24961_06_Uotila.pdf A method for assessing absorptive capacity of a regional innovation system TUOMO UOTILA, VESA HARMAAKORPI AND HELINÄ MELKAS Uotila, Tuomo, Vesa Harmaakorpi & Helinä Melkas (2006). A method for assess- ing absorptive capacity of a regional innovation system. Fennia 184: 1, pp. 49– 58. Helsinki. ISSN 0015-0010. The present study focuses on two important dynamic capabilities in regional in- novation systems: visionary capability and innovative capability. Visionary capa- bility is based on the ability to acquire and assimilate future-oriented knowl- edge, and innovative capability on the ability to transform and exploit the ac- quired knowledge in the actual innovation processes. In the regional innovation system, innovation processes often take place in heterogeneous multi-actor in- novation networks that set special demands for the absorptive capacity of the entire system. The present article sheds light on the aggregate process of generat- ing and using foresight knowledge in regional innovation processes. Experiences gained by resource-based futures research and an “innovation session method” in the Lahti Region in Finland are described in a case study. Tuomo Uotila, Helsinki University of Technology, Lahti Center, Saimaankatu 11, FI-15140 Lahti, Finland. E-mail: tuomo.uotila@tkk.fi. Vesa Harmaakorpi, Lappeenranta University of Technology, Lahti Unit, Saimaan- katu 11, FI-15140 Lahti, Finland. E-mail: vesa.harmaakorpi@lut.fi. Helinä Melkas, Helsinki University of Technology, Lahti Center, Saimaankatu 11, FI-15140 Lahti, Finland. E-mail: helina.melkas@tkk.fi. Introduction According to the resource-based view, an actor’s performance depends on its resources and capa- bilities (see e.g., Wernerfelt 1984). Valuable, rare, inimitable and non-substitutable resource configu- rations lay the basis for the competitiveness of an actor. This leads to strong path-dependency. The world is in continuous change, and the actors en- counter the risk that the old resource-base be- comes uncompetitive, which again leads to a de- clining performance. Therefore, the resource con- figurations need to be continuously renewed. The framework of dynamic capabilities (see Teece et al. 1997) offers a good basis to assess the capabilities needed in the transformation processes of an actor. An actor’s dynamic capabilities can be defined as the actor’s processes that use resources – specially the processes that integrate, reconfigure, gain and release resources – to match and even create mar- ket change. Dynamic capabilities are thus the or- ganisational and strategic routines by which actors achieve new resource configurations as markets emerge, collide, split, evolve and die (Eisenhardt & Martin 2000). Actually, it is basically a question of an actor’s capability to innovate, since “the pro- duction and use of knowledge is at the core of value-added activities, and innovation is at the core of firms’ and nations’ strategies for growth” (Archibugi & Michie 1995). Innovative capability can be defined as actor’s ability to exploit and re- new existing resource configurations in order to create sustainable competitive advantage by inno- vation activities (Harmaakorpi 2004). The success of economic actors is strongly re- lated to their adaptability to the emerging techno- economic environment. Decisions have to be made in a great insecurity. The insecurity can be reduced by the creation of future-oriented knowl- edge. Future-oriented knowledge is often very challenging to use in an actor’s renewal process, since i) the possible futures are hard to outline, ii) future-oriented knowledge is even more abstract than tacit knowledge and iii) due to its nature, fu- 50 FENNIA 184: 1 (2006)Tuomo Uotila, Vesa Harmaakorpi and Helinä Melkas ture-oriented knowledge is hard to adopt in an ac- tor’s organisational and strategic routines. To make use of future-oriented knowledge, economic ac- tors need a special dynamic capability: visionary capability. In this context, visionary capability re- fers to an actor’s ability to outline the potential de- velopment directions based on paths travelled − utilising the opportunities emerging from the changing techno-economic paradigm. In this present study, we aim to clarify, following Zahra and George (2002), the role of absorptive capacity as an important dynamic capability for an actor's success. Absorptive capacity includes features of both visionary and innovation capabilities. In or- der to use and absorb knowledge, an actor needs to be able both to explore future-oriented knowl- edge and exploit it in practical innovation proc- esses. Thus, this present article takes a resource-based viewpoint of departure. As a change to the earlier research focusing on the internal resources, there is an increasing interest on the external resources and capabilities available to the actor through net- works (Zaheer & Bell 2005). Accordingly, and fol- lowing the teachings of non-linear multi-actor in- novation processes, economic actors are not seen as isolated islands, but entities being parts of re- gional and interregional innovating networks. Therefore, the competitiveness securing resource configurations have to be considered at the level of innovation networks, individual actors being embedded in these networks. Absorptive capacity of future-oriented knowledge as a dynamic capa- bility is seen as a crucial competitiveness factor of the individual actors and innovation networks. This article attempts to outline the principles and practical means for how absorptive capacity con- cerning future-oriented knowledge could be en- hanced in the multi-actor innovation networks. Measures taken in the Lahti region, Finland, are used as a case study. Futures research in regional contexts The future is a central challenge in developing competitive advantage based on technology and knowledge. According to the results in a report for the Futures Committee of the Finnish Parliament, one of the main factors behind the ability to inno- vate is the ability to foresee technology develop- ment. Technology foresight has received growing attention among those involved in the shaping and implementation of science and technology (S&T) policies (Salmenkaita & Salo 2004). Earlier, more focus was laid on an approach that stressed out- side objectivism during the foresight process, but nowadays those who will utilise or produce emerg- ing technologies are also more involved in the technology foresight process in order to influence the shaping of those technologies (Eerola & Väy- rynen 2002). Despite this development, a com- mon finding in several recent studies has been that the foresight activities at national, regional and in- stitutional levels ought to be better coordinated and that foresight activities at each level should be further strengthened. Besides the methodological competence, the importance of a problem-based approach is stressed (Eerola & Väyrynen 2002). When discussing technology foresight at the re- gional level, an important basic problem is that when the process is not rooted deeply enough in already existing structures and competences, or more generally, existing resource configurations of a region, there is a danger that the results are not absorbed into the regional strategy making and de- velopment processes. This problematic phenome- non can be called “the black hole of regional strat- egy making”. The birth of a black hole can be avoided by developing both the technological competencies and co-operative abilities of the po- tential users of new technology (companies and/or other organisations) and paying enough attention to communicating and managing the foresight process (Sotarauta et al. 2002). Thus, technology foresight processes cannot be treated separately from regional learning processes (Ronde 2003; Gertler & Wolfe 2004; List & Metcalfe 2004). Ger- tler and Wolfe (2004) even see learning dynamics as being fundamental to the ability of regional economies to achieve and sustain knowledge- based dynamism over the long run. They regard regional foresight processes to be, at their most fundamental level, socially organised learning processes involving learning by individuals, firms and institutions. The key question for policymakers at the region- al and local level is thus how to provide the right conditions for generating growth of more knowl- edge-intensive forms of economic activity within the context of dynamic innovation systems or learning regions. The concepts of path dependency and lock-in imply that the technological develop- ment directions of specific regions and localities are historically determined by the research and in- novation capabilities developed by individuals FENNIA 184: 1 (2006) 51A method for assessing absorptive capacity of a regional … and organisations over time (Gertler & Wolfe 2004). According to Ronde (2003), the develop- ment of a certain technological course is the out- come of the cumulative nature of learning proc- esses, and hence, the generation of new knowl- edge builds upon what has been learned in the past. Regional multi-actor innovation processes Analysts in the field of innovation systems have abandoned simplistic models of how innovation and innovation processes work. It is increasingly recognized that the dynamics of innovation sys- tems are complex and difficult to understand and that scientific and technological communities, not to mention the “users” of their products, face a number of challenges, both now and in the future (Kuhlman et al. 1999). Characterising innovation as a socially and economically embedded process raises the question of the socio-institutional envi- ronment, where the innovation processes are tak- ing place. In a regional context, innovation is seen as a process embedded in a regional innovation system (RIS) (see e.g., Cooke et al. 1997; Storper 1997; Braczyk et al. 1998; de la Mothe & Paquet 1998; Doloreux 2002). According to Autio, a RIS is composed of two subsystems: a knowledge generation and diffusion subsystem and a knowledge application and ex- ploitation subsystem (see Fig. 1). The former con- sists of four main types of institutions, and all of them participate in the production and dissemina- tion of both codified and tacit (technological) knowledge and (technical) skills. Key elements in- clude public research institutions, technology me- diating organizations, educational institutions and workforce mediating organizations. The knowl- edge application and exploitation subsystem, again, consists of four C’s: companies, clients, contractors and competitors. Ideally, there should be horizontal and vertical linkages among the firms. Also dialogue and interactions between sub- systems and actors within subsystems are a neces- sary prerequisite for RIS to operate sufficiently (Au- tio 1998; Tödtling & Trippl 2005). Fig. 1. Main structure of regional innovation systems (RIS) (Autio 1998; Tödtling & Trippl 2005). 52 FENNIA 184: 1 (2006)Tuomo Uotila, Vesa Harmaakorpi and Helinä Melkas Regional innovation system consists thus of in- novative networks with different kinds of social relationships. Social structure, especially in the form of social networks, affects economical out- comes, since the networks affect the flow and the quality of the information (Granovetter 2005). Granovetter (1973) defines the concepts of strong ties and weak ties in social networks. The strength of a tie is a combination of the amount of time, the emotional intensity, the intimacy and the recipro- cal services which characterize the tie (Granovet- ter 1973). Strong ties are characterized by com- mon norms and high network density. These strong ties are easier for innovation, since they include normally a relatively high amount of trust, com- mon aims and the same kind of language to com- municate. However, weak ties are reported be more fruitful for innovations, because more novel information flows to the individuals through weak ties than through strong ties (Granovetter 2005). People in the same strong networks tend to share the same knowledge basis preventing the Schum- peterian knowledge-combining innovation proc- esses to emerge (see Schumpeter 1942). Burt (2004) has developed the “strength of weak ties” argument further by arguing that innovations are most likely to be found in the structural holes be- tween the dense network structures (see also Burt 1992; Walker et al. 1997; Zaheer & Bell 2005). An actor able to span across the structural holes in a social structure is at a higher “risk” of having good ideas: new ideas emerge from selection and syn- thesis across the structural holes between groups (Burt 2004). A regional innovation system rich in structural holes offers a lot of opportunities for new networked innovation processes. The weak links or structural holes enabling the biggest innovation potential are somewhat prob- lematic for innovation processes. In order to be able to utilise the innovation potential in these structural holes, information should often be trans- ferred between very research-oriented and prac- tise-oriented partners – as well as partners of to- tally different horizontal knowledge interest (inter- disciplinarity). The potential innovating partners in different sub-systems might not be able even to be- gin the processes, as the common rules for com- munication are lacking. Even in the same techno- logical field, the language in basic research is so different from practice-based innovation processes that an innovation process could end before it has started, even if the innovation potential in the structural hole is obvious. The situation is the same between different technological disciplines. The situation is most complicated when there is a de- sire to span the structural hole between a partner with research-oriented knowledge interest in one technological field and a partner with practice-ori- ented knowledge interest in another technological field. A remarkable part of difficulties between the potential innovating partners stems from the infor- mation asymmetry on the different sides of a struc- tural hole (see e.g., Montgomery 1991). The part- ners on the opposite sides of the structural hole have information of different quality and achieved for their own purposes. The difference is often so big that a special interpretation function is needed. Burt writes about this special function as informa- tion brokerage in the structural hole. A structural hole is an opportunity to broker the flow of infor- mation between people and control the form of co-operation that brings together people from op- posite sides of the hole (Burt 1997). Absorptive capacity in multi-actor innovation networks Absorptive capacity was originally defined by Co- hen and Levinthal (1990) as an organisation’s abil- ity to value, assimilate and apply new knowledge. Kim (1998) argues that absorptive capacity re- quires learning capability and develops problem- solving skills; learning capability, again, is the ca- pacity to assimilate the knowledge for imitation and problem-solving skills to create new knowl- edge for innovation. Moreover, Zahra and George (2002) define two different types of absorptive ca- pacity giving good point of departure for this study: potential absorptive capacity that is important in acquiring and assimilating external knowledge, whereas realized absorptive capacity refers to the functions of transformation and exploitation of the knowledge collected. Both are, naturally, impor- tant in regional innovation processes: potential ab- sorptive capacity enables the exploration of knowl- edge (often) over the weak ties of the innovation system, and realized absorptive capacity secures the exploitation (often) in the strong ties of the net- works. Absorptive capacity is crucial when pon- dering questions about future-oriented knowledge adaptation in regional innovation networks; higher absorptive capacity enables the easier crossing of structural holes in the innovation system. FENNIA 184: 1 (2006) 53A method for assessing absorptive capacity of a regional … To understand better the characteristics of ab- sorptive capacity as a dynamic capability we have to take a closer look at its different parts: acquisi- tion, assimilation, transformation and exploitation. Acquisition refers to an actor’s capability to iden- tify and acquire externally generated knowledge that is critical to its operations. Assimilation refers to the actor’s routines and processes that allow it to analyse, process, interpret and understand the in- formation obtained from external sources. Trans- formation denotes an actor’s capability to develop and refine the routines that facilitate combining existing knowledge and the newly acquired and assimilated knowledge. Exploitation as a capabili- ty is based on the routines that allow actors to re- fine, extend and leverage existing competencies or to create new ones by incorporating acquired and transformed knowledge to their operations (Zahra & George 2002). According to these definitions, absorptive capacity is like a funnel, where poten- tial absorptive capacity (visionary capability) se- cures the newness and diversity of the knowledge needed, whereas realised absorptive capacity (in- novative capability) stands for operationalization of the new knowledge in the existing processes in order to make the actual innovation processes to take place. However, the difference between potential (PACAP) and realised (RACAP) absorptive capacity is blurry. According to Zahra and George (2000), PACAP could theoretically be equal with RACAP, but in most cases PACAP is larger than RACAP. Za- hra and George (2002) also suggest that there is a special need for a social interaction mechanism between assimilation and transformation process- es. In the following case study, we focus on these phases of the absorptive capacity in regional in- novation networks. Assessment includes both po- tential and realised absorptive capacity; however, exploitation is left for further research. The key question in the case study is: how could acquisi- tion, assimilation and transformation processes (absorptive capacity) be aided in regional innova- tion networks? The research focus is depicted in Fig. 2. The case study thus aims to outline the princi- ples and practical means for how absorptive ca- pacity concerning future-oriented knowledge could be enhanced in multi-actor innovation net- works by looking into measures taken in the Lahti region, Finland. Our underlying hypothesis is that absorptive capacity is crucial when pondering questions about future-oriented knowledge adap- tation in regional innovation networks; with suc- cessful operationalization of new knowledge in the existing processes, actual innovation processes are aided. The method to address this is to take a closer look at the different parts of absorptive ca- pacity within the case study environment – and by doing this, a “test” of the validity of our theoretical considerations is also undertaken. The case study: a resource-based foresight process in the Lahti region innovation system The Lahti region has set a goal to be the leading area in practice-based innovation activities in Fin- land, and the framework of network-facilitating in- novation policy has been adopted in the region in order to promote innovation activities. The Lahti region’s future competitiveness is seen to be great- ly dependent on its ability to promote practice- based innovations, due to the absence of a whole university and very low research inputs in the re- gion. The yearly research input in 2004 in the Lah- ti region was only 255 euros per capita compared to 1800 euros in the Helsinki region and 2530 eu- ros in the Tampere region. This tells something of the knowledge-intensity of the region. However, Acquisition Assimilation Transformation Exploitation Social integration mechanisms Knowledge management Collective creativity tools Future-oriented knowledge Potential absorptive capacity Realised absorptive capacity Fig. 2. Absorptive capacity of future-oriented knowledge in innovation processes (fol- lowing Zahra & George 2002). 54 FENNIA 184: 1 (2006)Tuomo Uotila, Vesa Harmaakorpi and Helinä Melkas the Lahti region has a favourable logistic setting: it lies only 100 km from two remarkable research centres, Helsinki and Tampere, enabling the rela- tively easy transfer of scientific knowledge to the practice-based innovation processes. The situation in the Lahti region has forced it to develop new tools to trigger innovation processes. One aim of the network-facilitating innovation policy is to search for structural holes between the regional knowledge-base and the future-oriented knowledge-base found in the surrounding research centres; that is, to absorb the surrounding future- oriented knowledge to the regional innovation sys- tem. Therefore, as part of the regional innovation policy, a resource-based technology foresight process was carried out in 2005 (the results of which will be reported on later, in other articles). In general, the existing resource configurations in a region set the basis for future development, and, therefore, regional foresight processes have to be tightly connected with an audit of the region’s re- source base (Harmaakorpi & Uotila 2006). Bear- ing this in mind, the technology foresight process was planned to be carried out in three phases: • Phase 1: Defining the regional development platforms and clusters to be assessed and identifying the related technologies • Phase 2: Exploring the future opportunities for the clusters and technologies using the Delphi process • Phase 3: Organising future-oriented innova- tion sessions in order to disseminate the re- sults of the Delphi process within the clus- ters In the Lahti region, the cluster-based develop- ment strategy was adopted during 2004–2005. Strong current clusters in the region are mechatron- ics, environmental, grain, wood, furniture and plastics clusters. The development resources dur- ing the coming years will mainly be allocated to the development of these clusters, and especially the environmental cluster. The aim of our regional technology foresight was to create an open, ex- ploratory foresight process, the limits of which are drawn on the basis of the regional cluster strategy. The focus was on mechatronics, environmental and plastics clusters. The actual process is depict- ed in Fig. 3. Fig. 3. Technology foresight process in the Lahti region (Ahlqvist et al., forthcoming). More detailed results of that research process will be reported on later in other articles by Ahlqvist, Uotila, Harmaakorpi & Melkas. FENNIA 184: 1 (2006) 55A method for assessing absorptive capacity of a regional … The idea of the regional technology foresight process in this case was to identify and evaluate technology signals related to nano-, bio- and ICT technologies that may have significance for the three clusters focused on in this foresight process. The definition of technology signal is analogical to that of weak signal (see e.g., Vapaavuori & von Bruun 2003; Mannermaa 2004), but implicating that the content of the signal is related to technol- ogy (hence the name technology signal). Potential technology signals were identified from several sources, out of which The MIT Technology Review was the most important. Around 200 potential sig- nals were ”muddled through”, grouped and pre- evaluated. Finally around 30 signals were selected to the Delphi process, one selection criteria being the potential link to the cluster strategy in the Lah- ti region. After the selection, the signals were writ- ten in the form of “technology theses” (for exam- ple, as follows: “Silicon-based nanosensors that detect atomic motion. Silicon-based nanosensors can be utilized as highly precise measurement de- vices, for example in measuring the smoothness of a surface.”). The purpose of this reformulation was to indicate the possible use of a certain technology signal so that the experts could more easily evalu- ate the potentiality and application areas of that technology signal. Delphi relies on the “informed intuitive opin- ions of specialists” (Helmer 1983). This collective judgement of experts, although made up of sub- jective opinions, is considered to be more reliable than individual statements – and thus more objec- tive in its outcomes (Johnson & King 1988; Masini 1993). One of the most challenging phases of the Delphi process is building up the expert panel (see Kuusi 1999; European Commission 2002). It is of critical importance that the panel members really are experts in the subject areas. In this re- search, the panel was build up by muddling through web-pages of those organizations − main- ly universities or other research organizations − that are doing research in the area of the selected technology signals and by choosing the potential respondents from those pages. The composition of this panel is thus very research and science ori- ented. All in all 300 potential respondents were selected to participate in the panel, from Finland and abroad. This kind of a procedure serves also the purpose of mobilizing expertise from outside of the region into the regional foresight process, which is of vital importance, since outside exper- tise is important in breaking possible mental lock- ins existing in a region (Harmaakorpi & Uotila 2006). The first round of the Delphi process was car- ried out in April 2005, and the second round in July–August 2005. The main purpose of the first round was to collect expert opinions concerning the issue of which of the technology signals are so-called emerging technologies. The second round was somewhat more focused, and it con- centrated on five technology signals, which were found to be the most promising during the first round. The main idea was to deepen the under- standing of those product, process or business in- novations that could utilize the technology signals focused on. Altogether 63 experts responded to the first round and 49 to the second round ques- tionnaire. Using Delphi in this context is, however, not enough. The results of the Delphi process must be again rooted back into the clusters to support prac- tical innovation processes in companies. This is done in part three of the foresight process. The op- portunities emerging from the Delphi assessment should take a practical form in regional develop- ment activities. It is also important to form creative social capital to exploit the resource configura- tions effectively (Tura & Harmaakorpi 2005). This can be done by organising future-oriented themat- ic innovation sessions. The aim is to organize alto- gether 60 sessions in the Lahti region during the period 2005–2006, out of which 40 sessions have already been held. Thus, in the future-oriented in- novation sessions, the aim is to assimilate and transform the foresight information gained during the Delphi process to future-oriented innovation knowledge to be exploited by companies (see Fig. 4). This task is not easy to fulfil. It has often been seen how difficult it is to reach a fruitful dialogue between the participants of the innovation ses- sions, since the knowledge interests are too far from each other, which threatens the spanning of the structural hole. The innovation potential is clear, but the innovation processes are inadequate due to the lack of communication. Normally, we conceptualise three archetypes of participants in an innovation session: (i) future-ori- ented knowledge producers, (ii) practical knowl- edge exploiters (usually representing a company, but sometimes also its customers/suppliers) and (iii) intermediators. Reaching a common under- standing of the problem by the efforts of knowl- edge producers and knowledge exploiters has proven to be problematic in many cases. The rela- 56 FENNIA 184: 1 (2006)Tuomo Uotila, Vesa Harmaakorpi and Helinä Melkas tionship between future-oriented nanotechnology knowledge and practical innovation processes in the plastics industry can be given as an example of that. The innovation potential is clear, but the in- novation processes are inadequate due to the lack- ing ways of communication. The adoption of fu- ture-oriented knowledge in the practical innova- tion processes is difficult but crucial in this kind of an environment. The role of information brokers has proven to be essential in making the participants innovate. The task of these intermediators is very challenging, since they need to understand the processed sub- stance knowledge, as well as have the social abili- ties to work in very diverse groups. To secure a successful innovation session, intermediators need to be able to set questions and deliberative argu- ments that, for example, enable (i) the people on both sides of the structural hole to become aware of the interests and difficulties of the other group, (ii) transferring the best practices between the groups, (iii) drawing analogies between groups os- tensibly irrelevant to one another, and (iv) making a synthesis of the knowledge interests (Burt 2004). In order to do this, each session must be prepared very carefully. Although the session usually lasts for one day, the preparation time can last for up to two months or even longer. During that time, the intermediators try to learn as much as possible about business logics in the industry the company is operating in, about technology used, current knowledge base of the company and also knowl- edge needs for the future, etc. The brokers need new methodology in order to succeed in their challenging task. The experiences gained in innovation sessions show that the famil- iar brain-storming methods, for example, do not suit very well to such sessions. The knowledge in- terests of the innovating partners often remain too distant to enable an active multi-actor innovation network to emerge. After many experiments, it be- came clear that the right questions set in the group work in the innovation sessions could open up the way for successful innovation processes. This de- velopment course led us to find the interrogative model of inquiry, i.e., a general method to gener- ate knowledge and skills by question-answer-proc- esses (see Sintonen 2006) as a possible methodo- logical approach to use in the networked innova- tion processes that aim at spanning the structural holes (see Harmaakorpi & Mutanen, forthcoming). The model being developed in the field of theo- retical philosophy poses a fascinating intellectual challenge − to apply the model in the context of innovation systems. Conclusions The present article took a resource-based view of regional development. The resource-based view emphasizes the renewal of existing resource con- figurations by dynamic capabilities. Two important dynamic capabilities in promoting regional inno- vation systems were defined: visionary capability and innovative capability. Visionary capability re- fers to the regional innovation systems’ ability to explore diverse future-oriented knowledge, and innovative capability to the systems’ ability to use the knowledge in the actual networked multi-actor innovation processes. The main question in this research is: how can these capabilities be promoted in a regional inno- Fig. 4. Absorptive capacity in the context of a regional in- novation system. FENNIA 184: 1 (2006) 57A method for assessing absorptive capacity of a regional … vation system? The question was assessed with the concept of absorptive capacity. Absorptive capac- ity was defined to be a dynamic capability includ- ing two elements: potential absorptive capacity and realized absorptive capacity. Potential absorp- tive capacity is strongly related to visionary capa- bility, and realized absorptive capacity to innova- tive capability. The article reported on the approach used in the Lahti region in Finland. Experiences gained from a regional technology foresight process to identify and evaluate technology signals related to nano-, bio- and ICT technologies were introduced. The article also sheds light on the so-called innovation sessions that are used to root future-oriented infor- mation and knowledge back into the region. In- novation sessions methodologies are under devel- opment, as described in the article. This article concentrated on a thorough descrip- tion of the background and probably raises more questions than it answers, as the research is in progress. In further research, important issues to be taken into account are, at least: • The re-rooting of the results of the foresight process described in the article was charac- terized by the inclusion of SMEs with limited resources for (futures) research, in mostly tra- ditional and usually less research intensive industries, in a region without major research organizations supporting SMEs. This is one case, interesting and challenging, but not enough for “universal” conclusions. • How could absorptive capacity be measured in innovation networks? In the Lahti region, the direction is towards us- ing the interrogative model of inquiry in regional innovation promotion activities. Although applica- tion of the model is still in its embryonic phase, it has proven to have potential for further develop- ment. The first experiences emphasize heavily the role of intermediate organizations – information brokers – in a successful questioning process. So far, the actors in these organizations seem to lack the qualifications needed to process questions and deliberative arguments in the inquiry process (see Harmaakorpi & Mutanen, forthcoming). Therefore, the next steps in making the interrogative model of inquiry really work in the innovation processes in the region are (i) to develop the model to better suit to the practical work by trying different kinds of inquiry scenarios in the innovation sessions and (ii) to educate the actors in the intermediate or- ganizations to use the interrogative model of in- quiry in the information brokerage of the innova- tion sessions. ACKNOWLEDGEMENTS The authors wish to thank the two anonymous refe- rees for their valuable comments. REFERENCES Ahlqvist T, T Uotila & V Harmaakorpi (forthcoming). Teknologiasignaalit, alueellinen teknologiaenna- kointi ja Päijät-Hämeen klusteristrategia (Technol- ogy signals, regional technology foresight and cluster strategy in the region of Päijät-Häme, Fin- land). Unpublished manuscript. Archibugi D & J Michie (1995). Technology and in- novation: an introduction. Cambridge Journal of Economics 19: 1–4. Autio E (1998). Evaluation of RTD in regional systems of innovation. European Planning Studies 6: 2, 131–140. Braczyk H-J, P Cooke & M Heidenreich (eds.) (1998). Regional innovation systems. 499 p. Routledge, London. Burt RS (1992). Structural holes: the social structure of competition. 313 p. Harvard University Press, Boston. Burt RS (1997). The contingent value of social capital. Administrative Science Quarterly 42, 339–365. Burt RS (2004). Structural holes and good ideas. American Journal of Sociology 110: 2, 349–399. Cohen W & L Levinthal (1990). Absorptive capacity: a new perspective on learning and innovation. Administrative Science Quarterly 35, 128–152. Cooke P, M Uranga & G Etxebarria (1997). Regional innovation systems: institutional and organisa- tional dimensions. Research Policy 26, 475–491. Doloreux D (2002). What should we know about re- gional systems of innovation. Technology in Soci- ety 24, 243–263. Eerola A & E Väyrynen (2002). Teknologian ennakoin- ti- ja arviointikäytäntöjen kehittäminen eurooppa- laisen kokemuksen pohjalta (Developing technol-(Developing technol- ogy foresight and technology assessment proce- dures based on European experience). VTT tiedot- teita – Research Notes 2174. 151 p. Eisenhardt KM & JA Martin (2000). Dynamic capa- bilities: what are they? Strategic Management Journal 21: 1105–1121. European Commission (2002). Practical guide to re- gional foresight in the United Kingdom. 196 p. Of- fice for Official Publications of the European Communities, Luxembourg. Gertler M & D Wolfe (2004). Local social knowledge management: community actors, institutions and 58 FENNIA 184: 1 (2006)Tuomo Uotila, Vesa Harmaakorpi and Helinä Melkas multilevel governance in regional foresight exer- cises. Futures 36, 45–65. Granovetter M (1973). The strength of weak ties. American Journal of Sociology 78, 1360–1380. Granovetter M (2005). The impact of social structure on economic outcomes. Journal of Economic Per- spectives 19: 1, 33–50. Harmaakorpi V (2004). Building a competitive re- gional innovation environment – the regional de- velopment platform method as a tool for regional innovation policy. Helsinki University of Technol- ogy Lahti Center, Doctoral dissertation series 2004/1. 235 p. Harmaakorpi V & A Mutanen (forthcoming). Knowl-forthcoming). Knowl-). Knowl-Knowl- edge production in networked practice -based in- novation processes – interrogative model as a methodological approach. Article submitted to Journal of Applied Philosophy. Harmaakorpi V & T Uotila (2006). Building regional visionary capability. Futures research in resource- based regional development. Technological Fore- casting & Social Change 73, 778–792. Helmer O (1983). Looking forward. A guide to futures research. 376 p. Sage, Beverly Hills. Johnson D & M King (1988). Basic forecasting tech- niques. 144 p. Butterworths, London. Kim L (1998). Crisis construction and organisational learning: capability building in catching-up at Huyndai Motor. Organization Science 9, 506– 521. Kuhlman S, P Boekholt, L Georghiou, K Guy, J-A Héraud , P Laredo, T Lemola, D Loveridge, T Lu- ukkonen, W Polt, A Rip, L Sanz-Menendez & R Smits (1999). Improving distributed intelligence in complex innovation systems. Final report of the advanced science & technology policy planning network (ASTPP). A thematic network of the Euro- pean targeted socio-economic research pro- gramme (TSER). 89 p. Office for Official Publica- tions of the European Communities, Brussels. Kuusi O (1999). Expertise in the future use of generic technologies. Valtion taloudellinen tutkimuskes- kus, tutkimuksia 59. 268 p. List D & M Metcalfe (2004). Sourcing forecast knowl- edge through argumentative inquiry. Technologi- cal Forecasting and Social Change 71, 525–535. Mannermaa M (2004). Heikoista signaaleista vahva tulevaisuus. 249 p. WSOY, Helsinki. Masini E (1993). Why futures studies? 144 p. Grey Seal, London. Montgomery J (1991). Social networks and labor market outcomes: toward an economic analysis. American Economic Review 81, 1408–1418. de la Mothe J & G Paquet (eds.) (1998). Local and re- gional systems of innovation. 341 p. Kluwer Aca- demic Publishers, Boston. Ronde P (2003). Delphi analysis of national specifici- ties in selected innovative areas in Germany and France. Technological Forecasting and Social Change 70, 419–448. Salmenkaita J-P & A Salo (2004). Emergent foresight processes: industrial activities in wireless commu- nications. Technological Forecasting & Social Change 71, 897–912. Schumpeter JA (1942). The theory of economic de- velopment. 255 p. Oxford University Press, Lon- don. Sintonen M (2006). From the logic of questions to the logic of inquiry. In Auxier RE & LE Hahn (eds.). The philosophy of Jaakko Hintikka. The Library of Living Philosophers 30, 825–850. Sotarauta M, M Kautonen & T Lähteenmäki (2002). Tulevaisuustiedosta kilpailuetua: teknologian en- nakointikonsepti Pirkanmaalla. SENTE-julkaisuja 14/2002. 82 p. Storper M (1997). The regional world: territorial de- velopment in a global economy. 338 p. The Guil- ford Press, New York. Teece DJ, G Pisano & A Shuen (1997). Dynamic ca- pabilities and strategic management. Strategic Management Journal 18: 7, 509–533. Tödtling F & M Trippl (2005). One size fits all? To- wards a differentiated regional innovation policy approach. Research Policy 34, 1203–1219. Tura T & V Harmaakorpi (2005). Social capital in building regional innovative capability. Theoreti- cal and conceptual assessment. Regional Studies 39: 8, 1111–1125. Walker G, B Kogut & W Shan (1997). Social capital, structural holes and formation of an industry net- work. Organization Science 8: 2, 109–125. Vapaavuori M & S von Bruun (eds.) (2003). Miten tut-(2003). Miten tut- kimme tulevaisuutta? 2nd ed. Acta Futura Fennica 5. 328 p. Wernerfelt B (1984). A resource-based view of the firm. Strategic Management Journal 5: 2, 171– 180. Zaheer A & GG Bell (2005). Benefiting from network position: firm capabilities, structural holes, and performance. Strategic Management Journal 26, 809–825. Zahra SA & G George (2000). Absorptive capacity: a review and reconceptualization. Academy of Management Proceedings 2000. Zahra AZ & G George (2002). Absorptive capacity: a review, reconceptualization and extension. Acad- emy of Management Review 27: 2, 185–203.