors were treated by the experts in the interviews. after identifying the primary and secondary nodes based on interviews, one-by-one-factor analysis was made. pieces of interviews were taken to support the exposed ideas and outcomes as well as a text matrix summarizing the experts’ arguments that support the outcomes. according to the gathered information from the experts, a general structure which characterizes success factors in bi solutions in organizational environments was posted (research results). this structure is aligned and matches with the reviewed literature and is a product of a detailed content analysis of conducted interviews with the nvivo10 software. 3.4 proposition of hypothetical explicative structures to study the phenomenon according to the identified factors from the literature, a single applicable hypothetical structure was formulated for each factor: hs0: the identified factor does not affect the bi solution’s success hs1: the identified factor affects the bi solution’s success 4. research results from the topics analysis of conducted interviews, results show that twelve pieces of literature identified factors that are consistent with experts’ perceptions about bi solutions success, adding the professional networks factor according its importance to the experts. figure 2 shows the obtained results. figure 2 shows the importance of every factor to the experts based on keywords attributed to each one, depending on the context in which each keyword was used by the experts. it should be noted that for this analysis 25% of the interviewees’ transcript in the interviewed documents was used. words or elements with less importance (which did not have a strong enough consistence to constitute an independent factor) according to this 57 analysis, were classified within the thirteen posted factors. the next part focuses on presenting detailed research results after making an analysis of content based on the codification. table 5 summarizes some of the experts’ arguments taken from the documents of the interviews in support of the affirmations. 4.1 directives and top management success factors according to the experts there are four important characteristics around this factor. as a first step, making a decision about developing a project or implementing a solution is a top management affair: a manager, an owner, a steering committee or, by default, a third party with influence at the managerial level. all this leaves aside suppositions that the decision is made by organizational technology areas, as is commented on by the experts. a second step is the deep knowledge about the request. a manager or top management executive of an organization is who decides what he/she needs. although it could lead to misrepresentations and, sometimes, to incorrect bi project conceptions and developments due to the power or the political position these people may have within organizations, bad decisions could be made with expensive and useless projects, and may also discard more useful and viable projects because of individual decisions. the third characteristic is the existence of a sponsor who is going to authorize and fund the idea of developing a bi project in an organization. the future of this kind of solutions depends on the top management’s credibility since they will provide resources (mainly financial) and will sponsor efforts to achieve their objectives and goals. finally, handling of power and politics plays a fundamental role. it is evident that when experts say that these are projects focused on the top management, which is political by nature, forces that go beyond single decisions, requests and social relations are played. for instance, there are deep-root personal interests when there is a pursuit for personal favoring or figuration. in spite of that, it may be a positive point since it helps to analyze engaged actors in the project, and by this way to determine the best way to reach them, taking into account that there will always be detractors and followers with different levels of power and influence. 1043 848 607 481 454 301 188 160 127 109 95 68 61 bi project deployment people and human talent teams information and technologies business linking learning and skills environment resources directives and top management project leader or “champion” set up metrics business strategy professional networks change management frecuence in interviews (allued to factor) k e y s u cc e ss f a ct o r figure 2 importance degree of key success factors of bi solutions. shows the importance of the thirteen identified factors to the experts based on keywords attributed to each one, depending on the context in which each keyword was used by the experts. 58 table 5 expert’s arguments regarding to identified factors. this summarizes some of the expert’s arguments taken from the documents of the interviews as support of the affirmations made within the article. validated factor contributions by expert e1 e2 e3 e4 e5 e6 e7 directives and top mgmt it has got to have the top management’s credibility and sponsorship or neither buy nor install. (...) directive is who says what he/she needs. simple! put the request [projects] sometimes it depends a lot on directive’s strength if they are not convinced of benefits, it has little success probabilities you have to buy the idea 100%. if the initiative does not emerge from them, you should get a good sponsor with good influence nowadays there is not bi initiative if it does not come from a directive or vp manager contact us, we make him an offer and he is who say if products are bought or not business linking [important] is what concerns with indexes, objectives, goals and monitoring. it is the opportunity to accompany the business. enterprise structure is determinant especially for functions and responsibilities the system must adapt to the organization as well as the organization to the system (…) you start by understanding the sector in which the enterprise is into. you understand the business and then needs and opportunities you need to know what works, what doesn’t work, and what you want to improve. you have to define a strategy, where it goes to, what you want to get and how, how much you want to bet and what will be the earning. you cannot implement anything if you do not know the business and customer’s needs. project leader or “champion” set up generally all projects need a manager, particularly in informatics projects projects managers or project leaders have a different scope depending on their selforganization this is a person who have to survive between daily fires and technological stream adoption it is required, you have to have a specific leader there. it is mandatory needed. he/she must be from the start, and, generally, it does not work with a single person, but with several leaders it is a role which is totally indispensable business strategy implementation supports strategy if i fix a strategy, i have to carry it out. it is just what makes a manager or a leader. to the extent that the environment changes, strategy changes it is necessary to know what the business strategy is, weaknesses and strengths [to know] where it goes to everything have to be routed to strategy this project does not exist if there is not data, people, technologies and business strategy. who buy our products and services are not it areas but strategy and decision making areas. change mgmt in any project and generally an informatics project, change management is needed sometimes changes are due to a greater control and it does not like to people i think there is a change resistance given more in a group than at individual level. first i need to start evangelizing people regarding to what this is. it is the main barrier, as i told you. human resources are needed to operate all this kind of solutions and an important process of change management is needed as well. we are in a great paradigm shift which is to leave the power point to use tableau bi project deployment all informatics project needs planning. (…) with that you can fix needed tasks, schedules and resources. it implies a process organization, planning, collection, control and infrastructur e to generate data. there is a follow-up, from business and the technical side. posing how to conceive and how to implement. from the beginning you need to know what you are looking for. we assemble role pyramids: manager, technical leader, functional leader, solutions architect and consultants. this kind of projects does not have neither a beginning nor an end, has a continuity. people and human talent teams people who belong to a functional area are going to be engaged within the solution. a single person cannot make everything, but the whole team can know about all of them who are needed. a topic that is important for me is the forces’ organization or work teams around this kind of projects. he/she might not have the experience but he/she may know where people who have it are, and it helps the project to be more effective. if you have well assembled a team than can implement and execute, they really could work better or worse with one or another technology. [they are] vital because if not, project tend to fail team support makes valid why i am the projects’ director, for instance. learning and skills in bi solutions value creation is you need to train people learning is given at the in the extent they technologies help you and it is necessary to start doing agreements are 59 validated factor contributions by expert e1 e2 e3 e4 e5 e6 e7 so evident, it makes all people get engaged. and remove their fear to the obstacles. slowest person pace, this to avoid barriers in the process. understand, information is obtained and a set of requests is collectively built. facilitate learning. knowledge transfer works. fundamental. training, consultancy. information and technology solutions are not expensive per se, they must be seen in a cost-benefit way. solution choosing depends on costbenefit relation. by using technology you can do whatever you want, good and bad, it depends on how you look at this. technology is able to make a lot of things, even imaginable things. you have to change perspective about “this” is only technology nor just to buy a software, a hardware or to make a databases, etc. i think that we are still in the first maturity levels in the adequate information treatment. i think that tools are as good as information you enter, so you have to start with that. there is a lot of information. it depends on what it is needed to the project and the working area. obviously there is a strong relationship, but there is no conditionality, that is to say, you do not depend on any technology to make anything. prof networks value creation is so evident, it makes all people get engaged. it is so important that now all what is about networks, it is an input. here i talk about professional and social networks. external consultants and competence are the most important actors in that network. the more you go expanding your circle, the more you enrich your learning. it helps you a lot if you are leading a project. you receive opinions about how to implement or how to carry out the systems. i look internally to see who has the skills to do it. or externally, and see how experienced they are. that is how my network gets bigger. network is outsize and united, and i think it is valuable to know about what the others are doing. resources to acquire a solution, a costbenefit analysis must be done, it implies resources. it must be allocated since the project planning stage. there must be people with intellectual capacities. online social networks are an important resource. if i would have to decide, i would choose intellectual resources. i greatly appreciate technologies but they are just tools. solutions must be upgradable in all senses. there must be agreements with suppliers. metrics indexes allow to measure goals achievement, these allow to measure objectives achievement and objectives allow to make strategies. when i have a decision, i do not think about what my heart feelings and my experience say, but i have a support on some indicators. the project must have clarity about what results it targets and what are its kpi and its performance indicators. one of the problems from the technical side is that you get indicators and deliver that, but, does it have any sense? you can measure all of your kpi with one or another tool. it facilitates your life and makes it fast. i must take into account those indicators to which i want to reach and how i get it. to be perceptive about what you have to sell: what generates value. which indicator you can set. why do not to formulate a metric? environment now there is a globalized world because the sources, the sizes, the ways to work and the approaches are different. paradigms have changed. then notice that is not only that but all the environment. the project must not change if environment changes. if you do not take into account organizational culture when you design a project like this, it could be a problem or a critical success factor of your project. value chain has to be transversal, it must have an amazing synergic to get this really arisen. 60 4.2 business linking success factors business linking is the starting point of any bi project. there is a consensus among several experts around the first-hand knowledge of the kind of business or organization and, derived from that, the sector in which it operates, activities developed by organization and, in itself, its position in economy. furthermore, addressing business strategy becomes the second essential element in this factor since it represents the mission, vision, strategies, objectives, needs and, generally, all issues than have led the organization to think about a bi solution. based on that, further actions can be determined in order to make a more optimal and efficient project. this factor is the roadmap to project development since it sets a frame to follow according to the collected information that characterizes conditions in which an organization operates both internally and externally. thus, subsequent actions can be stated to achieve results and fulfil the initially posted goals which justify the bi project development. 4.3 project leader or “champion” set up success factor it is vitally important to establish the project leader role. as experts stated, it is not reduced to a person but a position regardless of its denomination. they also emphasize the strategic importance that this role has within the project development. this person is integral at technical, operative and personal levels. they must always be at the knowledge vanguard in favor of the bi project, and guiding all participant members according to that acquired knowledge and experience, not only technically but professionally and personally. he/she must be influential in order to persuade other people of the benefits and the individual role within the project. equally, he/she must be strategist at forming teams and groups in such a way that he/she exploits individual and group capacities for the common benefit. he/she must be a person with values, always transparent to avoid influences from the top management or the operative side, understanding each one. this person will be in charge of negotiations among the parties involved, both internally and externally, dealing with problems and situations derived from the development and execution of the project. this person must match efforts through technological, intellectual and personal resources coordination, exploiting individual capacities, serving as a central project axis and propending for centralization of activities and delegating responsibilities to all participants. 4.4 business strategy success factors as a first step, business strategy works to align input between project development and its proposed objectives and its implementation. as expert 5 says “all has to be routed to the strategy. that is why it also has to be aligned with the top management, it will be the primary line”. what is the importance of business strategy for a bi project? in the words of expert 6 “any process and in this case a bi process, it is part of a strategy. the first thing to define is: what is going to be the strategy? what do you want and where do you want to go to? what are the goals and objectives you want to achieve? that is the first thing you have to establish. then you define a plan: how can you achieve that?” it indicates what works as a support factor for the organizational processes. in relation to the above, expert 4 states that “it is required to know what the strategy of the business is, weaknesses and strengths to know where it is oriented” it summarizes that the business strategy factor works as a diagnosis tool, allowing one to know what the initial situation is without bi project, and what the desired state to reach with the project is. business strategy is not static. thus, it is also presented with a factor of dynamism. according to the experts “there must be clarity that strategy is normally emergent” and it is dependent from the organizational environment, “to the extent in which the environment changes, strategy changes” otherwise the expected results could not possibly be achieved” states expert 3. it is evident that business strategy becomes a guide and at the same time a driving force that promotes the planning and implementation of a bi project, specifically its execution since the project will match the initial requests posted by the top management and the other people engaged. 4.5 change management success factors it is a linked factor to the organization’s culture in which the bi project will be developed. according to expert 1 “there should be an early and simultaneous preparation. in any project, 61 generally an informatics project, change management is needed. more in business intelligence. you need it as a key success factor to technology implementation” fear of change, as in any daily life situation, is present in this kind of project. linked to that, the perception of bi tools in the project as a means of control, makes users and affected people in general take negative attitudes towards the bi initiative. added to that, reactivity to carry out new processes and change the ones that exist, along with people’s perceptions about being replaced by technical tools, reaffirms negative perceptions regarding actions in the bi project. although the above is not positive for the project, positive perceptions are also found at the moment of managing the change. according to the experts’ opinions, to innovate with a bi project in an organization allows the organizations to optimize processes that were tedious before, improving developed activities and achieving better results. likewise, there is the perception of specialization, which gives the person an image opposite to which he/she can form based on the established organizational culture, receiving benefits and learning new ways to perform the same processes. 4.6 bi project deployment success factors according to the interviews with experts, the word project holds the first use-frequency place (number of times it is repeated within the texts) by experts interviewed. it is no wonder, since it is the most important part of a bi solution. it includes in detail all issues, from the beginning to the end, being the center of all activities. consistent with the experts, the first step to follow must be evangelization and engagement of all of the actors who are going to be immersed in the project. in order to make them participate in its development, one must take them into account and show them the importance that it is going to represent to both their individual work and the organizational processes. this is achieved by training, meetings and constant and accurate information exchange. at a general level, the bi project must start by setting its scope, thus, the relevant actions to formulate the project in detail should be set. that scope must obey the already set business requests mentioned, which indicate the need and relevance of formulating a bi solution, taking into account the expected goals. once those elements have been established, next one must undertake the project planning, which will determine in detail the schedules, tasks, and necessary resources (economic, intellectual and temporary) as well as business processes that will be engaged to achieve the goals established. equally important is the responsibilities and role distribution for the process development. within these business processes, experts ensure that is important to detail issues such as: planning, and data collection, structuring, control and quality, as well as infrastructure, feedback and environment adaptation, continuity of activities and their follow-up. the latter is very important since it must be seen from three different points of view: business, technical and analytical, always guaranteeing business continuity. 4.7 people and human talent team success factors although social relations present difficulties due to their dependence on emotional, cultural and personal factors, among others, bi solutions are developed in environments where everyone has their role, responsibilities and an awareness of being part of a team that aims to achieve the agreed objectives. the work team and the experience that members acquire are essential elements when developing a bi project. based on this, the knowledge building, meanings and experiences that will benefit both individuals and organizations are important. similarly, it is shown that the work team and its composition are mediated by six characteristics that could grow or limit its performance and development: collaboration, engagement, communication, trust, cooperation and coordination. collaboration is the first characteristic. according to expert 6, along with coordination, “[they are] vital because the project could tend to fail”, it must be immersed within the project from the conception because “[within] the plan there must be all details of collaboration strategy in different fronts” in order to know where you want to go with that collaborative work, and who must participate. the second characteristic is engagement. according to expert 2, “engagement [must be] formal, formalized engagement works well because when it does not, it ends badly. [it] is the first thing to be workable, to have engaged people. when people are engaged, they will 62 surely be responsible” but that is not so easy in practice because “engagement is usually too low since we are hunters of opportunities and to the extent in which we find a better one, we will go behind it” stated expert 3. communication appears in the third place. it “has to be open” said expert 6. according to expert 5, everything that happens, regardless of the kind of information, must be communicated. “(…) it is conveyed alike, if there is a day i do not inform people, small or big things, they work well or not” problems could appear, so “[it] must be as transparent as possible”. trust is the fourth characteristic. as expert 4 states, “is an essential element”, also for expert 5 who comments that “it is indispensable and it must be totally transparent in order to achieve integration of all engaged people in your project”. as expert 6 states “trust has to be vital, because everything that will be implement from the bi point of view is to improve the business”. the fifth place, and not the least important, is cooperation, which is essential because of the interdisciplinary nature of bi projects. as an expert states “if we do not cooperate between business, technical and analytic parties, it will be a failure” which is shared by another expert who states that “cooperation is important because these kinds of solutions or systems are naturally made for several working teams, they are not made for a single person”. indeed, cooperative work ends up being synergic by nature. finally, coordination is the last characteristic. this one “goes hand in hand with activities and responsibilities of each one and how i coordinate myself, with my pairs, my partners, to achieve the common goal, what is expected from all of these implementations” states expert 6. it is “one of the needed skills for a person who wants to be on bi” remarks expert 5. besides those elements and characteristics that are present in the teamwork, there are other cross constructs in group activities which are essential to the job. those are: involvement, empowering and participation which depend on organization of individuals. 4.8 learning and skills success factors learning processes, according to experts, are generated at several levels. first, at a macro level, in which there is a conception of value generation for collective learning. thereupon, there is a meso level, which is referred to as the existing relationship with external agents who foster learning through practices and knowledge that are initially foreign to the organization. finally, there is a micro level, which involves technology as a tool or a way to learn and apprehend knowledge in a suitable environment. that environment counts on issues such as the individual insertion within the project, involvement, constant communication, a continuing information flow to get feedback and improvement, and a practice and operation stage that will work as a foundation to gain knowledge and then create new knowledge. to promote that learning, an individual must possess certain types of skills, which make him/her liable to get and generate a specialized knowledge within a bi project. both technical and non-technical skills shape the set that will give a result of specialized knowledge and learning in the field. according to expert 3 “people’s skills in all levels are very heterogeneous” and likewise “they will depend on the role that individuals have within the project” states expert 6. in agreement with what the experts say at a general level, it is important to have technical and non-technical skills that carry them to be “people with a lot of negotiation skills, they must know how to listen to the internal client’s needs and have an open attitude, they have to be very analytic people that solve conflicts” affirm expert 5. concordant with that, they must “learn and apprehend” and “develop the ability of questioning, this for them to talk the same business language” state experts 3 and 4. on the other hand, it is necessary to have certain technical skills “which are related to structuring and designing a project of this nature. that is done by specialized people in bi”. according to expert 1’s opinion. “if the part of models is worked, analytic models, statistical models, [there] must be a person who has this skill, this knowledge; a person who does not know about it cannot be there” concludes expert 6. according to expert 4 it can be summarized in professional and cross skills, which allow one to understand a business situation, give a suitable use and interpretation, and thus “[be] able to carry this business request to a specific technical request.” 63 4.9 information and technologies success factors one of the essential inputs of bi solutions is information. according to the experts, it is more important than technologies because it could take the second or even third place when it is about seeing the importance of the component of the solutions. although data and information that could be generated are abundant, experts agree that information depends on the kind of project to be handled, for instance, financial projects, marketing projects, or human resources projects. with that, the kind of structure and design needed for its development can be established. to have access to that information, the first thing is to conceive the study and design access roles. not all users have the right to access to the same information and equally it must be ensured that the information they can access is pertinent to his/her task development. it happens to both internal information and external information coming from suppliers, customers and all related stakeholders. however, to discern, use, analyze and get meaning from the information obtained, an operation by using technologies is needed. those depend on the project scope, size of the organization, purposes, available resources and all elements analyzed above in the success factor of the bi project’s development. according to the experts, technology does not take a privileged place when thinking of a bi solution because it is only a tool that gives options and facilitates the development of actions that could not be done without it. in the words of one of the interviewed experts, there is a “very strong relation, but there is not conditionality, that is to say, it does not depend on any technology to do anything. not even on the use of excel [since] you can do an analysis generated by the experience, an industry analysis [for instance] with the simple fact of knowing how many new clients came”. it is concordant with the opinion of a second expert who says “they are marvelous but sometimes are overvalued, i can tell you that there are bi projects that perfectly work with excel”. according to expert 6 “whether it is wanted or not, technologies are important. (…) those tools exist for any reason, they are made for a different type of requirement”. those tools “must possess both functional and nonfunctional characteristics”. they must be also intuitive, friendly and accessible, as much as possible, always thinking about the users. as expert 1 states, maybe the most important issue of those technologies must be their usability, since “it must be addressed to final user, not to the informatics technicians”. likewise “they are made to be a tool for the functional areas, not only for technicians’ use, it is not a tool for the informatics area, but from this area tools are enabled to be used by final users”. technologies in bi solutions must work as learning tools in order to improve skills and facilitate issues such as communication, relationship consolidation and the strengthening of organizational processes. they should be used as complementary tools, generating timely advantages, even when it is only a supporting tool. this must be done without omitting key issues such as security and the collaboration developed jointly with new information technologies. it must be taken into account that technology, regardless of it costs, brand or reputation, must obey a need and must work under a cost-benefit logic, regarding the organization’s needs. “tools are as good as information you enter, that’s where all should start” states expert 5. “its investment will depend on its future return” argues expert 1. 4.10 professional networks success factors despite the fact that “professional networks” is not one of the most used terms in the experts’ speeches, it is also one of the key success factors for bi solutions as it could be observed. this is based on statements made by the six interviewed experts, who agreed that the fact of belonging or keeping up with what happens in professional networks, more exactly about bi topics, potentiates some faculties for professional and personal development in order to get more successful bi projects and solutions. according to the collected information, six features that characterizes professional networks as bi key success factor could be observed. first they work as input sources for the project development because they find information from third parties, which could complement specific project developments, according to their characteristics and past experiences. as a second step, an element to overcome obstacles is used, allowing one to beat possible personal and organizational barriers presented during the development of this kind of project. 64 linked to the above and with a remarkable importance, it works as a synergy source, meeting and centralizing the resources available in the network to the project benefit. this, taking into account that complementary visions could be reached, and concepts, roles, experiences and resources, among others, could be shared. an enrichment source is the fourth feature, having access to information and resources which allow a continuing learning and updating, based on interactions with third parties. similarly, resource sources that provides knowledge, human and intellectual capital, both internal and external, depend on the organizational needs and itself the bi project through collaborative work. finally, an associated source achieves the constant articulation and communication among parties which will contribute resources, source and whole network quality improvement. it is important to mark that this feature goes hand in hand with communication and tracking to have knowledge about activities that other parties, which belong to the network, are developing. 4.11 resource success factors 4.11.1 economic resources as expert 1 states, bi project or solution choice is based on a cost-benefit relation, for him “a solution is not expensive by itself, it must be seen in a cost-benefit context. solution choice depends on this relation”. although this topic is sensitive at an organizational level since it involves monetary resources, it is essential when working on a bi solution. as expert 2 states, “those are resources that must be used from the [project] planning stage” because “when there is money involved, the first word is always not. second is for what?” states expert 5. expert 3 asserts, “these kinds of projects are not usually cheap and enterprises are prevented because they have invested a gross quantity of money and do not see quick incomes”. this makes it more sensitive because when immediate results are not seen, bi solutions begin to be seen as great investments without any contribution or earning. regarding this topic, expert 6 affirms that it is viable to have two concepts of financial resource planning in the projects. as a first step, top down planning could be set “where [you have] a budget, a resource and [you plan] from that, trying to see what you do with what you have”. the second option is the reverse, a bottom up plan where “a series of plans and strategic initiatives are defined and consolidated, then give as a result a money quantity and then you see and look for funding, where money comes from and what to do to guarantee this resources”. 4.11.2 intellectual resources according to expert 3, “there is not [any] technology that works without the human element and intellectual capacity for processing and analyze information. you could have marvelous systems but if you do not have people behind it, who have the capacity to exploit it to the maximum, there is no way to make it work”. meanwhile experts 1 and 2 state that “when [there] is a project, [it] is necessary to know which experts [are] needed to be involved” given that and to develop it, “a specialization is necessary (…) [since it involves] specialized people in the bi field, [which] cannot be done by anyone, that is why there are firms specialized in bi”. it makes evident the importance of the kind of requested resource, facing also that it is “a fundamental intellectual resource, [which makes it] so difficult to get an expert person in the field”. as a conclusion and as experts 4 and 5 affirm, “if there is a well-formed team which can implement and execute it, they really could work better or worse with one or another technology but they will carry out and will get the best from that. if you have the best technology but you do not have the people who could carry it out, it will not work” therefore “you need the technology knowledge and you need people who have the knowledge around it”. 4.11.3 technological resources according to expert 6: “a technological resource is important because it often determines the success or not of the bi initiative. (…) it is not the same to make it with a software, product or hardware resource of low performance, poor upgradeability which does not have the capacity to grow in a corporate environment with all of what it involves: security, versioning, collaboration and all corporate issues you could have, compared with a tool that gives us this kind of possibilities”. it is concordant and it goes hand in hand with the affirmation of expert 7 saying that “technologies will be used, it should be the best existing in the market” and it is advisable that “a project like that (bi project) must have an alliance with infrastructure organizations, because [it] needs servers, machines, etc.” with 65 that you get constant updates and avant-garde technologies are promoted. in this point, online social networks (osn) are presented as “a still well-unexplored field”, expert 4 states, and adduces that: “there is an opportunity. (…) one of the current trends is: why do we not take advantage of that which is in social networks? why do not we bring it and transform it? since those data exist there, why do not we transform it into knowledge for the organization? although osns were not considered to be a key success factor in bi solutions, they are involved at the time to think in sources, data handling, etl, market analysis, brand perception and generally, issues related with marketing, as experts said. 4.12 metrics key success factors according to information gathered from the experts, metrics allow one to fix goals and to know where to go with the project development or what one wants to achieve. accordingly, indexes allow one to do a follow-up of the project development, showing results based on the initial goals. metrics also allow one to determine behaviors during the development and execution of the project, which allows them to handle it in less uncertain environments, and establish proactive and reactive actions. it allows the organization to identify the degree in which objective fulfilment has been achieved and thus the achievement of dependent activities of the strategy that gave rise to the project development. they are also immersed as management tools as part of the advanced reports or the project’s results, and this works itself, supporting the management decisions based on real and consolidated information backed up by reliable systems or technologies. this success factor is key as a management tool since it allows one to analyze, diagnose, preview and make decisions in favor of the project development in order to be successful. 4.13 environment key success factor this success factor refers to the conditions that are inherent to the bi project during its planning, development and execution on behalf of both internal and external environmental factors, which have influence and direct involvement in the project activities and the people involved in the project. since environment is changing, project condition must change as well according to new demands. it is part of the paradigmatic rupture of always doing things the same way. as is evident in interviews, bi solutions, by engaging a set of processes and new or improved technologies, present a resistance on behalf of individual and/or the group culture that is formed at an organizational level, or by the sum of the individual cultures that generate environmental conditions both positively and negatively. these environmental conditions, despite the fact that they generate barriers, also generate benefits as joint problem solutions on behalf of positive issues formed by the organizational culture. factors like founded organizational structure are influential in solving problems, since bases of personal and group relationships that operate through past experiences have been settled. 5. conclusions up to now, academic research on the key success factors of implementing bi systems were still rare, limited in the scope of analysis (pham et al. 2016) and poorly understood (yeoh and popovič 2016). although bi solutions try to focus on success in the technological component, they adopt an approach that puts business needs first (yeoh and koronios 2010; yeoh and popovič 2016). thus, bi solutions must be part of the company strategy, managed in a centralized way, involving all users from the first initiative, appropriating skills and suitable and needed knowledge. research exhibits 13 factors that contribute to improve the success rate of bi solution implementation. these solutions must involve a sponsor from the top management, permanently developing and adapting the expectations and challenges that face the organization, providing training as well as human, material, technical and economic resources needed for its development (olszak and ziemba 2012), all aligned with the strategy and the environment in which the organization operates. when all of these elements are identified from the beginning and are used as drivers for the implementation effort, there is a greater probability of success in the bi solutions implementation (yeoh and koronios 2010). although this literature review identified a total of 12 key success factors for bi solutions, another contribution from the research was the professional networks key success factor. this has emerged due to new trends in practice communities, a disseminated access to 66 knowledge and the narrowing of the professional ties among professionals from different or even the same industries or economic sectors. for further research, this work may involve a greater sample of experts that allow for a more detailed analysis by economic sector, industry and likewise by distinguishing the kind of affiliation (public and private). also, it could include participants who participated in projects as final users, since this research was developed based on experts who participated as implementers or were part of the top management team that was not necessarily implied to be a user. 6. references adamala, s., & cidrin, l. 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(2016). extending the understanding of critical success factors for implementing business intelligence systems. journal of the association for information science and technology. https://doi.org/10.1002/asi.23366 appendix 1 conducted interview to experts objective: to explore and to know about experiences that have had people considered as experts due to their academic and practice knowledge in business intelligence solutions implementation. general question 1. please shortly tell me about your professional and academic background regarding business intelligence and implementations of this kind of solutions. top management and directives block questions 2. how do you think people of top management influence on this kind of implementations? 3. how has the communication between top management and the rest of organization’s people at the time to think in this kind of implementations been? 4. describe in a single phrase the role that the next factors play between people and top management at the time to make bi solutions implementations: a) trust b) cooperation c) coordination 5. how do you think power or people political influence impacts on the bi solutions implementations? business issues block questions 6. how do you perceive the influence of business in the bi solution implementation planning? 7. likewise, how do you perceive the role of technologies and information inside the business issues? “champion” block questions 8. how do you perceive the idea of establishing a leader of the project for the bi solution implantation? is it necessary? 9. how do you think the engaged people’s trust is influenced by the fact of having a leader figure? 10. how do you perceive the influence of a leader within the negotiations that there may be among people involved in the project? strategy block questions 11. from your point of view, what is the role of the strategy in the project planning? 12. how do you think the adopted strategy to the bi project influences the collaborative processes performed in the organization? change management block questions 13. how do you see the impact in the change resistance on behalf of individual and group culture at the time to make an implementation? 14. how do technologies impact the change management at the time of making an implementation? project developing block questions 15. how do people’s participation within the project usually happens? 16. how are learning topics and knowledge management handled at the time to conceive the project and implement it? 17. have a central control entity figure to make the implementation been stablished? how does it work? 18. do you think organizational structure influences in some way the bi solutions implementation? if yes, how does it happen? 19. how do technologies influence the project implementation? 20. what kind of information is handled during the project development? who has access to that information? people and human talent teams block questions 21. which role do people’s networks play when thinking about bi solutions? (it is not referred to online social networks) 22. what do you think about the influence of proximity among people in their collaborative work under the project execution? understanding proximity as common issues existent among people. learning and skills block questions 23. how learning processes happen and what abilities are required from the people participating in these implementations? 24. how do people’s communications and commitment influence their learning processes and skills development? 25. how do people’s networks influence their learning and skills development? technologies and information block questions 26. how do you describe the role of social networks and its relation with 69 technologies and information used in bi solutions? 27. describe in a single phrase the relation (if there is any) that you find between technologies and information in a bi solution and: a) learning b) abilities c) communication among participants resources block questions 28. what is your opinion about the relation between planning and economic resources used in a bi solution? 29. how do you define the importance of technological and intellectual resources in bi solutions? 30. what additional factors do you consider that affect/impact? is there anything else, positively or negatively, related to this collaborative work? 31 critical factors of competitive intelligence in the power plant industry: the case study of mapna group afrooz momeni, mehdi mehrafzoon mapna group, iran afrooz.momeni@gmail.com and m.mehrafzoon@gmail.com received january 7 2013, accepted february 19 2013 abstract: this paper aims to discuss the critical factors of competitive intelligence that influences the iran’s power plant industry (mapna group). design/methodology/ approach: the paper has identified critical factors of competitive intelligence through iran’s power plant industry based on a comprehensive review of recent literature. for this purpose, a questionnaire was designed, applied and analyzed by the use of statistical methods. the results discuss various perspectives from a competitive intelligence point of view, and provide critical factors and a regression model for showing essential issues on the subject. findings: the statistical analysis determines seven factors as critical issues in this case study. these factors are “proportion of company’s structure and goal”, “company’s competitive conditions”, “international policies about foreign trade”, and “economics and politics condition of country”. research limitation/ implications: the extracted factors can act as a guideline to design a strategic plan. this helps to ensure that the essential issues are covered during design and implementation of the plan. for academics, it provides a common language to discuss the factors crucial for competitive intelligence in this industry. originality/ value: the paper may represent high value to researchers in the competitive intelligence and strategic management fields. this study further provides an integrated perspective of critical issues for competitive intelligence in the power plant industry. it gives valuable information and guidelines that can help leaders consider the important issues during strategic planning. keywords: competitive intelligence, factor analysis, strategic management, power plant industry, iran available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2013) 31-43 mailto:afrooz.momeni@gmail.com mailto:m.mehrafzoon@gmail.com https://ojs.hh.se/ 32 1. introduction today’s firms operate within a rapidly changing business climate created by advances in technologies (aaby and discenza, 1995; raymond, 2003), economic and social changes (wheelen and hunger, 1998), and fast-shortening product life cycles, which lead to “hypercompetition” (chakravarthy, 1997). such complex and unstable environment necessitates a need for timely, first-rate business information and knowledge (hannula and pirttimaki, 2003). thus, companies must devote a greater proportion of their resources to knowledge and innovation (raymond, 2003; guimaraes, 2000). hannula and pirttimaki (2003) argue that a competitive edge is gained through the ability to anticipate information, turn it into knowledge, craft it into intelligence relevant to the business environment, and actually use the knowledge gained from it. in planning their strategies, companies need to analyze carefully the business environment, especially the pressures and challenges caused by it, in order to thrive in the global digital economy (hannula and pirttimaki, 2003). thus, enterprises should view the strategic plan as a reaction to external stimuli rather than a long-term, unchangeable course of action (persidis, 2003). groom and david (2001) point out that corporate planning in the 1960s and 1970s consisted simply of new product development to meet the growing affluence of consumers, especially in the usa. nowadays, the world economy is experiencing a downturn as global growth has slowed, intensifying competition, and changing customer needs. also, the macroeconomy continuously challenges businesses, requiring them to evaluate and change their strategic goals (groom and david, 2001) and strategic plans (persidis, 2003) constantly, in order to gain efficiency and a competitive advantage. persidis (2003) points out that, a few years ago, business managers talked in terms of 58 year strategic plans, whereas today they talk more of 2-3 year plans, and many firms are discovering that the only way to grow is by taking market share from the competition and introduce new products (groom and david ). ci is generally a new research area at the international level, the vast majority of the research being concentrated in us firms (wright et al., 2002). the focus of this paper reflects the fact that iran has undergone significant competitive economic changes over the last few years and plays a key role in the economy of the middle east. its market is attractive and open, although regulations and government operations may seem bureaucratic and complex. yet, there is a scarcity of research on ci in iran. the findings of this study could be of value to both marketing practitioners and academics, because of the challenges faced in operating in a speedily changing globalized business environment. its aim is to explore how familiar iranian companies work with ci and to what extent they make use of it. specific objectives are to:  investigate the key factors of ci;  identify the key factors in iranian companies  establish a model from key factors the remainder of this paper is organized as follows: in next section a brief overview of the literature on competitive intelligence is presented; then we focus on the methodology followed and the empirical analysis of the data; finally, in the last section, conclusions are reached and recommendations made. 2. literature review competitive intelligence (ci) is a business tool that can make a significant contribution to the strategic management process in modern business organizations, driving business performance and change by increasing knowledge, internal relationships and the quality of strategic plans (bernhardt, 1993). ci is formally defined by the society of competitive intelligence professionals as “a systematic and ethical program for gathering, analyzing and managing external information that can affect your company’s plans, decisions and operations” (www.scip.org). according to myburgh (2004), the objectives of ci are to manage and reduce risk, make knowledge profitable, avoid information overload, ensure privacy and security of information, and use corporate information strategically. in essence, ci helps strategists to understand the forces that influence the business environment and, more importantly, to develop appropriate plans to compete successfully (mcgonagle and vella, 2002). because of this critical impact on business decisions and on shaping company strategy, ci should be an important responsibility 33 of top management (wee tan tsu, 2001). further, guimaraes (2000) argues that a company can improve its competitive edge and its overall performance by applying an effective ci program, and thereby satisfy two vital goals for its survival. the literature of ci is limited (wright et al., 2002). it appeared as a “marketing child” in the 1960s (walle, 1999) and has developed slowly, but regularly since the mid-1970s due to expansion of companies into foreign countries, globalization of markets, and the varying needs of consumers (prescott, 1995). indeed, all of these have influenced the life and actions of companies and have led management to a continuous search for new theories and techniques to help them face the competition (fuld, 1995). executives in small and medium sized enterprises normally focus mainly on strategic initiatives that will yield direct profits (wright et al., 1999). they are cautious about actions that could damage the company economically, and thus prefer to invest in a plan that will deliver profit in the short-term rather than one that obliges them to wait for results in the medium or long run. this attitude militates against adoption of ci for, even though it can yield direct profits, the medium or long-term outcomes are what render it priceless (wright et al., 1999; prescott, 1995; white, 1998). ci is both a product and a process. the product is information on the competitors in the market, which is used as the basis for specific action. the process is the systematic acquisition, analysis and evaluation of information for competitive advantage over known and potential competitors (myburgh, 2004). information assists decision makers to understand their competitors and to make sound strategic decisions (wee tan tsu, 2001; hewitt-dundas et al., 1997; simkin and cheng, 1997). it is a common mistake to confuse ci with market research, but the gathering and analysis of information takes a quite different form (wright et al., 1999; prescott, 1995; white, 1998; attaway, 1998; walle, 1999; vedder and guynes, 2000/2001). threats in the market do not emanate only from the large competitors, and planners should, therefore, find ways to monitor the whole market, in order to stay ahead of competition. guimaraes (2000) provides a summary of the benefits of ci practice in strategic planning: bringing to light business opportunities and problems that will enable proactive strategies; providing the basis for continuous improvement; shedding light on competitor strategies; improving speed to market and thereby supporting rapid globalization; improving the likelihood of company survival; increasing business volume; providing better customer assessment; and improving understanding of external influences. although it seems obvious that ci is becoming more and more vital to a firm’s survival in today’s dynamic markets (mcgonagle and vella, 2004), a large number of companies still have no formal ci department. this is typically the result of cost cutting and competition from abroad (attaway, 1998), but another reason might be the lack of formal education in ci (fleisher, 2004). however, there is evidence in the usa that more companies are beginning to recognize ci as a critical component of the best strategic and tactical decisions (heath, 1996), and thus have organized formal ci units. typically, these are the major players: shermach (1995) names ge, xerox, motorola, microsoft, h-p, ibm, at&t as cases in point. persidis (2003) suggests that a larger number of smaller companies are also recognizing ci as an important part of their operations, and do practice it, possibly without realizing they are doing so. previous studies have verified these trends. in 1998, research by the futures group in 103 large, small and medium enterprises in the usa found that exactly three quarters had a formal ci department. interestingly, exactly half said they did not believe that their competitors watched them (groom and david, 2001; dishman and calof, 2008). the concept of intelligence as a process has long been proposed as an effort to improve the firm’s competitiveness and its strategic planning process (guyton, 1962; montgomery and urban, 1970; pearce, 1971, 1976; montgomery and weinberg, 1979; porter, 1980). already in 1966 william fair proposed the creation of a corporate “central intelligence agency” within the firm whose function it would be to “collect, screen, collate, organize, record, retrieve and disseminate information” (fair, 1966, p. 489). since that time, this proposition has grown to become an emerging business function with delineated job functions directly responsible for intelligence collection, analysis, and dissemination (kahaner, 1996). competitive intelligence’s goal is to provide “actionable intelligence” (fahey, 1999; fuld, 1995, 2000; nolan, 1999), namely, information that has been synthesized, analyzed, evaluated and 34 contextualized. competitive intelligence presents part of the strategic information management process that is aligned with an organization’s strategy (bergeron, 1996; kennedy, 1996; moon, 2000). 3. research methodology based on literature review, the points discussed above, the authors’ recent researches on ci and applying some statistical methods, the research structure of this study has been developed in five main stages as shown in figure 1. in this way, at the first stage, a questionnaire was designed with some questions that evaluate ci effects on the company. the content of second section is based on critical dimensions of competitive intelligence listed in table 1 which are the important factors; and finally the third section of the questionnaire including questions about the characteristics of the interviewees. figure 1: research methodology it is important to say that a hypothesis test must be designed to evaluate positive ci effects on organizational success and considering this hypothesis proof at second stage, the research can be continued. at the second stage, the survey is run to collect data from interviewees and based on the collected data; a reliability analysis can be performed. reliability analysis allows you to study the properties of questionnaire and the items that make them up. the reliability analysis procedure calculates a number of commonly used measures of scale reliability and also provides information about the relationships between individual items in the measurement scale (hair et al., 1998). the main purpose of third stage is to confirm the mentioned hypothesis in stage one. in this way, it is necessary to determine the statistical distribution of collected data at the first part of the questionnaire. subsequently, based on distribution of data, one of parametric or non-parametric tests can be performed for hypothesis proof. the fourth stage of research framework is based on “factor analysis” and is concentrated on extraction and identification of the critical factors affecting the ci in the iranian companies. factor analysis is also known as a generic name given to a class of multivariate statistical methods whose primary purpose is to define the underlying structure in a data matrix. broadly speaking, it addresses the problem of analyzing the structure of the interrelationships (correlations) among a large number of variables (e.g. test scores, test items, questionnaire responses) by defining a set of common under-lying category, known as factors. with factor analysis, the researcher can first identify the separate factors of the structure and then determine the extent to which each variable is explained by each factor. once these factors and the explanation of each variable are determined, the two primary uses for factor analysis-summarization and data reduction-can be achieved. in summarizing the data, factor analysis derives underlying factors that, when interpreted and understood, describe the data in a much smaller number of concepts than the original individual variables. data reduction can be achieved by calculating scores for each underlying factors and substituting them for the original variables (hair et al., 1998). evaluating the suitability of collected data, performing factor analysis and naming the extracted factors are different steps of this stage. finally, the most important factors and their effect become clear 35 through multiple regression analysis at stage five. the linear regression model assumes that there is a linear or straight line relationship between the dependent variable and each predictor. linear regression estimates the coefficients of the linear equation, involving one or more independent variables that best predict the value of the dependent variable (hair et al., 1998). 4. discussion 4.1. data collection the research targets were members of mapna group including managers, senior experts and effective staff in decision making. mapna group has already posted seminars on competitive intelligence and organizational success. therefore, most of the members are aware of the importance of ci. in order to understand the viewpoints on ci from all sectors of the mapna central office and different factories, questionnaires were sent to different departments including information, research and development, academic and human resource departments. the number of questionnaires sent out was 600; the number returned was 390, which showed a return rate of 65 percent. 36 number dimension related research v1 market weiss, 2001 v2 rate of interest albrecht, 1993 v3 economics terms antia and hesford, 2007 v4 appraisal fleisher and bensoussan, 2002 v5 supported industries denise lemos, 1998 v6 exploitation combs and moorhead, 1993 v7 quality combs and moorhead, 1993 v8 process beal, 2000 v9 international politics keegan, 1999 v10 governmental politics blenkhorn and fleisher,2007 v11 religious politics blenkhorn and fleisher,2007 v12 local-political powers fehringer, hohhof, and johnson, 2006 v13 culture bartlett, 2002; keegan, 1999 v14 esteem boucher, 1996 v15 behavior boucher, 1996 v16 talent rousseau, 1994 v17 skill flamholltz, 1999 v18 competition area porter, 1995 v19 services and products porter, 1980 v20 new competitors porter, 1980 v21 distributors fehringer, hohhof, and johnson, 2006 v22 geophysics muller, 2004; kartler and armstrang, 1993 v23 competitive price fleisher and bensoussan, 2002 v24 tax rules murphy , 2005; west, 2001 v25 foreign trade rules kok, 2005 v26 absorption rules for abroad capitals wee tan tsu, 2001 v27 labor union wright and ashill, 1998 v28 employment rules mcgonagle and vella, 2004 v29 protest groups nolan, 1999 v30 monopolist rules wheelen, 1998 v31 local rules myburgh, 2004 v32 tariffs muller, 2004 table 1: critical dimension of competitive intelligence 4.2. reliability analysis with reliability analysis, you can get an overall index of the repeatability or internal consistency of the measurement scale as a whole, and you can identify problem items that should be excluded from the scale. the cronbach’s is a model of internal consistency, based on the average interitem correlation. the cronbach’s a (likert, 1974) calculated from the 32 variables of this research was 0.894 (89 percent), which showed high reliability for the designed measurement scale. 4.3. demographic profiles of interviewees the demographic profile of employees who participate in the survey has been summarized in table 2. the results showed that 54.36 percent of the interviewees are from central office and the others are from factories. the subjects of this study were members of the mapna group, who are specialized in power plant projects design and development. all of the members had bachelor of science (bs) or higher education, as shown in table 2. for the job title point of view, 73 percent of the participants were experts, 18 percent were supervisors and the others were managers at different levels. table 2 also shows the seniority of the participants. 37 area description number of interviewees percent cumulative location central office 212 54.36 54.36 factories 178 45.64 100 sum 390 100 educational degree bachelor of science(bs) 87 22.31 22.31 master of science(ms) 270 69.23 91.54 phd 33 8.46 100 sum 390 job position expert 285 73.08 73.08 supervisor 72 18.46 91.54 managers and senior managers 33 8.46 100 sum 390 table 2: demographic profile of the interviewees 4.4. identification of critical factors the main technique of this stage is based on “factor analysis”. factor analysis is a technique particularly suitable for analyzing the patterns of complex, multidimensional relationships encountered by researchers. it defines and explains in broad, conceptual terms the fundamental aspects of factor analytic techniques. factor analysis can be utilized to examine the underlying patterns or relationships for a large number of variables and to determine whether the information can be condensed or summarized in a smaller set of factors or components. to further clarify the methodological concepts, basic guidelines for presenting and interpreting the results of these techniques are also included. factor analysis provides direct insight into the interrelationships among variables or respondents and empirical support for addressing conceptual issues relating to the underlying structure of the data. it also plays an important complementary role with other multivariate techniques through both data summarization and data reduction (hair et al., 1998). an important tool in interpreting factors is factor rotation. the term rotation means exactly what it implies. specifically, the reference axes of the factors are turned about the origin until some other position has been reached. the un-rotated factor solutions extract factors in the order of their importance. the first factor tends to be a general factor with almost every variable loading significantly, and it accounts for the largest amount of variance. the second and subsequent factors are then based on the residual amount of variance. each accounts for successively smaller portions of variance. the ultimate effect of rotating the factor matrix is to redistribute the variance from earlier factors to later ones to achieve a simpler, theoretically more meaningful factor pattern. the simplest case of rotation is an orthogonal rotation, in which the axes are maintained at 908 (hair et al., 1998). in order to determine whether the partial correlation of the variables is small, the authors used the kaiser-meyer-olkin measure of sampling adequacy (kaiser, 1958) and bartlett’s x 2 test of sphericity (bartlett, 1950) before starting the factor analysis. the result was a kmo of 0.692 and less than 0.05 for bartlett test, which showed good correlation as depicted in table 3. kaiser-meyer-olkin measure of sampling adequacy 0.692 bartlett’s test of sphericity approx. χ 2 3267.941 df 276 sig. 0.00 table 3: kmo and bartlett test results 38 the factor analysis method is the “principle component analysis” in this research, developed by hotteling (1935). the condition for selecting factors is based on the principle proposed by kaiser (1958): eigen value larger than one, and an absolute value of factor loading greater than 0.5. the 32 variables were grouped into ten factors. the results can be seen in table 4. ten factors have an eigen value greater than one and the interpretation variable is 91.943 percent. the factors are rotated according to varimax. rotated sums of squared loadings factor initial eigen value total percentage of variance cumulative percentage 1 11.866 5.655 23.563 23.563 2 2.393 3.324 13.851 37.414 3 2.000 2.997 12.488 49.902 4 1.727 2.134 8.892 58.794 5 1.367 1.621 6.756 65.550 6 1.324 1.417 5.902 71.452 7 1.273 1.271 5.295 76.747 8 1.207 1.206 5.164 81.911 9 1.139 1.169 5.083 86.994 10 1.041 1.108 4.949 91.943 table 4: factor analysis results factor loading of each variable on the resulted seven factors is depicted in table 5. each variable should have significant factor loading (greater than 0.5) only on one factor. therefore, factors 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10 had 5, 5, 2, 1, 4, 3, 3, 2, 1 and 1 variable. in this way, v4, v5, v6, v7, v8 are significant for factor 1; v18, v19, v20, v21, v23 are significant for factor 2; v22, v29 are significant for factor 3; v30 is significant for factor 4; v11, v24, v25, v26, are significant for factor 5; v15, v16, v17, v28 are significant for factor 6; v3, v9, v10 are significant for factor 7; v13, v14 are significant for factor 8 ;v31 is significant for factor 9 and v12 is significant for factor 10. because of factor loading less than 0.5, the variables v1, v2, v27 and v32 can be omitted. the variable v12, v30, v31 because of grouping just in 1 factor, can be eliminated as well. the content of each factor can be seen in table 5. so the interpretation variable is 76.747 percent. 4.5. factors naming the authors attempted to name the factors compendiously without losing contents of factors. in this way, the names and content of the seven factors are shown in table 6. “proportion of company’s structure and goal”, “company’s competitive conditions”, “environmental conservation union”, “international policies about foreign trade”, “human resource”, “economics and politics condition of country” and finally “social milieu” are the names which have been allocated to the extracted factors. 39 factors questions 1 2 3 4 5 6 7 8 9 10 v1 0.055 -0.064 -0.057 0.039 0.257 0.108 0.089 -0.056 -0.040 0.089 v2 0.045 0.126 -0.064 0.045 0.173 -0.059 0.171 0.395 -0.023 0.308 v3 0.186 0.133 0.058 0.011 -0.043 -0.068 0.685 0.072 0.080 0.420 v4 0.635 0.151 0.059 0.045 0.321 0.163 0.001 0.029 0.178 0.222 v5 0.788 -0.036 0.007 0.140 0.085 0.065 0.083 0.130 0.060 0.071 v6 0.738 0.196 0.013 0.125 0.115 0.272 0.097 0.232 0.066 0.020 v7 0.635 0.237 -0.040 0.115 -0.023 0.268 0.451 0.055 -0.066 -0.077 v8 0.600 -0.038 -0.007 0.076 0.160 -0.052 0.473 0.143 -0.026 0.367 v9 0.157 0.119 -0.057 0.374 0.091 0.017 0.598 0.020 0.452 0.127 v10 0.166 0.021 0.038 -0.074 -0.204 -0.097 0.756 0.202 -0.031 -0.098 v11 0.052 -0.056 0.004 0-.004 0.686 0.019 0.192 -0.083 0.128 -0.358 v12 0.059 0.049 0.118 0.073 0.154 0.178 0.182 -0.029 0.112 0.757 v13 0.088 0.143 0.179 0.157 0.240 0.301 0.018 0.666 0.220 -0.061 v14 0.294 0.057 0.245 -0.053 0.193 0.088 0.119 0.715 0.235 0.174 v15 -0.090 0.016 0.094 0.205 0.039 0.759 0.105 0.039 0.182 0.139 v16 0.203 -0.004 0.120 0.055 0.020 0.545 0.170 0.130 0.212 0.197 v17 0.178 0.253 0.209 0.324 0.114 0.697 0.038 0.009 0.130 0.120 v18 0.036 0.867 0.061 0.095 -0.090 -0.024 -0.090 0.130 0.143 0.043 v19 -0.006 0.650 0.295 0.351 -0.059 0.154 0.227 0.102 -0.002 0.296 v20 0.135 0.510 0.263 0.475 -0.017 0.162 -0.004 0.167 0.441 0.111 v21 0.253 0.563 -0.039 0.092 0.229 0.240 -0.031 0.109 0.155 0.132 v22 0.277 -0.075 0.832 0.038 0.185 -0.047 0.114 0.038 0.061 -0.047 v23 0.190 0.805 0.028 0.003 0.062 0.177 0.110 0.213 -0.044 0.109 v24 0.004 -0.055 0.160 0.214 0.823 0.172 0.062 0.110 -0.001 0.055 v25 -0.096 0.084 0.218 0.221 0.558 0.063 -0.077 0.196 0.076 0.254 v26 0.048 0.026 -0.066 0.468 0.694 -0.093 0.069 0.076 0.263 0.172 v27 0.180 0.171 0.477 0.192 0.215 0.476 -0.096 0.316 0.011 0.044 v28 0.009 0.120 0.142 0.330 0.123 0.817 -0.037 0.025 0.037 0.053 v29 0.180 0.129 0.843 0.172 0.009 -0.108 0.089 0.119 0.002 -0.044 v30 0.027 -0.016 -0.053 0.913 0.071 0.036 0.129 0.047 0.058 -0.045 v31 0.001 0.110 0.056 0.077 -0.055 -0.007 -0.059 0.223 0.766 0.162 v32 0.458 0.160 0.311 0.130 0.001 -0.070 0.475 -0.047 0.065 0.101 note: rotation method was varimax with kaiser normalization table 5: rotated component matrix 4.6 multiple regression analysis table 7 shows the relationship of ci to the enhancement of company competitiveness. we used the average mean of factors as a dependent variable to carry out regression analysis with the seven factors. table 7 shows the results of the regression analysis. the p-value of the f-test was less than 0.05, which was significant, making the seven factors valid in predicting the relationship between ci and company competitiveness. as a result, the seven factors were valid critical adoption factor benchmarks for ci in the power plant industry in iran. in addition, regression coefficients were used to predict the effect of independent variables of dependent variables by t-test. the results showed that factor 1 “proportion of company’s structure and goal”, factor 2 “company’s competitive conditions”, factor 4 “international policies about foreign trade”, and factor 6 “economics and politics condition of country” had significant effects on ci; factors 1, 2, 4 and 6, therefore, had a higher significance for company competitiveness than the other factors. 40 factors critical factor names no. dimension 1 proportion of company’s structure and goal v4 appraisal v5 supported industries v6 exploitation v7 quality v8 process 2 company’s competitive conditions v18 competition area v19 services and products v20 new competitors v21 distributors v23 competitive price 3 environmental conservation union v22 geophysics v29 protest groups 4 international policies about foreign trade v11 religious politics v24 tax rules v25 foreign trade rules v26 absorption rules for abroad capitals 5 human resource v15 behavior v16 talent v17 skill v28 employment rules 6 economics and politics condition of country v3 economic terms v9 international politics v10 governmental politics 7 social milieu v13 culture v14 esteem table 6: the name and content of critical factors unstandardized coefficients β std. error standardized coefficients β t sig. r 2 f. sig. (constant) 3.871 0.034 95.638 0.000 0.273 4.840 0.000* f1 0.264 0.034 0.467 14.117 0.000* f2 0.032 0.034 0.598 11.309 0.000* f3 0.057 0.034 0.061 0.677 0.500 f4 0.168 0.034 0.297 3.309 0.001* f5 0.024 0.034 0.077 0.852 0.379 f6 0.077 0.034 0.228 6.737 0.000* f7 0.015 0.034 0.016 0.181 0.856 note: *significant at the 0.01 level table 7: summary of multiple regression analysis 5. conclusion 5.1. summary this study attempts to detect critical ci factors in the power planet industry in iran. we use a “likert scale” to measure affected factors on the power plant industry. from a comprehensive literature review 32 critical variables of competitive intelligence were distinguished and embedded in the second part of the research. the interviews selected more important dimensions 41 from these 32 variables by assigning ranks to them. the study then used factor analysis to extract critical factors of competitive intelligence in the power plant industry through 32 variables. these factors were: “market”, “rate of interest”, “economics terms”, “appraisal”, “supported industries”, “exploitation”, “quality”, “process”, “international politics”, “governmental politics”, “religious politics”, “local-political powers”, “culture”, “esteem”, “behavior”, “talent”, “skill”, “competition area”, “services and products”, “new competitors”, “distributors”, “geophysics”, “competitive price”, “tax rules”, “foreign trade rules”, “absorption rules for abroad capitals”, “labor union”, “employment rules”, “protest groups”, “monopolist rules”, “local rules”, and “tariffs”. after factor analyzing the variables were reduced to 10 groups. three groups only have 1 factor, so they were eliminated. the remaining groups included 25 variables, so 7 variables were reduced. after that, we used regression coefficients to predict the effect of independent variables on dependent variables. the results showed that “proportion of company’s structure and goal”, “company’s competitive conditions”, “international policies about foreign trade”, and “economics and politics condition of country” are effective in the regression model. 5.2. recommendations the authors believe that after this research, power plant industry management can decide in a better way how to establish a competitive intelligence system using the 7 factors defined here in their strategies. further research is needed. one area is influence of each factor on power plant industry’s profitability. other research directions can include studying the effects of the work environment on ci. refrences [1] aaby, n.e. and discenza, r. 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(2017) patent bibliometrics and its use for technology watch. journal of intelligence studies in business. 7 (2) 17-26. article url: https://ojs.hh.se/index.php/jisib/article/view/220 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index patent bibliometrics and its use for technology watch björn jürgensa and victor herrero-solanab aagency of innovation and development of andalusia idea; citpia patent information centre (patlib network); ceseand enterprise europe network, granada spain bscimago-ugr, universidad de granada, granada, spain journal of intelligence studies in business please scroll down for article patent bibliometrics and its use for technology watch björn jürgensa* and victor herrero-solanab aagency of innovation and development of andalusia idea; citpia patent information centre (patlib network); ceseand enterprise europe network, granada, spain bscimago-ugr, universidad de granada, granada, spain *corresponding author: bjurgens@agenciaidea.es received 12 may 2017; accepted 5 june 2017 abstract technology watch is a methodology for organisations to systematically analyze technical information in a continuous way in order to gain insight and competitive advantage in a specific technical domain and is based mainly on statistical analysis of patent information. patent statistics are commonly based on bibliographic data and generated with bibliometric techniques. in this paper we describe the differences between patent bibliometrics and classic bibliometrics and propose several patent indicators for technology watch activities which we classified into four categories: performance, technology, patent value and collaboration indicators. in a case study we undertook a bibliometric patent analysis using the described groups of indicators in order to generate a technology watch of nanotechnology for the domain of a whole country (spain) and explained the different data visualizations we used in order to represent the indicators. we conclude that statistical analysis of patent information and its visualization is a powerful methodology for any competitive intelligence activity centred on technology but there are also some limitations to bear in mind when undertaking technology watch activities using patent information discussed in terms of its timeliness, patentability criteria, sector dependence, quantity vs. quality. keywords competitive intelligence, nanotechnology, patent bibliometrics, patent indicators, patent information, patent statistics, patents, spain, technology intelligence, technology monitoring, technology watch 1. introduction technology watch, also known as “technology intelligence”, “technology monitoring” or “patent intelligence”, is a methodology for organisations to systematically analyze technical information in a continuous way in order to gain insight and competitive advantage in a specific technical domain. technology watch is a part of the broader concept of “competitive intelligence” (ci) which can be defined as a methodology for gathering, analyzing and managing external information 1in fewer cases also other technological sources are included in the technology watch process (like funded r&d project abstracts or profiles from technology transfer platforms) that can affect the organisation’s plans, decisions and operations (negash 2004, miller 2001). especially high tech corporations or research intensive companies need to be able to anticipate technology trends, since a wrong choice can result in low profits and obsolete products and can have a major impact on the financial performance for many years (hodgson 2008). technology watch is based mainly on statistical analysis of patent information1. translating patent information into although this data is less structured than patent data and has much lover coverage over countries and/or sectors. journal of intelligence studies in business vol. 7, no. 2 (2016) pp. 17-26 open access: freely available at: https://ojs.hh.se/ 18 competitive intelligence allows to measure the current technical competitiveness and to forecast technological trends of specific sectors (fleisher 2003). as an example we can mention the works of salvador who analyzed the plastics industry (2012) and additive manufacturing technologies (2014), or the study from deshpande et al. (2016) who looked into relatively new fields with r&d activity like energy efficiency in cloud data centres. patents are publicly available documents that describe, in a structured and unified way, a technical invention which, once granted by a government or regional patent office gives the owner the monopoly to commercially exploit the invention in a specific country. nowadays, with currently more than 95 million open access patent documents2, patent information is a powerful source to conduct technology watch of specific technological domains. as patents cover mainly technical inventions, they are a rich source of data reflecting technical change and in technology fields with high research and development activities. especially in emerging sectors like nanotechnology or biotechnology, patent data can reveal the intermediate stages of innovation activities and can offer a basis for analysis where other data is lacking (zuniga, 2009). patent statistics have been used to monitor and evaluate science and technology activities from the 1960s with the work of schmookler (1966), who was one of the first to use patent counts as indicators of technological change in particular industries. taking advantage of its structured format, patent statistics are commonly based on its bibliographic data and therefore generated with bibliometric techniques. this is why it is also known as patent bibliometrics, first introduced by narin (1994). table 1 scientific literature vs. patent literature. from lloyd (2015) and own research. scientific publications patent publications content mainly basic research findings technical solutions to a problem access paid access or open access or depending on the journal open access via public patent databases quality filter peer review patent examination process indexing scientific papers can have inconsistent bibliographical details, meaning that they can be hard to index. patent publications have a (more or less) standardised numbering system, meaning that it is possible to fully index them. subject categorization core journals by subject field patent classifications by technology field reason to publish scientific recognition economic (gain commercial monopoly, licensing, etc.) who publishes research entities (mainly universities) companies and to a lesser degree research entities and private persons (inventors) cost sometimes fee based and others for free (depending on journal prestige) fee based (depending on patent office and coverage) content duplicity no (the article can only be published in one single journal) yes (as patents are territorial, the same invention can generate several different patent documents for each country) timeliness article publishing depends on the efficiency of the peer review process of the journal patent is not published before 18 month after filing 2source: https://www.epo.org/searching-forpatents/technical/espacenet.html table 2 performance indicators. indicator metrics description top country applicants (per patent family) patent family counts per applicant indicate the company/institutions which have most inventions in a field or topic. top country applicants (per patent publication) patent document counts (published) per applicant indicate the top company/institutions which have most patents in a field or topic. patent counts by the applicant over years patents filed (priority) / applicant / year measure the level of r&d efforts. a variation can be interpreted as a change in their r&d strategy. patent internationalisation rate of applicants patent document counts (published) per applicant / patent family counts per applicant indicate the applicants with the highest ratio of generated patents of their invention portfolio. top country inventors (patent family) patent family counts per inventor indicate the inventors which have most inventions in a field or topic. top country inventors (patent publication) patent document counts (published) per inventor indicate the inventors which have most patents in a field or topic. patent internationalisation rate of inventors patent document counts (published) per inventor / patent family counts per inventor indicate the inventors with the highest ratio of generated patents of their invention portfolio. 2. patent bibliometrics vs. classic bibliometrics bibliometrics was first mentioned in 1969 by pritchard, who defined it as "the application of mathematical and statistical methods to books and other media of communication" (pritchard, 1969). the general properties of classic bibliometrics which analyze scientific publications and patent bibliometrics which analyze patent publications are very similar (narin, 1994) but we have to be careful when comparing both types of analyzed documents since they have some substantial differences. in table 1 we sum up the main distinctions regarding several aspects such as their content, access, and indexing. table 3 technology indicators. indicator metrics description technology evolution (per patent family) patent family counts in technology field / year forecasts the technological trend on the number of inventions. technology evolution (per patent publication) patent document counts (published) in technology field / year forecasts the technological trend on the number of patents. technological distribution patents filed (priority) / classification identifies the core technologies of the analyzed technology. technological networks (macro level) cpc level 4 / cpc level 4 ipc level 4 / ipc level 4 relationships between technological domains technological networks (micro level) cpc level 7 / cpc level 7 ipc level 7 / ipc level 7 relationships between specific technologies applicant technology network cpc level 7 / applicant ipc level 7 / applicant relationships between company/institution and technological domains (macro and micro level) inventor technology network cpc level 7 / inventor ipc level 7 / inventor cpc level 4 / inventor ipc level 4 / inventor relationships between inventor/researcher and technological domains (macro and micro level) table 4 patent value indicators. indicator metrics description publications per patent office patent application published / patent authority indicate which are the most important markets for patents from the analyzed technological domain. family size patents application published / family members reflects the intention to produce or commercialize globally the products related to the invention. top applicants geographic coverage ratio patent application published / family size indicates the grade of internationalization of applicants patent portfolio. top inventors geographic coverage ratio patent application published / family size indicates the grade of internationalization of an inventors patent portfolio. family network patent authority / patent authority indicates which markets are co-protected and identifies the essential markets where protection is sought together. top patents with backward citations number of cited patents / patent helps to identify technical complementarities or substitutes or prior art patents. top forward cited patents number of citing patents / patent reflects the technological impact of the patented invention and helps to identify key patents which influenced other patents. 3. patent indicators for technology watch in patent bibliometrics we can distinguish two main types of analysis: single field analysis and multiple field analysis (e-ipr 2013). the single field analysis, widely used also in classic bibliometrics, is a one field analysis based on lists or rankings and is conducted on a set of bibliographic patent references. multiple field analysis, also known as cross reference analysis, combines different types of bibliographic fields via matrices. this is the basis for data visualization via collaboration networks that can reveal valuable information for a technology watch activity. with these types of analysis we can generate several patent indicators for technology watch activities which we propose to classify in the following four categories that will be explained subsequently: • performance indicators • technology indicators • patent value indicators • collaboration indicators 3.1 performance indicators we considered performance indicators to be patent indicators that deal with the patent output of the analysed entities (inventors or applicants) and that are used to monitor the technological performance of company / institutions and inventors / researchers and to track their technological leadership in a given technology over time (zuniga, 2009). in table 2 we describe various typical patent indicators of this type. 3.2 technology indicators technology indicators analyze patent classifications and are another very valuable indicator for technology watch activities since every patent is classified with one or more classes according to its technological field. with single and multiple field analysis of the classification we can reveal the technological focal points of an organisation, the research fields of inventors, the evolution of a technology sector and the relationships between technological domains (table 3). macro and micro vision of the technology field can be distinguished in some cases by analyzing the patent classes in different hierarchy levels. for instance a more general vision of the technology landscape (macro vision) can be obtained by aggregating to a 4digit classification level (“level 4” till subclass hierarchy) and for a more detailed technology perspective (macro vision) the 7-digit classification level (“level 7” till sub group hierarchy) can be used. 3.3 patent value indicators patent value indicators can give us an idea about the economical value of a patent by looking at several factors (table 4). first of all, the size of the patent family and the geographic 21 coverage are important indicators. patents provide protection on a country level and can be extended to other countries in the 12 months of priority since its first filing. in this sense, the more countries a patent is extended, the broader is their protection and the invention can be considered as economically more promising since the applicant is willing to assume the correspondent high costs of the patent extensions (hullmann, 2003). in this context another indicator is the ratio of the family size and total invention output compared, which can be used to measure the grade of internationalization of an inventor’s or applicant’s patent portfolio. apart from the quantitative measure of patent families, specific patent types or countries are also used as patent indicators. patenting in certain countries can be considered as more important than in others (palmberg, 2009). for example a european patent (ep) or pct patent application is considered of special relevance, and if a invention is filed as a japanese, us and european patent by the same applicant or inventor the patent is given a special importance since it covers the three most important patenting authorities worldwide (the so called triadic patent family). patent citations are another important indicator related to patent value and to identify knowledge flows from company to company, or from other sectors, e.g. research institutes and academia to companies (meyer, 2002). similar to citations in scientific articles, in patents you can distinguish forward and backward citations. backward citations are the references in a patent document to earlier documents whereas forward citations are more recent documents that cite the patent. as a difference from scientific articles, in patent citation we can distinguish citations from the inventor and citations from the patent examiner. citations from the inventor are the references that the inventor provides in the patent to describe the state of the art and to give evidence for the novelty of the patent. citations from the patent examiner on the other hand are the documents that the patent examiner references in the patent examination procedure. in most countries before a patent gets granted, in order to measure the novelty of the invention the patent office appoints an examiner who is ideally an expert in the particular technical field and who searches for documents in the scientific and technical literature that are related to the particular invention and were published before the date of filing of the application. in both cases citations in patents can be used to: • trace the information sources on which the invention was built, • illustrate the relations with other inventions • and reveal geographical and technological linkages. citation indicators have to be handled with care since one must consider that new patents rarely earn many forward citations because it takes time for a patent to be cited by newer patent documents and therefore a strict forward citation analysis will favour older patents. furthermore, with the obligation to cite all possible prior art, patent applicants tend to cite many more references than needed, leading to patent references where the cited patent is not of particular relevance. this is the case especially in us patents since, contrary to the european patent system, in the us both the applicant and every other involved party (e.g. the patent attorney), must include any possible prior art of an invention in order to minimize the risk of the application being rejected, which leads to the fact that us patents on average include far more citations than european ones (azagra-caro 2009, alcacer gittelman 2006). 3.4 collaboration indicators these type of indicators provide information about collaboration patterns of the entities. they are generated with multiple field analysis and can be visualized with network maps. similar to traditional bibliometrics, in patent bibliometrics the most important collaboration indicators are related to coauthorship (glänzel et al., 2003), although their interpretation slightly differs as outlined in table 5. 4. case study: technology watch of nanotechnology in spain in the framework of a funded project (see acknowledgements) a bibliometric patent analysis study was done using the described groups of indicators in order to generate a technology watch of nanotechnology for the country of spain (jürgens 2016). table 5 collaboration indicators. indicator metrics description applicant collaboration network applicant / applicant collaboration between organisations: connect entities that share the ownership of a patent and contrary to co-inventions can point to a shared interest in utilising a patented invention. inventor coauthorship collaboration network inventor / inventor research collaborations: identifies individuals (inventors or researchers) who generated the technology in a common undertaking and can be considerate as most closely related to the co-authorships in scientific publications. applicant collaboration by country applicant country / applicant country identifies international collaboration on an institutional level. inventor coauthorship by country inventor country / inventor country identifies international collaboration on a research level. in spain competitive intelligence and technology watch as a discipline was first brought to a wider audience by the work from palop & vicente (1999). nowadays, it is an established methodology for fostering the competitiveness of organisations and even has its own certification scheme within the spanish certification entity aenor (garcía & velasco 2006). although it is applied by many spanish multinational companies from a diversity of sectors, e.g. telefónica and repsol, there is still a knowledge gap amongst the small and medium enterprises which is why many regional development agencies have initiated it to provide technology watch services to fill this gap (jürgens, herrero-solana, 2011). in the case of nanotechnology in spain only one study was identified (andaluz & sanchez, 2006) centred more in information analysis of the r&d output than patents. this apparent lack of patent analysis in this sector in spain led to the project of this case study where we analyzed the nanotechnology patent publications of spanish applicants of the years 2004 till 2014. regarding the search strategy, relevant nanotechnology patent classifications were identified (jürgens, herrero-solana, 2016) and combined with an established lexical query for nanotechnology (magrebi et al 2010). as a data source the database espacenet-worldwide from the european patent office was used since it provided the best data coverage for the purpose of the study (jürgens, herrero-solana 2015). the search process retrieved more than 3400 patent records with spanish authorship and after an exhaustive data harmonization process a bibliometric patent analysis was performed using the software tool matheo patent. for a patent/paper comparison, furthermore, scientific article data was retrieved from the database scopus. subsequently several indicators were generated according to the groups described earlier and were presented via data visualization techniques. apart from graph and pie charts, which were used for many single field indicators (e.g. numbers of nanotech patent publications over time), we used choropleth maps containing patent data aggregated over predefined regions with colour ranges representing the data ranges in order to visualize the geographical “hot spots” of nanotechnology patenting in spain (figure 1). scattergraphs were used in the study to compare the patent and scientific publication outputs of the most important nanotechnology players in spain, segmented in colour by their type of institution (e.g. company, university) (figure 2). figure 1 geographical patent hotspot map (the darker the more nanotech patents were published). 23 furthermore, network maps were used extensively as they are intuitive to read since entities are connected to each other in the form of a node and link diagram. in the case study we used network maps to visualize several types of indicators, as shown in the examples in figures 3-5. figure 3 coauthorship network revealing collaboration patterns of two research groups (red circles) and showing their leaders in terms of publications (in dark grey). figure 2 comparison of patent and scientific papers output revealing which institution/company has more focus on basic (papers => y axis) or aplied research (patents => x axis). 24 5. limitations of patent bibliometrics and conclusions there are also some limitations to take in mind when undertaking technology watch activities using patent information. first of all, the timeliness. the patent system of most patent offices worldwide establishes that a patent is not divulged by the patent office until 18 months have passed. only then the patent office publishes the application via its patents office bulletins and patent databases. this means that patent indicators have a considerable delay of a minimum 18 months. second, not all innovative activity is patented or even patentable and therefore cannot be captured in a patent analysis. this can be due to the following reasons: • the costs a patent process incurs are too high for the inventor/researcher • the necessary public disclosure of the invention is not wanted by the inventor/researcher and it is preferred to keep the invention secret instead of patenting • the invention itself is not patentable because it does not fulfil the patentability criteria (e.g. in most countries scientific theories, mathematical methods, plant or animal varieties or commercial methods are not patentable) • the invention is not patented due to strategic decisions third, when comparing patent data between technological sectors it has to be taken in mind that patenting activity tends to vary significantly across different industries (pavitt, 1985). finally, most patent indicators are quantity based and do not measure quality of the patents. it has to be taken in mind that not every patent has the same value and the distribution of the value of patents is skewed as only a few patents turn out to be commercially successful (and therefore are of substantial value) whereas many patents do not reach the market. further research in this specific aspect would be of interest. figure 4 technology network map revealing a common technology focus (in green) of two spanish nanotech institutions (in red and light red). 25 nevertheless, we can conclude that statistical analysis of patent information and its visualization is a powerful and successful methodology for any competitive intelligence activity centred on technology, since it can be effectively used to monitor and evaluate technology activities. this can be observed by the increasing numbers of studies which use this type of analysis, although we would recommend to take in mind the afore mentioned limitations when doing this kind of analysis. acknowledgments the authors acknowledge the spanish ministry of education for funding the framework project “technology watch of spanish nanotechnology via its patents“ (project number: cso201238801) for which this work was used. furthermore this article originated a presentation given by the authors at the 9th international conference “competitive and market intelligence”, held during 9-12 may 2017 in amsterdam, netherlands. 6. references andaluz, d. j., & sánchez j. (2006). nanotecnología en españa. http://www. madrimasd. org/revista/revista34/tribuna/tribuna4.asp (accessed: 05.02.2015) alcacer, j., & gittelman, m. (2006). patent citations as a measure of knowledge flows: the influence of examiner citations. the review of economics and statistics, 88(4), 774-779. azagra-caro, j. m., fernández-de-lucio, i., perruchas, f., & mattsson, p. (2009). what do patent examiner inserted citations indicate for a region with low absorptive capacity?. scientometrics, 80(2), 441-455. deshpande, n., ahmeda, s., & khodea, a. (2016). business intelligence through patinformatics: a study of energy efficient data centres using patent data. journal of intelligence studies in business, 6(3). e-ipr (2013). fact sheet automatic patent analysis. european ipr helpdesk https://www.iprhelpdesk.eu/sites/default/files/ newsdocuments/20131127_patent%20analysi s_updated_0.pdf (accessed: 09.02.2016) fleisher, c. s., & bensoussan, b. e. (2003). strategic and competitive analysis: methods and techniques for analyzing business competition (p. 457). upper saddle river, nj: prentice hall. garcía, c. q., & velasco, c. a. b. (2006). inteligencia competitiva, prospectiva e innovación: la norma ue 166006 ex sobre el figure 5 citation node map of a spanish nanotech patent (orange box) reveals who was influenced by the technology (green boxes). 26 sistema de vigilancia tecnológica. boletín económico de ice, información comercial española, (2896), 47-64. glänzel, w., meyer, m., du plessis, m., thijs, b., magerman, t., schlemmer, b., ... & veugelers, r. (2003). nanotechnology: analysis of an emerging domain of scientific and technological endeavour. steunpunt o&o statistieken. hodgson, a., arman, h., & gindy, n. n. (2008). an intelligent technology watch function for the high technology enterprise. international journal of industrial and systems engineering, 3(1), 38-52. hullmann, a., & meyer, m. (2003). publications and patents in nanotechnology. scientometrics, 58(3), 507-527. jürgens, b., herrero-solana, v. (2011). estudios sectoriales de vigilancia tecnológica para la comunidad empresarial e investigadora de andalucía. el profesional de la información, 20(5), 533-541. jürgens, b., herrero-solana,v. (2015). espacenet, patentscope and depatisnet: a comparison approach. world patent information. vol. 42. doi:10.1016/j.wpi.2015.05.004 jürgens, b., & herrero-solana, v. (2017). monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes. journal of nanoparticle research, 19(4), 151. jürgens, b. (2016). nanotechnology in spain: technology watch by patents (doctoral dissertation). university of granada. maghrebi, m., abbasi, a., amiri, s., monsefi, r., & harati, a. (2010). a collective and abridged lexical query for delineation of nanotechnology publications. scientometrics, 86(1), 15-25. meyer, m. (2002). tracing knowledge flows in innovation systems. scientometrics, 54(2), 193-212. miller, s. h. (2001). competitive intelligence–an overview. competitive intelligence magazine, 1(11). narin, f. (1994). patent bibliometrics. scientometrics, 30(1), 147-155. negash, s. (2004). business intelligence. the communications of the association for information systems, 13(1), 54. lloyd, m. (2015). patent vs scientific literature how do they compare?, amberblog. http://www.ambercite.com/index.php/amberbl og/entry/patent-vs-scientific-literature-acomparison (accessed 10.10.2015) salvador, m. r., & bañuelos, m. a. t. (2012). applying patent analysis with competitive technical intelligence: the case of plastics. journal of intelligence studies in business, 2(1). salvador, m. r., zamudio, p. c., carrasco, a. s. a., benítez, e. o., & bautista, b. a. (2014). strategic foresight: determining patent trends in additive manufacturing. journal of intelligence studies in business, 4(3). schmookler, j. (1966). invention and economic growth. harvard university press, cambridge, ma palop, f., & vicente, j. m. (1999). vigilancia tecnológica e inteligencia competitiva: su potencial para la empresa española. madrid: cotec. palmberg, c., dernis, h., & miguet, c. (2009). nanotechnology: an overview based on indicators and statistics. pavitt, k. (1985). patent statistics as indicators of innovative activities: possibilities and problems, scientometrics 7(1-2), 77–99. pritchard, a. (1969). statistical bibliography or bibliometrics?. journal of documentation, (25), 348-349. zuniga, p., guellec, d., dernis, h., khan, m., okazaki, t., & webb, c. (2009). oecd patent statistics manual. organisation for economic co-operation and development. page 4 editors note vol 10 no 1 editor’s note vol 10, no 1 (2020) on the 10th anniversary of jisib: reflection on academic tribalism this is volume number 10, meaning jisib has published articles in intelligence studies for ten consecutive years. we have addressed the changes in the discipline during these years in articles and notes. i want to share with you another reflection. this year i am a reviewer and a member of the organizing committee of two similar conferences. the first is the ci2020, a conference on collective intelligence with participants from many larger and well-known universities. the second is the ici2020, this year with a focus on collective intelligence and foresight. there are many more conference and journals presenting and publishing on similar topics simultaneously, but in different networks. science as a whole—the advancement of knowledge for the benefit of all mankind— would most likely be better off if at least some of these groups merged. that was also my impression when reviewing the extended abstracts for these two conferences. i also tried to see if members of the ci2010 conference would consider joining the other, but that seemed more difficult than first imagined. this is also about ownership and identity, which is not an entirely unfamiliar idea. the consequences of these tendencies are not favorable for the objects we study. the unnecessary division of networks that look at the same phenomenon is sometimes referred to as “academic tribalism.” academic tribes become a barrier to learning and this can result in closemindedness1. this is also according to my own experience. academic clustering is a similar mechanism whereby graduates from one institution favor those who come from the same institution, but there are also those universities that systematically refrain from this. among these is harvard university, which seldom hires their own phds, or so i have been told. if so, that is probably better for the progress of science. where is it meaningful to draw a line between academic groups then? everyone will agree that the natural sciences are quite different from the humanities. between psychology and business though there is much overlap with psychology in business. between accounting and management, a good understanding of how to manage a business requires the knowledge of income statements, balance sheets and how to set up a cash flow analysis. one way to think about division is if the method is different. according to this criterion most social scientists should be able to do each other’s work, and subsequently go to each other’s conferences. another meaningful division is based on experience and the depth of specialization obtained by the discipline. this criterion is less precise. i do not pretend to have the answer, but i think it’s a pity that all these tribes exist, with their own buzzwords often studying more or less the same phenomenon, with the same methods. what distinguishes intelligence studies from other tribes is, in my opinion, first of all that we see that the private organization is better organized as an intelligence organization, with focus on information gathering and analysis. it has less to do with departments of marketing, hr or accounting, even though the one does not exclude the other. another way is to see the intelligence organization as a superstructure, a layer that exists above all functional departments where the aim is to achieve a competitive advantage through better information. in this respect the need for ceos is not unlike those of ministers of state. now, is this perspective so radically different that it deserves its own tribe with its own journal and conferences? that is the important question. and in some way, i cannot help but think that learning would be better without them, that is, it would be better if it was all one big interchangeable group, going to one another’s conferences, and writing for each other’s journals. science would benefit from it. from time to time i have also peeked over into other groups and joined their conferences. what is astonishing especially for an outsider is that you are immediately confronted with a pecking order that 1 rogers, s. l., & cage, a. g. (2017). academic tribalism and subject specialists as a challenge to teaching and learning in dual honours systems; a qualitative perspective from the school of geography, geology and the environment, keele university, uk. journal of academic development and education, (8). journal of intelligence studies in business vol. 10, no 1 (2020) p. 4-5 open access: freely available at: https://ojs.hh.se/ 5 is related to who has been there the longest and published the most in the group. this cannot be an advantage for the advancement of science, i tell myself. but, then again, pecking orders seems to be the rule rather than the exception for most social creatures, not only chicken. the first article by nasullaev et al., entitled “technology intelligence practices in smes: evidence from estonia,” is on operationalization of technology intelligence practices by small firms in catching-up economies. their analysis reveals that elements of technology intelligence in large and small companies are similar. furthermore, they conclude that there is no unique set of technology intelligence. the second article by nguyen entitled “the effects of cross-functional coordination and competition on knowledge sharing and organisational innovativeness: a qualitative study in a transition economy” reveals the potentially significant effect of coopetition (i.e., the simultaneous coordination and competition) on the degree of knowledge sharing between marketing and other departments in business organisations. the enhanced knowledge sharing can, according to author, positively improve organisational innovativeness. the third article by hendar et al. entitled “market intelligence on business performance: the mediating role of specialized marketing capabilities” integrates market intelligence dimensions and one dimension of marketing capabilities, i.e. specialized marketing capabilities (smc), into an empirical model to try to gain a deeper understanding of the relationship between market intelligence and smc and how these factors shape business performance (bp). the study suggests that owners or managers of smes recognize that important market intelligence factors are increasing smc and bp. this helps them make better investment decisions in developing the right combination smc to increase bp. the fourth article, by zafary, is entitled “implementation of business intelligence considering the role of information systems integration and enterprise resource planning”. it shows the value of integrated information systems and enterprise resource planning in the success of business intelligence implementation. the author concludes that organizations should pay more attention to their working processes to improve business intelligence success. the fifth and last article is an opinion piece by barnea. the title is “how will ai change intelligence and decision making?” in the article barnea argues that with increased attention on artificial intelligence (ai) capabilities, the value of the human factor will not become redundant but rather improve its use. furthermore, in the future ai will be significant to analysis and predictions in advance of competitors’ moves and delivering early warning signals of threats both in the private sector as well as in state services. in the last issue of jisib we said we were looking forward to a meeting in bad nauheim for the ici2020. now due to the corona pandemic the conference will be held online, but we still hope to see you, on video camera, that is. as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2020 jisib, halmstad university. all rights reserved. page 4 editors note vol 9 no 3 editor’s note vol 9, no 3 (2019) the argument that “there is nothing new in the competitive intelligence field” it is often heard, and even more often seen written, for example on social media, that that there is nothing new in the competitive intelligence (ci) field. there are no new ideas, the ideas that are being expressed are the same old, there is no development, there is, at best, stagnation. even the old claim that ci is dead1 reappears with a certain frequency2: “competitive intelligence as a profession is dead. there are fewer and fewer full-time, dedicated ci professionals in organizations, and even fewer legitimate ci departments or functions. the need to understand an organization’s competitors has been diffused to several other functions including market research, finance, sales, r&d and others. what the founders of the profession jan herring, leonard fuld, and ben gilad built through the 80s and 90s no longer exists. and organizations are the worse off for it”3. is this true? yes and no. from a research perspective ci has developed and emerged with information technology (it) solutions over the past ten years. it has come to the point where it does not make much sense to talk about new ci practices. most advancements and developments are now about it solutions and applications. this has again given rise to a whole new world of intelligence related problems and opportunities, not only for engineers but for users of these technologies. it is probably fair to say that the intelligence perspective has never been as important for businesses as it is today. companies and organizations have never collected and analyzed as much information. another way to explain this development is to say that ci has evolved, thus is no longer the same. trying to look for the same or insisting that it has not changed gives the impression that there is nothing new in ci. ci consists of an interesting body of literature, but it was not the first term to deal with questions of intelligence in private organizations, and it is not the last. before ci there was social intelligence, strategic intelligence and corporate intelligence with their own consultants and literature. as sawka rightly points out ci was a label used in the 80s and 90s. other terms used include market intelligence, marketing intelligence, business intelligence, collective intelligence, financial intelligence, scientific and technical intelligence, foresight, insight, and equivalent terms in other languages, like “l’information stratégique et de la sécurité économiques” (sisse) [previously “intelligence économique"], “veille” in french and “omvärldsanalys” in swedish. all these fields, where a field is defined as a body of literature, basically study the same phenomenon, how to gather information to make better decisions. as such intelligence studies is a part of the information age. the information age gave birth to several bodies of literature, of which the more established include information systems, management information systems and customer relations management. the intelligence perspective never really caught on among business scholars, maybe because it was associated with industrial espionage. the intelligence parallel in business is also a bet, the argument that private organizations are better organized as intelligence organizations, much like in state and/or military organizations. the idea is that this will give better information, which again will lead to a competitive advantage. so far, this bet has not caught on. business organizations continue to be organized much as they were a hundred years ago: into production, sales, 1 sawka, kenneth. (2010). the death of the competitive intelligence professional. outward insights, 13(2), 36-39. 2 sawka, kenneth. the death of the competitive intelligence professional. retrieved january 30, 2020 from https://www.linkedin.com/feed/update/urn:li:activity:6627549366062194688 3 idem journal of intelligence studies in business vol. 9, no 3 (2019) p. 4-6 open access: freely available at: https://ojs.hh.se/ 5 marketing, hr, finance and accounting. however, the way people work in all of these departments with ever larger amounts of information and data is starting to look more like intelligence operatives with their extensive system of files. in other words, the ci position never really saw a breakthrough, but ci has become an ever more important part of employees’ jobs, as a function. how can we then explain the frequently raised discussion related to the problems of ci? let me suggest two answers, one general, the other more specific. once we create something, we insist that it has either to exist, as it is, or it must disappear, thus at the end it is declared dead. this is the western mind at work, thinking in dichotomies, a thing either exist or it does not exist. there is no room for evolution, only constants. if a phenomenon such as a discipline evolves, we shouldn’t say that it’s dead, it just isn’t the same anymore, and nothing is more natural than that. so, what must change is rather the way in which we think about the fields we study. the other suggestion is that the critic of ci has more to do with another problem, the selling of consulting services. the market for consultancy services is highly segmented and fiercely competitive. as consultants we are trying to make a name for ourselves in a niche we can call our own and strive to be an acknowledged expert in it. this takes years, often a whole career. academic careers are created much according to the same logic so the problem is the same there. the underlying message is “this is my area”, my niche, and as such i will defend it. what often happens is that another persons’ or group’s area grows into our own and sometimes is better at explaining the reality of our business problem, thus challenging our very raison d'être. instead we insist that we are still relevant refusing to read up on other areas. we cease to be curious and the very business problems we study pass on to others. some would argue this is what happened to ci. so, where is ci today? there certainly are many answers to this question. one suggestion is that it is more often treated as business intelligence again (it very much started there, but then without the it association), data mining, search engine optimization, social media marketing and digital marketing in general. it suffices to look at the articles in this issue to find other examples: bleoju et al. write about how moocs can be used to teach intelligence. sperkova writes about customer experience (cx) and voice of customer (voc). poblano-ojinaga et al. write about structural equation modeling for the identification of the intelligence factors. all authors have that in common that the are studying how organizations handle intelligence. in more detail, the first article by bleoju et al. entitled “empirical evidence from a connectivist competitive intelligence massive open online course (ci cmooc) proof of concept” reveals how “the ci learning community perceives the capability of a cmooc to train foreknowledge practices, given the best match between its content and context.” the paper argues for “an open intelligence approach to cmooc collective training.” the second article by maune entitled “competitive intelligence as a game changer for africa’s competitiveness in the global economy” develops a conceptual framework for how competitive intelligence can be adopted by african countries to improve their performance in the global economy. the third article by sperkova entitled “integration of textual voc into a cx data model for business intelligence use in b2c” is a summary of her phd, which will be defended in february 2020 at the university of economics in prague, the department of information technologies. the author presents a model to store the customer experience (cx) and voice of customer (voc) data as part of a business intelligence system. the model can help to improve customer relationships and make future performance more automatic and effective. the fourth article by palilingan and batmetan entitled “how competitive intelligence can be used to improve a management vocational high school: a case from indonesia” shows how competitive intelligence can be applied to make a vocational high school more efficient. the fifth and last article by poblano-ojinaga et al. entitled “effect of the competitive intelligence on the innovation capability: an exploratory study in mexican companies”, is an investigation using a methodology of structural equation modeling for the identification of the intelligence factors, to evaluate their relative importance and relationships with the innovation capability of mexican companies. the empirical results show that the relationship between competitive intelligence and the innovation capability is indirect, with knowledge management as a mediating factor. some news worth mentioning: we would like to thank the swedish research council/ nop-hs for receiving the “large” grant for open access journals for two years starting in 2020. jisib is now indexed by crossref, which should give users direct access to pdf full text through databases like scopus and web of science. the scip organization, owned by frost & sullivan, has been reignited with a new executive director. we wish them good luck. there are numerous conferences on intelligence related topics this spring and next winter. see the jisib website for details. some of the editors of jisib will be at the ici in bad nauheim 11-14 may 2020. we hope to see you there. 6 as always, we would above all like to thank the authors for their contributions to this issue of jisib. thanks to dr. allison perrigo for reviewing english grammar and helping with layout design for all articles. on behalf of the editorial board, sincerely yours, prof. dr. klaus solberg søilen halmstad university, sweden editor-in-chief copyright © 2019 jisib, halmstad university. all rights reserved. vol9no3paper2 to cite this article: maune, a. (2019) competitive intelligence as a game changer for africa’s competitiveness in the global economy. journal of intelligence studies in business. 9 (3) 24-38. article url: https://ojs.hh.se/index.php/jisib/article/view/475 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index competitive intelligence as a game changer for africa’s competitiveness in the global economy alexander maunea* auniversity of south africa, south africa; *alexandermaune6@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: empirical evidence from a connectivist competitive intelligence massive open online course (ci cmooc) proof of concept competitive intelligence as a game changer for africa’s competitiveness in the global economy alexander maune pp. 24-38 integration of textual voc into a cx data model for business intelligence use in b2c lucie sperkova pp. 39-55 how competitive intelligence can be used to improve a management vocational high school: a case from indonesia verry ronny pailingan and pp. 56-61 johan reimon batmetan v ol9,n o 3,2019 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 9,no.3,2019 gianita bleoju, alexandru capatina,valter pp. 7-23 vairinhos, rozalia nistor, and nicolas lesca effect of competitive intelligence on innovation capability: an exploratory study in mexican companie eduardo rafael poblano-ojinaga, roberto pp. 62-67 romero lópez, jesús andrés hernández gómez, and vianey torres-arguelles competitive intelligence as a game changer for africa’s competitiveness in the global economy alexander maunea* auniversity of south africa, south africa *corresponding author: alexandermaune6@gmail.com received 15 december 2019 accepted 30 december 2019 abstract this article presents a “competitiveness intelligence” conceptual framework developed from a literature review for adaptation by african countries to improve their competitiveness in the global economy. the role of competitive intelligence in national competitiveness has been shrouded with a lot of controversy in this era of trade liberalisation, globalisation and the fourth industrial revolution. we see africa’s poor performance in the global competitiveness rankings. research findings, however, show a positive nexus between competitive intelligence and competitiveness, though not much is known pertaining to africa. the presented conceptual framework will, however, act as a catalyst for the adoption of competitive intelligence by african countries to improve their performance in the global economy. this article is of great importance to policymakers, researchers and academia. furthermore, given the history and importance of competitive intelligence in economic development, the conceptual framework has the potential to inspire many african countries through subsequent adaptions. keywords africa, competitive intelligence, competitiveness, global economy 1. introduction the role of competitive intelligence in the global economy has attracted a lot of controversy and attention from researchers, policy makers and intelligence professionals. some have taken competitive intelligence (ci) to mean business or economic espionage. dishman and calof (2008) and casadosalguero and jiménez-quintero (2016) cited by salguero et al. argue that ci is based on the environmental school of strategic management and plays a very important role in the development and deployment of both national and corporate strategies. colakoglu (2011) argues that people must not confuse ci with economic espionage. richardson and luchsinger (2007) cited in colakoglu (2011) state that “economic espionage is unlawful and unethical while ci is legal and associated with a detailed code of ethics.” to bisson (2014), the scope of ci goes beyond entities, as new forms of territorial governance must include tools and methods of ci to optimise the creation of knowledge and intelligence. françois (2008) and moinet (2009) cited by bisson (2014) argue that this is defined as territorial ci. according to barnea (2013), for many years, intelligence capabilities have been recognized as one of the basic skills of a state, while decision-makers demand quality intelligence on which they can depend. to juhari and stephens (2006): “ci has become an indispensable part in strategic decision-making aspect of [companies] and nations. as history has shown, intelligence engagements have always been the forefront of military journal of intelligence studies in business vol. 9, no. 3 (2019) pp. 24-38 open access: freely available at: https://ojs.hh.se/ 25 processes, where country leaders and high ranking government officials use intelligence to make crucial decisions for political sovereignty, protection of countries and their people, for creating and maintaining strategic alliances and for predicting the future of their countries. it is apparent that the purposes for intelligence use in governing a nation are parallel to managing a business, where ci has a significant role in business survival, in maintaining relationships with other businesses, counterintelligence, short-term and long-term aims and objectives.” with the advent of globalisation, a term that was introduced in the 1980s, the role of intelligence becomes more visible and is strengthened by the increase in competition among nations. to afzal (2007), globalisation simply means growing integration of national economies, openness to trade, financial flows, foreign direct investment and the increasing interaction of people in all facets of their lives. it further implies the internationalisation of production, distribution and marketing of goods and services. globalisation brought with it both benefits and detriments. to todaro and smith (2003), globalisation presents new possibilities for eliminating global poverty and globalisation can benefit poor countries directly and indirectly through cultural, social, scientific and technological exchanges as well as trade and finance. some very important low-income countries like india and china have used globalisation to their advantage and have succeeded in achieving enviable economic growth rates and thus reducing some international inequalities (afzal, 2007). dollar and kraay (2004) note that over half of the developing countries that have embraced globalisation have benefited tremendously through increased trade and tariffs reduction. globalisation has also played a critical role in poverty reduction through the integration of economies. it has also helped improve the competitiveness of nations. opponents, however, argue that globalisation has worsened inequalities both across and within countries. this has caused serious competition across and within countries with developed countries establishing dominance over poor and developing nations. the effects are seen in environmental degradation, climate change and ballooning national debts. streeten (1998) observes that economic liberalisation, technological changes, and competition in both labour and product markets have contributed to economic failure, weakening of institutions and social support systems, and erosion of established identities and values. to afzal (2007), globalisation has been bad for africa and in many parts of the world for employment as international competition is forcing both governments and firms to ‘downsize’ and to adopt all necessary steps to save labour costs. these negative effects of globalisation might be a result of many factors affecting governments’ decision making processes, one of which includes lack of actionable intelligence critical in competitive environments. this argument is supported by authors such as lee and karpova (2018), who state the importance of actionable intelligence in determining a country`s competitiveness in the new global arena. the lack of ci in many african countries may therefore contribute to the negative effects of globalisation as pointed out by afzal (2007). organisations such as the world economic forum (wef), international institute for management development (imd) and the world bank’s international finance corporation (ifc) have provided national economic metrics since the 1970s. for example, the wef provided frank overviews of nations’ competitiveness. these measurements have spurred robust debates among policymakers. recently, the wef introduced a new methodology that strengthens the importance of the role of human capital, innovation, resilience and agility. this is in context with technological changes espoused by the fourth industrial revolution (fir). despite years of positive talk about africa’s economic growth, africa’s performance leaves much room for improvement as shown by competitiveness indexes. for example, the global competitiveness index (gci) shows africa’s diverseness at the bottom of the rankings. among the 148 economies covered by the wef survey, mauritius is 49 and south africa 67, barely in the top half of the ranking. it is argued that the root causes of slow growth and inability to leverage on new opportunities offered by the fir continue to be the old developmental issues such as institutions, infrastructure, culture and skills among many other factors. much attention is required on basic factors such as health, skills, good governance and financial prudence. africa, on average, is the worst region across all 12 pillars of competitiveness as measured by the wef’s 26 gci, with major weaknesses in the basic enablers or drivers of competitiveness such as security, rule of law, red tape and corruption. of particular concern also is the unsustainable level of public debt, with the average public debt-to-gdp ratio, for example, in subsaharan africa, increasing from 32.4% in 2014 to 45.9% in 2018. despite these traditional weaknesses, ci can still play a critical role in the continent’s future, leveraging on the continent’s resource base, young growing population and technological advancement of the fir. it is the centrality of knowledge and actionable intelligence in decision making and policy formulation that places africa in a position that requires the embracement of ci to enhance its competitiveness in the global economy. to date, only south africa and nigeria have taken a serious stance in embracing the concept of ci through opening the scip’s chapters. this is a commendable move towards competitiveness, though certain quarters feel that scip is an american influence. however, this can be adopted with certain amendments to suit the african context. in recent years, information and knowledge have become two important elements in decision making at both corporate and national levels. informed decisions are critical in resource allocation, production and marketing. theories such as competitive advantage theory (porter, 1990), comparative advantage theory (krugman and obstfeld, 2000) and the new growth theory (romer, 1986 and krugman, 1990) will be utilized in this study as they have proved to be critical in national competitiveness. lee and karpova (2018) argue that, in the new global environment, knowledge becomes a central factor in determining competitiveness. the purpose of this article is to develop a conceptual framework that enhances africa’s competitiveness as a continent in the global family of nations leveraging on its untapped natural resources, human capital intelligence, young population and vast virgin lands. to help construct this framework, ci and competitiveness indicators will be complimented by expert opinions and current research findings as explained in the methodology section below. what needs to been seen is whether embracing ci will help africa achieve its 2063 seven aspirations for socioeconomic transformation or if there are other factors that are critical in addressing africa’s challenges at the global level. the remainder of the article is divided into four sections. 2. literature review 2.1 definition of terms in his article entitled, “competitive intelligence and firm competitiveness: an overview,” alexander maune (2014) provides an in-depth analysis and definitions of the terms competitive intelligence (ci) and competitiveness. a number of definitions have been provided by a number of different authors and this article will be guided by the following definitions taken from the above-mentioned article. pellissier and nenzhelele (2013) define ci “as a process or practice that produces and disseminates actionable intelligence by planning, ethnically and legally collecting, processing and analyzing information from and about the internal and external or competitive environment in order to help decision-makers in decision-making and to provide a competitive advantage.” this definition is in line with casado-salguero and jiménezquintero (2016) cited by salguero et al. (2017) who define ci as “a set of practices aimed at gathering information from the business environment ethically and legally, in order to transform it into intelligent information useful for strategic decision-making and, therefore, leading to business success and survival.” to barnea (2013) ci has its roots from national intelligence that involves secret state activities to understand or influence foreign entities. barnea (2013) further argues that, governmental decision-makers are aware that intelligence is an important and often critical tool to the national decision-making process. to him ci is based on the “intelligence cycle” (www.cia.gov, 2013 and omand, 2010). ci adopted the discipline of national intelligence and applies it to its needs, with necessary modifications. according to field manual [fm] 34-3 (1990), ci operations follow a four-phase process known as the intelligence cycle. the intelligence cycle is oriented to the mission (fm 34-3, 1990); this can be for the country or organisation. the fm 34-3 (1990) reports that, “supervising and planning are inherent in all phases of the cycle. the intelligence cycle is continuous. even though the four phases are conducted in sequence, all are conducted concurrently. while available information is processed, additional information is collected, and the intelligence 27 staff is planning and directing the collection effort to meet new demands. previously collected and processed information (intelligence) is disseminated as soon as it is available or needed.” competitiveness is defined in maune (2014a) as the abilities of individual firms, or whole sectors, regions and even countries to successfully assert themselves in the domestic and global market. it is not only a result of entrepreneurial activity of individual firms, but also a result of an appropriate structural policy, functioning competitive policy and adequate infrastructure. competitiveness is also seen a multidimensional concept that refers to the ability by nations, industries, and firms to create sustainable competitive advantages in the global market. globalization of markets has created the need to enhance companies’ and countries’ competitiveness more rapidly hence the call for the adoption of ci. this is in line with arguments by romer (1986) and krugman (1990) who in the new growth theory propose that knowledge significantly increases production output in an industry, even with the same amount of traditional inputs, such as labour and capital. subsequently, the industry competitiveness increases substantially, especially in highly sophisticated sectors. however, since ci is about how to gather and analyse information and this is predominantly done through the internet with the help of software, africa is at a great disadvantage due to poor or lacking internet access and connectivity. 2.2 global overview of the role of competitive intelligence on competitiveness theoretical debates have generally focused on the increasing roles and functions of ci on competitiveness. ci plays an intermediation role between economic development and its factors. according to rouach and santi (2001), “ci’s benefits were long understood in the states of pre-modern germany.” rouach and santi (2001) further argue that “more modern german intelligence grew in the 18th century, and by scouting the european continent the germans discovered they could compete with british and french firms by applying foreign scientific advances to their own industrial processes.” because of that, the germans rapidly developed their own base of education and research that was used as a foundation for technological innovation (rouach and santi, 2001). rouach and santi (2001) state that “japan was also early endowed with a grasp of the importance of ci.” to rouach and santi (2001), japan and intelligence have grown hand-inhand. information serves as the axis and central structural support of the nation’s companies.” herring (1992) in fleisher and wright (2009) comments “that japanese corporate ci capabilities are well developed, benefiting both commercial and governmental programs, which in turn support japan’s international competitiveness.” to fleisher and wright (2009), kahaner (1996) observes that “ci has had a significant influence in the country’s prosperity and claims; ‘it is their absolute and unbending belief in ci as a strategic corporate tool to make the best decision possible. ci is the secret to their continued success.’” søilen (2017) argues that “japan and sweden are mentioned as examples of countries that do take this discipline seriously.” kahaner (1996) cited by global intelligence alliance [gia] (2004) provides the following arguments regarding the impact of intelligence: “the impact of intelligence operations is indirect, just like in advertising, when the decision-maker does not know which part of the budget is actually responsible for the profit. similarly, there is usually no direct causal relationship between revenues and the money spent on a particular piece of intelligence. therefore, it may be difficult to justify intelligence expenditures to top management. one way of looking at the gains is to evaluate how much money the company has lost by not having effective intelligence. even so, it is difficult to prove that a lost deal or a late product launch was in fact due to inaccurate information about the competitors’ actions or customer preferences.” according to prescott and bhardwaj (ref. herring, 1999) cited in gia (2004) argue that, “the benefits of ci are directly identifiable, although there are no quantitative measures to support this. an improved market position and improved revenue/profits are not directly identifiable since they are ‘uncertain effects.’” these benefits fall into the category of bottomline measures, which are usually the most commonly requested. fleisher and wright (2009) cite chao (1998) and tao and prescott (2000) who state that 28 “…chinese leaders have considered intelligence as a useful means of helping the country to overcome its relative isolation from other economic and global trading systems.” fleisher and wright (2009) further state that “tzu made the case for intelligence as a key element of warfare when he wrote, ‘know the enemy and know yourself; in a hundred battles you will never be in peril. when you are ignorant of the enemy but know yourself, your chances of winning or losing are equal. if you are ignorant of both your enemy and yourself, you are certain in every battle to be in peril’”. du toit and strauss (2010) cite viviers et al. (2005) who argue that the business environment in africa is highly complex thereby affecting the competitiveness of the continent. trade liberalisation and globalisation have exposed africa to foreign competition. du toit and strauss (2010) opine that “trade liberalization and globalisation together with the problems posed by fluctuating financial markets and unstable political conditions call for effective ci practices.” to du toit and strauss (2010), no nation can develop and compete without adequately organizing its ci. du toit and strauss (2010) further state that, “ci as a business discipline has formed an integral part of efforts to enhance the competitive behavior of african companies and society as a whole. entry into the global economy requires highgrade ci.” du toit and strauss (2010) state that “ci has long been acknowledged as a strategic management means to improve competitiveness.” ci becomes critical in decision making processes and policy formulation. according to sewdass and toit (2014), “ci has a positive impact on economies and on the quality of lives of citizens.” the current information/knowledge generation has placed ci at the centre stage for competitiveness and economic growth. previously, factors such as capital, labour and natural resources were traditionally considered as the only factors that matter for economic growth. maune (2014b) argues that, the emergence of the internet and online databases have offered an almost inexhaustible supply of information that has caused information overload in many instances. calof and skinner (1999) in maune (2014c) argue that a country is likely to underperform without an appropriate ci infrastructure. they further state in sewdass and toit (2014) that, “countries such as france, sweden, japan and canada have recognized the value of government and industry working jointly in the development of an intelligence culture.” according to sewdass and toit (2014), “the new paradigm in development economics is based on self-analysis, self-reliance and self-renewal, which would seem to necessitate a development-orientated intelligence policy in a country.” pellissier and kruger (2011) cited in sewdass and toit (2014), opine that “utilising ci enables companies in developing countries to gain a greater market share and to compete successfully against international competitors.” the implementation of ci contributes to the generation of fdis in developing countries through value addition and beneficiation given the natural resources that are in abundance. maune (2014a) and maune (2015) state that “reliable global information has become central to national success, whether the need is for knowledge of an industry, a market, a product or a competitor.” ci is now at the cutting edge of competition, survival and growth of economies (maune, 2014b). degerstedt (2015) argues that “the objective of ci is to understand how the surrounding competitive environment will impact an organization – by monitoring events, actors, trends, research breakthroughs, and so forth – in order to be able to make relevant strategic decisions.” a major trend in the world today is the increasing competition in global and digitalized markets where the speed of change and innovation is becoming faster than ever before due to developments in information technology (degerstedt, 2015). ci provides a better understanding of the dynamic global world. however, søilen (2017) argues that new technology is also a threat to companies as today, when every individual is a potential spy. he further argues that corporate espionage has also become a big problem with its consequences still underestimated. 2.3 competitive intelligence and competitiveness in africa literature shows that limited research has been conducted on ci and competitiveness in africa. the state of ci remains fragmented in africa. with the exception of south africa and nigeria that have managed to establish scips chapters, nothing much is taking place in other domains in the african continent regarding ci. a scip chapter was launched in sa in the mid1990s and, albeit slowly, companies are becoming increasingly competitive minded. 29 until that time, research into ci in south africa had also been limited. the first comprehensive research projects [in africa] were launched in the beginning of the century in south africa. before that, only a few papers were written on ci (viviers and muller, 2004 in viviers et al., 2005). du toit and strauss (2010) in maune (2015) state that as a result of factors such as history, culture, diversity, geography, and political and institutional landscape, the business environment in africa is highly complex, and this has affected its competitiveness in the global economy. maune (2015) argues that, for ci to flourish in africa and for the discipline to be implemented and used optimally, there has to be an appropriate awareness of ci and a culture of competitiveness. du toit and strauss (2010) point out that african society also tends to favour collectivist. collectivism, in contrast with individualism, refers to a society, in which people from birth onwards are integrated into strong, cohesive in-groups, which throughout people's lifetimes continue to protect them in exchange for unquestioning loyalty (mersha, 2000). without proper empirical evidence of ci as a source of competitiveness, awareness and attitudes that favour both ci and information sharing, it is difficult to develop ci programmes within the african continent (du toit and strauss, 2010). research shows that south africa and morocco have taken greater strides in in designing national competitive intelligence systems. there has been a number of studies that have been carried out in south africa, in particular on ci practices, showing how the concept has been developed in that country in comparison with other african countries. table 1 shows the poor performance of african countries in terms of global competitiveness rankings as given by the literature. this table helps in building a case for the need to adopt competitiveness strategies by african countries, through embracing ci. these figures are important for decision making and policy formulation as well as policy targeting by african countries to achieve sustainable growth and compete meaningfully in the global economy. 3. methodology the purpose of this article is to construct a ‘competitiveness intelligence’ conceptual framework that can be adopted by african economies. this article offers a conceptual framework based on a literature review. it uses grounded theory rather than description of data as stressed by strauss and corbin (1990). this is important for research in order to establish the exact focus of the study and its potential contribution. one of the aims of science is theory testing or building, as without thorough literature reviews it would be impossible to achieve this. the authors identified two major differences between theory and descriptions. this article was also informed by the procedures expounded by jabareen (2009) in his study entitled, “building a conceptual framework: philosophy, definitions, and procedure.” this article adopted the wilsonian methods of concept analysis (wilson, 1963, 1987). these are based on a philosophical design, a literature study and intellectual analysis without empirical (qualitative or quantitative) methods. a literature review was conducted on some of the peer-reviewed and published journal articles on ci in africa. to identify relevant literature and journals, academic databases and search engines were used. a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. keywords including ‘competitive intelligence,’ ‘business intelligence,’ ‘tactical intelligence,’ ‘market intelligence,’ ‘corporate intelligence,’ ‘competitor intelligence,’ ‘social competitive intelligence,’ ‘technological intelligence,’ ‘product intelligence,’ and ‘strategic intelligence’ were used in search engines to find relevant sources. to ensure reliability, peer-reviewed articles were manually reviewed. the researcher skimmed through the text of the journal articles first, checking whether it was relevant for the purpose of this research article. reviewing data of existing journal articles was necessary to enhance the generalisability of the findings (morse, 1999). the purpose of this review was to identify the contributions of research in advancing the understanding of the concepts that make ci. criteria for inclusion of articles in the review included the following: • written in english • published in a peer-reviewed journal • cited ci concepts in developing this conceptual framework, the researcher did not simply review and summarised some body of theoretical or empirical publications but also considered other conceptual resources for current 30 knowledge, such as unpublished papers, dissertations in progress, and grant applications, as well as in the heads of researchers working in the field of ci as suggested by locke et al. (2007). the researcher worked closely with advisors in the field of ci. the researcher also brought in ideas from outside the traditionally defined field of ci and integrated different approaches, lines of investigation, or theories that had no previous connections. the researcher’s purpose was not only descriptive, but also critical. the researcher used literature not as an authority to be deferred to, but as useful but fallible sources of ideas about developments in ci. the researcher developed the framework to serve as the basis for understanding the causal or correlational patterns of interconnections across events, ideas, observations, concepts, knowledge, interpretations and other components of ci. table 1 global competitiveness ranking, 2012 – 2019 for african countries. source: author’s own compilation, constructed from literature specifically for this study. country gci 2019 gci 2018 gci 2016/17 gci 2015/16 gci 2014/15 gci 2013/14 gci 2012/13 rank /141 rank /140 rank /138 rank /140 rank /144 rank /148 rank /144 morocco 75 75 70 72 72 77 70 algeria 89 92 87 87 79 100 110 tunisia 87 87 95 92 87 83 egypt 93 94 115 116 119 118 107 mauritius 52 49 45 46 39 45 54 south africa 60 67 47 49 56 53 52 rwanda 100 108 52 58 62 66 63 botswana 91 90 64 71 74 74 79 namibia 94 100 84 85 88 90 92 kenya 95 93 96 99 90 96 106 côte d’ivoire 118 114 99 91 115 126 131 gabon 119 108 103 106 112 99 ethiopia 126 122 109 109 118 127 121 cape verde 112 111 110 112 114 122 122 senegal 114 113 112 110 112 113 117 uganda 115 117 113 115 122 129 123 ghana 111 106 114 119 111 114 103 tanzania 117 116 116 120 121 125 120 zambia 120 118 118 96 96 93 102 cameroon 123 121 119 114 116 115 112 lesotho 131 130 120 113 107 123 137 gambia, the 124 119 123 123 125 116 98 benin 125 123 124 122 130 119 mali 129 125 125 127 128 135 128 zimbabwe 127 128 126 125 124 131 132 nigeria 116 115 127 124 127 120 115 madagascar 132 128 130 130 132 130 congo, drc 139 135 129 liberia 131 129 128 111 sierra leone 132 137 138 144 143 mozambique 137 133 133 133 133 137 138 malawi 128 129 134 135 132 136 129 burundi 135 136 135 136 139 146 144 chad 141 140 136 139 143 148 139 mauritania 134 131 137 138 141 141 134 seychelles 76 74 eswatini 121 120 guinea 122 126 burkina faso 130 124 angola 136 137 4. developing the “competitiveness intelligence” conceptual framework trade liberalization and globalisation have exposed africa to serious global competition. this has been a wakeup call for africa to increase its competitiveness. many suggestions have been tabled on how africa can improve its competitiveness globally. this study has, however, resulted in the construction of a conceptual framework as a result of the confluence of ci and competitiveness. the conceptual framework in figure 1 was developed out of this confluence and figure 2 shows a more refined and straight-forward framework. ci is defined as a process or cycle in the literature section above and competitiveness is defined as the ability of a country (region, location) to deliver the beyondgdp goals for its citizens today and tomorrow. although there are different theoretical approaches to the measurement of competitiveness, three well known indices include the global competitiveness report prepared by the wef, the world competitiveness yearbook prepared by the imd and business competitiveness ease of doing business report prepared by the ifc. these are all prominent and have been used to construct the “competitiveness intelligence” conceptual framework described herein. owing to different definitions, indices and data sources these approaches use, rankings of competitiveness of countries are different, hence countries are encouraged to follow either one approach or to follow them concurrently. these approaches use a multitude of indicators—partly hard data, partly survey results—to assess the competitiveness of countries. this has the advantage of measuring a wide range of economic aspects, which potentially reduces measurement error and help cope with the complexity of the problem, such as differences in countries’ starting position and socio-economic systems. a disadvantage of "large indicator approaches" is that they sometimes lack a clear concept. the reason why african countries must embrace ci is that very few seem to know themselves. for example, very few countries in africa can quantify the amount of mineral resources they have. very few keep up to date statistics that are critical for decision making and negotiating deals, for example, with investors. investment in ci should be a starting point for many african countries and this should be embraced at a grassroots level. educational programs need to address competitive intelligence issues especially in this era of big data analytics, artificial intelligence and connectivity. calof and viviers (2001) indicate that appropriate education about intelligence is the only way to develop correct attitudes towards ci, and that awareness of ci can be enhanced through responsible reporting of intelligence results by the media, associations and other opinion leaders, as was the case in canada and the usa. they add that the most successful technique for stimulating ci within organisations is to conduct training sessions for each industry. to cement the centrality of ci in achieving national competitiveness lee and karpova (2018) reformulate the definition of competitiveness. to lee and karpova (2018), “competitiveness is an ability to achieve a high standard of living through productivity growth in the new global environment, where knowledge [ci] becomes a critical factor.” although macroeconomic fundamentals have been considered critical in explaining economic development trends, ci has long been acknowledged as a strategic management means to improve competitiveness (viviers and muller, 2004 and de pelsmacker et al., 2005). the space age, electronic, global village and the fir era have seen the phantasmagoria of events, ideas, and images, exploding worldwide. this era has marked the dawn of a new reality, that is, truly global in its nature, snowballing with the enormity of its ideas and the velocity of its changes. the present era is even more accelerative, so much that countries need to embrace ci to remain competitive in the global economy. ci touches a number of fields and areas, including: • market intelligence, • competitor intelligence, • technological intelligence, • operational intelligence, • strategic intelligence, • product intelligence and • social competitive intelligence (degerstedt, 2015) degerstedt (2015) states that a new term called “social ci” will be used to refer to any ci process, method or tool that is adapted for the 32 networking organization. social ci relies on notions of enterprise 2.0 and wikinomics, using systemic principles such as openness, participation, individual freedom, democracy, self-organization, sharing and co-creation. ci programs are generally project-oriented, going after knowledge to address or answer a specific question. facilitators and teams are formed around key issues, and then let loose to find the key information that leads to the best strategic or tactical decision. ci identifies knowledge gaps and then goes out and fills them. ci has also been identified as critical in designing economic policy and programs (calof, et al., 2015). figure 1 competitiveness intelligence conceptual framework. created for this study from a literature review. 33 there is need for the continent to fully embrace ci so as to achieve meaningful and sustainable growth rates given the abundant natural resources as well as the intellectual capacity. ci must be the focal point in policy formulation and strategic planning within government structures. ci provides the foundation or starting point in policy direction and this is critical as it identifies the countries’ strengths, weaknesses, opportunities and threats. the effort is worth investing as it gives government direction in resource allocation. the role of information in this technological era cannot be over emphasized, hence the need for governments to join hands with academia and the private sector to fully embrace ci towards economic growth and development. ci will help governments formulate sustainable policies that are growth oriented by providing the much-needed intelligentsia. governments can make use of the available national and military intelligence resources or refocusing them towards economic development and growth. these institutions are well established and resourced with intellectual capabilities in a number of economic areas such as cyber technology, agriculture technology, artificial intelligence, fintech and medicine. innovative ideas and technologies must be seen emanating from these institutions. these institutions must be the source of start-up companies as well as spillovers to the corporate sector, and creating synergies with academia and the private sector. a well-designed system of ci can help nations in the strategic planning process, as well as in determining the intent and ability of their competitors in the global economy, and also determine the extent of the risks to which they may be exposed to. although organisations and countries are well aware of the methodologies and tools of ci, it is not possible to transpose them directly to a developing country, as careful analysis of the ci cultural context must be undertaken to understand the existing business culture. this was the conclusion by dou and manullang (2004) in a research study on ci and regional development in indonesia. african countries must emulate innovative approaches from countries such as israel to grow their economies in a sustainable manner. there must be a confluence between private sector, government and academia for african countries to develop and compete meaningfully in the global economy. africa must also create an environment that promotes innovation and creativity through establishing technological hubs, venture capital markets and tolerance to failure. ci growth in africa must be promoted through academic development (courses and research), corporate activity (exporting firms) and government activities. for example, the canadian government has come up with three broad programs to develop ci (calof, 2016). a program aimed at enhancing its own ability to develop ci, a program for industry and others to develop ci as well as a program to help communities develop ci for local economic development. a review of these programs shows the positive economic impact of ci. the following are some of the programs that can promote ci: • training initiatives and creating intelligence units, • sponsoring industry and others to develop ci (joint projects between government, academia and business working together to develop ci), • sponsoring communities to develop ci or local economic development, • joint intelligence assistance, for example, french government ci assistance to companies and associations through the chamber of commerce (bisson, 2014) and in israel where military, academia and business have come together in the negev desert to develop a cyber-city (nakashima and booth, 2016). another example is sweden, which for the last several decades has shown a great increase in the interest in intelligence as a topic. hedin (2004) argues that this interest has come from the government, from associations, from universities and from companies and organizations that have seen a greater need for ci. these developments in modern swedish ci figure 2 simplified “competitiveness intelligence” conceptual framework. created for this study from a literature review. 34 have led to a mature and competitive ci industry in comparison to that of other european countries. as of 2004, intelligence education and training was offered by no less than nine universities, five colleges, four private companies and five governmental institutions (hedin, 2004). in sweden, all men are required to participate in military service for a period of 9-18 months. intelligence and communication were then two topics that were taught. since it is obvious from a military perspective that it is virtually impossible to act properly without good intelligence, this lesson has been learned by many that later continued with a career in business (hedin, 2004). this has helped shape the ci industry in sweden in a greater way. information or intelligence has proven to be a critical factor in economic growth the world over. hughes (2005) argues that in order for an organization or country to be competitive, a successful strategy to locate itself in the market is vital. he further argues that ci is a tool to increase competitiveness hence the arguments by viviers et al. (2005), that countries must inculcate cultures that value information and intelligence, in their response to why europe and asia are the leaders in ci. to du toit and strauss (2010), hardly any nation can develop and compete without adequately organizing its information infrastructure and africa suffers from poor infrastructure-physical, institutional and procedural. intelligence had been in use since the exodus of egypt when moses sent the 12 spies to the land of canaan, the promised land (torah, numbers chapter 13). many countries made use of intelligence during and after world war ii to industrialize through economic espionage, which has been proven to be illegal. since then, ci has been developed to gather critical intelligences in a legal and more acceptable way. the “competitiveness intelligence” conceptual framework will be critical in influencing policy formulation, implementation, as well as policy targeting through provision of the much-needed critical intelligentsia. this conceptual framework will also help trigger debate and further future research on the role of ci in national competitiveness, especially in africa. although theoretically ci is argued to influence competitiveness, very few empirical studies have been done to test and determine the direction of this relationship. therefore, as much as there is theoretical evidence supporting the positive relationship between ci and competitiveness there is need to test empirically this relationship. the proposed hypotheses will go a long way in providing such evidence. the researcher proposes to follow a simplified research model and hypotheses (figure 3), derived from the literature review, for the purposes of future research: hypothesis 1 (h1). wef competitiveness drivers have a positive effect on national competitiveness. hypothesis 2 (h2). imd outcomes and drivers have a positive effect on national competitiveness. hypothesis 3 (h3). ifc ease of doing business has a positive effect on national competitiveness. hypothesis 4 (h4). ci has a positive effect on wef competitiveness drivers. hypothesis 5 (h5). ci has a positive effect on imd competitiveness outcomes and drivers. hypothesis 6 (h6). ci has a positive effect on national competitiveness. figure 3 proposed research model and hypotheses. created for this study from a literature review. 35 hypothesis 7 (h7). ci has a positive effect on ifc ease of doing business. a model constructed on the basis of the variables and hypotheses described above is expressed in figure 3. this model will help identify the factors that influence national competitiveness through ci, in addition to analyzing how these factors are interrelated. this relationship can be analysed through structural equation modelling in r. 5. conclusion in this article the researcher started with a brief background of ci and competitiveness as well as defining these two concepts. the influence of trade liberalization, globalisation and the fir was also assessed in the context of competitiveness. measurements of competitiveness as given by institutions such as the wef, ifc and imd were also taken into consideration as these were critical in tracing africa’s performance globally. theories such as the new growth theory by romer (1986) and krugman (1990) were also looked at and their role in influencing ci adoption. lee and karpova’s (2018) argument on the centrality of knowledge in national competitiveness formed the backbone of this article. research also shows that ci adopted the discipline of national intelligence and applies it to its needs, with necessary modifications. the global overview of ci and competitiveness was also taken into consideration, tracking it back to the chinese fighting their isolation from other economic and global trading systems as provided by chao (1998) and tao and prescott (2000). japan and some european countries were also analysed in the theoretical review. arguments by researchers such as calof and skinner (1999), rouach and santi (2001), fleisher and wright (2009), sewdas and toit (2014), degerstedt (2015) and soilen (2017), among others, were considered in building the case for the development of the conceptual framework for adoption by african countries. reasons as to why countries need ci now more than ever were also given. the article also provided a brief background analysis of ci and competitiveness in africa with table 1 denoting the gci for african countries performance rankings from 2012 to 2019, taken from wef’s global competitiveness reports. arguments by viviers and muller (2004), du toit and strauss (2010) and maune (2015) that the business landscape in africa is highly complex due to its historical, cultural, diversity and political factors were noted as these had seriously affected africa’s competitiveness globally. a brief methodology informed by a literature review was presented and data was gathered for the construction of the “competitiveness intelligence” conceptual framework as presented in figure 1 and figure 2. section four of the article presents the development of the conceptual framework and some analysis. the researcher recommends the adoption of other research methods to measure the impact of ci on competitiveness in africa as the field of ci has proved critical in influencing economic growth and development in developing countries. commentators, knowledge management experts and intelligence researchers, that is, business and competitive intelligence alike, are always looking for better ways of doing things through intelligence. the following will be areas that can stimulate future academic research: the impact of ci on economic growth in africa, big data and ci in developing countries, ci, ai and unstructured data (social media intelligence) in africa, intelligence and policy – the evolving relationship and intelligence community and policy-maker integration. also crucial to the adoption and implementation of ci is the three-legged approach to the embracement of ci towards economic growth and development, that is, the confluence of government, academia and the private sector. ci is critical as was stated in literature in providing economic solutions to challenges facing africa as it moves ahead with its agenda 2063. some of these challenges, if not all, are due to lack of actionable intelligence. 6. references afzal, m. 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(2020) the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry. journal of intelligence studies in business. 10 (3) 3862. article url: https://ojs.hh.se/index.php/jisib/article/view/588 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering 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and bus se, germany *tefan.zwerenz.sz@googlemail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: v ol10,n o 3,2020 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 10,no.32020 opinion: a project management approach to competitive intelligence miguel-ángel garcía-madurga and miguel-ángel esteban-navarro pp. 8-23 an examination of the organizational impact of business intelligence and big data based on management theory mouhib alnoukari pp. 24-37 the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry stefan zwerenz pp. 38-62 the impact of perceived accounting benefits on the enterprise resource planning success: the mediating role of effective system use phan thi bao quyen and nguyen phong nguyen pp. 63-79 financial intelligence: financial statement fraud in indonesia muhammad ikbal, irwansyah irwansyah, ardi paminto, yana ulfah and dio caisar darma pp. 80-95 the linkage between competitive intelligence and competitive advantage in emerging market business: a case in the commercial vehicle industry stefan zwerenza,* aman truck and bus se, germany *corresponding author: stefan.zwerenz.sz@googlemail.com received 8 september 2020 accepted 26 october 2020 abstract to achieve competitive advantage (ca) in emerging markets (em) firms are suggested to increase market orientation, using competitive intelligence (ci) as a source to increase firm performance. however, in-depth linkage between ca and ci, as well as its awareness/culture and process/structure constructs, has been researched and understood only in a limited way in general and for em business in particular. this paper gives in-depth clarification of six research questions relating to the connection between ci, its constructs and ca for em business as well as how ci as a product/process could be adapted for a larger impact on ca. it reports on a qualitative, document and interview data based in-depth single case study at a ci department of a european union (eu) commercial vehicle manufacturer engaging in em business. it finds that overall the linkage of ci for ca was traceable and transparent to users/generators of ci in the specific case with ambiguously perceived limitations, and influenced by seven identified factors. seven out of eight pre-identified ci constructs were promoted but also heterogeneously understood as contributing to ca, with no other relevant constructs identifiable. adaptions for more impact on ca were recommended for ci as a product in a limited sense, and as a process with eight potential levers more comprehensively. these results help businesses to improve ci, its constructs, its products and process for a better linkage to ca and firm performance. keywords competitive advantage, competitive intelligence, firm performance 1. introduction emerging markets (em) became highly attractive target markets in the last two decades (london and hart, 2004; goldmansachs, 2007, 2011; international monetary fund, 2011) as part of firm growth strategies to expand to new markets (ansoff, 1965). they are characterized as turbulent, high velocity, unstable, unpredictable and high rivalry environments, quickly changing in opportunities and threats (pillania, 2009; chen, riitta, mcdonald & eisenhardt, 2010). this requires firms’ to respond by adjusting management activities (fahy, 2002) to not lose their competitive advantage (ca) (cuervocazurra, maloney & manrakhan, 2007). that is why “today’s business environment demands a comprehensive system for managing risks in the external business environment“ (calof & wright, 2008, p.3) for rapid competitive and strategic maneuvering (thomas & d’aveni, 2009). hence, “with high market turbulence and high competitive intensity it is crucial to continually gather and utilize market information to adapt adequately. under these conditions, a market orientation is assumed to journal of intelligence studies in business vol. 10, no. 3 (2020) pp. 38-62 open access: freely available at: https://ojs.hh.se/ 39 represent a superior market learning capability, giving a competitive advantage” (ottesen & gronhaug, 2004, p.956). moreover, academic writing proposes that competitive intelligence (ci) can deliver required knowledge of the external environment (kohli & jaworski 1990; trim, 2004; dishman & calof, 2008; fleisher, wright & allard, 2008; prior, 2009; wright 2013) for firm competitiveness (maune, 2014). nevertheless, the linkage between ci and ca has been researched in only a limited way in general (miles & darroch, 2006; seyyed amiri, shirkavand, chalak & rezaeei, 2017) and for em business in particular (adidam, banerjee & shukla, 2012). in the quest for superior firm performance in em business, in-depth understanding of that linkage is considered critical (kumar, jones, venkatesan & leone, 2011). this study aims for in-depth understanding of the linkage between ci, its constructs and ca with regard to its perceived potential and transparency amongst ci generators and users. furthermore, it clarifies how ci as a process and a product can be managed and/or modified for ca in em business. 2. literature review and knowledge gap the literature proposes a connection between the concepts of ca and environmental based knowledge (day & wensley, 1988; civi, 2000; hult, ketchen & slater, 2005; ketchen, hult & slater, 2007; voola & o’cass, 2008). enhancing that conceptual idea, an empirically supported (april & bessa, 2006; badr, madden & wright, 2006; kumar et al., 2011; adidam, banerjee & shukla, 2012; seyyed amiri et al. 2017), but not undisputed (connor, 2007; ketchen, hult & slater, 2007; qiu, 2008; kraaijenbrink, spender & groen, 2010) linkage between firm performance, ca and the concept of ci was found in existing research (figure 1). however, the concept of ci itself was heterogeneously defined (wright & calof, 2006; bisson, 2014; grezes, 2015) and described with varying terminology (table 1), causing difficulties identifying a comprehensive body of academic knowledge. nevertheless, conceptual frameworks for the complex (dishman & calof, 2008; saayman et al., 2008, nasri, 2012) connection between ci, its constructs, ca and firm performance (nadkarni & barr, 2008; qiu, 2008; nasri, 2012) were identifiable in the literature. based on two suggested overarching viewpoints of ci (seyyed amiri et al., 2017)—process and structure (gayoso & husar, 2008; saayman et al, 2008) as well as organizational ci awareness and culture (nasri, 2012; asghari, targholi, kazemi, shahriyari & rajabion, 2020)—it was advocated for potential links to ca contributing and non-contributing ci constructs (lewis, 2006; maune, 2014). eight ci constructs were identified from the reviewed literature as being potentially relevant to ca: 1. intelligence timing (april & bessa, 2006; nadkarni & barr, 2008), 2. intelligence type (momeni & mehrafzoon, 2013; bisson, 2014), 3. organisational intelligence activity integration (adidam, banerjee & shukla, 2012; fatti & du toit, 2012), 4. the communication channel through which intelligence is filtered through the organization (rothberg & erickson, 2012; barnea, 2014), 5. structured, purposeful collection of intelligence (adidam, banerjee & shukla, 2012; rothberg & erickson, 2012), 6. capability of the organization to convert information into action (kamya et al., 2010; adidam, banerjee & shukla, 2012), 7. organizational resource allocation to intelligence activities (salvador and reyes, 2011; ngo & o’cass, 2012), and 8. organizational attitude to environmental change pressures (momeni & mehrafzoon, 2013; barnea, 2014). despite of these findings, “the means by which individual firms gain a competitive advantage and enhance corporate performance in a global environment remain poorly understood” (fahy, 2002, p.58). this “… lack of empirical evidence” on how “knowledge [is empirically linked] to exceptional performance” or “how knowledge-based advantage is sustained” was also identified by mcevily & chakravarthy (2002, p.285). peteraf & bergen (2003, p.1037) claimed that few “resource-based theorists have paid explicit attention to the conditions necessary and sufficient for competitive advantage of the temporary kind” in the context of ci activities. only “more recently, strategists and strategy academics have focused their attention on ci as a means for further engendering sustained competitive advantage for businesses” (april & bessa, 2006, p.86). ichijo & kohlbacher (2008, p.181) motivated other scholars to “conduct further… studies… of other global players in order to analyze the process of… knowledge creation in different environments and under different conditions”. further in-depth 40 investigations for lacking empirical insights on the if-and-how to create and sustain ca by ci in different industry, firm or country settings were suggested to be required (kumar et al., 2011, p.16): “few studies have investigated the longer-term benefits of market orientation” beside the intensive academic quest for indepth understanding of superior firm performance in global business environments. hence, “there is little empirical work linking the impact of a firm’s ci activities on a firm’s performance” (adidam, banerjee & shukla, 2012, p.242-243) and despite that, “there is much empirical research on planning and performance in general, but no major research on ci and performance” (jenster & solberg søilen, 2013, p.16). also “formalising… the constructs of competitive intelligence” lacked sufficient prior research (saayman et al., 2008, p. 383). all in all, the linkage of ca relevant ci constructs was indicated by academics as still being under-researched with regard to a systematic investigation approach. combined research in ci constructs that could potentially contribute to ca was rarely conducted or analyzed in-depth. moreover, little research was identifiable on ca relevant ci constructs for em business (ezenwa, stella & agu, 2018), despite its growing importance (global intelligence alliance, 2011). this was surprising, since in “increasingly discontinuous environmental change” (civi, 2000, p.169) ca was frequently linked to the exploitation of market orientated knowledge strategies, making use of external environment insight generation, with internal figure 1 ci connection to competitive advantage and firm performance. 41 dissemination and responsiveness to these insights (civi, 2000; durand, 2003; peteraf & bergen, 2003; ketchen, hult & slater, 2007). additionally, “64% of global companies intend to increase their investments in competitive intelligence or market intelligence over 2012 2013, with a geographical focus on emerging markets in asia and latin america” (global intelligence alliance, 2011, p.1). in that context peyrot, childs, van doren & allen (2002, p.749) claimed, that “the greater the perceived competitiveness of an organization’s environment, the higher the level of competitive intelligence use”. despite some academic coverage on em (poblano ojinaga, 2018; oubrich, hakmaouia, bierwolf & haddanic, 2018; nte, omede, enokie & bienose, 2020) and related in-depth understanding of ci, ci constructs and ca linkage was perceived as scarce. table 1 overview of identified terminology on intelligence. terminology source business intelligence ettorre (1995), wright & calof (2006), nikolaos & evangelia (2012), köseoglu, ross & okumus (2016), mcgonagle (2016), saddhono, chin, tchuykova, qadri, & wekke (2019). competitive april & bessa (2006), wright & calof (2006), brody & wright (2008), nadkarni & barr (2008), saayman, pienaar, pelsmacker, viviers, cuyvers, muller & jegers (2008), prior (2009), adidam, banerjee & shukla (2012), jenster & solberg søilen (2013), momeni & mehrafzoon (2013), barnea (2014), bisson (2014), calof (2014), maune (2014), calof, mirabeau & richards (2015), mcgonagle (2016), solberg soilen (2017). competitor wright, pickton & callow (2002), chakraborti & dey (2016), lee & lee (2017), el-muhtaseb (2018), köseoglu, mehraliyev, altin & okumus (2020). competitive technical april & bessa (2006), calof & smith (2010), salvador & reyes (2011), salvador & banuelos (2012), cerny (2016), zhang, robinson, porter, zhu, zhang & lu (2016). strategic lasserre (1993), trim (2004), pirttimäki (2007), alnoukari, razouk & hanano (2016), arcosa (2016), walsh (2017), levine, bernard & nagel (2017), ben-haim, (2018), ahmadi, baei, hosseini-amiri, moarefi, suifan & sweis (2020). market wee & ahmed (1999), pirttimäki (2007), nikolaos & evangelia (2012), rakthina, calantone & fengwang (2016), soilen (2017), falahata, ramayah, soto-acosta & lee (2020). market surveillance nadkarni & barr (2008), colakoglu (2011). strategic analysis lessard (2003), papulovaa, gazovaa (2016), seguraab, moralesab & somolinosb (2018), köseoglu, mehraliyev, altin & okumus (2020). foresight rohrbeck, heinrich & heuer (2007), mueller (2008), kuosa (2016), adegbile, sarpong & meissner (2017), iden, methlie & christensen (2017), stan (2017). marketing information wright & ashill (1996), fleisher, wright & allard (2008), barakat, shatnawi & ismail (2016), mandal (2018). intelligence buechner & mulvenna (1998), wee (2001), glance, hurst, nigam, siegler, stockton & tomokiyo (2005), wright & calof (2006), fleisher (2008), göb (2010), mandal (2017, 2018). research walle (1999), van birgelen, de ruyter & wetzels (2000), wee (2001), crowley (2004). environmental scanning ghoshal & kim (1986), babbar & rai (1993), bergeron & hiller (2002), calof & wright (2008), mueller (2008), nikolaos & evangelia (2012), du toit (2016). analysis mueller (2008), dobson, starkey & richard (2004). examination miles and darroch (2006). impact analysis babbar and rai (1993). knowledge of markets voola and o’cass (2008). of business environment civi (2000). management weiss, (2002), greiner, bohmann and krcmar (2007), nikolaos and evangelia (2012). research and analysis ghoshal and kim (1986). concluding, three clear knowledge gaps emerged from the literature review. the need to better understand the transparency of the potential for ci to create and sustain ca in em competition from the developed market firm perspective was identified (knowledge gap 1). furthermore, a need for clarification was noticed on ci preor not yet identified constructs as potentially connected to ca (knowledge gap 2). additionally, potential was seen for new insights on possible impacts on the core view of ci as a process and a product (knowledge gap 3). 3. research questions the following research questions emerged from the knowledge gaps identified in the extensive literature review (appendix 1 shows research question 1 as an example): • (rq1a) can the potential of ci for ca be ascertained in the case setting? • (rq1b) how transparent is the potential of ci for ca for generators and users of ci in the case setting? • (rq2a) do the underpinning ci constructs potentially contribute to ca in em business? • (rq2b) do ci constructs other than the underpinning potentially contribute to ca in em business? • (rq3a) is an adaptation of ci processes recommended to increase its potential for ca? • (rq3b) is an adaptation of ci products recommended to increase its potential for ca? 4. research methodology and design 4.1 research approach and inquiry strategy a pragmatism paradigm informed, qualitative research approach was chosen, as it was successfully used in comparable ci research contexts (april & bessa, 2006). the author selected a mode of inquiry uniting deductive and inductive elements (alasuutari, bickman & brannen, 2008) for desired insights into the pre-defined concepts, but also emerging ones. empirical investigations were carried out in a unique and under-researched single case setting. single-case studies are flexible enough to generate the required in-depth (yin, 2003; van wynsberghe & khan, 2007), integrated insights into real-life contexts (dubois & gadde, 2002; hancock & algozzine, 2006) and highly individual experiences (vissak, 2010) on complex phenomena in business management (cepeda & martin, 2005; ghauri & firth, 2009) and ci studies (april & bessa, 2006; fleisher, wright & allard, 2008; ichijo & kohlbacher, 2008, salvador & reyes, 2011; salvador & banuelos, 2012; calof, mirabeau & richards, 2015). for research on ci and firm performance, adidam, banerjee & shukla (2012, p.243) stated that “most literature addressing this issue has been… case-based”. ichijo & kohlbacher (2008) applied case study inquiry to investigate the automotive industry. since no generalization but in-depth particularization was the aim of this study a single case was selected. 4.2 selection of case industry, case firm, unit of analysis the case industry was purposefully (flyvbjerg, 2006; ghauri & firth, 2009) chosen due to its suitability (eisenhardt & graebner, 2007) to meet the research objectives: the eu commercial vehicle industry showed a very high degree of globalization (vda, 2006), a high importance of emerging markets for the industry (kpmg, 2006), and of ci activities for em business (roland berger strategy consultant, 2009b). hence, one of the top european based original equipment manufacturers in that industry was chosen as the case firm since it evidently matched the criteria of globalization (datamonitor, 2010), em engagement (collins stewart, 2010), a high level of ci activities (case firm, 2010b) and granted access for research purposes. a fairly complete capture of intelligence activities for em business activities was believed to be achievable, with the case firm’s competitive intelligence department and its intelligence services being selected as a unit of analysis (case firm, 2011a). this purposeful selection was expected to allow enriched understanding of the researched phenomena. 4.3 data collection and analysis rigorous procedures for single case studies (yin, 2003; brereton, kitchenham, budgen & li, 2008; creswell, 2009) were applied. that is why empirical data for the six research questions was collected through a two-stage approach similar to ichijo and kohlbacher (2008). extensive analysis of 77 documents 43 (stage 1a: external documents; stage 1b: case firm internal documents) followed by 18 semistructured interviews with the case firm and industry experts (stage 2). the research questions rq1a/b, rq2a/b and rq3a/b were broken down in qualitatively formulated, openended sub-questions (appendix 1 showing research question 1 as an example) to prepare and increase knowledge retrieval (hancock & alogzzine, 2006). a case study protocol and databases (beverland & lindgren, 2010) were established. then, at the first stage more than 50 external reports, publications, articles and presentations from 27 trustworthy, carefully selected and expert-checked expert organizations as well as 30 case firm internal highly-relevant, member-checked presentations, reports, charts and tables were collected. a thorough content and thematic data analysis and interpretation (bowen, 2009) was undertaken in a qualitative analysis software (nvivo®) allowing early conclusions and informing the next data collection stage. to establish a transparent chain of evidence and explanation building, data was labelled in nvivo® with codes, which were in turn categorized (table 2), allocated to the research questions and assigned to themes reflecting viewpoint and argumentation patterns. then patterns in the data were matched, negative, discrepant or rivalling insights were addressed and additional documents were searched for; the rivalling explanations were taken further. from the six original research questions, the sub-questions and the early insights from stage 1, interview questions (appendix 1 showing research question 1 as an example) for the semi-structured interview guideline master were prepared for a comparable “thematic approach” in each interview (qu & dumay, 2011, p.364) which were piloted with two respondents. the experts were purposefully (rowley, 2012) screened with 10 established criteria and 6 external experts and 12 internal experts were sampled (appendix 2) from the total of 30 experts approached. this procedure ensured that the 18 respondents (appendix 2) promised valuable and fairly exhaustive input from different perspectives and viewpoints. the interviews were compliant with research ethics and data protection acts, lasted 45 to 70 minutes and were carried out in person or via telephone. during the interviews, notes were taken or the interviews were audiorecorded. each completed interview was transcribed to nvivo®, was run through constant comparison analysis procedures (leech & onwuegbuzie, 2007) and industry and firm experts’ member checking allowing incremental improvements in data collection, analysis and interpretation. the iterative analysis covered the transfer of interview data and memos to nvivo®, coding of interview data (with emerging, in vivo and constructed codes from stage 1), building a code structure by member-checked categorization of code, allocation to the six research questions as well as construction of themes. while analyzing interview after interview, the initial code list from stage 1 was extended and enhanced by a hierarchical structure via axial coding. different themes were interrelated and then also categorized after reflection on the six research questions. where necessary, respondents were revisited during the analysis and interpretation stage. table 2 extract of code system structure. categories codes applied relevance to research focus intelligence role explicitly mentioned intelligence term used rq 1 other terms used rq 1 intelligence role indicated market by market understanding advocated rq 1a, 1b, 2a, 2b market orientation as key success factor rq 1a, 1b, 2a, 2b other (indication of intelligence role) rq 1a, 1b, 2a, 2b link ci to ca given market intelligence as key success factor for ca to ca rq 1a intelligence as a strategic advantage rq 1a intelligence constructs used content relevance rq 2a, 2b organisational level rq 2a, 2b timeliness rq 2a, 2b intelligence insights reflecting emerging market specifics geopolitical specifics rq 1a, 1b, 2a, 2b dynamism rq 1a, 1b, 2a, 2b speed of change rq 1a, 1b, 2a, 2b as required for single case studies (baxter & jack, 2008), existing theory was extensively used for comparison with empirical results. in the analysis stage, the empirical findings on the perception and transparency between ci and ca (rq1a/b), on the pre-identified or other ci constructs’ relationship to ca (rq2a/b), and on the ci process and product adaption needs for emerging market business (rq3a/b). further, other emerging themes on the research focus were constantly and consequently compared to the theoretical frameworks from the literature. they were also matched with already retrieved findings from our own data collection. moreover, two industry experts reviewed the case draft. 5. study results 5.1 potential and transparency of ci as a source for ca in the examined research setting, potential of ci for ca was traceable (rq1a). however, classic manufacturing industry competences such as “purchasing” (kern, 2009), “engineering” (roland berger strategy consultants, 2009a, 2009b; r 1, 3, 4, 5, 14, 15, 17), “production” (frost & sullivan, 2011; r1, 5, 13, 17 b4a), or “sales or after sales activities” (mckinsey & company, 2009a, 2009b; roland berger strategy consultants, 2009b) were still perceived as dominant potential sources for achieving “low-cost” (roland berger strategy consultants, 2009a, p.1) or differentiation advantages (mckinsey & company, 2009a, 2009b). moreover, intelligence as a source required for advantageous positioning in the highly product-driven commercial vehicle industry was transparent to generators and users of ci in general (rq1b). however, this was taken as partly limited and ambiguously perceived. the diverse understanding was retrieved as a very subjective perception as taken from the interviews of generators and users of ci data and literature (kumar et al., 2011). in particular, transparency in the relationship between ci and ca was a better identifier in an emerging market setting. for example, the potential of ci was transparent to industry experts expressing in their reports that more market orientation for emerging market business is needed “in order to successfully implement… globalization strategy” (roland berger strategy consultants, 2009b, p.3) to finally gain a higher competitiveness (koegel trailer gmbh & co.kg, 2008; roland berger strategy consultants, 2009a, 2009b; pa consulting, 2010; frost & sullivan, 2011; mckinsey & company, 2011). additionally, market orientation activities such as to “adapt… along local market expectations and the competitive environment” (pa consulting, 2010, p.3-4), “assessing the competitive landscape” including “comprehensive market research” (mckinsey & company, 2011, p.3) or listening to the “voice of customers” (frost and sullivan, 2011, page 5) were identifiable as signposts of a given transparency on the ci and ca relationship. furthermore, statements such as “careful analysis of the markets” and “examine the obvious differences that exist between the triad and emerging markets” also proposed transparency of the potential of intelligence-based advantages to industry experts (roland berger strategy consultants, 2009b, p.3). this understanding matched with the central stance of market orientation as the “generation, dissemination and responsiveness to intelligence” for advantageous competitive positions (kyriakopoulos & moorman, 2004, p.224; ichijo & kohlbacher, 2008). analyzed interview statements such as “for emerging market competition... competitive intelligence will... become a source of competitive advantage” (r10) also stated that “knowledge building and converting it into action” is an essential asset for ca (r16) as perceived from existing research (april & bessa, 2006; badr, madden & wright, 2006) as well. it was said, that “intelligence in all fields... needs to be generated” (r2), avoiding blind spots for emerging market business. another expert expressed that “knowledge building and converting it into action” is an essential asset for ca (r16). experts added that “for emerging market competition of the future, competitive intelligence will most likely become a source of competitive advantage since for the organization involving so far in low risk export business, missing market insights already used to be a competitive disadvantage in the past” (r10). others were more reluctant on the potential of ci for ca stating that “competitive intelligence is too frequently only nice to know” (r13) or that the “full potential of bi... is not really used” (r7) or “exploited” (r8), questioning intelligence effectiveness (r6, r12) in an “industry [which] is too much product/ engineering driven”. 45 all in all, even for emerging markets transparency was less clearly identifiable than the proposed significant business challenge of these markets suggested (peyrot et al., 2002). concluding from the data, transparency on the ci/ca relationship was determined to be dependent on seven influencing factors: (a) industry or individual predominant mindsets, (b) individual risk awareness on ci target markets’ complexity, volatility, and insecurity depending on firm or individual familiarity with intelligence target markets, (c) different purpose and objectives of ci, (d) the process of conducting ci (systematic, timely), (e) delivered or achievable quality of ci, (f) type of intelligence available, and (g) action being derived from ci/conversion capability of the firm. 5.2 potential contribution of ci constructs to ca seven (#1,2,3,4,5,6 and 8) out of the eight preidentified ci constructs from the literature were suggested as potentially contributing to ca in this study setting (rq2a). interestingly, the understanding of the single ci constructs’ connection to ca was highly individually and frequently ambiguously retrieved from documents and interview data. appendix 3 shows key insights found in the data for each construct and the understanding created from these. due to the heterogeneity and the complexity of market drivers influencing the commercial vehicle industry in the emerging market setting (mckinsey & company, 2011), as well as above-average product, sales and after sales complexity in the case industry (mckinsey & company, 2011), intelligence timing (#1) was supported in its influence on ca. however, respondents also opposed that conclusion since “the commercial vehicle industry and commercial engine industry is due to long product cycles not involved in hyper-competition business environment” (r5). in line with rothberg and erickson (2013) respondents expressed the type of intelligence (#2) as “highly relevant” (r12) for ca, however also limiting it to “actionable knowledge” only (r17). however, this connection was also partly rejected for the case since “rare knowledge is not existing for this industry” (r10); this supported greiner, bohmann & krcmar (2007, p.3) since “not all knowledge... activities have been shown to positively influence business performance or to result in a competitive advantage”. organizational intelligence activity integration (#3) was perceived as potentially ca-relevant since it was stated that “for ca, involvement [of ci] in the strategy process is very important” (r17), advocating that ci needs to be closely linked to decision making to unfold impact on ca. moreover, ci was demanded to be centralized since “ca most likely created in central functions which sees the company in its wholeness” (r11). however, the opinions on which organizational level ci unfolds its influence best ranged from all organizational levels to corporate level only. it could be concluded from the analyzed data to aim for well-balanced collection and dissemination between central and decentralized organizational units to outweigh biases on both sides (r9, 17) or to increase speed and timing (r16). nevertheless, ambiguous perception of the influence of the organizational level ci construct for ca was also retrieved since it was understood as rather a prerequisite of ca than determining it (r15). in the communication channel through which intelligence is filtered through the organization (#4), internal and external respondents across business functions were almost unanimously convinced that it has an impact on ca creation in em environments. this supported that “disseminating intelligence across the firm is one of the most critical components of effective competitive intelligence” (adidam, banerjee & shukla, 2012, p.249). respondents suggested to organize a more effective and efficient channel of collection and dissemination by reduction of process barriers (“the closer the channel to operative decision makers, the better”, r7) to connect ci closer to decision making. reduction of the number of involved stakeholders (“too many stakeholders are linked in the process between intelligence creation and usage, so channels are usually long and insights... get easily lost”, r2), realtime insight access (“often access to intelligence is missing”, r3), and it tools (r3, r8) were believed to be supportive. despite the positive perceptions, it was doubted that an ideal channel could be found at all to establish this construct as relevant for ca (r10). interesting opinions were retrieved on ca influence of structured, purposeful collection of intelligence (#5) and the capability of the organization to convert information into action (#6). one group of respondents believed that both constructs influence ca relevance of ci (r1, 11, 13, 14, 15, 17). others preferred the conversion capability since “the ability to convert... to action is key” (r13), “collection is important but the capability... might be an 46 outstanding asset” (r2) and conversion “plays a more important role than sheer collection and analysis of intelligence” (r3) since “unique knowledge in this industry is rare and success is more depending on how quick the insights can be converted into action by experience and talent” (r9). this was overall in line with herring (1992, p.57) expressing that “successful strategies are derived from good intelligence” whereas “good intelligence by itself, will not make a great strategy” and babbar & rai (1993, p.105) stating that “intelligence is merely a necessary but not a sufficient condition for competitive vitality”. case firm internal as well as external experts supported the positive influence of organizational attitude to environmental change pressures (#8) on ca (r6, 8, 18). respondents believed, that “continuity and a long-term holistic intelligence scope impact ca relevance” (r6) as an expression of organizational awareness for change in attitude and skills towards a greater outside in perspective is required to harvest the potential of ci best. it was claimed that through all hierarchical levels, from supervisory board, management board to each single member of staff, a change of attitude towards market orientation on the individual level is an essential prerequisite for successful ci exploitation (r8, r16). furthermore, to the above constructs, neither the last pre-identified construct, organizational resource allocation to intelligence activities (#7), nor any other construct’s influence on ca was retrievable (rq2b) in this study. however, the absence of other proposed constructs led to the conclusions that either no further constructs were of relevance in that case setting or that the respondents experience on the matter of ca relevant constructs did not go beyond the discussed constructs. 5.3 recommended adaptions of ca as a product and a process for ca on research question 3a only two major recommendations for em business modification of ci products were identified (rq3a). while documents provided no insights at all, it was expressed by a generator of ci, that on ci products for em “the expectation is extremely high while at the same time uncertainty of the results is extremely high” (r18). ci in em was said to be expected “to deliver not only decision relevant insights but delivering also the decision itself” (r11) requiring the adaptation of the deliverables of ci wherever possible even more directly for direct decision making. another pattern was identifiable with adapting the product towards full and more proactive transparency on insight reliability (r4, 5, 8, 14, 15, 17). r5 as a user of ci also experienced the even more evident necessity in insecure and highly volatile business environments to “highlight obviously existing higher uncertainty in results” as also identified in tao and prescott (2000), suggesting a quality framework determining timeliness, accuracy and reliability of intelligence for em ci. on research question 3b (rq3b), dealing with ci as a process, more comprehensive recommendations for optimization were retrievable for em from the literature (gayoso & husar, 2008). it identified stages of planning, collecting, analyzing and adapting (appendix 4). it was perceived that the “core process stays the same but the characteristics are different due to low decision relevant data available, frequently lacking basic and advance knowledge of emerging markets amongst decision makers, a high change and dynamism in these environments resulting in a higher uncertainty for decisions and subsequently an increased entrepreneurial risk” (r9). so need for change in the process was expressed by respondents for single but also across phases (appendix 4) with (a) balanced intelligence insight generation and usage between central and decentralized firm units (plan phase), (b) fit-to-market qualitative research approaches making use of primary sources (collect phase), (c) proactive use of data triangulation approaches combined with analysis against a validity/uncertainty result scale for transparent communication (analysis phase), (d) presentation of developed vs. emerging market deviations (adapt phase), (e) sharing cross-country or cross-segment insights (adapt phase), (f) higher degree of analyst involvement in decision making (adapt phase), (g) it tool usage, actionable ci generation (across phase), (h) usage on all relevant organizational levels (across phase) as well as (i) analyst training for extended responsibility and task portfolio (across phase). appendix 4 interprets modification needs against existing academic perspectives. 6. conclusions and business benefits 47 6.1 conclusion this study of a commercial vehicle oem and its ci activities for em business illuminated the in-depth understanding of ci and its constructs for ca in a not yet investigated, unique and holistic research single case setting. in the examined research setting, the potential of ci for ca was traceable (rq1a). moreover, intelligence as a source required for advantageous positioning in the highly product-driven commercial vehicle industry was transparent to generators and users of ci in general (rq1b), along with, as from literature expectable (kumar et al., 2011), diverse and ambiguously perceived limitations and influenced by seven identified factors. for the first time in academia, ci and preidentified ci constructs were investigated in a systematic and joint research approach in this specific context. concluding, seven out of the eight pre-identified ci (#1,2,3,4,5,6 and 8) constructs from literature were suggested to be potentially contributing to ca (rq2a), while beyond that neither the last pre-identified construct, organizational resource allocation to intelligence activities (#7), nor any other construct’s influence on ca was retrievable (rq2b) in this study. furthermore, two major recommendations for modification of ci products (rq3a), and eight levers for each in literature (gayoso & husar, 2008), identified ci process stages of planning, collecting, analyzing and adapting for ci (rq3b) that were retrievable for em. 6.2 business benefits despite acknowledging that no generalization is possible from this single case study, generated insights still enable firms to reflect on how to potentially achieve greater impact of ci on ca for their specific case. benefits would arise from analyzing and improving firmspecific linkages between ca and ci and its transparencies for generators and users in general. improving the ci setup specifically for constructs such as ci timing, ci type, organizational intelligence activity integration, communication channel through which intelligence is filtered through the organization, procedures for structured, purposeful collection of intelligence and the capability of the organization to convert information into action. further, firms could also improve organizational attitudes to environmental change pressures on ca impact. considering potential adaption possibilities such as the two identified for ci as a product or the eight suggested for ci as a process gives further possibility to influence the potential of ci for ca. 7. limitations and areas for future research 7.1 limitations as with other research, this study also has limitations. these could be based in underlying theory, since the conceptual connection of ci and ca was not undisputed (qiu, 2008) although it is empirically supported (adidam, banerjee & shukla, 2012). furthermore, terminological heterogeneity of ci (bisson, 2014; grèzes, 2015) could have limited the exhaustive knowledge retrieval from the literature review. due to the selected crosssectional, single case study setting, research was consequently limited in regard to theory generation, and verification as well as generalization of other firms or industry settings (rowley, 2002). potential limitations of the data collection and analysis could have occurred as well. however, possible biases were reduced through rigorously-applied research procedures for document selection, interviewee sampling as well as strictly applied qualitative analysis. 7.2 future research with little “empirical work linking the impact of a firm’s ci activities on a firm’s performance” (adidam, banerjee & shukla, 2012, p.242-243) in existing research, this study in a very particular case setting provided substantial further—but not an exhaustive—contribution to this knowledge gap. hence, further in-depth or complementary particularization as demanded by ichijo & kohlbacher (2008) for further “formalizing... the constructs of competitive intelligence” (saayman et al., 2008, p. 383) are obvious areas for future research. this could be done, for example, by researching in-depth in the same case a) in one ci construct only, b) in all constructs but longitudinally; or examining another complementary case 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(2016) technology roadmapping for competitive technical intelligence. technological forecasting and social change, 110 , 175-186. appendix appendix 1: interrelating central research problem, research questions, sub-research questions and interview questions shown for research question 1 as an example. research objectives= research objectives in the context of emerging market business from a developed market firm perspective this study aimed. in this table, the central research problem is: what potential does competitive intelligence have to create and sustain competitive advantage in emerging market competition by exploiting an adapted process and tailored-to-fit products? research objectives and research question sub-questions interview questions for the semi-structured interview guideline to ascertain the potential of ci to create and sustain ca 1a: can the potential of ci for ca be ascertained? 1a.1) which sources (resource-/ competence/capability-/knowledgebased) for firm performance differences / ca in emerging markets are considered? 1a.2) how is ci (or any synonymously/ similar term) linked in this context? 1a.3) if a link is considered: how is it described? 1a.4) if no link is considered: what are reasons for that? 1a.5) if other sources are considered: which sources are mentioned? 1a.6) if other sources are considered: what are reasons for mentioning them? b1) what is your understanding of a competitive advantage a firm holds? b2a) which competitive advantage do you believe a commercial vehicle oem needs to hold in the industry by now? b2b) which competitive advantage do you believe a commercial vehicle oem needs to hold in 5 to 10 year? b3a) which competitive advantage do you believe the case firm holds by now? b3b) which competitive advantage do you believe the case firm needs to hold in 5 to 10 year? b4a) which sources of ca at the case firm do you identify? b4b) [if knowledge/data/information/ intelligence of the external environment is not named]: how about ca by knowledge of external environment? c1a) when coming to emerging market competition: which competitive advantage do you believe a commercial vehicle oem needs to hold in the industry by now? c1b) when coming to emerging market competition: which competitive advantage do you believe a commercial vehicle oem needs to hold in the industry in 5 to 10 years? c2a) when coming to emerging market competition: which competitive advantage do you believe the case firm inhibits by now? c2b) when coming to emerging market competition: which competitive advantage do you believe the case firm needs to inhibit in 5 to 10 year? c3a) which sources of ca for emerging market at the case firm do you identify? c3b) [if knowledge/data/information/ intelligence of the external environment is not named]: how about ca by knowledge of external environment? d1) which character do bi results have according to your opinion? □ nice to know □ important to know □ decision criticial □ ca relevant insights □ other to clarify how transparent the potential link between ci and the creation of ca is for generators and users of ci. 1b: how transparent is the potential of ci for ca for generators and users of ci? 1b.1) is a link between ci (or any synonymously/ similar term) and firm performance differences/ ca considered? d2a) is ci explicitly used to create competitive advantage for emerging market competition? who is aware of link of ci and competitive advantage and uses it explicitly? d2b) does in your opinion the company retrieve and absorb actionable knowledge and transfer it to activities meaning a temporary or sustainable competitive advantage for the emerging market business of the firm? d2c) if so, which competitive advantage for emerging market competition are suggested to be achieved by ci? d2d) how does this link look like for emerging market competition: intelligence as a whole (elements of it) embedded process wise in product development, business/functional strategy development? how is ci embedded? d2e) if the link how competitive intelligence as a process and a product can be managed to create and/or sustain competitive advantage in emerging market competition is non-existant in the case company: why is this the case? what needs to be changed to link ci and competitive advantage? e1) what is the perception since when the company uses competitive intelligence in the case firm? e2) what is the initial trigger/ reason for implementation of competitive intelligence in the case firm (initial target, today’s target?)? what did change with emerging market competition? 56 e3) where (at which levels, where in the organisation) is competitive intelligence created? is all part of the external strategic analysis explicitly done by competitive intelligence department? if not, where else does the information come from-how, by whom and why is it there created? were any amendments made for emerging market competition? e4) how is the bi department organized in regard of organisational structure, division of labour, mission and vision, aims and objectives, processes, …? were any amendments made for emerging market competition? e5) how is intelligence in general and for emerging market competition process and process-stage-wise (plan-, collectand data source-, analysisand dissemination-wise) generated? e6) which kind of information is collected in the bi department in general? what kind of knowledge tries the company to build on emerging market (as the growth promising perspective) in regard of the macroand microenvironment? e7) at what organisational levels, where and by whom is competitive intelligence for emerging market competition used? what happens with the generated information and how is it used? appendix 2: biographical interview background data and sampling criteria. cv = commercial vehicles. criteria for purposive sampling interviewee number #1 #2 #3 #4 #5 #6 #7 #8 #9 case firm int. expert v (>=10) x x x x x x x x x case firm ext. expert v (>=5) industry v (cvi or related to cvi and case firm) cv cv cv cv cv cv cv cv cv dept. business strategy dept business strategy dept product strategy dept product strategy dept sales dept sales dept project management office strategy and planning dept bi dept position v (>=expert) senior consultan t new business segments senior consultant multi brand strategy and globalisatio n head of business foresight commercia l vehicles senior product strategy develope r global trucks sales manager external engines off highway business develope r emerging market projects program manager light vehicles head of strategy and planning southern africa senior manage r professional expertise in industry (in years) v (>=three) five six four six five six five ten five work focus on em in % v (>=50) 70 80 60 70 60 100 60 100 50 relationship to ci v user (u) / generator (g) u u g and u g and u u u g and u g and u g and u anticipated understandin g of ci v ci as process/produc t to create business environment insights advanced advanced advanced advanced adequate advanced adequate adequate top anticipated degree of ci usage high high high high low/ mediu m high low/ mediu m mediu m high anticipated preference on potential sources for firm performance differences v 50:50 share of kbv vs cbv cbv cbv kbv/ cbv cbv cbv (cbv)/ kbv cbv (cbv)/ kbv (cbv)/ kbv 57 criteria for purposive sampling interviewee number #10 #11 #12 #13 #14 #15 #16 #17 #18 case firm int. expert v (>=10) x case firm ext. expert v (>=5) x x x x x x x industry v (cvi or related to cvi and case firm) cv cv cv cv (competito r firm 2) cv (competito r firm 1) automotiv e consultanc y intelligenc e research service provider 1 intelligenc e research service provider 2 intelligenc e research service provider 3 dept. bi dept bi dept bi dept bi dept business strategy automotiv e practice automotiv e practice automotiv e practice automotiv e practice position v (>=expert) head of market and competito r analysis truck and bus head of market researc h analyst for emergin g market cis and india market analyst senior consultant manager global director managing partner manager professional expertise in industry (in years) v (>=three) five three five nine three eight ten twelve ten work focus on em in % v (>=50) 50 60 100 60 60 70 50 60 60 relationship to ci v user (u) / generator (g) g and u g and u g and u g and u g and u u g g g anticipated understandin g of ci v ci as process/ product to create business environmen t insights top top top top top advanced top top top anticipated degree of ci usage high high high high high medium/ high high high high anticipated preference on potential sources for firm performance differences v 50:50 share of kbv vs cbv kbv kbv kbv kbv cbv cbv/ (kbv) (cbv)/ kbv kbv kbv 58 appendix 3: created understanding on ca relevant ci constructs. c re at ed u n d er st an di n g in t h is s tu dy th e st ud y su pp or te d fr om th e ca se s et ti ng th e de m an d fo r a fr eq ue nc y an d ti m in g of c i w hi ch is a da pt ed t o th e co m pe ti ti ve ne ss o f t he fi rm s pe ci fic e nv ir on m en t. ti m el y st ra te gi c re sp on se s to c ha ng es in t he e nv ir on m en t t o ou tp er fo rm c om pe ti to rs in t he q ue st fo r c a w as co nf ir m ab le fr om th e se le ct ed c as e. t hu s, d ou bt s on w he th er in t ur bu le nt , v ol at ile a nd h ig h ve lo ci ty en vi ro nm en t s pe ed y re sp on se s co ul d bu ild a s us ta in ab le c a a t a ll w er e al so u nd er st oo d fr om th e se le ct ed c as e. h ow ev er , i nd iv id ua l p er ce pt io n of e nv ir on m en ta l a nd co m pe ti ti ve p re ss ur e st ill s ug ge st ed t ha t i nc re as in g sp ee d an d fr eq ue nc y of in si gh t av ai la bi lit y co ul d su pp or t c a cr ea ti on . a ct io na bi lit y re sp ec ti ve ly u sa bi lit y an d re le va nc e of in te lli ge nc e w as u nd er st oo d as p ot en ti al ly c a r el ev an t. q ua lit iy , t yp e, a cc ur ac y, u pto -d at en es s, d ep th a nd co m pr eh en si ve ne ss w er e in th e ca se s et ti ng fo r em er gi ng m ar ke t bu si ne ss id en ti fie d c a a nd p er fo rm an ce r el ev an t pr op er ti es o f t he in te lli ge nc e ty pe . h ow ev er , t he p er ce pt io n in t he c as e on w he th er in te lli ge nc e as n on -s ub st it ut ab le , ra re , v al ua bl e an d in im it ab le , c om pl ex a nd fi rm s pe ci fic a s w el l a s ta ci t r ar el y av ai la bl e an d ac ce ss ib le n ow le dg e as a so ur ce o f c a is r et ri ev ab le a t a ll in t he c om m er ci al ve hi cl e in du st ry , p ro vi de d a va lu ab le c ri ti ci sm o f t he su pp or ti ve p os it io n on t ha t c on st ru ct . it c ou ld b e sh ow n, t ha t o rg an is at io na l a ct iv it y in te gr at io n of c i i s al so p ot en ti al ly p er ce iv ed a s c a r el ev an t. h ow ev er , th e op in io ns o n w hi ch o rg an is at io na l l ev el c i un fo ld s it s in flu en ce b es t r an ge d fr om a ll or ga ni sa ti on al le ve ls to co rp or at e le ve l o nl y. f ur th er m or e it w as d em an de d th at c i ne ed s to b e cl os el y lin ke d to d ec is io n m ak in g to u nf ol d im pa ct o n c a . t hu s, a m bi gi ou s po si ti on s or c le ar r ej ec ti on s sh ow ed th at in di vi du al e xp er ie nc es a nd p er sp ec ti ve s on em er gi ng m ar ke ts v ar y th e pe rc ep ti on o f a c on st ru ct s si gn ifi ca nt ly . k ey i n si gh ts f ro m s tu d y d at a su pp or t f or c on st ru ct : “ fa st er a nd m or e in ti m e de li ve ry o f i nt el li ge nc e w ou ld b e ac co un te d as he lp fu l” fo r c a (r 6, 1 2) , “ co nt in ui ty a nd a lo ng -t er m [o ri en te d] in te ll ig en ce s co pe ” w er e al so su gg es t t o im pa ct c a (r 6) . r el uc ta nt s up po rt fo r co ns tr uc ts c on tr ib ut io n fo r c a : c on st ru ct m ig ht b e“ le ss im po rt an t t ha n th e ot he r [c on st ru ct s] ” (r 17 ). r ej ec ti on o f c on st ru ct s su pp or t f or c a “ re al ly [n ot ] s ee in g re le va nc e, n ot e ve n in e m er gi ng m ar ke ts ” (r 5) un de rl in in g th at th e “ th e co m m er ci al v eh ic le in du st ry a nd c om m er ci al en gi ne in du st ry is d ue to lo ng p ro du ct c yc le s no t i nv ol ve d in h yp er co m pe ti ti on b us in es s en vi ro nm en t” . su pp or t f or c on st ru ct : “ ty pe o f i nt el lig en ce [i s] r et ri ev ed a s hi gh ly r el ev an t” (r 12 ), lim it in g it t o “ ac ti on ab le k no w le dg e” fo r c a r el ev an ce (r 17 ), r el uc ta nt s up po rt fo r co ns tr uc ts c on tr ib ut io n fo r c a : e xp er ts fe lt u ns ec ur e re ga rd in g th e su pp or ti ng p ot en ti al o f t ha t v er y co ns tr uc t i n th e lig ht o f o th er s (r 15 ) r ej ec ti on o f c on st ru ct s su pp or t f or c a : pe rc ep ti on th at “ ra re k no w le dg e is n ot e xi si ti ng fo r th is in du st ry ” (r 10 ) su pp or t f or c on st ru ct : “ fo r c a , i nv ol ve m en t [ of c i] in th e st ra te gy p ro ce ss is v er y im po rt an t” (r 17 ), “ c a m os t l ik el y cr ea te d in c en tr al fu nc ti on s w hi ch s ee s th e co m pa ny in it s w ho le ne ss ” (r 11 ), r el uc ta nt s up po rt fo r co ns tr uc ts c on tr ib ut io n fo r c a : a ct iv it iy in te gr at io n is a r el ev an t m at te r bu t r at he r a pr er eq ui si te o f c a th an d et er m in in g it (r 16 ) n o im pa ct s ee n si nc e ot he r co ns tr uc ts m or e cl ea rl y de te rm in in g c a (r 7, r 10 ) c i co n st ru ct s in te ll ig en ce ti m in g in te ll ig en ce ty p e o rg an is at io n al in te ll ig en ce ac ti vi ty in te gr at io n 59 c re at ed u n d er st an di n g in t h is s tu dy fo r th e c om m un ic at io n ch an ne l t hr ou gh w hi ch in te ll ig en ce is fi lt er ed th ro ug h th e or ga ni za ti on c on st ru ct t he d at a pr es en te d a po te nt ia l i m pa ct o n c a . t hi s un de rl in ed th e fin di ng s fr om a di da m , b an er je e an d sh uk la (2 01 2, p .2 49 ) s ay in g th at “ di ss em in at in g in te lli ge nc e ac ro ss t he fi rm is o ne o f t he m os t c ri ti ca l c om po ne nt s of ef fe ct iv e co m pe ti ti ve in te lli ge nc e” – a s th e st ud y da ta s ho w ed in pa rt ic ul ar fo r em er gi ng m ar ke t bu si ne ss . o rg an is in g m or e ef fe ct iv e an d ef fic ie nt c ha nn el o f i nt el lig en ce c ol le ct io n an d di ss em in at io n by re du ct io n of p ro ce ss b ar ri er s co nn ec ti ng c i cl os er to d ec is io n m ak in g, r ed uc ti on o f n um be r of in vo lv ed s ta ke ho ld er s, r ea l-t im e in si gh t a cc es s an d by i t to ol s is u nd er st oo d as s up po rt iv e fo r c a im pa ct . h ow ev er , t he p ot en ti al im pa ct o n c a w as a ls o cr it is ed fo r th e ch al le ng in g qu es t e st ab lis hi ng a n id ea l c ha nn el in c om pl ex or ga ni sa ti on s. o n th e st ru ct ur ed , p ur po se fu l c ol le ct io n of in te ll ig en ce a nd th e ca pa bi li ty o f t he o rg an iz at io n to c on ve rt in fo rm at io n in to a ct io n co ns tr uc t t hi s st ud y co nt ri bu te d di ve rs e kn ow le dg e. o n on e ha nd bo th c on st ru ct s w er e be lie ve d as in flu en ci ng c a r el ev an ce o f c i. a ls o in e xi st in g re se ar ch s ou rc in g of in te lli ge nc e in e m er gi ng m ar ke t c on te xt w as id en ti fie d as a s ig ni fic an t c ha lle ng e fo r or ga ni sa ti on s. o n th e ot he r ha nd e xp er ts c on si de re d th e ca pa bi lit y of th e or ga ni za ti on to c on ve rt in fo rm at io n in to a ct io n as th e on ly re le va nt c om pe ti ti ve i nt el lig en ce c on st ru ct in r eg ar d to c a im pa ct ou t o f t he tw o di sc us se d. i n th ei r vi ew in te lli ge nc e w as r eg ar de d as a ne ce ss ar y bu t no t s uf fic ie nt p re re qu is it e fo r c om pe ti ti ve a dv an ta ge . t hi s su pp or te d a vi ew po in t i n ex is ti ng a ca de m ic re se ar ch in w hi ch “ de ve lo pi ng a c om pe ti ti ve a dv an ta ge r eq ui re s ap pr op ri at e [o rg an iz at io na l] ca pa bi lit ie s” ( k am ya e t a l., 2 01 0, p. 29 78 ; a di da m , b an er je e an d sh uk la , 2 01 2) a nd in w hi ch th e ca pa bi lit y of th e or ga ni za ti on to c on ve rt in fo rm at io n in to a ct io n is un de rs to od a s a ke y en ab le r fo r an a dv an ta ge ou s po si ti on o f f ir m s in t he ir in du st ry . k ey i n si gh ts f ro m s tu d y d at a su pp or t f or c on st ru ct : “ c ha nn el m os t c ri ti ca l” (r 3) b ut c om m un ic at io n m us t b e ef fe ct iv e an d ef fic ie nt : a nd “ th e be st c ha nn el is d ep en di ng o n se ve ra l v ar ia bl es su ch a s th e to pi c/ le ve l o f d em an de d de ta il , o n es ta bl is he d fo rm al is ti c or le ss fo rm al iz ed p ro ce ss es , o n pe op le (a nd th ei r pr oa ct iv e at ti tu de to w ar ds k no w le dg e) , o n in di vi du al c om pe te nc es a s w el l a s po si ti on s an d fu nc ti on s in th e or ga ni za ti on ” (r 9) , i nt el lig en ce “ re su lt s ne ed di re ct a cc es s to to p m an ag em en t w it ho ut b ei ng fi lt er ed (r 11 ) a m bi gi ou s pe rc ep ti on o n c a im pa c t “ m os t e ffe ct iv e an d ef fic ie nt c ha nn el fo r ea ch c i t as k” h ar d if no t un re al is ti c to b e fo un d (r 10 ) b ot h co ns tr uc ts r el ev an t o ne g ro up o f r es po nd en ts b el ie ve d th at b ot h co ns tr uc ts in flu en ce c a re le va nc e of c i (r 1, 1 1, 1 3, 1 4, 1 5, 1 7) c on ve rs io n ca pa bi lit y as m or e re le va nt c on st ru ct “ th e ab il it y to c on ve rt ... to a ct io n is k ey ” (r 13 ), “ co ll ec ti on is im po rt an t b ut th e ca pa bi li ty m ig ht b e an o ut st an di ng as se t ” (r 2) a nd “ pl ay s a m or e im po rt an t r ol e th an s he er c ol le ct io n an d an al ys is o f i nt el li ge nc e” (r 3) s in ce “ un iq ue k no w le dg e in th is in du st ry is r ar e an d su cc es s is m or e de pe nd in g on h ow q ui ck th e in si gh ts c an b e co nv er te d in to a ct io n by e xp er ie nc e an d ta le nt ” (r 9) . c i co n st ru ct s c om m u n ic at i on ch an n el th ro u gh w h ic h in te ll ig en ce i s fi lt er ed th ro u gh th e or ga n iz at io n (i n te ll ig en ce d is se m in at io n ) s tr u ct u re d, p u rp os ef u l co ll ec ti on of in te ll ig en ce t h e ca p ab il it y of th e or ga n iz at io n to co n ve rt in fo rm at io n in to a ct io n 60 c re at ed u n d er st an di n g in t h is s tu dy th e or ga ni sa ti on al a tt it ud e to e nv ir on m en ta l c ha ng e pr es su re s co ns tr uc t w as a ls o id en ti fe d as p ot en ti al ly c a r el ev an t. in di vi du al m ar ke t o ri en ta ti on a tt it ud e w as e xp re ss ed a s an e ss en ti al pr er eq ui si te . f or e m er gi ng m ar ke t bu si ne ss o rg an is at io na l aw ar en es s fo r ch an ge in a tt it ud e, c ul tu re a s w el l a s sk ill s to w ar ds a gr ea te r ou ts id ein p er sp ec ti ve s ee m ed to s up po rt t he p ot en ti al o f c i. o n fu rt he r co ns tr uc ts p ot en ti al ly im pa ct in g c a n o ad di ti on al co ns tr uc t w as r et ri ev ed . i t w as o nl y co nc lu da bl e fr om t he r et ri ev ed da ta t ha t c i c on st ru ct s m os t l ik el y ca nn ot b e ap pl ie d so le ly t o un fo ld im pa ct to w ar ds c a . i t i s su gg es ta bl e th at c i co ns tr uc ts sh ou ld b e jo in ed a nd in te gr at ed in a h ol is ti c c om pe ti ti ve in te lli ge nc e ap pr oa ch to u nf ol d si gn ifi ca nt im pa ct o n c a . k ey i n si gh ts f ro m s tu d y d at a su pp or t f or c on st ru ct : in a n em er gi ng m ar ke t b us in es s co nt ex t “ co nt in ui ty a nd a lo ng t er m ho lis ti c in te lli ge nc e sc op e im pa ct c a r el ev an ce ” (r 6) r es po nd en ts b el ie ve d fu rt he rm or e, th at in p ar ti cu la r in e m er gi ng m ar ke t bu si ne ss o rg an is at io na l a w ar en es s fo r ch an ge in a tt it ud e to w ar ds a g re at er o ut si de in p er sp ec ti ve is r eq ui re d to h ar ve st t he po te nt ia l o f c i b es t ( r 8) . i t w as c la im ed t ha t t hr ou gh a ll hi er ar ch ic al le ve ls , f ro m s up er vi so ry b oa rd , m an ag em en t bo ar d to e ac h si ng le m em be r of s ta ff a ch an ge o f a tt it ud e to w ar ds m ar ke t o ri en ta ti on o n in di vi du al le ve l i s an e ss en ti al p re re qu is it e fo r su cc es sf ul c i ex pl oi ta ti on (r 8, r 16 ). c i co n st ru ct s o rg an is at io n al a tt it u d e to en vi ro n m en t al ch an ge p re ss u re s o th er s 61 appendix 4: ci process phase modification needs for em business. in te rp re ta ti on an d c on cl u si on fr om t h e re se ar ch er e ff ec ti ve a nd ef fic ie nt di ss em in at io n of in te lli ge nc e vi a an it t oo l c an fo st er it s us ag e in cr ea si ng al so in te lli ge nc e cr ed ib ili ty w he n ac ce ss to r aw da ta /a na ly s is m ad e po ss ib le . in n ot ed tu rb ul en t an d vo la ti le em er gi ng m ar ke ts a ho lis ti c c i ge ne ra ti on a nd di ss em in at io n ap pr oa ch s ee m s to de liv er th e m os t pr om is in g re su lt s, ho w ev er qu es ti on in g bu si ne ss e ffi ci en cy . f in d in g cr it ic al ly as se ss ed a ga in st ex is ti n g ac ad em ic p er sp ec ti ve s it s up po rt ed c i to ol fo r th e fu ll in te lli ge nc e cy cl e al lo w s m or e ef fe ct iv e an d ef fic ie nt pr oc es si ng b ut m or e im po rt an tl y ac ce ss in g th e in te lli ge nc e ge ne ra te d (b ar ne a (2 01 4) . “ in te rn al pr oc ed ur es gu ar an te ei ng th e tw o s id ed fl ow o f in fo rm at io n fr om ex te rn al a nd in te rn al s ou rc es an d m ak in g in te lli ge nc e av ai la bl e to th os e w ho n ee d it t o ac co m pl is h th ei r as si gn m en ts ” a ct as a k ey s uc ce ss fa ct or fo r c i (b ar ne a, 2 01 4, p. 10 5) a cr os s p h as e m od if ca ti on n ee d s id en ti fi ed fr om f in d in gs o p ti m iz e ch an n el li n g of ge n er at io n , d is se m in at io n an d re sp on si ve n es s b y an i t t oo l g en er at e an d u se c i at a ll r el ev an t ce n tr al a n d lo ca l or ga n is at io n al le ve ls in te rp re ta ti on a n d c on cl u si on f ro m t h e re se ar ch er to o ve rc om e th e ch al le ng e of la ck in g m ar ke t i ns ig ht s kn ow le dg e cr ea ti on a nd s ha ri ng pr ac ti se s be tw ee n ce nt ra l a nd de ce nt ra l u ni ts a re r eq ui re d to b e es ta bl is he d, h ow ev er or ga ni sa ti on al s tr uc tu re s ar e fr eq ue nt ly a b ar ri er fo r an o pe n an d ti m el e xc ha ng e. q ua lit at iv e re se ar ch a pp ro ac he s in e m er gi ng m ar ke ts r at he r se em to b ri dg e cu lt ur al in ac ce pt an ce o f qu an ti ta ve s ur ve y de si gn s in (f or ex am pl e in a ra bi an c ou nt ri es o r in m ar ke ts w er e th e nu m be r of ex pe rt s is n ot la rg e en ou gh re pr es en ti ng a p op ul at io n su it ed fo r su rv ey d es ig n) . m is si ng o r la ck in g re lia bi lit y of st at is ti cs i n em er gi ng m ar ke ts se em to b e a re as on t o re ly r at he r on d ir ec t c on ta ct to m ar ke t ex pe rt s (c us to m er s, a ss oc ia ti on m em be rs , a na ly st s, ... ) = > re al ly al lo w u nd er st an di ng t he m ar ke ts . f in d in g cr it ic al ly a ss es se d ag ai n st e xi st in g ac ad em ic p er sp ec ti ve s d is pe rs ed d is tr ib ut io n pl an ni ng (r ot hb er g an d e ri ck so n, 2 01 2) : d ec en tr al in te lli ge nc e to b e w el l l in ke d to fi rm s’ r eg io na l/ ce nt ra l he ad qu ar te r (l as se rr e, 1 99 3; d u to it a nd m ul le r, 2 00 4; ic hi jo a nd k oh lb ac he r, 2 00 8; h op pe , 2 01 3) . r at he r qu al it at iv e th an qu an ti ta ti ve a pp ro ac he s to em er gi ng m ar ke ts p ro po se d as su cc es s fa ct or (t ao a nd pr es co tt , 2 00 0) . r at he r pr im ar y so ur ce (p er so na l c on ta ct ) b as ed (t ao an d pr es co tt , 2 00 0; a di da m , b an er je e an d sh uk la , 2 01 2) th an s ec on da ry d at a ba se d re se ar ch a pp ro ac he s (l as se rr e, 1 99 3; w ee a nd za fa r, 1 99 9) s ui ta bl e fo r e m . s in gl e p h as e m od if ca ti on n ee d s id en ti fi ed fr om f in d in gs b al an ce d in te lli ge nc e in si gh t ge ne ra ti on a nd us ag e be tw ee n ce nt ra l a nd de ce nt ra l f ir m un it s fi tto -m ar ke t qu al it at iv e re se ar ch ap pr oa ch es fi tto -m ar ke t pr im ar y so ur ce ba se s s in gl e c i c yc le p h as e p la n p h as e c ol le ct p h as e 62 in te rp re ta ti on a n d c on cl u si on f ro m t h e re se ar ch er sp ec ia lis at io n of a na ly st s al on g em er gi ng m ar ke t re le va nt c ri te ri a (c ou nt ri es , se gm en ts ,.. .) ca n po te nt ia lly in cr ea se in te lli ge nc e ef fe ct iv en es s an d ef fic ie nc y by o ve rc om in g co m pl ex it y, un ce rt ai nt y on a nd m is si ng ex pe ri en ce o n em er gi ng m ar ke ts . a ct io na bi lit y of in te lli ge nc e as r es ul t o f a na ly si s is pe rc ei ev ed a s vi ta l f or c a w hi ch is a c ro ss p ha se pr oc ed ur e of t he c i c yc le . f in d in g cr it ic al ly as se ss ed ag ai n st ex is ti n g ac ad em ic p er sp ec ti ve s - th e or ga ni sa ti on al co nv er si on ca pa bi lit y at t he en d of in te lli ge nc e cy cl e su gg es te d as k ey to c om pe ti ti ve a dv an ta ge (a di da m , b an er je e an d sh uk la , 2 01 2) . a cr os s p h as e m od if ca ti on n ee d s id en ti fi ed f ro m fi n d in gs p re p ar e an al ys ts fo r th e sp ec ia li sa ti on d eg re e an d a n ex te n si on s of t h e an al ys ts t as k , p ro d u ct a n d p ro je ct p or tf ol io to w ar ds d ec is io n m ak in g o p ti m iz e ac ti on ab il it y of c i ac ti vi ti es in te rp re ta ti on a n d c on cl u si on fr om t h e re se ar ch er d iff er en t s ou rc es in e m er gi ng m ar ke ts a re s ug ge st ed to b e re qu ir ed t o ov er co m e la ck in g co m pl et en es s, a cc ur ac y an d re lia bi lit y of s ec on da ry d at a; ho w ev er ta ki ng a ls o in co ns id er at io n th at o pi ni on s of fr eq ue nt ly fe w a va ila bl e in du st ry ex pe rt s m ig ht b e al so b ia se d. in te lli ge nc e us er s w hi ch a re m ai nl y ex pe ri en ce d in d ev el op ed m ar ke t in te lli ge nc e m ig ht b e ov er co nf id en t w he n ac ce ss in g in te lli ge nc e re su lts o f e m er gi ng m ar ke ts w it ho ut a p ro ac ti ve s ta te d re lia bi lit y ju dg em en t. d em an de d fo r cr os sem er gi ng / de ve lo pe d or c ro ss -s eg m en t m ar ke t co m pa ri so n po in t t o th e ne ed fo r to de ve lo pe d m ar ke ts c on te xt ua lis ed su pp or t f or u nd er st an di ng h ow ev er , i t i s qu es ti on ab le w he th er t hi s co nt ra st in g pr es en ta ti on s ty le is a lo ng -t er m so lu ti on in a g lo ba lis ed w or ld . in cr ea si ng e m er gi ng m ar ke t ex pe ri en ce m ig ht r ed uc e th is pr ob le m o f u nd er st an di ng o ve r ti m e. in te gr at iin g c i a na ly st s in d ec is io n m ak in g so un ds p ro m is in g to in cr ea se in fo rm ed d ec is io ns , ho w ev er it b in ds a dd it io na l ca pa ci ti es a nd d em an ds fo r di ffe re nt c ap ab ili ti es . f in d in g cr it ic al ly as se ss ed a ga in st ex is ti n g ac ad em ic p er sp ec ti ve s tr ia ng ul at io n of di ffe re nt s ou rc es t o in cr ea se r el ia bi lit y an d in si gh t d ep th (t ao a nd pr es co tt , 2 00 0) . “ ta r ” fr am ew or k su gg es te d: t im el in es s, a cc ur ac y an d r el ia bi lit y of in te lli ge nc e (t ao a nd pr es co tt , 2 00 0, p .7 4) . --o rg an is at io na l ac ti vi ti y in te gr at io n of c i in d ec is io n m ak in g (t ao a nd p re sc ot t, 20 00 ; d u to it a nd m ül le r, 2 00 4; i ch ijo an d k oh lb ac he r, 2 00 8) . s in gl e p h as e m od if ca ti on n ee d s id en ti fi ed f ro m fi n d in gs pr oa ct iv e us e of d at a tr ia ng ul at io n ap pr oa ch es a na ly ze a ga in st a v al id it y/ un ce rt ai nt y re su lt s ca le fo r tr an sp ar en t c om m un ic at io n pr es en ta ti on o f de ve lo pe d vs . e m er gi ng m ar ke t de vi at io ns sh ar in g of c ro ss -c ou nt ry o r cr os sse gm en t i ns ig ht s h ig he r de gr ee o f a na ly st in vo lv em en t i n de ci si on m ak in g s in gl e c i c yc le p h as e a n al ys is p h as e a d ap t p h as e 5 competitive intelligence in the south african pharmaceutical industry a. fatti and a.s.a. du toit centre for information and knowledge management, university of johannesburg, south africa e-mail: afatti@gmail.com e-mail: adeline.dutoit@up.ac.za received february 12, accepted 25 february 2013 abstract: currently the south african pharmaceutical industry is being affected by legislation, as the government is readjusting the whole healthcare system to make it cost-effective and equitable. the purpose of this article is to establish what the current situation is within the south african pharmaceutical’s industry’s competitive intelligence (ci) capacity. questionnaires were administered electronically to senior managers in the pharmaceutical industry. the majority of the respondents were of the opinion that a culture of information sharing and an environment of collaboration on competitive issues exist in their companies. respondents confirm that ci is used on a continuous basis in strategic decision-making and that company strategies are used to manage competitors. it is recommended that senior management of pharmaceutical companies capitalise and consolidate the ci function which is used on a continuous basis in strategic decision-making. keywords: competitive intelligence, pharmaceutical industry, south africa, strategic decision-making introduction in a developing country such as south africa, the local pharmaceutical industry needs to compete in highly dynamic international markets. all global economies are in a state of flux, constantly evolving to accommodate changes, risks and opportunities as their markets develop or subside (badr, madden & wright 2006, 18). consequently, if south africa is to compete, it will need to be open to world trade etiquette along with all the rules and regulations that operate in global markets. the south african government has new procurement rules ready to boost home-grown production to encourage export rather than importing medicines subject to fluctuating world prices. the revised preferential procurement regulations to drive economic transformation were issued on december 7 th , 2011 and this preferential procurement policy framework act (pppfa) confirms the south african government’s seriousness and concern in creating jobs for its previously economically disadvantaged people. on the international front the pharmaceutical industry has been undergoing tremendous changes as it responded to turbulent world markets. currently the south african pharmaceutical industry is being affected by much legislation, as the government is readjusting the whole healthcare system to make it cost-effective and equitable, i.e. national health insurance (nhi). local pharmaceutical manufacturers can ‘think smart’ when competing with resident multinationals who have their competitive intelligence (ci) functionality assessed at headquarters in their mother countries, i.e. glaxco, kline and smith pharmaceuticals (gks). changes emanate from the overall economic downturn, the rising cost of healthcare and the costs associated available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2013) 5-14 mailto:afatti@gmail.com mailto:adeline.dutoit@up.ac.za https://ojs.hh.se/ 6 with the development and sales of pharmaceuticals (baines 2010, 8). baines outlines four major challenges facing the industry: • decline in the discovery, approval and marketing of new chemical entities (nce). • fewer and fewer highly successful drugs are making it to the market. • competition from generic drugs. • regulatory pressures. in south africa all four challenges outlined above are pressing factors that pharmaceutical manufacturers have to deal with on a daily basis. medical aid schemes too are feeling the pressure from another source, namely biologics. buthlezi (2012, 15) reported on the unsustainability of the costs of these medicines in the next few years, despite an increasing demand for these specialised expensive drugs. buthlezi noted too that liberty medical scheme was concerned with the extensive biologics pipeline, resulting in future unsustainable medicine expenditure. discovery health also contributed to the argument that health-care funders and policymakers need to find a way to make these expensive medicines sustainable and affordable (buthlezi 2012, 15). it is the purpose of this article to report on the ci capacity of south african pharmaceutical manufacturing companies. competitive intelligence mcgonagle and vella (2002, 36) define ci as: • the use of public sources to develop data (unprocessed facts) on competition, competitors, and the market environment; and • the transformation, by analysis, of those data into information (usable results) able to support business decisions. evans (2005, 6) defines ci as integrated knowledge, namely ci = c³: collecting data; converting it through analysis into meaningful information and communicating it. according to correia (2003, 1) “unlike business intelligence, which has become a catch-all term that companies like ibm use to describe data mining and activities involving business information, ci involves competitive analysis and examines competitive forces within one’s industry.” senior managers need to understand that good ci is critical to an organisation’s competitive decision and competitive performance (hall & bensousson 2007, 101). they need to start practising ci routinely and comprehensively and use the intelligence in their strategic decision-making (viviers, muller & du toit 2005, 253). sewlal (2004, 3) concurs in his research: “for a company to use its ci efforts successfully, an appropriate organisational awareness of ci and a culture of competitiveness are necessary.” competitiveness in the pharmaceutical industry according to wright, fleischer and madden (2008, 2), the pharmaceutical industry needs to maintain its position by keeping “abreast of all decisions influencing factors, including competitors.” astra zeneca was one of the few pharmaceutical companies that “had devised a fully integrated early warning system” concerning the impact of biotechnology on the industry (badr et al. 2006, 19). furthermore, fuld (2004), cited in badr et al. (2006, 19), states that the “frenzy surrounding the provision of aids drugs to africa” was due to “the inadequacies of a ci function in many leading pharmaceutical companies.” since 2008, south africa, along with the rest of the modern world, has witnessed evolving business platforms where complexity, rapid change and a competitive environment co-exist. in order to grow in this new global economy, organisations tend to address the advantages of implementing ci. south african industries need to grow markets internationally because their domestic market offers limited returns on their investments and as a result of more complicated government regulations, a volatile currency and political uncertainty, profit margins are under threat. in addition, to penetrate and maintain a position in international markets, significant hurdles need to be overcome. in aspects of decision-making that involve factors such as competitors, risks, blind spots and unseen opportunities, ci has the edge in terms of analysis to provide actionable intelligence for strategy. the pharmaceutical industry has been experiencing major shifts since 2008. henderson (2011, 35) states that “the past decade has not been kind to the pharmaceutical industry. while many of its biggest blockbusters stating anti-depressants and painkillers have drifted out of patents, others have been forced off the market by serious side-effects with health services driving a harder bargain than ever and the cost of research and development pushing £630 million ($1 billion) for every new drug.” savioz and sugasawa, cited in wright, fleisher and madden (2008, 2), particularly state that because the pharmaceutical industry is a highly dynamic market, it needs to maintain its position by keeping “abreast of all decisions influencing factors, including competitors.” richardson (2008, 1) notes that while some pharmaceutical companies have jettisoned their ci activities, others have invested more into developing them. 7 the manufacturing of drugs is an expensive business. the pharmaceutical industry itself is highly competitive, driven by the need to innovate and discover new, expensive drugs. the time span of 20 years to discover and market a new drug is an added reason why multinationals have unique ci challenges. by becoming more globalised, multinationals can reduce their dependency on local markets where competition has increased, especially in the pharmaceutical industry. global markets offer a better return on investments. in particular, the global affluent ageing populations with higher disposable incomes are an enticement to multinationals, which have to contend with the current south african government’s decision to give business to foreign manufacturers that offer donor-funded discounts (rncos industry research solutions 2011, 1). consequently, when profit margins are under pressure, multinationals need to base future strategy by factoring in such a unique ci challenge if they initially saw the risk, but if they saw the opportunity too, they might have global markets earlier. rncos industry research solutions (2011, 2) supports this notion by stating that their “overseas expansion strategy is being driven by a need to reduce its dependence on its home market.” seemingly the current characteristic of the south african pharmaceutical industry is to encourage multinationals to keep their bases on south african soil, as this is where the huge disease burdens occur, for example diabetes, tb, high blood pressure and hiv/aids. they could expand globally to gain a profitable return on their investments, but keep their options open in the hope that new government regulations, economic and political agendas will become more favourable. notably the incidence of clinical trials for hiv/aids is significantly lower than in other countries (montague & oosthuizen 2010, 23), providing further reason for multinationals to continue doing business in south africa. since the new political dispensation after 1994, the south african pharmaceutical industry has undergone dramatic changes in trying to adapt to the new order. martin (2002, 4) advocates that: “the new landscape in which business operates, demands agility.” government and business operate in the same environment. their integration defines characteristics for the pharmaceutical industry. some of these characteristics, such as price and volume of medicines, a volatile labour force, changing regulations and government legislation can be characterised by the contemporary examples given below. medical aids have to decide annually which patients should benefit in the current economic climate from expensive biological drugs because there is a growing demand from a minority of patients who need to be serviced by these new drugs (kahn 2012, 10).these specialised drugs are used for chronic conditions. the majority of clients would have to have their monthly premiums increased to accommodate these escalating costs, which are unlikely to drop, as biologics are sought after innovations and pharmaceutical companies need to get a return on their investments. pushing up costs is a dilemma for patient, doctor and medical aid (kahn 2012, 10). dr rajesh patel, head of risks and benefits at the board of healthcare funders, affirms this analysis and suggests that the south african government’s nhi could have a central fund that would be a solution to finance biologics (kahn 2012, 10). this example illustrates one of the problems of the industry, the dilemma of cost versus quality healthcare in a developing country. a second example highlights a problem accelerated by government legislation. in 2011 doctors and hiv clinicians warned of a pending national shortage of antiretroviral (arv) drug supplies. those responsible are the suppliers rather than the manufacturers per se, because contracts are awarded annually to government-favoured suppliers, in this case 30% to sonke pharmaceutical and 70% to aspen pharmacare. in addition, there has been an enormous increase in the number of hiv patients requesting treatment and the usa’s contribution has been dwindling. the department of health seems to lack the capacity to put timeous pressure on contracted suppliers to be answerable to their mandate (bodibe 2012, 1). admittedly the fallout was addressed in june 2012 by the department of health. it requested other suppliers to assist; among others aspen pharmacare exceeded its contractual mandate. subsequently the cause of the problem was related to an increase in the number of patients requesting arv drugs because of government’s advertising of free testing and free medication. in addition, the previous international nongovernmental organisations donors did not fulfil their commitments, stating that the south african government had enough funds to supply the drugs. government was caught unprepared. a third matter of concern in the industry is cost. the manufacturer, pharma dynamics, recently cut its prices on antidepressants and drugs for hypertension and diabetes to benefit “a greater proportion of the population” (buthelezi 2012, 19). such a magnanimous step characterises the agility with which the south african pharmaceutical industry is able to participate in the global economy. these examples help to illustrate the kinds of challenges that characterise the current industry. timur (2006, 8) identifies a set of more universal characteristics which are equally applicable to the south africa situation. he states that 8 pharmaceuticals are “the world’s most researchintensive industry, generating new drugs that satisfy vital consumer needs in healthcare by saving lives and significantly increasing quality of life”, which is fundamental to its existence. scherer, cited in timur (2006, 8), credits the industry as a ‘crucial component in delivering healthcare’. ultimately, although these characteristics have a noble ring to them, the industry also demands a heavy price in terms of service delivery, involving factors such as government regulations, fluctuating profit margins, spiralling costs and an escalating capacity demanding to be addressed. the south african pharmaceutical industry is undergoing rapid transformation spurred on by the current economic climate, government policy and an evolving local existing customer base. also within this cauldron of factors is the dominating framework of globalisation. south africa, like many developing countries, needs to embrace an open-market economy to develop competitiveness which, in turn, will “enhance its competitiveness to improve living standards” (blanke 2007, 3). besides the evidence from literature reviews narrated above, it seems that there is a powerful argument for the pharmaceutical industry to adopt a ci functionality in south africa. there are additional benefits that ci can bring to the industry. ci‘s chief benefit to any organisation, is its ability to monitor a company’s competition within the industry and the wider market continuously. this is currently of great importance as there are opportunistic firms that have penetrated the traditional, monopolistic pharmaceutical industry. buck-luce (2011, 1) confirms this trend: “it firms, telecommunications companies, data management firms, internet services companies and social media sites” are encroaching on the lucrative international pharmaceutical industry.” empirical survey of ci in south african pharmaceutical companies: methodology there is no complete list of manufacturing pharmaceutical companies in south africa, except for a list of viable current manufacturers used by retail pharmacies (mims, 2011, 2063-2064). additional manufacturer’s contacts were accessed via telephone directories and the internet and eventually a list of 68 manufacturing pharmaceutical companies was compiled. the questionnaire consisted of 24 questions divided into sections a, b, c, d and e. section a required background information while section b explored the respondents’ thinking on ci activities. section c attempted to elicit the extent of ci capacity in the respondent's company. section d focused on analysis and interpretation of a senior manager's use of ci as a tool to help with information analysis. section e queried whether respondents could comment on the value ci adds to strategic management. the questionnaire was tested in a trial or pilot run with six different respondents involved with the medical and pharmaceutical industry. they appreciated the significance of strategic planning and knew about ci. consequently justifiable constructive criticism was levelled at the existing questionnaire. a few minor changes were made to accommodate the valid criticism. an electronic questionnaire as an instrument of data collection was chosen because of its practicality in surveying the perceptions of busy senior managers spread across a wide geographical base. access to the questionnaire was via an electronic link embedded in the covering letter. the link is part of the web-based surveymonkey tool (www.surveymonkey.com). it was used as a format to capture completed responses, which could be automatically submitted once each respondent had completed the questionnaire. the statistical consultation service (statkon) at the university of johannesburg assisted with data capturing analysis, using statistical package for social science (spss) software. the main disadvantage of an electronic questionnaire over most other forms of surveys is that response rates can be low (o’leary 2005, 106). to address the problem, the authors reminded potential respondents every week to participate. an email was sent directly to the contact responsible for strategic planning in the company. the email included a covering letter with a link embedded for the recipient to access the questionnaire. the number of completed questionnaires was 30 giving a response rate of 44%. findings background information the majority of respondents were between the ages of 40 and 49 years (44.8% (13)), with 27.6% (8) respondents falling into the 30 to 39 years range and 20.7% (6) respondents in the 50 to 59 years level. in findings by strauss (2008, 51), she noted that the majority of respondents fell into the age category 40 years and above, while du toit and sewdass (2012, 230) found that 50% of respondents were younger than 50 years. all three findings suggest a tendency for a younger generation of ci professionals starting to filter through in south africa. the majority of respondents (30% (9)) have a post-school diploma/certificate. however, 39.9% (12) of the respondents have a post-graduate degree – 13.3% an honours degree, 23,3% a master’s degree and 9 3.3% a doctoral degree and the majority of the respondents (80.0% (24)) were at top management level. these findings suggest that ci is being supported by senior management in the south african pharmaceutical industry, which is in keeping with the position of taking on responsibility for a company’s strategy. ci activities a formal ci function is only available in 42.3% (11) of the companies. according to du toit (2003, 117) formal intelligence units were used by only 26% of the manufacturing companies she surveyed, with 76% having some kind of ci system in place. when comparing the present results, where only 42.3% of the pharmaceutical manufacturing companies have a formal ci function, no real improvement since 2003 is evident for companies operating in 2012. research by du toit and sewdass (2012, 231) found that 60% of the companies they surveyed had a formal ci function. the ci function has been operating in the majority of companies for less than ten years and only 23.1% (3) of respondents confirmed that the ci function has been operating in their companies for more than 10 years. nineteen respondents said they did not know, indicating that they did not have a ci function in their companies. these findings support the research by du toit and strauss (2010, 29) that ci has been around for more than five years but less than 10 years and that of du toit and sewdass (2012, 231) that “the ci function has been in existence for more than five years in 65% of the companies” surveyed. the majority of respondents (69.6% (16)) viewed environmental scanning as extremely important and 68% (17) of the respondents have strategies in place to manage competitors on a continuous basis. according to the findings of du toit (2003, 117), only 43% of the companies used “formal environmental scanning systems.” the 69.6% mentioned above shows that there has been some improvement in the importance pharmaceutical companies paid to environmental scanning systems. this result suggests that the pharmaceutical industry is starting to take ci more seriously and using it to get a competitive edge. ci capacity the majority of respondents (52.2% (12)) confirmed that ci capacity is used in their company to generate profit. according to table 1, ci is often used to guide decision-making processes in 71.4% (15) of the companies. ci is often conducted in an organised and systematic way by 42% (9) of the companies, while it is sometimes used for early warning of competitive activities by 33.3% (7) of the respondents. ci is often used as early warning of emerging industry trends by the majority (52.45 911)) of respondents and it often helps to consolidate intelligence for strategic reasons at 42% (9) of the companies. at 42% of the respondents, the ci stature sometimes affects strategic planning. this evidence shows that ci is often considered by the majority of respondents to be a worthwhile business tool to be used in the company. the majority of the respondents (82.6% (19) were aware of the key intelligence needs of senior managers in their companies. this finding shows an improvement on how companies viewed the ceo’s needs in comparison to the findings of du toit (2003, 117) in 2003 where only 21% of ci units regularly interviewed ceos to understand their needs. with regard to the question ‘how are details of ci held collectively by your company?’ the majority of respondents (42.1% (8)) said that data were held in a database that was only available to the ci unit professionals. never rarely sometimes often always total ci is used to guide decision-making processes 0 0% 3 14.3% 2 9.5% 15 71.4% 1 4.8% 21 100% ci is delivered in an organised and systematic way 2 9.5% 5 23.8% 5 23.8% 9 42.0% 0 0% 21 100% ci is used for early warning of competitor activities 1 4.8% 2 9.5% 7 33.3% 6 28.6% 5 23.8% 21 100% ci is used for early warning of emerging industry trends 1 4.8% 2 9.5% 4 19.0% 11 52.4% 3 14.3% 21 100% ci helps to consolidate intelligence for 1 4.8% 3 14.3% 3 14.3% 11 52.4% 3 14.3% 21 100% 10 strategic reasons ci stature impact on strategic planning 1 4.8% 1 4.8% 2 9.5% 9 42.0% 8 38.1% 21 100% table 1: ci as used in company (the modal category for each option is shaded) use of primary sources according to table 2, the most important primary sources are staff attending conferences and seminars on a quarterly basis (54.5%), employees reporting back on competitor actions on a monthly basis (45%) and members of professional trade and industry associations on a monthly basis (40.9%). employees in competitor organisations are seldom used, indicating that the respondents use ethical ways to collect primary information. suppliers, customers (33.3% of respondents) and distributors (26.1% of respondents) are accessed on a daily basis. industry experts were accessed quarterly by 36.4% (8) of the respondents, which supports the finding by du toit and sewdass (2012, 232) that industry experts were an important source (see table 2: the modal category for each option is shaded). source daily weekly monthly quarterly annually never total consultants, market researchers 0 0% 0 0% 8 34.8% 3 13% 7 30.4% 5 21.7% 23 100% suppliers, customers 7 33.3% 5 23.8% 1 4.8% 5 23.8% 2 9.5% 1 4.8% 21 100% distributors 6 26.1% 4 17.4% 4 17.4% 4 17.4% 2 8.7% 3 13% 23 100% industry experts 0 0% 1 4.5% 5 22.7% 8 36.4% 6 27.3% 2 9.1% 22 100% staff joining from competitors 2 10% 0 0% 3 15% 3 15% 7 35% 5 25% 20 100% members of professional trade and industry associations 1 4.5% 2 9.1% 9 40.9% 4 18.2% 3 13.6% 3 13.6% 22 100% employees in competitor organisations 0 0% 1 4.8% 4 19% 2 9.5% 2 9.5% 12 57.1% 21 100% journalists 0 0% 1 4.8% 3 14.3% 7 33.3% 2 9.5% 3 38.1% 21 100% staff attending conferences and seminars 0 0% 1 4.5% 3 13.6$ 12 54.5% 5 22.7% 1 4.5% 22 100% recreational social activities 0 0% 1 4.5% 4 18.2% 4 18.2% 3 13.6% 10 45.5% 22 100% employees report back on competitor actions 3 15% 5 25% 9 45% 2 10% 1 5% 0 0% 20 100% employees report back on customer needs 5 23.8% 7 33.3% 8 38.1% 0 0% 0 0% 1 4.8% 21 100% other 0 0% 0 0% 0 0% 0 0% 0 0% 0 0% 2 100% table 2: use of primary sources (the modal category for each option is shaded) use of secondary sources according to table 3, the most important secondary sources are trade literature, which is accessed monthly by 59.1% of the respondents, promotional material, which is accessed monthly by 54.5% of the respondents, information on regulatory bodies, which is accessed monthly by 50% of the respondents, and general newspapers, which is accessed daily by 50% of the respondents. survey summaries are seldom used by the respondents. this finding is in direct contrast to a similar finding by du toit and sewdass (2012, 231) that survey summaries are accessed quarterly and monthly by south african companies. corporate websites (accessed by 22.7% of the respondents on a monthly and quarterly basis) and industry analyst reports (accessed by 45.5% of the respondents on a quarterly basis) were not as frequently accessed, according to the findings of du toit and sewdass (2012, 231). 11 source daily weekly monthly quarterly annually never total corporate websites 1 4.5% 4 18.2% 5 22.7% 5 22.7% 4 18.2% 3 13.6% 22 100% sales forecasts 4 19% 6 28.6% 5 23.8% 2 9.5% 1 4.8% 3 14.3% 21 100% operational performance data 4 19% 6 28.6% 4 19% 5 23.8% 1 4.8% 1 4.8% 21 100% internal financial information 3 13.6% 7 31.8% 7 31.8% 2 9.1% 0 0% 3 13.6% 22 100% information on regulatory bodies 3 13.6% 2 9.1% 11 50% 4 18.2% 0 0% 2 9.1% 22 100% customer demographics 1 4.5% 1 4.5% 8 36.4% 6 27.3% 6 17.3% 0 0% 22 100% information on potential business partners 2 9.1% 1 4.5% 5 22.7% 11 50% 3 13.6% 0 0% 22 100% research reports 1 4.5% 1 4.5% 8 36.4% 7 31.8% 4 18.2% 1 4.5% 22 100% trade shows/conferences 0 0% 1 4.5% 3 13.8% 11 50% 7 31.8% 0 0% 22 100% trade literature (journals) 1 4.5% 3 13.8% 13 59.1% 4 18.2% 0 0% 1 4.5% 22 100% promotional material 2 9.1% 3 13.8% 12 54.5% 3 13.8% 0 0% 2 9.1% 22 100% corporate annual/quarterly reports 0 0% 2 9.5% 1 4.8% 9 42.9% 7 33.3% 2 9.8% 21 100% industry analyst reports 0 0% 2 9.1% 2 9.1% 10 45.5% 6 27.3% 2 9.1% 22 100% survey summaries 0 0% 0 0% 2 9.5% 5 23.8% 8 38.1% 6 28.6% 21 100% market research reports 1 4.5% 0 0% 6 27.3% 9 40.9% 5 22.7% 1 4.5% 22 100% specific government literature 1 4.5% 2 9.1% 7 31.8% 8 36.4% 3 13.6% 1 4.5% 22 100% general newspapers 11 50% 5 22.7% 3 13.6% 0 0% 0 0% 3 13.6% 22 100% other 0 0% 0 0% 0 0% 0 0% 0 0% 1 100% 1 100% table 3: use of secondary sources (the modal category for each option is shaded) analytical methods/models used table 4 shows that the respondents often use industry analysis (59.1% of respondents), gap analysis (57.1% of respondents) and benchmarking (54.5% of respondents). only 31.8% of the respondents always use swot analysis, while the sophisticated methods porter’s tm four corner model and blind-spot analysis are seldom used by the respondents (see table 5.6: the modal category for each option is shaded). method/model never rarely sometimes often always total benchmarking 2 9.1% 1 4.5% 6 27.3% 12 54.5% 1 4.5% 22 100% porter’s tm four corner model 8 38.1% 8 38.1% 1 4.8% 4 19% 0 0% 21 100% blind-spot analysis 7 33.3% 7 33.3% 4 19% 2 9.5% 1 4.8% 21 100% competitor analysis 1 4.5% 2 9.1% 3 13.6% 10 45.5% 6 27.3% 22 100% gap analysis 2 9.5% 1 4.8% 3 14.3% 12 57.1% 3 14.3% 21 100% industry analysis 1 4.5% 0 0% 4 18.2% 14 59.1% 4 18.2% 22 100% macroenvironment (steep) analysis 3 14.3% 3 14.3% 6 28.6% 7 33.3% 2 9.5% 21 100% 12 patent analysis 5 22.7% 3 13.6% 6 27.3% 7 31.8% 1 4.5% 22 100% scenario analysis 3 13.6% 4 18.2% 5 22.7% 8 36.4% 2 9.1% 22 100% strategic group analysis 4 18.2% 4 18.2% 4 18.2% 9 40.9% 1 4.5% 22 100% swot analysis 1 4.5% 1 4.5% 3 13.6% 10 45.5% 7 31.8% 22 100% value chain analysis 4 20% 3 15% 3 15% 7 35% 3 15% 20 100% table 4: analytical methods/models used importance of analysed information for decision making recent findings by du toit and sewdass (2012, 231) confirm that 30% of companies they surveyed in south africa strongly agreed that they use ci for decision-making. with regard to the question on how often ci is used in strategic decision-making, the majority of the respondents (47.6% (10)) use ci on a continuous basis (see figure 1). this is encouraging, because it shows that ci is a business tool in the pharmaceutical industry. it is important to note that because of the rapid changes in the external environment, continuous use of ci is imperative for a company to survive. figure 1: use of ci in strategic decision-making conclusion and recommendations the objective of this article was to determine the situation of the south african pharmaceutical industry and ci capacity. with regard to ci capacity and the south african pharmaceutical industry, the findings suggest that there is sustainable commitment to the principles and practices of ci, although the enhancement of a ci culture through organisations seems to be lacking. the use and importance of ci environmental scanning showed positive development, thereby expanding ci capacity. most companies tend to access primary sources quarterly and monthly rather than continuously, which is a better option in terms of ci capability. staff attending conferences and seminars and employees reporting back on competitive actions were the most popular primary sources. secondary sources are accessed daily, quarterly and monthly, with trade literature and promotional material being the most popular. surprisingly, blind-spot analysis is seldom used as an analysis method/model and there is room for concern, as it is part of the analysis toolkit necessary to glean intelligence. the findings do support the importance and value of analysing information for continuous strategic decisionmaking. most organisations attempt to nurture ci capacity in the industry. in order to contribute to the existing pool of ci evidence in the industry, the following recommendations based on the findings of the questionnaire are detailed for further consideration: • senior management of pharmaceutical manufacturing companies needs to take advantage of the current climate of information-sharing and collaboration that exists and promote ci values. • companies in the pharmaceutical industry should try to establish a formal rather than an informal ci function. • senior management needs to capitalise and consolidate ci that is used on a continuous basis in strategic decisionmaking. 0 2 4 6 8 10 annually bi-annually quarterly continuous basis 13 • the frequent use of analytical methods and models to generate ci requires finetuning with more sophisticated analysis techniques. • companies should organise ci information systems to reduce time and the costs of monitoring of external environment profiling. • companies should capitalise and consolidate on the use of ci activities to promote strategic decision-making. • although primary and secondary sources are accessed mainly monthly and quarterly, there should be a directive from management to access these sources daily wherever possible. • senior management needs to promote a full ci team by upgrading the ad hoc team that will service ci principles and practices. • there needs to be more nurturing within companies to establish a thriving ci culture. • senior management should endorse the need to have one full ci database into which all employees feel valued to add their snippets of gossip and any other more serious items of information. the ci professional will be able to select and continue with appropriate analysis. • more training is required for all employees to become knowledgeable about ci’s value in the company. • innovation is generated from applied sciences, accumulated knowledge and human creativity; consequently a highly specialised industry like pharmaceuticals needs to rigorously adopt a full ci package to help find solutions to global competitive markets. in the light of the world-wide interest in ci, the hope is expressed that the definition of ci as quoted earlier (mcgonagle & vella 2002, 36), can be paraphrased as follows: ci is the process of gathering information that would then be processed, analysed and disseminated to those who require 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(2017) identifying key effective factors on the implementation process of business intelligence in the banking industry of iran. journal of intelligence studies in business. 7 (3) 5-24. article url: https://ojs.hh.se/index.php/jisib/article/view/241 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index identifying key effective factors on the implementation process of business intelligence in the banking industry of iran salah rezaiea, seyed javad mirabedinib and ataollah abtahic adepartment of it management, economics and management faculty, science and research branch, islamic azad university, tehran, iran; bcomputer faculty, central tehran branch, islamic azad university , tehran, iran; cdepartment of it management, economics and management faculty, science and research branch , islamic azad university, tehran, iran; j.mirabedini@yahoo.com journal of intelligence studies in business please scroll down for article identifying key effective factors on the implementation process of business intelligence in the banking industry of iran salah rezaiea*, seyed javad mirabedinib and ataollah abtahic a department of it management, economics and management faculty, science and research branch, islamic azad university, tehran, iran; b computer faculty, central tehran branch, islamic azad university, tehran, iran; c department of it management, economics and management faculty, science and research branch , islamic azad university, tehran, iran corresponding author (*): j.mirabedini@yahoo.com received 17 august 2017; accepted 23 october 2017 abstract though many organizations have turned to developing and using business intelligence systems, not all have been successful in implementing such systems. these systems have social-technical dimensions with many elements and are very complicated. numerous studies have been carried out on implementation and employment of business intelligence, but in the past studies only specific aspects and dimensions have been addressed. the aim of this study is to identify key factors in the implementation process of business intelligence in the iranian banking industry. the present research is objectively applied as a survey study in implementation strategy. also it is a descriptive study in terms of the research plan and data collection where two documentary and field study methods have been used for collecting data. the statistical population of this study comprises experts and professionals in information technology who are active in implementing solutions for business intelligence in the banking industry of iran. in this study, 16 people were chosen based on non-random judgment sampling combined with targeted and snowball sampling as a statistical sample and their viewpoints were extracted and refined using the fuzzy delphi technique. first through studying past research records and reviewing literature of effective factors in implementing business intelligence process, 37 factors were identified. then by implementing five rounds of the fuzzy delphi technique, 39 factors were confirmed as significant among 37 factors affecting the business intelligence implementation process in past studies and 10 factors proposed by experts. also, these 39 factors were classified in nine main groups including organizational, human, data quality, environmental, system ability, strategic, service quality, technical infrastructure, and managerial factors. managers and executives of business intelligence projects in iran's banking industry can achieve the given objectives and results by considering such significant factors in planning and taking measures related to effective implementation of business intelligence. keywords banking industry, business intelligence, fuzzy delphi technique, implementing business intelligence, key factors 1. introduction in recent years, business intelligence technologies have become a significant concept in information systems management, mixed with progressive organization culture and placed in the forefront of information technologies in supporting decision making. in journal of intelligence studies in business vol. 7, no. 3 (2017) pp. 5-24 open access: freely available at: https://ojs.hh.se/ 6 order to have a quick reaction to the market changes, organizations need managerial information systems to make different causal analyses about an organization and its environment. meanwhile, business intelligence systems, which are the most complicated information systems, provide a tool based on which information needs of the organization are properly fulfilled. in fact, business intelligence systems provide updated, reliable and sufficient trade information making it possible to deduct and understand concepts lying in trade information through process of discovery and analysis (azoff and charlesworth 2004). gartner (2009), a leading company in business analysis, carried out research on 1500 information senior managers throughout the world and identified business intelligence as the first priority of technology. thus, implementation and establishment of business intelligence systems have turned into a major priority for organizations’ information senior managers (yeoh and koronios 2010). but implementation of business intelligence systems, like other organizational solutions for information technology, had different results in different companies. some organizations have reported that their business intelligence systems have been successful while others reported that they failed in its implementation (sangar and iahad 2013). in fact today many organizations have adopted business intelligence systems for improving decision making process, however, not all implementations have been successful despite being used by so many organizations (zareravasan and rabiee 2014). implementation of information systems at organization level has been a vital step that can lead to disorder and problems in the organization, especially regarding implementation of business intelligence systems where there are more complications and problems since such systems relate to decision making, which is a complex and abstract task influenced by an environment’s potential and condition. implementing a business intelligence system requires diverse infrastructure and is financially considered to be an expensive project implemented throughout an organization. research shows that about 50-70 percent of business intelligence projects fail at the stage of implementation (taqwa and noori 2014). in fact, implementing business intelligence technology is often accompanied by much suffering of failures leading to waste of time and resources (bargshady et al. 2014). thus, while the market for business intelligence seems turbulent, establishment of business intelligence systems is complicated and expensive. generally, development and implementation of business intelligence has high risks and hazards for organizations (farrokhi and pokoradi 2012). therefore, despite the fact that implementing business intelligence has become a major priority for organizations’ information senior managers, not all have been successful in its implementation (yeoh and koronios 2010). though most studies have been carried out on information systems to increase the understanding of information technology implementation and evaluate information technology, involvement in improving organizational performance and effectiveness, the majority of these studies consider implementation to be one of the general phases of technology transfer while for successful implementation it is required that each phase is considered and their activities are taken into account (lai and mahapatra 1997). based on studies on business intelligence literature, different studies have been carried out on different fields including: vital factors of implementation success (zare ravasan and rabiee 2014; hwang et al. 2004; yeoh and koronios 2010; ariachandra and watson 2006; olsak and ziemba 2012; yeoh and popovic 2015; hawking 2013; vodapali, 2009), application and implementation of business intelligence (ramarkrishnan et al. 2012; popvic et al. 2012; seah et al. 2010; boyer et al. 2010; wixom and watson 2001; grubljesic, 2014; doodly 2015; chasalow 2009), system performance (lin et al. 2009), business intelligence system adoption (ramamurty et al. 2008; hwang et al. 2004), capabilities and applications of business intelligence (isik et al. 2013; moro et al. 2015; isik et al. 2011), intelligence maturity (najmi et al. 2010; popovic et al. 2009), implementation readiness factors (bagshady et al. 2014; anjariny et al. 2012), and performance evaluation (lin et al. 2009; rouhani et al. 2012). but in each of these studies, implementation and establishment of business intelligence process has been examined in a different dimension, angle and aspect. in fact, in these studies, business intelligence implementation has not been inclusively examined by a systemic and holistic approach. thus, the present study examines factors affecting the implementation process of 7 business intelligence based on process theory and approach. therefore, it has identified and classified factors through studying related literature and considering factors affecting the implementation process of business intelligence such as organization readiness, system design and development, project management, system adoption, system abilities and intelligence maturity in the iranian banking industry environment. in fact, the main problem in this study is to identify key effective factors in the implementation process of business intelligence in the banking industry of iran. 2. research: theoretical principles and background in this section, given the subject, problem and methodology, the literature and research history including business intelligence, business intelligence in the banking industry, factors affecting business intelligence implementation, delphi method and fuzzy sets are reviewed. 2.1 business intelligence business intelligence is an umbrella term introduced by howard dresner of gartner group in 1989 as a series of concepts and methods which, using fact-based computer systems, lead to improved decision making (rouhani et al. 2012). business intelligence is a comprehensive concept through which the whole organization decides to use information systems in the most effective manner in order to acquire timely and high quality information for decision making so that competitive advantages are created (hocevar and jaklic 2010). in the age of information explosion and information system formation and development in organizations, insular or integrated, the appropriate use and report making of information is an inevitable necessity. thus, due to competitive economy and business, making organizational data meaningful and facilitating decision making process has been at the center of attention of experts in information technology and management science and business professionals (howson 2008). since the introduction of business intelligence, information systems have witnessed fast growth of systems and decision support software applications, as well as business intelligence systems, while organizations started moving toward a business intelligent environment to have a single image of reality through organizational data presented by the integrated architecture (isik 2010). companies have increasingly recognized the significance of information technology as an enabler to achieve their own strategic objective. regarding this, the concept of using information systems to support decision making has been companies’ objective since the introduction of business based computer technologies. one information system with a specific purpose is named the “decision support system”. decision support systems are responsible for providing timely, related information with analytical abilities for managers’ effective decision making. with increased demands for information systems for supporting decision making terms have been used such as data warehouse, knowledge management, data mining, participation systems, online analytical processing and finally business intelligence systems, which covers all of the preceding terms (hawking 2013). business intelligence systems are an integrated collection of tools, technology and programmed products used for collecting, integrating, analyzing, and accessing data. in simple words, the main tasks of business intelligence systems include intelligent exploration, integration, storage and multidimensional analysis of data taken from different information sources (olszak and ziemba 2007). 2.2 business intelligence in the banking industry banking is a dynamic market with changing customer demands, intense competition, a need for strict control and management of risk. these are only some of the business environment features where modern banks do their operations. better decision making management and processes in such a market determine the success or failure of banks. thus, it is important to use business intelligence solutions in banks to provide decision makers with information sources in all of the bank’s business sections in order to take action for solving problems and to have timely, high quality decision making (erfani 2013). in fact banks need related and timely information to adapt to the new challenges of the complicated dynamic environment. to do so, banks collect data from different inside and outside sources while business intelligent tools lead to intelligent decision making using information technologies such as online analysis and data mining in the complicated 8 banking environment. implementation of business intelligence systems in banks begins with collection, improvement and refinement of daily operational data from inside and outside sources while more low-cost data help banks use business intelligence possibilities to boost their relationship with customers, attract potential customers, and increase growth. in fact, business intelligence effectively relates business strategy to information technology to make use of the present infrastructure of information technology and skills (curko and bach 2007). banking is an arena where plenty of data is produced, thus, business intelligence applications can potentially benefit banks and increase the validity of this study. on the whole, banking has been significant as an active industry in adopting innovations related to information systems and technologies so that banking areas such as credit evaluation, branches’ performance, electronic banking, and customer retention and classification have excelled in widely applied concepts of business intelligence and data mining techniques, data warehouse, and decision support systems (moro et al. 2015). 2.3 factors affecting business intelligence implementation implementing business intelligence systems can be very complicated. in addition to common problems in implementing information systems, there are other complicated problems such as integration, security, system scalability, managing the data warehouse, analysis tools and dashboards. generally there are many problems regarding business intelligence implementation, the most significant of which include: system development and need for integration, profit and cost and its justification, confidentiality and legal problems, present and future of business intelligence, business process management, documentation and security of support systems, and moralities in failure of business intelligence projects (turban et al. 2011). the costly and difficult project of business intelligence is distinct from other information technology projects in some fundamental aspects. the key distinctions identified between business intelligence projects and other information technology projects include: 1) these projects are business based, 2) support of business and information technology analysts is required in such projects, 3) the perfect definition of project requirements is impossible, 4) project management requires different approaches, 5) implementing solutions of business intelligence is the beginning of the work thus, broad tests are needed for system assessment, 6) due to the connection of users to project tools, changing management styles is vital, and 8) establishment of business intelligence in organizations is a program rather than a project (analytics 2010). moss and atre (2003) suggested that 60% of business intelligence projects have failed due to inappropriate planning, weak project management, non-fulfillment of business requirements, undefined tasks, undesirable data, not understanding the significance of some parameters such as meta data, and those that have been implemented were of low quality (moss and atre 2003). in general, many business intelligence application programs have failed due to infrastructure, cultural, organizational and technical problems. also, many business intelligence solutions have failed due to the final users’ lack of access and not effectively meeting the final users’ needs. business intelligence projects have also failed due to not considering activities at the organizational level, non-commitment of business supporters, disinclination or lack of access of business representatives, lack of skillful and trained staff, lack of business activity analyses, lack of understanding of the impact of acquired information on business profitability, and lack of using information by users and staff (chuah and wong 2013). as a whole it can be said that organizations implement decision making support systems to improve and deliver information required by decision makers and to support decision making activities. but results of studies indicate that all these systems are not successfully implemented, and predicted interests are not always realized. thus, it is not surprising that business researchers and experts have become sensitive about determining key factors affecting implementation (hartono et al. 2007). in this regard, it is said that the interventions to improve the success of information technology implementation is rooted in behavioral science, which using theories and models determines conditions and factors effective in its successful use (kukafka et al. 2003). also, in the past decades, contingency theory has become a stabilized basis in information systems and seven success variables in information systems have been determined as basic factors 9 including size, environment, strategy, structure, technology, duty and individual characteristics. size refers to the volume indices, such as the number of employees or amount of income. environment refers to the space around the system such as related industries. strategy refers to the information property and quality of explaining the company’s strategy. structure refers to an organization’s proportion to information system structure. technology refers to the type of technology or complication of the implemented technology. duty refers to various activities and their features, and finally individual characteristics refers to individual differences and their proportion to information system activities (raber et al. 2013). in general, in this study with regard to business intelligence system implementation as a process, it can be noted that choosing appropriate methodology for the system development, project team formation, project correct management and development requirement identification are topics raised in the system implementation stage. success of the implementation stage depends on previous stages. when pre-implementation actions are fully done and there is enough readiness, the design and implementation stage begins. postimplementation actions for business intelligence systems are summarized in topics such as business intelligence maturity, continuous improvement, performance management, and profitability of business intelligence. this stage indicates that system implementation in the organization is not periodical (taqwa and noori 2014). thus, effective factors in implementing process of business intelligence include different factors in the implementing stage such as an organization’s readiness, designing and methodology of development, project management, performance assessment and system maturity, system adoption, system capabilities, business and beneficiaries needs, and environmental factors. therefore, in the present study, effective factors in implementing processes of business intelligence are reviewed through deep examination of the theoretical and empirical history related to the aforementioned dimensions and aspects. based on this study’s results, a list of factors affecting implementation of the process of business intelligence with the most popularity in the literature and research background is presented in table 1. table 1 list of factors affecting the business intelligence implementation process. references factors (ansari et al. 2014) ; ( olbrich et al. 2012) ; (yeoh and koronios 2010) ; (bargshady et al. 2014) ; (vodapall 2009) ; (anjariny et al. 2012) ; (sangar and lahad 2013) ; (yeoh et al . 2008) ; (watson and wixom 2007) flexible and extensible technical infrastructure f1 (bargshady et al. 2014) ; (zare ravasan and rabiee 2014) ; (ansari et al. 2014) ; (hoseini et al. 2015) ; (raisivanani and ganjalikhan hakemi 2015) ; (yeoh and koronios 2010) ; (vodapall 2009) ; (anjariny et al. 2012 ) ; (sangar and lahad 2013) ; (yeoh et al. 2008) ; (dawson and van belle 2013) clear vision and objectives for business intelligence f2 (bargshady et al. 2014) ; (zare ravasan and rabiee 2014) ; (hoseini et al. 2015) ; (raisivanani and ganjalikhan hakemi 2015) ; (hawking 2013) ; (vodapall 2009) ; (anjariny et al. 2012) ; (sangar and lahad 2013) ; ( yeoh et al . 2008) ; (ojeda and ramaswamy 2014) ; (ojeda-castro et al. 2011) ; (mungree et al. 2013) planning and effective project management f3 (bargshady et al. 2014) ; (piri,2014) ; (zare ravasan and rabiee 2014) ; (ansari et al. 2014) ; (hoseini et al. 2015) ; ( ramamurthy et al. 2008 ) ; (hawking 2013) ; (grubljesic 2014) ; ( olbrich et al. 2012) ; (yeoh and koronios 2010) ; (vodapall 2009) ; (anjariny et al. 2012) ; (wixom and watson 2001) ; (hwang et el. 2004 ) ; (seah et al. 2010) ; (sangar and lahad 2013) ; (dawson and van belle 2013) ; (yeoh et al. 2008) ; ( foshay and kuziemsky 2014) ; (yeoh and koronios 2010) ; (howson 2008) ; ( watson and wixom 2007) senior manager’s commitment and support f4 (haqiqatmonfared and rezaei 2011) ; (ramamurthy et al. 2008) ; (grubljesic 2014) ; (anjariny et al. 2012) ; (sangar and lahad 2013) ; (almabhoud and ahmad 2010) ; (dawson and van belle 2013) usefulness and easy use of business intelligence system f5 (ronaqi and feizi 2013) ; (zare ravasan and rabiee 2014) ; (hoseini et al. 2015) ; (haqiqatmonfared and rezaei 2011) ; (ronaqi et al. 2014) ; (raisivanani and ganjalikhan hakemi 2015) ; (dooley 2015) ; (yeoh and koronios 2010) ; (isik et al. 2011) ; (sangar and lahad 2013) ; (almabhoud and ahmad 2010 ) ; (dinter et al. 2011) ; (howson 2008) the flexibility and speed of response to changes in the business intelligence system f6 (raisivanani and ganjalikhan hakemi 2015) ; (hawking,2013) ; (yeoh et l. 2008) strong and suitable framework for data governance and quality f7 (babamoradi 2012) ; (zare ravasan and rabiee 2014) ; (ansari et al. 2014) ; (hoseini et al. 2015) ; (raisivanani and ganjalikhan hakemi 2015) ; (hawking 2013) ; (grubljesic 2014) ; (vodapall 2009) ; (anjariny et al. 2012 ) ; (sangar and lahad 2013) ; (almabhoud and ahmad 2010) user training f8 10 (zare ravasan and rabiee 2014) ; (ronaqi and feizi 2013) ; ( ansari et al. 2014) ; (hoseini et al. 2015) ; ( boyer et al. 2010) ; (vodapall 2009) ; (almabhoud and ahmad 2010) user support f9 (hawking 2013); (seah et al. 2010); (chasalow 2009); (ansari et al. 2014); (hwang et el. 2004 ) ; ( yeoh et al. 2008) ; (grubljesic 2014) project leader and championship to lead and facilitate participation f10 (piri 2014) ; (zare ravasan and rabiee 2014) ; (ansari et al. 2014) ; (hoseini et al. 2015) ; (raisivanani and ganjalikhan hakemi 2015) ; (hawking 2013) ; (grubljesic 2014) ; ( olbrich et al. 2012) ; (anjariny et al. 2012) ; (wixom and watson 2001) ; (watson and wixom 2007) ; ( brooks et al. 2015) organization’s ability to provide sufficient resources f11 (nazari 2014); (rouhani et al. 2012) ; (ronaqi and feizi 2013) ; (ansari et al. 2014) ; (haqiqatmonfared and rrezaei, 2011) ; (ronaqi et al., 2014) ; (isik et al. 2013) ; (dooley 2015) ; (mahlouji 2014) ; (yeoh and koronios 2010) ; ; (isik et al. 2011) ; (vodapall 2009) integration capability of business intelligence system f12 (najmi et at. 2010) ; (ronaqi and feizi 2013) ; (hoseini et al. 2015) ; (ronaqi et al.,2014) ; (mahlouji 2014) analysis capability of business intelligence system f13 (babamoradi 2012) ; ( olbrich et al. 2012) ; (almabhoud and ahmad 2010 ) role of organizational communications f14 (ansari et al. 2014) ; (hawking 2013) ; ( olbrich et al. 2012) ; (grubljesic 2014) ; ( brooks et al. 2015) level of automation and maturity of organizational processes f15 (piri 2014); (zare ravasan and rabiee 2014); (hoseini et al. 2015); (haqiqatmonfared and rezaei 2011); (raisivanani and ganjalikhan hakemi 2015); (hawking 2013); (grubljesic 2014); (olbrich et al. 2012) ; (vodapall 2009); (anjariny et al. 2012); (sangar and lahad 2013); (dawson and van belle 2013) ; (lupu et al. 2007); (watson and wixom 2007) involvement of end users f16 (zare ravasan and rabiee 2014); (ansari et al. 2014); (khodaei and karimzadehgan moqadam 2014); (vodapall 2009); (thamir and polis 2015); (dinter et al. 2011) ; (williams and williams 2004) interaction and collaboration between business and information technology units f17 (khodaei and karimzadehgan moqadam 2014) ; (lonnqvist and pirttimaki 2006) ; (williams and williams 2004) culture of continuous process improvement f18 (khodaei and karimzadehgan moqadam 2014) ; (popvic et al. 2012) ; (williams and williams 2004) engineering culture of decision making process f19 (najmi et at. 2010) ; (khodaei and karimzadehgan moqadam 2014) ; ( popvic et al. 2012) ; (grubljesic 2014) ; (chasalow 2009) ; (foshay and kuziemsky 2014) ; (lonnqvist and pirttimaki 2006 ) culture of using information and analytics f20 (ansari et al. 2014) ; (raisivanani and ganjalikhan hakemi 2015) ; (hawking, 2013) ; (grubljesic 2014) ; (derarpalli 2013) ; (yeoh and koronios 2010) ; (anjariny et al. 2012) ; (castra and ramaswamy 2014) ; (howson 2008) the use of iterative development approaches in business intelligence projects f21 (zare ravasan and rabiee 2014) ; (khodaei and karimzadehgan moqadam 2014) ; (hawking 2013) ; ( boyer et al. 2010 ) ; (yeoh and koronios 2010) ; (dinter et al. 2011) ; (tarokh and mohajeri 2012) ; (esmaeili 2015) ; (mungree et al. 2013) ; (williams and williams 2004) the alignment of business intelligence strategy with organization’s strategy f22 (ramarkrishnan et al. 2012) ; (olbrich et al. 2012) ; (sangar and lahad 2013) laws and regulations related to business requirements and limitations f23 (olbrich et al. 2012) ; (isik et al. 2011) ; (vodapall 2009) ; (anjariny et al. 2012) ; (wixom and watson 2001) ; (almabhoud and ahmad 2010); (dawson and van belle 2013) ; (ansari et al. 2014) ; ( thamir and polis 2015) quality and reliability of data resources f24 (dooley 2015) ; (hawking 2013) ; ( popvic et al. 2012) sharing and presentation of information f25 (zare ravasan and rabiee 2014) ; (hawking 2013) ; (grubljesic 2014) ; (vodapall 2009) ; (wixom and watson 2001) ; (sangar and lahad, 2013) ; ( castra and ramaswamy 2014) ; (ojeda-castro et al. 2011) choosing technology and tools appropriate to organization’s conditions f26 (zare ravasan and rabiee 2014) ; (ansari et al. 2014) ; (hawking 2013) ; (yeoh and koronios 2010) ; (vodapall 2009) ; (almabhoud and ahmad 2010 ) ; (olsak and ziemba 2012) ; (williams and williams 2004) effective change of management f27 (raisivanani and ganjalikhan hakemi 2015) ; (hawking 2013) ; (anjariny et al. 2012) ; (yeoh et al. 2008) ; (yeoh and koronios 2010) ; (sangar and lahad 2013) using outside consultants f28 (hawking 2013) ; (sangar and lahad 2013) interaction with vendors and choosing suitable suppliers f29 (ansari et al. 2014) ; (hoseini et al. 2015) ; (olbrich et al. 2012) ; (yeoh and koronios 2010) ; (vodapall 2009) ; (anjariny et al. 2012) ; (yeoh et al. 2010) ; (almabhoud and ahmad 2010) ; (ojeda castro and ramaswamy 2014) ; (ojeda castro et al. 2011) balanced and strong combination of project team f30 (grubljesic 2014); (olbrich et al. 2012); (yeoh and koronios 2010); (hwang et el. 2004) competition setting in business f31 (hawking 2013); ( foshay and kuziemsky 2014 ); (sangar and lahad 2013); (friedman et al. 2003); (cuza 2009); (watson and wixom 2007); (tabarsa and nazari poor 2014); ( olbrich et al. 2012) skills of information technology, business and analytical f32 (ronaqi and ronaqi 2014); ( popvic et al. 2012); (dooley 2015 ); (isik et al. 2011); (isik et al. 2013) quality of access to information f33 (ronaqi and ronaqi 2014); ( popvic et al. 2012); (dooley 2015); ( lin et al. 2009) quality of information content f34 (ansari et al.,2014); (hoseini et al. 2015); (sangar and lahad 2013); (almabhoud and ahmad 2010) the precision, accuracy, and perfectness of data f35 (hoseini et al. 2015); (raisivanani and ganjalikhan hakemi 2015); (sangar and lahad 2013) user friendliness and easy learning of business intelligence tools f36 (haqiqatmonfared and rezaei, 2011); (dooley, 2015); (isik et al., 2011); (sangar and lahad 2013) precision of information at system output f37 11 2.4 an overview of the delphi method the delphi technique is one of the qualitative research methods used for reaching consensus in group decision making. practically, the delphi method is a series of questionnaires or consecutive rounds with controlled feedback attempting to reach consensus among a group of experts on a particular subject (hasson and mckenna 2000). this method relies on the supposition that consensus among experts is stronger than individual viewpoints. thus, unlike survey research methods, the delphi method’s credit depends not only on the number of participants but on the scientific credit of expert participants. thus, a number of participants between 5 and 20 would be enough (rowe 2001). the classic delphi technique has always suffered low convergence of experts’ opinions, high implementation cost and potential exclusion of some individuals’ viewpoints. thus, the traditional delphi method concept of integration with fuzzy theory was raised and in this regard, fuzzy delphi method was invented by kaufman and gopta in 1990s (cheng and yin 2002; hsu and yang 2000). the fuzzy delphi method application for decision making and consensus on problems where parameters and objectives are not defined leads to valuable results. the significant feature of this method is presenting a flexible framework covering many obstacles related to imprecision and inaccuracy. many problems in decision makings are related to imperfect and inaccurate information. on the other hand, decisions taken by experts are based on their individual qualification and are strongly subjective. thus it is better for the data to be displayed by fuzzy numbers rather than definite numbers. the fuzzy delphi method’s implementation rounds in fact is a combination of delphi method implementation and analyses of information using definitions of fuzzy sets theory (toy and garai 2012). 2.5 fuzzy sets in order to deal with the vagueness of human thought, zadeh (1965) first introduced the fuzzy set theory. a fuzzy set is a class of objects with a continuum of grades of membership. such a set is characterized by a membership function which assigns to each object a grade of membership ranging between zero and one. fuzzy sets and fuzzy logic are powerful mathematical tools for modeling. fuzzy sets theory provides a wider frame than classic sets theory, and this has contributed to its capability of reflecting the real world. modeling using fuzzy sets has proven to be an effective way for formulating decision problems where the information available is subjective and imprecise (kahraman et al. 2003b). it is possible to use different fuzzy numbers according to the situation. in applications, it is often convenient to work with triangular fuzzy numbers (tfns) because of their computational simplicity; moreover, they are useful in promoting representation and information processing in a fuzzy environment. therefore, in this paper, we use triangular fuzzy numbers. triangular fuzzy numbers are a special kind of fuzzy set. a triangular fuzzy number can be denoted as: n = (a, b, c). figure 1 is an illustration of the membership function of a triangular fuzzy number. the membership function of triangular fuzzy numbers is: 𝜇 𝑥 = %&' (&' if 𝑎 ≤ 𝑥 ≤ 𝑏 ; /&% /&( if 𝑏 ≤ 𝑥 ≤ 𝑐; 0 else particularly, when a = b = c, triangular fuzzy numbers become crisp numbers. figure 1 triangular fuzzy number. 12 that is, crisp numbers can be considered to be a special case of fuzzy numbers (daghighi masouleh et al. 2014). in this paper, after the data were collected, the fuzzy triangular numbers were converted into absolute fuzzy numbers by means of minkowski. 3. research methodology since the results of the present study have the potential of being applied to planning and actions taken to implement business intelligence in the banking industry of iran, this study is applied objective research and a survey in implementation strategy. also, based on the research plan and method of data collecting, it is a descriptive study which uses two methods of documentary and field studies for collecting information. the statistical population of this study comprises experts and professionals in the field of information technology who are active in implementing solutions for business intelligence in iran's banking industry. in the present study, 16 people were chosen in a nonrandom judgment sampling combined with targeted and snowball samplings as a statistical sample. using the fuzzy delphi method their opinions were extracted and refined. experts’ information was collected using a questionnaire so that each expert using the fuzzy approach expressed his/her opinion on the level of significance of factors affecting business intelligence implementation as well as on how to classify such factors in liker fivefold spectrum and through verbal variables (very low, low, average, high and very high). following the initial framework preparation resulting from the research literature review, a questionnaire was set and designed. then, 6 experts’ opinions were used to evaluate the questionnaire. they were university professors and experts in information technology. thus following the review of the questionnaire by these experts, their proposed ideas were exerted. also given the fact that their factors and dimensions have been verified by experts using the delphi technique, nominal and content validity of the measuring tool was confirmed by experts with a high score. to determine the questionnaire’s reliability, the cronbach alpha method was used with an alpha coefficient of 0.91 obtained for the questionnaire indicating an acceptable reliability. 3.1 research implementation process in this study, first a recognition of the present condition of this field was attained through examining the past research history. then the research literature background related to factors affecting the implementation process of business intelligence was closely reviewed. as a result of this review, 37 factors affecting the implementation process were identified that are shown in table 1. then, using the initial framework of factors and running five rounds of the fuzzy delphi technique, key factors affecting the implementation process of business intelligence in the iranian banking industry were identified then classified. the method for running the fuzzy delphi technique in the present study is explained in the following. as pointed out, the delphi panel members in this study were chosen in a non-random sampling and a combination of targeted (judgment) and chain (snowball) methods. in order to select experts and professionals, criteria such as sufficient knowledge and experience on the subject, inclination and enough time for cooperation in the research, and effective communication skills were considered, based on which 16 people were nominated as qualified by researchers for this study. these people were involved in implementing solutions, and plans and projects of business intelligence in the iranian banking industry. the demographic situation and features of the delphi panel experts in this study is presented in table 2. 13 table 2 frequency distribution and percentage of respondents based on demographic characteristics. sex age education activity background m f -25 2635 3645 +45 bachelor master phd -5 yrs 6-10 yrs +10 yrs 11 5 1 6 5 4 3 5 8 5 9 2 frequency 69 31 6.25 37.5 31.25 25 18.75 31.25 50 31.25 56.25 12.5 percent in this study all experts expressed their opinions through a questionnaire on the significance and classification of factors affecting the implementation process of business intelligence on a likert fivefold spectrum and trough verbal variables (very low, low, average, high and very high) using a fuzzy approach. given table 3 and figure 2, the mentioned factors and variables are defined as triangular fuzzy number (mousavi et al. 2015; mirsepasi et al. 2013; cheng and lin 2002; daghighi masouleh et al. 2014). in the present study, absolute fuzzy numbers ( χ ) in table 3 are calculated using a minkowski equation as the equation (1) . χ = 𝑚 + 9&: ; equation 1 in the above formula (α) is expressed as the lower limit (bound), (𝛽) is expressed as the upper limit (bound) and (m) is the biggest membership degree. also, each variable in the rounds of the fuzzy delphi technique was obtained using equations (2) and (3): 𝐴? = 𝑎@ ? ,𝑎b ? ,𝑎c ? , 𝑖 = 1,2,3,…,𝑛 equation 2 𝐴'jkl 𝑚@,𝑚b,𝑚c = 1 𝑛 𝑎1 ? , m ?l@ 1 𝑛 𝑎2 ? , m ?l@ 1 𝑛 𝑎3 ? m ?l@ equation 3 where ai stands for the expert’s opinion, ith and aave stand for the experts’ opinion fuzzy mean. in this study, if in running delphi technique rounds, the difference of opinions between experts (χi – χj ) on the rate of significance and/or their agreement on their classification is lower than 0.1, consensus is reached and the opinion poll process stops (cheng and lin 2002). it is noteworthy that conditions for reaching consensus in the delphi method are determined by the experts of the research and there isn’t any particular rule for that, but the higher the number of procedures and the stricter the consensus condition, the more valid the delphi results are (fink 1984). also to screen improper factors, a threshold must be chosen. usually, the threshold is determined by the experts’ subjective deduction and there is no general way or rule for determining that value. threshold values affect the number of factors to be screened. thus, given the objective of this study for identifying key factors affecting the implementation of business intelligence, threshold value for accepting factors was determined to be 0.75, i.e. equal to crisp value “high” for verbal variables in table 2. in fact, in case of expert consensus, if the experts’ final opinions mean (χj) on the rate of significance of factors and /or classification of factors reaches 0.75, then that factor is considered to be significant and/or the factors’ classification is approved by experts. but if the experts’ final opinions mean is lower than 0.75, then that factor is not considered to be significant and/or the factors’ classification is rejected by them. 14 table 3 triangular fuzzy numbers of verbal variables. absolute fuzzy )χ ( numbers fuzzy triangular )m , α ,β (numbers symbols linguistic variables 0.9375 ( 1, 0.25 , 0 ) vh very high 0.75 ( 0.75, 0.15, 0.15 ) h high 0.5 ( 0.5, 0.25, 0.25 ) m medium 0.25 ( 0.25, 0.15, 0.15 ) l low 0.0625 ( 0, 0 , 0.25 ) vl very low table 4 mean expert opinions on the significance of factors affecting implementation of business intelligence in the first round of the opinion poll. triangular fuzzy mean (m,α, β) factors triangular fuzzy mean (m,α, β) factors triangular fuzzy mean (m,α, β) factors β α m f β α m f β α m f 0.19 0.19 0.63 f27 0.20 0.22 0.61 f14 0.07 0.21 0.86 f1 0.22 0.20 0.48 f28 0.19 0.21 0.64 f15 0.12 0.19 0.77 f2 0.21 0.21 0.53 f29 0.16 0.18 0.66 f16 0.11 0.20 0.78 f3 0.15 0.23 0.72 f30 0.14 0.20 0.73 f17 0.08 0.20 0.81 f4 0.19 0.22 0.58 f31 0.13 0.21 0.75 f18 0.18 0.19 0.67 f5 0.12 0.19 0.77 f32 0.16 0.18 0.72 f19 0.13 0.21 0.77 f6 0.15 0.18 0.69 f33 0.15 0.19 0.77 f20 0.17 0.23 0.64 f7 0.12 0.19 0.78 f34 0.19 0.19 0.58 f21 0.18 0.19 0.64 f8 0.11 0.18 0.80 f35 0.13 0.19 0.78 f22 0.21 0.21 0.53 f9 0.14 0.18 0.73 f36 0.21 0.21 0.61 f23 0.18 0.21 0.67 f10 0.11 0.19 0.80 f37 0.11 0.20 0.81 f24 0.10 0.23 0.78 f11 0.20 0.22 0.61 f25 0.11 0.21 0.80 f12 0.17 0.17 0.70 f26 0.11 0.20 0.78 f13 table 5 new factors proposed by experts in the first round. proposed factors affecting the implementation process of business intelligence in the iranian banking industry f38 standardization of technical infrastructure in the bank f39 senior managers’ risk taking in modern technologies investment f40 quality of data extract, transformation, and loading process f41 appropriate architecture for business intelligence system f42 level of security in the business intelligence system f43 business intelligence technology compatibility with existing technologies f44 data integrity and consistency of data sources f45 the use of project risk management f46 tendency of managers to adopt information technology innovations f47 set up business intelligence strategy 15 table 6 mean expert opinions on significance of factors affecting implementation of business intelligence in the second round of the opinion poll. triangular fuzzy mean (m,α, β) factors triangular fuzzy mean (m,α, β) factors triangular fuzzy mean (m,α, β) factors β α m f β α m f β α m f 0.13 0.16 0.77 f33 0.08 0.19 0.81 f17 0.07 0.20 0.89 f1 0.12 0.19 0.80 f34 0.07 0.20 0.88 f18 0.09 0.18 0.84 f2 0.08 0.19 0.86 f35 0.11 0.18 0.81 f19 0.08 0.19 0.86 f3 0.13 0.17 0.77 f36 0.12 0.18 0.80 f20 0.06 0.21 0.88 f4 0.08 0.19 0.84 f37 0.19 0.19 0.66 f21 0.17 0.18 0.70 f5 0.20 0.20 0.53 f38 0.08 0.19 0.86 f22 0.10 0.19 0.81 f6 0.15 0.19 0.73 f39 0.15 0.16 0.75 f23 0.14 0.18 0.75 f7 0.11 0.20 0.81 f40 0.08 0.20 0.88 f24 0.14 0.17 0.77 f8 0.16 0.19 0.72 f41 0.19 0.19 0.64 f25 0.19 0.19 0.64 f9 0.13 0.21 0.77 f42 0.08 0.19 0.86 f26 0.14 0.17 0.77 f10 0.18 0.21 0.67 f43 0.15 0.15 0.75 f27 0.10 0.21 0.81 f11 0.13 0.19 0.77 f44 0.19 0.19 0.66 f28 0.09 0.20 0.84 f12 0.16 0.21 0.70 f45 0.18 0.18 0.67 f29 0.12 0.19 0.80 f13 0.21 0.20 0.50 f46 0.11 0.19 0.81 f30 0.19 0.21 0.64 f14 0.12 0.19 0.80 f47 0.15 0.17 0.73 f31 0.19 0.19 0.66 f15 0.11 0.19 0.80 f32 0.13 0.19 0.78 f16 table 7 experts’ difference of opinions on effective factors significance in the first and second rounds. difference of opinions rate mean defuzzificated opinion factors difference of opinions rate mean defuzzificated opinion factors difference of opinions rate mean defuzzificated opinion factors 1χ –2χ 2χ 1χ f 1χ –2χ 2χ 1χ f 1χ –2χ 2χ 1χ f 0.08 0.76 0.68 f33 0.06 0.79 0.72 f17 0.03 0.86 0.83 f1 0.02 0.78 0.76 f34 0.11 0.84 0.73 f18 0.07 0.82 0.75 f2 0.05 0.83 0.78 f35 0.089 0.80 0.71 f19 0.07 0.83 0.76 f3 0.04 0.76 0.72 f36 0.02 0.78 0.76 f20 0.04 0.84 0.78 f4 0.04 0.82 0.78 f37 0.08 0.66 0.58 f21 0.03 0.70 0.67 f5 0.53 f38 0.06 0.83 0.77 f22 0.04 0.79 0.75 f6 0.72 f39 0.14 0.75 0.61 f23 0.11 0.74 0.63 f7 0.79 f40 0.05 0.84 0.79 f24 0.12 0.76 0.64 f8 0.71 f41 0.03 0.64 0.61 f25 0.11 0.64 0.53 f9 0.75 f42 0.13 0.83 0.70 f26 0.09 0.76 0.66 f10 0.66 f43 0.12 0.75 0.63 f27 0.04 0.79 0.75 f11 0.75 f44 0.17 0.66 0.49 f28 0.05 0.82 0.77 f12 0.69 f45 0.14 0.67 0.53 f29 0.02 0.78 0.76 f13 0.50 f46 0.09 0.79 0.70 f30 0.03 0.64 0.61 f14 0.78 f47 0.16 0.73 0.57 f31 0.02 0.66 0.64 f15 0.03 0.78 0.75 f32 0.12 0.77 0.65 f16 table 8 mean expert opinions on the significance of factors affecting implementation of business intelligence in the third round of the opinion poll. triangular fuzzy mean (m,α, β) factors triangular fuzzy mean (m,α, β) factors triangular fuzzy mean (m,α, β) factors β α m f β α m f β α m f 0.14 0.17 0.77 f41 0.15 0.15 0.75 f27 0.13 0.16 0.78 f7 0.11 0.19 0.81 f42 0.16 0.16 0.75 f28 0.11 0.19 0.81 f8 0.14 0.17 0.77 f43 0.15 0.16 0.77 f29 0.18 0.18 0.69 f9 0.11 0.18 0.81 f44 0.14 0.17 0.77 f31 0.09 0.19 0.86 f16 0.13 0.19 0.78 f45 0.22 0.22 0.58 f38 0.05 0.21 0.91 f18 0.23 0.23 0.56 f46 0.13 0.18 0.78 f39 0.14 0.15 0.77 f23 0.08 0.19 0.86 f47 0.08 0.20 0.88 f40 0.07 0.21 0.89 f26 16 table 9 expert differences of opinions on effective factors’ significance in the second and third rounds. difference of opinions rate mean defuzzificated opinion factors difference of opinions rate mean defuzzificated opinion factors difference of opinions rate mean defuzzificated opinion factors 2χ – 3χ 3χ 2χ f 2χ – 3χ 3χ 2χ f 2χ – 3χ 3χ 2χ f 0.05 0.76 0.71 f41 0.00 0.75 0.75 f27 0.03 0.77 0.74 f7 0.04 0.79 0.75 f42 0.04 0.75 0.66 f28 0.03 0.79 0.76 f8 0.1 0.76 0.66 f43 0.09 0.76 0.67 f29 0.05 0.69 0.64 f9 0.05 0.80 0.75 f44 0.03 0.76 0.73 f31 0.07 0.84 0.77 f16 0.08 0.77 0.69 f45 0.05 0.58 0.53 f38 0.02 0.86 0.84 f18 0.06 0.56 0.50 f46 0.05 0.77 0.72 f39 0.01 0.76 0.75 f23 0.05 0.83 0.78 f47 0.05 0.84 0.79 f40 0.03 0.86 0.83 f26 table 10 key factors affecting the implementation process of business intelligence based on related dimensions in the banking industry of iran. factors (f) dimensions (d) flexible and extensible technical infrastructure (f1) choosing technology and tools appropriate to organization’s conditions (f26) appropriate architecture for business intelligence system (f41) business intelligence technology compatibility with existing technologies (f43) technical infrastructure d1 clear vision and objectives for business intelligence (f2) the alignment of business intelligence strategy with organization’s strategy (f22) set up business intelligence strategy (f47) strategic d2 planning and effective project management (f3) effective change of management (f27) balanced and strong combination of project team (f30) the use of project risk management (f45) managerial d3 senior manager’s commitment and support (f4) organization’s ability to provide sufficient resources (f11) interaction and collaboration between business and information technology units (f17) culture of continuous process improvement (f18) engineering culture of decision making process (f19) culture of using information and analytics (f20) senior managers’ risk taking in modern technologies investment (f39) organizational d4 strong and suitable framework for data governance and quality (f7) quality and reliability of data resources (f24) the precision, accuracy, and perfectness of data (f35) quality of data extract, transformation, and loading process (f40) data integrity and consistency of data sources (f44) data quality d5 laws and regulations related to business requirements and limitations (f23) using outside consultants (f28) interaction with vendors and choosing suitable suppliers (f29) level of competition setting in business (f31) environmental d6 user training (f8) project leader and championship to lead and facilitate participation (f10) involvement of end users (f16) skills of information technology, business and analytical (f32) human d7 the flexibility and speed of response to changes in the business intelligence system (f6) integration capability of business intelligence system (f12) analysis capability of business intelligence system (f13) level of security in the business intelligence system (f42) system ability d8 quality of access to information (f33) quality of information content (f34) user friendly and easy learning of business intelligence tools (f36) precision of information at system output (f37) service quality d9 17 table 11 expert opinion means on the rates of agreement in the classification of factors affecting implementation of business intelligence in the fourth round of the opinion poll. triangular fuzzy mean (m, α, β) dimensions and factors (d, f) triangular fuzzy mean (m, α, β) dimensions and factors (d, f) triangular fuzzy mean (m, α, β) dimensions and factors (d, f) β α m f d β α m f d β α m f d 0.14 0.21 0.73 f31 d6 0.15 0.19 0.73 f17 d4 0.12 0.20 0.78 f1 d1 0.13 0.19 0.77 f8 d7 0.14 0.20 0.75 f18 0.15 0.19 0.73 f26 0.14 0.22 0.73 f10 0.14 0.20 0.75 f19 0.14 0.20 0.75 f41 0.13 0.18 0.77 f16 0.13 0.19 0.78 f20 0.15 0.20 0.72 f43 0.12 0.20 0.78 f32 0.14 0.21 0.73 f39 0.13 0.21 0.77 f2 d2 0.13 0.18 0.77 f6 d8 0.15 0.20 0.72 f7 d5 0.13 0.19 0.77 f22 0.13 0.18 0.77 f12 0.13 0.18 0.77 f24 0.11 0.19 0.81 f47 0.13 0.19 0.77 f13 0.12 0.18 0.80 f35 0.13 0.19 0.77 f3 d3 0.15 0.19 0.73 f42 0.12 0.21 0.78 f40 0.14 0.20 0.71 f27 0.13 0.21 0.77 f33 d9 0.15 0.18 0.73 f44 0.14 0.21 0.73 f30 0.12 0.19 0.80 f34 0.13 0.21 0.77 f23 d6 0.15 0.20 0.72 f45 0.13 0.21 0.77 f36 0.14 0.21 0.73 f28 0.14 0.20 0.75 f4 d4 0.12 0.18 0.80 f37 0.16 0.19 0.72 f29 0.13 0.19 0.77 f10 table 12 expert opinion mean based on the rate of agreement on the classification of factors affecting implementation of business intelligence in the fifth round of the opinion poll. triangular fuzzy mean (m, α, β) dimensions and factors (d, f) triangular fuzzy mean (m, α, β) dimensions and factors (d, f) triangular fuzzy mean (m, α, β) dimensions and factors (d, f) β α m f d β α m f d β α m f d 0.14 0.18 0.75 f31 d6 0.14 0.17 0.77 f17 d4 0.10 0.18 0.83 f1 d1 0.13 0.18 0.78 f8 d7 0.13 0.18 0.78 f18 0.13 0.16 0.78 f26 0.13 0.18 0.77 f10 0.14 0.17 0.77 f19 0.12 0.17 0.80 f41 0.13 0.16 0.78 f16 0.11 0.18 0.81 f20 0.12 0.17 0.80 f43 0.11 0.19 0.81 f32 0.13 0.18 0.77 f39 0.12 0.17 0.80 f2 d2 0.13 0.16 0.78 f6 d8 0.13 0.18 0.78 f7 d5 0.12 0.17 0.80 f22 0.13 0.16 0.78 f12 0.12 0.17 0.80 f24 0.08 0.19 0.86 f47 0.13 0.18 0.78 f13 0.09 0.19 0.84 f35 0.11 0.18 0.81 f3 d3 0.15 0.16 0.75 f42 0.10 0.19 0.83 f40 0.12 0.17 0.76 f27 0.13 0.19 0.78 f33 d9 0.14 0.16 0.77 f44 0.13 0.16 0.78 f30 0.10 0.18 0.83 f34 0.11 0.19 0.81 f23 d6 0.15 0.16 0.75 f45 0.12 0.18 0.80 f36 0.13 0.18 0.77 f28 0.13 0.18 0.78 f4 d4 0.11 0.17 0.81 f37 0.15 0.16 0.75 f29 0.11 0.18 0.81 f10 table 13 expert difference of opinions based on the rate of agreement on the classification of factors affecting the implementation of business intelligence in the fourth and fifth rounds of the opinion poll. di ff er en ce o f op in io ns ra te m ea n de fu zz ifi ca t ed o pi ni on d im en si on s an d fa ct or s (d , f ) di ff er en ce o f op in io ns ra te m ea n de fu zz ifi ca t ed o pi ni on d im en si on s an d fa ct or s (d , f ) di ff er en ce o f op in io ns ra te m ea n de fu zz ifi ca t ed o pi ni on d im en si on s an d fa ct or s (d , f ) 4χ –5χ 5χ 4χ f d 4χ –5χ 5χ 4χ f d 4χ –5χ 5χ 4χ f d 0.02 0.74 0.72 f31 d6 0.04 0.76 0.72 f17 d4 0.05 0.81 0.76 f1 d1 0.02 0.77 0.75 f8 d7 0.04 0.77 0.73 f18 0.05 0.77 0.72 f26 0.04 0.75 0.71 f10 0.02 0.76 0.73 f19 0.05 0.79 0.73 f41 0.02 0.77 0.75 f16 0.03 0.80 0.77 f20 0.08 0.79 0.71 f43 0.03 0.79 0.76 f32 0.04 0.75 0.72 f39 0.04 0.79 0.75 f2 d2 0.02 0.77 0.75 f6 d8 0.06 0.77 0.71 f7 d5 0.04 0.79 0.75 f22 0.02 0.77 0.75 f12 0.03 0.79 0.75 f24 0.04 0.83 0.79 f47 0.02 0.77 0.75 f13 0.04 0.82 0.78 f35 0.05 0.80 0.75 f3 d3 0.02 0.75 0.72 f42 0.05 0.80 0.76 f40 0.05 0.75 0.70 f27 0.02 0.77 0.75 f33 d9 0.04 0.76 0.73 f44 0.05 0.77 0.72 f30 0.03 0.81 0.78 f34 0.05 0.79 0.75 f23 d6 0.04 0.75 0.71 f45 0.04 0.78 0.75 f36 0.04 0.75 0.72 f28 0.04 0.77 0.73 f4 d4 0.02 0.80 0.78 f37 0.04 0.75 0.71 f29 0.05 0.80 0.75 f10 4. data and findings analysis as stated in the previous section, researchers have examined and reviewed the research literature related to factors affecting the implementation process of business intelligence. the results of these reviews, according to table 1, were the identification of 37 factors affecting the implementation process. using this initial framework of factors and running five rounds of fuzzy delphi, key factors affecting implementation processes of business intelligence in the iranian banking industry were identified and classified. a summary of the results from running several rounds of the delphi technique is presented as follows. in the first round of the delphi technique, experts commented on the significance rate of factors affecting implementation processes of business intelligence in the iranian banking industry. using table 3 and equations (2) and (3), fuzzy mean experts’ opinions in the first round (m, α, β) are presented in table 4. also, experts were asked to comment on other significant factors affecting the implementation process of business intelligence in the banking industry of iran. thus, based on the experts’ opinions, 10 new factors affecting the implementation process of business intelligence were proposed, as shown in table 5. in the second round, in addition to reflecting the results of the first round of expert opinions, given the results of first round, they were asked to present new and corrective opinions on the significance rate of factors in the first round and give their proposed factors. using table 3 and equations (2) and (3), the expert opinion fuzzy mean (m, α, β) in the second round is shown in table 6. also, using equation (1), the expert opinion defuzzification mean in the first round (χ1) and second round (χ2) and expert difference of opinions (χ2 – χ1) in the first and second rounds on the significance of factors affecting implementation of business intelligence are shown in table 7. given the results shown in table 7, regarding 26 factors affecting implementation of business intelligence from table 1 including rows 16, 10-15, 17, 19-22, 24, 25, 30, and 32-37 there was a consensus due to the mean difference of opinions (χ2 –χ1) lower than 0.1, so that factors in rows 5,14,15, 21,and 25 are rejected due to their final mean (χ2) lower than 0.75 while other factors were significant and approved. in the third round of the fuzzy delphi technique opinion poll, experts were informed of the first and second rounds’ opinion results and given the results of the previous rounds new and corrective opinions of experts on the significance rate of 21 remaining factors were obtained. using table 3 and equations (2) and (3), the expert opinions fuzzy mean (m, α, β) in the third round is presented in table 8. also, using equation (1), table 9 shows the defuzzificated mean of expert opinions in the second round (χ2) and third round (χ3) as well as experts difference of opinions (χ3 –χ2) on the significance of factors affecting implementation of business intelligence in the second and third rounds. given the results in table 9 on the remaining factors, consensus was reached due to the mean difference (χ3 –χ2) lower than 0.1 so that the three factors in rows 9, 38, and 46 were rejected due to their final mean (χ3) which was lower than 0.75, while other factors were identified as significant key factors. in general, based on the opinion poll in rounds 1, 2, and 3, a total of 39 key factors affecting implementation of business intelligence were approved by experts and 8 factors were considered to be less significant. based on results of experts opinions in rounds 1, 2 and 3, 39 significant key factors affecting implementation of business intelligence were approved by consensus. first, these factors were classified in 9 groups as shown in table 10 based on research literature, opinions of university professors, concept similarity and their role in implementation of business intelligence, then they were presented as proposed aspects for the experts’ final opinion poll. it is to be noted that without going through this round it couldn’t be claimed that a reliable and integrated list is prepared (schmidt 1997). thus, in the fourth round of the delphi poll, experts were asked to give their opinions on the rate of agreement on this type of classification. using table 3 and equations (2) and (3), the fuzzy opinion mean (m, α, β) of experts in the fourth round is presented in table 11. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.2 0.4 0.6 0.8 1 vl l m h vh figure 2 verbal variable definition (fuzzy triangular number). 19 in the fifth round of the delphi technique, in addition to reflecting the result of the fourth round to experts, given the result of the previous round on classification of key factors affecting implementation process of business intelligence, they were asked to give their corrective opinions on the agreement rate with this classification again. using table 3 and equations (2) and (3), the expert fuzzy opinion mean (m, α, β) in the fifth round is presented in table 12. also using equation (1), table 13 shows the defuzzificated mean expert opinions in the fourth round (χ4) and fifth round (χ5) and expert difference of opinions (χ5χ4) in the fourth and fifth rounds on the rate of agreement on classification of key factors affecting implementation of business intelligence. given the results of table 13, experts reached consensus on the proposed classification of key factors due to a mean difference of opinions (χ5 – χ4) lower than 0.1 and this proposed classification was approved as the experts’ final opinion mean (χ5) was not lower than 0.75. therefore, it can be concluded that significant factors affecting the effective implementation of business intelligence in the iranian banking industry includes 9 dimensions: organizational, human, data quality, environmental, system ability, strategic, service quality, technical infrastructure and managerial, as shown in figure 3. 5. conclusion and proposals organizations are often faced with problems such as data congestion and redundancy, insufficient information and knowledge and low quality of needed reports. thus, for timely decision making in the minimum time by senior management, decisions are usually made based on their experiences, which in turn leads to increased risk of decision making or even decreased output of their decision making. business intelligence is a tool to be used by organizations to collect and analyze structured and unstructured data and information, and is a suitable response to the aforementioned challenges. though many organizations have turned to developing and using business intelligence systems, not all have been successful in their implementation. thus, it is very important to examine the reasons for failure in implementing business intelligence projects and identify factors affecting their implementation. the aim of the present study is to identify key factors affecting implementation of business intelligence in the iranian banking industry. thus, in this study, by running five rounds of the fuzzy delphi technique, among 37 factors affecting the implementation process of business intelligence in the past studies as well as 10 factors proposed by experts, finally 39 factors were identified and approved as significant. also, the 39 factors were classified in 9 main groups, as shown in table 10. in fact, it can be concluded that the significant factors affecting the effective implementation of business intelligence in the iranian banking industry include 9 dimensions: organizational, human, data quality, environmental, system ability, strategic, service quality, technical infrastructure and managerial, as shown in figure 3. accordingly, managers and executives of implimentation projects of business intelligence in the iranian banking industry can achieve the intended results and objectives by considering these important factors in planning and actions taken for the efficient implementation of business intelligence. achievements of this study not only can help banks to successfully implement business intelligence systems but also help researchers in conducting future research in this field. for future research and study of how each key factor affects the efficient implementation of business intelligence systems during different phases of project implementation and to examine the rate of these factors’ effects and interrelationship figure 3 key factors affecting implementation process of business intelligence. 20 between them, the authors propose a cognitive mapping methodology, case studies and an interpretive structural modeling approach. 6. references almabhouh, a., and ahmad, a. 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(2016) business intelligence evaluation model in enterprise systems using fuzzy promethee. journal of intelligence studies in business. 6 (3) 39-50 article url: https://ojs.hh.se/index.php/jisib/article/view/178 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index business intelligence evaluation model in enterprise systems using fuzzy promethee mansoureh maadia*, mohammad javidniab and malihe khatamia aschool of engineering, damghan university, damghan, iran, bschool of industrial engineering, iran university of science and technology, tehran, iran, *m_moadi@du.ac.ir journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: geospatial analysis of census data for targeting new businesses using geoeconomics business intelligence through patinformatics: a study of energy efficient data centres using patent data nishad deshpande, shabib ahmed and pp. 13-26 alok khode cross-cultural strategic intelligence solutions for leveraging open innovation opportunities journal of intelligence studies in business v ol 6 , n o 3 , 2 0 1 6 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 6, no. 3 2016 alexandru capatina, gianita bleoju pp. 27-38 and kiyohiro yamazaki business intelligence evaluation model in enterprise systems using fuzzy promethee mansoureh maadi, mohammad javidnia pp. 39-50 and malihe khatami sushant k. singh pp. 5-12 economic and industrial espionage at the start of the 21st century – status quaestionis klaus solberg søilen pp. 51-64 business intelligence evaluation model in enterprise systems using fuzzy promethee mansoureh maadia*, mohammad javidniab and malihe khatamia aschool of engineering, damghan university, damghan, iran; bschool of industrial engineering, iran university of science and technology, tehran, iran *corresponding author: m_moadi@du.ac.ir received 29 september 2016; accepted 25 november 2016 abstract in this paper, a new model to evaluate business intelligence (bi) for enterprise systems is presented. evaluation of bi before making decisions about buying and deployment can be an important decision support system for managers in organizations. in this paper, a simple and practical method is presented that evaluates bi for enterprise systems. in this way, after reviewing different papers in the literature, 34 criteria for bi specifications are determined, and then by applying fuzzy promethee, different enterprise systems are ranked. to continue to assess the proposed model and as a case study, five enterprise systems were selected and ranked using the proposed model. the advantages of promethee over other multi-criteria decision making methods and the use of fuzzy theory to deal with uncertainty in decision making is assessed and it is found that the proposed model can be a useful and applied method to help managers make decisions in organizations. keywords business intelligence, enterprise systems, fuzzy promethee, fuzzy theory, promethee 1. introduction traditional industrial informatics focus on how to provide more efficient and productive operations. but nowadays they cannot stay competitive just by providing more efficient and productive operations. they are facing the challenge of processing huge amounts of data and turning it into smart and timely decisions to deliver better products and services (lian & li 2012). in the present competitive world, accurate and up-to-date knowledge and information is considered to be a crucial factor for all organizations. in fact, today organizations need knowledge and information to achieve a competitive advantage when making important decisions. it development in recent decades has led to the appearance of different enterprise information systems such as enterprise resources planning (erp), supply chain management (scm) and customer relationship management (crm), which are introduced as modern tools in important enterprise decision-makings by storing different data in themselves (alter 2004; power 2008). enterprise information systems or enterprise systems can be defined as follows: software systems for business management, encompassing modules supporting enterprise functional areas such as planning, manufacturing, sales, marketing, distribution, accounting, finance, human resources management, project management, inventory management, service and maintenance, transportation and e-business (rashid et al. 2002). in order to deliver useful information for decision-making, business intelligence (bi) is a key technology (moss & atre 2003). bi software is among the many software products that organizations utilize to ensure their place in the market (abzaltynova & williams 2013). journal of intelligence studies in business vol. 6, no. 3 (2016) pp. 39-50 open access: freely available at: https://ojs.hh.se/ 40 most companies today use a set of different bi tools, instead of focusing only on one. the reason for this may be that different users prefer different types of bi tools (sabanovic & søilen 2012). the concept of bi was first introduced by the gartner group and in general it refers to tools and technologies such as data storing, reporting and analyzing information. in the past, researchers dealt with presenting tools for evaluating bi in enterprise systems. but in most studies, bi was examined and analyzed as an independent tool from enterprise systems. until 2006 and before lönnqvist & pirttimäki’s study, the existing studies in the field of bi tried to explain and prove the need for investment and the value of bi. lönnqvist & pirttimäki (2006) for the first time introduced a set of criteria for examining the performance of bi. albashir et al. (2008) investigated the effect of bi systems on business procedures and presented a method to measure the effect. in 2009, lin et al. established a performance assessment model based on analytic network process (anp) for an independent system (lin et al. 2009). nyblom et al. (2012) proposed a simple model for evaluating the performance of bi software systems based on what companies find to be most important; efficiency, user friendliness, overall satisfaction, price and adaptability. fourati-jamoussi & niamba (2016) proposed an evaluation model for bi tools using cluster analysis. ghazanfari et al.'s study in 2011 can be regarded as the first study to investigate bi in enterprise systems in which the authors have presented some criteria to evaluate bi in enterprise systems by examining different studies of bi and enterprise systems (ghazanfari et al. 2011). in 2012, rouhani et al. presented the fuzzy topsis method for evaluating bi in enterprise systems. also, in 2015, rouhani & zare presented a method for evaluating bi by using a fuzzy analytic network process (f-anp) (rouhani & zare 2015). one of the actions that influences the efficiency of decisions while making them is choosing a suitable method for decision-making among the existing methods. the preference ranking organization method for enrichment evaluation (promethee) is one of the best known decision-making methods. compared with other methods, this method is considered to be the best and has more advantages in different factors such as the ease of use, interpretation of parameters, reliability of results, amount of interaction required by the user and ease of understanding (al-shemmeri et al. 1997; gilliams, 2005; mahmoud & garcia, 2000). on the other hand, since the existing data on decision-making methods are usually based on opinions and the experiences of decision-makers and are expressed qualitatively, it is more likely to have errors in opinion interpretation. this has led to the suggestion of using fuzzy theory in solving problems with qualitative observations. in this paper, a model for evaluating bi in enterprise systems based on a fuzzy promethee method is presented. the rest of the paper is organized as follows: the second section of the paper deals with introducing the concept of bi and its definitions. also in this section, the promethee method is briefly described. the third section covers the description of the steps for the fuzzy promethee method for evaluating bi in enterprise systems. finally, the conclusion section deals with conclusions, results and suggestions. 2. theoretical basics 2.1 business intelligence business intelligence can bring critical capabilities to an organization, but the implementation of such capabilities is often problematic (adamala & cidrin 2011). bi was first defined by howard dresner, a researcher of the gartner group, and incipiently referred to the tools and technologies including data warehouses, reporting query and analysis (lian & li 2012). bi helps organizations make on-time decisions to reach their goals through using an advanced tool of analysis and prediction and by covering tasks like gathering, processing and analyzing large amount of data. ghoshal & kim (1986) defined bi as a management philosophy in the business environment. lönnqvist & pirttimäki (2006) used "business intelligence" for the two following concepts: 1. related information and knowledge of an organization, which describe the business environment, the organization itself, the conditions of the market, customers and competitors and economic issues; 2. systemic and systematic processes, by which organizations obtain, analyze and distribute the information for making decisions about business operations. 41 the main purpose of bi is to help organizations to improve their performance and promote their competitive benefits in the market. through evaluation of whether activities lead to organizations' progress toward their goals or not, bi helps in better decision-making (mohaghar et al. 2008). by investigating the literature on bi we encounter two attitudes toward it. first, a management attitude which looks at it as a procedure in which data is gathered and organized from inside and outside of the organization to provide information related to decision-making procedures. the second attitude is technical and introduces it as a set of tools which support the aforementioned procedures. in this respect, the focus is on the algorithms and tools which provide capabilities of data storing, recovery, gathering and analyzing, instead of procedures. 2.2 promethee promethee is a preferred structural method for evaluation and a multi criteria decision making (mcdm) method which was introduced by brans et al. in 1986. this method is well adapted to problems where a finite number of alternative actions are to be ranked with respect to several, sometimes conflicting criteria. the first method provides a partial priority relationship for ranking the alternatives while the second method assigns a numerical privilege for each alternative which is used in ranking (brans et al. 1986). a few years later, several versions of the promethee method have been developed. the implementation of promethee requires two additional types of information. the first one is information on the relative importance of the criteria, which is their weights, and the second one is the information on the decision maker's preference function, which the decision maker uses when comparing the contribution of the alternatives in terms of each separate criterion. in promethee, six basic types of preference functions are used: the usual function, the u-shape function, the v-shape function, the level function, the linear function and the gaussion function. the choice of preference function depends on decisionmakers and analyzers and their understanding of the relationship between the alternatives and criteria. the following parameters are used in these functions: q: indifference threshold. p: total preference threshold. σ: it is a parameter which shows the distance between p and q. considering the data matrix a = (a&,a(,a),…,a+) with n alternatives that should be evaluated by k criteria 𝑐 = (𝑓&,𝑓(,…. ,𝑓0 ) with the weights of 𝑤 = (𝑤&,𝑤(,…. ,𝑤0), the steps of the promethee method are as follows: step 1: determination of deviations based on pair-wise comparisons of two alternatives, a and b: (1) d3 a,b = f3 a − f3 b where d3(a,b) is the difference of the value of "a" and "b" in each criterion. step 2: application of preference function: (2) p3 a,b = g3[d3 a,b ] where p3 a,b denotes the preference of alternative "a" with regard to alternative “b” in each criterion, as a function of d3 a,b . the preference function can have a value in the range of 0 to 1 and it is interpreting the difference in terms of a specific criterion between the evaluations of a and b. step 3: calculation of global preference index: (3) ∀ a,b ϵa π a,b = p3 a,b < 3=& w3 where π a,b is defined as the weighted sum of p3 a,b for each criterion. step 4: calculation of outranking flows for all alternatives as follow: (4) φ@ a = & ab& πcde (a,x) (5) φ b a = 1 n − 1 π cde (x,a) (6) φaij a = φ@ a -φb a in this step φ@ a is the measure of how alternative "a" dominates the other alternatives of a and φb a gives how alternative "a" is dominated by all the other alternatives of a. φaij a represents a value function whereby a higher value reflects a higher attractiveness of alternative "a" and is called net flow. 42 promethee i is based on partial ranking, an alternative "a" is preferred to alternative "b" according to eq. 7, alternatives "a" and "b" are indifferent according to eq. 8 and alternatives of "a" and "b" are incomparable according to eq. 9. (7) φ@ a > φ@ b & φb a < φb b ;𝑜𝑟 φ@ a > φ@ b & φb a = φb b ;𝑜𝑟 φ@ a = φ@ b & φb a < φb b (8) φ @ a = φ@ b & φb a = φb b (9) φ@ a > φ@ b & φb a > φb b ;𝑜𝑟 φ@ a < φ@ b & φb a < φb b ; promethee ii is a complete ranking whereby alternatives are ranked from the best to the worst using net flows. the alternative with the highest net flow is assumed to be superior to the others and the rest of the alternatives are ranked by their net flow values as well. since in some problems certain figures cannot exactly express a decision maker's opinions and conditions of the alternatives, fuzzy number and fuzzy set theory provides a thorough approach which can help remove data's ambiguity. in this paper, the menhaj symbolizing method is used for fuzzy calculations in which the fuzzy number a is from lr type. in this way, every fuzzy number is shown by special functions, called reference functions, which determine the right and left sides of the fuzzy membership function. figure 1 presents fuzzy number 𝐴 = 𝑎,𝑤t,𝑤ut . in this article, the fuzzy promethee method explained by goumas and lygerou (2000) is used. in this method, numbers used in calculations of the promethee method are fuzzy numbers. of course, total preference and indifference thresholds (p,q) are expressed as definite numbers. if these numbers were fuzzy, some assessments would become inexact (goumas and lygerou, 2000). in addition, the indices' weights can’t be expressed as fuzzy numbers because in promethee the sum of indices' weights should be exactly equal to 1. the preference function applied in this paper is the v-shape function, which is shown in figure 2. in figure 2, d shows the difference between two compared alternatives, q is the indifference threshold and p is the total preference threshold. if d is expressed as a fuzzy number, the v-shape preference function can be written as eq.10. (10) p d = 0 a − we < 𝑞 a,we𝑤′t − q p − q a − we ≥ q and a + 𝑤′t ≤ p 1 a + 𝑤′t > 𝑝 fuzzy operations for calculations using fuzzy numbers to apply the above function are briefly explained in table 1. the overall preference of each alternative compared with other alternatives should be calculated and at the end, input and output flows and net flows should be determined for all alternatives. by finishing the calculations, fuzzy numbers are used to make the comparisons. first, through eq. 11, fuzzy numbers are changed to definite numbers and then comparisons are made. (11) 𝑋 = 𝑎 + 𝑤ut − 𝑤t 4 in eq.11, 𝑋 is a definite number equivalent to the fuzzy number 𝑎,𝑤t,𝑤ut . 3. suggested method to evaluate bi in enterprise systems using the fuzzy promethee method, first the evaluation criteria should be identified. to do so, after studying and examining the literature on this subject, 34 factors influencing bi were identified and are mentioned in table 2. after identifying evaluation criteria, five enterprise systems were chosen for evaluation and were named es1, es2, es3, es4, and es5, respectively. figure 2 v-shape preference function. figure 1 lr triangular fuzzy number. table 1 basic fuzzy operations equation type 𝑎,𝑤t,𝑤ut `a + b,𝑤b,𝑤ub `a = a + b,𝑤t + 𝑤b,𝑤ut + 𝑤ub `a addition −𝐴 = − 𝑎,𝑤t,𝑤ut `a = 𝑎,𝑤t,𝑤ut a` opposite 𝑎,𝑤t,𝑤ut `a − b,𝑤b,𝑤u� `a = a − b,𝑤t + 𝑤bu,𝑤tu + 𝑤b `a subtraction 𝑐.𝐴 = 𝑐. 𝑎,𝑤t,𝑤ut `a = 𝑐𝑎,𝑐𝑤t,𝑐𝑤ut `a multiplication by scalar 𝑎,𝑤t,𝑤ut `a. b,𝑤b,𝑤ub `a = ab,𝑏𝑤� + 𝑎𝑤b,𝑏𝑤ut + 𝑎𝑤ub `a 𝐴 > 0 ,𝐵 > 0 𝑎,𝑤t,𝑤ut `a. b,𝑤b,𝑤ub `a ≈ ab,𝑏𝑤t − 𝑎𝑤ub,−𝑏𝑤ut − 𝑎𝑤b a` 𝐴 < 0 ,𝐵 > 0 𝑎,𝑤t,𝑤ut `a. b,𝑤b,𝑤ub `a ≈ ab,−𝑏𝑤ut − 𝑎𝑤ub,−𝑏𝑤t − 𝑎𝑤b a` 𝐴 < 0 ,𝐵 < 0 multiplication by fuzzy 𝑎,𝑤t,𝑤ut b&`a ≡ 𝑎 b&,𝑤t𝑎b(,𝑤ut𝑎b( a` inverse 𝑎,𝑤t,𝑤tu `a ÷ b,𝑤b,𝑤bu `a = 𝑎 𝑏 , 𝑏𝑤t + 𝑎𝑤ub 𝑏( , 𝑏𝑤ut + 𝑎𝑤b 𝑏( 𝐴 > 0 ,𝐵 > 0 division to evaluate the above systems by a decisionmaking team, six linguistic values were used. these values and their equivalent fuzzy numbers are shown in table 3. all fuzzy numbers shown in table 3 are lr. according to linguistic values of table 3, five alternatives were examined based on 34 criteria by the decision-making team. the fuzzy decisionmaking matrix for five enterprise systems of the article based on experts' judgment is shown in table 4. in the following, the procedure of solving the problem using the fuzzy promethee method will be explained. table 2 business intelligence evaluation criteria (continued on next page). criteria id criteria name related studies c1 group wares shim et al. (2002), reich & kapeliuk (2005), damart et al. (2007), marinoni et al. (2009) c2 group decision-making eom (1999), evers (2008), yu et al. (2009) c3 flexibility of decisionmaking model reich & kapeliuk (2005), zack (2007), lin et al. (2009) c4 problem clustering reich & kapeliuk (2005), loebbecke & huyskens (2007), lamptey et al. (2008) c5 optimization technique lee & park (2005), nie et al. (2008), shang et al. (2008), azadivar et al. (2009), delorme et al. (2009) c6 learning technique power & sharda (2007), ranjan (2008), li et al. (2009), zhan et al. (2009) c7 import data from other systems ozbayrak & bell (2003), alter (2004), shang et al. (2008), quinn (2009) c8 export reports to other systems ozbayrak & bell (2003), shi et al. (2007), shang et al. (2008) c9 simulation models power & sharda (2007), shang et al. (2008), quinn (2009), zhan et al. (2009) c10 risk simulation evers (2008), galasso & thierry (2008) c11 financial analysis tools santhanam & guimaraes (1995), raggad (1997), gao & xu (2009) c12 visual graphs noori & salimi (2005), kwon et al. (2007), power & sharda (2007), li et al. (2008), azadivar et al. (2009) c13 summarization bolloju et al. (2002), hemsley-brown (2005), power & sharda (2007), power (2008) c14 evolutionary prototyping model fazlollahi & vahidov (2001), bolloju et al. (2002), gao & xu (2009), zhang et al. (2009) c15 dynamic model prototyping koutsoukis et al. (2000), bolloju et al. (2002), goul & corral (2007), gonzález et al. (2008), pitty et al. (2008) c16 forward and backward reasoning gottschalk (2006), evers (2008), zhang et al. (2009) 44 c17 knowledge reasoning ozbayrak & bell (2003), plessis & toit (2006), evers (2008) c18 alarming and warning power (2008), ross et al. (2009), zhang et al. (2009) c19 recommender/ dashboard nemati et al. (2002), hedgebeth (2007), bose (2009) c20 combination of experiments courtney (2001), nemati et al. (2002), gottschalk (2006), gonnet et al. (2007), ross et al. (2009), hewettet al. (2009) c21 situation awareness modeling raggad (1997), plessis & toit (2006), feng et al. (2009) c22 environmental awareness phillips-wren et al. (2004), koo et al. (2008), güngörsen et al. (2008) c23 fuzzy decision metaxiotis et al. (2003), zack (2007), makropoulos et al. (2008), wadhwa et al. (2009), yu et al. (2009) c24 olap (online analysis processing tool) tan et al. (2003), lau et al. (2004), rivest et al. (2005), shi et al. (2007), berzal et al. (2008), lee et al. (2009) c25 data mining techniques bolloju et al. (2002), shi et al. (2007), berzal et al. (2008), cheng et al. (2009) c26 data warehouses tan et al. (2003), tseng & chou (2006), march & hevner (2007), nguyen et al. (2007) c27 web channel tan et al. (2003), oppong et al. (2005), anderson et al. (2007), power (2008) c28 mobile channel power (2008), wen et al. (2008), cheng et al. (2009) c29 e-mail channel granebring & re’vay (2007), baars & kemper (2008), wen et al. (2008) c30 intelligent agent gao & xu (2009), lee et al. (2009), yu et al. (2009) c31 multi agent bui & lee (1999), xu & wang (2002), granebring & re’vay (2007) c32 multi-criteria decisionmaking tools hung et al. (2007), yang (2008), marinoni et al. (2009), tanseliç & yurdakul (2009) c33 stakeholders’ satisfaction goodhuea et al. (2000), lönnqvist & pirttimäki (2006), evers (2008), gonzález et al. (2008) c34 accuracy and reliability of analysis gregg et al. (2002), lönnqvist & pirttimäki (2006), phillips-wren et al. (2007), zack (2007),gonzález et al. (2008), power (2008) step 1: after determining the fuzzy decision-making matrix, the difference between each of the two alternatives is calculated as d, in the form of a pair. these numbers are calculated by subtraction relation, shown in table 1. step 2: in this phase, the amount of p(d) is obtained through eq. 10 with regard to the preference function used in the article. step 3: in this phase, the decision-making team is asked to determine the weight of each criterion by using lr fuzzy numbers. then, by normalizing the weight of each criterion through eq.12, which is in the form of fuzzy numbers, the definite weight of each criterion is obtained. (12) 𝑊i = 𝑎i 𝑎i j i=& step 4: after determining the values of p3 and definite weights, the overall preference indexes should be calculated through eq.13. in this method, j = 1,2,…,m indicates the criteria. (13) 𝜋 𝑎,𝑏 = 𝑝i 𝑎,𝑏 .𝑤i j i=& table 3 linguistic values and fuzzy numbers. linguistic value fuzzy number very low (0 , 0, 0.2) low (0, 0.2, 0.2) medium (0.4, 0.2, 0.2) high (0.6, 0.2, 0.2) very high (0.8, 0.2, 0.2) excellent (1, 0.2, 0) step 5: in this phase, the leaving flow (∅@) and entering flow (∅b) for each alternative are calculated with regard to the amounts obtained in step 4 and by using eq.14 and eq.15. in these, a is a set of alternatives and n is the number of alternatives. (14) ∅@ a = 1 n − 1 × π a,x c∈e (15) ∅b a = 1 n − 1 × π x,a c∈e for example, in the problem under examination, leaving flow and entering flow values for es1 are calculated as follows: ∅@ = 𝜋 es1,es2 + 𝜋 es1,es3 + 𝜋 es1,es4 + 𝜋 es1,es5 4 ∅b = 𝜋 𝐸𝑆2,𝐸𝑆1 + 𝜋 𝐸𝑆3,𝐸𝑆1 + 𝜋 𝐸𝑆4,𝐸𝑆1 + 𝜋 𝐸𝑆5,𝐸𝑆1 4 45 step 6: the leaving flow and entering flow values cannot rank the alternatives completely. therefore, another concept named the net flow value is introduced, which is an instrument for ranking all alternatives. this value is obtained through eq.16. (16) ∅ 𝑎 = ∅@ 𝑎 − ∅b 𝑎 step 7: in this phase, through eq.11, we can change net flow values that are fuzzy numbers into definite numbers and rank the enterprise systems with regard to the results. in table 5, the leaving and entering flow values of all five enterprise systems are shown in columns 1 and 2. the fuzzy net flow values and their definite equivalence values for different alternatives are described in columns 3 and 4. indifference threshold is considered to be zero for all alternatives and the total preference threshold is set to 0.9. regarding the net flow values of five alternatives, the final ranking of the enterprise systems is: es4, es2, es5, es1 and es3 respectively. the evaluation of the obtained results shows that the suggested method has a good performance in determining the best enterprise system. 4. conclusion a correct evaluation of enterprise systems is important for organizations' managers. bi evaluation tools and models used as a decision support system in enterprise systems can help managers to make the right choice and decisions. therefore, in the present paper a model is presented to evaluate and rank the enterprise systems using bi and it is tested through a case study. the suggested model uses the fuzzy promethee method for evaluation and ranking, based on the promethee method as one of the best methods of multi-criteria decision-making. table 4 fuzzy decision matrix. alternatives criteria es5 es4 es3 es2 es1 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 c1 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 c2 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 c3 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 ,0.2) ,0.2 (0.2 c4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0 (0 ,0.2) ,0.2 (0.6 c5 ,0.2) ,0 (0 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 ,0.2) ,0.2 (0.4 c6 ,0.2) ,0 (0 ,0) ,0.2 (1 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 ,0.2) ,0.2 (0.8 c7 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.6 c8 ,0.2) ,0.2 (0.6 ,0.2) ,0 (0 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 c9 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 c10 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 ,0.2) ,0.2 (0.4 c11 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 ,0) ,0.2 (1 c12 ,0) ,0.2 (1 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 c13 ,0.2) ,0 (0 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 ,0.2) ,0.2 (0.8 c14 ,0.2) ,0 (0 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 ,0.2) ,0.2 (0.2 c15 ,0.2) ,0 (0 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.2 c16 ,0.2) ,0 (0 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 c17 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.6 c18 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 ,0.2) ,0.2 (0.8 c19 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 c20 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 ,0.2) ,0 (0 ,0.2) ,0.2 (0.2 c21 ,0.2) ,0 (0 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0 (0 c22 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0 (0 c23 ,0.2) ,0.2 (0.4 ,0) ,0.2 (1 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.6 c24 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 c25 ,0.2) ,0.2 (0.6 ,0) ,0.2 (1 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.8 c26 ,0.2) ,0.2 (0.8 ,0) ,0.2 (1 ,0) ,0.2 (1 ,0.2) ,0.2 (0.8 ,0) ,0.2 (1 c27 ,0) ,0.2 (1 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 c28 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 c29 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.6 ,0.2) ,0 (0 c30 ,0.2) ,0.2 (0.4 ,0.2) ,0 (0 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0 (0 c31 ,0.2) ,0.2 (0.8 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.6 c32 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 c33 ,0.2) ,0.2 (0.6 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.4 ,0.2) ,0.2 (0.2 ,0.2) ,0.2 (0.6 c34 46 table 5 ranking with promethee. alt. = alternative, d∅ = defuzzied ∅, r = rank r d ∅ ∅+xy ∅b ∅@ alt. 4 -0.0209 ,0.121) ,0.100 (-0.026 ,0.043) ,0.075 (0.085 ,0.046) ,0.057 (0.596 es1 2 0.0174 ,0.125) ,0.132 (0.019 ,0.035) ,0.050 (0.054 ,0.075) ,0.097 (0.074 es2 5 -0.0367 ,0.122) ,0.125 (-0.033 ,0.081) ,0.100 (0.080 ,0.022) ,0.044 (0.046 es3 1 0.0586 ,0.115) ,0.130 (0.062 ,0.029) ,0.046 (0.050 ,0.069) ,0.100 (0.112 es4 3 -0.0204 ,0.133) ,0.129 (-0.021 ,0.065) ,0.092 (0.097 ,0.041) ,0.064 (0.076 es5 in order to remove the problems and ambiguities that result from changing the observations to definite variables; fuzzy numbers are used in the calculations of the promethee method. here, 34 criteria were examined to evaluate the enterprise systems identified by reviewing the literature. to improve and develop the present 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(2019) business intelligence using the fuzzy-kano model. journal of intelligence studies in business. 9 (2) 43-58. article url: https://ojs.hh.se/index.php/jisib/article/view/408 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index business intelligence using the fuzzy-kano model soumaya lamrharia*, hamid elghazib, abdellatif el fakera aensias, mohammed v university rabat, morocco, bnational institute of posts and telecommunications rabat, morocco *soumaya_lamrhari@um5.ac.ma journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: making sense of the collective intelligence field: a review collective intelligence process to interpret weak signals and early warnings fernando c. de almeida and humbert lesca pp. 19-29 study on the various intellectual property management strategies used and implemented by ict firms for business intelligence journal of intelligence studies in business v ol 9 , n o 2 , 2 0 1 9 j ou rn a l of in telligen ce s tu d ies in b u sin ess issn: 2001-015x vol. 9, no. 2 2019 klaus solberg søilen pp. 6-18 shabib-ahmed shaikh pp. 30-42 and tarun kumar singhal a new corpus-based convolutional neural network for big data text analytics wedjdane nahili, khaled rezeg pp. 59-71 and okba kazar business intelligence using the fuzzy-kano model soumaya lamrhari , hamid elghazi pp. 43-58 and abdellatif el faker using open data and google search data for competitive intelligence analysis jan černý, martin potančok pp. 72-81 and zdeněk molnár the potential of business intelligence tools for expert finding mehdi dadkhah, mohammad lagzian, pp. 82-95 fariborz rahim-nia and khalil kimiafar business intelligence using the fuzzy-kano model soumaya lamrharia*, hamid elghazib and abdellatif el fakera aensias, mohammed v university rabat, morocco bnational institute of posts and telecommunications rabat, morocco corresponding author (*): soumaya_lamrhari@um5.ac.ma received 25 september 2019 accepted 24 october 2019 abstract today, understanding customer satisfaction is becoming a difficult and complex task for companies due to the explosive growth of the voice of the customer in online reviews. this has pushed companies to rethink their business strategies and resort to business intelligence techniques in order to help them in analyzing customer requirements and market trends. this paper proposes a decision support framework for dynamically transforming the voice of the customer data into actionable insight. the framework measures the customer satisfaction by extracting key products’ aspects along with customers’ sentiments from online reviews using a text mining technique: the latent dirichlet allocation approach. we apply the fuzzy-kano model to classify the real customer requirements, then, map them dynamically to the swot matrix. the proposed approach is extensively tested on an empirical dataset based on several performance metrics including accuracy, precision, recall, and f-score. the reported results showed that latent dirichlet allocation approach has correctly extracted aspects with 97.4% accuracy and 92.4 % precision. keywords business intelligence, customer satisfaction, decision support framework, fuzzy-kano model, latent dirichlet allocation, online reviews, text mining, voice of the customer, web intelligence “the secret of successful retailing is to give your customers what they want.” sam walton 1. introduction in today’s competitive marketplace, business leaders have realized that customers are the major driving force leading a company to thrive (carulli et al., 2013) (lee et al., 2014). in fact, most of the product-based companies require an in-depth understanding of their customers’ satisfaction. thus, they resort to business intelligence (bi) techniques in order to provide competitive products that meet the customer needs and go in line with the current market trend (sabanovic and søilen, 2012). the voice of the customer (voc) is a widely used term in market research that describes the customers’ feedback about their expectations and experiences in relation to products and services. this is considered an essential first step in developing a successful product or service (aguwa et al., 2012). the voc is usually captured in a variety of ways such as questionnaire surveys, face to face interviews, telephone interviews, and discussion groups (goodman, 2014) (rese et al., 2015). however, most of these methods are demanding in terms of time, cost, and their geographic reach (szolnoki and hoffmann, 2013). additionally, the participants’ willingness to provide actual input can impact the collected data quality (reyes, 2016). besides, the surveys are generally conducted occasionally, which makes journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 43-58 open access: freely available at: https://ojs.hh.se/ 44 the timeliness of the gathered data questionable (culotta and cutler, 2016). consequently, we need to consider other alternative data sources to reveal customer expectations. the growing popularity of social media and bi in the last decade makes them a valuable digital channel for listening and capturing customers’ voices (gioti et al., 2018). unlike conventional approaches, the voc on social media is publicly available, easily accessible anywhere and anytime at low cost. examples of these vocs include customer posts, comments, and reviews. customer reviews can be considered a trustworthy voc since they hold massive data where customers voluntarily share their experiences about a specific product or service after use or purchase. unfortunately, these reviews may not explicitly reflect customer needs since they require more advanced data analysis methods. therefore, most companies have adopted bi techniques (nyblom et al., 2012), such as text mining, to discover hidden patterns in this large amount of textual data to support the decision making process (søilen et al., 2017) (xu and li, 2016) (jia, 2018). plenty of studies have been conducted to explicitly or implicitly understand customer satisfaction from online review content. for instance, decker and trusov (2010) applied an econometric framework based on poisson regression, binomial regression, and latent class poisson regression models. the basic potential of using those classification algorithms is to estimate the relative strength of effects resulting from the list of attributes identified through customer reviews about mobile phones. the methodology findings reveal that the negative binomial regression approach provides significant estimation parameters, which quantify the effects that the product attributes have on overall customer satisfaction. park and lee (2011) proposed a systematic framework for extracting customer requirements from an online customer center and transforming them into product specifications data. in their approach, customer opinions are collected, then a text mining analysis is conducted on customer complaints to extract meaningful keywords. based on the extracted vocs, customers are clustered into different groups with similar needs. then, the target groups will be carefully selected by the companies. further, a co-word and a decision tree analysis are used to translate the customer requirements into product specifications. xiao et al. (2016) established a novel econometric preference measurement model for extracting overall customers’ preferences from online product reviews. the model allows a semi-automatic extraction of product features along with the related reviewers’ sentiments. then, aggregate customer preferences are extracted from online product reviews by a modified ordered choice model, which considers the variety of customers’ ratings and allows them to assign rating sores with their own thresholds. furthermore, the identified customer requirements are classified into different categories, e.g. basic, performance, excitement, innovation-needed, reverse and divergent, by using a marginal effect-based kano model, which is an extension of the classical kano model that employs the marginal effect information disclosed by the proposed modified ordered choice model. in addition, other research studies have applied an aspect-based sentiment analysis approach for understanding customers’ satisfaction. this approach involves extracting aspects and finding their corresponding sentiments. latent dirichlet allocation (lda) is considered a state-of-the-art modeling tool for extracting products’ features in the aspectbased sentiment analysis (saura et al., 2019). for instance, farhadloo et al. (2016) proposed a bayesian approach that models the customer satisfaction based on the individual aspect ratings. first, the study utilizes the aspectbased sentiment analysis method described in (farhadloo and rolland, 2013) as a basis to transform unstructured input data into semistructured data. then, the bayesian method enables the extraction of the relative importance of each aspect of the product or service. for consumer-generated content in marketing, tirunillai and tellis (2014) proposed a unified framework that extracts the key latent quality dimensions (known as a “topic” in the lda literature) of consumer satisfaction and the associated sentiments using unsupervised bayesian learning algorithm based lda. moreover, the approach determines the validity, importance, dynamics, and heterogeneity of the extracted dimensions. in another context, guo et al. (2017) put forward an lda based approach to identify the most important dimensions of customer service in the hotel sector. then, they performed a perceptual mapping to represent the key dimensions influencing the visitors’ satisfaction and the visitors’ perceived ratings 45 in different hotel classification. qi et al. (2016) proposed an automatic filtering model to mine customers’ requirements from online reviews. first, it filters out the reviews that are helpful for product improvement. then, a lexiconbased sentiment analysis, lda, and page rank are used to rank the terms based on their frequencies and semantic relationships. in addition, the conjoint analysis and the kano model are utilized to determine the product attribute weights and categories and evaluate their impact on customer satisfaction. despite the contributions made by the aforementioned studies regarding the understanding of customer satisfaction from online reviews, they still have some drawbacks. first, in (decker and trusov, 2010), (farhadloo et al., 2016), (qi et al., 2016), (xiao et al., 2016); (park and lee, 2011), the authors quantified the effects that customer requirements may have on their satisfaction by using various modeling methods that measure product attributes, e.g. weights and importance. while in (guo et al., 2017), (tirunillai and tellis, 2014), the authors focused only on mining the relevant products’ attributes. second, most of the existing studies that have measured the effects of customer requirements on customer satisfaction have not classified the identified requirements either from the customer or the provider perspectives. third, our approach bears a close resemblance to the one proposed by qi et al. (2016), except that in our study, we have incorporated the fuzzy analysis to the kano model instead of the conjoint analysis. with fuzzy analysis, the measurement of each product’s attribute is presented in the form of the degree of membership allowing the customers to express their preferences towards multi-attributes at the same time, unlike the conjoint analysis where the customers can only express their preferences for a single attribute. based on the results reported in (tirunillai and tellis, 2014), (qi et al., 2016), (guo et al., 2017), lda has demonstrated good stability and satisfactory performance in terms of accurately extracting the key customer requirements from a large volume of online reviews. therefore, we have selected it as a topic modeling method in our approach. to the best of our knowledge, this is the first attempt to combine lda, the fuzzy-kano model and the swot method into one decision support framework for understanding customer satisfaction. specifically, we will analyze the collected voc from online reviews, then, extract the actual customers’ requirements that have more impact on their experiences with a given product or service. such a framework is beneficial for companies since it allows them to deeply understand the customers’ needs and proactively adapt their product/service or even their business model accordingly. it is composed of four major modules. the first one consists of collecting and preprocessing data from online customer reviews. the second one extracts the products’ aspects and the corresponding customers’ sentiments from the preprocessed data using lda. the third module classifies the real customer needs that affect their satisfaction based on the fuzzykano model. the fourth module maps the fuzzy-kano model’s output to a swot matrix in order to easily interpret the obtained results. the proposed approach is extensively evaluated using an empirical dataset, which includes mobile phone reviews collected from amazon. the evaluation is based on several performance metrics including accuracy, precision, recall, and f-score. the remainder of this paper is organized as follows. section ii provides the theoretical background of the proposed framework. section iii describes our methodology. in section iv, we evaluate the effectiveness of our method using a real case study. in section v, we draw some conclusions and shed light on further research directions. 2. theoretical background 2.1 latent dirichlet allocation (lda) in this paper, we seek a way to map customers’ reviews to the topics, without having prior knowledge on what those topics are. this calls into question the unsupervised classification problem on natural language. lda is an unsupervised topic modeling approach widely applied in natural language processing. the present study deployed lda (blei, 2012) instead of other topic model approaches found in the literature because it relies on more comprehensive probabilistic assumptions on the text generation and has shown satisfactory performance and good stability when classifying large data sets (lu et al., 2011) (alghamdi and alfalqi, 2015) (hofmann, 2017). in lda, each document consists of a mixture of topics and each topic consists of a collection of words. given a corpus 𝐷 consisting of 𝑀 documents each of length 𝑁, each document contains a sequence of 𝑊 words, each of these words represents the 𝑣&' word in a vocabulary 46 of 𝑉 distinct terms and 𝐾 is the total number of topics. thus: • 𝛼 and 𝛽 define the prior distribution parameters per-document topic distribution and per-topic word distribution respectively. • 𝜃. is the topic distribution for document 𝑚. • 𝜑1 is the word distribution for topic 𝑘. • 𝑧4. is the topic for the 𝑛&' word in document 𝑚. • and 𝑤.4 is the specific word formally, lda generates a corpus 𝐷 of 𝑀 documents according to the following generative process: • choose a topic distribution 𝜃7 ~ 𝐷𝑖𝑟(𝛼), where 𝑖 ∈ {1,…. ,𝑀}, and 𝐷𝑖𝑟(𝛼) is a dirichlet distribution with scaling parameter α which typically is sparse (𝛼 < 1). • for each topic 𝑘 ∈ {1,…. ,𝐾}, choose 𝜑1 ~ 𝐷𝑖𝑟(𝛽), where 𝛽 is typically sparse. • for each of the word positions 𝑖, 𝑗 , where 𝑗 ∈ {1,…. ,𝑁7} , and 𝑖 ∈ {1,…. ,𝑀}: o choose a topic 𝑧7,f ~ 𝑀𝑢𝑙𝑡𝑖𝑛𝑜𝑚𝑖𝑎𝑙( 𝜃7). o choose a word 𝑤7,f ~ 𝑀𝑢𝑙𝑡𝑖𝑛𝑜𝑚𝑖𝑎𝑙(𝜑lm,n). moreover, a graphical model can also mirror the generative process of documents. as depicted in figure 1, the boxes refer to repeated contents where the number of repetitions is presented by the variable at the corner of the corresponding box. the blue node represents the only observed variable (𝑤). the white nodes denote latent variables (𝜑, 𝜃); gray nodes represent hyperparameters (𝛼 and 𝛽). the arrows indicate dependencies among the model parameters. practically, the model must determine the hidden variables from the data, namely the document-topic distribution 𝜃, and the topicword distribution 𝜑. to this end, the gibbs sampling algorithm (darling, 2011) is applied to estimate those two lda parameters. 2.2 kano model the kano model (kano, 1984) is an effective tool used by companies to integrate the voc into the product and service development lifecycle. it is regarded as a nonlinear relationship between product quality and customer satisfaction. it measures customer sentiments to discover which customer requirements have the highest impact on customer satisfaction (tontini et al., 2013). the kano model often carries out surveys and questionnaire investigations on customers to determine the requirements of a particular product or service. for a given product’s aspect, a functional question (aspect’s presence) and a dysfunctional question (aspect’s absence) are asked. each question form should be answered on a five-point scale such as: like, necessary, neutral, unnecessary, and dislike. based on a statistical analysis of all the accumulated responses of the survey, each answer pair is aligned with the kano evaluation (table 1), forming certain requirements (ullah and tamaki, 2011). table 1 shows that by combining the two answers (functional and dysfunctional), the product’s aspects can be classified into six categories of requirement that influence customer satisfaction, including: • “must-be” (m) requirement is expected by the customers, its presence does not lead to customer satisfaction, but its absence leads to extreme customer dissatisfaction. table 1 the standard kano evaluation (ullah and tamaki, 2011). nec = necessary; neu = neutral; unnec = unnecessary; dis = dislike. dysfunctional like nec. neu unnec dis f u n ct io n al like q a a a o nec r i i i m neu r i i i m unnec r i i i m dis r r r r q figure 1 the graphical representation of the lda model, redrawn from (blei, 2012) 47 • “one-dimensional” (o) requirement is the property of a customer need that increases customer satisfaction when it is fulfilled. inversely, customer satisfaction decreases when it is not fulfilled. • “attractive” (a) requirement is usually uncommon or unexpected by the customers, if included, can truly increase customer satisfaction; if not, there is no feeling of dissatisfaction. • “indifferent” (i) requirements are those that the customer does not care about whether they exist or not. that is, these attributes will cause neither the satisfaction nor the dissatisfaction of customers, but that does not mean they do not impact the company's production decisions. • “reverse” (r) requirements are those whose presence results in dissatisfaction since not all customers are alike. in other words, what makes one customer satisfied might probably alienate another. • and the “questionable” (q) requirement, which occurs when the customer selects an unclear answer from both functional and dysfunctional sides. in addition, the kano questionnaires and surveys allow the users to select only a single option from a set of options. that makes them unable to express their uncertainty toward certain aspects by selecting more than one choice. to address the issue of uncertainty concerning people’s satisfaction as well as the vagueness of human thought, our study combines the classical kano model with the fuzzy analysis to obtain an equivalent fuzzykano model that classifies the customers’ requirements based on fuzzy logic rather than binary logic (lee and huang, 2009). the fuzzykano model allows customers to express multifeeling, with the help of the different kano categories, by giving fuzzy satisfactory values to certain aspects. this fuzzy set of values is represented by variable membership degrees ranging from 0 to 1, reflecting the uncertainty, where the sum of elements is equal to 1. furthermore, this approach automates the building of the kano model. it incorporates the vocs into the fuzzy-kano model through lda to obtain much larger scale data with more reliable insights since the classical kano model, when used alone, cannot directly handle such data. 3. methodology the proposed framework is composed of four modules as illustrated in figure 2: (1) data extraction and preprocessing; (2) aspectsentiment pairs extraction using lda; (3) requirements classification based on the fuzzy-kano model; and (4) decision-making analysis driven by fuzzy-kano and swot. in this section, we describe each of these modules. 3.1 data extraction and preprocessing the first module consists of gathering online customer reviews as the material for analysis and saving them in the form of a table in which each review denotes a document. generally, reviews contain emoticons, special characters, punctuation, html tags, capital letters and misspelled words. so, it is necessary to apply a figure 2 the proposed decision support framework. 48 set of operations to each review before moving to the next module. these preprocessing operations include: tokenization: is the act of breaking up a sequence of textual content into words, phrases, and symbols called tokens. these tokens are used as input data for further processing. stop word removal: is the process of filtering out irrelevant words and characters from data, such as prepositions and pronouns. part-of-speech tagging (post): is applied to assign a special label to each token (word) in a text such as a noun, verb, or adjective. filtering tokens: is used to filter out all words where the length is out of the range [2-25 characters]. transforming cases: consists of converting all tokens into lowercase. stemming: is applied to discard affixes from each word to obtain their root form. additionally, some reviews can be wrapped in a specific electronic file format, such as html, xml or json, which sometimes requires transformation into another format so as to be easily processed by the next modules. after performing the aforementioned preprocessing operations, a set of valid words is generated by excluding all meaningless words from the token list. thus, a document-term matrix is produced, which indicates terms and their occurrence frequencies in each document. 3.2 aspect-sentiment pairs extraction using lda in this module, we begin by implementing lda to reveal all topics being discussed by customers in the reviews. for this, we compute the probability of each word in the review as written in equation 1: 𝑝(𝑤|𝑅) = s𝑝(𝑤|𝑇) u 7vw × 𝑝(𝑇|𝑅7) (1) where 𝑝(𝑤|𝑇) is the probability of a word 𝑤 given a topic 𝑇 and 𝑝(𝑇|𝑅7) is the probability of a topic 𝑇 given a review 𝑅7, with 𝐾 is the total number of reviews in the overall collection. then, we extract aspects and sentiments that appear together in the same topic distribution according to the pos tagging process. words describing sentiments are mainly represented by adjectives and adverbs, meanwhile, a product aspect is mainly represented by nouns or noun phrases (hu and liu, 2004a), but not all nouns refer to aspects. therefore, we select first the most representative nouns as aspect candidates according to their co-occurrence frequencies in the review, as well as their appearance with sentiment words. to identify sentiment word orientation, the wordnet (miller, 1995) is used as well as the opinion lexicon provided in (hu and liu, 2004b), when the sentiment words are not supported by wordnet. next, we use the popular approach of hu and liu (2004b) to construct aspect-sentiment pairs, which is based on extracting nearby adjectives to a frequent aspect. practically, we define a nearby adjective as the nearest opinion word to a specific aspect considering token distance (measured in the number of words far away from that aspect). the maximum number of the nearest sentiment words is set at two for the simple reason that usually when a third word is found, it was certainly describing another aspect that was ignored during processing. by doing so, we prevent the incorrect attribution of a sentiment word to an aspect. moreover, we consider that once a sentiment word is assigned to an aspect, it will not be considered in the future attribution. to compute the final sentiment score for an aspect (positive or negative), we sum up all sentiment word scores related to that aspect as follows: 𝐴7.𝑠𝑠 = s 𝑆𝑊f.𝑠𝑠 𝑑𝑖𝑠𝑡(𝑆𝑊f,𝐴7)f (2) where 𝐴7.𝑠𝑠 is the sentiment score of an aspect 𝐴7, 𝑆𝑊f.𝑠𝑠 is the polarity score {−1,1} given to the 𝑗&' sentiment word according to the opinion lexicon, and 𝑑𝑖𝑠𝑡(𝑆𝑊f,𝐴7) is the distance between the aspect 𝐴7 and the identified sentiment word 𝑆𝑊f. this allows us to identify the opinion words with the highest weight, i.e. the nearest opinion word to the aspect. 49 3.3 requirements classification based on fuzzy-kano model in this module, we use the aspect-sentiment pairs generated previously in combination with the fuzzy-kano model to classify the real customer requirements that affect customer satisfaction. in the document collection, each comment is written by a customer, 𝑐, to express a sentiment, 𝑠, toward several aspects 𝑎𝑠𝑝 of an item, 𝑖. by using the quadruplet {𝑠, 𝑖,𝑎𝑠𝑝,𝑐}, we form the matrix of aspect and sentiment distribution, denoted as 𝐴 = (𝑎7f)w`f`a w`7`b . for instance, in equation 3, rows represent aspects and columns denote items. the matrix entries represent the customer’s sentiment 𝑐ba toward the aspect 𝑝 of the item 𝑞. we assign +1 to a positive attitude, -1 to a negative attitude, and 0 to a neutral attitude or no opinion expressed. then, we construct for each aspect a set of ndimensional vector distributions. for example, the first row in the matrix indicates that for aspect 1, the customer marks a negative attitude for item 1, neutral or no feeling toward item 2, and a positive attitude for item 𝑞. thus, each row in the matrix constitutes a customer’s sentiment vector corresponding to that aspect. 𝐴 = d −1 0 ⋯ 1 0 1 ⋯ 0 ⋮ ⋮ ⋱ ⋮ −1 −1 ⋯ 1 i (3) to apply the fuzzy-kano, first we calculate for each aspect the customer’s degree of preference when the aspect has a functional presence and the customer’s degree of dislike when the aspect has a dysfunctional absence or insufficiency. probability gives real knowledge when the customer feelings are ambiguous or uncertain. so, we calculate such degrees as probabilities of preference and dislike. they are represented, respectively, in equations 4 and 5: 𝑝𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒(𝑐,𝐴𝑠𝑝7) = 𝑁m 𝑝 × 𝑞 × 𝑆7 n 𝑆7 (4) 𝑑𝑖𝑠𝑙𝑖𝑘𝑒(𝑐,𝐴𝑠𝑝7) = 𝑁m 𝑝 × 𝑞 × 𝑆7 p 𝑆7 (5) where 𝑝𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒(𝑐,𝐴𝑠𝑝7) and 𝑑𝑖𝑠𝑙𝑖𝑘𝑒(𝑐,𝐴𝑠𝑝7) represent the probabilities that customer, 𝑐, has a positive or negative sentiment, respectively, for aspect 𝐴𝑠𝑝7 for a specific item, 𝑁m denotes the number of sentiments either positive or negative expressed by a customer, 𝑐, toward some aspects, 𝑝 × 𝑞 refers to the dimension of aspectsentiment matrix, 𝑆7n and 𝑆7p represent the number of positive and negative sentiments given by 𝑐 for aspect 𝐴𝑠𝑝7 respectively, and 𝑆7 is the total number of sentiment attitudes expressed by several customers for the aspect 𝐴𝑠𝑝7. second, each of the obtained preference and dislike values refers to a fuzzy set, which contains elements that have varying degrees of membership in the set. these degrees correspond to the five kano’s standard answers (‘like’, ‘necessary’, ‘neutral’, ‘unnecessary’, and ‘dislike’). they are determined using the membership functions where each element of the fuzzy set is mapped to a value ranging from 0 to 1. in particular, we employ in this paper the triangular membership function because of its simplicity in determining the input parameter values, namely the 𝑝𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 and 𝑑𝑖𝑠𝑙𝑖𝑘𝑒 in our case (umoh and isong, 2013). according to the triangular membership method, the five kano’s standard answers are represented as five triangular fuzzy numbers between 0r and 1r, as follows: • dislike: (0,0,0.25) 𝜇t(𝑥) = v 0.25 − 𝑥 0 ≤ 𝑥 ≤ 0.25 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 • unnecessary: (0,0.25,0.5) 𝜇t(𝑥) = y 𝑥 0 ≤ 𝑥 ≤ 0.25 0.5 − 𝑥 0 ≤ 𝑥 ≤ 0.5 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 • neutral: (0.25,0.5,0.75) 𝜇t(𝑥) = y 𝑥 − 0.25 0.25 ≤ 𝑥 ≤ 0.5 0.75 − 𝑥 0.5 ≤ 𝑥 ≤ 0.75 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 • necessary: (0.5,0.75,1) 𝜇t(𝑥) = y 𝑥 − 0.5 0.5 ≤ 𝑥 ≤ 0.75 1 − 𝑥 0.75 ≤ 𝑥 ≤ 1 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 • like: (0.75,1,1) 𝜇t(𝑥) = v 𝑥 − 0.75 0.75 ≤ 𝑥 ≤ 1 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 where 𝑥 is the fuzzy set represented by the degree of preference/dislike, and 𝜇t(𝑥) is its triangular membership function. figure 3 illustrates the graphic presentation of the triangular membership function. the closer the value of preference/dislike degree to a kano’s standard 50 answers, the higher the membership degree to it. for instance, while a 𝑝𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 value is located between 0 and 0.25, namely 𝛽, the membership degrees to “dislike” and “unnecessary” are 𝛼wand 𝛼{ respectively. in table 2, we illustrate an example of a customer’s membership degrees of preference and dislike for aspect 1 in topic 0. using table 2 only, it is difficult to determine the proper classification of the customer requirements. therefore, the customer’s membership degrees of preference and dislike can be transformed into two five-vector representations, namely 𝑃𝑟𝑒 = {0.75,0.21,0.04,0,0} and 𝐷𝑖𝑠 = {0,0,0,0.91,0.09} as defined in (lee and huang, 2009). then, using a matrix multiplication 𝑃𝑟𝑒~ ⨂𝐷𝑖𝑠, a 5 × 5 kano’s twodimensional fuzzy relation matrix ‘𝑀𝑆’ is obtained as: 𝑀𝑆 = 𝑃𝑟𝑒~ ⨂ 𝐷𝑖𝑠 = ⎣ ⎢ ⎢ ⎢ ⎡ 0 0 0 0.68 0.06 0 0 0 0.19 0.01 0 0 0 0.03 0.003 0 0 0 0 0 0 0 0 0 0 ⎦ ⎥ ⎥ ⎥ ⎤ (6) relative to table 1 stated in the literature, the customer requirements can also be written as a two-dimensional 5 × 5 matrix ‘𝑀𝐸’ as: 𝑀𝐸 = ⎣ ⎢ ⎢ ⎢ ⎡ 𝑄 𝐴 𝐴 𝐴 𝑂 𝑅 𝐼 𝐼 𝐼 𝑀 𝑅 𝐼 𝐼 𝐼 𝑀 𝑅 𝐼 𝐼 𝐼 𝑀 𝑅 𝑅 𝑅 𝑅 𝑄⎦ ⎥ ⎥ ⎥ ⎤ (7) after ‘ms’ being obtained, we sum the values of the ‘ms’ matrix entries with each other if they belong to the same cell in the evaluation matrix ‘me’. as a result, the classification of the customer requirements can be acquired as follows: 𝑅 = � 0.68 𝐴 , 0.013 𝑀 , 0.06 𝑂 , 0.22 𝐼 , 0 𝑅 , 0 𝑄 � (8) as mentioned earlier, the kano model’s classification of requirements is qualitative and judged to be ineffective in the quantitative evaluation of customer satisfaction. therefore, berger et al. (1993) proposed customer satisfaction coefficients to provide quantitative values of satisfaction and dissatisfaction in case of fulfillment or non-fulfillment of a customer requirement, as given in equations 9 and 10: 𝐶𝑆7 n = 𝐴7 + 𝑂7 𝐴7 + 𝑂7 + 𝑀7 + 𝐼7 (9) 𝐶𝐷7 p = − 𝑂7 + 𝑀7 𝐴7 + 𝑂7 + 𝑀7 + 𝐼7 (10) table 2 an example of a customer’s membership degree to kano’s standard answers for aspect 1 in topic 0. s = standard answers; m = membership degrees; nec = necessary; neu = neutral; unnec = unnecessary; dis = dislike. s m like nec neu unnec dis preference 75% 21% 4% dislike 91% 9% figure 3 the triangular membership function of the degree of preference/dislike to the kano standard answers. 51 where 𝐶𝑆7nand 𝐶𝐷7p are respectively the customer satisfaction and dissatisfaction coefficients of the 𝑖&' customer requirements, and 𝐴7,𝑂7,𝑀7 and 𝐼7 represent the probability distributions obtained according to the kano’s evaluation for the requirement 𝑖. reverse and questionable requirements were ignored. note that the minus sign in equation 10 emphasizes the negative impact on customer satisfaction, which will be decreased if these (onedimensional and must-be) requirements are not included. on the other hand, the value of 𝐶𝑆7 n is usually positive, indicating that customer satisfaction will be increased by providing these (attractive and onedimensional) requirements. a positive satisfaction coefficient ranges from 0 to 1, while a negative satisfaction coefficient runs from 0 to -1. a value of zero implies no impact on customer satisfaction whether the requirement is met or not. the closer 𝐶𝑆7n is to 1, the higher the influence of meeting the requirement is on the customer satisfaction, and the closer 𝐶𝐷7p is to -1, the greater the influence of not meeting the requirement is on the customer dissatisfaction. in this way, all evaluated requirements can be represented graphically through a scatterplot, which is divided into four quadrants according to the satisfaction coefficient values. the xaxis is for 𝐶𝑆n and the y-axis is for 𝐶𝐷p. each customer requirement could be assigned to different quadrants of the scatterplot based on the kano requirements. as shown in figure 4, the first quadrant stands for the onedimensional requirements, the second quadrant stands for the attractive requirements, the third quadrant stands for the indifferent requirements and the fourth quadrant stands for the must-be requirements. therefore, in designing new products/services, priority should be given to the higher 𝐶𝑆n and the lower 𝐶𝐷p i.e. attractive requirements, and when improving an existing product/service, more focus should be given to the high 𝐶𝑆n value and the high 𝐶𝐷pvalue, i.e. onedimensional requirements. this rule guides the decision-maker’s team of a company when deciding on which customer requirement has more impact on the company’s quality production process. 3.4 decision making analysis driven by fuzzy-kano and swot in this module, we propose a bi-layered matrix that maps the fuzzy-kano outputs into the swot matrix in order to interpret the requirements from the customer and the provider perspectives, as shown in figure 5. the upper matrix lists the requirements from the customer’s perspective. its horizontal axis represents the fulfillment level of a requirement deducted from the customer satisfaction and dissatisfaction coefficients previously calculated, while the other axis refers to the fuzzy-kano requirement’s classification. the upper matrix results are mapped into the swot matrix (lower matrix). swot is used as an analysis tool to provide insights about products by identifying their strengths and weaknesses (i.e. internal factors) along with potential opportunities and threats (i.e. external factors) (phadermrod et al., 2019). as can be seen from figure 5, the upper matrix includes six zones ranging from (a) to (f). zone (a) contains unfulfilled must-be requirements. the product’s provider needs to fulfill these requirements in order to guarantee the minimum quality of the product. zone (b) includes fulfilled must-be requirements which figure 4 the kano requirements classification according to customer satisfaction coefficients. figure 5 the kano and swot bi-layered matrix. 52 means that the product already retains a minimum of quality. zone (c) includes unfulfilled one-dimensional requirements. the product’s provider should invest more in improving these requirements in order to avoid customer dissatisfaction and increase customer satisfaction. zone (e) contains unfulfilled attractive requirements. even though these requirements will not cause the customer dissatisfaction since they are not expected by the customers, they create a product with a novel attractive aspect that can achieve unexpectedly positive effects. zones (d) and (f) hold fulfilled/one-dimensional and fulfilled/attractive requirements, respectively. the product’s provider does not need to modify the product since those requirements are already at a high level of satisfaction. however, if they make more effective improvements, this can dramatically raise customer satisfaction. the improvements to be made in both zones are different. in (f), improvements are more innovative, while in (d) they are more realistic. in the lower matrix, the aforementioned zones are mapped to the swot matrix. zones (a) and (c) include unfulfilled/must-be and unfulfilled/one-dimensional requirements which can be regarded as a weakness of the product or even a potential threat for the provider. therefore, zones (a) and (c) can be put in the w-t cell. zone (e) holds unfulfilled attractive requirements that can be interpreted differently depending on the studied case. they can be considered as weaknesses that the product’s provider can minimize by improving further the product quality and turn those weaknesses into an opportunity. in this case, zone (e) can be put in the w-o cell. on the other hand, those requirements can be considered strengths if the provider includes them in the product and they were not expected by the customers. however, if these requirements do not meet the customers’ expectations, then they can become a potential threat. in this case, zone (e) can be put in the s-t cell. zones (b), (d), and (f) respectively include the fulfilled/must-be, fulfilled/one-dimensional, and fulfilled/ attractive requirements that can be considered strengths since they can be easily fulfilled. in addition, adding new features to the product can be an opportunity to create a new market related to these features. thus, these zones are put in the s-o cell. note that the indifferent requirements are not considered in the bi-layered matrix, simply because they are of little or no consequence to the customer. so, the provider can ignore them to save time, cost, and resources. 4. experiments and results in this section, we conduct a case study to evaluate the effectiveness and feasibility of the proposed framework using online mobile phone reviews collected from amazon. in the following, we describe our dataset and show potential results. 4.1 dataset 4.1.1 preprocessing in order to evaluate the effectiveness and feasibility of the proposed framework, the first phase consists of collecting and preprocessing the required dataset. in this paper, a dataset of unlocked mobile phone reviews has been selected. this dataset was acquired from amazon using (“promptcloud”). it includes 400,000 mobile phone reviews, containing product and customer information, ratings and plaintext reviews. in this study, we conducted the experiments on a subsample of the original dataset, which contains approximately 2000 reviews. table 3 partial demonstration of experimental dataset. review price rating i feel so lucky to have found this used (phone to us & not used hard at all), phone on line from someone who upgraded and sold this one. my son liked his old one that finally fell apart after 2.5+ yea... 199.99 5.0 it’s battery life is great. it’s very responsive to touch. the only issue is that sometimes the screen goes black and you have to press the top button several times to get the screen to reilluminate. 199.99 3.0 table 3 illustrates some samples from the dataset. each single review includes a considerable amount of unnecessary data, which must be cleaned to reduce noisy data and extract insightful information such as aspects and sentiments. the preprocessing operations applied in this work include tokenization, stop word removal, transform cases, stemming, and non-alphanumeric character removal. all the preprocessing operations were conducted using the python nltk toolkit (version 3.7). in addition, we grouped synonyms to reduce dimensionality by using a manually entered list including the most common synonyms e.g. the words “cellphone”, “smartphone”, “phones” are all transformed into “phone”. negation 53 handling is quite important in this study, it assists in improving sentiment analysis accuracy. therefore, we used the simplest approach proposed in (das et al., 2001), which is based on appending a negation tag “_neg” to every word found between a negation and the first punctuation mark following it, so as to reverse the polarity of all these words while computing their scores. misspelling is also taken into consideration since the reviews are usually hand-typed. some predefined functions from the “autocorrect package” are used to deal with misspellings. the pos tagging is used to find adjectives that are considered sentiment words, as well as products’ aspects where nouns (nn) and noun phrases (nnp) are considered potential aspect candidates. table 4 setting values for running lda. parameter settings values number of documents (𝑀) 1593 number of topics (𝐾) 20 number of iterations 50 𝛼 = 1/𝐾 1/20 𝛽 = 1/𝐾 1/20 table 5 list of aspects along with their sentiment polarity and scores for topic id = 5. aspect(s) polarity sentiment score battery safety -1 -0.72 booting time -1 -0.14 price 1 0.53 speakers quality 1 0.83 battery life -1 -0.57 shipping 1 0.33 screen size -1 -0.92 internet speed -1 -0.10 weight 1 0.69 camera resolution 1 0.86 moreover, we applied certain filtering operations, such as: excluding reviews without an adjective pos tag, since sentiments are mainly identified from adjectives; pruning words that are not recognized by the opinion lexicon or wordnet; and keeping reviews in which an aspect appeared at least once. in the end, the final list was made up of 1763 reviews, which was split into 1593 reviews intended for training and 170 reviews for testing. the testing reviews were chosen randomly, and a new column was added, including aspects and the relative sentiments’ polarity. 4.1.2 extracting topics and constructing aspectsentiment pairs before proceeding with the lda application, we prepared the data for phrase modeling, which consisted of grouping common words that often get a special meaning when they are used together. that is, we built bi-gram phrases from the reviews. then, using the “gensim” library, we built our lda model over the parameters cited in table 4. the number of topics 𝐾 was set at 20 to avoid producing a general result with a lack of details. moreover, a larger number of topics may take longer to converge. for the other parameters, gensim default values were used. through the lda model, we obtained the first output, namely, the word-topic matrix. it included 20 meaningful topics each represented as a weighted list of words in descending order. figure 6 indicates the first four topics with the top 20 most frequent words. topics were inspected by a specific index. instead, topic names can be defined manually by inferring topics from relevant words’ meanings. for instance, looking at topic 1 keywords, we can summarize it to “phone screen and battery performance”. the second output generated by lda was the documentfigure 6 list of top 20 keywords for the first four topics. 54 topic matrix. an example of topic allocation to the five first documents (reviews) is illustrated in figure 7. by extracting numerous aspects that customers are reviewing and their corresponding sentiments along with the accumulated sentiment scores calculated using equation 2, we gain insights into what negatively or positively impacts product reviews, as well as what the customers like or dislike about the product. table 5 shows a partial list of such aspects along with their polarity classes and sentiment scores grouping by topic id 5. 4.2 evaluation and results 4.2.1 results of the extracting aspect-sentiment pairs to evaluate how the extracting aspectsentiment pairs approach performed, two set of experiments were conducted: (i) measure the effectiveness of the aspects extraction and (ii) measure the effectiveness of the sentiments assignment to the corrected aspects extracted. in this regard, four performance metrics were used: accuracy (acc), precision (p), recall (r), and f1-score (f1). accuracy means how often our model is correct but when used alone, it cannot be trusted to select a well-performing model. therefore, we used the three other metrics to give more detailed insights into the performance characteristics of our method. precision refers to the percentage of the relevant data. a higher precision indicates more true positives and less false positives. on the other hand, recall expresses the proportion of all relevant results correctly classified by our model. high recall means less false negatives and high true positives. according to the confusion matrix notations (ting, 2017), the accuracy, precision, and recall are computed respectively by the following equations: 𝐴𝑐𝑐 = 𝑇𝑃 + 𝑇𝑁 𝑇𝑃 + 𝑇𝑁 + 𝐹𝑃 + 𝐹𝑁 (11) 𝑃 = 𝑇𝑃 𝑇𝑃 + 𝐹𝑃 (12) 𝑅 = 𝑇𝑃 𝑇𝑃 + 𝐹𝑁 (13) where tp is true positives, tn is true negatives, fp is false positives, fn is false negatives. the f1-score combines precision and recall and gives an overall view of the accuracy of the approach. the f1-score is given by: 𝐹w = 2 ∗ 𝑃 × 𝑅 𝑃 + 𝑅 (14) in the experiment set (i), tps refer to the correctly extracted aspects. tns are the aspects that were discarded by the model and did not appear in the test data either. fps are words that the model classified as aspects but are not actually aspects. fns are the aspects that the model labeled as not being aspects when they were actually aspects. in the experiment set (ii), tps refer to the aspects correctly classified with positive scores. fps are the aspects incorrectly classified with positive scores. fns are the aspects incorrectly classified with negative scores. table 6 performance results. acc = accuracy; pre = precision. experiments set acc. pre recall f1score (i) aspects extraction 97.4% 92.4 % 84.5% 88.27% (ii) sentiments assignment 89,8% 90.7% 94.7% 92.6% table 6 depicts the accuracy, precision, recall, and f1-score of the proposed aspectsentiment pairs approach in the experiments set (i) and (ii). as one can see, in (i), the model reports a high precision value (92.4%) meaning that most of the actual aspects are correctly classified with low fp values. the recall rate is 84.5%, suggesting that the most returned aspects are correctly labeled with low fn values. the f1-score is relatively high, meaning that the model represents insightful document 1 document 2 document 3 document 4 document 5 0 20% 40% 60% 80% 100% p ro ba bi lit y topic 0 topic 9 topic 11 topic 15 topic 19 figure 7 topic distribution for the first 5 documents. 55 results in terms of extracting the most discussed aspects of specific products. in (ii), the results are significantly different than the first experiment set. in particular, the f1-score is 92.6%, which indicates that assigning correct sentiments’ polarity performs fairly well compared to the aspects’ extraction, which reports 88.27%. these results suggest that the extraction of aspect-sentiment pairs performs efficiently in identifying accurate aspects and assigning appropriate sentiments to them. this will help in feeding the fuzzy-kano model with accurate inputs, consequently providing valuable business insights. 4.2.2 results of the fuzzy-kano model the fuzzy-kano model classified the ten aspects previously extracted into must-be, onedimensional, attractive, and indifferent requirements by calculating their degrees of preference and dislike. table 7 highlights the findings of the assessed requirements’ classification along with their impact on customer satisfaction. according to the customer satisfaction coefficient (cs+/cd-) reported in table 7, we can represent all the classified requirements via a scatterplot, as shown in figure 8. table 7 fuzzy-kano classification and customer satisfaction coefficients results. r.no. = requirement number; a. req. = assessed requirements; kano class = kano classification. r. no. a. req. kano class cs+ cd r0 battery safety must-be 0.29 -0.83 r1 booting time onedimensional 0.78 -0.62 r2 price indifferent 0.06 -0.05 r3 speakers quality onedimensional 0.54 -0.58 r4 battery life must-be 0.46 -0.89 r5 shipping indifferent 0.42 -0.12 r6 screen size attractive 0.83 -0.36 r7 internet speed onedimensional 0.60 -0.70 r8 weight attractive 0.57 -0.32 r9 camera resolution attractive 0.71 -0.49 from figure 8 and table 7, the findings indicate that all the must-be requirements are battery-related, namely, r0 and r4 since they have a higher level of dissatisfaction among the customers compared to other requirements. furthermore, r1, r3, and r7 are all onedimensional requirements, which implies that customers expect the companies to improve the performance of this product requirement. on the other hand, the attractive requirements such as r6 and r9 have a greater impact on satisfaction if fulfilled while r8 has a relatively lower impact on customer satisfaction when compared to r1. the indifferent attributes, r2 and r5 reflect a low impact on customer satisfaction and dissatisfaction, thus, they should be the last to be focused on over the three other requirements. 4.2.3 fuzzy-kano and swot mapping and analysis results in this section, the identified requirements are mapped to the bi-layered matrix. first, they are classified according to the fuzzy-kano model from the customer’s perspective, then, classified according to the swot method from the provider’s perspective. the results of the mapping are shown in figure 9. considering the aforementioned results and the analysis reported in the fourth module of our proposed framework, r0 and r4 must be fulfilled to guarantee the minimum quality of the product and meet the customers’ requirements. these requirements are headed to w-t, which motivate the provider to improve the battery performance, including safety and durability. in addition, internet speed (r7) is considered w-o from the provider’s perspective. therefore, further enhancements of r7 will not only lead to increased customer satisfaction but also decrease its dissatisfaction. requirements in the zones (d) figure 8 the representation of the fuzzy-kano classification results according to cs+ and cd-. 56 and (f) such as booting time (r1), loudspeaker quality (r3), and weight (r8) are included in so, which means that those requirements are easy to fulfill, and when the provider makes more improvements on them, this will lead to a higher level of customer satisfaction than the current level. the requirements in zone (e) are related to s-t. even though (r9) and (r6) are not expected by the customers, the provider should be able to assess the customers’ preferences and overcome the current threat by adding a new value to the product, e.g. improve the camera resolution. 5. conclusion a good understanding of customer satisfaction is important for the survival of any company in today’s competitive market. no business can deny the critical role of the customers’ voices in increasing customer satisfaction. however, drawing insights from a huge amount of voc data is challenging. thus, companies resort to bi methods and tools to extract actionable information for improving their products and meeting their customers’ needs. this study proposes a decision-making framework for assisting companies in understanding their customers’ satisfaction through extracting meaningful insights from online voc data. the proposed framework consists of four main modules: data extraction and preprocessing, aspect-sentiment pairs extraction using lda, requirement classification based on the fuzzy-kano model, and decision-making analysis driven by fuzzykano and swot. a case study including online reviews of mobile phones is considered to evaluate the performance of the aspect-sentiment pair extraction module based on several metrics including the accuracy, precision, recall, and fscore. the results showed that the aspects were correctly extracted with a value of 97.4% in accuracy and 92.4 % in precision. additionally, the sentiments were accurately assigned to the extracted aspects with a value of 89.8% and a precision value of 90.7%. these results constitute an accurate voc input to feed the fuzzy-kano model. they allow us to classify the customer requirements that affect their satisfaction into four main categories: must-be, one-dimensional, attractive, and indifferent. then, we can map them dynamically to the swot matrix in order to provide valuable and interpretable insights for companies. this framework has some potential limitations that serve as a direction for future work. first, the study is conducted on online reviews which are assumed to be hand-typed and written by honest reviewers (i.e. not fake). however, if these reviews have been maliciously manipulated, they may impact the analysis process and result in biased decisions. an efficient spam review detection technique would be needed to identify whether the reviews are real or fake. in addition, the aspect-sentiment pairs extraction module deals only with the explicit aspects but does not tackle the implicit ones. for example, in the following 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(2019) effect of competitive intelligence on innovation capability: an exploratory study in mexican companies. journal of intelligence studies in business. 9 (3) 62-67. article url: https://ojs.hh.se/index.php/jisib/article/view/478 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index effect of competitive intelligence on innovation capability: an exploratory study in mexican companies eduardo rafael poblano-ojinagaa*, roberto romero lópeza, jesús andrés hernández gómeza, and vianey torres-arguellesa atecnológico nacional de méxico, instituto tecnológico de la laguna, mexico; *pooe_65@hotmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: empirical evidence from a connectivist competitive intelligence massive open online course (ci cmooc) proof of concept competitive intelligence as a game changer for africa’s competitiveness in the global economy alexander maune pp. 24-38 integration of textual voc into a cx data model for business intelligence use in b2c lucie sperkova pp. 39-55 how competitive intelligence can be used to improve a management vocational high school: a case from indonesia verry ronny pailingan and pp. 56-61 johan reimon batmetan v ol9,n o 3,2019 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 9,no.3,2019 gianita bleoju, alexandru capatina,valter pp. 7-23 vairinhos, rozalia nistor, and nicolas lesca effect of competitive intelligence on innovation capability: an exploratory study in mexican companie eduardo rafael poblano-ojinaga, roberto pp. 62-67 romero lópez, jesús andrés hernández gómez, and vianey torres-arguelles effect of competitive intelligence on innovation capability: an exploratory study in mexican companies eduardo rafael poblano-ojinagaa*, roberto romero lópeza, jesús andrés hernández gómeza, and vianey torres-arguellesa atecnológico nacional de méxico, instituto tecnológico de la laguna, mexico *corresponding author: pooe_65@hotmail.com received 25 november 2019 accepted 30 december 2019 abstract market globalization and fast technological change drive organizations to apply information management systems that allow them to analyze information and convert it into intelligence. because of this, companies need to manage information for decision making. this process is complex, beginning at the level of the company's strategy, and reaching all the way to manufacturing strategy, with the creation, development and deployment of the technological capabilities needed for quick and flexible responses to customers and market situations and their changes. the information can be gathered and managed through several models, mainly, competitive intelligence, knowledge management and intellectual capital. this article presents an investigation using a methodology of structural equation modeling for the identification of the intelligence factors, to evaluate their relative importance and relationships with the innovation capability of mexican companies. the empirical results show that the relationship between competitive intelligence and the innovation capability is indirect, with knowledge management as a mediating factor. keywords competitive intelligence, innovation capability, structural equations modelling 1. introduction in our highly competitive business environments, companies need ways to manage information for decision making purposes. this is a difficult management function. deciding the needs, type and specific information can be a hazardous problem, as is the design and characteristics of the information management system required, so useful and timely information is available for the determination and management of the technological capabilities and competences for the delivery of the right goods. this information has several sources and can be obtained by typical functions of competitive intelligence, knowledge management and intellectual capital, which are briefly discussed in the following paragraphs. competitive intelligence (ci) is defined as a systematic effort aimed at specific objectives, ethical and in a timely manner, to collect, synthesize and analyse relevant information on competition, markets and the external environment, with the purpose of producing actionable information that can provide a competitive advantage (fleisher, 2009; rodríguez & chávez, 2011; prescott & miller, 2002). knowledge management (km) is of great interest in areas of business administration, industrial engineering and communication because it focuses on the organization, acquisition, storage and use of knowledge to achieve objectives such as problem solving, dynamic learning, strategic planning and decision making (hammed 2004, cited by herschel and jones, 2005). the journal of intelligence studies in business vol. 9, no. 3 (2019) pp. 62-67 open access: freely available at: https://ojs.hh.se/ 63 interest related to the set of intangible assets, such as knowledge, held by a company known as intellectual capital (ic) has aroused similar interest. also worth noting is that knowledge is an important source of competitive advantage (shujahat et al., 2017; rodríguez gómez, 2006; prusak, 1997), therefore, the identification of the most important factors for the effective management of the three information sources (ci, km & ic) has the utmost importance. although these theories manage information and knowledge, the relationship between them and innovation capability is not clear in the literature. 2. methodology this investigation is managed by a three-step process. first, a literature review made a list of the factors of ci, km, the ic and innovation capability. with the list of factors, a questionnaire was constructed, tested and evaluated. the internal reliability was also estimated. in step two, an initial exploratory analysis gave outlier values using the mahalanobis distance method. following that was a kaiser-meyer-olkin test for sample fit and a bartlett’s sphericity test of the correlations. this determined if they were adequate for the modelling process. step three, was the structural equations modelling process, beginning with the model specification, followed by the identification and the estimation, the test of the model and the lomax & schumacker (2012) modification. statistical analyses are done with minitab v. 17, spss v. 22, and amos v. 22. for the purpose of this study, structural equations modelling (sem) is utilized because it is useful for the analysis of the relationships between the observed variables (items) and the latent variables (factors). sem uses a confirmatory approach for the analysis of the theory related to some phenomena (byrne, 2010). it is increasingly used because researches are aware of the need to use multiple constructs or observed variables to explain the phenomena in question, investigating more advanced and complex theoretical models. the software is also spreading and getting friendlier (lomax & schumacker, 2012). sem has been applied in several fields is the search for predictors of effectiveness in mexico. for instance, in total productive maintenance (hernández et al., 2018), organizational philosophy, (davila et al., 2017), and in single minute exchange of dies (romero et al., 2011). 3. results in the first step, with the critical success factors obtained from the literature review, we constructed a questionnaire with a five category likert scale, in which 1 represents a “non-important” level and the highest, 5, means “extremely important”. it is applied to a sample size of 40 participants who possess the attributes to be measured from the target population. this sample size ranges from 30 to 40, as recommended by hertzog (2008). the type of sampling is for convenience (malhorta, 2008), and the information gathered was determined by the questionnaire for internal consistency with the cronbach alpha coefficient. a cronbach alpha of 0.965 indicates the questionnaire reliability is good, accordingly to tavakol & dennick, (2011). then, the questionnaire was given to 214 engineers from 32 automotive and electronics transnational companies. a sample size of more than 200 is recommended by lloret et al. (2014). in the second step, the initial scan analysis indicated that data were missing in 35 questionnaires. this was followed by the identification of outliers in the remaining 178 questionnaires. this was done using the mahalanobis distance method, using minitab v. 17. given the points on the reference line, y = 6.387, there are 29 outliers that will be eliminated (figure 1). next we performed a kaiser-meyer-olkin fit test and a bartlett's sphericity test of the correlation between the variables and the adequacy of the sample for the factor the analysis gave. the former was 0.930, indicating small partial correlations, which was precisely measured as a common factor. in the barter’s test, the chi-square = 2918.587, fd = 325, & a p-value = 0.000 means that the correlations matrix is not an identity matrix, figure 1 outliers data chart. 64 indicating there is a high correlation, which is acceptable according to levy et al. (2003). finally, the factor correlations and the factor loads were determined using the main axes method to extract the factors, and the promax method for its rotation. the factor loads for all items exceeded the recommended level of 0.60 (hair et al., 1998). this was followed by calculations of the composite reliability, convergent validity and discriminant validity. the composite reliability (cr) values are in the range of 0.87 to 0.92, exceeding the recommended level of 0.70. the average variances extracted (ave) are in the range of 0.59 to 0.64, exceeding the recommended level of 0.5 (hair et al., 1998). the discriminant validity was examined and results of the analysis show that the square correlations for each construct are smaller than the average variance extracted (matzler & renzl, 2006). these results indicate that the measured items have good reliability and validity. in step three, we established relationships between the variables of the theoretical model, according to the theory being scrutinized. this was required to specify the model, meaning that to determine the best model capable of producing the sample covariance matrix, we must find the one that presents the theory under construction. now we have the second order hypothetical factorial model (figure 2), giving four latent variables and 26 observed variables. then, the model is identified. in this process, all the parameters have to be specified as free, restricted or fixed. then the parameters are combined to construct the implicit variance-covariance matrix of the model, to determine the differences between the real model by the data gathered and the implicit theoretical model. once the model and the parameters are specified, they are combined in the σ variancecovariance matrix implicit of the model. a free parameter is unknown, but needs to be specified. a fixed parameter has a specific value in the range [0,1] and a restricted one, also is unknown but is equal to one or more parameters (lomax & schumacker, 2012). because the number of values estimated (s = 171) is bigger than the number of free parameters (42), the model is identified and the free parameters can be estimated. the estimation of the model gives the estimation of all the parameters. the regression weights and structure coefficients of the hypothetical model are significant as 𝛼 =0.05 is lower than the p-value. calculations were made with amos v.22 with the method of maximum likelihood, which is adequate for normally distributed data, as well as ordinal and moderately non-normal data. the test of the model indicates the degree at which the variance-covariance data of the sample fit the structural equations model. for this purpose, several fit indexes are calculated, among them, chi-square = 522.176, p-value = 0.000, and cmin/df = 1.782, which is smaller than the value recommended of 3. agfi = 0.77, which is less than 0.80; the comparative adjustment index, cfi = 0.94, is bigger than 0.9, as recommended by chau & hu (2001). the figure 2 hypothesized confirmatory factorial model. 65 root mean square error aprox. (rmsea) is 0.073, which is lower than the limit 0.08 proposed by browne & cudeck (1993). the estimated adjustment indexes combined indicate a good adjustment of the data to the model. due to this there was no modification of the model. 4. conclusions in the hypothesized structural model, four factors are identified with six structural coefficients, assuming that each of the estimations is an effect between the latent variables. we have the four hypotheses (h2, h4, h5 and h6) with significant structural coefficients (figure 3). these empirical results support the acceptance of the hypotheses: h2: competitive intelligence influences knowledge management h4: knowledge management influences intellectual capital h5: intellectual capital influences innovative capability h6: knowledge management influences innovative capability that is, ci has a positive effect on km; intellectual capital has a positive effect on ic, and km has a positive effect on both intellectual capital and ic. the results are consistent with studies that analyze the relationship of km with intellectual capital (serenko et al., 2010; diez et al., 2010; kianto et al., 2014); and intellectual capital with ic (santos-rodrigues, 2011; wang & chen, 2013; sivalogathasan & wu, 2013). however, the results also reflect, for lack of sufficient statistical evidence, that the following hypotheses are rejected: h1: competitive intelligence influences innovation capability h3: competitive intelligence influences intellectual capital in the case of h1, the empirical results coincide with a similar study that concludes ci activities are not yet carried out (formally) in order to improve the innovation capability of (mexican) companies (güemes & rodríguez, 2006). this might be explained by means of the combination of several factors, the fact that ci activities are incipient. recommendations are not acknowledged and followed, therefore, although ci has a direct impact, it is small, but its combination with km enhances the explanations and because the information is more properly managed, increases the impact. on the other hand, when analyzing the results of the indirect effects, a high value is observed of the indirect effect of ci and ic (.667). given the above, although there is no direct effect of ci on ic, there is an effect through km as a mediating factor. these results support the importance of integrating km and ci with the intention of obtaining better results (herschel & jones, 2005; galeano et al., 2008; sharp, 2008; ramirez et al., 2012) and as a source of competitive advantage for companies (rothberg & erickson, 2013; chawinga & chipeta, 2017; shujahat et al., 2017). 5. recommendations the results obtained are valuable, because they could be used to carry out studies to evaluate the effect of ci on the ic of organizations, and even consider the possibility of defining the course of study that evaluated the mediating effect of km between ci with ic. although the main limitation of the study is the sample size, several aspects indicatate the study is still valid. these include: • the internal consistency of the im (cronbach's alpha) and kmo greater than the recommended of .70; • compliance with the cases of convergent validity and discriminant validity; • compliance with the model fit criteria. this paper constitutes evidence that sem is a powerful tool for the determination of total or partial effects, direct or indirect between a measurable variable and a latent variable, as figure 3 hypothesized structural model. 66 in the effects between latent variables or constructs. 6. references bartes, f. 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(2017) an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france. journal of intelligence studies in business. 7 (2) 40-50. article url: https://ojs.hh.se/index.php/jisib/article/view/222 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france sophian gauzelina and hugo bentza agroupe esc troyes, 217 avenue pierre brossolette, 10 000 troyes, france; sophian.gauzelin@get-mail.eu and hugobentz0@gmail.com journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: integration of business intelligence with corporate strategic management patent bibliometrics and its use for technology watch björn jürgens pp. 17-26 why care about competitive intelligence and market intelligence? the case of ericsson and the swedish cellulose company journal of intelligence studies in business v o l 7 , n o 2 , 2 0 1 7 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 7, no. 2 2017 klaus solberg søilen pp. 27-39 an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france sophian gauzelin and hugo bentz pp. 40-50 mouhib alnoukari and abdellatif hanano pp. 5-16 the impact of supply chain management on business intelligence audrey langlois and benjamin chauvel pp. 51-61 an examination of the impact of business intelligence systems on organizational decision making and performance: the case of france sophian gauzelina* and hugo bentza* agroupe esc troyes, 217 avenue pierre brossolette, 10 000 troyes, france *corresponding authors: sophian.gauzelin@get-mail.eu and hugobentz0@gmail.com received 21 march 2017; accepted 15 june 2017 abstract turbulent times are a part of modern-day business, and the way a company handles disruptive events determines its success. various technological tools have been developed to help businesses overcome unforeseen and anticipated events that may impact the business. one such technological tool is business intelligent systems, which help to gather data regarding business operations and environment turning it into information that can be clearly understood. large companies have adopted the use of these big data analytic systems, but most small and medium sized enterprises (smes) lag behind. there is little information on how business intelligence systems impact sme businesses. this study examined the impact of business intelligence systems on organizational decision-making and performance. the study consists of an empirical qualitative research that was carried out with interviews of 200 members of 10 selected smes. the study found out that when bi systems are deployed in smes, they facilitate timely decision making, improves organizational efficiency, enable a company to meet client’s needs appropriately and lead to more satisfied employees. keywords business intelligence systems, competitive advantage, customer satisfaction, employee satisfaction, organization, smes 1. introduction today, businesses face various unforeseen events that normally have a detrimental impact on their progress and performance. business intelligence systems are currently perceived as a solution to such disruptive events that hit the businesses unexpectedly, irrespective of whether it is a large or small business enterprises (fourati-jamoussi & niamba, 2016: jenster & søilen, 2013). business intelligence systems refer to those computerized methods and processes that turn data into information, which is then converted into business knowledge (popovič et al., 2012). these systems offer technological solutions that provide analytical capabilities as well as data integration services that can provide valuable information for business stakeholders. however, assessing the success of business intelligence systems is a problem as they cover entire organizations and their benefits can only be long-term (popovič et al., 2012). additionally, small and medium enterprises (smes) are perceived as laggards when it comes to implementation of technological systems. this is because they lack the financial capacity as well as the required expertise to implement and manage big data systems. on the topic of business intelligence, most researchers have focused on large companies and therefore neglect smes despite bi tools being essential for all businesses. therefore, there is a lack of sufficient information on the impact that bi systems have on smes. this empirical research provides the results of a study that journal of intelligence studies in business vol. 7, no. 2 (2017) pp. 40-50 open access: freely available at: https://ojs.hh.se/ 41 examined the impact of the business intelligence systems in smes by collecting and analyzing data on how organizational members perceive these big data analytical systems. the purpose of the study was to determine whether and how business intelligence systems facilitates timely organizational decision making and other impacts in smes and also to examine how organizational members perceive business intelligence systems. 2. business intelligence and business intelligence systems the term business intelligence (bi) has become increasing popular in the last few decades. according to sabanovic, & søilen, (2012), business intelligence is a multifaceted term that encompasses techniques, processes, and tools that facilitates faster and more effective decision making in business enterprises. this definition agrees well with the definition of popovič et al., (2012) of business intelligence, which is a composition of computerized processes and methods that help to turn data into information then into knowledge that aid in business decision making. business intelligence systems provide essential tools that help in effective reporting and analyzing business information so as to understand the organizational internal and external environments (fourati-jamoussi and niamba, 2016: søilen, 2015). this gives the managers essential data that is used in decision-making processes. a business enterprise can use one or more types of business intelligence systems so as to boost its decision-making processes. there are four major business intelligence systems that are used in a business, namely: reporting, analysis, monitoring, and prediction tools (sabanovic, 2008). the reporting intelligence business systems focus on the development of business documents that contain valuable information on what has happened. these provide the businesses with information about the company activities within a given time span. the intelligence business analysis systems provide information on why an event happened (vesset & mcdonough 2007). this is a crucial part of the business because the provision of data without analysis is useless. the intelligence business analysis systems collect and analyze data before presenting it which makes it easy for business leaders to understand and interpret it. the tools that are commonly used under these types of systems include the following: spread sheet analysis, ad-hoc query, and visualization tools (sabanovic, 2008: sabanovic, & søilen, 2012). the spreadsheet analysis tools analyze data that are contained in spreadsheets and help to evaluate the entire organization or a specific unit of performance. for instance, spreadsheet analysis tools can be used in tracking the number of hours that the employees have worked. the ad-hoc query tool is software that allows companies to develop specific data queries such as the creation of query of the number of items that have been sold within a specific period (vesset & mcdonough, 2007). the visualization tools, on the other hand, are software that accepts raw data and creates visualizations that business leaders can read and understand (negash & gray, 2008). an example is a tool that can create a graph comparing methods by which customers have been contracted within a specific and given time. the third type of business intelligence systems is monitoring tools. this allows businesses to monitor information and data in real time. snapshots can be taken at any time to get reports thatcan assist in timely decision making. tools under this form of business intelligence systems include the following: dashboards, key performance indicators and business performance management (sabanovic, & søilen, 2012). according to eckerson (2010), the dashboard tools provide a central location whereby actionable and useful metrics are contained and represented graphically, making it easy for users. the key performance indicators (kpis), on the other hand, measure the performance of a given specific project within a company, for example, return on investment. the business performance management tools refer to the system that ensures that the organization meets the set performance goals. it is therefore designed to deliver results on whether the performance goals are met or not. lastly, the prediction business tool helps those businesses that are keen on predicting what may happen to their business based on the data that they have on business trends. vesset & mcdonough (2007) note that the prediction business intelligence systems are more complex and therefore most businesses contact third parties to provide the services while others use software that automates the entire processes. these systems are comprised of data mining and predictive modeling tools. the data mining tools work by finding patterns and relations that exist between large data sets and 42 transform them into understandable information for the companies. the predictive modeling tools, on the other hand, uses modeling techniques to predict an outcome of a given event or its probability (vesset & mcdonough 2007). 3. the role of business intelligence systems in organizations business intelligence systems are an important part of organizations as they can be used to determine their performances. from the definition of business intelligence, it is clear they enhance decision-making (sabanovic & søilen, 2012: popovič et al., 2012). according to popovič et al., (2012) business intelligence provides quality information to organizations which are essential in the process of decision making. this is because it equips the knowledge workers with an opportunity to timely access of information, analyze it effectively and intuitively present the right information. such an opportunity enables an organization to make the right decision and take the right action. therefore, business intelligence should be understood as the ability of an entity to think, plan, predict and solve the problem in an innovative manner (popovič et al., 2012). business intelligence emphasizes abstract thinking and innovative ways of solving problems in a timely manner because appropriate actions are taken so as to advance business goals and overcome any looming business disruption event. this is only possible when the right business systems are implemented. apart from helping a business organization in making proper decisions regarding their functions, business intelligence has other benefits. sabanovic, & søilen (2012) argue that business intelligence systems (bis) do not only help in making better and more efficient decisions but also impact the entire organization to improve its return on investment, gain new customers and suppliers and also recruit the best employees and enhance their satisfaction. business intelligence systems bring greater visibility into business by allowing the leaders to have an entire understanding of the company and the environment that it operates in (sabanovic, & søilen, 2012). this is possible because bis lead to the gathering of the information that is used in strategic planning. the strategic plans of an organization touch on different areas that give an organization a competitive advantage. these plans allow a company to target consumers in a better manner, attract top employees, have the best suppliers and as such a return on investment will be realized. these systems are also important in determining the strategic decision of a business. when bis are implemented, misunderstanding the goals of an organization can be avoided. this is vital in ensuring that all organizational members and their actions are going to the same direction (sabanovic, & søilen, 2012). business intelligence can be used to gain competitive intelligence which is vital in shaping the strategy of a company. according to jenster & søilen (2013), competitive intelligence encompasses the following processes: defining, gathering, analysis and distributing information that is used in decision making. the competitive intelligence gathered, therefore, facilitates strategic planning in an organization. thus, a bis leads to the accumulation of competitive intelligence, which is used in making strategic decisions for a given firm. bis also have a role in providing businesses with information for marketing functions. one of the platforms for marketing of a company is through trade shows. søilen (2010) argues that, for the longest time trade shows have been neglected in the arenas of marketing research. they have not been considered to be important parts of market information because marketing strongly focused on customers rather than competitors and other market influencers. however, currently trade shows are becoming important in not only selling company products but also marketing the company and confirming the company presence in the market (søilen, 2010). at trade shows a company meets different customers who provide important marketing information. nevertheless, the knowledge transfers in trade shows occur through face to face communication despite being extensive. the marketing information can be obtained by using bis during these trade shows. this is what can be termed an intelligent gathering of information that can be used in integrated marketing functions. therefore, søilen (2010) affirms that bis can be used in gathering information for use during marketing and related function. lastly, bis have an impact on the performance of a company. the major objective of adopting business intelligence is to enhance the overall performance of a company. however, there are some complications in 43 determining the actual outcome of these business systems. although it is difficult to measure the outcome of any intelligent system that is implemented by a company, the overall outcome can be used to determine its effectiveness (amara, søilen, & vriens, 2012). according to jenster & søilen (2013) bis lead to the collection of competitive intelligence that is used in strategic decision making. this helps to shape the operations of an organization. jenster & søilen (2013) further argue that strategic planning has an impact on company performance. therefore, bis are vital in shaping the overall performance of an organization. 4. business intelligence systems and small and medium enterprises smes have been lagging behind in the adoption of intelligent business systems. they only consider these systems to be effective for large companies which invest highly in technologies. the large organizations have the required resources to install, maintain and hire highly skilled personnel to work on the bis. this is like smes which operate on meager resources. the expensiveness of these technologies renders them economically unfeasible for small-scale businesses (lueg & lu 2013). however, smes can utilize those bis which are not complex and do not require high levels of expertise to manage. one of the economically feasible bis for smes is the spreadsheets for simple data. according to lueg & lu (2013), smes can use spreadsheets to store data and for financial analysis. the spreadsheets offer applications such as cell modeling and holistic spreadsheet modeling that help to gain important information. bis are important tools in the management of the clients in smes. søilen (2012) who carried out research on small business enterprises in sweden found that smes use bis to manage clients and also consolidate information in an easy and quick way. therefore, bis are important tools for smes because they help them manage their customers. clients form one of the important pillars of smes, and therefore the bis can help businesses to maintain a positive relationship with its customers. further, søilen (2012) notes that these organization’s views on bis depend on how they solve the information needs. additionally, the decision on the intelligence systems to be adopted depends on the experience that a person has had in another company. there is a research gap here in looking at smes outside of sweden and comparing the results. small business can use bis to increase their efficiency in budgeting. the budget is an important document in a small business enterprise because it provides a print on how to balance different goals by maximizing the limited resources that are available. budgeting problems among smes are due to the lack of understanding of the budgeting process, simplicity and also user-friendly it systems. the lack of systems to validate the data used in budgeting also leads to errors in the final budget. the outcome of this is wastage of company resources. according to (lueg & lu, 2013), business intelligence can be used to drive budgeting efficiency. this is because business intelligence increases transparency, user friendliness, and simplicity, which are essential in enhancing data validation and thus driving budgeting efficiency. further, business intelligence can help small businesses in dealing with competition. today, businesses operate in a dynamic environment whereby competition seems to drive all the strategic plans of the business. it is a challenge that smes grapple with on a daily basis. an sme should, therefore, learn to deal and cope with these competition challenges. this can be achieved by turning a small business to be proactive and agile in its decision-making processes. ponis & christou (2013) argue that competitive intelligence adoption is one of the ways in which small business enterprises can deal with competition successfully. this is because competitive intelligence involves a process through which organizations gather information about competitors and use it in decision making and planning process so as to improve its performance. competitive intelligence is part of business intelligence, and therefore it can be of help for a small-scale business enterprise (ponis & christou, 2013). therefore, business intelligence can help smes to achieve a competitive advantage. guarda et al. (2013) affirm this by stating that those small business enterprises which embraced business intelligence have an upper hand in the market as they compete more effectively. this is because they have additional information about their competitors as well as customers. the information that an sme obtains from business intelligence can be used for future strategic planning which can help to avert any looming competition (guarda et al., 2013). 44 lastly, those who claim that bis cannot be applied for smes should reconsider their stance. this is because small businesses are dealing with increased volumes of data and use of business intelligence can help them derive a logical meaning from it. the only factor the smes should consider is making the appropriate choice for the best business intelligence that is in line with their strategy. this will allow the smes to have a competitive advantage. 5. method this study was based on a qualitative descriptive approach. semi-structured interviews were conducted on organizational members of smes to collect data on issues regarding bis (shields & rangarjan, 2013). emerging themes from these interviews are then discussed. the study started by recruiting 200 research participants who were categorized into sme managers and sme junior employees. the participants were drawn from 10 smes located in france. from each sme, 5 managers and 15 junior employees were randomly selected. therefore, the study ended up with 50 sme managers and 150 junior employees. a semi-structured interview (see appendix i and ii) that consisted of questions regarding various aspects of business intelligence was given to each participant. all participants completed the study. the results from the interview were then coded and analyzed, and the emerging themes are discussed as portrayed in the following sections. table 1 a summary of sme managers’ responses on various aspects of bis. bis aspects tested through mangers interviews % yes % no deployment of bis 45 55 usage of bis at all organizational levels 19 81 complexity of the bis deployed 39 61 availability of skilled employees for manage bis 25 75 bis assistance in decision making 89 11 other impacts of bis other than helping in decision making 95 5 perception on continuation of the use of bis 96 4 6. research results this research shows the results of interviews regarding the top management in small business enterprises. tables 1 and 2 and figures 1 and 2 show a summary of sme manager’s responses on several aspects of bi systems and also how junior employees perceived bi systems within smes. table 2 table showing a summary of sme junior employees’ responses to various aspects of business intelligence systems. business intelligence systems aspects tested through junior employee interviews % yes % no usage of bis in the company 15 85 knowledge of bis 20 80 bis impact on employee productivity and performance 70 30 bis impact on business performance 69 31 views on continuation of bis use 85 15 7. analysis 7.1 bis deployment and usage one of the themes that emerged from the results is concerned with bis deployment and usage in smes. from the results that were obtained by interviewing both the junior employees and managers of smes, it is clear that the majority of smes have not deployed bis. among the 50 top management employees who were interviewed, only 45% accepted that their smes had implemented bis. the junior employees, on the other hand, seemed not to be sure on whether the smes they work for have implemented bis or not, as only 15% agreed that they use these systems. further, 19% of the top managers confirmed that they use bi throughout the organizational levels. this shows that smes are yet to fully embraced the deployment and usage of bis. these results agree with lueg & lu (2013) who found that small businesses lag behind when it comes to adoption of bis. according to lueg & lu (2013), the intelligence systems are so expensive for businesses and therefore they are economically unfeasible for smes. the high cost of bis is, therefore, one of the barriers that keeps smes at bay when they try to adopt these tools. this is because smes operate on a tight budget and therefore they believe that investing in bis is tantamount to straining their meager resources. secondly, the lack of 45 proper information technology systems in smes is also a barrier towards the adoption of bis (puklavec, oliveira, & popovic, 2014). olszak, & ziemba (2012), found out that small business enterprises do not have sufficient computer equipment to host bis. this computer equipment is capital intensive, and this is why most of the smes opt not to invest in them as a cost saving strategy. these decisions, therefore, limit the small firms in the opportunities that come with having computer systems. yeboah-boateng and essandoh, (2014) affirm that smes lack appropriate computer system installations and also do not have trust in any business function hosted online for security reasons. some of the business intelligence functions are hosted online through cloud-based services, and therefore the lack of trust and security associated with online services is a major factor that keeps smes from adopting bis. 7.2 bis complexity and availability of skilled bi maintenance personnel the second theme that emerged in this study is the complexity of bis and availability of skilled bis maintenance personnel. among the interviewed managers, a 61% majority agreed that the bis implemented in their small companies are complex and only 39% claimed that they have simple bi tools in their companies. despite the majority confirming that their smes have deployed complex bis, the results show that most of the companies lack the required personnel to manage these systems. according to the results, only 25% of the managers agreed that their companies have skilled employees who can handle bis. the results of the interview conducted on the managers are consistent with those which were carried out by employees. the interview conducted on the employees demonstrates that only 20% of the employees have knowledge of bis. from these results, it is apparent that those smes that have embraced bis use the complex one. according to boonsiritomachai, mcgrath & burgess, (2014) complexity alludes to the extent in which a given innovation is perceived or seen to pose usage or understanding difficulties. complexity remains one of the barriers to the adoption of any innovation or technology. this is because those technologies which are less complex are highly likely to be adopted unlike those that are highly complex: they indeed result in a higherrate of adoption (boonsiritomachai, 2014). the complexity of bis is about the fact that they include mathematical functions that are vital in predicting a particular phenomenon in a firm so as to bring a given solution. it skills are also vital when dealing with bis (boonsiritomachai, mcgrath & burgess, 2014). as portrayed in the interviews, most employees lack knowledge on bis, and this could be affected by the deficit in it skills. figure 1 graph showing the responses of sme managers to the various aspects of business intelligence systems. 46 additionally, employees may have poor mathematical skills, which may make them view bis as complex. further, the lack of resources in smes may be a contributing factor towards the lack of quality personnel to manage bis that are implemented. lueg & lu (2013) argues that smes have limited resources that may even curtail their adoption of bis. therefore, smes fail to attract highly qualified personnel to manage their bis because they lack resources that can be used to pay experts. 7.3 the impact of bis on smes the third theme that emerged in this study was the impact of bis on smes. according to the interview, 89% of the managers accepted that bis facilitate decision making in their companies. one of the business managers said that: “our company, though categorized as a sme has deployed business intelligence systems which provide real-time data. this information is essential because it allows us to make a timely decision. for instance, i remember, there was a time we were registering a low number of sales, but the business intelligence system we use was able to show that our product was pretty expensive and that could perhaps be the reason for the low number of sales. this was real-time information from market intelligence that allowed the company to resolve to adjust the price of the product, which led to improved sales afterward”. translated from french. this form of confession response shows that bis provide important technological tools that enable firms to make decisions based on a reliable knowledge. the market trends remain highly uncertain and competitive and as such provisions of valuable information in a timely manner is of the essence. bis bring efficiency to the businesses because they provide vital information that is used in timely decisionmaking processes. according to wieder & ossimitz, (2015), apart from providing information in a timely manner, bis leads to the generation of quality data. the information generated is of high quality as it is free of errors and highly analyzed: the only job that is left for the business leaders is to interpret the results. therefore, bis are important because they give a business the capability to scan the market and forecast events. the market analysis function of a bis is also important because it allows an organization to identify changing trends and emerging threats in good time so that the appropriate steps can be taken. one of the respondents attested that "in our company, we rely on business intelligent solely for market scanning so as to figure 2 graph showing the responses of smes junior employees on the various aspects of business intelligence (bi) systems. 47 get the most recent changes." this is in line with davenport, (2010) who argues a company needs to constantly be provided with information on consumer behavior and how their preferences are changing. bis, therefore, provide a business with timely and complete information that is vital for decision making (vizgaitytė & rimvydas, 2012). thus, it is apparent that bis are important in helping business leaders to make timely decisions. bis, thus, help front-line employees and company executives make informed decisions. they combine both historical data and real-time data that are available to the business leaders whenever needed. therefore, they empower the business managers to make decisions quickly and with a high level of confidence because the information that is provided is highly reliable. these business analytics do not only generate information based on what happened in the past as they also consider the current situation, and also they incorporate the anticipated changes (davenport, 2010). bis extract data that is full of facts from a large pool of unstructured data and then transform it into meaningful information, which is also actionable. this is vital for making informed decisions in organizations whether large or small. therefore, businesses depend on bis as a rich source of reliable data to make informed and strategic decisions. apart from providing reliable information that is used for timely decision making, bis have other benefits. according to the results of the interview, 95% of the managers agreed that bis brings many benefits other than just timely decision making. one of the manager participants attested that: “business intelligence is not just about timely decision making as it helps the businesses in other ways. for example, in our company, which is an sme, the business intelligence software has been able to provide vital information that has been used to reduce errors in production and therefore allowing the company to realize operational efficiency.” translated from french. therefore, one of the benefits of bis that came out in this study was the increased organizational efficiency and productivity. this is in line with the argument of poleto, carvalho & costa (2015) that informed strategic decisions that are made courtesy of bis are vital in driving operational efficiency as well as business productivity. for instance, bis can analyze customers’ emails and chats with the company and be able to determine the characteristics of such customers as well as their demands. this makes a company strategize as to address customer needs and improve its operations so as to retain its competitive edge and achieve the set goals. therefore, the result shows that bis provides vital and accurate information that is used to inform the company on how to improve its efficiency and productivity as well. further, the results demonstrated that bis had an impact on the return on investments. according to wieder, chamoni, & ossimitz (2012), business intelligence gives companies opportunities to reduce cost, increase their revenues and increase their profit margins. business intelligence has an impact on return on investment because it offers a cost effective method of gathering information regarding the business. traditionally businesses have channelled huge amounts of cash to carry out market research that can gain important information on how to increase a company's efficiency. the business intelligence provides a cost and time-saving strategy of gathering business information. therefore, money that would have otherwise been used to carry out market research will be directed to other important functions of a firm. additionally, the return on investment is impacted by business intelligence because employee productivity is enhanced (wieder, chamoni, & ossimitz, 2012). the interview shows that 70% of the employees agreed that business intelligence helps to foster their performance and productivity at work which in return leads to improved performance in a company. this is affirmed by one of the junior employee participants who said that: “our company has made the use of business intelligence systems a norm in all its operations. at first, when they were implemented we thought the company wanted to tame us, but it was not the case. instead, the managers use it to determine the productivity of each employee. this is vital because the low performing employees are empowered further through training and offered other supportive services to increase their efficiency. the report is also used to guide the managers and supervisors on how to motivate them and increase their performance. i thus find business intelligence systems crucial to my 48 performance and productivity.” translated from french. therefore, from the junior employees’ responses, it is apparent that business intelligence helps to foster employees’ productivity as well as performance. this comes because the reports that are provided by bis are vital in giving company leaders information on how to motivate the employees (wieder, chamoni, & ossimitz, 2012). employee motivation is vital as it leads to the satisfaction that is essential in maintaining the loyalty of the workers. 8. perception of organizational members on the use of bi systems by smes the result of the study indicates that both the managers and junior employees of the smes interviewed are positive about the use of bis in their companies. according to the results of the interviews conducted on the managers, 96% of them accepted that their companies should continue using bis. on the other hand, the interviews that were conducted with junior employees indicate that a majority of 85% accepted that bis use should be continued in the companies they work for. these positive responses could be attributed to the benefits that come with bis. the bi tools have the following advantages to a company whether large or small: improved timely and strategic decision making, increased customer satisfaction and highly motivated and satisfied work force (elbashir, collier & davern, 2008). all these benefits are compounded by the enhanced overall organizational performance. 9. conclusion the result of this study affirms that bis have a far-reaching impact on the operations of smes. first, bis facilitate the process of decisionmaking at the managerial level by providing quality, timely and accurate data. the data generated also consider the past, present and future events and therefore allow business leaders to make informed decisions for the smes. additionally, the impact of deploying bis in smes extends beyond facilitation of decision making, to have an effect on employees, customers and other functions of the firms. this is because they make the operation efficient, allow an organization to meet customer needs appropriately and provide information on how to improve employees’ individual performances through the needed support and motivation. the overall results of all these impacts of bis are improved company performance, as portrayed by the study. these findings are similar to those found about swedish smes, so we can argue for certain universal observations of behavior when it comes to smes. lastly, the improved performance of smes courtesy of bi tools as underscored by this study can be used as a measurement indicator of the outcomes of bis. measurement of the outcomes of bis is one of the challenges that businesses struggle with. however, it is vital in monitoring the performance of an organization (elbashir, collier & davern, 2008). the performance is determined by comparing goals and the outcomes. when determining the performance of bis in smes, it is important to consider the following dimensions: financial, operational and overall effectiveness. according to ramsey & bahia (2013), these dimensions should be determined both subjectively and objectively. this shows that the determinant of the impact of bis should be carried out holistically by determining the overall outcome of the organization, which ranges from financial performance, to the 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(2007). worldwide business intelligence tools 2006 vendor share. idc software market forecaster database, 1. 50 vizgaitytė, g., & rimvydas, s. (2012). business intelligence in the process of decision making: changes and trends. ekonomika, 91. wieder, b., & ossimitz, m. l. (2015). the impact of business intelligence on the quality of decision making–a mediation model. procedia computer science, 64, 1163-1171. wieder, b., chamoni, p., & ossimitz, m. l. (2012). the impact of business intelligence tools on performance: a user satisfaction paradox? international journal of economic sciences and applied research, (3), 7-32. yeboah-boateng, e. o., & essandoh, k. a. (2014). factors influencing the adoption of cloud computing by small and medium enterprises in developing economies. international journal of emerging science and engineering, 2(4), 13-20. appendix i: the interview questions for sme managers a) has your company deployed business intelligent systems? yes/no. b) are the business intelligent systems used at all levels of organizational department? if not which departments use business intelligent systems? yes/no c) are they complex or simple business intelligence systems? yes/no d) do you have skilled employees to run these systems? yes/no e) does the information that is generated by the business intelligence system help in making timely decision making? if yes, how? yes/no/space to explain f) other than helping in prompt decision making are there other impacts of business intelligence systems in your company? if yes, how? yes/no/space to explain g) do you feel the company should continue using business intelligent systems, why? yes/no/space to explain appendix ii: the interview questions for junior organizational members in smes a) does your company use business intelligent systems? yes/no b) are you conversant with the uses of business intelligent tools? yes/no c) do you feel that the business intelligent tools intelligent tools help you to improve your productivity and business performance? if yes, how? yes/no/space to explain d) do you think that the business intelligent systems help to improve overall organizational performance? if yes, how? yes/no/space to explain e) should the company continue using business intelligent systems? if yes, how? yes/no/space to explain vol7no3paper3 alrashdi and nair to cite this article: al rashdi, s.s. and nair s.s.k. (2017) a business intelligence framework for sultan qaboos university: a case study in the middle east. journal of intelligence studies in business. 7 (3) 35-49. article url: https://ojs.hh.se/index.php/jisib/article/view/243 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index a business intelligence framework for sultan qaboos university: a case study in the middle east saud sultan al rashdia and smitha sunil kumaran nairb asultan qaboos university, sultanate of oman; saud.alrashdi@gmail.com; bdepartment of computing, middle east college, coventry university, uk; smitha@mec.edu.om journal of intelligence studies in business please scroll down for article a business intelligence framework for sultan qaboos university: a case study in the middle east saud sultan al rashdia and smitha sunil kumaran nairb asultan qaboos university, sultanate of oman; bdepartment of computing, middle east college, coventry university, uk *corresponding authors: saud.alrashdi@gmail.com and smitha@mec.edu.om received 1 october 2017; accepted 25 october 2017 abstract higher education institutions generate big data, yet they are not exploited to obtain usable information. making sense of data within organizations becomes the key factor for success in maintaining sustainability within the market and gaining competitive advantages. business intelligence and analytics addresses the challenges of data visibility and data integrity that helps to shift the big data to provide deep insights into such data. this research aims to build a customized business intelligence (bi) framework for sultan qaboos university (squ). the research starts with assessing the bi maturity of the educational institutions prior to implementation followed by developing a bi prototype to test bi capabilities of performance management in squ. the prototype has been tested for the key business activity (kba): teaching and learning at one college of the university. the results show that the aggregation of the different kbas and kpis will contribute to the overall squ performance and will provide better visibility of how squ as an organization is functioning, which is the key towards the successful implementation of bi within squ in the future. keywords business intelligence, decision making, key business activity key performance indicator, maturity assessment, performance management 1. introduction the business environment is rapidly changing through different market transitions. these transitions introduce disrupting technologies and new ways of working. at the same time there is a massive growth of data within organizations. making sense of data within organizations becomes the key factor for success in maintaining sustainability within the market and gaining competitive advantages. one of the major trends disrupting business is the evolution of business intelligence and analytics (bia). however, business intelligence (bi) is not new as a concept, it has evolved over the past few years in terms of maturity and sophistication (tapadinhas, 2014) (sarma & prasad, 2014). organizations are facing double challenges when dealing with such trends. from one side, organizations have huge and diverse data sources, yet many of them are not doing much to capitalize on those data and convert them into useful and usable information. from another side, there is a lost opportunity on improving the data integrity and quality for providing better ways for decision makers/stakeholders to make the right decisions. bia is one of the methods that could be used to address the challenges of data visibility and data integrity that will help to shift the existing data from different resources and hence provide deep insights into the data. information management and analytics enable innovation and transformation in how different organizations conduct business. the journal of intelligence studies in business vol. 7, no. 3 (2017) pp. 35-49 open access: freely available at: https://ojs.hh.se/ 36 importance of bia is distilled from the fact that it is important to provide the right information and the right analysis to make the right decisions. the paradox that many organizations face today is how best to optimize their data, yet many of them often limit bi initiatives to focus on technology selection, neglecting the organizational approaches, processes and best practices necessary for success. at first glance, one would think that educational institutions would be a prime area to utilize bi. the reason for such a belief is that educational institutions have a lot of data and often lack visibility to the importance of such an asset. there is often a struggle on how to use the data and how best the huge data coming from different sources could be utilized. if educational institutions want to get a competitive advantage from it, there is a need for these institutions to explore an efficient use of data. bi provides the ability to combine data sources in one place to analyze and improve the decision-making process. the success of the bi implementation journey can enhance productivity and improve efficiency. on the other hand, it creates the impression that every implementation will indeed be unique because no two institutions work in the same way. though bi can be very important, it is still a developing process. the major objective of this research is to develop a bi framework to be used for educational institutions. the study utilizes sultan qaboos university (squ) as a case study to build this framework. furthermore, in order to build the framework, there is a need to understand the maturity level of the university initially. once the maturity level is understood, then the framework can be developed based on the maturity level assessment and the future direction of the university. although this framework will use squ as the main case study, it is assumed that this framework can later be used by other educational institutions within oman (or even outside) to help implementing bi initiatives in their organizations. in addition, the study will also involve building a prototype of how bi can be used as a strategic initiative for squ. 2. literature review looking at the evolution of business analytics, there are other areas where bi can be used. for example, it can be used to model business challenges and for using predictive analysis to generate a future prospective (sherman, 2014). depending on the business challenges and the business maturity, different organizations use bi in different ways. the main difference between the different methods is how efficient the use of data is. since data is the main ingredient of any bi analysis, sherman argues that in order for the bi to provide such benefits, the data has to meet five criteria; it has to be clean, consistent, conformed, current and comprehensive. however, the reality is that not all organizations will have all the above criteria for their data. thus bi implementation within organizations becomes very challenging and prone to failure (shaokunfana, y.k.laub, & leonzhaob, 2015). traditional bi uses olap tools and reporting, which are currently in use today. if such reports exist today, what is so special about using bia? the simple answer can be evolution. however, the initial enthusiasm about bi was generated from e-commerce by companies such as amazon, where consumers’ data is used to anticipate future purchases. in addition, there are other benefits anticipated from bi. one study (ramanigopal, palaniappan, & mani, 2012) lists the number of key benefits that bi can provide; such as: • bi can enhance the time to take action by making it shorter, • bi is used to analyze market trends against the company capabilities and help in making informed decisions, • bi enhances business agility by improving the communications among departments and enables the company to respond quickly to market changes. bi provides comprehensive and flexible access to data (fouche & langit, 2008). in addition, it provides near real-time access to information, making it easier and faster for decision makers to make decisions. although the authors (fouche & langit, 2008) were referring mostly to microsoft bi tools, the same benefits can be achieved by other bi tools from other vendors. at this point, it is important to mention that the value of bi can only be seen when the bi initiative is well integrated within the organization's decision making process (ramanigopal, palaniappan, & mani, 2012). in addition, the choice of technology can also affect the speed of the decision making. the evolution of in-memory computing technologies gave birth to a new breed of what the industry 37 refers to as ‘engineered systems’. these engineered systems provide faster access to the data in near-real time, hence, improving the speed of the decision making (muntean & surcel, 2013). in addition, the importance of bi is very clear from trends in the industry. gartner classified bi as a top priority for cios in the 2015 cio agenda. furthermore, gartner also classified bi as one of the top 4 technologies for cios in the higher education sector making this study very important and relevant to the university. 2.1 business intelligence maturity models the benefits of bi that any organization would like to exploit are presented. nevertheless, in order for organizations to embark on the bi journey, there is a need to assess its current maturity. a business intelligence maturity assessment is required to determine the organization's business needs, its capabilities, and the availability of the information sources (tdwi, 2015) (chuah & wong, 2012). the literature provides several maturity assessment models that can be used to assess an organization's readiness for implementing bi. the business information maturity model is focused on assessing the bi importance within the organization. it assesses the organization's maturity based on three different criteria: alignment and governance, leverage, and delivery (rajterič, 2010). the results of the assessment are then divided into 3 different levels with level 3 representing a mature organization. although this model sounds interesting, it lacks full coverage of the usage of bi and its business value. gartner developed a maturity model for bi and performance management (pm). the model assesses an organization's maturity in five levels: unaware, tactical, focused, strategic, and pervasive (rajterič, 2010). gartner assesses the level of maturity based on three dimensions: people, processes, and metrics and technology. although the gartner model has a good coverage of the different elements of bi within an organization, there is limited literature available on its reliability. furthermore, only gartner (or maybe a special consultancy firm) will be able to help in assessing the maturity level. advanced market research (amr) developed a maturity model for bi (rajterič, 2010). the model consists of 4 stages; reacting, anticipating, collaborating, and orchestrating. amr was acquired by gartner in 2009 although this acquisition doesn't necessarily mean that the maturity model can't be used. however, since gartner has its own maturity model for bi, it is very likely this model will be made redundant. another business intelligence maturity model was developed by mit sloan management. the model comprises of 3 maturity stages; aspiration, experienced and transformed and has 6 evaluation dimensions, namely: motive, functional proficiency, business challenges, key obstacles, data management and analytics in action (gudfinnsson, strand, & brendtsson, 2015). this maturity model for bi was tested with 3000 executives from 108 countries and 30 industries mostly in manufacturing (lavalle, hopkins, lesser, schokely, & kruschwitz, 2010). although this model is well established and tested, it is mostly used to evaluate bi maturity in manufacturing. since this research paper is focused in measuring the bi maturity in educational institutions, this model will not suffice. the data warehouse institute (tdwi) developed a maturity model for bi (tdwi, 2015). although this model is primarily focused on the technical aspects of maturity, it is considered to be more practical in assessing any organization maturity for bi. the model has 5 different assessment dimensions: organization, infrastructure, data management, analytics, and governance. there are 5 stages which the organizations go through in their maturity journey namely: infant, child, teenager, adult, and sage (rajterič, 2010). however, this model was modified later to have different names for the maturity levels. the new model stages are nascent, pre-adoption, early adoption, corporate adoption and mature or visionary (tdwi, 2015). in addition, the model also describes an interesting stage that exists between early adoption and corporate adoption called chasm. the tdwi model describes the chasm as the stage in which the organization must overcome certain obstacles for the transition to the corporate adoption stage. furthermore, these struggles can be overcome through the use of proper funding, good governance, improved skill sets, and better management of change management. 38 due to the tdwi maturity model simplicity, it was decided to use it in this research. furthermore, the tdwi maturity model has developed 35 questions to help organizations assess their maturity level. although the questions are general, there is a need to customize them to suite the educational institutions. 2.2 bi in educational institutions although there are not many articles found in the literature that cover the implementation of bi in educational institution, there are a few that are critically analyzed that have some insight on the use of bi within higher education sectors. one study (guster & brown, 2012) discusses the bi system structure that can assist a strategy map for higher education whether achieved or not achieved. this also focused on the linkage between a strategy map and molap system, which reads from different databases and its article makes use of the strategy map to measure how well the performance is done. in addition, there are some challenges regarding how the information got extracted from different data sources such as in the use of the metrics and fine-tuning the data warehouse to calculate the performance. furthermore, the data modelling took a lot of time and suffered in assessing the data quality. aziz & sarsam (2013) investigate on how a bi system called glis influences the decision making process in uppsala university. the author concludes that glis has a big positive impact on the decision making process in uppsala university. león-barranco et al. (2014) use an analytical model for analyzing decision making in educational institutions. although the study covered only two semesters and the authors have selected specific careers, the developed model seems to help in analyzing the data required for making decisions. randy (2014) carried out a survey on implementing bi in educational institutions and concluded that key performance indicators (kpi) are important for successful implementation of bi in educational institutions. zilli (2014) discusses the self-service usage of bi for students. the author developed dimensional modelling utilizing the excel powerpivot modelling tool. although the impact of bi on relative technical efficiency of higher institutions was not assessed in this research, it provided some evidence that powerpivot can be used as a bi method. the second part of the research focused on undergraduate retention and detection of obstacles to successful graduation. while a selfserving portal will help students, the implementation of the bi and how best to ensure its success could be better covered. rajterič (2010) proposes an overview of bi maturity models detailing the pros and cons of six maturity models. 2.3 bi frameworks the purpose of bi initiatives within many organizations is to create value out of existing data that will provide either improved decision making or give a competitive advantage. hence, bi frameworks are supposed to provide the basic elements of how organizations should identify direction, standards and best practices required to ensure that bi meets organizational requirements. in addition, the framework will guide the development of the implementation roadmap (washer, 2007). in order to develop a bi framework for squ, it is important to understand the different frameworks available for bi in the literature. most of the frameworks available in the literature are either technical (chu, 2013) or specific to develop a bi solution (ortega, avila, & gomez, 2011). therefore, for the purpose of this research it has been decided to shift our review to the available framework in the industry. hence, focus has been on two main frameworks that are widely used gartner's business analytics framework and the business intelligence framework 2020. gartner's business analytics framework: this is based on an approach to integrate people, processes and platforms to create an approach to bia and pm initiatives (tapadinhas, 2014). the framework was established as early as 2006 but gained more momentum recently due to the organization's increased appetite to invest in bi and analytics. the center of the framework focuses on three main pillars: people, processes and platform. the ‘people’ element refers to the human element for producing, consuming or enabling the activities required for successful business analytics. the ‘processes’ element addresses the different processes used within the business. these processes vary to include decision making processes, analytics processes and information governance processes. the final pillar is the platform which is the technology part of bi. there are three capabilities that the technology needs to provide. firstly, decision capabilities that will 39 enable organizations to build applications that help to learn and understand the business. secondly, analytic capabilities, that will develop applications which have predefined data and process workflows, and models for the analysis capabilities. the third capability has to do with information. as organizations create more and more data, the search for such information can be tedious. the solution is to develop an information infrastructure that will unify all these technologies, services and schemas under one umbrella to be used as a source for other capabilities as well. the bottom of the framework represents information which is the most important ingredient in the bi implementation. metadata, program management, and business models, strategy and metrics form different layers of how the center is integrating with the rest of what's going on inside the organization. above all, the true measure of how successful the bi framework is, is the performance it generates for the organization. in other words, bi success should be measured on how well it helps the business achieve its strategic goals. bi framework 2020: it is one of the recent approaches to try to create an ecosystem for implementing bi solutions. in this framework, multiple reporting and analysis systems can be used and they are designed to help business people use information to make smarter decisions. the bi team in this framework needs to disseminate standards that govern the use of data. this framework defines four domains of intelligence and maps them to end-user tools, design environments and architectures. 3. research methodology 3.1 research background there are two schools of thought when educational institutions are embarking on business intelligence initiatives. the first school of thought questions the real need for bi within educational institutions based on the fact that bi initiatives tend to be expensive, time consuming and they don’t deliver the anticipated business results. this school of thought argues that most universities around the world are traditional education institutions and therefore their prime focus should be in providing quality education rather than investing time and resources in bi tools. the second school of thought is the opposite of the first one. it supports the idea of bi and positions it as the main stream to enhance the university both academically and professionally. this school of thought has an assumption that bi brings value to educational institutions in terms of visibility of the university data and increases productivity. the basis of our research is to support the second school of thought primarily due to the fact that educational institutions need to evolve and innovate. the more insight such educational institutions have into their dark data, the more capable they become to face future challenges. this was evident from the journey that the university of minnesota and the university of indiana took to invest in bi tools. furthermore, bi, if used properly, can provide a competitive advantage for the university over other educational institutions. although squ is a government funded university, any improvement made within the university will derive value. squ has a huge volume of data. the processing of such data quickly and accurately can improve the decision making process, by making the use of such data more effective and efficient. for example, modeling the student’s grades and subjects can provide the university an advantage in responding quickly to changes in the industry, making the university more agile. 3.2 research questions based on the above, this research aims to provide answers to the following main research questions: 1. what are the future cases in squ that use bi? it is important during the maturity assessment to understand how bi is used currently and how bi will be used in the future. the first part describes the as-is situation while the second part describes the future aspirations of squ. 2. if an educational institutions want to implement a bi solution, what is the best approach? from the maturity assessment, it will be clear what the current situation and bi status of squ is. educational institutions are different in nature than commercial organizations and therefore it is important to develop the best approach for implementing bi. this will be clear during the development of the bi framework. once squ begins to implement the bi framework, it will improve the success rate of the bi implementation. 40 3. how can bi be used in squ to address strategic decision making challenges? as stated in the literature review, the field of bi is wide. furthermore, bi tools can be used as descriptive, diagnostic, predictive or prescriptive tools. in order to know what's best suited for squ, a prototype will be developed to demonstrate the value of bi in addressing the strategic decision making challenges. 3.3 proposed methodology the objective of this research is to develop a bi framework to be used for educational institutions. furthermore, the research will use squ as a case study to build this framework. in this research, both qualitative and quantitative research methods have been utilized. as can be seen from figure 1, the research process uses two important approaches. the first approach is the selection of the research topic that followed certain steps starting from identifying the problem statement to identifying the aim and research objectives. the aim is divided into two-sub sections which are the research questions and objectives of the research. from a literature review, the maturity model and bi framework have been selected. finally ending up with using both the quantitative approach (through questionnaire and interviews) and the qualitative approach (through the development of framework and using that framework to develop a prototype). 3.4 data analysis the data analysis method followed two main approaches. the first approach was to use secondary data analysis such as literature reviews and case studies to identify the different bi maturity models and bi framework available in the industry. two main frameworks were evaluated, namely, gartner and bi 2020. in addition, five maturity models, namely, tdwi (tdwi, 2015) (chuah & wong, 2012), the business information maturity model (rajterič, 2010) , gartner's maturity model, advanced market research (amr) (rajterič, 2010) and mit sloan (lavalle, hopkins, lesser, schokely, & kruschwitz, 2010) were evaluated. once a maturity model was identified, we started using the primary data to create a custom questionnaire that suits squ requirements. a number of interviews with the executive board of squ were conducted to provide strategic direction and business priority for the bi implementation in squ. figure 2 shows a graphical overview of the data analysis approach. 4. bi framework design for squ the objective of the bi framework is to provide a formal structure to be adopted by the organization (in this case: squ) when implementing bi. in addition, another objective of the bi framework is to provide a practical guide to help squ understand the different considerations it needs to include when embarking on the bi journey. it is important to note that frameworks might be implemented in different ways depending on the maturity level and the type of industry. nevertheless, bi frameworks are mostly used within business organizations and rarely used within educational institutions. although general frameworks are commonly used in educational institutions to describe structures figure 1 research methodology. 41 and hierarchy (qaa, 2014), the literature provided little evidence on the use of bi frameworks in educational institutions. this prompted the development of a bi framework to be used specifically for squ. 4.1 basis of the framework in order to select which framework is suitable for squ from gartner and bi 2020, the following criteria were developed: 1. framework should cover people, process and technology elements. 2. framework should be flexible to include elements from the maturity assessment without affecting its structure. 3. framework can be easily fragmented into different layers where accountabilities and responsibilities can be defined for each layer. 4. framework should be simple and easy to understand. comparing the two frameworks, gartner's framework met the above criteria. therefore, the basis for our bi framework was gartner's business analytics framework. figure 3 shows the proposed bi framework adopted from gartner. 4.2 bi framework components as depicted in figure 3, the framework is divided into five main components: 1. people: this component will describe the main user groups within the university. it is important to identify the main users of bi within squ in order to develop the different applications that each group will use. three main user groups were defined for squ; student, administration and faculty. each user group has a different set of requirements. furthermore, this component also covers the skills required by each user group to utilize and benefit from the bi implementation within squ. in addition, this component addresses the organizational structure required for having successful bi implementation. it is important to note that in gartner's framework, the definition of people is different from the one used in this research. in gartner's framework, people are divided into producer (mainly it), consumers (mainly business) and enablers (mainly information managers who facilitate analytics). due to the maturity level of squ, the three groups will be mainly consuming bi. this is due to the fact that in order for squ to start producing analytics, it needs to be mature. this can be achieved in figure 2 data analysis approach. 42 phases and not necessarily from initial bi implementation. 2. technology: in gartner’s framework, this section is referred to as the platform. gartner classifies the platform into capabilities such as decision capabilities, analytics capabilities and information capabilities. since squ bi maturity is low, the classification is done based on different technology layers. this was clear from the maturity assessment since the respondents were more interested to see the bi framework covering different layers such as access, infrastructure, data, integration, analytics and presentation. the description of each layer is as follows: • infrastructure layer: describes the different components of servers, network, storage, etc. • data layer: describes the different databases and data warehouse used to store data. • integration layer: describes the different tools used to extract and load data. • analytics layer: smart analysis takes place. it represents the different bi applications that are used for decision analysis or even performance management. • presentation layer: covers the different dashboards that are used for representing analyzed or processed data. • access layer: during the maturity assessment, many respondents complained about data accessibility. this layer is to ensure that the different user groups are able to access data they are authorized to access. 3. process: during the maturity assessment, there are two main use cases for bi within squ: decision making and performance management. since these two are the main use cases for bi in squ, it is essential to develop processes for using bi tools to help in performing the above two use cases. for example, in order to perform performance management, there is a process, which will define the different stages that performance management undertakes. at each figure 3 proposed bi framework. 43 stage of the process, there is a need to define where bi plays a role. this will become clear during the prototype stage. 4. change management & communication: it was evident from the maturity assessment that there are gaps identified in communication. apart from the fact that squ has a low bi maturity, the survey questions revealed a need to address the communication gap between the different levels within the university. therefore, as part of the framework, communication is included. furthermore, any introduction of new technology has to be accompanied with change management. this is required in general for any change in technology environment and it is essential for squ to have one due to the low level of maturity and high expectation for bi success. therefore, it is important to allow for a better management of change when introducing bi. 5. governance the assessment of bi governance during the maturity assessment proved that squ has a low level of governance. the policies are still maturing and there is a need to develop a better governance model around data that will help in improving the data integrity. in addition, there is a lack of clarity in the roles and responsibilities of who is supposed to do what in a business intelligence environment. it is essential that a governance structure has to be in place to address these gaps. 4.3 governance the assessment of bi governance during the maturity assessment proved that squ has a low level of governance. the policies are still maturing and there is a need to develop a better governance model around data that will help in improving the data integrity. in addition, there is a lack of clarity in the roles and responsibilities of who is supposed to do what in a business intelligence environment. it is essential that a governance structure has to be in place to address these gaps. 4.3.1 start with business demand three main user groups will be the main users of bi within squ. the initial judgment based on the maturity assessment and structured interviews provided the current demand for performance management and decisionmaking. although this might sound like a complete demand, it is not. therefore, it is important when using the framework to capture specific needs related to performance and decision making requirements. this can be in the form of different capabilities (i.e. the tool should be capable of doing so and so) or a particular feature (i.e. the tool needs to be colorful). regardless of the type of requirements, once all the requirements are captured, an overall synergy needs to be done to arrive at the different user groups’ expectations. during the maturity assessment and the structured interviews, few requirements were captured from the administration and faculty. respondents to the survey expect easy access to the bi tools. they expect training to be an integral part of any solution. they also expect that there is a need to centralize the bi support and to have a single ownership for the solution. while these expectations will drive some of the design principles of the technical solution, this is only the initial assessment and doesn't cover the full bi requirements of squ. 4.3.2 technology is an iterative process once the demand is identified, the technology can be determined. during the maturity assessment and the structured interviews, it was clear that the university needs to revamp its technical capabilities to address bi requirements. under the technology element, there are different layers that need to be addressed. it is important to note that when designing a bi solution for the university, the solution will need to undergo several iterations before determining the best fit. for example, it is clear from the maturity assessment that the university doesn’t have a data warehouse and doesn’t have the tools for extracting and loading the data. in order to address this gap, the data layer (in the framework) needs to be designed to include a data warehouse. the infrastructure layer needs to have all the different components (servers, storage and databases) to enable the development of the data warehouse. the integration layer will have all the etl tools required to extract and load the data while the analytics layer will be responsible for executing different algorithms to help data analysis. it was also clear from the maturity assessment that the user groups demand easy access and good representation of data. the presentation layer is responsible for 44 presenting the analyzed data in a format that is understood by the user groups. it is clear from the above that when designing the solutions there are interdependencies between the different layers. thus, it is important to do the first iteration rather than correct any misalignment in the following iterations. 4.3.3 agree the target process technology will not solve defects in the process or the organization. it is important when capturing the user demands to develop the target process. for example, one of the squ target processes is performance management. this process needs to be clarified prior to implementing the technology element to understand how the different users will use performance management to address their needs and how the technical infrastructure can help. therefore, it is important that once the technology solutions are finalized (as an initial or detailed design), the two main processes (i.e. decision making and performance management) are designed to work in harmony with the technical solution and people's expectations. 4.3.4 plan the change the bi solution is new to the university and it is going to change the way they carry out decision making and performance management. the university has a style of doing things at present that will need to evolve once bi tools are introduced. managing the transition between the old and new way of making decisions and managing performance will be one of the key success criteria for bi project. therefore, it is important to plan for the change and to develop a comprehensive communication plan. since the awareness level of bi is low in squ, the first step will be to increase the level of awareness. it is important at this stage to plan how the change will be managed and communicated. once decided, communication can be done through a series of presentations, posters, circulars, etc. the different communication channels will be determined by the current policies within squ for communicating project information or changes to the status quo. table 1 main differences between the gartner and squ bi frameworks. dimension gartner bi framework squ bi framework components gartner model has 3 core components: people, processes, and platform and 4 noncore components: program management, performance, metadata and information. squ framework has 5 core components: people, processes, technology, change & communication and governance. framework focus this framework is focused to ensure the bi strategy in place before organizations start to implement bi the focus is on bi implementation. there is an assumption that a bi strategy already exists within squ. people focuses mainly on people as produce, consume and enable. people are users of bi but they also support bi and thus there is a need to include training & development as part of this dimension. technology or platform process driven and focuses mainly on 3 main capabilities; decision, analytics and information. technically driven and focuses on how the access, infrastructure, integration elements will work together. processes very general and focuses on 3 processes: decision, analytics and information processes. specific to educational institutions needs and focuses on processes related to squ and what is important for the bi framework to deliver. change & communication not clear in the framework. the importance of managing change and communication is clearly visible as an important part of the framework. governance focused mainly on information governance. focused on how to govern the overall implementation of bi within squ. 4.3.5 govern and improve governance is important to make sure that things are implemented in the right order. currently, the university has no policies for data management. these policies need to be created and implemented. there is a need to have a body within the university to oversee bi implementation and steer the direction of the implementation. in addition, any improvement initiatives need to be captured and fed back to the framework to ensure that the different layers are working together to deliver the maximum value to the university. the result from the above five steps is an implementation plan for bi within the university. this plan can be used by the system integrators to implement the bi solution for the university. 4.4 bi framework features although the bi framework in figure 3 is adopted from gartner’s bi framework, there are a few differences between the proposed framework and gartner's framework. table 1 illustrates the main differences. 5. the implementation of bi 5.1 introduction as discussed previously, squ’s interest in bi is driven towards performance management. in order to demonstrate how bi analytics can help the university, it is important to develop a prototype of the bi system. the objective of developing a bi prototype is to provide a closer insight into the design of the bi solution and highlight issues and risks associated with the implementation. furthermore, the prototype will highlight challenges that the university might face during the implementation of the performance management part. in order for the prototype to reflect reality, the prototype design will be aligned to the industry’s best practices. there are many vendors who have developed bi solutions for different organizations and it will be very useful to utilize their architecture as a reference for this prototyping exercise. in addition, the prototype will use available tools for academic use. these tools (such as microsoft sql and microsoft visual studio) might not necessarily provide the best of breed scenario, but they are mainly used to demonstrate the concept. although the prototype is based on simple tools, the university might have to use a more sophisticated bi solution from bi companies such as microsoft or oracle in the future. 5.2 bi architecture in order to develop a prototype, there is a need to examine the real life setup of a typical bi implementation. since the university doesn't have a bi solution in place, it was difficult to find a company in oman that would allow access to its bi solution setup. therefore, it was important to search for the top providers for bi solution and see if there is a way to examine their bi solutions. two main vendors were identified, microsoft and oracle, who have a local presence in oman. since microsoft office tools are widely used, microsoft business intelligence solution was selected. in addition, it was easier to get support from microsoft, due to their strong local presence in oman. microsoft bi architecture is divided into three tiers: 1. data tier: this tier is based on the microsoft database server (sql server) and has four main elements: • sql analytics tools: mainly analytics. • sql reporting tool: creating dashboards. • sql integration tool: main etl tool for loading and extracting data from other non-microsoft sources. • sql dbms: where the database tables are located. 2. microsoft sharepoint provides the main content management and search. this is where all the delivery aspects of bi will happen. 3. end user reporting tools such as microsoft excel and performance point dashboard. in addition, microsoft introduced power view bi as part of their bi solutions to aid organizations to get a better view of their data. there are a number of options for power bi, the desktop, mobile and cloud options. when trying the cloud option, squ it department blocked the use of any power bi usage in the cloud. since squ already has office 2013 and excel 46 2013, power bi is integrated as part of that option so as to utilize the existing tool. 5.3 prototype design it was decided when building the prototype that one key business activity (kba) (teaching and learning) will be used among 1. teaching and learning 2. research and consultancy 3. community service and 4. resources and facilities. under this kba, there are 15 different kpis with different algorithms to calculate, as follows: 1 -percentage of course section with 30 or less students 2 -percentage of reviewed programs during the past 4 years 3 -percentage of courses assessed and evaluated 4 -growth in the total number of student enrolled 5 -percentage of undergraduate students achieving cgpa ≥ 2.7 6 -percentage of undergraduate students on probation 7 -percentage of postgraduate students on probation 8 -percentage of international undergraduate students 9 -percentage of international postgraduate students 10 -percentage of undergraduate student withdrawn 11 -percentage of postgraduate student withdrawn 12 -percentage of student transferring into the college 13 -percentage of students transferring out of the college 14 -full time equivalent (fte) student-staff ratio 15 -percentage of students graduated within expected period of graduation of concerned cohort furthermore, since the university has nine colleges, it was difficult to demonstrate this using a prototype. therefore, it was decided to focus the prototype in one college initially. the initial prototype design was based on the three tier model: • data layer: ms access. • bi layer: ms excel using power bi. • user interface layer: excel or web page integration. however, during the development work, power bi in excel didn’t provide the right level of analytics required by the university. therefore, it was decided to use a new prototype design that reflects in close proximity with the microsoft bi solution. the final prototype design was based on the three tier model as well: • data layer: all tables were created in microsoft sql server 2008 r2. • bi layer: the algorithm for calculating and analyzing the performance data was scripted using visual basic (vb) coding in microsoft visual studio 2013. the reason for selecting visual basic is due to its simplicity and wide adoption in squ. • user interface: login page distinguishes between different user profiles. there are two user profiles created. the interface for the whole solution was developed in sql reporting. figure 4 shows the architecture of the prototype solution showing the user interface: squ dashboard. when designing the different layers for the prototype, the following were the main considerations: 1. simple user interface. although we focused our efforts on one kba and one college, there are 15 different kpis to be represented. the initial interface design had multiple web pages to show the different kpis in different years. however, after a number of iterations, it was decided to simplify the interface with one page that represents the 15 kpis. figure 4 architecture of the prototype solution showing the user interface. 47 2. use of real data. the college of science was selected to be the first college to run their kpis using the prototype. in order to make the prototype more realistic, it was decided to use real data from the college. 3. segregation of users. two types of users were identified during the prototype design. one user that has access to the final performance dashboard. another user that has access to the data entry and performance dashboard. the roles of each should be segregated. 4. availability for staff to test the prototype. in order to ensure that the bi prototype meets the university expectations, two users were identified; one user from the college of science and another from the planning and statistics department. their role is simply to ensure the prototype meets the expected requirements. since agile methodology is utilized for the development of this prototype, it was important to have someone to own the requirements as they change during the different iterations. 5.4 user acceptance testing results the current performance calculation for the university is done by the planning and statistics department in squ. there is no dashboard currently to show the status of different kbas for the different colleges. the following is the feedback from the acceptance test: • the overall performance result for college of science in teaching and learning kba is shown as low in this dashboard. this reflects reality while we didn’t have this visibility of the college performance before. we thought they are doing fine. • it is easier using this dashboard to track the changes of the different kpis in different years. it provides solid evidence of which kpi needs more attention and which kpi doesn’t change over the years. • it would have been nice if each kpi has a traffic light showing if it is above or under target. this can be added as part of the interface improvements. • the thing i like most about this dashboard is its simplicity. i assume that the real life dashboard will have all four kbas aggregated to the squ level and the overall college performance will be represented in a similar fashion. 5.5 research analysis and discussion the maturity assessment questionnaire was sent to key staff in squ including staff working in technical, faculty and administrative positions. the total number of key staff was 200 but only 68 responded. this means that the response rate was 34% which is considered to be a good rate. table 2 shows the main findings of the maturity assessment questionnaire. as discussed previously, the squ bi framework consists of a number of elements. table 2 main findings (maturity assessment questionnaire). maturity assessment questionnaire main findings the breakdown of the survey respondents are; 47.1% technical staff, 30.9% administrative staff and 22% faculty. the overall maturity of bi within squ based on tdwi model is 1.4, which is considered low. majority of respondents do understand bi although the initial assumption when this research commenced was the opposite. majority of the people who understand bi think that bi is mostly used to predict and not necessarily to describe or analyze. majority of staff within squ don't understand how bi can be used in squ. majority of staff in squ (91.2%) expect the bi initiative to be more than 60% successful. there is a need for a better communication strategy for bi initiatives within squ. 80% of respondents stated that squ doesn't have any mechanism to ensure data quality while 20% believe it exists somehow. all the interviewed executives agreed that the university should invest on bi solution. improved strategic performance management is the first priority for squ management. majority of executives agreed that bi should be owned by the planning and statistics department. executives believed that bi will help in improving the decision making process. 48 the prototype reflects the technical element of the framework only. this is due to the fact that the main focus of the prototype is to demonstrate the applicability of bi to the performance management within squ. table 3 shows the main findings from the squ bi framework and prototype. table 3 . main findings (squ bi framework & prototype). main findings (squ bi framework & prototype) the framework has a wide coverage on the main elements that will contribute to a successful bi implementation. prototype covered one college and one kba, yet provided overall feasibility on the college kpi. the data sources for the prototype are manually entered but in real implementation integration points need to be in place to extract the data. thus, use of a data warehouse is recommended. the use of agile methodology provided a faster feedback cycle to correct and optimize the prototype design. the real value of the prototype was to give the college the aggregated performance of that particular kba in addition to visibility on all kpis as related to benchmark. 6. conclusion and future work this research was carried out to develop a framework to implement bi solutions for higher education institutions with squ as the case study. in order to develop a customized bi framework, the study utilized gartner's business analytics framework and the results from the bi maturity assessment. although the results of the bi maturity assessment came as no surprise, the effort needed to ensure that squ implemented bi successfully, was dramatically increased due to its low maturity level. this was challenging initially and changed management needs which played a major role in ensuring successful implementation. in addition, the research developed a bi prototype to test the concept of performance management utilizing the bia capabilities. it was clear from the maturity assessment and the stakeholder engagements that bi is positioned as a performance management improvement tool. this encouraged the development of the prototype using the kba and kpi that the university had. furthermore, the prototype has to be based on a real life scenario to increase its success and its reality check. microsoft bi architecture was used as the main reference for the bi prototype. thus, the prototype consists of 3 main elements, namely a database where performance data are stored, an analytics tool using excel power bi, and a web interface representing the visualization of the dashboards. although the focus of the prototype was limited to one kba in one college (college of science), it provided critical insight into how the college of science has been performing during the last three years. such insight into this information is a critical part of the value proposition the bi is recommending. to our knowledge, this research is the first of its kind to build a bi implementation framework for educational institutions, especially in the middle east sector. it is important to note that while squ scored low in the bi maturity assessment, other educational institutions might not have the same maturity level. therefore, it is recommended that the bi framework is tested against different maturity levels to see how it works. as discussed previously, the prototype developed during this research was limited to one kba and one college. there are 4 kbas within squ and 9 colleges that need to be examined with this prototype. by building such a prototype, the credibility of bi will be established and tested in real life. moreover, the aggregation of the different kbas and kpis will contribute to the overall squ performance and will provide better visibility of how squ as an organization is functioning. this is the key towards the successful implementation of bi within squ in the future. future researchers can use this framework to test how bi should be implemented in educational institutions. they can focus on testing the squ bi framework through using comparative analysis of two organizations with and without using the bi framework. also, the future research will expand the prototype to include all squ colleges and all four business kbas. acknowledgement we would like to thank coventry university uk, middle east college and sultan qaboos university in sultanate of oman for all the support provided to carry out this research. 7. references aziz, m.n and sarsam, z. 2013. the impact and power of business intelligence (bi) on the 49 decision making process in uppsala university: a case study. m. sc thesis, uppsala university. chu, t.-h. 2013. a framework for bi systems implementation in manufacturing. international journal of electronic business management. vol. 11, no. 2, pp. 113-120. chuah, m.-h. and wong, k.-l. 2012. construct an enterprise business intelligence maturity model (ebi2m) using an integration approach: a conceptual framework. d.m. business intelligence solution for business development, intech. fouche, g. and langit, l. 2008. foundation of sql server 2008r2: 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[online], available: http://tdwi.org/portals/businessintelligence.aspx [20 march 2015]. washer. 2007. revisiting key skills: a practical framework for higher education. quality in higher education, vol. 13, no. 1. zilli, d. 2014. self-service business intelligence for higher education managemen. int’l conference on management, knowledge and learning, slovenia. eg-uk conference paper style guide 29 using the ssav model to evaluate business intelligence software yasmina amara, klaus solberg søilen* and dirk vriens† *(corresponding author), halmstad university, sweden klasol@hh.se † nijmegen school of management, netherlands d.vriens@fm.ru.nl revised version accepted december 20 2012 abstract: choosing the right business intelligence (bi) software is critical to increasing productivity and effectiveness in organizations today. at the same time it is a very elaborating and complex process to choose the right software due to the fact that a large number of bi products exist on the market, which are quite different and updated frequently. the objective of this study is to develop and test a model for the evaluation of bi software. the findings of the study revealed that it is difficult to declare what is the most competitive bi software as what is good for one user might not be good for another depending on their different business needs. having said that the study initiated a new classification of bi software vendors depending on the degree to which they comply with the functions in the competitive intelligence (ci) cycle. the software tested was divided into five categories: fully complete, complete, semi complete, incomplete and insubstantial. we conclude that the ssav (solberg søilen, amara, vriens) model together with some proposed non technological variables and a classification developed can be used as a user's selection tool for deciding which bi software to purchase. keywords: business intelligence, software evaluation, competitive intelligence, ssav model 1 introduction with the emergent volume of data handled by companies in our fast changing business environment, staying competitive means constantly analyzing the existing market for relevant changes. this puts a burden on business owners, continuously to find and interpret information that is imperative for their survival. according to gartner group (2007) "the amount of data collected by an organization doubles every year. knowledge workers analyze only 5% of this data. knowledge workers spend 60% of their time searching for important relationships in the data, 20% analyzing the discovered relationships, and only 10% on doing something with the analysis (i.e., making decisions, implementing strategies and plans, etc.). information overload reduces decisionmaking capability by 50%". there is an increasing demand for software that can assist in this process, what is broadly known as business intelligence available for free online at https://ojs.hh.se/ journal of intelligence studies in business 3 (2012) 29-40 https://ojs.hh.se/ 30 (bi) software (for a list, see solberg søilen, k. 2005). 2 problem formulation the purpose of this research was to generate a new model with a new set of criterion for evaluating bi software. the idea was to propose an assortment of evaluation variables for each function of the ci cycle. so far the bi term has been used by a too large variety of software solutions. moreover, the research aimed at testing the model upon a chosen sample of bi software vendors to determine the most complete bi software. the aim was also to determine the software’s most important values, which ought to be considered by companies when deploying bi applications. the new bi software evaluation criteria and vendors categories aim to differentiate various vendors in the market and hence initiating a more informed user selection discussion. the research will attempt to answer the following questions:  what discussed variables/criteria are selected for evaluating business intelligence bi software?  how are these bi software variables measured?  according to the criterion selected what are the most competitive bi software available among the few that have been selected?  what credible categorization can be used to classify bi software vendors?  what is the potential for the proposed variables/criteria and vendor's categories? 2.1 a short background to the problem business survival today is based on companies’ abilities to analyze their rivals’ moves, and to anticipate market developments rather than simply react to them (millre, s. 2001). ci enables senior managers in companies of all sizes to make informed decisions about everything from marketing, r&d, and investing tactics to long-term business strategies. moreover, ci is considered a value-added concept that outperforms the top of business development, market research and strategic planning (arik, j. 2005). authors mostly refer to two reasons for obtaining a competitive intelligence capability. firstly, ci contributes to the overall organizational goals such as improving its competitiveness or maintaining the viability of the organization. in addition it contributes to the organizational activities needed to reach the overall goal like decision-making or strategy formulation (vriens, d. 2003). hence as claimed by jan p. herring (1993) the roles of ci efforts fall into the following categories:  strategic decisions and actions (tactics)  early-warning topics that prevent surprises to the organization relating to product launches, new emerging, or changing market and new technologies or business methods  knowledge of, learning from and assessments of key players and competitors, and  intelligence assessments for planning and strategy development. therefore, with ci capabilities a business can predict the action of their competitors & key players, remain competitive in the market and reach its goals through better decisions and more focused strategy planning. 2.2 business intelligence (bi) software more and more intelligence tasks today are automated, by the use of business intelligence. effective competitive intelligence results not from luck, but from the same careful planning, discipline, and systematic process that scientists employ. "however, the companies with the highest success rates at winning new business have found that competitive intelligence is not a magical art; it is a science whose ethical practice readily impacts a company’s top and bottom lines" (o'quinn, o. 2001). according to vriens (2003) in order for the intelligence cycle to be carried out properly, an organization should implement a balanced mix and an intelligence infrastructure that consists of following three parts:  a technological part, comprising the ict applications and ict infrastructure that can be used to support the intelligence cycle phases  a structural part, referring to the definition and allocation of ci tasks and responsibilities (e. g., should ci activities be centralized or decentralized), and  a human resources part, which has to do with selecting, training and motivating personnel that should perform the intelligence activities. thus, although technology matters for building effective ci it should be combined with good planning for the allocation of the ci tasks, making sure ci activities are carried out by professionals and get others involved. human resource departments should plan the selection of ci staff cautiously to ensure a superior ci performance. 31 all along different information & communication technologies (ict) tools are used for supporting the different activities in the competitive intelligence cycle. ict for ci (or competitive intelligence systems, cis) is best seen as a collection of electronic tools (vriens, d. 2003) that support strategic decision-making, that are dispersed over different management levels; and that supports structured and unstructured intelligence activities. according to vriens three types of ict tools can support or sometimes even replace the ci activities: the internet as a tool for direction or collection activities, general applications to be used in ci activities (groupware or intranets etc) and business intelligence software. this paper is concerned with the latter. 3 method empirical research was carried out to test the developed model. a selected sample of bi software vendors and their products was tested against the set of evaluation criteria originated from the conceptual work. initially a custom-made cover letter requesting free access to the sample vendor's products for measuring purposes was sent out. the vendor's sample which has been integrated in the evaluation is a non-probability purposeful quota sample that includes 11 bi software products: business objects, microstartegy, microsoft, information builders, panorama, qlickview, spotfire, cognos, sas, astragy and digimind. observations and experiments were conducted using mostly the free software accesses obtained from the software trial demonstrations already available and the vendors' presentations & white papers to collect data regarding the capabilities. the evaluation model developed with its variables and proposed measuring scale (likert scale) were documented and mapped as a checklist and used to evaluate the bi software samples and demeanor quantitative analysis of numerical data obtained from the likert scale scores enabling the comparative investigation of the bi vendors who are participants in the study. the research will attempt to answer the following questions: 1) what discussed variables/criteria are selected for evaluating business intelligence bi software? 2) how are these bi software variables measured? 3) according to the criterion selected what are the most competitive bi software available among those few that have been selected? 4) what credible categorization can be used to classify bi software vendors? 5) what is the potential that the proposed variables/criteria and vendor's categories can be used as bi software users' selection foundation? for business intelligence systems to be successful, there is need to create an appropriate infrastructure to capture and create data, information, and knowledge, and store them, improve them, clarify them, analyze them and disseminate them to decision makers so that there can be an overall understanding of a company's operations for actionable results (thierauf, r. 2001). thus for ensuring effective business intelligence platform, five essential steps are needed: understanding the problem, collecting the data, analyzing the data, sharing the results, and acting on the information which represents the phases of the ci cycle all of which are supported with different technologies (capabilities) whether data warehousing, business analytics, analytical models (user's interfacing) business performance management (bpm), user's interfacing as explained by ericsson (2004): 32 data warehousing business analyticis olap data mining predictive analysis qualitative analysis information delivery analytical models (user interfaces) report & queries planning & directing (frameworks) figure 1: bi software capabilities (ericsson, 2004) the priorities of the business are understood here by mapping the existing data flows and structures and understanding the needs of the decision makers (ericsson, 2004). this bi function basically supports the planning phase in ci cycle. 3. 1 software evaluation "business organizations are still struggling to improve the quality of information systems (is) after many research efforts and years of accumulated experience in delivering them" (duggan, e. 2006). building an information system, whether it is a customized product for proprietary use or generalized commercial package, means providing sophisticated high-quality software, with the requisite features that are useable by clients, delivered at the budgeted cost, and produced on time. however, these goals are not frequently met; "hence, the recurring theme of the past several years has been that the information system community has failed to exploit it innovations and advances to consistently produce high-quality business applications" (brynjolfsson, 1993; gibbs, 1994). the evaluation of software and its business value are recently the subject of many academic and business discussions. since investments in it are growing extensively, and business managers worry about the fact that the benefits of it investments might not be as high as expected (van grembergen, 2001). the business value of a software product results from its quality as perceived by both acquirers and end users. therefore, quality is increasingly seen as a critical attribute of software, since its absence results in financial loss as well as dissatisfied users, and may even endanger lives (duggan, e. 2006). thus users’ perception of software quality is the base of evaluating software. palvia (2001) interpreted information system quality as discernible features and characteristics of a system that contribute to the delivery of expected benefits and the satisfaction of perceived needs. other scholars, such as ericsson and mcfadden (1993), grady (1993), hanna (1995), hough (1993), lyytinen (1988), markus and keil (1994), newman and robey (1992), have further explicated is quality requisites that include:  timely delivery and relevance beyond deployment  overall system and business benefits that outstrip life-cycle costs  the provision of required functionality and features  ease of access and use of delivered features  the reliability of features and high probability of correct and consistent response  acceptable response times  maintainability which means easily identifiable sources of defects that is correctable with normal effort  scalability to incorporate unforeseen functionality and accommodate growth in user base, and  usage of the system. besides quality, bass (1998) uses the following attributes to evaluate software:  performance: the responsiveness of the software  reliability: the ability of the software to keep operating  availability: the proportion of time the system is up and running  security: the measure of the software ability to resist unauthorized attempts at usage and denial of service while providing the service to the user  portability: is the ability to make changes to software quickly and cost effectively  functionality: the ability of the software to do the work for which was intended  variability: how well the software can be expanded or modified  conceptual integrity: the underlying theme or vision that unifies the design of the software at all levels, and  usability: the user's ability to utilize software effectively. 33 furthermore, fenton & pfleeger (1997) introduced a quality model which evaluates software based on the following three dimensions.  the people dimension: this dimension includes the competent is specialists along with their skills and experience necessary to manage both the technical and behavioural elements of the software. whereas delivery is central to ensuring high-quality is products (perry et al., 1994). additionally, it is said that the user-centred perception of the software delivery increase the opportunity of producing higher quality systems (duggan, e. 2006).  the process dimension: this dimension prescribes the timing of each deliverable, procedures and practices to be followed, tools and techniques that are supported, and identifies roles, role players, and their responsibilities (riemenschneider et al., 2002). its target is process consistency and repeatability as is projects advance through the systems life cycle (duggan, e. 2006).  the product dimension: the product quality is concerned with inherent properties of the delivered system that users and maintenance personnel experience (duggan, e. 2006). the noticeable growth in the bi software market is leaving companies of different spheres in bewildering status by having to decide amongst diverse bi software vendors that want to assist them to achieve their business objectives. according to cbr staff writer (2007) "the scope for differentiation between bi vendors has shifted higher up the stack, towards issues such as predictive analytics and real-time bi. it has also moved lower down the stack, towards more pervasive bi and client bi applications. other differentiation strategies may focus on strategic issues such as ease of deployment, on-demand offerings, industry-specific packages, enterprise application integration or go-to-market approaches". for this reason, choosing the right bi software is critical to increase productivity and effectiveness in the organization. nevertheless it is a very elaborating and complex process due to the fact that numerous bi software packages exist on the market most of which are updated very rapidly. most importantly the selection process involves various criteria and variables against which bi software are compared and evaluated which on the whole are not apparent and generally vague (turban et al., 2007). besides, most of the evaluations done are not able to combine both the testing of the bi effectiveness as a tool and its support of the phases in the competitive intelligence ci cycle. so far only gartner, forrester and fuld & company are established for performing evaluations of bi software. the attributes that are used here to evaluate software can't be used directly for evaluating bi software. hence the need to find specific attribute to evaluate bi software quality. 3.2 gartner gartner inc. is accredited for having introduced the term “business intelligence”. gartner initiated the magic quadrant for business intelligence platforms evaluation which states that users should evaluate vendors in all four quadrants, including the niche players, visionaries, leaders and challengers. according to gartner research 2005 the vendors are placed in one of four positions (leaders, challengers, visionaries and niche players) in a “magic quadrant.” as follows:  leaders: have strong market position, solid customer support, and an extensive pool of skilled developers. their products have generic functionality. also, there is limited or no access to key personnel, and there is little room to negotiate prices.  challengers: are characterized by their stability, solid customer support, reliable technology, and functional completeness. their products’ architecture may be outdated, they have a limited pool of skills, and they may compete with potential application partners.  visionaries: have cutting-edge functionality in their offerings and have the potential for aggressive discounting. on the flip side, they are potentially unstable, offer limited support, and have an extremely meagre skills pool.  niche players: typically have critical and unique functionality—but they have a limited ability to compete in the market and enhance their product. of course, not all of these characteristics apply to each and every one of the vendors, but they serve as a framework to categorize them for comparison purposes. vendors were included in the magic quadrant if they met the following requirements:  they deliver at least eight of the (12) bi platform capabilities divided into three functionality categories integration, information delivery and analysis. 34  they have a reasonable market presence, which we define as greater than $20 million in annual revenue from bi platform software.  they demonstrate that their solutions are used and supported across the enterprise, and go beyond departmental deployments. (gartner 2007). later on the vendors who can be added to gartner's magic quadrant are evaluated based on two evaluation criterions. the first is based on vendor's ability and success in making their vision a market reality and the second on their understanding of how market forces can be exploited to create value for customers and opportunity for themselves. to conclude, gartner's evaluates bi software from the pure business perspective. it assesses bi software ability to achieve its business goals and vision. although it looks at bi software functions to determine the intrusion condition of any bi software in the gartner's evaluation, it doesn't measure the bi functions effectiveness nor the software support of the ci cycle phases. 3.3 forrester wave bi forrester wave bi software evaluation includes a detailed in depth evaluations criteria based on three level buckets: offering, strategy, and market presence (keith, g. 2006). forrester wave evaluates bi vendors who met the following criteria:  a vendor with annual estimated bi revenue in excess of $100 million  a vendor with or more products specifically targeted at the bi reporting and analysis market, and  a market-leading pure-play bi vendor, rdbms, or enterprise application vendor with a native analytic or enterprise reporting product/component, or a supporting reporting engine and repository. forrester found through users interviews that most users are unsatisfied with the way they currently receive analytic information. thirty percent of those surveyed thought their analytic software has significant gaps in usability. twenty-two percent cited lack of detail as an issue. forrester assesses the bi vendors on their functions effectiveness and usability but in a very general manner without going into any depth of each bi capability. moreover, it didn't evaluate the level of support bi software functions provide to the ci cycle phases. 3.4 fuld & company ci software evaluation fuld & company compare ci users’ reactions of ci software to those of animals with certain traits in order to motivate hundreds of users to respond and complete a survey that is aimed to convey both the characteristics of the technology and their responses to that technology. the animals they chose were as follows:  slug because of its lack of speed and responsiveness  gerbil a fast animal but one that seems to go in circles, quickly spinning its wheels, but going nowhere  bee for its speed, smarts, and sense of the bigger picture  parrot that would spit back the information, adding little, and  labrador a dog who would go and retrieve what you need when you need it. "the largest single segment of respondents, 42%, compared their competitive intelligence ci technology to a beean insect that “creates a useful pattern or swarm of information and helps me connect the dots.” nearly one-third (29%) saw their solution more like a labrador retriever, “good at fetching and retrieving.” a vocal minority of nearly 30% of respondents gave the software low grades, comparing it to a parrot (11% “just spits back what you sent to it; no added value”), a slug (12% “just takes up space and never seems to go anywhere”), or a gerbil (6% “lots of action, spins its wheels and offers no substance whatsoever – and definitely consumes my time”) (fuld & company, 1999). fuld & company evaluates the software packages with regard to the five steps of the intelligence cycle in relation to how much we can reasonably expect the technology to support each step of the ci cycle. they first had to distinguish between packages that promoted themselves as business intelligence tools. “business intelligence software”, as the industry labels many of its products, typically deals with data warehouses and quantitative analysis, almost exclusively of a company’s internal data (e.g. crm, customer relationship management data) (fuld & company intelligence report, 2006-2007). fuld (2002, page 12-13) state that the fulfilment of the following functions acts as criteria in judging ci applications in the direction phase:  providing a framework to input key intelligence topics and key intelligence questions, and  receiving ci requests managing a ci work process and project flow that allows 35 collaboration among members of the ci team as well as with the rest of the company. for the data collection phase the criteria includes the following:  the ability to capture qualitative, ‘soft’ information from employees throughout the company, either through internal message boards, e-mail, or another easily accessible medium by which primary information can be inputted and retrieved  the capacity to target and retrieve qualitative information (such as consumer feedback) from message boards, news groups, and other external forums, and  an area in the software and user interface for inputting interviews, field reports, and other first-hand accounts. the criteria for the analysis phase include:  the ability to sort information by user-defined rules  data visualization interface(s) to sort and view collected information  multiple viewing models, such as swot (strength weaknesses opportunities threats) and porter’s five forces model  display of information in chronological order  extraction of relationships between people, places, dates, events, and other potential correlations  text-mining technology to locate and extract user-defined variables, and  the ability to relate analyses to quantitative data. for the reporting and informing phase:  both standardized and customizable report templates  the ability to link and export reports to microsoft office formats, coreldraw, pdf, multimedia formats, other databases, and/or other reporting systems, and  the capability to deliver reports via hard copy, the corporate intranet, e-mail, and/or wireless sources. fuld's evaluation criteria evaluated software packages with regard to the backup it provides for the four ci cycle phases. the software packages that have participated in the fuld's evaluation were the one not dealing with bi functions from: frameworks, data warehousing, business analytics and user's interface but rather those with more simple functions assigned for planning, data collection, and analysis and information delivery methods. fuld's criteria didn't measure the effectiveness & efficiency of the software as a tool. hence, this study used and set off further from fuld's model criteria by applying the developed model on software packages escorts bi functions. 4 results and analysis the ssav bi software evaluation model was developed and tested on a sample of bi software discussed earlier by analyzing their various capabilities (functions). its aim is to evaluate bi software effectiveness & efficiency as a tool in addition to assess how each bi function supports a particular ci activity in the cycle. moreover, the variables used for evaluating bi software can be divided into the following three classes:  process variables i: they include variables for evaluating the effectiveness & efficiency (quality) of bi software functions (capabilities).  product variables: they include variables for evaluating the effectiveness & efficiency (quality) of artifacts, deliverables or documents that result from bi software function, and  process variables ii: they include variables for evaluating how a bi function supports a particular ci cycle activity. consequently, the variables used in the evaluation criterion were divided into four parts as illustrated. a five point likert scale was used to evaluate the bi software functions against the developed evaluation criteria by selecting a number from highest to lowest (0-4) for each specified trait/variable. the numbers are arranged horizontally and are added up to arrive at an overall score as follows: 4 = excellent, 3 = good, 2 = satisfactory, 1 = poor, 0 = (n/a) seeing that, selecting the right bi software is critical to improve the productivity and effectiveness of organizations huge burdens are put into developing a suitable methodology that can be used for selecting bi software that will best suit the users' needs. in this paper the focus is to develop a new technological model for evaluating bi software 36 effectiveness & efficiency as a tool besides assessing the extent in which they support the four phases of the ci cycle. consequently, these technological variables can be used as a starting point when selecting a bi tool. although, the technological variables can aid users in narrowing down their bi vendors alternatives, they are not enough. further, investigation should be conducted to extract some non technological variables which could be critical to enhance users end decision regarding which bi tool to pursue. three additional non technological variable groupings can be used as a bi evaluation criterion and hence as a selection tool as demonstrated below.  human & structural variables: it includes variables relating to the effectiveness of the development teams and the allocation of ci tasks and responsibilities among them. moreover it has to do with the human competencies that should be available when selecting, training and motivating personnel that should perform the intelligence activities. the proposed human & structural variables are illustrated in the table (4) below:  users variables: they include variables concerning the in-house staff using the software. as shown in table (5) below.  vendors variables: usually the final choice regarding the bi tool selection is often based on the ability of the chosen vendor to support the company's current and future projects in terms of stability, resources, and experience. consequently, to aid users in their bi tool selection it is recommended to evaluate the software upon the technological and non technological variables mentioned in this chapter using the likert scale. however, in this study only the technological variables are used in the ssav model to test some bi vendors' software for two reasons, time constraints and the difficulty to assess the non technological variables using the projected methodology. using bi vendors free trials, demos, presentations and white papers collected, performance assessment along with comparative analysis were conducted for each vendor software participating in testing the ssav model; resulting in a pertinent score on the likert scale for each variable in the different bi functions & ci phases of the model for each vendor. in addition to an overall score for each bi function, support of ci cycle phase and the total phase score were calculated correspondingly for each bi participant. 4.1 the most competitive bi software saying that a particular bi software vendor is the most competitive is not possible. it is possible to say that a certain bi vendor concentrates and stands out in one phase or more in the ci cycle while disregarding the rest. moreover, a software vendor can do better in a certain bi function compared to the others functions. so, it is of great importance for users to determine what intelligence cycle feature or bi software function is essential to work properly. and decide which software to purchase. on the other hand it is important to be able to spot the complete (standard) bi vendors which offer the four ci cycle phases in one package and identify those who have the highest overall score in the ci phases together. below are the findings resulted from analyzing the likert scale scores for the limited number of bi software vendors who participated in this study. 4.2 the top data collection vendors according to the scale below information builders is the best bi vendor when it comes to data collection followed by cognos and business objects. alternatively tibco spotfire is the least good. 37 table 1: bi software ranking in data collection ranking bi software vendor 1. information builders 2. cognos 3. business objects 4. sas 5. microsoft 6. panorama 7. microstrategy 8. qlickview 9. tibco spotfire 10. astragy 11. digimind source: evaluation results as for the two ci software vendors digimind and astragy they come at last since they don't provide table 2: bi software ranking in analysis source: evaluation results any bi functions which here contribute to the data collection overall score. both vendors score high in supporting the ci data collection variable but using different means and functions. 4.3 the top vendors in analysis from the next figure we see that sas is the best in analysis followed by microsoft and business objects. and the vendor who is less good in analysis is qlickview. while the rest vendors analytical capabilities are somehow below average. again although digimind & astragy provide good analysis their score are low on the scale since they don’t provide any bi business analytics from olap, data mining, predictive or qualitative analysis. when it comes to the ability of dissemination the list is as follows: table 3: bi software ranking in dissemination ranking bi software vendor 1. business objects 2. cognos 3. panorama 4. information builders 5. microstrategy 6. tibco spotfire 7. sas 8. microsoft 9. qlickview 10. digimind 11. astragy source: evaluation results the top dissemination vendors are business objects, providing the best information delivery, followed by cognos and panorama. microstartegy is at the bottom of the list. as for astragy and digimind they have low scores for the same reason mentioned above though their score for supporting the ci dissemination phase is almost the same as for other bi vendors. 4.4 the top vendors in planning & directing astragy is the only vendor who supports this phase of the ci cycle as its consultants helps and advises users with the organization of their intelligence system. no list is therefore added here. the most complete (standard) vendors are business objects, with the highest overall score making it the most complete vendor followed by cognos, microsoft and information builders. qlickview has the lowest overall score. if the total score was calculated by adding up only the ci phases supporting variables without the bi functions variables digimind would have scored highest followed by business objects. from the empirical findings and their analysis a new categorization for bi software can be generated. this categorization segregate bi software into five categories depending on the level of support it provides for the ci cycle phases as follows.  fully complete: bi software in this category excels in the four phases of the ci cycle including: planning, data collection, analysis and dissemination.  complete: since the planning & directing phase is seldom supported by any bi software, they can be considered complete but not fully complete if it performed very well in the other three phase of the ci cycle: data collection, analysis and dissemination.  semi complete: in the case the bi software excels in two ci phases out of four it is ranking bi software vendor 1. sas 2. microsoft 3. business objects 4. microstrategy 5. cognos 6. tibco spotfire 7. panorama 8. astragy 9. digimind 10. information builders 11. qlickview 38 considered to join this category for example: data collection & analysis, data collection & dissemination or analysis & dissemination.  incomplete: when the bi software stands out in only one phase of the ci cycle it is positioned as incomplete. for example: merely data collection, solely analysis or just dissemination.  insubstantial: if the bi software perform well in any of the ci cycle phases is it included in this category. in order to consider a bi software excelling in a phase it ought to have an overall score of (2.5) or more in that particular phase on the likert scale. consequently, the sample bi software evaluated can be classified using this categorization, as shown in the following table: table 4: bi software classification bi software category phases it excels in information builders semi complete data collection & dissemination microstrategy incomplete dissemination microsoft semi complete data collection & analysis business objects complete data collection, analysis & dissemination panorama semi complete data collection & dissemination cognos semi complete data collection & dissemination spotfire incomplete dissemination qlickview insubstantial: none sas semi complete data collection & analysis source: evaluation results the proposed categorization can be used as a foundation when selecting bi software by enabling users to clearly see what ci phases are critical for serving their business needs. 5 conclusions the purpose of this paper was to develop a model (the ssav model) with a scale and test it on a small sample of bi vendors. moreover the aim was to decide upon which bi software is the most competitive, classify them using a credible categorization and examine the models' and the categorizations' potential to be user's selection foundation. by reviewing the theoretical framework comprehensively, the ssav model with its evaluation criteria for assessing bi software using a five point (0-4) likert scale is developed. it consists of technological variables covering the bi functions and ci cycle phases which is capable of evaluating the bi tool effectiveness & efficiency as well as assessing its level of support for the ci cycle phases. thus, being able to build up a model that benefits and add from previous evaluations' models as gartner, fulds and forrester wave. the assertion that a particular bi software vendor is the most competitive is difficult. a business intelligence vendor might excel in one phase or more in the ci cycle and/or stand out in a certain bi function while disregarding the rest. accordingly, it is of great importance to determine what intelligence cycle feature or bi software function is crucial to work properly for them users when pursuing bi software. as of the analysis of the empirical findings for our limited number of bi software participants we found that information builders is number one in data collection, sas is the best in analysis and business objects is the leader in dissemination. the most complete bi tool are cognos and astragy, the only vendor in our sample who supports the planning & directing phase of the ci cycle. additionally, information builders are the top in providing data warehouses and data integration; business objects excels in metadata reports, qualitative analysis, user interfaces and reports. the best olap is from microstrategy and data mining & predictive analysis from sas. whereas cognos stands out in the user interfaces & in reporting. it is crucial to point out that astragy & digimind bi software don't include any kind of frameworks, data warehousing, business analytics or user interfaces capabilities or any other bi software functions being evaluated in the ssav model. their more ordinary common functions for supporting the ci cycle phases results in a low score on the overall ci cycle phase score, even though they could be achieving an outstanding performance in that particular phase. hence, further adjustment ought to be started in order to develop a model that will be able to give these kinds of bi software a more reliable evaluation. generally speaking the planning & direction phase of the ci cycle is not commonly available in any bi software being evaluated. therefore more attention should be given to the development of frameworks that support this phase since it is fundamental for determining the strategic information requirement and it is considered the base for the other phases in the ci cycle. nevertheless, the analysis of the empirical shows that on average bi vendors perform good in the dissemination and data collection phases but still most of them lack the analytics capabilities where more emphasize should be placed. lastly, bi software vendors nowadays can be classified into five categories: fully complete, complete, semi complete, incomplete and 39 insubstantial depending on the level of support it provides for the ci cycle phases. hence, it can be a further help for users' selection of the bi software vendor that best meets it business needs by helping users select from these five categories the bi software that will aid them in achieving their long & short term objectives. business objects is the only complete bi vendor among the vendors being evaluated. information builders, microsoft, panorama, cognos and sas belong to the semi complete category. whilst, microstartegy and spotfire are considered incomplete and qlickview insubstantial. accordingly, the technological variables of the ssav model, the proposed non technological variables and the categorization developed can together be used as users' bi software selection tool. 6 suggestions for further study during the theoretical and empirical study, many questions, which deserve further investigation, have come up. these questions can be answered through some future studies. so the followings future studies can be suggested subsequently. one of the findings of this study was that the ssav model of technological criterion in conjunction with the proposed non-technological variables consisting of human, users and vendors factors are to be used to evaluate bi software. consequently, the first suggestion for future studies is to test these non technological variables on the bi software. this couldn’t been done during this study due to the time limitations as it was difficult to observe development teams in their natural working environments nor conduct personal interviews with end users and bi vendors. additionally, free software accesses, free trial demonstrations, vendor presentations and white papers were used to compare bi software and grant each a score on the likert scale depending on the variable being evaluated which good to some extent. but, in order to get more accurate measuring results an alternative way could be implemented which were constricted along with the time factors. the alternative measuring method can include using the same data source (data set) for all the participant bi vendors and thus tracking what occurs to this data source throughout the whole ci cycle phases for each vendor separately and can be considered as a further suggestion for advanced studies. besides, again due to the time constraints and not being able to get free trials from all the credible bi vendors the ssav model was tested only on 11 bi vendor. so, in order to make a more comprehensive reliable evaluation it is vital to include the rest in another study. at least it can include: proclarity, teradata, pilot, prelytis, epicor, codec, sap and comarch. finally, the ssav model couldn't be totally applied on astragy and digimind bi software since they don't contain the usual bi functions like frameworks, data warehousing, business analytics and user interface but rather other functions that support the ci cycle phases. accordingly, building a new version of this evaluation model to support these kind of bi software could be an interesting topic for further studies. 7 references arik , j. 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(2005). sorting out what’s new in decision support. business intelligence journal. http://elin.lub.lu.se.miman.bib.bth.se/elin?func=record&resid=9afaae6a727c4bb189e89da6c3d5f3a0&lang=se&query=%28all%3a%22jan%20herring%22%29%20and%20year%3a%5b1993%20to%202010%5d&start=2&sessionid=2eef8a30e234a4ce8ddd4c5f11ae5fcb&orgfunc=basicsearch&ftxtonly=&sdi= http://elin.lub.lu.se.miman.bib.bth.se/elin?func=record&resid=9afaae6a727c4bb189e89da6c3d5f3a0&lang=se&query=%28all%3a%22jan%20herring%22%29%20and%20year%3a%5b1993%20to%202010%5d&start=2&sessionid=2eef8a30e234a4ce8ddd4c5f11ae5fcb&orgfunc=basicsearch&ftxtonly=&sdi= http://www3.interscience.wiley.com.miman.bib.bth.se/journal/60500175/home http://www3.interscience.wiley.com.miman.bib.bth.se/journal/88010879/issue http://www3.interscience.wiley.com.miman.bib.bth.se/journal/88010879/issue http://www3.interscience.wiley.com.miman.bib.bth.se/journal/60500175/home http://www3.interscience.wiley.com.miman.bib.bth.se/journal/88010879/issue http://www3.interscience.wiley.com.miman.bib.bth.se/journal/88010879/issue http://www3.interscience.wiley.com.miman.bib.bth.se/journal/60500175/home http://www3.interscience.wiley.com.miman.bib.bth.se/journal/72514615/issue vol9no2paper7 to cite this article: dadkhah, m., lagzian, m., rahimnia, f. & kimiafar, k. (2019) the potential of business intelligence tools for expert finding. journal of intelligence studies in business. 9(2) 82-95. article url: https://ojs.hh.se/index.php/jisib/article/view/411 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index the potential of business intelligence tools for expert finding mehdi dadkhaha, mohammad lagziana*, fariborz rahimniaa, khalil kimiafarb adepartment of management, faculty of economics and administrative sciences, ferdowsi university of mashhad, iran; bdepartment of medical records and health information technology, school of paramedical sciences, mashhad university of medical sciences, mashhad, iran *m-lagzian@um.ac.ir journal of intelligence studies in business please scroll down for article the potential of business intelligence tools for expert finding mehdi dadkhaha, mohammad lagziana*, fariborz rahimniaa and khalil kimiafarb adepartment of management, faculty of economics and administrative sciences, ferdowsi university of mashhad, iran bdepartment of medical records and health information technology, school of paramedical sciences, mashhad university of medical sciences, mashhad, iran corresponding author (*): m-lagzian@um.ac.ir received 30 july 2019 accepted 28 october 2019 abstract finding the right experts for data gathering through interview serves as a key for particular research works. however, most expert finding methods in the literature require great deals of technical knowledge, making them somewhat impracticable for business researchers without deep technical knowledge. accordingly, there is a need for an expert finding solution for researchers without a deep technical background. as business researchers may have knowledge about business intelligence and its tools, the use of business intelligence tools can be used to solve such issue. the present paper discusses the process of using business intelligence tools to find potential experts for example topics. subsequently, based on a literature review, criteria are presented for distinguishing different experts. finally, the analytic hierarchy process is discussed for assigning weights to both selection criteria and potential experts. the audience of this paper is researchers who are familiar with business intelligence tools or would like to learn how to work with them. keywords business intelligence, business intelligence tools, expert selection, expert selection criteria, participant selection 1. introduction in social science, qualitative methods are popular for conducting research. in the qualitative research methods, interviews with participants are one data collection instrument (louise barriball & while, 1994). accordingly, different strategies are presented for selecting potential participants. in some cases, unavailability of participants for face-to-face interviews or other difficulties led researchers to utilize computers as a research instrument (girvan & savage, 2013; markham, 2004). a review of the literature on research methodologies shows that, unlike quantitative research, qualitative research tends to select participants purposively (flick, 2008; marshall, 1996) based on specific criteria. in such studies, the researcher decides, based on the specific criteria, who to consider as a participant for the research (flick, 2008; marshall, 1996). there are a number of strategies for purposive sampling in qualitative research (palinkas et al., 2015). as described by palinkas et al., such strategies can be grouped into three major categories: (1) the strategies emphasizing similarity, (2) the strategies emphasizing variation, (3) and the strategies with no specific emphasis (palinkas et al., 2015; patton, 2002). despite the apparently extensive research on purposive sampling in qualitative research, it is not always an easy task to accomplish. it is not journal of intelligence studies in business vol. 9, no. 2 (2019) pp. 82-95 open access: freely available at: https://ojs.hh.se/ 83 always easy to find participants for a research plan where the required data shall be obtained from people with professional knowledge (i.e. experts). the situation becomes even more critical when such expert experience falls within multiple contexts, with only few experts in each context, or when such experts are in multiple locations (for example, country, university, or organization) making it impossible for the researcher to become aware of all of them. even though snowball sampling can be a good alternative for such conditions, finding participants within a reasonably short period of time is also an issue. finding expert participants for a qualitative research may be difficult in some cases. this problem is not limited to some cases in qualitative research: there are studies that discuss this issue without considering this domain (gretsch, mandl, & hense, 2011; ru, xu, & guo, 2007; serdyukov & hiemstra, 2008). so, finding the right expert can be a challenging task. in such situation, using a machine-made method for finding experts can be helpful. the present research aims to show how to use business intelligence (bi) tools and the analytic hierarchy process (ahp) to find experts. the target audience of the current study is researchers who are interested in bi or have knowledge in this regard. for example, business students can learn to work with the tools used in this paper as they may learn bi in university or at workshops, section 2 gives a brief overview of some available methods. section 3 describes the process of using bi tools to find experts and presents a discussion on its results. the final conclusions are drawn in section 4. 2. brief overview of expert finding research researchers have presented various methods to find experts. deng et al. presented three models for finding experts by using dblp bibliography and google scholar services (deng, king, & lyu, 2008). naeem et al. utilized data mining for the same purpose (naeem, khan, & afzal, 2013). kardan et al. presented and discussed a model for expert selection in social networks (kardan, omidvar, & farahmandnia, 2011). other research focuses on finding experts in social networks or community question answering websites (bozzon, brambilla, ceri, silvestri, & vesci, 2013; kao, liu, & wang, 2010; kardan et al., 2011; riahi, zolaktaf, shafiei, & milios, 2012; zhang, tang, & li, 2007; zhao, zhang, he, & ng, 2014). wang et al. proposed an algorithm, called expertrank, that identifys and evaluates experts based on both documentation and an individual’s authority in his or her knowledge community. this algorithm is a modification of the pagerank algorithm to evaluate an individual’s authority (wang, jiao, abrahams, fan, & zhang, 2013). demartini used wikipedia as the knowledge source to find experts in topics. he used wordnet and yago to improve retrieval effectiveness (demartini, 2007). zhan et al. employed probabilistic latent semantic analysis to propose a mixture model for expert finding. semantic themes will be identified by such mixture models between terms and documents. then by using these themes, their method finds relevant experts based on the query (zhang, tang, liu, & li, 2008). yang et al. proposed an expert finding system by analyzing an individual’s journal papers. they state that journal publication can be used to find the expertise of a researcher (yang, chen, lee, & ho, 2008). lin et al. in a survey discussed methods and models that focus on expert findings and show the current status of research in this regard (lin, hong, wang, & li, 2017). boeva et al. proposed a data driven expert finding technique. their technique also weighs experts based on their expertise (boeva, angelova, & tsiporkova, 2017). further search into the literature would highlight other technical methods for expert finding. even though these are valuable and interesting, such methods are only useful for researchers with advanced technical knowledge. other researchers without deep technical knowledge may not be able to take advantage of such techniques, unless the technical methods are translated into convenient tools for social science researchers. there are some easy-to-use expert finding methods in the literature. on its user interface, scopus provides an interested option for analyzing search results (beatty, 2015), offering an easy-to-use method for nontechnical researchers who are looking for particular experts. this method can be used for expert selection. schuemie and kors developed a web-based tool entitled jane (http://jane.biosemantics.org/index.php) which can be used for expert finding. jane uses pubmed as the source of data and presents result by using the lucene morelikethis algorithm and k-nearest neighbor approach (schuemie & kors, 2008). cifariello et al. developed a semantic search engine entitled 84 wiser that finds experts. it models each author’s expertise with a graph by using wikipedia. experts are identified through cooccurrence of searched keywords in their publications and this graph. wiser has an online graphical-based version (https://wiser1.sobigdata.d4science.org/search) which works based on university of pisa publications (cifariello, ferragina, & ponza, 2019). these tools help researchers to find experts. however, when a user with no advanced technical knowledge aims to analyses his or her own data or data related to other academic sources, this method is not helpful. it should be noted that is possible to the adapt proposed method in literature to be used for different data sources, but technical knowledge in this regard is required. bi tools are especially useful for business students to find experts. this study focusses on a process that helps researchers to find experts by utilizing bi tools. the process in this paper can be used by individual who are familiar with bi to find experts. this paper does not present a new method, it shows the capability of existing bi tools to be used for expert finding. 3. process of finding experts using bi tools today, organizations are encountering large sets of data that cannot be used without bi. in order to make better decisions, organizations utilize bi to create knowledge out of their data (chaudhuri, dayal, & narasayya, 2011). a bi solution follows a bi architecture. generally, companies store different data of different sources. however, before a bi solution can be successfully implemented, the entire set of such data must be integrated to a data warehouse by using a special process called etl (extract, transform and load). given the inefficiency of executing queries on an entire set of data in an organization, it is necessary to extract related data before proceeding to executing such a query. once an integrated data warehouse is developed, different servers can efficiently access the data in the warehouse through front-end applications. such an application can be used by particular decisionmakers depending on their roles in the organization (chaudhuri et al., 2011; negash, 2004; sherman, 2014). details of bi are out of scope of the present work, where only the bi tool is used, rather than a full bi implementation. a bi tool is a vendor’s software that is used to develop bi applications or styles (e.g. dashboards or scorecards) (sherman, 2014). figure 1 schematic presentation of the proposed method for expert selection. 85 x table 1 the data extracted from scopus by searching the term “internet of things”. author ids title year source title author keywords records of data 14018777000; 27867946500; 57202208939; 57202211443; 38461465700; multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 2019 advances in intelligent systems and computing classification; internet of things; machine learning; multidimensional wavelet neuron; online learning; pattern recognition 57202334348; fan: framework for authentication of nodes in mobile ad hoc environment of internetof-things 2019 advances in intelligent systems and computing access control; internet-ofthings; mobile ad hoc network; secure permission; security; ubiquitous 57203555315; 56238720400; study and design of smart embedded system for smart city using internet of things 2019 lecture notes in electrical engineering electronic devices; internet of things (iot); smart city other records of data table 2 the cleaned data for the analysis in this study. author ids title year source title author keywords records of data 14018777000 multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 2019 advances in intelligent systems and computing classification; internet of things; machine learning; multidimensional wavelet neuron; online learning; pattern recognition 27867946500 multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 2019 advances in intelligent systems and computing classification; internet of things; machine learning; multidimensional wavelet neuron; online learning; pattern recognition 57202208939 multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 2019 advances in intelligent systems and computing classification; internet of things; machine learning; multidimensional wavelet neuron; online learning; pattern recognition 57202211443 multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 2019 advances in intelligent systems and computing classification; internet of things; machine learning; multidimensional wavelet neuron; online learning; pattern recognition 38461465700 multidimensional wavelet neuron for pattern recognition tasks in the internet of things applications 2019 advances in intelligent systems and computing classification; internet of things; machine learning; multidimensional wavelet neuron; online learning; pattern recognition 57202334348 fan: framework for authentication of nodes in mobile ad hoc environment of internetof-things 2019 advances in intelligent systems and computing access control; internet-ofthings; mobile ad hoc network; secure permission; security; ubiquitous 57203555315 study and design of smart embedded system for smart city using internet of things 2019 lecture notes in electrical engineering electronic devices; internet of things (iot); smart city 56238720400 study and design of smart embedded system for smart city using internet of things 2019 lecture notes in electrical engineering electronic devices; internet of things (iot); smart city other records of data 86 partially inspired by the general bi solution, and its uses for academic research introduced by chaudhuri et al. (2011), sherman (2014) and dadkhah and lagzian (2018) the process of experts finding is schematically presented in figure 1. similar to the work by boeva et al., the process herein uses a keyword-based search to identify experts (boeva, angelova, & tsiporkova, 2017). a basic requirement of a bi process is data. the data may come from different sources. in the field of research, such data may be collected from academic databases such as scopus or google scholar, academic papers, un-published documents, or reports. for the most part, the academic databases provide the user with an option to extract relevant data based on various criteria. for example, upon searching scopus for the term “internet of things”, one can extract the titles, authors’ names, keywords, and/or names of the journals corresponding to the search, resulting in a file of a particular format. figure 1 highlights such data as “extracted data”. when it comes to possibly large offline documents on a local disk, there is a need for methods to either automatically extract such data and print that into a file or do the same manually. various methods have been proposed for keyword extraction in the literature (matsuo & ishizuka, 2004; merrouni, frikh, & ouhbi, 2016; rose, engel, cramer, & cowley, 2010). in such processes, keywords play a fundamental role. the present work is focused on two features in each document: the author’s name and keywords. table 1 shows a summary of the data extracted from scopus by searching the term “internet of things”, as an example. this search was limited to 2000 records by the authors (search date: 7 september 2018). accordingly, the following features were included in the data: author id, title, year, source title, author keywords. upon extracting the relevant data, one should check for possible inconsistencies, errors or related issues. for example, there may be duplicate records to be cleaned up or inconsistencies to be addressed by reformatting the data. the data cleanup stage is critical for the successful accomplishment of the entire process. in the present work, an easy-to-use freeware called openrefine was used to clean up the data ("openrefine," 2018) (verborgh & de wilde, 2013). after the cleanup stage, one should evaluate the acceptability of the extracted keywords. if the keywords were found to be unacceptable, automatic keyword extraction methods can be applied to extract other keywords. table 2 shows the extracted data following the cleanup stage. as suggested by the designation, author ids indicate the authors’ names and help classify keywords by authors. accordingly, a single author id was presented per row. also, correction may be necessary for spelling multiplicity in the source title. the records lacking an author id, with the corresponding field left blank, were deleted in this study. in table 2, each row refers to a particular author and provides details of paper title, year of publication, place of publication, and keywords. at this stage, the dataset is ready for analysis. this paper deals only with the bi tool rather than a full bi implementation. there are different bi tools with different features, and their associated costs vary from free to paid. bi tools provide different features including dashboards and reporting capability. dashboards provide graphical elements for data visualization. reporting capability lets the user use the information element (bernardino & tereso, 2013). both reporting and dashboard elements can be used to find relevant experts. in this paper, a trial licensed version of dbxtra (https://dbxtra.com) was used as we had access to it, and it provided a drag-and-drop option. the documentation of this tool provides a good source for operating the software (dbxtra, 2018). utilizing the software, a constraint was set to consider only records for which at least two features were available: author’s name and keywords. then the authors were filtered based on keywords to find relevant experts. this is why the present method was said to be based on keywords. for example, we filtered authors by selecting the keywords “energy”, “sensor” and “iot”, then the software listed the authors who published papers contained these terms as keywords. in dbxtra, a dashboard is designed using a list box, two combo boxes, a chart, and a pivot table. for the example considered in this research, the list box contained the author keywords values. accordingly, a list of relevant experts could be obtained by applying a filter on this list. as shown in figure 2, a filter was designed to extract the list of authors who had used the terms “energy”, “sensor” and “iot” as keyword. the two combo boxes could filter the data by year and place of publication, with the chart indicating the count of candidate experts. 87 figure 3 shows the dashboard with the experts who had paper(s) containing the following keywords: “energy”, “sensor” and “iot”. accordingly, a list of 66 experts with expertise related to sensors and energy in the iot domain was obtained. there are different dashboard elements that researchers can refer to in order to document and understand their tools. by using such elements, there is the possibility to visualize data and do relevant analyses, then find experts. when the data is clean, the availability of working with bi tools and their elements plays an important role in finding relevant experts from data. based on their needs, researchers should decide which elements are helpful for their analysis add them to their dashboard. also, each element needs to be configured. for example, the chart in figure 3 is configure to count the number of author ids in the data. generally, it counts a distinct value of author ids in all data. the combo box is configured to include data related to the keywords. when a filter is applied on this combo box, the chart counts only the author ids that are accessible through this filter. we do not discuss more about the capabilities of each bi tool and their related elements, as there is good documentation in this regard. 3.1 ranking experts based on the research topic once one is finished identifying the relevant experts, it is possible to evaluate the suitability of such potential experts for the research. the bi tool provides potential experts and next the researchers should confirm result. they should evaluate each potential expert to understand if the person is a suitable expert. as an example, one may need only 10 experts. if the bi tool provided 66 experts (figure 3), one must select the 10 most suitable experts. for this purpose, beginning with an attempt to distinguish between experts based on some general criteria, one should remember that specific research exists with additional features for the purpose. in this study, relevant features were figure 2 the filter applied on the list box to extract the list of authors who had used the terms “energy”, “sensor” and “iot” as keyword. figure 3 the dashboard designed for finding experts who had published paper(s) containing the following keywords: “energy”, “sensor” and “iot”. 88 identified by looking into the literature. accordingly, papers presenting criteria for expert selection were identified (afzal, kulathuramaiyer, & maurer, 2008; afzal & maurer, 2011; benner, tanner, & chesla, 1992; boeva et al., 2017; cameron, alemanmeza, decker, & arpinar, 2007; hirsch, 2005; naeem et al., 2013; quatrini carvalho passos guimarães, pena, lopes, lopes, & bottura leite de barros, 2016); (academia europaea as cited in naeem et al., 2013; pakistan academy of sciences as cited in naeem et al., 2013; fehring as cited in quatrini carvalho passos guimarães, pena, lopes, lopes, & bottura leite de barros, 2016). as some of these papers were subject-oriented, respective criteria were generalized and used as a feature for expert identification and ranking (table 3). researchers may need to define new criteria based on their research. in the next step, an analytic hierarchy process (ahp) can be used to assign weights to the features to facilitate the process of decisionmaking for expert selection. ahp refers to a pairwise comparison method for weighting a pool of alternatives, so as to select an alternative based on particular criteria. using multilevel hierarchic structures, an ahp involves alternatives, criteria, and a goal. it has been widely used in businessand government-led applications (saaty, 1977, 1990, 2013). in this paper, ahp is utilized to rank a set of candidate experts based on particular criteria extracted from the literature, for the purpose of final expert selection. ahp arranges the decision criteria into a hierarchical structure. in this stage, the scale shown in table 4 can be used as a foundation to design a questionnaire for pairwise comparison (saaty, 1977, 1990, 2013). table 3 the features used for selecting and ranking the experts (adapted from the references cited in the text). no. feature description 1 projects to distinguish experts participating in a particular project(s). 2 awards to distinguish experts who have achieved a particular award(s) 3 honorarium to distinguish experts who have contributed into a particular domain(s). 4 affiliations to distinguish experts with a particular affiliation(s), taking the affiliation as a measure of proficiency in a particular domain(s). 5 request for comments (rfc) to distinguish experts who were frequently requested for comments, taking rfc as a measure of experimental skills in a particular domain(s). 6 supervision to distinguish experts who are active in the field of academic supervision of students. 7 collaboration to distinguish experts who have collaborated with others at international level. 8 relevance to distinguish experts who are actually relevant to the considered research. 9 keynote speaker to distinguish experts who have been a keynote speaker in a conferences or other societies. 10 reviewer to distinguish experts with the required deals of skill and expertise to serve as a reviewer for a journal or conference. 11 protocol design to distinguish experts with the required deals of skill and knowledge to design protocol standard(s). 12 distinctions to distinguish outstanding experts, in comparison to peers. 13 citation number to distinguish experts with a particular number of received citations. 14 publication number to distinguish experts with a particular number of publications. 15 co-author network to distinguish experts who have worked with a particular number of co-authors. 16 academic degree to distinguish experts with a particular academic degree. 17 gender to distinguish experts of a specific gender. 18 experience duration to distinguish experts with a particular number of years of contribution into the considered domain. 19 extent of citations in given domain to distinguish experts based on the number of received citations in a particular domain: 𝐸𝑥𝑡𝑒𝑛𝑡 𝑜𝑓 𝐶𝑖𝑡𝑎𝑡𝑖𝑜𝑛 = 𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑟𝑒𝑐𝑒𝑖𝑣𝑒𝑑 𝑐𝑖𝑡𝑎𝑡𝑖𝑜𝑛 𝑖𝑛 𝑎 𝑡𝑜𝑝𝑖𝑐 𝑏𝑦 𝑐𝑎𝑛𝑑𝑖𝑑𝑎𝑡𝑒 𝑒𝑥𝑝𝑒𝑟𝑡 𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑟𝑒𝑐𝑒𝑖𝑣𝑒𝑑 𝑐𝑖𝑡𝑎𝑡𝑖𝑜𝑛 𝑖𝑛 𝑎 𝑡𝑜𝑝𝑖𝑐 20 impact factor of publication journals to distinguish experts who had papers published in journals of particular impact factor(s). 21 h-index to distinguish experts based on the metric proposed by hirsch. this metric indicates the j number of papers that received j or higher number of citations. 22 researcher profile to distinguish experts based on their profile in terms of relevant skills, keywords, and topics of interest. table 4 scales for comparing alternative experts (saaty, 1977, 1990, 2013). numeric scale meaning 1 the two alternatives are equally important. 3 an alternative is moderately more important than another. 5 an alternative is essentially more important than another. 7 an alternative is strongly more important than another. 9 an alternative is extremely more important than another. 2, 4, 6, 8 intermediate values between the above milestones. the yellow blocks in figure 1 show the corresponding steps through the whole process. if there is uncertainty in decision making, fuzzy ahp can be used. it uses fuzzy numbers as the numerical scales (özdağoğlu and özdağoğlu, 2007; wang and chin, 2011; ramík and korviny, 2010). the value of features in table 3 should be gathered or calculate manually for each candidate expert, but it is possible to use a programming language to automate some tasks. in order to implement ahp in this study, the experts list and the features described in table 3 were taken as the alternatives and criteria, respectively (figure 4). then, two pairwise comparison questionnaires can be designed for the considered criteria and experts. the questionnaires should be presented to a number of university professors and researchers in the field of research. the data extracted from the questionnaires can be analyzed using different tools such super decisions, a tool for multi-criteria decision making (superdecsion, 2018), and the results should be used to assign weights to the criteria and experts. researchers usually need to select and rank such criteria for their research activities, as may be necessary depending on the specific research question(s). figure 4 shows the hierarchy of the ahp model developed for expert selection. in this study, weights are calculated for each criterion and the bi tool provides a list of potential experts as alternatives for this model (figure 4). in a final step, the experts were ranked based on the criteria. in ahp, the consistency ratio shall be equal to or smaller than 0.1; otherwise the result of pairwise comparison may be unreliable (saaty, 1977, 1990, 2013). indeed, the consistency ratio increases when increasing the number of elements in a comparison (benítez et al., 2011). accordingly, the use of 22 criteria or an expert list with many candidates in the developed ahp model may lead to a consistency ratio exceeding 0.1, indicating unreliable results. however, researchers could choose to select only a subset of the 22 criteria, depending on the scope of their research, or narrow their queries to find a smaller number of experts. other methods have also been proposed for addressing the problem of inconsistency in ahp (benítez et al., 2011; benítez et al., 2012). the value of features shown in table 3 should be determined manually by researchers, however it is possible to gather values for some of the features automatically. for example, hindex and total citation count, number of figure 4 the ahp model developed for expert selection. 90 publication and co-authors can be gathered through scopus. by using bi tools, it is possible for researchers to do more advanced analysis on their data. for example, by extracting data from scopus by searching the term “internet of things”, it is possible to find experts with different conditions such as: experts who published a paper about the internet of things and started their publication in this topic at least 5 years ago and have a total citation count on this topic above 1200 and have the article type “journal paper” and are affiliated to a specific country and published by a specific publisher and published in a top information system journal. it is possible to add four columns including journal impact factor, author h-index, publication number, and total number of coauthors to the extracted data from scopus. here we attach new data to the extracted data from scopus. this data is the value of the four features discussed in table 3. now, the previous query could be more advanced as: experts who published a paper about the internet of things and started their publication in this topic at least 5 years ago and have citation counts on this topic higher than 1200 and their article type is a journal paper and are affiliated to a specific country and published by a specific publisher and published in a top information system journal and published in a journal with an if higher than 1 and with a total number of published papers higher than 10 and author’s h-index is higher than 5 and total number of coauthor is higher than 12 this process can be done through other tools and data sources. to evaluate this expert finding process, researchers used two other tools and tried to find potential experts who are familiar with both the internet of things (iot) and patient monitoring. the researchers are interested in experts who received at least 700 citations on a publication in this topic and published it at least five years ago. they used publish or perish (publish or perish, 2018) to extract data from google scholar and metabase (metabase, 2018) to analyses the data (search date: 10 november 2018). as publish or perish does not provide keywords for each paper, there are two option to find keywords: 1) use methods for extracting keywords from papers, 2) narrow the search by defining all keywords then analyzing the result instead of doing a broad search and then limiting result by keywords. figure 5 shows the output of the analysis in metabase. based on this analysis, the researchers found 15 potential experts. in the extracted data from google scholar via publish or perish, there are other features including source title, publisher, article url, cites per year, author count, and title of papers. this means that it is possible to use these features to do more advanced searches to find potential experts figure 5 identified experts using metabase. 91 from this data. after finding expert via the bi tool, now we can manually review experts and use the table 3 criteria to confirm experts with regard to our research. experts can also be found via pubmed (https://www.ncbi.nlm.nih.gov/pubmed/) as the source of data, and knowage (https://www.knowage-suite.com/site/home/) as the business intelligence tool. we searched for "wireless sensor network" (search date: 24 july 2019) and download all 769 result as the xml file. by using pubmed2xl (available from http://blog.humaneguitarist.org/projects/pubm ed2xl/), the xml file was converted to an excel spread sheet (isaak, 2016). by using openrefine, the data was clean. as with jane, it is possible to find potential experts based on the relevance of keywords. in pubmed, data is sorted according to its relevance to the search term, then downloaded. by having relevance of data to searched terms, it is possible to find experts based on relevance. by doing this, it is concluded that from the top 20 identified potential experts in knowage, 15 of them were also in the list of retrieved experts from jane. the difference was their rank compare to the jane result. it is possible to get a list of potential experts who are familiar with wireless sensor networks by using the extracted data from pubmed. for example, we can find all individuals who have at least four publications about wireless sensor networks and at least one publication in the top 300 results, based on relevance. it is possible to do a more advance query to find individuals who have at least four publications about wireless sensor networks and at least one publication in the top 300 results based on relevance and at least one publication published in a journal in the first two quarters of the scimago journal ranking (sjr). this query needs to merge new data with extracted data from pubmed. the sjr data can be retrieved from the scimago journal ranking website (available from https://www.scimagojr.com/journalrank.php). then it is possible to merge the data together by using available tools such as openrefine. figure 6 illustrates the dashboard in knowage for finding such experts. this dashboard also has extra filters to find experts such as the first year of publication and the number of publications in a top quarter journal. it also shows some information about experts and their relevant papers. the process discussed in this paper was also tested to find research method experts from a personal repository, and another study about knowledge management. using this method was helpful for both this study and to simplify the expert finding task. in the earlier expert finding task, eight potential experts of the former 10 potential experts were identified. the main advantage of the process compared to most expert finding methods is that it has lower requirements for individual bi tool technical knowledge. bi tools currently support different options (for example drag and drop) to simplify the data analysis task (smuts, scholtz, & calitz, 2015). by using a bi selfservice tool, individuals can use bi tools with less technical knowledge (imhoff & white, 2011). figure 6 a dashboard in knowage for finding experts. in this dashboard, an expert has been selected and the information is shown. 92 x table 5 comparison between jane, wiser and the proposed process in this paper. this table considers the currently available tools, not the techniques that are behind them. for example, wiser can be used on different data sources, but in the currently available version, it is based only on university of pisa publications. publish or perish is not an expert finding tool, it is an effective citation analysis tool that can be used for expert finding purposes. we recommend to import output data of publish or perish in bi tools for expert finding purposes. name* data source level of required knowledge capability for defining criteria by user visualization capability expert ranking jane pubmed no special knowledge, easy to use limited criteria can be defined based on advanced search option in the tool ui no yes, automatically wiser university de pisa publications no special knowledge, easy to use there is no option for defining criteria in wiser ui yes yes, automatically publish or perish web of science, scopus, crossref google scholar, and microsoft academic search. it is also possible to import external data primarily knowledge about scientific bases and citation analysis is necessary user can define some criteria no it is possible to rank expert based on output values. for example, sorting based on h-index proposed process publications data from different sources such as scopus, or google scholar primarily knowledge about data, scientific databases and data tools necessary user can define different criteria as there is data to support such criteria yes, by using bi tools visualization elements yes, manually by using ahp and automatically by defining in bi tools this process can be compared with two main expert finding approaches: manual expert finding by searching in scientific databases and proposed technical methods in the literature. researchers can use scientific databases such as google scholar or scopus to search for keywords and manually inspect search result to find experts. the process in this paper has other advantages including: • in the manual inspection of result, researchers cannot consider all results and are limited in the publications that they can analyze in terms of time and effort. • researchers cannot execute an advance query on search result without utilizing bi tools without advanced technical knowledge. • when data are collected from other sources, such as organizational publications or internal repositories, it is not possible to use scopus or scientific databases to import data for analysis. • when data come from internal repositories, they may be in different topics and domains, thus, manual inspection of such data may require significant time and effort to assess. in comparison with proposed technical methods in the literature for expert finding, this process is easier in terms of implementation for researchers who have bi knowledge but do not have advance technical knowledge. if technical methods are the tool implemented and are publicly accessible for all researchers, they can be compared in terms of capabilities and advantages with bi tools. for that purpose, a comparison between jane, wiser and the process in this paper is shown in table 5. the process in this study may be limited to cases where data is related to the potential experts’ publications. future research can focus on using bi tools to find experts based on data gathered from social networks or community question answering websites. in this paper we only focus on the usefulness and level of required technical knowledge to evaluate this process with the proposed methods in the literature. the main goal of this study is to propose a simpler expert finding process, which provides acceptable results based on analyzing publications, not providing a comprehensive expert finding method. the 93 contribution of this research is a discussion on a process for finding experts by using bi tools. this paper does not propose a new tool or method, but it introduces the capability of existing bi tools for finding potential experts. 4. conclusion given that the existing expert selection methods are usually impractical for researchers without deep technical knowledge, an expert selection process is discussed here for individuals who are familiar with bi tools. taking advantage of bi tools, the process was found to have a large potential for expert finding. the process will be helpful in research that aims to gather data from expert participants. here, we may need the opinions of experts and finding these experts is key. the process in this paper requires a certain level of technical knowledge, because the method for expert finding is based on computers, which are technical in nature. the primarily knowledge about data, scientific databases and data tools is necessary for individuals who aim to use bi tools for expert finding. however, such knowledge can be obtained by participating in a workshop or reading relevant books and tutorials. this process is simpler, when we are aware of bi tools that support different options to simplify tasks, such as providing drag and drop options (smuts, scholtz, & calitz, 2015). in addition, there are efforts for providing self-service bi tools which individuals can use with less technical knowledge (imhoff & white, 2011). however, utilizing expert knowledge of programming helps researchers to collect more complete data and execute more complex queries. also, for advanced data analysis, the knowledge of programming may be essential. researchers, by improving their skills, could gain more benefit from this process. bi tools have the potential for data visualization and analysis, but related skills are required for such capabilities be reachable. in this paper, bi tools have been used to find an early list of potential experts from the data, then ahp helps to manually distinguish them and produce a final list of experts. based on available data, a primary filtering of the list of many experts is done through bi tools, then by using ahp, a final list of experts is identified manually. so, queries in the bi tool may be simple, for example finding experts who have a total of more than 1000 citations. such queries will make a limited list of potential experts, which is usable in ahp. the threshold and criteria for early filtering of experts using bi tools can be defined by consulting with experts. all thresholds in the presented cases in this paper are examples. in the actual expert finding process, consulting with experts to identify threshold and selection criteria based on available data for early filtering of experts is required. this process helps researchers to find experts for their work, even they are not experts in bi tools. however more knowledge and skills are needed for bi tools, to make them more successful in finding suitable experts. acknowledgements it is our pleasure to thank dbxtra company for their support and providing a trial license of their tool for our work. we also appreciated assistance of researchers who helped us to understand their methods or answered our questions regard to this research. they are: professor robert davison, city university of hong kong; professor dr. muhammad tanvir afzal, department of 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(2017) business intelligence and smes: bridging the gap. journal of intelligence studies in business. 7 (1) 70-78. article url: https://ojs.hh.se/index.php/jisib/article/view/201 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription https://ojs.hh.se/index.php/jisib/index information: business intelligence and smes: bridging the gap ekavi papachristodouloua, margarita koutsakia and efstathios kirkosa,* adepartment of accounting, atei of thessaloniki, greece; *stkirk@acc.teithe.gr journal of intelligence studies in business please scroll down for article https://ojs.hh.se/index.php/jisib/index business intelligence and smes: bridging the gap ekavi papachristodouloua, margarita koutsakia and efstathios kirkosa,* adepartment of accounting, atei of thessaloniki, greece *corresponding author: stkirk@acc.teithe.gr received 15 february 2017; accepted 1 march 2017 abstract according to research findings, small and medium enterprises (smes) are facing problems such as an excessively large volume of data, lack of information and lack of knowledge. therefore, in order to make decisions on time, the managers of smes use mainly their experience, which implies a high risk of failure. business intelligence (bi) is a useful and helpful tool, which brings many advantages and benefits to businesses. however, like any technology, it is accompanied by some limitations that must be overcome in order to help businesses to develop. this paper summarizes current research findings addressing the issue of the development and application of business intelligence systems for smes. the issues addressed are models for the estimation of the readiness of a sme to establish bi tools, alternative bi solutions for smes, benefits and challenges of bi in smes, implementation methods for bi systems in smes and finally, bi systems in cloud computing platforms. research papers dealing with these issues are analyzed and the results are presented. this paper contributes to the understanding of problems and potentials regarding the development and application of bi systems in smes. keywords business intelligence, competitive intelligence, smes 1. introduction despite the economic size of each company, access to relevant and important information is very important to ensure the success of the acquisition of a market share. business intelligence is considered a very important tool to achieve such a goal. according to the gartner’s surveys, business intelligence (bi) and analytics systems are ranked as the top technological priority of companies in the last years worldwide. the main objective of bi systems is to facilitate the decision making process by providing quality information, based on the analysis of large amounts of internal and external data. however, bi systems are characterized by their difficulty and complexity to handle. also, economic factors are the ones that make many sme’s administrations fail to proceed to the acquisition of a system. normally, the development and maintenance of a bi system requires considerable funding. moreover, the majority of smes do not have a specialized it department. many smes are run by the owners, who might not have advanced technological knowledge. it is known that the applications of bi are not primarily accessible to smes. the available systems are expensive, difficult to use and require excellent technological training of business staff. commonly, these applications meet the needs of large enterprises, that have all the appropriate resources for their proper functioning. despite these limitations, better information provision, facilitated by a bi system, may lead to better decisions and become a consistent competitive advantage. a prerequisite is the successful confrontation of problems, stemming from the specific characteristics of smes. with the evolution of technology, bi suppliers have designed and journal of intelligence studies in business vol. 7, no. 1 (2017) pp. 70-78 open access: freely available at: https://ojs.hh.se/ 71 developed applications and tools to meet real small businesses needs. τhere are bi systems that are available online. these systems are affordable, easy and they belong to the category of cloud systems. such solutions are suitable for smes, as they do not incur additional installation and maintenance cost. tools and it system applications are not considered a privilege of large companies, as the services offered are designed for the needs and requirements of smes, which can be just as competitive and successful. the present paper addresses a wide spectrum of issues related to the application of bi systems in smes. bi practitioners and sme managers might find this brief but concise summarization useful in their attempts to apply this cutting-edge technology in this specific business sector. 2. readiness of an sme for bi hidayanto et al. (2012) conducted research to assess the readiness of a sme to establish a bi tool. for the development of the framework, the researchers used as their tools the critical success factors and the analytical hierarchy process. they focused on three categories of functions found in an sme. the framework formed by researchers primarily focuses on three main categories that are identified, which were developed and evaluated. these categories are organization where nine relevant factors were explored, process where four factors have been analyzed and technology where five factors were explored. in this study the researchers initially make a theoretical presentation on the development of the model and then they proceeded to a more detailed description. finally, the proposed framework is applied to a real case of a sme. through this research, they explored and evaluated the critical success factors, namely the elements that are necessary to ensure the success of such a venture in the evaluation and acquisition of a bi system. we chose the analytical hierarchy process method for the development of the proposed framework, because this method allows the analysis of a complex problem in a more simple structure and selects the most effective solutions that lead the administration to better decisions (taylor 2005, cheng 1997). the researchers define the three steps of this method. the first step is the decomposition of the model into three levels (objective, criteria and alternatives). in the second step, the comparisons between pairs of criteria and alternatives were created. the comparison was made with a rating scale of 1-9. the third and final step is the weight of each pair. this method was used to give the weight of each factor based on specific criteria and the better alternative was the one with the higher weight. to be valid comparisons, the researchers chose values less than 0.1 (consistency ratio <0.1). then, they began to develop a framework that would apply in a real and not virtual enterprise. the target frame raised the level of readiness of bi in an sme (level 1). criteria joined the function categories of business (level 2), while the critical success factors were considered alternatives (level 3). for the purpose of the study, hidayanto et al. (2012) used 18 factors based on the scientific literature references by atre (2003), williams and williams (2004) and yeoh and koronios (2010). for the category of organization, the critical success factors selected were committed management support and sponsorship, clear vision and well-established business case, strategic alignment, effective business/it partnership for bi, bi portfolio management, continuous process improvement culture, culture surrounding the use of information and analytical applications, cross-organizational collaboration and decision process engineering culture. for the process category, the factors chosen were balance team composition, availability of skilled team members, business driven development approach and iterative development approach and user oriented change management. for the technology category business driven scalable and flexible technical framework, sustainable data quality and integrity, importance of metadata, bi and dw technical readiness and the silver bullet syndrome were selected. once the problem decomposition process was completed, the researchers proceeded to create pairs of criteria and alternatives, with the help of four specialists in bi. experts, using the delphi technique, gave values to results which arose from four comparisons: i) the inter-category pairwise comparison, ii) the pairwise comparison for organizational category, iii) the pairwise comparison for 72 process category and iv) the pairwise comparison for technology category. finally, the validity of comparisons of each class of the consistency ratio was calculated (consistency ratio < 0.1) and the weight of each factor was calculated. to give a more accurate and fair decision about the value of each factor in business, the researchers used the e-gp model (electronic government procurement) readiness selfassessment. thus, they evaluated the level of readiness of each factor using a scale (0-3) measuring each factor’s readiness level. the results of this research reaffirm the findings of previous research, mainly conducted by williams and williams (2004) and yeoh and koronios (2010). according to the bi experts the most crucial factors in developing bi systems are the following:  strategic alignment between business and it. consistency is required between business strategy, organization and processes and it strategy, infrastructure, organization and processes.  managements support and sponsorship. the determination of the management to support the project secures the availability of resources such as funding and human skills.  clear vision and well established business. a clear strategic business vision is required. such a strategic vision is needed for the establishment of a solid business case. misunderstanding of the long-term vision and objectives may derail the bi project. other important issues are the composition of the bi team and the quality of the data. it is critical to include business experts who understand the strategic vision in the bi team so they can foresee the organizational challenges. after the comprehensive development of the model, the researchers applied it to a real sme. they randomly chose an sme in indonesia, which did not use a bi system. through semi-structured interviews they assessed the level of preparedness of each factor separately and then multiplied it by the weight factor of the level of preparedness. after, they added all the results to give the final grade. the company managed to collect 58.05%. the result showed that although the company understood the importance of the factors for the implementation of bi, it had to face some obstacles and then proceed to the implementation of bi. by applying a similar model, businesses will be able to analytically evaluate their readiness and then they can decide whether they will be able to deploy bi software, as they may be confronted with unexpected situations that may arise during the project. management should be aware of the real needs of the enterprise and adopt corresponding services to manage and support them. 3. bi solutions for smes tutunea and rus (2012) study alternative bi solutions for smes. in their research, they tested and evaluated the available commercial bi solutions, open source solutions and it systems tools offered for small and medium businesses. the software tested was available on the websites of companies that provide bi solutions. for the evaluation of commercial solutions, they set two criteria. the first criterion set was the complexity that characterized the provided solutions. the variables set for this criterion were the functionality, maintenance and system support, accessibility and user interface and the final purchase price. the second criterion was characterized as the reputation of the company that was on the market. by conducting this research, they have concluded that, depending on company size, the management and some specific internal factors, there are three types of bi solutions that allow companies to choose the one that best fits their requirements and needs. as a first choice, they ranked the solutions developed within the company and did not involve specialized bi providers. these solutions mainly focus on static or dynamic analyses of the data with the help of excel spreadsheets, open office calc, lotus 1-2-3, computer graphics, and what-if type analysis. such bi solutions are part of saas (systemas-a-software) and have gained ground in their acquisition by smes. this is because the final purchase cost is low, it is easy to use and the installation time is very fast. also, there is no further staff training. the products are hosted in a secure online platform where the company has access without leaking data. as a second option, the researchers ranked the commercial bi solutions. of the software that was tried, they found that there are two types of providers. 73 the first category includes specialized software companies that provide exclusive bi tools. businesses rely on a specialized team to design the software according to their needs and requirements. such providers are information builders, microstrategy, and qlickteck. in the second category, they identified companies that have a greater variety of interests. in this category are the bi solutions that are aimed at a particular sector such as education, banking or insurance systems. such providers include oracle, microsoft, sap, and sas. as a third option, they ranked bi solutions and open source solutions. the motivation that drives companies to proceed to the acquisition of such solutions is the low cost. therefore, the architecture, the functionalities and their environment are considered to be the main criteria on which smes choose a bi tool. providers of open source software are actuate, jaspersoft, pentaho and spagobi. enterprises can choose a suitable solution, taking into account the quality of the information provided, data analysis tools and visualization, cost, accessibility and effectiveness of the decisions. thus, companies depending on resources choose the best solution that will bring advantages 4. benefits and challenges of bi in smes in this section two surveys aiming at identifying the benefits and challenges of bi adoption in smes are presented. also, through the research, they identified the sections of their application. for this purpose were used two research studies by scholz et al. (2010) and nenzhelele (2014). scholz et al. (2010) were able to identify the beneficial factors, challenges and types of smes that adopt bi tools. the authors study the adoption of bi by german smes by examining 214 firms in saxony. the method applied was based on references of other authors and researchers. the study was based on exploratory factor analysis (efa), which identifies the perceived benefits and challenges of implementing bi. initially, to verify the suitability of the sample they used the kmo measure as proposed by kaiser and rice (1974). then, they applied the msa measure to validate the sample and then applied the pca measure to extract relevant information. a number of factors have an impact on businesses, including applied graphics and an eigenvalue with ev>1 according to thompson and daniel (1996, 200). after identifying the strengths and challenges, they focused on identifying the type of businesses applying bi. for this, they used a cluster analysis, namely the k-means algorithm and the proximity measure ed. the numbers of clusters were defined by the use of a fc measure (fusion coefficient) (toms et al. 2001). to collect the necessary data, the researchers assessed 4960 saxon firms, where the operators responded to an on-line questionnaire via e-mail, which covered a wide range of issues focusing on bi. the questionnaire was validated in two ways (fowler 2001): it was originally created and written by experts in the field of information technology and then evaluated by conducting a preliminary test. in this way, they managed to ensure that respondent companies fully understood the terms and the importance of the questions in the questionnaire. in total they collected 452 questionnaire responses. of these 452 companies, 214 already had a bi tool. in these companies, they applied the technique of cluster analysis, to find the kind of companies that implement bi. from the research conducted, they managed to identify three main beneficial factors including improvements to data support. in this factor the main benefits are reduced effort of data analysis and reporting, reports are available faster and with better quality, easy access to information and flexible reactions to new information. the second beneficial factor was improvements to the decision process where the main benefits are that business decisions are being eased by more precise and current data analyses, risks and chances are supported in a higher level and the company’s results are improved. the last beneficial factor is savings and it’s characterized by savings on personnel in different departments that can be achieved, competitive advantages can be achieved and cost savings in it that can be achieved. on the other hand, they were able to identify the main challenging factors. these were the challenges depending on usage. the main challenges are that the handling of the solution is too complicated and reports are to complex, data is poorly structured, capabilities do not cover business needs and bi staff are not qualified enough. 74 challenges related to data such as software errors, inadequate security function, range of bi tools and functions don’t match with the business needs. the last challenging factor is the interface challenges. in this factor the main challenges are limited data export and also that the data are not usually enough finally through the cluster analysis, they were able to identify four categories of companies using bi (rapidly growing b2c, lightly regulated companies with a focus on collaboration, service-oriented b2b companies, and high-regulated productoriented companies). the research carried out by scholz et al. (2010) showed that companies and organizations that do not have a bi tool should not only focus on the positive effects that could generate from its use. they should study and all those challenges and constraints that may arise, e.g. software errors, reduced resources, and unnecessary costs. through cluster analysis, they concluded that productoriented companies have better prospects in the application of bi. also, through cluster analysis bi providers can identify the real needs of smes. in the second examined paper, nenzhelele and pellissier (2014) identify which business areas mainly applied business or competitive intelligence and whether they understand the concept. according to bernstein (2009) competitive or business intelligence is formed by processing the data, which produce information, processed information which produces knowledge and processed knowledge which leads to intelligence. the data collection was done by using a questionnaire sent to a hundred smes in the greater region of south africa. their original purpose was to discover whether smes are aware of bi and then to identify the main challenges they face. also, they tried to find the sections where companies apply bi. from the research, the researchers concluded that although companies understood the importance of bi, they did not apply an equivalent tool. businesses using a bi tool asked about the main challenges and discovered that three restrictions are common to all businesses. the lack of time working with the system shows that small businesses do not have the needed time to manage a competitive intelligence system, the lack of human resources and economic factors were the main problems they face. the application area is not located in a particular part, but somewhere independently. this is because smes have no formal organizational structure, but one very important role is the application of competitive intelligence in market research and marketing department. apart from the various challenges and benefits identified, smes are trying to be more competitive to be able to achieve higher profits and more sales. in this case, it is stated that smes choose to spend more money and establish bi software in market research and marketing departments. 5. implementation methods for bi systems in smes frion and yzquierdo-hombrecher (2009) present a new competitive intelligence model for the management of large amounts of data and information entering business. initially they conducted a literature reference which focused mainly on the concept of bi. the second method was based on their long experience in competitive intelligence systems and their application mainly in small businesses. also, through their experience, they managed to develop and present a new information management model: the acrie model. from the literature, research is found that studies and research are carried out based on large companies. for this reason, the authors noticed that there are many different ways and methods to apply competitive intelligence. the literature survey was completed with the presentation of the new method and the new competitive intelligence information management model was developed. the model was called the method acrie. the basic principles of this model are less data, more inductive reasoning tests and analysis and less information, more curiosity about the problem, focuses on human behavior and on information approach through questions. the method takes place in three steps. the first step is a formal command formulation and an informal discussion to reformulate the first vague intent. the second step is a question plan, which consists of three levels and is formed by ten questions. this is to help the manager reach his expectations in a specific field. the third step consists of ten seeking plans, one for each question. it takes a few weeks to prepare a small company for the acrie method. when the preparation process is achieved, experts 75 implement the proposed model in the company. according to frion and yzquierdohombrecher (2009), a small company is doing bi when the company is running an outgoing coordination prior to the five mail skills of bi activity: questioning, information seeking, information treating, distribution and protection of information. the large amount of data and information entering business is not always a good phenomenon. this is why the authors developed a new information management model. through this model, the acrie model, the leader creates plans and plans with the rest of the team to help to reach a better result for the company's interest. this method is used by small and large companies, with various tools to suit the needs of each company individually and to ensure the continuous coordination of the five main skills of competitive (business) intelligence. the acrie method is a proposed model of information management that can manage data and also focus on people who are involved in this process. 6. cloud computing and bi in the present section two papers, which aim to present bi in cloud computing platforms are discussed. agostino et al. (2013) identified the key success factors in their study for the adoption of cloud bi for smes and their characteristics based on the needs of bi users and suppliers. past approaches based on scholz et al. (2010) and yeoh and koronios (2010) have discovered three categories of factors. the first category is distinct from the organization, the second by processes and third by technology. according to rockart (2009), the critical success factors represent a number of areas where satisfactory results will ensure a competitive position for the individual, the enterprise or a company’s section. little has been said about the association of smes with bi software in a cloud level and therefore there is no framework to analyse their connection. the categories of factors to assess the saas software level cloud according to godse and mulik (2009) are functionality, system architecture, use, reputation, costs and risk. researchers’ methodology consists of two stages. the first stage was characterized as qualitative. researchers interviewed four experts (bi suppliers and bi users) in cloud bi software. at this level, they tried to identify the weaknesses and the improvements through interviews given by bi users and suppliers. critical success factors are divided into six categories: performance-functionality, integration, adaptability, reliability, support and cost of ownership. the second stage was considered to be a quantitative stage. at this level, researchers tried to rank the key success factors for the adoption of a bi system. for this, an electronic questionnaire was created, which aimed to rank the importance of success factors. the use of cloud bi for smes was always a challenge for researchers, as the number of enterprises applying such a system was limited. in this stage, scholars gathered information from 36 companies through a questionnaire on the issue of bi. the questionnaire was created by bryman and bell (2011). the findings of the first phase were that the main factors for the adoption of bi systems was that they must have reduced costs, installation time and implementation and a quick response to user requests. the results of the second stage showed that the main factors to be taken by an enterprise bi are the functionality of the system, continuous data access, rapid response to user requirements, a large amount of data management and implementation costs. both stages have shown that users are looking for easy tools to use as they have the necessary expertise. the economic factor plays a very important role because smes have very limited resources. cloud software is an economic solution, which outlines additional requirements adopted by smes. both stages have shown that users are looking for easy tools to use as they have the necessary expertise. the economic factor plays a very important role because smes have very limited resources. the cloud is an economic solution, which outlines additional requirements adopted by smes. sheshasaayee and swetha (2015) present the challenges of bi software combined with cloud computing. the combination bi with cloud software has many important advantages. the most important advantages are the speed of construction and speed of services, reduced costs of organization and payment of services depending on the use (henning and kemper 2010). 76 over the years, it has been observed that the application of bi at the cloud level is increasingly of interest in the field of information technology. the goal of cloud services is the acquisition and provision of resources to meet the maximum requirements and needs of users. according to scholars, cloud software consists of a three level structure: infrastructure, platform and software. cloud software is easy to use and flexible, but has some problems. the most common problems according to the scholars are the different compatibility models, risk performance, and the variable price and cost ratios. according to sheshasaayee and swetha, bi refers to technologies that convert users’ available data resources and exportable information into business solutions. the cloud combined with bi is considered to be one of the most modern technologies in the field of information technology and this is the main reason it is facing some serious challenges. in studies, it is argued that the combination of bi and cloud software encountered some obstacles. the main challenges are the introduction of new technologies to the general public, the absence of idealized suppliers of specific software systems, the lack of control over the cloud services as all activities are done online and the movement of some compatible models that attempt to replace the actual abilities of cloud systems (henning and kemper 2010). this together leads to the conclusion that cloud software is aimed at companies with reduced financial resources, such as smes, but is easy to use and functional. the functions that cloud bi offers have been designed specifically for the needs of smes. 7. conclusions through studies and surveys, many researchers have reached the conclusion that smes are the largest part of the market, and therefore of the economy, in most european countries. they are the driving force of the economy as they provide the majority of jobs in the private sector, so they compete with larger companies. the main tool in the development and support of competitiveness among smes is bi. the decision support systems that are based on computer applications offer tools so that businesses can process data to extract information and to make better business decisions many researchers have researched the topic of bi in smes as well the benefits and challenges arising from the implementation of bi. hidayanto et al. (2012) shaped and developed a framework so that businesses can know in advance their level of readiness to adopt bi systems, as to avoid unpleasant results. tutunea and rus (2012), undertook more commercial research. they focused on the available bi tools and their capabilities according to the type of business and their needs. scholz et al. (2010) found that the main beneficial factors from the application of bi are the improvements in data support, improvements in decision support and economic factors, while the main challenges they face are the errors and failures of software, the complexity of handling the failure of appropriate data and often inadequate data protection. nenzhelele and pellissier (2014) were able to identify in which sections companies applied bi and what challenges the enterprises face. the main application areas are market research and the independent sector, since businesses have no formal and specific organizational structure. the challenges identified in this study proved to be the lack of resources, lack of time to learn and economic restraints. decision support systems don't only have benefits but they also have challenges and obstacles. frion and yzquierdo-hombrecher (2009) created a new competitive intelligence model to help companies reach better decisions by managing a large volume of data. the proposed model (the acrie model) takes a lot of time to implement and, according to previous studies that have been conducted, smes don’t have the necessary time to deal intensively with the software learning process. some researchers have focused on the new technology of cloud computing combined with bi. agostino et al. (2013) identified the key success factors from adopting bi in cloud software. through questionnaires and interviews given by businesses using similar systems and bi suppliers, they concluded that continuous data access, ease of use, reduced costs and quick installation time, implementation, and responsiveness are the main features that lead users to purchase software. but even this technology faces some 77 challenges. according to sheshassayee and swetha (2015), the main challenges of cloud software are the extra costs that may arise from their use, the limited checking services and the non-establishment within the general public. the main tool to create and support competitiveness is considered to be bi or otherwise competitive intelligence. decision support systems based on computer applications offer the necessary tools and the right infrastructure so businesses can process the data, extract relevant information and come to appropriate conclusions and therefore make better business decisions. until a few years ago, the acquisition of bi systems by smes was considered difficult. also, business owners did not consider it useful to obtain such a system. but over time, the evolution of technology and the continuous increase in competition, led to bi systems becoming a necessary tool for facing businesses’ competitors and helping smes to evolve. however, smes have different needs compared to larger companies. this is the main reason bi vendors design and create software that is affordable, convenient and effective so as to meet the needs of smaller companies and organizations. such technology is called cloud computing, and it is easy to use, economical and provides many features. some of the advantages of using decision support information systems are the conversion of data into useful information in order to draw useful conclusions, the understanding of key elements in a company (e.g., customers, suppliers, or resources) and the use of a common code of understanding between different departments, the company's profit growth and the creation of a competitive advantage. it is understood that bi is an essential part in the development of smes. businesses will be able to make better business decisions and compete more effectively by choosing an appropriate system from a wide variety of programs based on the programs’ weaknesses and challenges. of course, the results from the use of the systems are not initially visible, but are perceived gradually. businesses initially make slow but steady movements to become familiar with system tools. then they take into account the system outputs that lead to decisions. finally, once the companies are familiar with the system, all decisions are made by it. once one knows the challenges and obstacles that may arise they will be in a position where they are prepared to face any obstacle presented to reach a satisfactory result through the application of bi. 8. references agostino, a., solberg søilen, k., & gerritsen, b. 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(2010). critical success factor for business intelligence systems. journal of computer information system, 50(3), 23-32. 44 an overview of articles on competitive intelligence in jcim and cir klaus solberg søilen, halmstad university, school of business and engineering se-301 18 halmstad sweden klasol@hh.se received december 28 2011, accepted march 25 2013 abstract: this paper presents an overview of fifty-one articles from the journal of competitive intelligence and management (jcim) posted on the strategic and competitive intelligence professionals´ webpage. it also looks at sixty-tree randomly selected articles out of about 250 from the competitive intelligence review (cir), published between 1996 and 2001. the first analysis is based on a comparison with eleven different variables that have been picked out from each of the articles. findings: the most common country where the authors’ come from is the united states of america. sixty-one of the eighty-three authors have a higher degree, first of all mba and/or ph.d. north american authors have a higher degree than authors from europe. authors from north america have contributed with fifty-seven percent of the proposals for further research of a total of twenty-one proposals. fourteen articles have a professional author. the rest are academic contributions. the main topic in these articles is how to develop competitive intelligence (ci) but also how to define ci. the articles have different methodological approaches, qualitative and quantitative. seventy tree percent have a qualitative approach and of those there are thirty-seven percent that also have a qualitative approach. for the second analysis dedicated to cir one clear conclusion points to the large number of articles which resulted from the introduction of the economic espionage act of 1997. most contributions at cir come from practitioners. 1 keywords: journal of competitive intelligence and management, competitive intelligence review, historical method, review 1 thanks to lovisa andreasson, isabell bergsten, johanna ossiansson, fredrik garnäs, erik hagberg and niklas radhammar for help with this article. available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2013) 44-58 mailto:klasol@hh.se https://ojs.hh.se/ 45 1. introduction 1.1 the aim of this paper the purpose of this study is to present an overview of scientific articles in the journal of competitive intelligence and management (jcim) and the competitive intelligence review (cir). the analyses were done to bring clarity on key variables identified for this study. part 1.2 – 3 are concerned with jcim. part 4 is concerned with cir. 1.2 focus the first table (table 1.) show empirical findings divided into eleven variables. these variables form the basis of the analysis. these are; geographic, focus, theoretical, empirical, qualitative, quantitative, proposals for further research, the author’s background, gender, nationality and education. geographic means were the study takes place and were the research is done, focus is the authors main topic in the article, theoretical/ empirical/ qualitative/ quantitative these are variables that show how the articles are built-up and which method have been used. proposals for further research are suggestions for continued research. author’s background tells us if the author works at a university or for a company. gender is the sex of the author(s). nationality tells us where the authors are citizens and education is the author’s degrees. 1.3 report structure the report is structured as follows: section 2 is methodology. in section 3 empirical findings are represented. this includes a table of all the scientific articles that have been investigated. other tables and diagrams can be found here, containing comparisons with selected variables. conclusions from the empirical findings are placed in this section. section 4 contains an overview of article published in cir. conclusions which summarizes the papers findings are found in section 5, followed by references of all articles checked. 2. methodology the journal of competitive intelligence and management was published between 2004 and 2008. three articles were excluded from this overview as they did not include a sufficient amount of variables. an empirical analysis was conducted in order to detect similarities and inequalities in the articles. to compare the articles, eleven variables were selected. the selected variables were picked out from reading a few articles at random first. similar variables were interesting to explore further in other articles. the empirical table is focused on eleven variables. these variables form the basis of the analysis and conclusions. there are three tables. table 1 shows geographical background, focus of research articles and it says whether or not the article is theoretical or empirical. table 2 continues and says whether articles are qualitative or quantitative and what suggestions they have for future research. table 3 shows authors professional background, gender, nationality and education level. 3. empirical findings data is provided for fifty-one articles. thirty-three percent are about ci as a new study and its different forms in different countries. this reflects the newness of the topic. art geographic focus theo emp 1 italy customer satisfaction x x 2 finland business information x 3 canada technology x 4 brasilia relation: bi and business success x x 5 new zealand development of ci x x 6 lithuania development of ci x x 7 japan current status of ci in japanese business x 8 germany ci in germany x 9 uk software x 10 canada, us, uk, japan, china ci status on the web x 11 us competitive advantage x 12 us marketing x 46 13 us bi x 14 us knowledge management/ value chain x 15 us ci field study x 16 greece corporate intelligence x 17 australia, us managing and compering in competitive intelligence in australia versus usa x 18 korea how ci developed in korea, focus on environment x 19 russia how ci developed in russia x x 20 spain how ci developed in spain, barriers. x x 21 sweden how ci developed in sweden x 22 canada how ci developed in canada, problems with pessimism, unawareness x 23 finland how ci developed in finland x x 24 israel how ci developed in israel, preparing for threats x x 25 south africa how ci developed in south africa x x 26 uk how ci developed in uk, notoriety. x x 27 canada how should you act in terror crises in bi x 28 us understand the rolls in informal networks x x 29 spain how to get ci in ethical ways x 30 us how to divide in virtual team x 31 us how to collect and convert knowledge into an advantage x 32 france find creative ways to gather intelligence in org. environment x 33 israel how different concept taken from the field of topics can tribute to bi x 34 us defining ci x 35 us accounting as ci x x 36 finland implications that ci operations have on coevolution x 37 france the emergence and uniqueness of ci in france x 38 us and canada critical factors to assess ci performance x x 39 uk increasing global demand for bi x 40 us examination of the classic ci model x 41 us process oriented view of ci and it's impact on organizational performance x x 42 uk, canada, us bibliography and assessment of key competitive intelligence scholarship x 43 us existence and usage of ci in professional sports x x 44 us using ci processes to create value in the healthcare industry x x 45 finland analysis of the intelligence activities of finnish companies x x 46 canada reporting on the state of the art (scip06 academic program) x 47 2 uk 1 lebanon the contribution of ci to the strategic decision making process x 48 us and canada improve awareness of environmental scanning practices x 49 uk, rome, mongolia, japan, china, middle tracing the origins of competitive intelligence x 47 east, us 50 canada to provides a practical teaching tool for business educators x 51 us info-terrorism in the age of the internet x table 1: country of origin, topics and method art qualitative quantitative proposals for further research (when applic.) 1 x 2 x test the cube 3 x value of technology 4 x x 5 x courses in ci 6 x 7 x 8 x 9 x field study of software to identify ci-technics 10 x the value of webometrics 11 x ci´s effect on businesses 12 x memetics and psychological factors 13 x 14 x 15 x field study of ci 16 x 17 x x australia should take lessons from the u.s. 18 x x check the cultural background to get the foundation of the theory 19 x x 20 x x 21 x research to be the leader of the ci in the eu 22 x raise awareness of ci in canada 23 x 24 x 25 x 26 x 27 x 28 x study informal roles highlighted in the literature, affect im 29 x 30 x 31 x 32 x 33 x 34 x continued research about defining ci 35 x x include members from scip outside the us. and canada. the use of ci may be tied to another management innovation. 36 x empirical study about the effects of adopting ci solutions and processes 37 x 48 38 x 39 x 40 x 41 x x examine how different types of analysis are related to patterns of dissemination. 42 x 43 x analyze the relationship between the performance of the organization and the use of various ci activities and to seek the link between ci and strategic planning. 44 x a quantitative study using a survey instrument to explore the relationship between the use of formal hr related ci processes and measures of strategic and hr performance. 45 x 46 x 47 x x investigation into the physiology of effective ci managers in a high technology/innovation driven industry. 48 x 49 x how some countries have managed to position themselves as economically stronger then their neighbors, and how intelligence has played a part in their growth. 50 x 51 x table 2: method and suggestions for future research (when applicable) art the authors' background gender nationality education 1 university female italian ph.d. 2 university female, male finland dr., msc. 3 university male us ph.d. 4 university male brasilia dr. 5 university male new zeeland none 6 university 1 female, 2 males lithuania mba & ph.d., none, none 7 university male japan mba 8 university male germany mba 9 university female male uk none, ph.d. & cisa 10 university female, male canada none, mlis 11 university female us bs & mba & ph.d. 12 university male us bd&mba 13 university female us ph.d., mb 14 university female, male us ph.d. & mba & ba, ph.d. & mba & bs 15 university 1 female, 2 males us ph.d., ph.d., ph.d. 16 business male greece ph.d. 17 business, university female, male australia none, bsc. 49 18 university 2 males korea, france ph.d., none 19 business male russia none 20 university 2 males spain ph.d. & ph.d. & mba, bsc. & mba 21 business male sweden none 22 university 2 males canada none, none 23 business female finland none, none 24 business male israel none 25 university, business female south africa ph.d. & bed, none 26 university 1 female, 3 males uk mba, bsc, &msc.& dr., none, none 27 university male canada none 28 business & university female us mba&ma 29 university & business male spain bsc. & mba 30 business, business & university female, male qatar, us bd&mba 31 business & university female us ph.d & ma & mba 32 university 2 females, 1 male france ph.d., none, ph.d. 33 university & business male israel mba & msc. & b.sc. 34 university female us ph.d. 35 university male us mba & ph.d 36 university 2 females finland m.sc., m.sc. 37 university male, female france mba, ph.d. 38 university 2 males canada none, bsba & mba & ph.d. 39 university male uk ph.d. 40 business male us b.a&j.d&ll.m& m.a 41 university 2 males us b.com & msc. & ph.d., ph.d., ph.d. 42 university 2 males 1 female 2 canada 1 uk bsba & ph.d., mba, b.com 43 university female, male us bs & mba & ph.d., ph.d. 44 university 2 females 1 male us ph.d., ph.d., m.d. 45 university female finland msc. 46 university male canada none 47 university 2 females 1 male uk m.b, mba 48 university male canada dba 49 university 2 males uk bsc. & msc. & ph.d., ph.d. 50 business male canada mba 51 university female india ph.d. & ma & mba table 3: background, gender, nationality and degrees 50 the chart over the fifty-one articles shows that there are a total of eighty-three authors. that gives 1.63 writers per article. figure 1: jcim authors by country the chart shows that the authors comes from twenty-one different coutries, and the country most authors come from is the u.s with 30% of the writers. the countries that follow are canada and the united kingdom, both with 13% of the writers. the countries that are the least represented in the journal of competitive intelligence and management of the ones published is brazil, germany, greece, india, italy, korea, lithuania, new zeeland, russia, sweden and qatar; all with 1% of the authors. the authors’ backgrounds show that 60% are males and 40% females. (both editors were females.) totally there were fifty men and thirty-three women represented as authors. the table shows that sixty-one of these eighty-three authors have a higher academic degree, first of all mba, ph.d. and dr. continent ph.d. dr. mba other none = europe 11 2 6 6 11 36 n. america 19 5 5 6 35 s. america 1 1 oceania 1 2 3 asia 2 2 1 1 6 africa 1 1 2 tot. 33 3 13 13 21 83 table 4: a summarized table of education and geographical location of authors 51 europe is represented with a total of thirty-six authors. eleven of these have a phds degree, two have a dr. degree (often equivalent to a phd, for example can be that the dissertation was completed in a german speaking country), six have an mba degree, six have other sorts of higher degrees and eleven authors have no higher degree stated. north america is represented with nineteen phds degrees, no dr., five mbas, five other sorts of higher degree, six of no higher degree from a total of thirty-five authors in north america. south america has one dr. degree represented. oceania has one other sort of higher degree and two with no other higher degree. the continent of asia has two phds, two mbas, one other higher degree and one no higher degree. this makes a total of six authors from asia. africa got one phd and one other no higher degree presented. there are sixty-two authors who has got some form of degree, 47% of these are from north america. europe comes next with 37% and the other four continents constitute under 10%. on the phd level north america is represented with the most, with 58% and europe comes second with 33%. the table demonstrates that the continent of north america is represented with higher degrees and more degrees then the continent of europe despite that europe got one more author represented than north america. table 1 shows that almost 40% of the articles suggest further research within the subject of competitive intelligence or business intelligence. there is a need identified to explore the areas deeper. figure 2: articles with suggestions of future research the chart above shows that the continent of north america gives 57% of all the proposals or suggestions for further research of a total of twenty-one proposals. next come europe with 31%. oceania has 10% of the proposals and asia 2%. south america and africa are not represented with further proposals for future research. another variable that can have an impact on the articles is the author’s backgrounds. some authors are professionals, from the business community, but most come from universities and have an academic background. out of fifty-one articles only fourteen have authors with a business community attachment. that is 27% of all articles published in jcim. a conclusion from the variable focus is that they can be divided in to different groups. the main topic is how to develop competitive intelligence but also how to define ci. the articles about developing ci have also different subjects. some are about development in general (universal) others about development in different countries (cultural). the second largest group is on defining ci and about the growth of ci throughout history. the third largest focus is on business intelligence (bi) and how to use it in the best way. of all the articles about the use and development of ci, 90,9% have chosen a qualitative approach and of those there are 30% that have both approaches. 9,10% of all articles have chosen a quantitative approach. 100% of the articles with the topic defining ci are qualitative. 100% of the articles on the topic of bi are qualitative, out of those 17 % are both qualitative and quantitative. out of those articles which explore ci in different industries 66,67% are qualitative, and 50% of those have both a qualitative and a quantitative approach. there are 33,33% which only use the quantitative approach. the articles that use only a qualitative approach typically have proposals for further research where they suggest a quantitative rmethod. in total, of all articles regardless topic, there are 92,16% with a qualitative approach and of those 52 there are 17,02% with both approaches. only 7,84% has solely a quantitative approach. 4. overview of cir when gathering information for the data set, we used a stratified random sample approach. the methodology gives the possibility to collect a number of articles from each year. from approximately 250 articles published between 1996 and 2001, we picked every fourth article to summarize in the data set. in the data set, we present the variables we found interesting for the summary. we used four levels of competitive intelligence as sub-categories. these were categories that were most popular as subjects: article about companies, products, about marketing and partnership and cooperation (organization). the sub-categories give the opportunity to analyze differences between articles on the four levels. 4.1 company level. the first category is the company level. these accounted for forty-seven articles. origin quantity percentage usa 31 65,96% australia 4 8,51% canada 2 4,26% switzerland 1 2,13% italy 1 2,13% croatia 2 4,26% sweden 2 4,26% brazil 2 4,26% cuba 1 2,13% singapore 1 2,13% 47 100,00% sex quantity percentage male male 40 85,11% female 7 14,89% 47 100,00% based on quantity percentage own experiences 29 61,70% case study 11 23,40% survey 7 14,89% 47 100,00% authors background quantity percentage industry 28 59,57% academic 19 40,43% 47 100,00% method or purpose quantity percentage quantitative 6 12,77% qualitative 2 4,26% informative 18 38,30% guide-to 21 44,68% 47 100,00% table 5: articles categorized by company level 53 4.2 product level the second category is articles about products, where ci is used to support product development. the table below gives a summary of the findings: origin quantity percentage usa 4 80,00% france 1 20,00% 5 100,00% sex quantity percentage male 4 80,00% female 1 20,00% 5 100,00% based on quantity percentage own experiences 4 80,00% case study 1 20,00% survey 0 0,00% 5 100,00% authors background quantity percentage industrial 4 80,00% academic 1 20,00% 5 100,00% method or purpose quantity percentage quantitative 0 0,00% qualitative 0 0,00% informative 3 60,00% guide-to 2 40,00% 5 100,00% table 6: articles categorized by the product level 4.3 marketing level articles about marketing is the third category. it contains all data from the articles that treats marketing as a function in connection with ci. origin quantity percentage usa 5 83,33% great britain 1 16,67% 6 100,00% sex quantity percentage male 4 66,67% female 2 33,33% 6 100,00% based on quantity percentage own experiences 6 100,00% case study 0 0,00% survey 0 0,00% 6 100,00% authors background quantity percentage industrial 4 66,67% 54 academic 2 33,33% 6 100,00% method or purpose quantity percentage quantitative 0 0,00% qualitative 0 0,00% inform 4 66,67% guide 2 33,33% 6 100,00% table 7: articles categorized by the marketing level 4.4 partnership level the last category is called partnership level. we placed here all data from articles that are about the cooperation between different companies and different departments within a company as relates to ci. origin quantity percentage usa 1 25,00% great britain 1 25,00% canada 1 25,00% hungary 1 25,00% 4 100,00% sex quantity percentage male 1 25,00% female 3 75,00% 4 100,00% based on quantity percentage own experiences 1 25,00% case study 2 50,00% survey 1 25,00% 4 100,00% authors background quantity percentage industrial 3 75,00% academic 1 25,00% 4 100,00% method or purpose quantity percentage quantitative 0 0,00% qualitative 1 25,00% inform 3 75,00% guide 0 0,00% 4 100,00% table 8: articles categorized by the partnership level 5. conclusion in conclusion cir was a popular magazine primarily for the american market. this is reflected in the high number of american authors (67%) writing about their experience with ci in 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adamala * and linus cidrin ** * business intelligence and data warehousing consultant, poland, szymon.adamala@gmail.com ** management consultant, sweden, linus.cidrin@hotmail.com received 25 may 2011; received in revised form 3 june 2011; accepted 25 november2011 abstract: business intelligence can bring critical capabilities to an organization, but the implementation of such capabilities is often plagued with problems. why is it that certain projects fail, while others succeed? the aim of this article is to identify the factors that are present in successful business intelligence projects and to organize them into a framework of critical success factors. a survey was conducted during the spring of 2011 to collect primary data on business intelligence projects. findings confirm that business intelligence projects are wrestling with both technological and non-technological problems, but the non-technological problems are found to be harder to solve as well as more time consuming than their counterparts. the study also shows that critical success factors for business intelligence projects are different from success factors for information systems projects in general. business intelligences projects have critical success factors that are unique to the subject matter. major differences can be found primarily among non-technological factors, such as the presence of a specific business need and a clear vision to guide the project. success depends on types of project funding, the business value provided by each iteration in the project and the alignment of the project to a strategic vision for business intelligence at large. furthermore, the study provides a framework for critical success factors that, explains sixty-one percent of variability of success for projects. areas which should be given special attention include making sure that the business intelligence solution is built with the end users in mind, that the business intelligence solution is closely tied to the company’s strategic vision and that the project is properly scoped and prioritized to concentrate on the best opportunities first. keywords: business intelligence, data warehouse, critical success factors, enterprise data warehouse, success factors framework, project risk management 1. introduction this article originated from a master’s thesis that the authors wrote as part of their mba studies at blekinge institute of technology, supervised by dr. klaus solberg søilen. the aim of the article is to develop the tools necessary to analyze, predict and manage the success of business intelligence, data warehousing and competitive intelligence initiatives in contemporary organizations. “there is no reason that each organization, as it begins and continues to develop data warehouse projects, must wrestle with many of the very difficult situations that have confounded other organizations. the same impossible situations continue to raise their ugly heads, often with surprisingly little relation to the available for free online at https://ojs.hh.se/ journal of intelligence studies in business 1 (2011) 107-127 mailto:kss@bth.se mailto:philipbaback_orbsix@msn.com https://ojs.hh.se/ 108 industry, the size of the organization, or the organizational structure” (adelman, 2003). if there is indeed little correlation between success and the environmental factors of those initiatives, the cause of success must be related to something else. it is worth investigating whether the difficulty, complexity of initiatives and the high probability of failure are related to some factors inherent to business intelligence itself. in fact, most of the business intelligence and data warehouse projects fail and the failure rate is estimated to be between 50-80% (beal, 2005; meehan, 2011; laskowski, 2001; legodi & barry, 2010). why do so many of these projects fail? “ the warehouse is used differently than other data and systems built by information systems” (inmon, 2002). therefore, the available knowledge on how to manage ordinary projects in the information systems domain should not be expected to be readily applicable to the area of business intelligence. our initial information search revealed that business intelligence has been covered in a large number of academic articles and books. however, business intelligence success is not widely treated. few articles attempt to analyze what the factors are which influencing bi. some of them have developed frameworks, but there is no proven framework that can be relied upon for this particular problem. the success of bi initiatives undertaken by companies depends on various factors. because bi implementation depends on the successful use of it resources, some of those factors are undoubtedly technological. however, information technology is merely a tool in implementing a bi solution. bi success depends chiefly on organizational and process factors that business administration focuses on. despite differences in bi systems between various industries, those factors should be identified and classified. the existence of a link between individual factors or their combinations and the success of bi initiatives should be verified. moreover, success factors could be classified and a method of measurement could be devised for each individual factor. as the management thinker peter drucker once said, “what gets measured, gets managed”. currently, bi initiatives have a relatively low success ratio. the successful ones achieve roi in excess of 400% (according to some vendors). this figure is even more impressive when taking into account the (traditionally capital) investments in the infrastructure and equally high (traditionally operational) expenses on development projects, operations, consulting services etc. an ability to assess the chances of success prior to engaging in the initiative would have two practical benefits: 1. preventing some of the initiatives from commencing if they score low in the framework of success factors or allowing them to focus on critical issues that otherwise would have caused a failure as a result, the success ratio of all bi initiatives improves. 2. facilitating management of the investment in business intelligence and lowering the entry barriers (given the high level of investment, 50% probability of failure might be too high for smaller companies if the loss resulting from failure push the company into bankruptcy). the article focus on the following hypotheses: hypothesis 1. it is possible to identify critical success factors (csfs) of bi initiatives and they are different from the csfs of information systems (is) in general. hypothesis 2. non-technical and non technological csfs play a dominant role in bi initiatives’ success. hypothesis 3. technology plays a secondary role and is less critical for bi initiatives’ success. hypothesis 4. it is possible to develop objective measures for each of csfs of bi initiatives. if the abovementioned hypotheses can be proved, csfs of bi initiatives can create a framework that can be used to predict the success in early stages of bi initiatives. it should be noted that, even though this study is primarily focused on vendors in poland, the conclusions from this study may have relevance and be applicable to other countries as well, especially since many of the companies studied were global enterprises and other aspects of projects and it are global: outsourcing, offshoring, nearshoring and other forms of international operations. the differences in survey results between poland and other countries were not significant and drawing conclusions from the sample we gathered, we claim that our findings are also applicable to business intelligence projects in larger enterprises worldwide. the reason for choosing poland as the primary country is that one of the authors has been working there for many years and had good access to empirical data. there is some ambiguity around the use of the terms data warehouse and business intelligence among practitioners. historically, data warehousing meant “the overall process of providing information to support business decision making” (kimball, ross, thornthwaite, mondy & becker, 2008, p. 10). following these authors, “delivering the entire end-to-end solution, from the source extracts to the queries and applications that the 109 business users interact with” (kimball et al.,,2008, p. 10) has always been a fundamental principle. however, the term business intelligence coined in the 1990s meant only reporting and analysis of data stored in the warehouse, effectively separating the two terms. even now, there is no agreement in the industry – some “refer to data warehousing as the overall umbrella term, with the data warehouse databases and bi layers as subset deliverables within that context” (kimball, et al., 2008, p. 10), while others “refer to business intelligence as the overarching term, with the data warehouse relegated to describe the central data store foundation of the overall business intelligence environment” (kimball et al., 2008, p. 10). because the aim of this article is not to define the term of business intelligence, but rather to investigate its success factors, both conventions are accommodated. the literature referring both to data warehouse systems/projects and business intelligence systems have been reviewed. there is no difference in their relevance to our study, especially when taken into account the industry practice that even “though some would agree that you can theoretically deliver bi without a data warehouse, and vice versa, that is ill-advised /…/. linking the two together in the dw/bi acronym further reinforces their dependency” (kimball et al., 2008, p. 10). despite this argumentation, business intelligence is used in this article as an overall term. the research is concentrated mainly on the factors that lead to the success of bi initiatives, cause its success (or are able to prevent it), or are otherwise correlated with the success. however, little attention is paid to the definition of the success itself or its measurement. according to delone and mclean (1992; 2003), success in business entails net benefits. to properly define success, those net benefits need to be measured. the authors’ goal of obtaining objective measurement criteria would call for a method to compute the npv of a bi initiative. a similar subject (without the emphasis on bi, but rather for software in general) has recently been a topic of a phd thesis at blekinge institute of technology (numminen, 2010). clearly, calculating the npv of bi initiatives will be out of scope for this article. therefore, the success itself will not be defined as clearly as the authors should want to at first. this would instead be a suggestion for further research in this area. several of the models proposed in the literature (delone & mclean, 1992; 2003; hwang & xu, 2008; wixom & watson, 2001) analyze the interdependency between independent variables. furthermore, none of the abovementioned authors propose a direct correlation with success for those variables that were used to explain variability of other independent variables. the goal of this study is to enumerate all the csfs of bi projects, not to analyze how they depend on each other. for each of the independent variables analyzed, a direct dependency between success and that variable is analyzed. 2. literature review dr ralph kimball is credited with developing arguably the most successful data warehouse architecture, the dimensional modeling. the success criteria as described by kimball are named “readiness factors”. the author suggests giving up the initiative, if some of the criteria are missing or insufficient. “readiness shortfalls represent project risks; the shortfalls will not correct themselves over time. it is far better to pull the plug on the project before significant investments have been made than it is to continue marching down a path filled with hazards and obstacles” (kimball r., ross, thornthwaite, mondy, & becker, 2008, p. 16). let us examine the existing frameworks that might be applicable for explaining business intelligence success. 2.1 information systems success the most obvious first choice when trying to discover bi success factors is to look at information systems (is) in general. there exists an excellent framework proposed by delone and mclean (delone & mclean, 1992; 2003) that has been widely cited, revisited, criticized, validated or extended in hundreds of articles (delone & mclean, 2003). the original framework proposed by delone and mclean (1992) has been reexamined in the light of that subsequent research, resulting in a slightly updated version (delone & mclean, 2003) that will be discussed here. the proposed framework defines is success in terms of system use, user satisfaction and net benefits whereas the factors leading to the success encompass information quality, system quality and service quality. the interdependences between those variables are depicted in figure 1. 110 figure 1: delone&mclean model for is success (delone & mclean, 2003) our study did not measure system quality and service quality at all, as they are inapplicable to business intelligence. as solberg søilen and hasslinger (2009) found, vendors of bi tools do not differentiate their products and tools (other than adopting different definitions of business intelligence). therefore, system quality should not be a factor in the business intelligence domain. because business intelligence systems are built to present data and facilitate its analysis, data quality is probably the most important factor. from the “ second tier” variables, intention to use and user satisfaction should play a small role in business intelligence. if bi is tied to strategic vision for the entire company, users are obliged to use the solution and not their own data sources. therefore, use alone as a variable plays a role. one major drawback with this framework that we identified is the concentration on technology. the findings of our research dictate that the success of bi initiatives relies on numerous factors that are within the management domain rather than on technological factors. therefore, although the delone and mclean model of is success has been applicable to many specific information systems, even those that have been unforeseen when the framework was originally constructed (delone & mclean, 2003), we think it cannot be applied to business intelligence systems without due changes. delone and mclean’s framework not only does not propose any specific measurement methods, but also avoids specific variable definitions, leaving them to be concretized at the time of framework application, depending on the specific context (delone & mclean, 2003). 2.2 critical success factors for bi systems “the implementation of a bi system is not a conventional application-based it project (such as an operational or transactional system), which has been the focus of many csf studies” (yeoh & koronios, 2010). having noted that, the authors proceeded to propose a framework that included some of the critical success factors or success variables from delone & mclean (1992) as a part. system quality, information quality and system use were grouped together and labeled “infrastructure performance”. as an equal factors group, process performance was proposed, encompassing classical project management variables like budgets and time schedules. the authors emphasized a different set of factors, divided into three broad categories – organization (vision and business case related factors, management and championship related factors), process (team related factors, project management and methodology related factors, change management related factors) and technology (data related factors, infrastructure related factors). all those factors cause business 111 figure 2: yeoh & koronios model of success in bi (yeoh & koronios, 2010) orientation, which in turn, together with before mentioned infrastructure and process performance factors lead to implementation success and, subsequently, to perceived business benefit. this framework is illustrated in figure 2. a summary of success factors across all the dimensions with the highlight of the most important points: organizational dimension  committed management support and sponsorship  clear vision and well-established business case process dimension  business-centric championship and balanced team composition  business-driven and iterative development approach  user-oriented change management technological dimension  business-driven, scalable and flexible technical framework  sustainable data quality and integrity this framework is considerably better suited for business intelligence systems than the one presented by delone and mclean (2003). however, it has a few drawbacks. first, there are no specific measurement criteria proposed. since several of the variables are defined in a way so that very different measurement criteria can be defined or it would be hard to devise measures other than the likert scale, the framework would be impractical to apply and the results might depend on the subjective opinions of those that provide or calculate variable’s values, resulting in the false prediction of bi initiative success. another drawback is an artificial reliance on the delone and mclean (2003) model of is success. some infrastructure performance factors (system quality, information quality) belong under the technology category (infrastructure related factors or data related factors) and should not be repeated at all or the causal dependency should be included in the framework. further criticism of this article (yeoh & koronios, 2010) can be based on the way inclusion of technology related factors was performed. “ business-driven, scalable and flexible technical framework” and particular variables that fall into this category are too close to the way the vendor who delivered the solution gives advice on his or her product. also, the fact that this article (yeoh & koronios, 2010) was based on a single project 112 plays down the objectivity of its findings. as our survey later revealed, technical issues are of secondary importance. 2.3 impossible data warehouse situations. why are the success criteria so important? as we have already mentioned in the introduction, some data warehouse implementations fail. it is possible that many of these ‘failures’ would be considered successes (or at least to be positioned someplace between failure and success). the criteria for success are often determined afterwards. this is a dangerous practice since those involved with the project don’t really know their targets and will make poor decisions about where to put their energies and resources (inmon, 2002). according to adelman (2003), the example measures of success include the following elements:  the data warehouse usage.  usefulness of the data warehouse, including end user satisfaction.  acceptable performance as perceived and experienced by end users.  acceptable roi benefits justifying the costs.  relevance of data warehouse application.  proper leverage of a business opportunity (i.e. establishing competitive advantage thank to the application of data warehouse).  timely answers to business questions.  higher quality / cleanliness of data (than in the source systems).  initiation of changes in the business processes that can be improved as a result of the use of data warehouse (adelman, 2003, p. 5 & 40). douglas hackney emphasized the critical importance of establishing success measures – “ the ‘build it and they will come’ approach (…) does not work in data warehousing” (adelman, 2003, p. 41). he further suggests starting with business “pain” with the available data. the words “life-threatening” seem to accurately describe the problem that need to be chosen to solve (inmon, 2002, p. 41). an example of a business “pain” might be the “loss of revenue or excessive operating costs” (inmon, 2002, p. 42). the main theme of the book of adelman (2003) is not the success factors of business intelligence initiatives. instead, the author concentrates on various difficult situations and proposes methods to overcome those adversities. although he does not name those factors as influencing the success itself, some of them should at least be evaluated for possible inclusion in the final framework of this study. according to the author, all difficulties can be organized in one of the following categories (the first seven represent management issues, the rest is concerned with the technical side): 1. management issues 2. changing requirements and objectives 3. justification and budget 4. organization and staffing 5. user issues 6. team issues 7. project planning and scheduling 8. data warehouse standards 9. tools and vendors 10. security 11. data quality 12. integration 13. data warehouse architecture 14. performance from the factors identified in the book of adelman (2003), we found a few that were less important than others, while some were not considered at all in our survey as separate variables. for example, architecture, performance, security, tools and standards were considered as one broad variable technical issue in our research and were deemed of secondary importance. data quality, on the other hand, was measured in our survey separately for source systems and target solution, both being found to have importance. adelman ( 2003) devote at least equal attention to technical issues in general as to all nontechnical issues, the latter being mentioned in less detailed discussions. broad and general categories of “user issues”, “team issues”, “ organization and staffing” etc. make detailed comparison with our study difficult. also, a different terminology plays a role here. what the author considers measures, our study call variables. for example, “data warehouse usage” was a measure in the book (adelman, 2003) while as we propose three distinct measurement methods, namely number of queries per period, number of logons per period and number of users per period. 2.4 competing value model since different stakeholders will look at different criteria to determine if the initiative was a successful one, different perspectives may need to be taken into account. this issue of potentially conflicting criteria has been discussed by walton and dawson in their competing value model which organizes criteria in different dimensions (walton & dawson, 2001). this could be present in bi initiatives as well, where different 113 stakeholders can have different non-overlapping criteria for success; for example a system integrator can have different objectives for engaging in a bi initiative, different from the end user organization (the customer). this study did not attempt to define bi initiative success, but considered using this kind of classification of criteria for different dimensions, such as technical and non-technical. the definition of success of bi initiatives is not part of this study. one consequence of the findings of the article by walton & dawson (2001) is that the development of a framework allows for the interest of different stakeholders to be organized. this problem is left for future studies. 2.5 a critical success factor framework for implementing business intelligence systems qualitative studies have been used in the area of critical success factors in business intelligence many times. one of these is a critical success factor framework for implementing business intelligence systems (yeoh, gao, & koronios, 2007) where the authors performed a delphi study covering 15 bi systems experts to define a critical success factor framework for implementing business intelligence systems. the authors propose a framework that is organized into seven dimensions covering 22 factors. the seven dimensions of this article (yeoh, gao, & koronios, 2007) are:  commitment management support and championship  user-oriented change management  business vision  project planning  team skills and composition  infrastructure-related dimensions  data related issues the delphi panel rates the factors in those dimensions and a mean is calculated for each dimension. the above list of dimensions is ordered in a falling mean ranking, starting with the dimension with the highest rating. we see that more technical dimensions can be found at the very bottom of the list, while as non-technical dimensions are found higher up in the list. the paper by yeoh et al. (2007) demonstrates, in line with the result from this study, that management championship and the presence of a clear vision for business intelligence is important when executing a business intelligence initiative. while the result from this study seems to indicate that the technical factors are more important than the non-technical factors, the authors of the paper include two “technical” dimensions out of seven. it should be said that the ratings of the two technical dimensions are the lowest out of the seven, which is well in line with the findings of this study. 2.6 risk management in enterprise data warehouse projects in south africa the paper starts with the claim that data warehousing implementation projects have high estimated failure rates, up to about 50% (legodi & barry, 2010). the objective of the paper and the study was to investigate the main areas of risk for these projects, and a delphi method was used for the data collection. the study was performed in south africa. results from the study are in the form of the main problems and the success factors for this type of project. the identified factors that have the greatest impact on success from the study (legodi & barry, 2010) are (listed in priority order): 1. scope creep 2. uncontrolled finances 3. poor communication 4. stake holder non-involvement 5. skills shortage 6. unavailability of tools and technology 7. uncontrolled quality of deliverables 8. poor, wrong or no leader 9. technical difficulties 10. legal difficulties we note that the first technical difficulties can be found in the ninth item. (legodi & barry, 2010) show, like the results from this study, that non-technical factors affect the success of a project the most. out of the ten factors legodi and barry (2010) identified, only one were of technical nature and placed as the ninth factor (technical difficulties). the fourth item, stakeholder non-involvement, can be comparable to the importance of vision and addressing a specific business need of the sponsor. while the paper surveyed a more narrowly defined geography (south africa), the finding that non-technological factors dominate is shared between that paper and this study. 2.7 an exploratory investigation of system success factors in data warehousing the variables used in a study by shin (2003) are system throughput, ease of use, ability to locate data, access authorization, data quality (subdivided into 4 more detailed categories of recency/currency, level of detail, accuracy and consistency), information utility, user training and user satisfaction, with the latter is being used as dependent variable. the data was gathered from a single large us enterprise, based on a single 114 project, therefore even the author agrees that this study must be treated as a case study (shin, 2003, p. 157). the authors found that 70% of end user satisfaction could be explained by the independent variables that were measured. shin (2003) approaches data warehousing success in a different way than in the above study, treating end user satisfaction as a proxy for project success. this is also inconsistent with delone and mclean approach (delone & mclean, 1992; 2003) which shin cited and claimed to be “the most influential model in conducting research on information systems success factors” (shin, 2003, p. 144). the variables used are mainly different from the inspected ones, with only data quality being common with this study. variables used by shin (2003) describe predominantly technological factors. as in this study actual use is only one of the variables, the results are hardly comparable. also, a case study approach concentrated on success within just one company makes this article (shin, 2003) less valuable for creating a larger data warehousing or business intelligence success criteria framework. a structural model of data warehousing success by hwang & xu (2008) analyzes several factors influencing data warehousing success. success is not measured as a separate variable. instead, following delone and mclean (1992; 2003), benefits and quality are used as proxy, with a distinction between individual and organizational benefits as well as system and information quality. the independent variables are; operational factor, technical factor, schedule factor and economic factor. the authors propose at least two measures for each variable, dependent and independent. the model (figure 3) is able to explain between 27% (system quality) and 41% (organizational benefits) of the dependent variables variability. figure 3: hwang & xu structural model of data warehousing success (hwang & xu, 2008) the most prominent difference in approaches is the definition of what a variable is and what a measure is. many measures from this article (hwang & xu, 2008) are variables in our study, for example business benefits definition, business benefits measurability or scoping of a project. the aim for objective measurement methods were not one of the goals of hwang & xu (2008) and it is unclear how measures proposed in their work should be performed in practice. the authors were overly reliant on the model of is success (delone & mclean, 1992; 2003), obtaining little explanatory power for their model. from the way the model was constructed, it is also hard to compare whether technical or non-technical factors play major role in data warehousing success. an empirical investigation of the factors affecting data warehousing success (wixom & watson, 2001) examined the factors influencing data warehousing success. authors verified several hypotheses. findings can be summarized as follows: hypothesis 1a. a high level of data quality will be associated with a high level of perceived net benefits (supported). hypothesis 1b. a high level of system quality will be associated with a high level of perceived net benefits (supported). hypothesis 2a. a high level of organizational implementation success is associated with a high level of data quality (not supported). 115 hypothesis 2b. a high level of organizational implementation success is associated with a high level of system quality (supported). hypothesis 3a. a high level of project implementation success is associated with a high level of data quality (not supported). hypothesis 3b. a high level of project implementation success is associated with a high level of system quality (supported). hypothesis 4a. a high level of technical implementation success is associated with a high level of data quality (not supported). hypothesis 4b. a high level of technical implementation success is associated with a high level of system quality (not supported). hypothesis 5. a high level of management support is associated with a high level of organizational implementation success (supported). hypothesis 6a. a strong champion presence is associated with a high level of organizational implementation success (not supported). hypothesis 6b. a strong champion presence is associated with a high level of project implementation success (not supported). hypothesis 7a. a high level of resources is associated with a high level of organizational implementation success (supported). hypothesis 7b. a high level of resources is associated with a high level of project implementation success (supported). hypothesis 8a. a high level of user participation is associated with organizational implementation success (supported). hypothesis 8b. a high level of user participation is associated with project implementation success (supported). hypothesis 9a. a high level of team skills is associated with project implementation success (supported). hypothesis 9b. a high level of team skills is associated with technical implementation success (not supported). hypothesis 10. high-quality source systems are associated with technical implementation success (supported). hypothesis 11. better development technology is associated with technical implementation success (supported). a valuable part of in this article (wixom & watson, 2001) that even led to verifying the hypotheses proposed in this paper, was the statistical model using partial least squares regression. the resulting model can be seen in figure 4. figure 4: wixom&watson statistical model of dw success (wixom & watson, 2001) r 2 values obtained by wixom and watson (2001), (figure 4) ranging between 0.016 to 0.435, means that independent variables used in the model provide limited explanatory power for dependent variables. this makes it impossible to compare findings with our study. the model relies on the is success model by delone & mclean (1992) which defines system success using a structure of proxy variables – data and system quality, and benefits. variables used covered both technical and nontechnical factors influencing data warehouse implementation success. the way the model was 116 constructed makes it impossible to verify whether technical or non-technical factors influence the success more strongly. the article (wixom & watson, 2001) does not attempt to propose specific measurement criteria for the variables used. 2.8 current practices in data warehousing the study conducted in the article of watson, annino, wixom, avery, & rutherford (2001) concentrated on some of the factors influencing data warehousing projects success. survey respondents were asked to provide answers to questions about who sponsored the data warehouse, which organization unit was the driving force behind the initiative, about solution architecture and end users, about implementation costs, operational costs, solution approval process, after implementation assessment, realization of expected benefits (together with expectations). to describe success, two questions were used, one about roi and the other about perceived success of implementation. although the authors gathered enough data to analyze the dependency of individual factors with success or to build a statistical model of several variables, they chose not to do so. instead, they analyzed individual questions, summarizing contemporary practices. findings say that most data warehouse sponsors come from business units and no single architecture dominates all implementations (watson, annino, wixom, avery, & rutherford, 2001). because of the lack of a proposed framework, it is impossible to compare this article with our findings. also, the article did not attempt to propose any objective measurement methods for variables included in the study. 2.9 measuring user satisfaction with data warehouses: an exploratory study the study of chen, soliman, mao, & frolick, (2000) uses end user satisfaction as a proxy for success and examines factors influencing the aforementioned user satisfaction. study results identify three factors comprising several questions each. those factors are: support provided to end users, accuracy, format and preciseness of data, and fulfillment of end user needs. authors did not propose a framework for success and did not attempt to build a statistical model. they also did not attempt to develop objective and universal measurement methods for the variables identified. treatment of end user satisfaction as a proxy for project success and the goal to identify only the factors that influence this variable makes it difficult to compare the results with the findings. the authors (chen, soliman, mao, & frolick, 2000) claim to have relied on the model of is success (delone & mclean, 1992), but included only one of the “use” variables presented in that study. the study treated use as a whole and positioned it as one of the factors influencing success. it is impossible to tell whether technical or nontechnical factors are more important to project success following this article (chen, soliman, mao, & frolick, 2000) and no objective measurement methods are proposed. 3. empirical data for primary research, surveys were used and 68 fully completed surveys obtained. the results were analyzed using quantitative methods simple statistics (mean, mode, median) performed on individual questions, correlation analysis of individual variables with the dependent variable of success and partial least squares regression (plsr) used to build the target framework. internetbased e-surveys were used. each single data point / measurement was a distinct business intelligence project. this implies that several measurements could have been obtained from a single vendor, customer or individual, provided that each of those measurements described distinct projects. each survey contained optional questions about customer and vendor company names, project names, place where the project was performed as well as whether the survey participants were involved in a project on the customer or vendor side, and a precise project role of the participants. initial secondary research revealed that some of independent variables chosen by authors are correlated. because of this and the fact that we aimed at analyzing direct dependency of all independent variables with success, there was a very high probability of multicollinearity in the data. for this reason, a method of data analysis insensitive for multicollinearity had to be chosen. also, because of high number of independent variables chosen based on phase 1 findings and relatively low number of observations obtained through the survey, an appropriate method had to be chosen. both requirements combined were satisfied by partial least squares regression, a method that “was designed to deal with (…) regression when data has small sample, missing values, or multicollinearity” (pirouz, 2006). after completing the primary research, we propose our own framework for bi initiatives success, using prior research as a starting point. the framework was separated from the measurement methods to maintain the flexibility and applicability of the framework in various contexts. however, measurement methods were also proposed. keeping those two separated will allow any future studies to propose different measurement for the variables. also, a fact of 117 importance is that it is much easier to combine a theoretical framework with specific measurement methods if they are kept separated, than to split them if they are merged in a single framework. therefore, we decided to separately propose a theoretical framework and a specific measurement method for each of the variables. 4. analysis and implications as mentioned, this study excludes trying to define what bi project success looks like. instead, to determine whether a project is successful or not, the following interpretation from the survey results have been made throughout the article.  successful project/initiative project with answers “definitely yes” and “rather yes ” to the question q19:1 “was the project you are describing successful?”  non-successful project/initiative project with answers “neutral”, “rather no” and “definitely no” to the question q19:1 “was the project you are describing successful?”. that is, non-successful means unsuccessful or neutral. the reason behind such a distinction is that this article aims for developing tools that managers could use to achieve success. merely avoiding failure is not good enough. if the project failed to achieve success, it cannot be treated as a mild success or neutral. instead, it should then be considered as a non-successful project. results from the survey indicate that the funding of successful initiatives and non-successful ones differs. successful initiatives are more likely to be funded in a phased approach, with separate budgets for each iteration, while the non-successful tend to be funded in a traditional way as other it projects, i.e. one budget for the entire project. iterative development is used by both successful and non-successful initiatives, but results from the survey show that for an overwhelming majority (89%) of the successful initiatives, each of the iterations provided business value by themselves. this can be compared to the non-successful initiatives that used an iterative approach, where every other initiative had iterations that provided value by themselves. a bi solution designed with end users in mind will naturally have a greater usage than bi solutions that don’t consider the end users. a whopping 96% of the successful initiatives in this study have users that actually use the business intelligence solution. the results for the nonsuccessful ones vary. the presence of an overarching, clear strategic vision for business intelligence within the organization is important for the success of an initiative. results show that successful initiatives exist in an environment with a clear strategic vision to guide the initiative as compared to nonsuccessful ones. a total of 81% of the successful initiatives agrees to this compared to 46% of the non-successful. not only is the existence of a strategic vision for business intelligence important, the business need that the initiative tries to solve should be aligned to that vision. like the results for the existence of vision, the successful initiatives have business needs that tend to be more aligned with the strategic vision than for non-successful ones. 73% of the successful initiatives agree to that. corresponding figure for the non-successful initiatives is 39%. the survey shows that successful initiatives often concentrate on choosing the best opportunities for the project scope. 57% of the surveyed successful initiatives do this, compared to 23% of the non-successful ones. another parameter measured by the study is whether an expert assigned to a team or made available to a team, always was the best expert available. the results from the study reveal, somewhat surprisingly, that non-successful initiatives to a larger extent assigns the best expert available, with 85%. corresponding number for the successful ones are 54%. issues will occur during the duration of an initiative, which can be both technological and non-technological in nature. both successful and non-successful initiatives do, to some extent, encounter non-technological issues, with nonsuccessful encountering them slightly more often according to this study. the technological issues are commonly found in both successful and nonsuccessful initiatives, but they are somewhat more common in the non-successful initiatives (77% compared to 63% reports presence of technological issues). for all initiatives in the study only slightly more than 20% found technology related problems to be the hardest. consultants spend time on solving different kinds of problems, technological as well as nontechnological and for a majority of the initiatives a larger part of the time is spent on resolving nontechnological problems. this is especially true when looking at the non-successful initiatives, which show that almost 40% of the surveyed initiatives indicated that non-technological issues took the most time. 4.1 a statistical model of business intelligence initiatives’ success. the survey results were analyzed using the partial least squares regression method. two separate series of models were built, one using original, 118 untransformed data and the other, using the data transformed by centering on mean, dividing by a factor and applying basic mathematical functions. more details, and the rationale for performing those transformations, are provided later in the text. the models built for original data analysis used 25 variables defined by answers to survey question nr 19. for the clarity of information presentation, variables were named after their respective survey questions – variable a19_1 corresponded to question 19:1 answers, a19_2 corresponded to question 19:2 answers and so on. because question 19:1 asked users whether the project they described was successful, this variable was chosen as dependent for all the models, while every other variable was treated as independent. unlike other linear regression methods, adding more variables does not necessarily imply an increase of model’s r 2 when pls is being used. the method cannot be used to eliminate insignificant variables, which is easily achieved in other linear regression methods. therefore, the model that used all the available variables was not necessarily the best. because the method cannot eliminate insignificant variables by setting the linear combination coefficients to 0 (or even close to 0), models that used only some of the variables were built. choice of variables that explain success should be made based on the individual independent variables’ correlation with the dependent variable. after some experimentation, 5 variables with correlation of success stronger than 0.4 were chosen (absolute value of correlation coefficient greater than 0.4). figure 5: pls regression model with 5 significant variables as can be seen the model achieved a r 2 of 0.559, with changes in independent variables explaining 55.9% of changes in dependent variable. the variables that enabled these results were obtained as answers to the following questions: question 19_3. did the end users use the data warehouse / bi solution provided? question 19_6. were the business needs that project tried to solve aligned to the abovementioned strategic vision? question 19_10. did project scope definition concentrate on choosing the best opportunities ("low-hanging fruit")? question 19_19. if technological issues were present, were all of them resolved? question 19_20. were non-technological issues encountered during the project? pls is a linear regression method, but it is most likely that a dependency of success from the factors is not linear. the possibility of other dependencies had to be explored. while other, non-linear regressions could possibly be applied, a lack of any knowledge of the nature of the dependency would imply the need to try all of them, which was clearly beyond the scope of this study. instead, linear regression could be applied to the transformed factors. for example, if linear regression could be done on squared factors, the outcome would be a case of square regression for the original factors; if various powers could be applied to these factors, the outcome would be polynomial regression and so on. it is always possible to choose a function that will fit the given finite, discrete data set. to avoid such a pitfall, the transformations had to be limited to basic mathematical functions – power (including square root), logarithm, exponential functions, reciprocal or simple composition of aforementioned functions. similar selection criterion as for original data applied, but the transformation had to improve the data. the transformed data was considered better than original if for a given function f and variable x, f(x) had a stronger correlation with success than variable x itself. 119 before the abovementioned functions could be applied, initial data transformations were necessary. the data was centered on mean and divided by a factor to produce more distinct values instead of the same 5 values for all questions. none of those operations changed the correlation of data prior to applying the functions. based on the experience from model 1, the variables were sorted by correlation. to facilitate experimenting with the data model, a relative rank of correlation value was included in variable name while keeping the question number embedded. for example, variable v05_n19_20 had the fifth strongest correlation of all variables (05 in the name) and was a result of applying transformation (n in the name) to question q19:20 answers (19_20 in the name). for some variables, an alternative version of the same variable was also used. for example v18b_a19_15 was an alternative variable to v18a_n19_15, containing answers to question q19:15 without applying the function, with only the transformations described in data preparation section above. the decision on whether to include an alternative variable or not was made based on how much the correlation has improved as a result of applying a given function, with 0.05 as a threshold. however, models containing alternative versions of the variables were not any different from those using transformed variables and will not be presented here. the summary of functions applied to variables is presented below:  v01a_n19_3: q19_3 transformed using log(2, 1-x/4)  v02_n19_6: q19_6 transformed using power(x, 3)  v03_n19_6: q19_19 transformed using power(x, 3)  v04_a19_3: q19_10 transformed using x  v05_n19_20: q19_20 transformed using 1/power(2,x)  v06a_n19_5: q19_5 transformed using exp(x)  v07_n19_18: q19_18 transformed using 1/power(2,x)  v08_n19_22: q19_22 transformed using exp(x)  v09_n19_25: q19_25 transformed using sqrt(abs(x))  v10n19_17: q19_17 transformed using 1/power(x,3)  v11_n19_8: q19_8 transformed using sqrt(abs(x))  v12a_n19_16: q19_16 transformed using 1/power(2,x)  v13_n19_14: q19_14 transformed using 1/x  v14_n19_2: q19_2 transformed using sqrt(abs(x))  v15a_n19_12: q19_12 transformed using 1/power(x,3)  v16_n19_7: q19_7 transformed using power(x, 2)  v17_n19_11: q19_11 transformed using 1/power(x,3)  v18a_n19_15: q19_15 transformed using power(x, 3)  v19_n19_24: q19_24 transformed using 1/x  v20_n19_23: q19_23 transformed using 1/x  v21_n19_9: q19_9 transformed using sqrt(abs(x)) figure 6: pls regression model 2 equivalent of model 1 with transformed variables 120 in case of untransformed variables, the regression model with the best fit used only 5 independent variables. therefore, the analogical model was tried using transformed data. this time, the improvement in r 2 was smaller and the model was able to explain 0.584 of the success. the resulting regression model is presented in figure 6 above. figure 7: pls regression model with the best fit after some experimentation with various different models, r 2 =0.611 was achieved by one of them. it is presented in figure 7. this was the best model found using either transformed or untransformed data. the variables used in this model are summarized as follows:  v14_n19_2: overall, was it possible to define factors that were critical to how successful the project was?  v01a_n19_3: did the end users use the data warehouse / bi solution provided?  v06a_n19_5: was there a clear strategic vision for business intelligence or data warehouse?  v02_n19_6: were the business needs that project tried to solve aligned to the abovementioned strategic vision?  v16_n19_7: was project's underlying business case preceded by a business needs analysis? this does not mean your party (vendor or customer) performed this analysis as part of the project  v11_n19_8: did the final solution evolve beyond initial scope? in case a program was established, answer on a program level  v04_a19_10: did project scope definition concentrate on choosing the best opportunities ("low-hanging fruit")?  v17_n19_11: when an expert in a particular field was needed, was project team always granted access to an expert or enhanced by including one?  v15a_n19_12: when an expert was assigned to a team or made available to a team, was it always the best expert available?  v13_n19_14: if there were data quality issues at source systems, were they known before the start of bi initiative?  v12a_n19_16: were there data quality issues in bi system or data warehouse?  v10n19_17: were data quality issues in bi system or data warehouse eventually resolved?  v07_n19_18: were technological issues encountered during the project?  v03_n19_19: if technological issues were present, were all of them resolved?  v05_n19_20: were non-technological issues encountered during the project?  v08_n19_22: data architecture was performed at the beginning of bi initiative (note data architecture is different from 121 systems architecture or solution architecture)  v09_n19_25: was there a process in place to measure business benefits? 4.2 measures analysis from the three measures of data warehouse use proposed in the survey, none were found bad or even rather bad. conversely, none of them were found definitely good. the best from the three was a weekly number of queries. the fact that it was positively evaluated in most responses and that mean value was close to being rather good makes this measurement method adequate and fairly universal. it is objective and can be automatically computed. out of the two proposed measurement methods of access to subject matter experts, respondents found both “rather good”, with over two thirds of respondents agreeing with this view. despite the fact that the mean response time turned out to score slightly better, we propose to use both as measurement for the “access to subject matter experts”variable. to compute any of them, a formal process of request tracking should be made, but with this process in place, both measures are objective and easy to compute. only one of the three proposed measurement methods for subject matter expert quality was found applicable. it turned out to be the same measurement method as for the access to subject matter experts. because of that, the same arguments about measurement method objectivity and computability apply. from the three measures proposed in the survey for the question of whether there was enough business staff on the project, we found that both percentages of business issues resolved within a business week. the mean time to resolve a business issue qualify as an adequate measure for the variable was there enough business staff on a project. we found little difference in those measures as they are equally good and equally objective. they are both calculated in a similar way therefore either one of them could be used, or even both at the same time. two measures of deliverable size in iterative development were proposed and we found that only a percentage of total project time for each iteration is a good one. however, this measure is only objective after the project ends. it can be calculated during the planning phases and project schedule can be used for that purpose. unfortunately, this makes the measure less objective and easy to manipulate. this diminishes its applicability to predict initiative success. despite these drawbacks, we postulate to use this measure in absence of better alternatives. perhaps other measures could be examined in the future to replace this one, for instance percentage of total budget allocated or a similar measure. out of three measures proposed for data quality issues at source systems, it was found that both counting the total number of issues and the number of unresolved issues are adequate and almost identically rated. therefore no distinction can be made as to which one of them to use and we recommend using both. they should be easily computable if only the formal issue tracking process is in place. however, both measurement methods can only be used after the project end as the number of issues is unpredictable (following our earlier findings, a number of issues were discovered during the bi project). for this reason it would be hard to predict initiative success based only on the upfront knowledge about source systems data issues. from the three measurement methods proposed for data quality issues in bi system or data warehouse, no one better than the others were found. therefore, it is conclude that this variable should be measured using the number of unresolved issues. the fact that this variable could be objectively measured only after the project ends makes it unsuitable for use in predicting project success. all three measurement methods proposed for benefits quantification were found adequate for quantification. both roi and irr calculations were objective yet difficult to perform at project start, while relating capabilities to company strategy was less objective but easier to apply early in the project. it would be best if financial indicators could be calculated at project start; therefore those two methods would be preferred over the one called strategy, however all three are worth using and will probably work in practice. both measurement methods proposed for business benefits definition were evaluated positively by survey respondents with percentage of business benefits objectively measureable being significantly better than just a written definition of the benefits. both were objective and computable in the early stages of the project. although, percentages were recommended as a better measurement, we also note that both are likely to be used in practice as it is unlikely that a company will have the benefits that are measureable without first defining them. therefore, in practice, when the better measurement method can be applied, then so can the one that is worse off. from the two measurement methods proposed for business benefit measurements, only one was approved by survey respondents the presence or absence of business benefits process owner. this measurement process can and should be used in predicting the project success. 122 figure 8: analysis of measurement methods of variables (q22) for each of the variables analyzed in question 22, there was at least one measure that was deemed good enough to be generally used for all projects. however, almost no measure was found definitely good. there are two possible explanations for this phenomenon. either there is no universally acceptable measurement method for those variables or such a variable exists but was not discovered in this study. neither of the above possibilities can be verified using data gathered in this study. 5. hypotheses analysis hypothesis 1 (first part). it is possible to identify critical success factors (csfs) of bi initiatives in large enterprises. to determine if factors exist that, if present, are more likely to lead to initiative success, an analysis of the correlation between the success and different factors surveyed was performed. to demonstrate causality, the statistical evidence of correlation between success and different key success criteria are complemented with an argumentation on what the casual relationship is. to show correlation between different criteria and the success of the initiatives, spearman’s rank correlation coefficient (spearman’s ρ) was chosen. motivation for choosing spearman’s rank correlation coefficient includes that it does not require the relationship to be linear, but also the fact that it is often used for likert scales data sets in e.g. medicine, biochemistry and other sciences with success (jamieson, 2004). the questions/factors with correlation coefficients with an absolute value of 0.25 or higher are (correlation coefficient in parenthesis):  did project scope definition concentrate on choosing the best opportunities ("lowhanging fruit")? (0,43)  were non-technological issues encountered during the project? (-0,42)  were the business needs that project tried to solve aligned to the abovementioned strategic vision? (0,41)  was the project meant to address specific business needs of the sponsor? (0,38)  data architecture was performed at the beginning of bi initiative (0,37)  was there a clear strategic vision for business intelligence or data warehouse? (0,35)  were there data quality issues at source systems? (-0,30)  if iterative development was chosen, did each iteration provide business value by itself or in connection with previous deliverables? (0,29)  were technological issues encountered during the project? (-0,28)  were data quality issues in bi system or data warehouse eventually resolved? (0,27)  have business benefits been quantified? (0,26) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% q 2 2 :1 q 2 2 :2 q 2 2 :3 q 2 2 :4 q 2 2 :5 q 2 2 :6 q 2 2 :7 q 2 2 :8 q 2 2 :9 q 2 2 :1 0 q 2 2 :1 1 q 2 2 :1 2 q 2 2 :1 3 q 2 2 :1 4 q 2 2 :1 5 q 2 2 :1 6 q 2 2 :1 7 q 2 2 :1 8 q 2 2 :1 9 q 2 2 :2 0 q 2 2 :2 1 q 2 2 :2 2 q 2 2 :2 3 q 2 2 :2 4 q 2 2 :2 5 q 2 2 :2 6 analysis of measurement methods of variables no answer 1 definitely yes 2 rather yes 3 neutral 4 rather not 5 definitely not 123 from the above it can be conclude that there are in fact criteria (those factors with a large correlation with success of the initiative) that, when present, are associated with a higher likelihood of initiative success. hypothesis 1 (second part). csfs of bi initiatives are not the same as for other is in large enterprises. looking at the top criteria for successful initiatives with the highest ranking from the surveyed participants shows that success factors related to the project actually addressing a specific business need is most important. building a solution that is tailored to user requirements and therefore enables usage of the business intelligence solution is also important. in the third place comes; documenting success criteria for the initiative early on in the initiative. resolving technological issues, having a clear vision to guide the initiative and including a business need analysis early on are other important criteria. the survey clearly shows that nontechnological factors rank high amongst the answers. to compare this to success factors for is in general, a framework proposed by delone and mclean (delone & mclean, 1992; 2003) was used. the original framework proposed by these authors has been updated with an updated version (delone & mclean, 2003). as discussed previously the factors leading to the success of is project in general include information quality, system quality and service quality. the first thing that strikes one in the framework proposed by delone and mclean is the heavy focus on technical issues and factors, and little to none concentration on the softer factors that pertain to management issues. one difference from the general is framework proposed by delone and mclean and the findings from this study is the addition of more nontechnical factors such as the presence of a specific business need to be addressed by the initiative, a clear vision to guide the initiative and a preinitiative definition of success factors. hypothesis 2. non-technical and nontechnological csfs play a dominant role in bi initiatives’ success in large enterprises. from what has been seen earlier, most of the csfs with high correlation with success are in fact nontechnical. examples are: 1. successful initiatives do focus, to a larger extent, on choosing the best opportunities i.e. “low-hanging fruit” or quick wins. 2. successful initiatives are more likely to have a clear strategic vision for business intelligence or data warehouse. 3. successful initiatives are more often meant to address a specific business need of the sponsor. 4. the business needs addressed by successful initiatives are more often aligned with the abovementioned strategic vision. looking at individual csfs and the responses from the survey, one can see that for non-technical issues, there is a noteworthy difference between the results for successful initiatives and the nonsuccessful ones. one example of this is the area of iterative development. for those initiatives that used an iterative approach, each iteration was more likely to provide business value by itself for the successful ones. a total of 89% agreed to this, compared to 50% for the non-successful initiatives. another example concerns the presence of a strategic vision for business intelligence. a total of 81% of the successful initiatives had a clear strategic vision compared to only 46% of the nonsuccessful ones. in conjunction with the presence of a strategic vision for business intelligence as a whole, the successful initiatives are more likely to address a specific business need that is aligned to this strategic vision. some 73% of the successful initiatives were addressing a specific business need aligned with the strategic vision. this is almost twice as common as the 39% of the non-successful ones. when looking at the scope definition, the successful initiatives are more often concentrating on choosing the best opportunities as depicted by the chart below. 57% of the successful initiatives do this compared to the non-successful ones 23%. all of the above examples are non-technical factors that are (to a varying degree) more commonly found in successful initiatives than those initiatives that fail. this in turn, indicates that non-technical and non-technological csfs play a dominant role in bi initiatives’ success in large enterprises. hypothesis 3. technology plays a secondary role and is less critical for bi initiatives’ success in large enterprises the results from the survey show clearly that nontechnical factors were the hardest to solve. results show that for all initiatives in the survey only slightly more than 20% found the technology related problems to be the hardest to solve. the fact that the non-technology related problems were harder to solve is even more evident when looking at the non-successful initiatives only, where almost 124 as many as 70% of the initiatives found the nontechnology related problem to be the hardest. another view on this is the time spent on the different types of problems. again, as we can see a larger part of the time is spent on resolving nontechnological problems. this is especially true when looking at the non-successful initiatives, out of which almost 40% indicate that nontechnological issues took the most time. when comparing the successful initiatives with the non-successful ones and the presence of non-technological issues, it is clear that the initiatives that fail more often encounter nontechnological problems. one interpretation of this could be that the presence of non-technological issues will have a detrimental effect on the likelihood of initiative success. hypothesis 4. it is possible to develop objective measures for each of csfs of bi initiatives in large enterprises. the result of this study shows that all the csfs clearly have one or more measures that are ranked higher than the rest. the following summarizes the proposed measurements methods resulting from the survey. area/variable proposed method(s) data warehouse use  weekly number of queries submitted access to subject matter experts  percentage of requests responded within one business day  mean response time for a request subject matter expert quality  average number of questions needed to be asked per subject matter issue  average number of available documents per subject matter issue  percentage of questions answered within one business day adequate level of business staff on the project  percentage of business issues resolved within a business week  mean time to resolve a business issue size of deliverable in iterative development  percentage of total project time for each iteration data quality issues at source systems  total number of issues  number of unresolved issues quality issues in bi system or data warehouse  number of unresolved issues benefits quantification  calculated roi  proposition on how the business intelligence capabilities enables the realization of business strategy  contribution to the internal rate of return business benefits definition  percentage of business benefits that are objectively measureable business benefits measurements  presence or absence of business benefits measurements process owner table 1: summary of variables analysis 6. conclusions the hypotheses of this study are focused on the factors that make business intelligence initiatives successful. a quantitative approach was used to gather data to support or reject the above hypotheses and a primary research survey was used for gathering data on the above hypotheses. the survey was conducted online during q2 of 2011. the findings can be summarized as follows. 6.1 non-technological problems dominate in business intelligence projects business intelligence projects wrestle with both technological and non-technological problems, but the non-technological problems are found to be 125 both harder to solve sand more time consuming than their technological counterparts. for all initiatives in the survey, only slightly more than 20% found the technology related problems to be the hardest. when looking at the non-successful initiatives only, almost as much as 70% found the non-technology related problem to be the hardest. the other view on this, the time spent on the different types of problems, also shows that a larger part of the time is spent on resolving nontechnological problems. this is especially true when looking at the non-successful initiatives, almost 40% of which indicate that nontechnological issues drove the most time. 6.2 successful projects share common factors certain factors or attributes of business intelligence projects are correlated with the success of the initiative. the correlation has been calculated using spearman’s rank and shown in the model that was developed using partial least squares. by using rational argumentation, it can be shown that those factors do in fact have a causal relationship with the likelihood of success. the highest correlated factors are:  a project scope definition that concentrate on choosing the best opportunities ("lowhanging fruit")  the alignment of the business needs that project tries to solve aligned with the strategic vision of business intelligence  a project that is meant to address specific business needs of the sponsor  performing data architecture at the beginning of bi initiative  having a clear strategic vision for business intelligence or data warehouse 6.3 successful and non-successful projects show differences in certain factors for a number of different factors, clear differences can be observed for successful and non-successful initiatives. this shows that successful initiatives are doing specific things more frequently than the nonsuccessful. factors with great differences are:  the type of funding of the initiative  business value provided by each iteration  an alignment of the business needs that project tried to solve aligned to the strategic vision of business intelligence  a project that is meant to address specific business needs of the sponsor  a project scope definition that concentrate on choosing the best opportunities ("lowhanging fruit") 6.4 business intelligence project have success factors that differ from is projects in general comparing the critical factors for bi projects that are correlated with success, or are otherwise more commonly found in successful initiatives, with the success factors for general is projects found in literature shows that they do in fact differ. one of the major differences between the results found in this study is the focus on non-technological factors. one example of this are the frequently quoted papers by delone and mclean (1992; 2003), that predominately discussed technological factors while the results of this study point to the nontechnological factors as being more important. 6.5 clear objective measures for csfs can be identified clear objective measures that are commonly agreed upon according to the survey exist for each of the csfs analyzed in the survey. for some of the csfs, the results are clearly pointing towards one of the suggested measures, while others can have multiple measures that claim to be equally good measures. however, due to practical reasons, to the limit of the survey size, measurements for only 10 variables were proposed. for the remaining variables, it is impossible to verify whether the remaining variables do or do not have objective measurement methods. 6.6 a statistical model can be constructed that, to a certain extent, predicts the success of bi projects a critical success factors framework for business intelligence initiatives have been developed as part of this study. the results from the survey show that 61% of variability of success can be explained by changes in independent variables. limiting the model to 5 independent variables (out of 17 that offer the highest explanatory power of the model) makes the model only slightly less powerful, allowing it to explain 58% of success variability. a conclusion from this would be that managers need only to monitor properly and manage 5 factors to achieve better probability of success, than the 20%50% currently achievable in business intelligence. for a business intelligence project to be successful: 1. business intelligence solution must be built with end users in mind, as they need to use it 2. the business intelligence system needs to be closely tied to a company’s strategic vision 3. project needs to be properly scoped and prioritized to concentrate on best opportunities first 126 4. although technological issues are encountered, all of them need to be solved 5. non-technological issues should be avoided as they can hinder the success of the bi initiative below is a summary of the support for the four hypotheses of this study. hypothesis 1. it is possible to identify critical success factors (csfs) of bi initiatives and they are different from the csfs of information systems in general. (supported). hypothesis 2. non-technical and nontechnological csfs play a dominant role in bi initiatives’ success for initiatives (supported). hypothesis 3. technology plays a secondary role and is less critical for bi initiatives’ success for initiatives (supported). hypothesis 4. it is possible to develop objective measures for each of csfs of bi initiatives primarily (partially supported the survey did not cover measurement analysis all csfs). 7. future research the survey data received describes project primarily from poland and primarily from a vendor perspective. conducting a similar research on a more generalized sample spanning projects worldwide with equal emphasis on vendors and customers would be an obvious next step. it would verify if the relationship between success and its factors is a phenomenon local to poland or rather, as we suspect, general in nature. several other frameworks were reviewed in this study. a carefully constructed study with properly chosen variables would allow comparing each framework's validity with regards to contemporary business intelligence projects seeing if one is significantly stronger than the rest of them. this is not a trivial task, because of different treatment of success and its factors, using proxy variables for success or even modeling dependencies between various parts of a success. the word critical in its strict mathematical meaning would suggest that if even one of critical success factors is missing, success cannot happen. such a relationship is impossible to model using linear regression. even the application of data transformation must be taken into account, similar to the achieved linear combinations of some functions of variables. therefore, another study could be performed to search for a model that would better explain the success using the variables used by us. it is possible that the variables used in this study would be able to predict more of the business intelligence success when organized in a different fashion because almost 40% of success variability remains unexplained in this model, it is possible that it can be attributed to the weakness of the linear relationship assumed in the model, to the missing variable that remains unidentified or even to a random factor that is influenced only by chance and which cannot be controlled by management. before a model with higher explanatory power is constructed, it is appropriate to keep looking for a missing variable that might potentially account for a significant portion of unexplained success variability. although this work proposes several objective measurement criteria for independent variables, most of them cannot be considered universally applicable in all (or even most) business intelligence projects. therefore, another study could be conducted to verify whether such universal and objective measures exist and attempt to define them. in case such measures do not exist, perhaps there is a set of measures for each variable such that at least one of the quantification methods would be universally applicable. one of the delimitations in this work was lack the treatment of npv, roi and other financial measures of business intelligence projects. since success factors are different for bi than for is in general, perhaps business intelligence managers could also employ different methods for calculating financial measures than in the case of other is. in case such differences are identified, appropriate methods should be proposed and aforementioned differences should be uncovered. refrences adelman, s. 2003. impossible data warehouse situations. solutions from the experts. boston, ma: pearson education. adèr, & mellenbergh, g. 2011. advising on research methods: a consultant's companion. 3 rd ed. huizen, the netherlands: johannes van kessel publishing. ariyachandra, t., & watson, h. 2006. which data warehouse architecture is most successful? 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(2017) why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies. journal of intelligence studies in business. 7 (1) 5-37. article url: https://ojs.hh.se/index.php/jisib/article/view/198 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden; klasol@hh.se journal of intelligence studies in business please scroll down for article why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies klaus solberg søilena adepartment of engineering, natural sciences and economics, faculty of marketing, halmstad university, halmstad, sweden *corresponding author: klasol@hh.se received 15 january 2017; accepted 2 february 2017 abstract this article gathers arguments for why the social sciences should be based in evolutionary theory by showing the shortcomings of the current paradigm based on the study of physics. two examples are used, the study of intelligence studies and geoeconomics. after a presentation of the geoeconomics literature and an explanation of what the organic view of the social sciences is, we follow the study of economics as it developed after the second world war to see where it went wrong and why. keywords economics, evolutionary theory, geoeconomics, geopolitics, intelligence studies, social sciences 1. introduction the development of theory is essential to any science. a little more than a century ago it looked as if the study of economics was going to be based on evolutionary theory. then focus shifted with the methodenstreit and then after the second world war it was decided that the new brave social sciences would be based on the study of physics. the victors of the second world war were aware that the struggle for theory was more important than the military struggle. with a military you may win the war, but to win the peace you have to convince people of your moral high ground. oakeley, in her book “history & progress” (1923), expressed it this way: the principles which england and her allies are opposing is not merely one that claims moral worth (…) it is (…) a theory of history (from chapter “german though: the real conflict”, pp. 136-7). the great struggle seems then ultimately to be more accurately expressed as the struggle whether ideas have a sway in life. the allies were fighting german materialism, evolutionary thinking, the idea of history as physical power, as expressed by treitschke (1898), and at the end simply the notion of power (macht) in the literature altogether. this was done to avoid “prussian worlddominion”. instead we got american world dominion, but without the theories that said so or explained how. we got in its place a set of unrealistic and idealistic theories such as individual free choice, equilibrium theories and free open markets. but reality finally caught up with the theory. the gap between them became too big at the end of the cold war, bringing the physics paradigm in the social sciences to a definite impasse. germany had never shown any enthusiasm for the new social sciences. now the new chinese superpower made it clear it was not going to adopt western values. in russia the news was welcomed as a relief. instead the social sciences now have to journal of intelligence studies in business vol. 7, no. 1 (2017) pp. 5-37 open access: freely available at: https://ojs.hh.se/ 6 distinguish between on one hand explaining human and social behavior as it is and on the other hand thinking about how the world could be. this development may also lead to a revival of romanticism. 1.1 the example of intelligence studies and geoeconomics not all disciplines had adopted the new paradigm. some, such as intelligence studies, have lived their lives largely outside of the ivory towers of academia. others, such as the study of geopolitics, never left the old paradigm. those disciplines that embraced the realpolitik assumption found themselves to be popular again (they had been relevant all along, but now others rediscovered their relevance). the new version of geopolitics, called geoeconomics, automatically looked to the study of biology rather than physics. the aim of geoeconomics is to present intelligence (e.g., economic, political, or social) in the form of maps, wisdom and maxims that help explain current events and make predictions (for examples see søilen, 2012, pp. 140-295). it is a discipline adapted to the world of globalization and multinational enterprises which shifted the power balance from the nation state to private organizations. the methodology of geoeconomics is similar but not exactly the same as the study of geopolitics (søilen, 2012; søilen, 2010; søilen, 2016; wigell and vihma, 2016). geopolitics was defined as an evolutionary science right from the start with kjellén (1914) and had only to continue. the new study of intelligence studies, with its focus on information and its tradition in the practical work of intelligence organizations may also be based in evolutionary theory, even though most contributions in competitive intelligence, market intelligence and business intelligence do not take this approach. like so many other management disciplines they focused on solving practical problems and as a consequence have been seen as less valuable as academic disciplines. critics fail to see that these disciplines left theory because the existing scientific paradigm seemed unrealistic and to change it seemed an impossible task. while intelligence studies is often concerned with the micro level, geoeconomics is primarily occupied with the macro level. this then is how the two studies fit together, 1 thanks to karin jakobsen at ventus publishing for permission to reprint parts of the book for part 2 of this article. theoretically, methodologically and in the content they study. but unlike the study of geopolitics, intelligence studies is at the very beginning of its theory development, mainly because it has lived its life largely outside of academia and gained its legitimacy as a distributor of valuable practices to professionals. for geopolitics and geoeconomics it is a question of sticking to their roots, adjusted for a number of biases identified during the past half a century, which can be summarized as the seduction of maps (i), the seduction of history (ii) and the seduction of current events (iii) (see søilen, pp. 21-35). the study of geoeconomics is what we today should call a multidisciplinary field building on the study of history, geography (maps) and political science (the study of power based on realpolitik assumptions) to explain current events and try to predict future action by organizations. intelligence studies is also practiced as a multidisciplinary field, in fact all relevant social sciences today are forced to become multidisciplinary, meaning simply to revert the failures of specialization by the current scientific paradigm in order to become more relevant again. the overspecialization and over-compartmentalization that was the physics paradigm has led to entire disciplines like economics and political science becoming ever more irrelevant. the next section of the paper is in large part a reprint from the book “geoeconomics” (søilen, 2012)1 which explains the relevance of geoeconomics, its methodology and how it fits with evolutionary theory and the evolutionary approach to the social sciences, but it also presents current research in geoeconomics. 2. geoeconomic theory 2.1 the geoeconomic literature there cannot be any politics without political realism, and economic issues lie at the core of politics. the person, company, or nation which possesses economic wealth has resources, and resources are power; where power is defined as the ability to control the actions of others, thus increasing one’s own opportunities for creation of further and future wealth. we find this same notion in klare’s understanding of geopolitics as the study of “the contention between great powers and aspiring great powers for control over territory, resources, and important 7 geographical positions, such as ports and harbors, canals, river systems (fresh water supply), oases, and other sources of wealth and influence” (klare 2003: 51; see also klare 2001), but today it’s no longer the nation states who are driving these processes, but corporate interests which answer to different logic: thus the importance and relevance of geoeconomics (søilen, 2012, p 104). cowen and smith (2009) have previously shown how there is a recast from geopolitics to geoeconomics as the globalization ideologies from the turn of the 21st century have faltered. instead events have been understood with a geopolitical and geoeconomic logic. at the same time there has been an auto-destruction during the last decade of the relevance of critical geopolitics as presented by dalby (1991) and tuathail (1996). more constructivist criticism against geoeconomics comes from other geographers like sparke (2007). much of the interest for geoeconomics is coming from authors and topics outside the western world, for example from russia (cf. alexander, 2011; anokhin and lachininskii, 2015; lachininskii, 2012; rozov, 2012), the russian-german relationship (szabo, 2014) and former soviet states (scekic et al., 2016), but first of all china (cf. ciuriak, 2004; holslag, 2016; hsiung, 2009, huotari & heep, 2016, kärkkäinen, 2016; khurana, 2014; søilen, 2012 b) and comparisons inside of china (schlevogt, 2001), as if the political struggle is also a struggle for ideas, and more precisely for a new scientific paradigm. there are also those who see the geoeconomic logic as a new balance of power between east and west (couloumbis, 2003), and those who argue that the us policy was geoeconomic all along (mercille, 2008), or still is (morrissey, 2015). as shown by barton (1999) the system of flags of convenience can be seen as one of the oldest examples of geoeconomic flexibility, or a logic of geoeconomics. the first writings on geoeconomics had a focus on natural resources (kärkkäinen, 2016), realizing that the third world could have greater strategic importance than europe (hudson et al., 1991), and the west (oil, water). resources would in many cases have a larger meaning and include the financial system (sidaway, 2005), and infrastructure like oil and gas pipelines (vihma & turksen, 2015). also the notion of geography as space of economic importance has reemerged, not only concerning the new passages by the north pole (moisio & paasi, 2013). what is largely missing in the current literature is the attempt to build and explain geoeconomic theories. in this article we suggest how this is done through a paradigm shift, by shifting attention from the study of physics to biology and evolutionary theory. the shift itself is not new, but has been suggested at numerous intervals for more than a century. as a consequence the focus in the next section is just as much to explain historic events in the history of the social sciences, and more precisely for the study of economics and business. 2.2 the organic view of the social sciences the organic view of the social sciences says in essence that we human beings are not so much in control of our behaviour as we think we are. we are predominantly emotional and not particularly rational creatures. we learn not by theory, but by trial and error, that is through failures. consequently, we should seek to understand human behaviour more by personal experience and by studying values, which are the basis of character-formation, rather than by losing ourselves in the uncharted waste of abstract theories and assumption of rationality. the latter may be intellectually interesting, but do us little practical good. all living organisms are nowadays studied in the light of evolutionary theory, except for man. we have to ask why. why should the social sciences be any different from zoology in this respect, unless we hold that man stands outside biology? if we do hold that, as some christians do by advocating creationism, then at least we are being consistent; but that is not the position of the social sciences today. yet these sciences continue to define themselves as not part of biology. the intention here was good: this line was taken partly in order to emphasize that man has moral obligations. but a problem arises when the morality and values assumed are ones which belong to and favour one particular civilization or viewpoint. then we are facing not morality but moralism, the attempt of one person or culture to impose its values on others. we see this clearest today in the struggle between western and eastern values. in the light of claims about valueneutrality of the social sciences, it is problematic that most social-science journals support western values. the validity of western values must be questioned, if the social sciences are to have any credibility in the 8 21st century. or alternatively, the study of human behaviour must revert to the humanities, where moral positions are less problematic. it is no more than a century ago that we eliminated the moral component from the study of economics. at the beginning of the twentieth century, but particularly after the second world war, the discipline of economics decided to assimilate itself to physics and its logic of “dead material” (non-organic). the original motive for this was that physics was and is a successful science, and the social sciences needed greater rigour. it was also seen as a way to solve the normative problem, by literally taking the moral component out of the equation. furthermore, it was an inevitable consequence of splitting the discipline of political economy into two instrumental parts, political science versus economics and, later, management. over the past two decades, there has been criticism of this approach, and of the lack of results produced by ever greater specialization. over specialization seems to have shifted much of our research away from reality and towards obscurity, abstraction, and dogma. the phenomenon of interdisciplinary studies can be seen as a reaction against this development; so we saw a significant growth of interest in interdisciplinary scholarship around the turn of the 21st century. but this only solved parts of the problem. another characteristic of twentieth-century social-science research and methodology was a tendency towards linear thinking. everything in economics seemed to be explainable in terms of the intersection of straight lines on x and y axes. our linear way of thinking – as opposed to the cyclical ideas of ferdinand tönnies (1887) and the pendulum ideas of hegel (1820), his thesis, antithesis, and synthesis – can be traced back to the old testament and the introduction of christianity to europe. the notion was reinforced in the period we call the enlightment. the linear paradigm peaked with the contempt for the historical method on the part of the social sciences following the second world war. that is the direction that is here being questioned. we must question not only the lack of useful results, but equally the claim of objectivity. so what are the alternatives? the discipline of geoeconomics is founded on an organic understanding of social behaviour. this is also a method borrowed from the natural sciences too, but from the discipline of biology. by “organic” we mean that man and human organizations function rather like living organisms. they too are brought into life, grow, and fade away, some sooner than others. evolutionary theory is a powerful explanatory tool for any science, including the social sciences. that does not mean that all social behaviour can be understood by studying evolutionary theory, but this is the model with greatest explanatory strength and most potential to explain and predict human behaviour. this line of thinking is not novel within economics. evolutionary thinking got off to a good start in the discipline of economics in the usa with thorstein veblen in the closing decades of the nineteenth century. but economists chose to abandon evolutionary theory at the turn of the twentieth century, in part because it did not correspond to our political convictions about how man should think about himself and society. the new slogan of the time was liberalism, individualism, and free choice – ideas that had been seriously challenged by evolutionary thinking, which had a more deterministic perspective on human life. the newly liberated discipline saw that as infringing on our ability to think of ourselves as free individuals with almost unlimited choices. furthermore, a new world power needed to make a break with the existing scientific tradition, especially to the extent that it was associated with german thinking. the change of scientific paradigm corresponded in time to the rise of the american empire and continuation of englishspeaking world dominance under new leadership. thus, although the original thought underlying the new empiricist paradigm was largely european (austrian, french, british), its development was mostly american. the organic view of social behaviour in fact goes back far further than the nineteenth century. a venetian ambassador to france once said “states are like men in that their vigour and prosperity does not last forever; they mature, they grow old, they succumb” (quoted in ross and mclaughlin 1981: 305). the venetian diplomatic corps wrote some of the finest geopolitical analyses of all time, and their city’s dominance lasted for more than three centuries. the methodological focus was not on algebra, 3×3 matrices, and cartesian coordinates, such as we see so often in the social sciences today, but much broader. it covered observations on national character, ways of life, natural resources, and military strength and tactics. this methodological tradition later 9 spread to rome and to the catholic church. we find it, for instance, in the writings of olaus magnus, archbishop of uppsala, who in 1555 published an extensive book on the history of the nordic people (magnus 1982). the methodology was representative for the time; readers wanted books to give clear answers to real problems. a modern-style empirical article would probably have provoked outright laughter – “how long did you live there? where did you travel? do you speak the language? you mean to say you know because you questioned 250 people at a supermarket?” even if you put half a dozen of these research articles together it can still be difficult to say anything specific about a given social problem. often it will be more useful to read a good magazine, like the economist or some quarterly review. consequently companies often complain that they get too little value from modern social-science research. if business-school academics largely ignore this critique that is largely because they are safe to do so: it does not threaten them. they are responsible not to the world of reallife business but to a promotion system which is based on the type of research that businesspeople are complaining about. so companies often look for the social data they need among other sources, by piecing together gleanings from geography (maps), history, and current events (søilen, 2012, pp. 107-109). 2.3 evolutionary theory versus environmental adaptation in order to apply evolutionary theory to the social sciences we need to distinguish between a number of different issues. one problem is that people mean different things by the word “evolution”. the term is often used to refer to the fact that all living organisms are linked by descent from a common ancestor. alternatively, it is sometimes used to refer to ideas about how the first living organisms appeared; that might instead be called “abiogenesis”. we also use “evolution” when we really mean natural selection, which is just one of the many mechanisms of evolution. françois perroux (1983: 23) defines evolution as “changes that are interlinked, as opposed to a ‘random’ succession of events and structures occurring in irreversible and historical time”. these changes are what we may call genotypic changes. in a strict sense then, non-heritable changes are not part of what we call evolution. instead we may call them environmental adaptations. to many social scientists it seems that environmental adaptation is more relevant than evolution to their own subjects. evolutionary theory is relevant chiefly to the natural scientist, who studies behaviour over generations. not even the long-term business cycles of schumpeter and the kiel school bear much relation to evolution. what seems to be most relevant for evolutionary economists is therefore man’s phenotype, where phenotype is defined as the morphological, physiological, biochemical, behavioural, and other properties exhibited by a living organism. an organism’s phenotype is determined by its genes and its environment. at the cultural level mutation is not uninteresting to economists either: chinese and pakistanis are at least two mutations apart, europeans and africans perhaps as many as six or more. there are particularly many mutational differences within the african continent as this is where homo sapiens first evolved. we need to consider what role, if any, these particular genetic differences have for economic behaviour. as a comparison, modern neuroscience is showing a genetic basis for behavioural differences between the sexes: for instance, females communicate more sensitively than males. then there is the variable of change. we acquire new customers, develop and buy new computers, and communicate with one another using new tools and behaviour. we must distinguish between those changes which are “evolutionary” and those which are not. evolution in biology refers to (i) “the biological process in which inherited traits become more or less common in a population over successive generations”, recognizing that (ii) “over time, this process can lead to speciation, the development of new species from existing ones” (wikipedia article on “evolution”). under (i), we need to discover whether, say, a travelling salesman’s son becomes better at selling, whether younger people today are able to use computers more efficiently than older people, and to what extent the content of our communication and way of communicating are changing with each new generation. under (ii), we need to discover how rapidly these inherited changes occur. what biologists disagree about is not whether these changes occur, but whether they are continual or happen in occasional bursts (so-called punctuated equilibrium, advocated for instance by stephen jay gould). the extreme case of change, in which an animal’s lineage diverges into 10 separate species, seems to have little relevance for the study of economics, for the foreseeable future at least (ii above). what cannot be ignored by economists is the modification of “inherited traits” (i). what we need to discover is whether these changes have any implications for our economic models, and how significant they are. in other words, we need to ask what are inherited traits and what are explanatory factors to be accounted for in economic theory? it should be possible to begin coming up with answers to these questions soon thanks to the advance of genetic research. without ever forgetting the contribution attributable to man’s free will, we should be able to explain how a given individual will behave, based on his or her genome together with what we know about how he or she has acted in the past (habit). when we achieve this we are starting a real scientific study of man, not before. for evolution to continue, there must be mechanisms to create or increase genetic variation, and mechanisms to decrease it. the mechanisms of evolution are mutation, natural selection, genetic drift, recombination, and gene flow. these can be grouped into two classes: those that decrease genetic variation and those that increase it. we can treat the physical properties of the world as constants. human behaviour is changing. it is man’s appreciation of how the physical properties can be exploited which evolves. then there are the other limitations as to man’s action related to his resources; the material, capital and what man is capable of doing. what are then the fundamental buildingblocks of geoeconomics? from a materialist perspective these could be material, capital, people, and actions. by acting on material mankind initiates an evolution which is proper to his species. since mankind has chosen not to share material in common, but to control it through the institution of private property, capital is another building-block. capital and private property are products of political law. other man-made limitations include social rules and ethics, whether these are causes or effects. the first question is why man acts as he does? the answer will tell us what kind of actions to expect, which will help us foresee the direction of our evolution. when facing a decision, man participates in the process as a whole being; his interests are not only economic, but aesthetic, sexual, and humanitarian. these other interests cannot be assumed away if we are to understand the underlying causes or motives for human action and to suggest realistic answers. or, as veblen (1899: 10) puts it: “changes in the material facts breed further change only through the human factor. it is in the human material that the continuity of development is to be looked for; and it is here, therefore, that the motor forces of the process of economic development must be studied if they are to be studied in action at all”. this is a materialist approach, without necessarily being a marxist one. we appreciate the complexity of the task when we consider that we must list all the possible motives for action man can have, and decide which motives are strongest for each set of possible actions. we would need to do this for all human beings and all their economic actions every day. and it will be difficult to decide which actions are economic and which are not, since an economic action may be caused by a non-economic action. unless we can achieve this, which at this point seems well-nigh impossible, we will not achieve complete certainty about our evolution. the question then becomes, how accurate an estimate can we make of a person’s, a company’s, or a nation’s evolution, based on what we can observe? and will it be accurate enough to be worth our undertaking? we can always describe economic actions in terms of basic principles of evolutionary science and make them serve as examples without pretending that they have predictive capabilities, in much the same way as casestudies are written today: as descriptive data that resemble real life. one thing is clear: the better the knowledge we have about a subject’s actions, the greater the likelihood of getting accurate predictions. it will not do to sit at a desk and draw general conclusions from small data-sets. this is a major difference from the mechanistic approach, whose advocates believe that useful conclusions can be drawn from mathematical reasoning once a number of limited variables are found and defined. the major problem here is that they are way too few to be of much value. the natural sciences nowadays are concerned with “dynamic” relations and series. unlike chemistry, which was able to move away from its taxonomic stage and develop into a modern science, economics ignored new developments in the study of biology and chemistry and clung instead to the idea of natural rights, with its roots in the writings of the eighteenth-century french physiocrats, 11 men such as quesnay, baudeau, le trosne, and mirabeau, but also condorcet, gournay, and turgot (cf. veblen 1899: 2). these men laid the groundwork for the british development of economics, which evolved into the lausanne school with its refinement of the mechanistic programme as applied to economics, and that in turn led to the blossoming of the new approach in the usa with the neoclassical school, first of all the chicago school of economics, setting so the standard and the definition of what the nobel prize in economics should reward. it may be that the marginalist school will fade away as the american empire declines, or because the number of remaining marginalists drops below some critical mass, rather than as a consequence of the persuasiveness of evolutionary arguments. others would argue that the marginalist school will wither when other schools can make better predictions about economic behaviour. and these possibilities are not exclusive. this is a constructivist perspective on social-science paradigms. identifying the limitations of the marginalist approach, criticizing its assumptions, in a word “deconstructing” it, is only a first step, and will not be enough to make geoeconomics a real alternative. besides, many marginalists would agree with their critics to an extent: “our approach is an over generalization of reality, but it is the only way we know to develop an economic science”. if evolutionary economists want to offer an alternative, they must develop an alternative method which yields answers to real-life problems. instead geoeconomics can succeed where evolutionary economics or the evolutionary approach to economics has failed by developing a coherent methodology. the deconstructionist critic argues that marginalist economics typically assumes perfect competition, meaning that all parties have equal ability to compete. this assumption is refuted by what is called the matthew principle, from the words of the evangelist: “for whosoever hath, to him shall be given”, implying that it is easier for the rich to accumulate than the poor (boulding 1981: 75). this is relevant to evolutionary economics since economic development is almost bound to increase inequality, particularly in its early stages (op. cit.: 77). the great evolutionary development of the last two hundred years has undoubtedly increased world inequality (loc. cit.), even though more people are enjoying a higher standard of living. these facts in themselves will put further pressure on the marginalist school. “the activity is itself the substantial fact of the process, and the desires under whose guidance the action takes place are circumstances of temperament which determine the specific direction in which the activity will unfold itself in the given case. … the economic life history of the individual is a cumulative process of adaptation of means to ends that cumulatively change as the process goes on, both the agent and his environment being at any point the outcome of the last process. his methods of life today are enforced upon him by his habits of life carried over from yesterday and by the circumstances left as the mechanical residue of life of yesterday”. (boulding 1981: 75–7) in mainstream economic theory these forces are assumed away. another important assumption in marginalist economics is the maximization of gain. in reality, do we try to maximize gain, or to minimize the fear of loss? do we compete against all alike, or less against certain groups, family, and neighbours? marginalist economics also assumes free choice. this is questioned by a number of physicists and neurobiologists (cf. nicolas gisin in brunner, gisin, and scarani, 2005). research by angela sirigu showed that experimental subjects formed a conscious intention to perform an action only slightly after they had in fact started to perform it. if that is true, it puts the whole of rational choice literature into question. possibly the most convincing argument for an evolutionary approach in the social sciences was propounded by the russian scientist petr kropotkin. kropotkin (1902: vii–x) observed two aspects of human life which may help to explain behaviour. one was the extreme severity of the struggle for existence, and the great loss of life when food is scarce (the law of mutual struggle). the other was the fact that bitter struggle for the means of existence fails to occur among animals of the same species (the law of mutual aid). when food was plentiful he observed the phenomena of mutual aid and mutual support. thus individuals who enter the market economy from a situation of mutual struggle are often more motivated to work and succeed. the concept of struggle for existence as a factor in evolution was introduced by darwin and wallace. the idea of the law of mutual aid was suggested by kropotkin’s professor at the university in st petersburg, karl kessler, who was also dean of the 12 university. kropotkin essentially took up kessler’s side as and proved both of them empirically. when man has more than enough money to live he sets out to help his fellow man. this observation speaks against the assumption of constant competition, but fits well with observations of billionaires’ behaviour, for instance in the usa recently, at least on the face of things. bill gates and warren beatty, like rockefeller and carnegie before them, have decided to give away large parts of their fortunes to charity. the problem can also be seen from a more selfish perspective: it is easy to spend a million dollars on consuming, but difficult to spend a billion dollars. there are only so many things to buy. our needs may stay constant, but we want different things. giving may still be an expression of pure self-interest, as when it results in greater power and an enhanced reputation. the problem from the perspective of economic theory is that we have constructed our economic models with the individual as the reference point, acting to maximize his own self-interest at the present moment. our models have been set up to portray economic life as a matter of seeking to maximize satisfaction of our wants, assuming that the individual knows what is best not only for himself, but indirectly also for others. all these assumptions must be questioned. the discipline of economics has been imposing individualist assumptions, not only at the cost of thinking about society, but also at the cost of thinking for the long term. attempts by economists like nicholas georgescu-roegen to discount for future generations were rejected since it was thought – justifiably – that this would make our economic models very complicated. but perhaps even more important was that it would call into question the way we live. georgescu-roegen was a mathematician, so he did not object to the complexity, but it was argued that the models would be difficult to explain to a non-mathematical audience and to practising businesspeople, and difficult to apply. his ideas about discounting for future generations were seen as a political statement which broke with existing utilitarian practices. they were seen as a threat to our modern liberal democracy built on free trade. thus, from being the favourite student and follower of schumpeter, he soon became an outsider, and went to teach at minor universities. but in reality, of course, the accepted margin a list or neoclassical models are just as political as the models advocated by georgescu-roegen. but worse, and as i will show in more detail, they are leading man’s development in the wrong direction, encouraging the consumption of future generations’ resources. some will see this as implying a rather sombre outlook on human existence, but there is another element to consider, as mentioned before: our ability to shape our own evolution. we have the ability to change our nature by altering our ideas and actions (habits). in the short run we can adopt new habits, in the long run we can expect changes through genetic modifications and mutations. that is, we are not necessarily the pre-programmed competitive machines we are sometimes made out to be, but a complex competitive organism where only one aspect is mechanical. thus, to be considered truly human in today’s world one requires a good portion of empathy and an interest in others’ wellbeing. these values are already becoming part of our nature. science has shown that we have become more human just by living closer together in cities. these findings refute the idea, held by some, that we were more social and more caring when we lived in small isolated groups. the fact that we can include empathy in our equations, however, does not mean that we must abandon evolutionary theory or our biological explanatory models. empathy is part of nature, and can be explained as such. social ideas have influenced us for millennia, but they first had significant impact on our lives during the period we call the enlightenment, in the eighteenth century, through the writings of philosophers such as voltaire, montesquieu, rousseau, hume, kant, and schiller. to ignore the values bequeathed to us by these men and others would mean to close our eyes to human evolution. we should not allow ourselves to be reduced to mere animals, not even when we get bored with the entire project of civilization (as sometimes seems to happen) and decide to inflict massive destruction on our own kind. afterwards we wake up full of remorse. this, then, must be the full perspective of any introduction to the theory of competitive advantage, if we are to address the interests and concern of all mankind. the biological perspective is important not only because it gives us scientific data (since we indisputably are a part of evolution), but also because it helps us to realize our limitations. when evolutionary theory was abandoned at the turn of the last century (economics) and again at the 13 end of the second world war (political science), we swapped realism for elegant models and politically-correct opinions about the world, which have merely ended by making our studies less useful and putting our species in greater danger. instead we need more realistic models that can incorporate the idea of change (søilen, 2012, pp 107-114). 2.4 theoretical foundations and academic influences for the evolutionary approach the study of economics has two objectives; first, to develop theory to attempt to explain and predict human economic behaviour (economic theory), secondly to provide economic actors or agents with tools enabling them to conduct business and public operations more efficiently (applied fields). of these, the second is the less problematic. the discipline of economics is continually providing economic agents with practical working tools to enhance organizational performance and efficiency. much of this is done under the heading of management, and in close collaboration with practising businesspeople. it is the former objective which is a cause for concern. the larger methodological question is what basis we can found the discipline of economics on, to give its models predictive power. are there any such models? the choice of physics as a model for the development of economic theory, a methodological direction which has been particularly dominant since the second world war, has increasingly been criticized by economists, and not only by evolutionary theorists, but by members of a variety of schools. many of these critics see biology as an alternative methodological direction that merits investigation. modelling economics on biology is not a novel idea; it is an attempt to revisit a number of questions which were left behind at the turn of the twentieth century. thus the fundamental question is whether the concept of evolutionary economics was abandoned prematurely, or for good reasons. the french philosopher and mathematician rené descartes inspired two lines of scientific thought. one was abstract, mathematical, and mechanistic; it led to significant advances in knowledge thanks to men like leibniz and newto2. the other approach explored the 2 newton is said to have been inspired by descartes after having read his “geometry”. development of our living world with everything in it, from insects to animals. this second approach was taken forward by men like buffon (1749), lamarck (1809), cuvier (1812), wallace (1876), darwin (1872), and wegener (1915). in these terms we can say that evolutionary economists are trying to show where the former line of thought falls short when applied to the understanding of economic behaviour, and where the second line may be of help. adam smith (1776) is often used as a reference by the neoclassical or marginalist school of economic thought. we shall argue that smith, thomas malthus, and alfred marshall (1890) were in fact all inclined towards the evolutionary approach. if that is so, it means that the neoclassicals are not so much “classical” as “neo”. the “marginalist school”, which is a better term for the neoclassicals, might also be called the “mechanical approach”, as compared with the evolutionary approach. the marginalist school, or marginalism, studies marginal concepts in economics: problems related to marginal cost, marginal productivity, marginal utility, the law of diminishing rates of substitution, and the law of diminishing marginal utility. marginal calculations were a natural direction to follow once the physics paradigm had been selected. the evolutionary model is implicit in marshall’s principles of economics, even though he did not incorporate the idea into his more formal theories. that was part of the problem for evolutionary economists at the turn of the century: they had not succeeded in producing applicable theories and models, but mostly left their analyses on the descriptive level. so when it came to building a scientific platform on which the positivist study of economics could stand it was the french economist léon walras who was chosen. walras and his successors had mathematicized the newtonian system3. they could offer the discipline of economics a rigorous methodology which promised to deliver elegant answers, all in the spirit of the natural sciences. the underlying assumption was that if this method had worked wonders for the natural sciences then it should do the same for the social sciences. in other words, their answers promised to be more precise than what 3 their primary tool was elementary and linear algebra. 14 economists had delivered before; and that promise was delivered. the fact that the new models and their predictions often failed to correspond to actual economic behaviour was mostly due to their assumptions. they were nevertheless far better than nothing (a point which continues to be a main argument for the marginalists), and hence the evolutionary perspective was gradually lost from the discipline of economics (boulding 1981: 17). however, it soon became clear that the problem was no longer one of precision, but of relevance. in other words, the answers were detailed and elegant and might have been correct, but they did not correspond to the economic realities. later, with paul samuelson – whose models essentially involved stable parameters and a dynamics based on stable differences or differential equations – economics became even more newtonian, less darwinian (boulding 1981: 84). if it were not that current economic theories have still not demonstrated themselves to be the relevant predictive tools that economists had hoped for, our scientific journey would probably have ended here. but it continues. the best philosophical foundation for economic research seemed to many to be a renewal of utilitarianism. the rehabilitation of economic theory was due to the austrian carl menger – known to students today for his theory of supply and demand. menger’s essential aim was to discover the laws determining prices and to initiate discussions of supply and demand, human needs and marginal utility (schumpeter 1992: 84). the biggest flaw in his assumptions is that man is not entirely hedonistic, his nature is not wholly fixed and predetermined: he is not simply a bundle of desires that are to be saturated by being placed in the path of the forces of the environment, but rather a coherent structure of propensities and habits which seeks realisation and expression in an unfolding activity (veblen 1898: 11). both karl marx and menger were much influenced by ricardo. menger gave rise to what has today become mainstream economics, but that was not his original role. menger was at one time the outsider, at a time when marx and the german historical school led by gustav von schmoller represented the consensus 4 it was they who called menger and his followers the “austrian school”, to distinguish them from prevailing thinking among german economists. 5 this point is discussed clearly by bertrand russell (1903). within the discipline of economics4. critique of the “mechanistic approach” is by no means new either. in his 1875 book the character and logical method of political economy, the irish classical economist john elliott cairnes disputed jevons’s idea that economic truths are discoverable through mathematical reasoning (op. cit.: vi). what maths can do is illustrate and simplify conclusions that have been reached by other methods, or in his words: i have no desire to deny that it may be possible to employ geometrical diagrams or mathematical formulae for the purpose of exhibiting economic doctrines reached by other paths. (op. cit.: vii) the reason why mathematics can have only limited application to economics is twofold. first, “its close affinity to the moral sciences brings it constantly into collision with moral feelings” (op. cit.: 3). the second is even more fundamental: maths is ultimately by nature just another language, even if of course much more precise than ordinary languages5. but precision by itself does not help. in the same way as we do not solve a problem by translating it into a foreign language, maths by itself cannot solve economic problems. it can only express what is already there in a simpler and clearer form. progress using maths in the social sciences only comes through our ability to see and handle ideas more easily. the advantage is the same that came from the development of symbolic logic6. both mathematics and symbolic logic are very helpful in summing up what we have already discovered, but we have to draw the inferences for ourselves. why has physics not provided a successful cornerstone for the social sciences? when we compare the results of the social sciences to those of the natural sciences, we find that social phenomena are more difficult to study, less tangible, less physically observable. social systems are just too complex if we hope to pin down individual behaviour; they contain too many variables, with too many possible and often irrational outcomes, to be explained via physics and mathematics alone. more important, our mathematical approaches are not capable of treating the element of change – 6 unfortunately, the success of symbolic logic has reduced interest informal logic, a subject with much greater applicability in everyday life. 15 what is often referred to in the scientific literature as the dynamic aspect. newtonian and cartesian numerical mathematics, which has dominated the study of economics for a century now, is unsuitable for the more structural and topological relationships found in evolutionary systems, except insofar as the topological relationships can be mapped and converted into numerical relations (boulding 1981: 86). economic theory as developed in the twentieth century builds on a number of mechanistic assumptions. these assumptions were first criticized by herbert spencer in his 2 volumes book “the principles of sociology” (in peel, 1972: 6), who held that they must be wrong because “it assumes the character of mankind to be constant”. or put differently, the problem is that “existing humanity” does not exist, but is constantly changing. change is the law of all things, true equally for a single object as for the entire universe; all things are mutable: shells into chalk, sand into stone. “strange would it be, if, in the midst of this universal mutation, man alone was constant, unchangeable” (op. cit.: 7). everything is in a state of continual change or fluctuation, even the things we think of as most stable. dynasties and private fortunes seldom last more than a few centuries; even a stone monument has a limited life. we seem to have a cognitive difficulty with change, probably because we constantly need to find order in our everyday lives. we have a strong need to live and find our balance in the present, hence we prefer to think in terms of constants rather than of fluctuation. this seems to be the way we are born. in much the same way, we do not feel the earth speeding round the sun, and that is good: if we did, we would not be able to concentrate on anything else. in other words, we seem inclined to think in the linear terms of a static, mechanistic world perspective. likewise, we think we can have knowledge of the future, but we cannot. instead we are continually surprised; and to top it all we are not surprised that we are constantly surprised. within rational choice theory we might define these observations as a set of rationality errors. they mark a biological limit to our understanding of the real world, i.e. of kant’s ding an sich. 7 paul krugman (1996) calls neoclassical economics and evolutionary science “sister fields” (though he will not give up the maximization and equilibrium approach). from the above one might take it that we are confronted with an either/or choice between marginalist and evolutionary approaches. to the extent that these premisses are not contradictory, the method used should be whichever method has the strongest predictive power in each particular case of economic behaviour. it is not a question of either newton and physics or darwin and biology7. so far as we can tell to date, the evolutionary approach to economics is not necessarily, and not necessarily always, a replacement for neoclassical economics. for instance, it seems that it is more suited for studying economic behaviour over the long term, when the element of change becomes most significant. there are many problems, e.g. of production that are simple enough for marginalist calculations to be of value, but they seldom include problems of social complexity like international business. to complicate the question further, in many cases marginalists and evolutionary economists will both espouse the same methods or theories. so for instance game theory is seen as a marginalist contribution by some, because it can be highly quantitative, but as an evolutionary approach by others, because it is dynamic and does not seek to maximize a given set of variables. game theory can also be studied from either a mathematical or a nonmathematical perspective, as in the writings of von neumann and morgenstern (1944) on one side and axelrod (1984) on the other (søilen, 2012, p. 119). 2.5 on the european continent: from buffon to lamarck, cuvier, and darwin much attention is given to darwin, but mechanisms of evolution had already been set out by the french naturalist jean-baptiste lamarck in his classic 1809 work zoological philosophy. lamarck began as a botanist before becoming a professor of invertebrate zoology, and he is known for having developed the first positivist theory of evolution for living organisms, but also for the influence he had on darwin8. others would want to mention buffon as a pioneering figure. his contributions established the scientific foundation and the 8 darwin learned about lamarck through a fellow student while studying medicine at the university of edinburgh. 16 scope for natural history, a subject which he himself thought always leads back to a reflection on oneself (buffon [1749] 1984: 39)9. buffon called this the first truth: ...that man must arrange himself in the class of animals, of which he resembles above all in what is material, but even his instincts may seem more certain than his reason, and his industries more admirable than his arts. (op. cit.: 45) he reckoned that, when mankind becomes aware of the true possibilities contained in his intellect, “he could make his nature perfect, morally, as well as physically” (op. cit.: 247). this project, to improve mankind morally, has given rise to a whole series of normative, politically-correct studies in the social sciences, in connexion with topics such as gender, sustainable development, immigration, and human rights. putting it differently, many university departments today, especially in our newer universities, are not so much asking what the truth is, as what it ought to be, based on what kind of human beings we want to create. this becomes a new form of positivism whereby politicians steer science in an intended direction instead of letting it be free. it may also be seen as an evolutionary approach, but we must then distinguish normative from positivist evolutionists. unlike other animals, man can decide the direction of his own social development. in other words, he can elevate himself. this is done by creating an ideal, not by accepting what is “natural”. the problem, when we move away from the notion of natural truths, is to know which ideal is the right one to follow and who should decide which it should be. some academics go so far as to claim that the “natural” as such does not exist. one can then argue that the sciences can never really escape from the domain of politics, since all scientific findings have political consequences, whether we are talking about stalinism or the atom bomb. on the other hand one might argue that more politics will not make university life any more manageable, as became apparent on campuses all over the western world in the 1960s and 1970s. it is true that we can never become fully objective in the sense that we can escape our own subjective minds, but we can 9 buffon wrote his magnum opus over the years 1749 to 1788. a summary edition appeared the following year, in 1789. develop scientific methods to reduce our biases. to argue otherwise is in a sense to be a methodological fundamentalist. one might ask what a book about zoological philosophy has to do with the study of human behaviour. the fact is that when lamarck wrote about living organisms in general he actually had mankind in mind, as we see in a passage such as: in order to give a living body the ability to move without impulsion from a communicated force, to be aware of objects outside of himself, to form ideas, to compare or combine these ideas, and to produce opinions which to him are ideas of another order, in one word, to think; not only is this the biggest of all miracles which the forces of nature have attained, but, in addition, it is the proof of the employment of a considerable time, as nature has achieved nothing but gradually. (lamarck [1809] 1994: 122) we might see lamarck’s contribution to evolutionary economics as implicit in his writings, even though it was herbert spencer who first developed the idea explicitly: namely, that societies are like organisms, in that they (i) augment in mass, (ii) gain in complexity, (iii) their parts gradually acquire a mutual dependence, and (iv) society is independent of each of its component units, i.e. is not affected by individual deaths. these similarities are often referred to as the four parallelisms (peel 1972: 57). there are other parallels to human life as well. in chapter vii of his book lamarck discusses the influence of different circumstances on the actions and habits of animals, and the influence of those actions and habits on their living bodies, as causes of modifications to their structure and anatomy (peel 1972: 206). habits become a second nature. lamarck reminds us that for a long time we have observed the influence that different states of our organism have on our character, our inclinations, our actions, and even our ideas. but he also notes that no-one has yet recognized the influence of our actions and our habits on our structure. our whole organism changes when our behaviour changes. these changes are so slight that we hardly notice them. they are hard to notice because they only become apparent after a very long time. to demonstrate this, look at an old photo of your grandparents. not only the clothes are different: their facial expressions 17 are different too. the implication is that we have become our own evolutionary machines, even though the changes that we can observe are very small. what is driving this machine forward so fast is a system of technological development and economic growth. the changes in our organisms are initiated by needs. “if these new needs become constant or long lasting, the animals take on new habits, which are as constant as the needs which brought them to life” (peel 1972: 208). lamarck notes that the great diversity of animal life must be understood against the background of the great range of diverse needs that appear when new species encounter one another in an ever-changing environment. basic human needs for food, clothes, and shelter are much the same now as they were in the stone age, but their expression is changing because of the fact that we as human beings create new needs through a social mechanism called in everyday life “fashion” and the constant struggle for ever-higher living standards (again a form of social competition) in the shape of better and more diverse food, more clothes, and larger and more expensive houses than others have, than our neighbour has. in marketing we call this last form wants, to separate them from needs, which are more constant). we do this because we are always seeking greater comfort or because we want to impress our fellowman, out of some version of a struggle to survive but also out of habit and perhaps because we do not always know how else to express our will. this creation of new forms and degrees of need is a human characteristic, because we have the time and the resources to indulge in it. our needs are seemingly endless and depend only on our imagination. but the strength of some needs decreases as others are fulfilled. man is always looking to maximize his satisfaction (the marginalist perspective). we know too that types of need change: from basic human needs to luxury and what are understood as projects for self-realization, as we ask what the meaning of life is (evolutionary perspective). the discipline of marketing, we recall, is largely about how to register and communicate these needs and wants. as human being we act when there is a need to change something, to improve something. or putting it differently, a person who is satisfied with everything will seldom find a motive for pursuing truly great endeavours. “in human beings and in the most perfect of animals, life cannot be conserved without irritation in the parts which must react...” (peel 1972: 344). this phenomenon can be observed in business life too, as when the son or daughter of some great industrialist is too happy with life as it is to take on the hard work needed to develop his or her father’s business. often such individuals feel they have nothing to prove; all needs are satisfied, there is no irritation. this is noticeable when we consider the contrast between entrepreneurs and executives. the former are often less risk-averse, more adventurous and curious, while the latter are typically more concerned with stability and a steady flow of income. from a biological perspective these characteristics may be seen and understood as different types of psychological irritation, results of environment and upbringing as well as inheritance. teaching entrepreneurship from an evolutionary perspective then becomes largely a matter of making the student aware of these irritations and maintaining them. darwin was also indebted intellectually to the french naturalist and zoologist georges cuvier. in a famous letter to ogle in 1882, as a thank for a gift, darwin described linnaeus and cuvier as his “two gods”. cuvier set out to tell the history of our planet by showing all of the changing processes it has been through, continually giving life to new species. one example is the different types of shell found in separate marine strata (peel 1972: 150). cuvier noted that among all the thousands of fossils he had investigated, there was never a single human bone, which led him to conclude that mankind is a relatively young species. cuvier’s endpoint is darwin’s starting point: if all those other species had a predecessor, then the same must be true for mankind. we must have evolved from other species. darwin begins his origin of species by drawing a difference between natural and domestic variation (darwin [1852] 1994: 5). even though nature continues to bring about changes in mankind, these variations are considerably smaller than those of the domestic or self-imposed kind. this starting point has a parallel in modern evolutionary economics, with the contrast between those who focus on universal darwinism, represented by hodgson and knudsen, and those who focus more on domestic variation, represented by nelson, winter, cordes, and witt (witt 2006: 473–6). thus it is problematic to speak about a single school of evolutionary economics. instead what we have are different 18 varieties of theory with different starting points. rather than one school, there are various schools which all share an evolutionary approach. if we accept the arguments for the evolutionary approach, it follows that all social sciences that claim to be scientific must adhere to this method. also the study of history, which is part of the humanities, can be understood as following the methods of evolutionary theory. man’s “self-imposed” variation has increased significantly over the past hundred years. this domestic variation is governed by complex laws: variability is not actually caused by man; he only unintentionally exposes organic beings to new conditions of life, and then nature acts on the organisation and causes it to vary. (darwin op. cit.: 410) rather, we select among the variations given to us by nature, accumulating them in any manner desired. the same principles that act in circumstances of domestication also act in nature (op. cit: 412). the individuals selected are those which find a competitive advantage in the environment within which they live and function. finding such an advantage depends on the individual’s ability to adapt. since numerous individuals are involved and only some can succeed, competition is often fierce. these are very much the same forces that are involved in economic life. in nature males try to win females by being vigorous, by struggling, by acquiring special weapons, means of defence, or charm. in economic life mankind tries to gain an advantage in very similar ways. what this means is that the theory of natural selection is valid also for the discipline of economics; but, more, that it is being enhanced by the freemarket economy, which in turn is the product of our philosophical ideals, such as freedom of the individual. in economic life man struggles to satisfy human needs in very much the same way as animals struggle to survive: first by adapting, then by competing and trying to find a competitive advantage, a niche from which he can fend off competitors and sit undisturbed. the most common form of domestic variation is indefinite variability. these are changes that last for a limited time only, like coughs or colds resulting from a chill (op. cit.: 6–7). habits, inheritance, and the use or disuse of particular body parts are other reasons for variation. it is hard to distinguish clearly between individual differences and minor varieties, or between more plainly marked varieties and subspecies, or between subspecies and species (op. cit.: 212). these are all different degrees of variation. nature preserves these differences with the same keenness, hoping they will result in a competitive advantage. these ideas are relevant to and would find a natural place in the discipline of economics, if economists would accept them. “differentiation” is one of the generic strategies in porter’s model of competitive behaviour. porter’s contributions, although ignored by mainstream economists, in fact amount (probably unintentionally) to one of the more successful blueprints for a new discipline of evolutionary economics. what we have seen so far is that a first academic grouping developing the ideas which would eventually underlie evolutionary economics was well established in france with men like buffon, cuvier, and lamarck, long before darwin. darwin belonged to a second grouping, but we will postpone discussion of this (and take it up in conjunction with the fourth grouping), because its influence on economics occurred mainly in north america. before looking at that we shall consider a grouping that historically came third, and was located in german-speaking europe. 2.6 germany and austria: austrian versus historical schools economics as defined by marginalists is the study of a particular range of social facts to do with how we produce, distribute, exchange, and consume scarce resources. as anyone who has considered the matter will have noticed, it has also a lot to do with money, or wealth. when economics and political science was a single subject, about a century ago, the study of political economy was defined as the science of wealth (cairnes 1875: 8). the laws of this phenomenon of wealth were “simply the facts of wealth, such facts as production, exchange, price; or again, the various forms which wealth assumes in the process of distribution, such as wages, profits, rent, interest, and so forth” (op. cit.: 18–19). this definition, however, was inappropriate for the new group of economists who wanted to turn economics into a true science after the model of the natural sciences. the new definition needed to be value-neutral, and could not include factors such as power or the natural status that results from having different starting points in life. the assumption had to be that all human beings in principle have the same possibilities. the new, 19 more specialized science of economics, which was to replace political economy, was to be “positive” rather than “hypothetical” like its predecessor; and the tools which were to achieve that was the discipline of mathematics and empirical research. this soon created an academic and scientific culture based on small, narrowly-defined empirical projects, such as we today find in most highly-regarded economics and management journals. this would not be a problem, if it were not for the fact that, well over a century later, we have not made the advances we hoped for in terms of theory building. we are however wiser by many experiences. for one thing, we have refuted marxism, and we have also tested the limits of the mathematical method. in the words of the japanese economist michio morishima, in his introduction to the posthumous book by schumpeter and takata10: since the second world war economics has become mathematicised to what could be deemed an excessive degree (…) economics has become isolated; the isolation has in its turn promoted mathematical inbreeding. (schumpeter and takata 1998: vii) the reasons why mathematics has prevailed ever since as the dominant paradigm must be sought elsewhere. some critics argue that the study of economics has become a political tool, a means of defending free trade through the use and abuse of statistics. and the heavy use of mathematics in economics helps keep its critics at bay, rather as latin preserved the catholic church from its critics in the days of erasmus of rotterdam. today a whole class of bureaucrats and experts are putting forward figures and calculations that only a minority can understand and few can question. specialization within the discipline of economics, furthermore, has not always benefited the subject. after all, human beings do not only perform economic actions. a person also performs religious, political, and social actions, and, more importantly, these various actions have direct influence on each other. thus, a practising muslim may avoid earning interest. this more complex range of human actions as the starting point for the german 10 this book was a response to böhm-bawerk’s 1914 book macht oder ökonomisches gesetz (“power or economic law”). takata and schumpeter met for discussions in 1931. whereas takata wanted to incorporate power into the study of economics, sociologist niklas luhmann. luhmann (1985) saw human behaviour as a set of distinct and interacting social systems. accordingly his framework is well suited for an evolutionary approach to the social sciences, although to date his theories have chiefly inspired numerous interdisciplinary and multidisciplinary studies. when economics parted company with the disciplines of history, politics, and social investigation in general, its models and academic forms became simpler and more refined, but the discipline did not become better at predicting future events: the role of politics and sociological elements in explaining economic phenomena has gradually diminished, until finally pure economics (neo-classical school) has come to be regarded as the most important tool for elucidating economic problems. (schumpeter and takata 1998: ix) this is the same neo-classical school which schumpeter once helped to found in europe based on the ideas of eugen von böhmbawerk11. in fact, initially schumpeter’s work was seen as too mathematical and too theoretical for most english and american economists. it was not until after schumpeter had gained a secure academic position in the usa that he began changing his views, and drifted away from the use of maths towards the evolutionary approach, just as boulding did after him. unfortunately for us, this came rather late in his life. schumpeter was never able to complete his ideas on evolutionary economics. the closest he got to describing his method was in the outline at the end of his history of economic analysis, a book he never finished. today schumpeter’s contributions to economics are mostly associated with the study of entrepreneurship, an area which was to be taken forward by a fellow austrian emigré, peter drucker. unlike schumpeter, drucker never made any real attempts to set his theories within a broader methodological perspective so he was mostly ignored by fellow academics. his fame stems almost entirely from the fact that ceos and managers found his books relevant. the same can only be said for a few economists who have won the nobel prize. schumpeter wanted to leave that aspect to the discipline of sociology 11 böhm-bawerk in turn drew his inspiration largely from carl menger. 20 schumpeter looked to a range of different disciplines for inspiration. this is confirmed not only by his wide general reading, but by his affiliation and sympathy with the kiel school of economics and by his academic training in the austrian school. in his theory of economic development, schumpeter attempts to offer a theory of economic change in purely economic terms. in the japanese edition of the book he says that his aim is the same as that of marx’s economic teaching; he places his concept of economic evolution in a hegelian setting: “he concentrated his analytical powers on the task of showing how the economic process, changing itself by virtue of its own inherent logic, is incessantly changing the social framework – the whole of society in fact” (schumpeter 1952: ix). what distinguished marx from his contemporaries and predecessors in economics was a vision of economic evolution as a distinct process generated by the economic system itself (loc. cit.) and a deterministic certainty about future economic events and their consequences12. although trained in the austrian school, schumpeter’s convictions lay elsewhere, influenced not so much by eugen von böhmbawerk as by adherents of the historical school – marxists like hilferding and kautsky, but above all evolutionary economists of the kiel school such as lowe and lederer, with their focus on “structural” theories of growth and business cycles. together with the kiel-school economists, many of whom ended up at the new school in new york, schumpeter represents the third academic grouping in evolutionary economics. however, when they moved to the usa it was the physics paradigm and their mathematical contributions to the marginalist school that were wanted, not their evolutionary ideas. the young continent also approved of the laissez-faire doctrines of the austrian school, the very same doctrines which has just turned the western world close to bankrupt. the evolutionary ideas were abandoned with much of the rest of the intellectual baggage european emigrés carried with them from a nazi-infested europe. american evolutionary thought was soon a thing of the past, associated with men like veblen and later with isolated mavericks like boulding and georgescu-roegen, who were treated as unsuitable to teach at the great 12 the foreword to schumpeter’s book by his widow elisabeth boody explains the essence of his philosophy even better. universities. those who conformed to the new methodological plan for the discipline of economics could advance in their careers; those who did not were at best ignored. the new paradigm was established. 2.7 the usa: from veblen to boulding via spencer many economists had been inspired by herbert spencer’s introduction of the evolutionary approach into the social sciences. an american economist of norwegian extraction, thorstein veblen, is often seen as the first real evolutionaryeconomist on that continent, but also as the last of the classical evolutionists (peel 1972: xlvii). in his famous 1898 article “why is economics not an evolutionary science”, veblen wrote that economics was “helplessly behind the times”. biology as a science was on its march forward. the social sciences needed to follow. it is likely that veblen had read and was influenced by the british economist alfred marshall, fifteen years his senior, who in 1890 pointed out that economists had much to learn from the recent history of biology when developing their science. “darwin’s profound discussion of the question [in the origin of species] throws a strong light on the difficulties before us”, wrote marshall (1890: bk 1, ii). he felt strongly that it was biology, rather than newtonian mechanics, which should be the model for the study of economics. it is commonly thought that evolutionary economics is an attempt by economists to adapt economics to the principles of the natural sciences. in fact one might well argue that it was the other way round: darwin is said to have got the idea of natural selection by reading malthus. (boulding 1981: 84) when we look more closely at the history of economics we find that most useful progress has been achieved within the applied fields, such as the study of marketing or management, which are more concerned with real-life situations and applications than with theory building. yet it is the theoretical advances which have been rewarded, for instance with the nobel prize. an important question is how far the discipline of economics 21 really needs theory-building in order to justify its existence. many business schools, especially graduate schools and master’s programmes, are perfectly satisfied with teaching students how to do things (know-how), developing their skills and giving them “tools”. this matches heidegger’s notion of the future of the social sciences and the humanities as steuermannskunde or kybernetik (etymologically, “the art of the helmsman”), focusing on the ability to solve practical problems. these ideas have been shaping business schools for decades now. there is a another point here too, as mentioned before. there seems to be no real correlation between economic theory-building and economic success among industrial nations. thus countries like germany, south korea, japan and china are highly competitive nations economically, but have contributed little to the development of modern economic theory, particularly as compared to englishspeaking countries. the latter have lost much of their industry over the last few decades while those theories were being created. their economies have shifted from a society of craftsmen and industrial production to one of knowledge production and services, a shift which has been very much supported by their own economic theories. both the usa and britain, which are producing most of these theories, are now suffering from general economic decline. we talk of “economic theory”, but mean very different things. how often does phenomenon a (cause) have to lead to phenomenon b (effect) for the relationship to be called a theory? some talk of theory if they have done a small empirical experiment which gives answers that go in one direction. others avoid the term altogether. there is less confusion about the term “economic law”: few economists today would claim to have discovered any economic laws13. r. f. harrod, one of the founders of the oxford economics research group, may have come closest when he put forward a law of evolutionary economic behaviour summarized as “nothing for nothing” (perroux 1960: 8), but such common-sense theories are of little value. the evolutionary perspective on human behaviour leaves little place for a formulation of natural law in terms of definite normality. nor does it leave room for that other question of normality, namely what should be the end of 13 an economic law may be defined as a case where a phenomenon a invariably leads to a phenomenon b. the developmental process under discussion (veblen 1899: 12). the best way for the evolutionary approach to demonstrate its value is to produce theories with greater predictive success than those produced by alternative schools of thought, or else to reject the idea of theories in the social sciences altogether. one of the real challenges to evolutionary economics is how to define and measure change. early evolutionists discovered that the differences in traits and species increased with geographical distance, and they sought to classify change into (i) change of stations, and (ii) change of habit. a habitat is a special environmental area inhabited by a particular species or organism. similar animals may be found at many stations, but only within one habitat (wallace 1876: 4). there are a number of reasons why comparable research projects are troublesome in economics. first there is the globalization argument: economic agents travel extensively and live all over the world. they cannot be defined as belonging to one geographical location. secondly, any research that points to differences in economic performance between human groups is likely to meet serious criticism. one of the advantages of marginalist theory is that it is politically correct, since it complies with human-rights ideals and assumes that all men have the same economic abilities and possibilities initially, regardless of upbringing, cultural background, or genetics. this in turn is what makes differing economic outcomes fair, from the marginalist’s point of view. we know this is not so: for instance, children born in wealthy families have a better than average chance of economic success themselves, not least because they can expect to inherit their parents’ fortune. in that sense it could be argued that neoclassical economics is a convenient tool for the rich to defend their property. veblen’s definition of evolutionary economics does not ignore cultural differences, nor does it ignore the notion of power: [evolutionary economics is] the theory of a process of cultural growth as determined by the economic interest, a theory of a cumulative sequence of economic 22 institutions stated in terms of the process itself. (veblen 1899: 13) ... where man’s knowledge of facts may be formulated in terms of personality, habit, propensity/natural tendency and will power. (op. cit.: 5) this is the culturalist position, so heavily criticized by the academic establishment today for its political incorrectness. men living under different climatic conditions will tend to behave differently. they have simply developed different habits. for instance, in many places on earth the climate is simply too hot to engage in much economic activity. we see this in large parts of sub-saharan africa, the arab world, and south-east asia. we also behave differently depending on our geographical location. thus, island people tend to keep to themselves, or make occasional outbursts into the world, but are also inclined to engage in large-scale export efforts to stay competitive. among competitive island economics there is always the realization that if they keep to themselves they will decline, even if that is just as true for landlocked countries. we see this not only with japan, but also with britain, sweden (half-island), taiwan, south korea (half-island), and singapore. our cultures have imprinted their particular traits on us, which again helps to explain our behaviour, including our economic behaviour. this does not mean that individuals cannot break out of these patterns, or that cultures do not change. they do. the culturalist position does not have to be a dogmatic one. culturalists are also attacked for embracing the scenario summarized as survival of the fittest, implying that some individuals survive at the expense of others. however, it has been suggested that a better phrase would be survival of the fitting, since success is not restricted to a single individual or species, and survival seems to be more a question of finding a niche than of forcing others out (boulding 1981: 18). in the wild, animals who are not adapted, who have not found some sort of advantage, disappear. darwin called that the survival of the fittest, a phrase he borrowed from the english philosopher herbert spencer (rather than vice versa). again, objections to the doctrine have a lot to do with ways in which it has been exaggerated. it does not necessarily mean aggressive behaviour. we do not want to live in a society where only the fittest survive; that would be inhumane. instead we have constructed a political and social system in which those who are “unfit for survival” receive some form of help. however, if those who asked for help formed the majority of citizens, the nation would lose its competitive advantage. so the theory does apply and the effects of this phenomenon can be observed in large part of the western world today. the consequences are economic and social distress. what corresponds to extinction in business life is bankruptcy. bankruptcy does not mean that the bankrupt actually disappears, it merely simulates disappearance by excluding agents who perform poorly from conducting further business for a period of years. furthermore, the precise consequences of bankruptcy vary, depending on the social-welfare system in place in a particular country. thus the metaphor of survival of the fittest does not have the same consequences in modern society as it has in nature, and the cruelty involved is often exaggerated but on the whole the theory holds. spencer, who was greatly influenced by adam smith and lamarck, is one of the more neglected among classical sociologists. the reasons for this neglect are many: in part political, in part due to his outspoken, consequent denial of historic analysis as a method to gain scientific knowledge, and, no doubt, in part due to his notoriously blunt statements. his ideas were frequently utopian. hence spencer remained interesting for a long time as a literary figure but (like marx and comte) quickly became unacceptable as a scientist. his lamarckian biology was dismissed in europe, partly because it was bad timing to present a value-free social science in a western world marked by high unemployment and great social misery. he was misunderstood, as when he is associated with social darwinism and laissez-faire politics. in reality he argued for increased state intervention. spencer survived in the usa by virtue of ideas such as rejection of absolute standards of truth and elevation of practice over theory. in the 1920s and 1930s these ideas were taken up by dewey. two features were never abandoned in the us: (i) economicsbased models of social structure, and (ii) methodological individualism (peel 1972: xl). he also inspired a whole new school of american anthropologists, including l. h. white, j. h. steward, marshall sahlins, and elman service, who saw the task of anthropology as being to trace the path by which cultures “evolve” (loc. cit.). this 23 approach was inspired by the long-established german discipline of völkerkunde. a similar approach is familiar in linguistics – as when we can trace the indo-european languages back to sanskrit – and we see something similar when scholars trace the development of mythologies (cox 1870). the movements of populations suggested by such investigations are being confirmed today by genetic research. if sociology is not to be value-free, it must have a moral basis. this moral stance was widely accepted in sociology following spencer, but has since been largely forgotten. as spencer saw it, the chief role of evolutionary sociology was to reconcile man to the inexorable processes of nature. he wanted to describe a theory of social change. economists who have worked to unite economics and sociology along these lines have included schumpeter, vilfredo pareto, and ferdinand tönnies, a german sociologist who taught economics at kiel university (schumpeter and takata 1998: xxxiii). tönnies is perhaps best known for having reintroduced thomas hobbes into the social sciences. this strengthened the evolutionary approach to economics. the notion of power is vital in understanding human behaviour because we live in social, hierarchical systems. had tönnies not died in 1936 he would probably have had to flee germany, as his children and so many of his colleagues did because of the rise of nazism. the nazis made a short process of anyone criticizing their movement. tönnies was considered a social democrat, but this was also the fate of many conservative german intellectuals like the manns and carl schmitt.daniel defoe’s robinson crusoe represents life at the opposite extreme to the world of economics as portrayed by hobbes. economic marginalists reason very much as if man were created as an isolated individual in nature, like robinson crusoe on his island, and crusoe is therefore a favourite trope among marginalist economists. their critics argue that we do not live like crusoe, so that any such comparison is a gross oversimplification bound to give false answers. evolutionary economists argue that (whether we like it or not) the world is more hobbesian than we care to admit, and that the task of a science is to describe reality. for significant new discoveries in the study of man and human behaviour, we are reliant on future work by psychologists, biologists, and neuropsychologists to show us how we reason and why. this is an argument in favour of more interdisciplinary research in economics. a sensitive specialist pursuing his investigations in any field, boulding reminds us (1950: viii), finds himself on the frontiers of other disciplines. that was also very much a watchword in boulding’s own research. how can you study economics in mediaeval times without considering religion, and how can you study economics during the industrial revolution without considering the class distinctions of that period, boulding asked (perroux 1960). in the same way, how can you study the economics of today without considering the phenomenon of globalization – probably the greatest accelerator of change ever known on this planet, leaving aside natural catastrophes. every age, every nation, every climate exhibits a modified form of humanity (peel 1972: 7). this universal law of physical modification is also the law of mental modification (op. cit.: 9). according to spencer all imperfection is unfitness. progress, therefore, is not an accident, but a necessity (op. cit.: 13). rather than civilization being artificial, it is a part of nature. spencer thought that this imperfection would end and man would attain some sort of completeness. thus according to spencer the law of evolution may be expressed as a change from a less coherent homogeneity to a more coherent heterogeneity. there is and can only be one evolution, as all the different existences are component parts of the same cosmos. why should mankind be different, why should he follow different laws from all other living organisms? that is the question that every social scientist must ask himself. furthermore, towards what form is man evolving? for peel the ultimate man is seen as one whose private requirements coincide with the public ones (op. cit.: 26). considered over a large time interval, we find that man’s character is growing more civilized, less violent, shaping into what we might call “social man”. the further we come away from violence, the more successfull we seem to evolve. this development in our character can be seen for instance in styles of leadership over recent centuries – a shift from the boss to the leader, who gives fewer orders and instead aims to be a role model through his actions; from the military commander type associated with the early days of industrialization to the team player of today. this is also reflected in the terms “social intelligence” and “emotional intelligence”, which have become a focus today. we also 24 speak of “people skills”, but seem to mean the same thing. true, others say that man is becoming ever more selfish, a result of his striving for ever more independence. but that may represent more a backlash than an actual long-term trend. the evolution of our character can rather be plotted as a rising curve, so far as present data indicate at least. taking human actions as a starting point for the human sciences, instead of theories or ideas, has given us some of the most useful techniques or methods available in the social sciences today, including game theory and rational choice theory. but these contributions are not necessarily marginalist or even neoclassical. we shall rather argue that game theory relates more closely to informal and formal logic than to mathematics. in fact it is really a non-marginalist approach, with no fixed number of variables to be optimized. and yet arguably game theory, invented by the german economist oscar morgenstern and the hungarian-born mathematician john von neumann, is one of the better analytical tools available to describe and analyse social dynamic realities. it is also interdisciplinary, meaning that it is equally applicable in any of the social sciences, and in the humanities. so long as scarcity is a major problem, the economic forces that constrain us will be very real. on the island of utopia there is no need for the discipline of economics, because everything that people need is available in plenty, and people do not ask for more than they need. in thomas more’s book the character peter giles believes that: till property is taken away there can be no equitable or just distribution of things, nor can the world be happily governed: for as long as that is maintained, the greatest and the far best part of mankind will still be oppressed with a load of cares and anxieties. more draws this conclusion from his experience of early sixteenth-century england, ruled by henry viii, where “all things will fall to the share of the worst men” and where “all things are divided among the few”. from a national perspective this situation improved dramatically with industrialization, which allowed a large proportion of the poor to rise into the middle class, like in today’s china. from an international perspective the problem is more complicated, since what we have been doing is largely exporting low-wage jobs to other, less developed countries: as the saying goes, out of sight out of mind. the possibility of continual improvement in standards of living is limited, since it is those who already have money who have the best chance of making more. that is a consequence of the efficiency of financial markets, which has brought us to a point where the free-market system is once again being criticized as unfair because it is to the advantage of those who are already ahead. the result of these mechanisms in the western world has been a poorer middle class. more’s utopia is a land where leisure is to be used for reading books, playing chess, and engaging in gardening. but the problem of who will do the work if everyone lives a life of ease is solved by slavery; as more says, “all the uneasy and sordid services about the halls are performed by their slaves...”. in modern times the work these slaves contribute with can be compared to our taxes. to take a current example, a universal or citizen’s salary to replace unemployment benefits is mere relabeling and will not change the problem as to where the wealth will come from in a world free of slaves. man is always a child of his time, and the social scientist can seldom ignore the values of his time. being a successful social scientist is to a large extent a question of writing in conformity with the values of one’s time. those who do not do that are choosing to live the hard way. one economist who places in that category was nicholas georgescu-roegen, schumpeter’s favourite student. few if any have done more to advance the evolutionary approach in the study of man. 2.8 georgescu-roegen : the right man at the wrong time bioeconomic analysis sees new technology as a set of man’s most sophisticated exosomatic organs. a stick picked up in the woods as a club meant a stronger arm, one of the earliest examples of an exosomatic organ. according to georgescu-roegen (1980: viii), man’s exosomatic evolution has brought with it three “predicaments”, or unpleasant situations from which escape seems difficult. the first is conflict between various human communities or cultures. thus homo indicus is different from homo americanus, in that the former travels more by foot and the latter by car. the predicament may also reflect differences in taste. the second predicament is the conflict between the two social classes of governors and governed. the third predicament is ranges of technically-sophisticated equipment, such as pcs, the internet, and mobile phones today. 25 this equipment is continually changing, and creating problems about haves and have-nots. we see this today in the area of e-commerce, where certain countries including japan, south korea, the usa, and sweden are ahead of the field and the companies are becoming bigger and fewer. georgescu-roegen’s bioeconomics builds on one major principle: mankind must not discount the future. by this he means that the price of a resource should be determined by all potential buyers, including those who are not yet born. “and since future generations cannot be present now, we should bid in their place” (op. cit.: xii). this problem is highly relevant today, since past generations have raised their standard of living by imposing debt burdens on future generations. thus, we may say that our current degradation of the environmental and the living conditions on the planet is in part a result of our economic theories. georgescu-roegen begins from the assumption that mankind is going to be around for a long time: “the dinosaurs lasted hundred and twenty millions years”14. if this assumption is correct, or so long as we do not know how long mankind will exist, we should manage our natural resources with care. marginalist economic theory typically models economic problems as if each generation were the last. when economies are put under heavy strain, the chances of war will increase. georgescu-roegen (op. cit.: xi) reminds us that “all major wars have had no main objectives other than the possession or the control of natural resources”. we have seen recent proofs of this whether it is in the form of america’s war on iraq (geopolitical logic) or with chinese investments in africa (geoeconomic logic). the difficulty with the discounting problem is that we have no way of knowing what resources future generations will need and how long they should be discounted for and, we could add, at what rate. to help resolve this question the aim of georgescu-roegen is: a world organization whose role be to decide the acceptable rhythm of depletion of mineral resources and their distribution among all nations according to a rough criterion of hierarchical needs. (op. cit.: xii) this is the idea of the world state, a project which will become relevant in the 22nd century at the earliest. it is in turn largely a question of human political and social evolution. 14 g-r wrote this some years ago, 165-185 million years is probably a closer number today georgescu-roegen follows schumpeter’s idea that the evolutionary approach is not an economic “theory” in the marginalist sense of the word, but must be more of an “analysis”. his first book (georgescu-roegen 1966), in which he outlines his thoughts on evolutionary economics, is entitled analytical economics: … theoretical science is logically ordered knowledge. a mere catalogue of facts, as we say now a day, is no more science than the materials in a lumber yard are a house. (p. 15) and: ... if the cornerstone of science is the dogma that all phenomena are governed by mechanical laws, science has to admit that life reversal is feasible. (p. 83) instead georgescu-roegen suggests that economic analysis should follow the formula set by cuvier: nommer, classer, décrire (name, classify, describe) – what is called a taxonomic process, or filing system. this same search for a universal principle of classification once led to the birth of formal logic. theoretical science is a logically ordered description. marginalist economic theory is an attempt to show that mathematics can be the logic for the study of economic phenomena. but, whereas the purpose of economics is to understand economic facts, the purpose of pure science is not prediction, but knowledge for its own sake (georgescu-roegen 1971: 37). this is the excuse science gives for not always producing realistic findings. georgescu-roegen rejects all accurate predictions in the social sciences: “no analytical device can allow you to describe the course of your future actions” (op. cit.: 335). he instead agrees with the hegelian approach we find in schumpeter: “if economics is to be a science not only of ‘observable’ quantities, but also of man, it must rely extensively on dialectical reasoning” (op. cit.: 337). dialectical reasoning cannot be exact, but can be largely correct. it implies that we attempt to express ourselves in numbers, weights, or some other measure. “hence careful reasoning and analysis should be the backbone of economics”, as marshall suggested” (ibid.). dialectical reasoning opened the way of literary economics, where both sides of each argument 26 are weighed up. that is also very much the tradition of critical theory applied in geoeconomics. in his next major book georgescu-roegen discussed the law of entropy, based on ideas of the german physicist rudolf clausius, who held that change undergone by matter and energy must be qualitative change (197: 1). georgescu-roegen argued that an economy is a biological process governed by the law of entropy, not by the laws of mechanics. the book is a critique of homo economicus, in which georgescu-roegen takes up the objection that economics as a science strips man’s behaviour of every cultural propensity, which is to say that man is treated as acting mechanically (ibid.). georgescu-roegen’s thermodynamic approach to economics is based on carnot’s work on entropy from 1865 and boltzmann’s from the 1870s: a cultural propensity may be a factor in economic growth, as when cultural activities in countries such as france, spain, or italy encourage the growth of tourism. it might have been similar observations that led spengler to the thesis that economic growth depends upon the degree of compatibility between the economic components of the respective culture (op. cit.: 362). evolution appears so mysterious to us only because man is denied the power of observing other planets being born, evolving, and dying away. and it is because of this denial that no social scientist can possibly predict through what kinds of social organizations mankind will pass in its future. (op. cit.: 15) had economics recognized the entropic nature of the economic process, it might have been able to warn its co-workers – the technological sciences – that “bigger and better” washing machines, automobiles, and super jets must lead to “bigger and better” pollution. (op. cit.: 19) economic theorists like robert solow, joseph stiglitz, and paul samuelson have praised georgescu-roegen’s mathematical contribution, but none of them have shown any interest in his ideas on evolutionary economics and bioeconomics. none could have failed to notice that georgescu-roegen was schumpeter’s favourite student at the harvard graduate seminar. so it was impossible to ignore him; but his thoughts deviated too much from existing theory. herman daly (1999) has asked how long neoclassical economists can go on ignoring georgescu-roegen’s contributions. for instance, what will future generations say about the fact that we are systematically denuding the planet of oil and gas, resources which may be needed for more important tasks in the future when alternatives are not available? faced with the threat of global warming, environmental deterioration, and now the financial crisis, georgescu-roegen’s economics are long overdue for a review. solow and the marginalists assume that natural resources can always be substituted. his well-known work in growth theory is based on an aggregate production function in which resources do not appear at all: it takes production to be a function solely of capital and labour (daly 1999: 15). this is like expressing improved cuisine as a function of a cook and a kitchen, forgetting the ingredients. the solow– stiglitz variant of the cobb–douglas function including resources is expressed as: 𝑄 = 𝐾$%𝑅$'𝐿$) – where q is output, k is stock of capital, r is the flow of natural resources used in production, l is the labour supply, a1+a2+a3=1, and a>0. in reality, increase in capital implies depletion of resources; and if k→∞, then r will rapidly be exhausted by the production of capital (daly 1999: 17). georgescu-roegen calls this a “conjuring trick”. land and resources have been eliminated, on the argument that capital is a near-perfect substitute. if so, then resources could equally be substituted for capital (reverse substitution). to do that would run counter to the whole direction of neoclassical theory, which is to deny any important role to nature (op. cit.: 18). none of georgescu-roegen’s ideas on the biophysical foundations of economics were ever canonized by inclusion in samuelson’s famous textbook. there has been no interest in georgescu-roegen’s ideas at mit, the american economic association paid little attention to his death, and hardly a trace of his influence is left in the economics department of vanderbilt university, where he taught for twenty years (op. cit.: 13). one reason may be that few economists understood his ideas with their emphasis on advanced mathematics, 27 physics, and biology15. he may also have been too interdisciplinary for his own time. a further reason may be that he is said not to have been easy to work with. a deeper explanation would be that if one accepted georgescu-roegen’s ideas, the consequence would be a complete paradigm shift in economics. the political and economic implications of accepting his theories would amount to nothing less than a revolution in the way we organize our lives, and it is perhaps one we are not yet ready to undertake. georgescu-roegen’s own explanation of why his ideas were never accepted was in terms of a romanian proverb: “in the house of the condemned one must not mention the executioner”. after arguing his case for decades without ever getting much response, georgescu-roegen gave up on standard economics and resigned from the american economic association (op. cit.: 15). in his own words “i was a darling of the mathematical economists as long as i kept contributing pieces on mathematical economics” (georgescuroegen 1992: 156). schumpeter too had come to the united states as a two-edged sword, like georgescuroegen later. influenced by léon walras and w.s. jevons, economics departments in the usa, especially after the second world war, decided to base development of their discipline on the mechanical perspective. to many critics this system quickly came to look more like a church than a community of independent thinkers. however, despite enthusiastic espousal of the mechanical approach in the usa, one american economist was never willing to abandon georgescu-roegen’s ideas: namely, kenneth boulding, a strong independent thinker among american economists. 2.9 parallels between boulding and luhmann: cybernetics and scial systems in his 1968 book beyond economics, boulding identifies some of the methodological limitations of economic theory: 15 this is an odd trait among many fellow economists, they argue for mathematics, by which they imply the right amount of mathematics, enough to separate them from academics studying the humanities. but, when someone with a physics background comes along, it becomes evident that they know too little mathematics, and then the physicists end up in the wrong. (i) the ceteris paribus assumption, associated with marshall, involves isolating a problem by assuming that all other variables are held constant. the problem with this assumption, boulding argued, is that it leads to results that are true only in a very limited domain, and there is a danger of over generalization. (ii) the method of simultaneous equations, associated with walras and the lausanne school, based on the proposition that any system of variables, each of which can be written as a function of all the others, yields n of these equations that are consistent with one another (boulding 1968: 10). this method often gives results that are mathematically correct but economically meaningless, such as negative prices. (iii) the study of macroeconomics, as associated with keynes16, consists essentially in using wage aggregates of economic variables as the basic parameter of simplified models, the exact properties of which can be fairly easily determined. the problem lie in the generalizations within these models, such as the “level of employment”, and the “price level”. furthermore, society has not become classless17. economic theory assumes that all individuals have the same starting point, the same possibilities. only then can it be fair. this ignores such factors as (family) contacts, culture, and nationality, relevant to the competition to win business contracts, and parental income, relevant to receiving a university education. it also ignores the phenomenon of contracts won through bribery, which means that much business conducted outside the western world must be excluded from the theory. perhaps the problem is that economics in fact remains a moral science, as in the old cambridge tripos, “in spite of all attempts to dehumanize the science of man”, boulding concludes (1968: 12). 16 macroeconomics began to emerge in the models of irving fisher and knut wicksell, but culminated in the work of john maynard keynes. 17 the essence of the term “class” as used today has to do with income differences. the marxist proletarian– bourgeois–capitalist distinction has become less relevant today, in the west at least. instead we have other, newer class divisions, as in “new class theory”. 28 boulding takes as his starting point the ideas of a theory of change outlined by schumpeter. as any pioneering scientist would necessarily do, he begins by asking what types of change occur in economics; and he concludes that there are two types: long-term and short-term. the biggest form of social change would be called a revolution. revolution can be understood as a social reaction to a situation where there has been no hope of change for too long. boulding’s social-dynamics perspective is inspired by georgescu-roegen’s ideas. if economics is to be a science, it must use dialectical reasoning. but whereas georgescuroegen thinks this relationship must be “extensive”, boulding holds it to be “relatively insignificant” (boulding 1981: 20). boulding argues that there are two types of process at work in human history: one dialectical, involving conflict and the victory of one group over another; and one non-dialectical – incidental, cumulative, evolutionary, and continuous (boulding 1970: v). of these two he sees the dialectical process as merely waves and turbulence on the great historical tides of evolution and development. one of the problems with the dialectical process is that it focuses on conflict likely to lead to even greater conflict (op. cit.: 52). the process of biological evolution seems on the whole to be nondialectical (op. cit.: 55). boulding believes in the historical method, but whereas boulding thinks that the future can in part be understood by studying history, georgescuroegen disavows any predictions about the future (georgescu-roegen 1971: 335)18. boulding himself acknowledges that the ability to predict is less robust than the ability to understand. boulding defines four processes through which we suppose that we might be able to gain knowledge of the future. these are: (i) random processes, such as throwing dice. for this method, recorded information is irrelevant. (ii) deterministic mechanical processes, as used for instance when estimating future population figures; (iii) theological processes, in which movement through time is guided by some image or information-structure of the agents in the system at the outset; and (iv) the evolutionary process. boulding (1970: 19) chooses to see human history largely as an extension of the evolutionary process from the 18 no analytical device can enable you to describe the course of your future actions. biological into the social domain (an idea which goes back at least to spencer). these methods are relevant for the discipline of intelligence studies within such areas as early warning, signal analysis, scenario analysis and just general prediction. according to boulding (1981: 11) the evolutionary perspective presupposes that at any one point in time and space there will be an ecosystem, and with a given set of parameters this will move to an equilibrium where the rate of growth of all populations within it will be zero. this seems to conflict with his later critique of the equilibrium approach19. however it is possible that boulding, like schumpeter before him, changed his mind. boulding also criticized neoclassical economics for not having incorporated time and space as factors in their theories, even though obviously “all productive processes involve space and a fine vine will turn into vinegar” (boulding 1970: 19). “bioevolution is characterized by constant ecological interaction, which is selection, under conditions of constant change of parameters, which is mutation” (boulding 1981: 12). put differently, mutation takes place in the egg, selection in the chicken (op. cit.: 65). the parametric changes can be physical, such as a change of climate, but the basic source of change is genetic mutation, that is change in the dna sequence. evolution is not a deterministic system, like celestial mechanics, because it is not an equilibrium system. it involves inherently unpredictable changes of parameters because of the long-run importance of improbable events (op. cit.: 69). as economic life is a subset of human activity, we should expect it to follow the general principles of evolution (op. cit.: 16). the principle of ecological interaction is the ultimate foundation of the evolutionary perspective (op. cit.: 11). like georgescu-roegen, boulding equates human history with the evolution of artefacts. human artefacts are of three kinds: (i) “things”, material objects; (ii) organizations; and (iii) learning processes (op. cit.: 15). this is very much the materialist perspective to economics. material artefacts have developed from the flint arrowhead to the space shuttle; organizations have developed from the clan to the corporation; and people’s minds have 19 but in tang et al. (1976) boulding says that “equilibrium is a fiction of the human imagination and is really unknown in the real world” (p. 3). 29 developed alongside these. exchange is the mechanism through which this process is carried on. exchange, which contains an element of reciprocity, makes the parties involved better off, hence more fit for competition. labour hours and price are two examples, or forms, of exchange. price may be seen as the expression of the balance or equilibrium of the social system of needs. thus the evolutionary approach to economics may be more relevant in times of great transformation, like the one mankind is facing today through the globalization process. according to boulding (1985: 7) it was his year at the international christian university in japan in 1963–4 that led him to a renewed interest in evolutionary theory, which produced a primer on social dynamics in 1970 and ecodynamics in 1978. in 1970 he also wrote a book on economics as a science, in which economics was treated as an ecological science. we see how both schumpeter and boulding were open and akin to asian ideas and analysis for understanding social economic behaviour through a direct cooperation with japanese economists. even before that, in beyond economics (1968), boulding defined a general theory of growth, which said that all growth phenomena have something in common. the phenomena can be classified into: (i) simple growth, the growth or decline of a single variable or quantity by accretion or depletion; (ii) population growth, that is births and deaths; and finally (iii) structural growth, as when a butterfly emerges from a chrysalis (boulding 1968: 64). growth phenomena in the real world usually involve all three types (op. cit.: 65). in the same book boulding defines “social systems” as whatever is not chaos (op. cit.: 98). the best way to reduce the complexity of human history to manageable, systematic form is to break up the social system into subsystems (op. cit.: 101). the same logic is applicable to the human sciences. the idea of the social world as made up of systems is an idea he held on to. in his 1985 book the world as a total system we find the same idea of the social sciences as systems: “the social system is so interconnected that any division of it is a little arbitrary, but, as we shall see, we can conveniently divide it into the economic system, the political system, the communication system, and the integrative 20 boulding wrote about social systems in 1970. luhmann wrote about evolution as early as 1972, and system” (boulding 1985: 29). the same idea is also central to the philosophy of the german sociologist niklas luhmann, who published his classic soziale systeme the same year. social evolution is also a central idea for luhmann20: “what evolves is simply meaningful possibilities, each possibility that is selected yielding new eligible possibilities”. only to the extent that money guides our choices does economics have strong predictive power in the social sciences, luhmann concludes. boulding (1985: 31) divides the world into three kinds of system: physical, biological, and social. social systems are an evolutionary development out of biological systems. they involve biological organisms that have the powers of communication, consciousness, and the ability to produce artefacts (op. cit.: 71). one of the great differences between the socio sphere and the biosphere is the much greater importance of decisions in social systems for determining the future (op. cit.: 82). there are many ways of classifying social systems. luhmann divides them into: 1. subsystems of society: a) religion b) law etc. 2. social systems proper: a) interactive b) organizational systems 3. other systems. boulding, on the other hand, classifies social systems according to the nature of the relationships (1985: 83), into: 1. the threat system 2. the exchange system 3. the integrative system the world economic system is seen as interacting closely with the political system and with organizations like the church, families, clubs, and so forth (op. cit.: 89). another biological idea which interests boulding is man’s limited ability to understand his own environment. what we know is a function of what we can imagine. that is to say that our brain, not the external environment, controls and sets limits to what we are capable about social systems as early as 1970. boulding makes no reference to luhmann. 30 of understanding21. this view, that we increase our knowledge of the world by studying the brain, not only by studying external reality, may be called a neurological approach to the social sciences. “we construct images in our minds of the world or even the universe as a succession of constantly changing states through time” (boulding 1981: 9). boulding shows great interest in this cognitive approach to the social sciences (cf. boulding 1985: 9; 1956). today neuroeconomists like antonio rangel have made great advancements in this direction (rangel et al., 2008). the belief that an image is true often derives from authority, or from evidence. in some cases we resolve the ambiguity of evidence by experiment. that only applies, however, to systems which are stable, repeatable, and divisible, such as chemical systems, where, for instance, all hydrogen atoms are essentially similar. we cannot do experiments on unique events or on the past (boulding 1981: 10). boulding explains (1950: viii) that “the first focus of my dissatisfaction with economics is in the theory of the firm, or the economic organism, and its immediate relationships and interactions”. this leads him to a “relationship” perspective on economics. we find the same parallel between the relational perspective of marketing by gummesson and the nordic school and kotler’s mechanistic and marginalist perspective on marketing (see e.g. gummesson 2002). as such this nordic school is very much founded in the european continental intellectual tradition. boulding’s second focus of dissatisfaction (1950: ix) was with keynesian macroeconomics, with “the failure to distinguish between the exchange of payment and the process of production”. this led him to the process perspective on economics. both concepts belong to what we could call evolutionary economics. we can follow the change in boulding’s perspective on economics through his books, from the more mathematical contributions he wrote while he was in michigan, to the anything-but-mathematical writings of his colorado years. what started as mere echoing of the status quo in economic thought developed into a strong, highly-differentiated contribution to the discipline of economics, turning him into a strong independent thinker, 21 the first philosopher to set this idea out in detail was kant, in his critique of pure reason of 1781 but also an outsider. unlike many other evolutionary economists discussed here, boulding never limited himself to any one perspective but continued to move in many different intellectual directions at once. this may have been his biggest weakness as an economist, in that he was unable to complete and present a coherent system of economic thinking. to sum up, the academic community of evolutionary economists in america can be divided into two: on one side economists of the midwest, inspired by the english-language economics literature, such as veblen and boulding, and on the other side the european diaspora, including kiel school economists and men like schumpeter and georgescu-roegen. of the five groupings defined here, the third, fourth, and fifth can be described as evolutionary economists, while the first and second were groupings which made direct contributions to a discipline of evolutionary economics. the purpose of this historical trajectory has been to show how the study of geoeconomics and intelligence studies can be based on the same ideas which are often referred to as an evolutionary approach. as such the studies have a methodological foundation as a part of the study of economics too. this does not mean of course that the evolutionary approach needs to lead to the study of geoeconomics only. geoeconomics can also be said to belong to critical theory and the normative sciences. 3. conclusion in this article we have shown why and how the scientific basis and methodology of the study of economics and management can be evolutionary theory and the evolutionary approach. as an example, intelligence studies is a discipline and an approach to the study of business that sees information as a basic building block for the study of organizations and human behaviour. it is not unique in this sense but shares this starting point with other information sciences after the shift called the information age with a focus on information and knowledge, as opposed to the age of the industrial revolution with its focus on more narrowly defined tasks and outcomes measured as a function of man hours, capital and material. however, unlike all the other 31 information sciences its methodology may be defined as biology instead of physics right from the start. the study of geoeconomics is a discipline that studies the macro environment of organizations through what we today should call a multidisciplinary approach consisting of history, geography and political science (the realpolitik assumption). the starting point is not marshall’s descartesian systems à la supply and demand curves, but the world map, resources and cultures. both intelligence studies and geoeconomics have more to gain as disciplines and sciences by using the evolutionary approach not only to explain their findings but to build coherent theory. so have all disciplines who study man. as a new study all researchers have not agreed upon clear definitions of geoeconomics yet (mattlin and wigell, 2016) and there is a need for analytical methods as suggested by wigell (2016). it suffices to look at the reference list to see that geoeconomics is new ground. the average article on the topic came out in 2011. the median publication date is 2012. the oldest publication is from 1991 and could be defined as an outlier. the number of researchers with profiles on google scholar who say they focus on geoeconomics are less than a dozen, but then many scholars in this field will typically steer clear of the publication haze that indexes promotes. of course the numbers for geopolitics are much higher. at the beginning of the 21st century it was clear that neoclassic theory as developed after the second world war had mostly been a flawed project, now even admitted at their own conferences and declared by conservative media like the economist. the neoclassic or marginalist paradigm is not able to predict economic behavior and its explanations of current events are too simplistic and narrow to be of much use outside of its journals, even though the committee for the nobel prize in economics (“in memory of alfred nobel”), which is still the final guarantor of the neoclassic paradigm, do their utmost to convince the public of the opposite. instead other schools have done better in the meantime, like institutional economics. keynesianism and marxism have also seen a revival in past decades and are clearly more relevant directions within the study of economics. the evolutionary approach was left for the wrong reasons, not because the science itself was flawed, but because of the way it was used, applied, first of all by german national socialists and fascists to dominate other people and countries. this is much like leaving the science of nuclear physics because of what happened in hiroshima and nagasaki. it’s understandable, but irrational. besides, the new american superpower needed a new paradigm, its own (the theories were invented on the european continent, but the new science developed on the american continent). those who deviated from this new paradigm were marginalized in the post-war academic world. a good example is peter drucker who was successful outside of academia among ceos and corporations. he was more relevant than all the neoclassic scholars put together. other scholars, who had completely different opinions about economics but could do the necessary math needed in neoclassic economics (econometrics, advanced statistics and calculus), like georgescu-roegen, were embraced, at least for a while, but isolated as soon as he openly objected to the paradigm. other scholars who started out supporting the neoclassic paradigm, like schumpeter, saw its scientific flaws and deviated from it in later life. schumpeter went back to evolutionary theory at the end of his “economic analysis”, published by his wife after his death. critical theorists can argue that the neoclassic paradigm has basically served to preserve the power of a certain american and anglo-saxon dominated elite. thus the decline of the neoclassic paradigm coincides with the decline of the american superpower. 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(2019) integration of textual voc into a cx data model for business intelligence use in b2c. journal of intelligence studies in business. 9 (3) 39-55. article url: https://ojs.hh.se/index.php/jisib/article/view/476 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index integration of textual voc into a cx data model for business intelligence use in b2c lucie sperkovaa* auniversity of economics, prauge, czech republic; *lucie.sperkova@vse.cz journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solbergsøilen included in this printed copy: empirical evidence from a connectivist competitive intelligence massive open online course (ci cmooc) proof of concept competitive intelligence as a game changer for africa’s competitiveness in the global economy alexander maune pp. 24-38 integration of textual voc into a cx data model for business intelligence use in b2c lucie sperkova pp. 39-55 how competitive intelligence can be used to improve a management vocational high school: a case from indonesia verry ronny pailingan and pp. 56-61 johan reimon batmetan v ol9,n o 3,2019 journal ofintelligencestudiesin b usiness issn: 2001-015x vol. 9,no.3,2019 gianita bleoju, alexandru capatina,valter pp. 7-23 vairinhos, rozalia nistor, and nicolas lesca effect of competitive intelligence on innovation capability: an exploratory study in mexican companie eduardo rafael poblano-ojinaga, roberto pp. 62-67 romero lópez, jesús andrés hernández gómez, and vianey torres-arguelles integration of textual voc into a cx data model for business intelligence use in b2c lucie sperkovaa* auniversity of economics, prague, czech republic *corresponding author: lucie.sperkova@vse.cz received 12 december 2019 accepted 30 december 2019 abstract customer experience (cx) focuses on customer feedback. cx is a holistic construct which contains different perceptual elements such as satisfaction and loyalty, but also emotions or personality. customers share their opinions, which contain these elements also in textual expressions through different channels, known in research as voice of customer (voc). currently, voc is collected mainly in customer surveys and manually evaluated, or through simple quantitative measurement from data scattered in various systems at the end of a customer journey. to bridge this gap, we designed a multidimensional cx data model for integrated storage of all customers’ data from structured and textual sources. a consolidated cx measurement to monitor elements of cx during the entire customer journey from the customer perspective is proposed to serve as business intelligence. the artefact offers a selfcontained expandable data mart affordable to implement in small and medium b2c enterprises. companies can now manage customer relationships and future performance more automatically and effectively thanks to integrated information mined from texts, combined with other data from internal systems and shared across the company in unified reporting. keywords customer experience, data model, perceptual metrics, sentiment, voice of customer 1. introduction customer experience (cx) can be understood in its holistic conception as a demonstration of experience through different elements, which originates in the customer. it encompasses cognitive, emotional, and social characteristics, as well as the user’s quantitative interaction with the company (verhoef et al., 2009) during the customer’s entire purchase journey (lemon and verhoef, 2016). it is also an instrument to improve the value of the customer and the company. from the latter, it follows that the experience can be managed through the measurement of the elements connected as antecedents, succedents, or as parallel constructs to cx. these elements represent share-of-mind metrics, which are critical when managing to achieve better performance of an organisation. the approaches for gathering data for cx are based mainly on the manual evaluation of questionnaires and surveys (e.g. klaus and maklan, 2013; klaus, 2015; khodadadi et al., 2016). reading every text is time-consuming and resource-demanding (nahili et al., 2019). in practice, the measurement of cx is currently dependent mostly on the evaluation of single metrics such as net promoter score (nps). these metrics are gathered with structured behavioural or transactional data as standalone quantitative indicators instead of metrics based on the text itself (e.g. godes and mayzlin, 2004; liu, 2006; wu and zheng, 2012). the evaluators extract necessary data journal of intelligence studies in business vol. 9, no. 3 (2019) pp. 39-55 open access: freely available at: https://ojs.hh.se/ 40 from specific tools or analytical crm (e.g. aziza, oubrich and søilen, 2015). cx management emphasises value creation. from a managerial perspective, firms should pay attention to textual content when managing cx and, more importantly, focus on the right measures. the value cannot be calculated merely from structured data as it is impossible to set the probability of a rise of such surprising information from voc. successful cx management needs to systematically collect voc, mine that voc for insights, share the insights with the business, and incorporate the insights into business decisions. that requires the ability to design, implement, and manage cx in a disciplined manner as a business intelligence (bi) solution. as is seen from the results of qualitative research in (šperková, 2019), the most challenging for marketers is the synthesis of information from voc into useful reports. the model targets this synthesis of the information to gain new insight into the cx. there are many barriers to achieving the full potential of voc analysis within cx, as the author identified in the previous qualitative research (šperková, 2019) which can be overcome with the cx data model (missing shared voc insights across the organisation, struggle to prove financial results, textual voc is not well-analysed, fragmented view of the customer and missing integration of data, missing action with individual customers, missing formalisation of the processes). since the underlying data for cx measurement are located in different internal and external sources of the company, the examination of voc for managing cx from one source only is incomplete. companies should collect both qualitative and quantitative data from these sources to acquire a holistic view of cx. when accessing data from separate systems, end-users are not able to interconnect the data according to their identifiers or metadata and find valuable information about individual customers resulting from various customer data and voc interconnections. endusers need to access the data from one integrated physical place stored in a unified form. the unified storage ensures the accuracy and reliability of the following measurement with minimal manual effort. the proposed cx data model follows and builds on the author’s previous research on the integration of voc into bi in the banking domain (šperková, 2014; šperková and škola, 2015a, 2015b; šperková, škola and bruckner, 2015; vencovský, bruckner and šperková, 2016). the model exploits data from analytical crm. the aim is not a complex platform based on crm but a self-contained expandable and transferable data model containing the data from textual voc among other data, which can be implemented in any bi solution that is also affordable for small and medium enterprises (smes). smes have not fully adopted big data analysis systems (gauzelin and bentz, 2017) as such applications are not primarily accessible to them (papachristodoulou et al., 2017). this solution can facilitate timely decision making based on cx and improve relationships with customers. 2. problem studied measurements of cx lack clear definitions of the constructs and dimensionalities. research emphasises the need for the development of robust metrics for the cx measurement (verhoef et al., 2009; jain, aagja and bagdare, 2017; lemon and verhoef, 2016; zaki and neely, 2019). gupta and zeithaml (2006, p.735) stressed “the need for more studies that view customer metrics comprehensively, rather than examining only a few constructs at a time”. many conceptual models were designed (e.g. parasuraman, zeithaml and berry, 1988; lemke, clark and wilson, 2011; grewal, levy and kumar, 2009; klaus, 2015; lemon and verhoef, 2016; mccoll-kennedy et al., 2018) with different dimensions of research; for comparison see khodadadi et al. (2016) and havíř (2017). prior research has suggested that the customer’s assessment of experience influences not only the single share-of-mind metrics such as customer satisfaction, customer loyalty or word-of-mouth, but also customer profitability and customer lifetime value (e.g. bolton et al., 2004; verhoef, 2003). organisations tend to measure specific aspects of the cx as customer perceptions for a single transaction at a point in time, or as an overarching perception. customer satisfaction is the dominant customer feedback for measuring perceptions; however, it typically does not capture the full cx as it is concentrated at the end of the customer journey while ignoring the underlying issues and concerns resulting from the experience during the customer journey. the idea of measurement of overall cx at each stage of the customer journey for every touchpoint (lemon and verhoef, 2016) is still in an early phase of development. there is no agreement on robust measurement approaches, and no rigorous 41 assessment of metrics that should be collected has been developed to evaluate all aspects of cx across the customer journey (lemon and verhoef, 2016; zaki and neely, 2019). existing scales (e.g. brakus et al., 2009; klaus, 2015) are aimed at specific research, and they are not understood as parts of the data model. researchers stress the importance of measurement of emotions, personality traits and sentiment detected in textual voc as these cx elements accompany the customers’ entire journey (chen and lin, 2015; verhoef and lemon, 2016; mccoll-kennedy et al., 2018). personality, along with emotions, is a latent construct of cx. they are the main drivers of customer behaviour, and their determination can recognise behavioural patterns. research in service quality analyzes sentiment as an indicator of satisfaction based on text analytics. however, they focus only on the product/service/organisation perspective (song et al., 2016; palese and piccoli, 2016; james et al., 2017; vencovský, 2018; farhadloo et al., 2016) rather than cx quality. the sentiment is aggregated for single products or product features, but it is not possible to map the sentiment back to the customer who wrote the comment. customer perspective is neglected. when appraising an interaction, it is essential to evaluate the polarity of the interactions in a particular context – not only from the viewpoint of a marketing objective, but also the customer perspective – if the company wants to contribute to customer retention. customer reviews predominate as a dominant source of voc. the evaluation of reviews is primarily performed with structured likert-type scale ratings (tsang and prendergast, 2009) and assessment of their effects on purchase decisions with some research focus on sentiment (zhang et al., 2016; li et al., 2019). although companies typically possess quantitative crm data on customer buying habits and classifications, there is little knowledge about the personality and emotions of these customers and their evaluations. cx is more complicated than simple crm metrics alone (zaki and neely, 2019). information like opinions and emotions, but also personality, which cannot be found in transactional and other structured data, are partly hidden in customers’ written expressions. metrics should focus more on perceptions and attitudes to gain a comprehensive understanding of customers from their perspective. some researchers have built frameworks for automatic analysis of single sources of textual voc data for bi purposes (chau & xu 2012; peng et al. 2012; yulianto et al., 2018), however without any context to structure data within the multidimensional data model. earlier, yaakub et al. (2012; 2015) proposed an enhancement to the customer analysis multidimensional data model for the ontology model to calculate and analyse the opinion orientation of some groups of customers for products in certain levels based on the ontology gained from textual customer reviews. the customer analysis model designed by yaakub (2015) represents the starting point for the cx data model in this article. yaakub’s research misses an integration with other structured customer data on an individual level, so the designed model stands alone without any context to other tables from the customer dimension. however, yaakub emphasises the importance of the integration of the opinion from textual data with other customer structured data. this research extends the opinion fact table by adding emotions and personality traits linked to the customer dimension. the cx data model significantly expands on yaakub's model by adding other tables with textual information and references to tables with the structural data from other sources. the cx data model results from the need for cx measurement. the artefact of cx measurements primarily builds on and extends the research in cx conducted by lemon and verhoef (2016) and zaki and neely (2019). 3. mining the cx elements from the textual voc customer’s opinions play a significant role in cx. these opinions are contained in voc and contain “sentiments, appraisals, attitudes, and emotions toward entities and their attributes expressed in a written text” (liu, 2015). analysing of voc requires text analytics due to the textual expression. text analytics characterises the content of the unstructured text by subject matter major and minor topics and by positive and negative sentiment or emotions. the aim of this article is not to find the specific methods of analysing the text, but the way to store the information gained by these methods in a unified data model. the opinion target is an entity which represents the object of the cx and its aspects described in the customer textual contribution (comment) as depicted in figure 1. the 42 elements of the cx then reflect perceptions of the opinion targets and are represented by: 1) sentiment expressed about the target objects (positive, negative, neutral) and its intensity. 2) discrete emotions expressed about the target objects (e.g. joy, sadness, trust). the text can be multi-emotional. 3) personality traits of the customer who expressed the opinion (e.g. extroversion, neuroticism) can be determined from the overall expression of the customer. a customer is considered to have more than just one personality, so its intensity must be tracked. the object can be a product or service, topic, event, person or an issue related to the product, service or company itself about how the customer expresses their opinion. the object can be discussed from different perspectives, which represent different aspects. these aspects can be product/service attributes (features), components, functionality or the dimensions of quality. for example, if the customer buys a sightseeing flight, the object is the flight itself, and aspects can be the plane comfortability, price the customer paid for the flight, weather on the day of the flight, or the satisfaction with the pilot. all these aspects the customer can evaluate with different words, some of which carrying the sentiment of appraisal words. according to song et al. (2016), only the crucial aspects should be considered features or components. some aspects can be close to each other on the same topic and clustered together into a aspect category under one term. this step reduces the number of different aspects with the same informative value. the aspect category is typically more general than the aspect term itself and does not necessarily occur as a term in the text. for example, if the customer talks about the aspect category weather, she or he can use a sentence like “it was a beautiful sunny day without any clouds”. the detected aspects are sunny day and cloud, and both terms fall under the aspect category weather. for the purposes of cx measurements, satisfaction and expressed emotions about individual objects and their aspects are not only interesting but also the overall customer satisfaction. the customer can write many comments; each comment contains opinions about different objects with several aspects. the sentiment and emotions are assigned to every aspect for every object in every subjective comment (if there is some detected). the object’s sentiment is derived from the expressed aspects’ sentiment; the comment’s sentiment is derived from the sentiment of discussed objects in the comment. in other words, the overall satisfaction and expressed emotions are gained from the classification of the lower levels of analysis. this approach is consistent with the multidimensionality and enables us to add customer perspective to the cx with preservation of the product perspective by drilling and slicing at lower levels of granularity (for example to measure the average sentiment of a specific aspect of an object from the perspective of a chosen customer segment). the personality traits are determined from all the comments the customer has written. more textual data ensures a better prediction of the personality. determination of the emotional elements is possible only from the subjective and evaluative text with the emotional sentiment. the element of personality traits is also possible to determine from the text with a rational sentiment. 4. methodology the research is driven by the design science methodology (wieringa, 2014). the solution design follows the preliminary research in cx and voc. definition of cx measurement is based on a literature review, which puts existing constructs and metrics into mutual relationships and previous research (šperková, 2019). necessary metrics and indicators to be followed by companies were detected in order to measure complex cx. figure 1 the parts of the voc content from a single customer perspective. 43 design of metrics for cx measurement is based on customer sentiment, customer emotions and personality traits extracted from textual voc by text analytics methods. the design respects the criteria for the application of text analytics methods to gain the necessary elements, and specifications of metrics and indicators are defined. the metrics are expressed from the bi perspective, according to kimball et al. (2015). design of the multidimensional cx data model is enhanced with stored information extracted from textual voc. the model respects the principles of multidimensional modelling (inmon, 2002), and uses the unified modelling language (uml) class-based approach. based on the target metrics, a method is suggested to store the underlying data for measurement and reporting of cx elements. the architectural framework for the solution design is depicted in figure 2. the picture shows the integration process of textual voc to the cx measurement from the data source collection to the reporting. the approach to the integration of textual voc applies a textual extract/transformation/load (etl) process onto the documents and extracts information as values of the entities and their attributes, as found in the text. information is stored in the multidimensional model as structured data. the process of integration requires more stages for the transformation of the data. therefore, three stages were suggested as depicted in figure 2. first, the textual prestage stores the results from a pre-processing phase, which includes data cleaning and feature extraction and selection. these results serve as a data layer for content analysis. second, the textual stage then stores information gained by text analytics methods above the content. and third, the analytical stage is then linked to the textual stage for the calculation of cx metrics as a logic layer of the bi. the analytical stage stores the structured customers’ data with the results of analytical processes (such as data mining models) where cx elements are modelled based on the extracted information from textual data. the textual stage must be loaded first to fill tables in the analytical stage. the loading phase in the model is a part of the textual etl. the highest layer of the framework is the access layer, which encompasses proposed metrics for reporting. 5. design of cx measurement the proposal of the metrics represents the application of cx constructs (parasuraman, zeithaml and berry, 1988; lemke, clark and wilson 2011; klaus, 2015; lemon and verhoef, 2016; mccoll-kennedy et al., 2018) with their constituent elements as the result of a thorough analysis of the current research in cx. the selection of the specific metrics and corresponding dimensions follows the figure 2 bi framework for the process of voc integration to cx. 44 literature review and the results of the quantitative research in šperková (2019). during the interviews, the participants were asked which metrics and indicators are important for the monitoring and evaluating the cx in their organisations. the measurement is enriched for new elements of customer sentiment, customer emotions and personality traits. since cx is in this research assumed a customer perspective during their decision journey, the following metrics were suggested for measurement, to evaluate elements of cx from a customer perspective during the customer journey. the metrics evaluating cx from a company perspective are omitted as the goal is to get to the individual level of the customer. metrics summarise various aspects of the data in the multi-level aggregated form and are comparable to the surveyed dimensions in the cx research. the metric is understood as a quantitative or qualitative indicator or an evaluation criterion to assess the level of cx with its constituent elements. the primary purpose is to highlight the relevant facts that the company needs to address and improve the level of cx. the underlying data for the evaluation of the metrics are stored in the data model, which is designed for the querying in order to gain the metrics results. the metrics are supposed to be visualized in reports and dashboards: applications that organise metrics in a clear and intuitive graphical form for further managing cx. the metrics listed in table 1 are designed on a general level as they can be customised according to the business and available data. the table contains the definition and construction of metrics and related cx elements which ensure a placing of the metrics into the cx construct. table 1 metrics and indicators in cx measurement. metric/indicator definition/construction/sub-metrics related cx elements customer effort score (ces) determines how much effort a customer has to exert to get a result (issue solved, request fulfilled, product purchased, question answered) on a scale from very easy to very difficult. engagement (cognitive); satisfaction; personality customer satisfaction score determines satisfaction on a scale from very unsatisfied to very satisfied. engagement (affective intimacy); satisfaction (evaluative) discrete emotion detects customer’s primary emotions according to the model of (plutchik 1980): anger, anticipation, disgust, fear, joy, sadness, surprise, trust. emotions can be enhanced for other from plutchik’s wheel of emotions. emotions; satisfaction; loyalty (attitudinal) emotional value detects the emotional value based on detected emotions on the scale: strongly negative, negative, rational, positive, strongly positive. emotions first response time calculates the average amount of time elapsed until initial response to the customer’s contact according to the type of the contribution: comment type = complaint, suggestion, requirement satisfaction involvement level indicates the involvement level based on the following metrics: number of unique site visits, number of advertising impressions and clicks, number of website page views, time spent per session, time spent per page, number of in-store visits, number of newsletter subscriptions engagement net promoter score (nps) determines detractors, promoters and passive customers. the indicator represents the answer to the question “how likely you would recommend company/product/service to a friend or colleague?” on a scale from 0 = very unlikely to 10 = very likely). detractors, for a score of 0–6, passives, for a score of 7 or 8, promoters, for a score of 9 or 10. satisfaction (evaluative) number of cancellations indicates the number of cancellations the customer made (i.e. cancel an ordered service). satisfaction number of complaints indicates the number of complaints the customer sent to the company by a summary of individual comments with the type = complaint. engagement (cognitive interaction); emotions satisfaction number of compliments indicates the number of compliments the customer sent to the company by a summary of individual comments with the type = compliments. engagement (cognitive interaction); emotions satisfaction number of public comments indicates the number of public contributions by summary. engagement (affective interaction); loyalty (attitudinal) number of requirements indicates the number of suggestions the customer sent to the company by a summary of individual comments with the type = requirement. customer expectation; engagement (cognitive interaction); emotions 45 metric/indicator definition/construction/sub-metrics related cx elements number of returns indicates the number of returns the customer made (for example to cancel the service). satisfaction number of suggestions indicates the number of suggestions the customer sent to the company by a summary of individual comments with the type = suggestion. engagement (cognitive interaction); emotions personality a mixture of personalities values (openness, agreeableness, conscientiousness, extraversion, neuroticism) according to the fivefactor model (mccrae and john 1992). can be visualised as a radar graph. personality problem resolution time calculates the average amount of time for resolution of the customer’s complaint: between when the customer first creates an issue ticket to when the issue is solved. satisfaction recency, frequency, monetary (rfm) determines: recency – how recently made the customer purchase (interval between the time of the last transaction and first day of each season); frequency – how often the customer purchases (number of days which occur a transaction during each season; monetary – how much the customer spent (the average amount of money spent on purchases during each season). the result is the customer’s placement in the cube according to binning the scores of frequency, recency and monetary into five equal frequency bins (kohavi and parekh 2004). state in the customer journey; engagement (interaction); loyalty (behavioural) referral value indicates the customer referral value by the following metrics: reach: number of impressions/responses/shares (forwarded content) to the customer’s contributions; sentiment of the responses to the customer’s contributions; importance of the responded contacts to the customer’s contribution; number of sent invitations to join the community by customer; number of public contributions; sentiment of the shared contributions sentiment; engagement (affective influence) review score indicates the quality of the subject of consumption at a numerical scale. satisfaction (evaluative) sentiment calculates the sentiment of the customer contribution as a value to determine the polarity of the sentiment: positive, if sentiment value > 0, negative, if sentiment value < 0, neutral, if sentiment value = 0. satisfaction (emotional); loyalty (attitudinal); engagement (affective intimacy) share-of-wallet determines how much of available budget customer spent at the company versus competitors.customer’s total revenue/total spend x 100 engagement; loyalty (behavioural) value of knowledge indicator of demanding (high value) and difficult customers (low value). demanding: willing to participate in finding problem solutions. difficult: requires energy on solving issues without the support of knowledge. engagement in reports, metrics can be viewed from many dimensions, for immediate use in decisionmaking processes in the organisation. the examples of considered dimensions for filtering, slicing and drilling the metrics are defined in table 2. the results of metrics can also act as dimensions to filter/slice/drill other metrics. for example, customer satisfaction is determined by customer sentiment. customer sentiment can be assigned both to all the customer’s comments as a summary sentiment and to a specific comment, object or aspect only. further, sentiment can be used to slice the measurement of most active customers (determined by a number of comments posted by the customer) and show only those with negative sentiment polarity. all metrics are related to the time dimension, and the customer dimension as the measurement is aiming to the customer perspective. the values in dimensions (e.g. particular segments) can change according to stakeholders‘ needs. the classification to the segments that can serve further as views to some metrics as dimensions can depend on results of other metrics. for example, the classification into loyalty segments depends on the results of the rfm score and engagement level (spreading positive wom). the rfm score ascertains if the customer is still alive and makes purchases, but it may be that customer has not purchased for an extended period of time, but still talks positively about the company, thus spreading positive wom. such a customer would be in the loyalty matrix more in the left top corner as a latent loyal. the understanding of the causes of weak and negative attitudes in a customer can help companies identify barriers to purchase. the definition of the segments and the borderlines between the segments depends on the business case and the goals of the company. the right segments should fulfil characteristics of similarity within the segments, differences between the segments, sufficient size of the segment and verifiability over time. table 2 dimensions in cx measurement. examples of dimensions resulting from the data model description channel dimension stores the different modes for interacting with customers. represents the source of data of voc (e.g. review, email, post on a social network) customer dimension stores the static information about the customer object dimension represents the product, service, topic, issue, person or event represented as an object detected in the text aspect dimension represents the aspects of the object (dimension of quality, functionality, component) detected in text comment dimension detect type of the comment (complaint, compliment, suggestion, requirement, need) time dimension universal periods used throughout the model (year, quarter, month, week, date, datetime) sentiment polarity detect the polarity of the sentiment (positive, negative, neutral) loyalty segment determines customer loyalty based on a two-dimensional model of (dick and basu 1994). the result is the customer’s placement in the matrix: no loyalty (low repeat purchases, weak relative attitude); spurious loyalty (high repeat purchases, weak relative attitude); latent loyalty (low repeat purchases, strong relative attitude); loyalty (high repeat purchases, strong relative attitude) recency, frequency, monetary (rfm) segment determines the rfm segment based on the measured rfm score. the segments can be refined according to stakeholders’ needs. loyal customer (highest recency, highest frequency, highest monetary); potential loyal (high recency, high monetary, more than one purchase); new customer (high recency, low frequency); attention seeker (high monetary, high frequency, low recency); sleeping customer (lower recency, lower frequency, lower monetary); lost customer (lowest recency, lowest frequency, lowest monetary) customer state in the journey dimension extends the rfm result for other information gained about the customer. detects the customer state in his/her customer journey according to buttle and maklan (2015): suspect: potential customer fit the target market; prospect: the customer fits the target market profile and is being approached for the first time; first-time customer: the customer makes the first purchase; repeat customer: the customer makes an additional purchase.; majority customer: the customer selects the company as a supplier of choice.; loyal customer: the customer is resistant to switching suppliers and has a strong positive attitude to the company or offer; recovered customer (customer who was considered as lost in last defined period, but purchased in the current period) 6. textual stage of the cx data model the textual stage of the designed data model is a result of the textual etl and can be divided into a textual pre-stage for results from preprocessing and a textual stage. in the prestage, the lexicons are stored for applications of models for content analysis or other data suitable for further processing. among these lexicons are sentiment, emotion and personality lexicons for detection of these elements, but also domain ontologies for result refinement. the results of text analyses are stored in the textual stage – sentiment, emotion, personality traits and opinion targets (objects and aspects), which further serve for measurement of cx elements in the analytical stage. 6.1 input data the customer interacts with the company and its other customers or prospects through different channels. an example of the process of collection of initial data from two different sources through web crawling and application interface is described in šperková, škola and bruckner (2015). the data are transferred in a clearly defined format suitable for storage in the relational database. the input to the etl process for the cx model is a structured table with all the raw interactions containing the opinions of the customers. every single interaction is stored in the database under its identifier. the meta-data of one interaction represents one row in the table, including the raw text of the content. the input table contains at least these attributes: • interaction identifier: the unique identification of the interaction • contributor identifier: the unique identification of the user who expresses the comment 47 • source identifier: the unique identifier of the source of the interaction • timestamp: the exact time the comment was sent or posted • comment text: the content of the interaction in plain text other attributes can be added (if any exist) containing additional information, for example, other contributors’ identifiers, if the comment is accompanied by a rating in likerttype scale or if the comments belong to different dimensions of experience. the table stores the raw textual data prior to any text analytics processes, so it is always possible to return to the original text. every comment discusses at least one target object (opinion target) and not all the target objects discussed in one comment must be correlated. in the textual stage, this table represents the table comment in the model and can be completed by other transformed input data from different channels. the determination of the opinion target is a task for text analytics. 6.2 pre-processing phase the pre-processing of the textual comments is based on a standard feature extraction and selection processes (liu, 2015). the comments are spell-checked and parsed to sentences based on punctuation, tokenised and lemmatised. after tokenisation, the morphological tags (attribute morpho_tag) are assigned to the words and store to the relational table entity (figure 3). the morphological tags are results of the morphological analysis, which works with isolated verbal forms, regardless of their context. each tag is a string of 16 characters. every position has its meaning. the first position determines pos (n for noun, v for verb, a for adjective etc.), the second position contains the detailed determination of the word part. the 11th position determinates negation (straka and straková, 2018). to encompass entire phrases or n-grams in the text as subjects of mining methods (for example an aspect wellness weekend) and not only features represented by frequent nouns, adjectives and adverbs, the syntactic dependencies depicting opinion and target relations are also assigned (for example, with the universal dependencies treebanks) and stored in the column dependency_relation. the relational storage of a czech sentence “flying a plane could be cheaper” after preprocessing is depicted in table 3. the pre-processing phase of the textual data serves directly for the text analytics methods, and it is not critical to store the intermediate results to the database. nevertheless, these results can serve for further improvement and adjustment of the methods or as a domain knowledge corpus which can be enhanced for other attributes, for example, entity type (number, person, organisation and similar) or even sentiment. such results can be stored in a relational table, which has a relation to the transformed input table comment, as demonstrated in figure 3. one comment contains many tokenised entities for the recognition of opinion targets and appraisal words in the next steps. only the opinion targets (objects and aspects) enter the next phase. features and other words or phrases – which are representative words of aspects or appraisal words – do not enter the model. they serve only as evaluative words for the modelling of sentiment, emotions or personality traits. the aspect extraction is already a result of content analysis after pre-processing. table 3 relational table with pre-processing results. comment_ id sentence_ id token_ order token lemma morpho_tag pos_tag dependency _relation 2899 4 1 létání létání nnns1-----a---noun nsubj 2899 4 2 by být vc------------aux aux 2899 4 3 mohlo moci vpns---xr-aa--verb root 2899 4 4 být být vf--------a---aux cop 2899 4 5 levnější levný aans1----2a---adj xcomp 2899 4 6 . . z:------------punct punct figure 3 relationship between the comment and entity tables. 6.3 conceptual data model of the textual stage the textual stage represents the entities capturing the tacit knowledge available in textual comments. figure 4 depicts the underlying conceptual model proposed to capture customers’ opinions. the model shows only the necessary attributes for storing the textual data. the relation to ontology tables (emotion/personality/sentiment lexicons) and history tables is not depicted due to the readability of the model. for simplification, only concepts related to object and aspect are shown, as they are considered sufficient for the model's needs. the model extends and builds on the knowledge of yaakub (2015). the issue of yaakub’s model for opinion is that the fact table can store only one feature (aspect) per comment. this research adds the fact table opinion into the conceptual model to gain a whole feature hierarchy. in contrast to yaakub’s multidimensional model, the cx model needs to relate satisfaction and sentiment to relevant customers. therefore, it is not sufficient to keep the sentiment value only for the particular aspect in the aspect table, but it is needed to determine which customer holds this opinion as opinions differ from customer to customers. in the conceptual model, the contributor table as the contribution (comment) can also be written by a person who is not a customer of the company yet (i.e. potential customer or detractor). in a snowflake schema, it is possible to link the contributor entity through the comment table to the fact table opinion and filter to the specific contributor. then it is possible to find out the overall satisfaction of the contributor or their satisfaction with a particular comment, object or aspect. the comment class stores the full content of each customer’s contribution, including the date when the comment was written. the source of each comment is stored in the class comment_source with values like ‘email’, ‘call centre’, ‘social media’, ‘review’ and similar. the comment_type determines the type of the comment based on the detected information in the text – whether it is a ‘requirement’, ‘complaint’, ‘compliment’, ‘suggestion’ or ‘need’. if the comment is a review accompanied by the rating in a likert-type scale, the attribute rating gets its value. each comment is written by a contributor, and the relationship is many to one, as one contributor can write many comments. the figure 4 conceptual model of the textual stage. 49 contributor table comes with attributes identifying the contributor based on cookies, email, name, telephone number, transaction number or other identifiers which can distinguish the author of the comment based on meta-data gained from the comment. since some comments are not tagged with customer or account identifiers, there is no direct way to link such comments with a particular customer or account in the database. during etl, these attributes are further matched with existing information presented in the customer and account profiles, and the best match is then linked with the customer table at the analytical stage. contributors without a match get the attribute flag_active with the value ‘non-active’ in the customer table. the linking of customer profiles with customer interactions is an essential step in etl as it brings together the factual information about the customer gained from structured data with the factual information gained from the textual interaction used later in the cx data model. the object table stores the title of the discussed object. this table can represent any entity such a ‘product’, ‘issue’, ‘service’, ‘event’, ‘person’ determined in table object_type. the object table allows the model to be multidomain since it is possible to store comments on a wide range of topics. the object can be recognised from the contribution based on the relation to the product/service it belongs to: metadata (i.e. review submitted to a particular product, an email regarding the product the customer purchased), the discussed domain or based on a dominant topic in the text. the object is represented by a finite set of its aspects a = {a1, a2, … an}. a customer contribution (stored in the model in the comment table) contains opinions about a finite set of objects {o1, o2, …, ov} and a subset of aspects of each object. the m:n relation between the tables object and aspect replaces the idea that the product or service, which is the subject of the comment, is always classifiable into a hierarchy or family of products or services (yaakub 2015; lau et al. 2009). the basic idea of m:n relations between the tables object, aspect and comment is that a negative comment about the object (product) does not mean that the customer gives a negative opinion on its aspects, or negative comment about the aspect, as this does not necessarily mean that whole comment is negative too. also, the same aspect can be assigned to different objects (the aspect ‘battery’ is associated with both the object ‘mobile phone’ and object ‘laptop’). if the statement does not mention any aspect at all (overall experience), then the evaluation stored in the table opinion is assigned to the object in table object. the fact table opinion contains the information detected by text analytics methods and transformed into structured data. the table contains an identifier to dimension tables comment, object and aspect as the relation between these tables is m:n. the table stores the calculated sentiment_value, which serves in reporting for sentiment polarity determination: • positive, if sentiment_value > 0, • negative, if sentiment_value < 0, • neutral, if sentiment_value = 0 if the sentiment_value of all objects and aspects in the comment is zero and no emotions are detected, the comment is considered rational. the attribute rationality_flag in the comment table determines the character of the comment based on detected opinion – if the comment is ‘rational’ or ‘evaluative’. the rationality is determined by detected emotions and sentiment in the text. the opinion table also contains flags for eight primary discrete emotions according to plutchik (1980). if the model were expanded to more emotions from the plutchik’s wheel of emotions, the schema would have to change, and the relational table opinion_emotion would extend the model (figure 5) as the relation is m:n – one opinion can contain more emotions. as personality detection is based on whole comments, the fact table personality is related to the comment table only. the detection of the personality traits depends on the expression as a whole and does not relate to an aspect or object. the table stores a calculated value for every personality trait according to the fivefactor model (mccrae and john 1992). the values are then aggregated on the customer level through related comments. the date table inserts the dynamic character of cx into the model and enables tracking information over time. timestamp is an essential attribute for the reporting, figure 5 the m:n relation between opinion and emotion. 50 considering that a customer can have an inconsistent experience during the iterative customer journey. the personality table is not linked to the date table due to the assumption that the personality does not change with time. the personality prediction can be refined with additional textual data. 7. analytical stage of cx data model the analytical stage of the data model builds mainly on the knowledge of customer intelligence and exploits tables used in analytical crm following the designed metric. the analytical stage modelled in figure 6 as a physical model depicts the interconnection of the textual stage with the tables typical in analytical crm (e.g. personal information, sociodemographic data, product preferences), but also with the tables resulting from other sources of eis: • transactional data (orders, sales, etc.) • campaign data (campaign costs, budgets, plans from campaign management systems) • web data (click-stream data and other data from web analytics platforms) • results of data mining and other analytical processes as aggregated data (e.g. clv). these aggregated data serve as underlying data for metric reporting. for this reason, the data model is denormalised. the denormalisation also enables easier querying for analytical purposes. it is emphasised that not all tables are depicted in the model as the complexity changes based on available sources of data and elements detected in the text. the model can contain several dimensions depending on the granularity level of the measured cx. the model corresponds to a part of a complex analytical model, which is linked to several other entities. it provides a data mart for cx measurement, which can, in turn, be extensible for new entities and attributes. the model in figure 6 presents the fact and dimension tables necessary for metric reporting with examples of attributes. the display of relations to the timestamp and date dimensions are omitted to keep the clarity of the model. only the relation between the opinion fact table and the timestamp dimension table are kept to demonstrate the time dimension of the model. in reality, all fact tables have links to the timestamp or date dimension table to ensure the history maintenance with snapshots and storage in historical tables. the relationship to the dimension tables customer and product is depicted in the physical model. since the table object can represent any entity, such as a product or service, it is desirable to map values to the right tables according to the dimension table object_type. following this information, the object table has links to other appropriate tables. the mapping to the right object type is built on the similarity rules. if the value of the attribute object_name in the table object is founded in the attribute product_name of the product table, the row containing this value also gets the attribute object_id mapped to the object table. the principle with other classes would be similar. comparably, the aspect_type table determines the mapping of the aspect table to other internal dimension tables. the customer table replaces the contributor table from the textual stage, and the unidentified customers (contributors without a match) get the ‘non-active’ value to the attribute flag_active as such a contributor has not made a transaction with the company. except for the product and product category tables, the analytical stage presented in figure 6 expands the textual stage for other tables loaded from internal systems listed in table 4error! reference source not found.. 8. implications the cx data model and the subsequent measurement bring significant benefits for cx measurement and management. the artefact mitigates the barriers in achieving the full potential of analysing voc within cx, detected in šperková (2019). the model represents the application of the cx construct. the model brings a certain formalisation to cx measurement and management. the cx data model can help with a scope definition of measures needed to be monitored in a company. the model enables the necessary integration of textual voc from various channels and links this data to operational data, data from web analytics and other sources at one consolidated place accessible to all stakeholders. the model is extensible and transferable to any business environment. new entities, attributes and related metrics and dimensions can always be defined. connectors for new sources of data can be added. 51 the model is multidimensional and enables one to monitor elements from different viewpoints; dimensions allow querying specific subsets of data. data which contain the specific forms of searched objects, aspects or comments are then displayed. the textual part of the model for storing the information from textual content leverages the use of insight gained from textual voc within the share-of-mind metrics and significantly simplify the sharing of knowledge throughout the organisation. thanks to dimensionality and collection of data across different touchpoints with the time dimension, the model enables one to measure the experience during the customer journey. due to the consistency with other trusted data in unified storage, the integrated data model guarantees higher credibility and accuracy of textual voc and its subsequent measurement, which in the internet environment may not be satisfied. consolidation enables the reduction of random, time-consuming and error prone processes with less human effort, which is challenging to scale with the growing data. the connection to other financial data such as purchases, marketing costs, the performance of the channels and similar help to prove the financial results of cx actions. the model reflects the customer perspective of the opinion target while the product perspective is not omitted. it is possible to aggregate the sentiment according to the particular object or aspect based on all comments from all customers who mentioned that aspect in these comments. the view on customers becomes unified, and their data stored in fine granularity at the individual level enables targeted one-to-one actions. the model enables employees to communicate with the customer consistently through all channels based on shared knowledge within the organisation. long-term monitoring of metrics within the consolidated reports allows finding patterns in cx and taking the corresponding approach or prevent certain situations. for business users, the reporting of metrics on dashboards brings the visibility and clarity of all monitored metrics and their instant overview of improving or deteriorating. the close cooperation of analysts and end-users is necessary. end-users must understand the essence of the metrics to be able to work with them correctly. this approach leads to continual improvement of cx and growth of agility, profitability and orientation to the customers. figure 6 physical model of the analytical stage of the cx data model. table 4 tables added in the analytical stage. table name description channel the channel dimension table replaces the comment_source table from the textual stage. it contains all possible channels through customer interactions, not only with textual expression. this table represents the interconnection with other sources of the data. campaign the campaign dimension table extends the channel for another granularity which represents campaigns the customer interacts through the web. the table can have foreign keys to tables medium, source, placement or banner depending on the granularity level. if it is possible to react to campaigns with textual data, the reference from the table comment would be modelled. clickstream the clickstream fact table collects data from web analytics tools. it represents the interactions of individual cookies with individual campaigns. the attribute interaction_flag determines if the interaction was click or impression. if the cookie_id is recognised and linked to the customer_id, the reference with the customer table is linked. clv in the clv fact table predictions are stored from the clv modelling by different clv models – the prediction of the transactions and profit for the next period for every customer. customer_ claim the customer_claim table stores the data about the customer’s claims on purchased items. the claim_flag attribute determines if the claim is a replacement of the item, compensation or money return. customer_ demographic the table expands the table customer for demographical data. this table serves for segmentation customers based on demographical data. customer_ experience the customer experience table serves for storage the results of different metrics or classifications to different segments which represent constituent elements of cx. for example, rfm_segment is based on the results from table rfm. this table serves for easier querying to gain the results faster and preserving history values. otherwise, these values can be found in other tables. involvement the involvement table stores the aggregated data from web analytics tools which serve as metrics. if the cookie_id is recognised and linked to the customer_id, the reference with the customer table is linked. order the order fact table contains information about customer’s orders. if the order was cancelled during the process of the purchase, the cancellation_flag gets the positive value. the table can contain many attributes regarding the prices, methods of payment, delivery and similar. order_item the order_item table represents items purchased within the order. the table has a reference to the table order. the attribute return_date represents the date of return if the customer returned the item. the table can have many attributes with references to additional tables like service, if the item is coming with additional services. order_ delivery the order_delivery table stores the information about the timestamp when the order was delivered to the customer. based on this information, the average time of delivery can be measured. referral the referral table stores aggregated data from social networks analysis as metrics. rfm the rfm table stores the information for rfm calculation – frequency, recency. monetary values together with the assigned bin and segment. this table is a result of calculations and modelling based on the table order. session the session table is based on data from web analytics tools and stores the information about the customer’s visits on the company’s websites. if the cookie_id is recognised and linked to the customer_id, the reference with the customer table is linked. ticket the ticket table represents the customer’s claim, requirement, need or complaint submitted to the company. the ticket can be composed of a thread of comments. the table has a reference to the channel table, representing the channel through the customer submitted the ticket; the assigned_employee_id can represent the foreign key to the employee table (not shown in the model). the timestamp_submitted shows the time when the ticket was sent to the company and timestamp_updated records every update in the ticket. ticket_ metric the ticket_metric table serves for a calculation of metrics based on the information from attributes of the ticket table. the table records number of replies to every ticket (number of comments), number of reopens, how many employees were assigned to the ticket till his solution, the time the customer had to wait to the first response to the ticket is stored in first_response_time, the resolution_time stores the total time from the first contact to the solution of the ticket. requester_wait_time records the total time the customer spent waiting for the response. 9. conclusion the designed cx data model represents the application of cx constructs from previous research. the data model can be understood as a data mart of the data warehouse. the model builds on the knowledge from the customer analysis model designed by yaakub (2015). it is divided into textual and analytical stages, where the analytical stage is dependent on results from the textual stage. the metrics are expressed from the bi perspective based on dimensional modelling as indicators and their characteristics, analytical dimensions and their characteristics, and the relationship between dimensions and indicators. the elements of emotions, sentiment and personality traits are automatically detected from textual voc data with text analytics methods, which are the subject of further research. the mined information is joined with other operational, transactional and behavioural structured data from various systems in the unified multidimensional data model. the artefact solves the complexity of understanding the customer base by implementing a sophisticated data-driven approach to the comprehensive measurement of overall customer experience. the collection of all customer data from multiple channels, with which the customer interacts during their journey, into singular storage with unified access enables one to look at all customer data from the customer perspective according to the time dimension and evaluate their experience in a timely manner and their state in the journey. the artefact brings customer experience measurement to a new level of customer insight which drives loyalty across different channels. this contributes to retention marketing efforts in companies and provides a direct customer-oriented approach, replacing mass marketing conducted on aggregated data. the aim of further research is to implement this cx data model and measurement in different business domains to validate its usefulness and portability in practice. the development of the application based on the artefact that enables collaboration, management of marketing activities, or alerting can also be a topic for further research. 10. references aziza, a., oubrich, m., & søilen, k. s. 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(2017) proposal of an assessment scale in competitive intelligence applied to the tourism sector. journal of intelligence studies in business. 7 (2) 38-47. article url: https://ojs.hh.se/index.php/jisib/article/view/199 this article is open access, in compliance with strategy 2 of the 2002 budapest open access initiative, which states: scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. there are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. there is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives. journal of intelligence studies in business publication details, including instructions for authors and subscription information: https://ojs.hh.se/index.php/jisib/index proposal of an assessment scale in competitive intelligence applied to the tourism sector gisela casado salgueroa, pedro carlos resende jr.b and ignacio aldeanueva fernándeza adepartment of business economy and administration, faculty of economics and business studies, university of malaga, malaga, spain; bdepartment of administration, faculty of economics, administration, accounting and information science, university of brasilia, brasilia, brazil; corresponding authors: gcasado@uma.es, pcrj73@gmail.com and ialdeanuevaf@uma.es journal of intelligence studies in business please scroll down for article editor-in-chief: klaus solberg søilen included in this printed copy: why the social sciences should be based in evolutionary theory: the example of geoeconomics and intelligence studies proposal of an assessment scale in competitive intelligence applied to the tourism sector gisela casado salguero, pedro carlos pp. 38-47 resende jr. and ignacio aldeanueva fernández key success factors to business intelligence solution implementation journal of intelligence studies in business v o l 7 , n o 1 , 2 0 1 7 j o u r n a l o f i n t e llig e n c e s t u d ie s in b u s in e s s issn: 2001-015x vol. 7, no. 1 2017 josé manuel villamarín garcía and pp. 48-69 beatriz helena díaz pinzón business intelligence and smes: bridging the gap ekavi papachristodoulou, margarita pp. 70-78 koutsaki and efstathios kirkos klaus solberg søilen pp. 5-37 a new model for identifying emerging technologies klaus solberg søilen pp. 79-86 proposal of an assessment scale in competitive intelligence applied to the tourism sector gisela casado salgueroa*, pedro carlos resende jr.b* and ignacio aldeanueva fernándeza* adepartment of business economy and administration, faculty of economics and business studies, university of malaga, malaga, spain bdepartment of administration, faculty of economics, administration, accounting and information science, university of brasilia, brasilia, brazil *corresponding authors: gcasado@uma.es, pcrj73@gmail.com and ialdeanuevaf@uma.es received 27 january 2017; accepted 20 february 2017 abstract companies operate in uncertain environments, where decision-making is a complex task. thus, one of the key elements to take into account in the aforementioned decision-making is the environment in which the business operates. this is where competitive intelligence (ci) makes sense, understood as the process of establishing the environmental information needs, information acquisition and its analysis, transforming it into intelligence and putting it at the service of decision-makers in the company. this paper focuses on the proposal of a ci model that can be applied in the tourism sector, specifically in hotels, due to the relevance of this sector in many economies worldwide. in order to build the model a deep review of the ci literature was made and subsequently the content validation method was applied, for the purpose of identifying the most important items in the two first stages of the ci cycle: planning and collection. keywords competitive intelligence cycle, decision-making, hotel management, tourism 1. introduction nowadays, companies develop their activity in more and more uncertain and complex everyday environments (zhang et al., 2010). the nature of that environment makes it a difficult task for the companies to maintain a competitive advantage (shih et al., 2010), as well as carry out decision-making. according to jiménez-quintero & aldeanueva-fernández (2016), a country’s political situation, together with their way of visualizing international business, has an important impact on decisionmaking. consequently, management systems are now becoming more dynamic and less predictable, i.e., more sophisticated. in order to make decisions that guarantee the maintenance of a competitive advantage and business survival, companies not only have to take into account their internal environment, but also what has happened, is happening or could happen in their external environment. it is the latter point that competitive intelligence (ci) processes are focused on. ci can be defined as the art of collecting, processing and storing information to be made available to people at all levels of a firm to help shape its future and protect it against current competitive threats. it should be legal and respect codes of ethics. it involves a transfer of knowledge from the environment to the organisation within established rules (rouach & santi, 2001). as søilen (2015) states, the growing importance of ci in academics brings it closer to become a relevant discipline in the social sciences. the tourism sector is a key element for socioeconomic progress, because of the enterprise and job creation that comes with it. its growth has been practically uninterrupted and it is expected to continue with this trend journal of intelligence studies in business vol. 7, no. 1 (2017) pp. 38-47 open access: freely available at: https://ojs.hh.se/ 39 until 2030, according to the world tourism organization (2015). tourism growth is, therefore, essential to achieve gdp increments. this has been proved by extensive research undertaken in several countries: sweden, norwegian, denmark and more (lee & chang, 2008); united kingdom, croatia and spain (pérez-rodríguez et al., 2015); hungary, romania, france and spain (zurub et al., 2015); brazil, chile, colombia, ecuador, peru and other latin-american countries (eugenio-martín et al., 2004); taiwan and south korea (chen & chiou-wei, 2009); china, pakistan, russia and india (tiwari, 2011). given the importance that tourism has acquired worldwide, and its prominent role in the gdp of many economies, we decided to conduct research that linked, on the one hand, one of the key agents in tourism: hotels; and on the other hand, ci, understood as a tool for decision-making, and hence, business survival. in this context, the main objective of this paper is to elaborate on an assessment scale of the ci process applied to the tourism sector using a content validation method. this is because, apart from the aforementioned, a literature review about ci between 2011 and 2016 has been conducted, finding a lack of ci research in tourism. 2. literature review on competitive intelligence ci is based on the environmental school of strategic management (casado-salguero & jiménez-quintero, 2016) and plays a very important role in the development and deployment of corporate strategies (dishman & calof, 2008). the proof of this is in the significant number of proposals present in specialised literature that incorporate ci in several countries and fields. for instance, šperková et al. (2015) in the banking sector of czech republic, bisson (2014) in public agricultural organisations in france, and fatti & du toit (2013) in the pharmaceutical industry in south africa, etc. a traditional definition of ci is the one that porter (1980) presented in his book “competitive strategy: techniques for analysing industries and competitors”, where he explains that ci includes the early recognition of threats and opportunities through gathering and analysing information related to the environment of the company to support managers in the business decisionmaking process. according to calof (2008), ci helps the company maintain and create competitive advantages by using information from the environment about clients, competitors, and technologies. fleisher & bensoussan (2007) define this term as the process whereby a company legally gathers and interprets the environmental information, to make it available to decision-makers. in this case søilen (2016) shows that the internet and mobile telephones allow access to a wider range of knowledge about companies’ and people’s activities. therefore, it is necessary to enable secure encryption to preserve confidential electronic information. casado-salguero & jiménez-quintero (2016) explain that ci in the organisation is the set of practises aimed at gathering information from the business environment ethically and legally, in order to transform it into intelligent information useful for strategic decision-making and, therefore, leading to business success and survival. table 1 concepts under which ci has been studied, based on dishman & calof (2008) concept authors environmental scanning aguilar, 1967; fahey & king, 1977; fahey & narayanan, 1982; hambrick, 1982; sashittal & jassawalla, 2001; saxby et al., 2002 business intelligence cleland & king, 1975; benjamin, 1979; pearce, 1976 strategic intelligence aaker, 1983; montgomery & weinberg, 1979 competitor analysis ghoshal & westney, 1991; rothschild, 1979 competitive technical intelligence albagli et al., 1996; brockhoff, 1991 market intelligence chonko et al., 1991; maltz & kohli, 1996 peripheral vision day & schoemaker, 2006 competitive analytics concept davenport, 2006 40 table 2 empirical research on ci by industries (2011-2016) sector of activity authors exploitation of natural resources rothberg & erickson (2013); sewdass & du toit (2014); ramírez et al. (2013); guimaraes (2011); jin & ju (2014); johns & van doren (2010) public sector sewdass (2012) technology-based companies adidam et al. (2012); dos reis et al. (2013); yap et al. (2013); ramírez et al. (2013); mariadoss et al. (2014); de carvalho & janissek (2014); sewdass & du toit (2014); guimaraes (2011); samtani & capatina (2012); capatina et al. (2013); nemutanzhela & iyamu (2011); sun & wang (2015); jin & ju (2014); opait et al. (2016); ahearne et al. (2013); xu et al. (2011); johns & van doren (2010) manufacturing adidam et al. (2012); pellissier & nenzhelele (2013); yap et al. (2013); dos reis et al. (2013); sewdass & du toit (2014); guimaraes (2011); jin & ju (2014); shih et al. (2010) service sector faust & gadotti (2011); nemutanzhela & iyamu (2011); adidam et al. (2012); zheng et al. (2012); pellissier & nenzhelele (2013); dos reis et al. (2013); yap et al. (2013); tuţă et al. (2014); de carvalho & janissek (2014); sewdass & du toit (2014); trong (2013); guimaraes (2011); garcíaalsina et al. (2013); fernández & tañski (2011); rapp et al. (2015); zambon & anunciação (2014); ahearne et al. (2013); hughes et al. (2013) ; guarrochena & paul (2013); erickson & rothberg (2013) ; gatsoris (2012) ; pelissari et al. (2012); safarnia et al. (2011); fernández & tañski (2011) hotel sector faust & gadotti (2011); rapp et al. (2015); calero et al. (2010) despite its presence both in academic and professional areas, a single generally accepted definition of ci does not exist (fleisher & wright, 2009). in fact, as can be seen in table 1, there are different ci perspectives approached by several authors in the literature. examining the literature, in last five years we can find empirical research about ci in different sectors, including tourism. however, studies about ci in hotels are scarce, which is a strong argument to conduct this paper. to reach that conclusion a literature review in two databases was undertaken: coordenação de aperfeiçoamento de pessoal de nível superior (capes) and web of science (wos). these databases contain the highest impact journals in the indexed literature. the keyword in the search was “competitive intelligence”, and in order to select the sample of papers the following criteria where established: a) papers had to include the keyword “competitive intelligence”, either in the title or in the keywords; b) they had to follow empirical research; c) they had to belong to the field of business and economics; and d) they had to be published between 2011 and 2016. thirty-six papers were obtained in all, which constitute the analysis base used in this paper. the analysed papers were classified, as shown in table 2, within the following industries: exploitation of natural resources, public sector, technology-based companies, manufacturing, service sector, and finally, hotel sector. research in ci during the last five years can be summed up as follows: research is mostly focused on service sector companies (33% of the selected papers), followed by technology-based companies (31%) and manufacturing (16.7%). note the scarce research on the public sector (2.4%) and natural resources exploitation (11.9%), but it is especially important to highlight the poor participation of ci research in hotels, which comprises only 4.8% of selected papers. 3. proposal of a competitive intelligence model many multinational companies are aware of the fact that, thanks to ci, a competitive advantage can be achieved, so some of them, such as procter and gamble, general motors and british petroleum, have established formal ci units within the organisation or have 41 adopted structured processes to gather and analyse information from the environment (bose 2008; groom & david, 2001; pepper 1999; vedder et al., 1999; cited by hughes et al., 2013). furthermore, companies with a higher standard in ci activities also show better financial performance (adidam et al., 2012). due to the above, and the relevance of the tourism sector in many economies, we propose a ci model that can be applied by hotels. we focus on the first two stages of the ci cycle, based on a comprehensive literature review to establish the items belonging to each stage, items that have subsequently been validated by a committee of experts in the tourism sector. the result is a ci model applicable to hotels (and even to other sectors, with the appropriate modifications), which will allow to organisations to implement a ci process. but in practice, how is a ci process applied? there are several authors that talk about the so-called “ci cycle”, in other words, a set of successive phases that help us obtain the necessary intelligence for decision-making. in the various ci cycles that we can find in the literature, there are common elements among them. however, the name and number of the stages can be different (cloutier, 2013). figure 1 shows one of the most widely accepted ci cycles among professionals and academics. we are referring to the one proposed by the strategic and competitive intelligence professionals (2014). this cycle consists of the following five stages: a) planning (recognition of the information needs); b) gathering (needed information and choosing a source to obtain it); c) analysis (turning information into intelligence); d) dissemination (making the obtained intelligence available for decision-makers); and e) feedback (setting a mechanism to validate the reliability of the obtained intelligence to determine the potential variances in any stages of the cycle). 4. methodology to build the assessment scale of the ci practices, a content validation by a panel of judges was applied, according to hernándeznieto (2002) and pasquali (2010). to measure the content validation coefficient (cvc) of each item in the questionnaire, the following criteria were adopted: a) clarity of language; b) practical relevance; and c) theoretical relevance. the aim of the validation through a panel of judges is to confirm, theoretically, the hypothesis that items properly represent the figure 1 . stages in the ci cycle, based on strategic and competitive intelligence professionals (2014) and cloutier (2013). 42 construct, by asking people who don’t constitute a representative sample of the population to build that instrument (pasquali, 2010). nine judges were selected to be part of the production of the questionnaire content validation coefficient (cvc). cvc calculation was made through the following steps: a) each item mean score (mx) is calculated from the judges’ score: 𝑀" = 𝑋%& ' %() 𝑗 where i=1 represents the total judges’ score and j the number of judges. b) the initial cvc is obtained from: 𝐶𝑉𝐶% = 𝑀" 𝑉-." c) error is the same for each item, and it is calculated as follows: 𝑃01 = 1 𝑗 & d) then, the final cvc is obtained for each item: 𝐶𝑉𝐶3 = 𝐶𝑉𝐶% − 𝑃01 e) finally, the total cvc of the questionnaire is calculated for each assessment criteriaon (clarity of language, practical relevance and theoretical relevance): 𝐶𝑉𝐶5 = 𝑀6761 − 𝑀891 where m;<;= is the mean of content validation coefficient items and m>?=, the mean of error of the items in the questionnaire. after the calculation, it is recommended that only items with cvcb > 0,8areaccepted. are accepted. 5. analysis and results the instrument consists of two blocks of items that assess some of the main ci activities found in the literature: planning of the ci needs and information gathering. for the planning block, 51 items were proposed, although 30 didn’t reach the minimum coefficient required in the literature after the panel of judges’ evaluation and those items had to be removed from the scale. items with a content validation coefficient below 0.8 were excluded from the proposed scale. therefore, the block was only composed of 21 items. table 3 items referring to planning of ci activities. items referring to planning of ci activities 𝐶𝑉𝐶5 1. competitor price is decisive to fix my price 0.90 2. there is a management practise to monitor competitor strategy 0.87 3. there is a management practise to monitor competitor price 0.87 11. takes into account guest satisfaction with each department to manage it 0.83 12. takes into account guest opinion on the state of the premises 0.92 13. provider prices determine if we continue working with them in the future 0.84 15. we know other existing providers’ prices 0.93 17. issuing country’s political stability in long-term concerning decisions is taken into account 0.83 18. the economical stability of the country in long-term concerning decisions is taken into account 0.81 20. our country’s threat of terrorism impacts long-term decisions 0.83 28. level of crime and public security affect tourists arrival 0.86 29. our country’s infrastructure affects tourist arrival 0.86 30. issuing countries’ infrastructure affects tourist arrival 0.81 33. unemployment rate affects domestic tourism 0.91 34. issuing countries’ unemployment rate affects tourist arrival 0.87 36. the standard of living in our country impacts domestic tourism 0.93 37. issuing countries’ standard of living impacts tourist arrival 0.90 43. process automation affects way of working 0.84 45. issuing countries’ culture in its management is taken into account 0.87 46. countries’ culture in its management is taken into account 0.85 50. energy costs affects management 0.87 43 this way, there is alignment between the assessed dimensions and a coefficient whose extent is 0.13, the accepted rate in the literature. for the gathering block, 41 items were proposed, although 24 didn’t reach the minimum coefficient required in the literature after the panel of judges’ evaluation and those items had to be removed from the scale. items with a content validation coefficient below 0.8 were excluded from the proposed scale. therefore, the block was only composed of 17 items. for items referring to information gathering, the extent of the cvct was 0.18, as recommended in the literature. that was possible due to the fact that in about 35% of the items, the cvct was between 0.9 and 1. at least one item, one out of the three assessed dimensions, had a maximum concordance qualification among the panel of judges. table 4 items referring to gathering of the information. items referring to gathering of the information 𝐶𝑉𝐶5 1. there is a management practise to identify main competitors 0.97 2. there is a management practise to monitor competitor strategy 0.84 3. there is a management practise to monitor competitor price 0.96 4. there is a management practise to monitor new competitor services 0.84 5. there is a management practise to monitor competitor scores on search engines 0.88 7. there is a management practise to segment the market 0.93 8. there is a management practise to determine each segment’s characteristics 0.87 9. there is a management practise to monitor guests’ suggestions 0.93 11. there is a management practise to monitor the information obtained about guests in each department 0.99 12. there is a management practise to monitor the information obtained about competitors in each department 0.84 20. there is a management practise to monitor environmental legislation 0.84 21. there is a management practise to monitor the level of crime and public security 0.81 31. there is a management practise to monitor labour qualification 0.84 33. there is a management practise to monitor new icts 0.87 34. there is a management practise to monitor the life cycle of the products 0.86 39. there is a management practise to monitor energy costs 0.90 41. there is a management practise to cooperate with strategic alliances to develop new products and services 0.84 6. conclusions and future research if a company wants to survive and be successful, it has to be accomplished by means of least bias decision-making. nowadays, it is a difficult duty as far as the environment is concerned due to its instability and turbulence, consequently it is indispensable to have a wide knowledge of it, in such a way that the environment information can be incorporated into decision-making. for decades, companies have understood this, and many well-known companies, even the most limited in size and resources, are applying ci processes that allow them to have a better understanding of their environment. in this paper we present a study of how ci processes should be applied in one of the most important sectors in many economies: tourism. specifically, this work focuses on the proposal of a ci assessment model for hotels, on the basis of the two first stages of the ci cycle described by the strategic and competitive intelligence professionals (2014). after a comprehensive literature review, in the first stage (planning), 51 items were obtained, and in the second one (gathering), 41. in each stage, hernández-nieto (2002) and pasquali’s (2010) content validation method was applied, and items were reduced to 21 in the first stage and 17 in the second. the aim of this research is that the first two assessed stages of the ci cycle can be of used for hotels’ decision-makers to get to know how their company applies ci processes, or to help them to establish structured ci process. furthermore, we pursue an increase in scientific knowledge in business management. in this line of research, and in accordance with the topic, we keep the possibility of 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