IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 2 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 CRITICAL FACTORS IMPORTANT FOR EFFECTIVE INDUSTRY- INSTITUTE INTERACTIONS (III): AN INDIAN PERSPECTIVE Sanjay Kumar International Institute of Technology and Management Murthal, India skbhardwaj19711971@gmail.com Sunil Luthra Lecturer, Department of Mechanical Engineering Government Polytechnic, Jhajjar- 124104, Haryana, India sunilluthra1977@gmail.com Abid Haleem Professor, Department of Mechanical Engineering, Faculty of Engineering and Technology, Jamia Millia Islamia, Delhi-110016, Delhi, India haleem.abid@gmail.com ABSTRACT The management of Industry-Institute Interactions (III) has been found to be an important aspect in today’s market. In this paper an attempt has been made to identify Critical Factors (CFs) and rank these for effective III from an Indian perspective. The present paper is based on two research stages. Initially, an extensive literature review was conducted to identify CFs of III. Forty three CFs for effective III were identified and categorized into nine dimensions based on input from experts. In the second stage, the Analytical Hierarchy Process (AHP) was utilized to rank these dimensions and CFs for effective III from an Indian perspective. Paired comparisons in AHP were based on the opinions of experts (selected from academia and industry). The proposed decision framework may offer some valuable guidelines for policy makers to develop their plan of action in terms of design of short and long term policies and strategies to promote effective III in India. A sensitivity analysis was also performed to investigate the robustness and priority ranking stability of CFs in the proposed framework. This paper may help India to achieve and manage effective III leading to potential economic, social, political, cultural and environmental advantages. Keywords: Critical factors (CFs), Indian perspective, Industry-Institute Interactions (III), Analytical Hierarchy Process (AHP), research and development (R & D), sensitivity analysis 1. Introduction A limited number of organizations benefit directly from universities/institutions (as a source of information/knowledge) for their innovative activities and/or the development of innovative products and processes through appropriately managing research and mailto:skbhardwaj19711971@gmail.com mailto:sunilluthra1977@gmail.com mailto:haleem.abid@gmail.com IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 3 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 development projects (Laursen & Salter, 2004). In fact, organizations may acquire knowledge and technology from many external sources and these sources may include competing organizations, research organizations, government laboratories, industry- institute research associations and universities (Santoro & Chakrabarti, 2002). Industrial organizations use a variety of relationships with university/institute research centers to accomplish various knowledge and innovation based targets and goals. Large organizations have more intense knowledge transfer capabilities and research support relationships (to strengthen skills and knowledge) for gaining access to university/institute facilities to advance technologies (Santoro & Chakrabarti, 2002).This may be for the simple reason that they have a large amount of funds available/allocated for this. Industry–university/institute alliances may represent an evolving trend for advancing knowledge and new technologies supporting the idea of establishing effective and efficient Industry-Institute Interactions (Chakrabarti & Lester, 2002). The journey of interactions and cooperation among industry and institutes has taken different forms which include problem solving, curriculum development, study/industrial visits, scholarships, and apprenticeship training and incubation centers. However, industry has not been involved in taking sustainable financial, technical and operational risks in the design, financing and building and operation of educational projects (Majumdar, 2008). Institute-industry collaborations have been encouraged in many countries by policy-makers, and institutes may play a key role as the economic/technical/knowledge/ innovations facilitator to create an altogether new mechanism for economic development (Bozeman, 2000; Etzkowitz & Leydesdorff, 2000). 1.1 Innovation and knowledge management Innovation may be visualized as the successful creation, development, implementation and use of knowledge for new or structurally improved products, processes, services and/or organizational forms (Greenhalgh et al., 2006). On the other hand, knowledge management has been one of the hottest topics over the past few decades in both the industry and information research worlds (more specifically in universities/institutes), but there is no universal definition of this term, just as there has not been consensus about what constitutes knowledge in the first place (Alrawi & Alrawi 2011). Innovation and knowledge management may play an effective role in motivating, encouraging and channeling Industry-Institute Interactions to gain value for customers, organizations, supply chains, and society (Chen & Huang, 2007). 1.2 Problem areas in Industry-Institute Interactions in India In India, Industry-Institute Interactions are not noticeably observable, and therefore it is necessary to have better (in terms of quality and quantity) interactions among institutions and industry. These interactions and collaborations should have a greater impact and influence on course frame work, curriculum development, student exposure to the industrial atmosphere in the form of industrial visits, research associations, and subsequent placement of young graduates/post graduates/doctorates in industries across the country. With the advent of globalization and the opening up of the Indian economy, competition among industries has become significantly stiff. India’s vast network of academic infrastructure churns out over 2 million graduates annually. However, there are growing concerns about parts of the existing available talent pool being unsuitable for employment due to a skill gap between graduate’s skill level and requirements of IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 4 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 industry (National Knowledge Commission, 2008). It has become apparent that there is an urgent need to prepare engineering/professional students so that they are skilled and employable in multinational organizations by exposing them to newer technologies and making them aware of various engineering/professional/management methodologies. This may only be achieved well by bridging the gap between industry and the academic institutes (Wallin et al., 2014). In India, several problem areas exist in attaining effective Industry-Institute Interactions and collaborations among industries and institutes and experts from academia and industry (Kulkarni et al., 2011).These include lack of vision, lack of appropriate policy planning and implementation, a more theoretical approach to business, management, technical/engineering and professional education, outdated syllabi and less frequent syllabi modification, lack of regular interaction and vital contribution of industry experts in the design of syllabi to match recent industry requirements, lack of industrial exposure of faculty, insufficient inclusion of professionals from industry in research programs, lack of invitations to engineers, executives and experts from industry to deliver lectures in institutes (which may go a long way to ensure and establish linkages between academia and industry), limited use of practical methodologies (like role playing, brainstorming, Delphi, case studies etc.), copying irrelevant western business practices without consideration of the Indian mind set and culture, inhibitions and reservations, a total divide between industry and educational institutes, and insufficient funding. The above problems need to be appropriately addressed, however to do this an open, conducive environment needs to be provided to the many individuals in academic institutions that have bright and innovative ideas that may be useful for industries (Vest, 2005). In our study, we have considered universities (government and private); colleges (government and private) - offering engineering, business administration and economics, commerce, arts, and other technical and professional courses; schools (government and private); and other research organizations. We have used a single word, “Institute”, for all of these throughout the rest of this paper. A brief summary of the organizations involved in research, directly or indirectly, in India has been given in Appendix I. 1.3 Need and objectives of the research Today, there continue to be relevant compelling reasons for industrial organizations and institutes to work together, which include access to highly trained students, facilities and faculty as well as an enhanced image when collaborating with a prominent academic institution (Fombrun, 1996). Close interaction between the institute and industry/enterprise is seen as the platform for showcasing best practices, latest technological advancements and their implementation, and impact on the industry (Majumdar, 2008). The problem areas discussed gave direction to the present research. The objectives of the research are:  To identify Critical Factors (CFs) important for effective Industry- Institute Interactions from an Indian perspective;  To prioritize the importance of identified CFs for effective Industry- Institute Interactions to develop a decision framework;  To check the sensitivity of the obtained priority results of the identified CFs. A literature review was performed to identify relevant Critical Factors for effective Industry- Institute Interactions. A literature review is an integral part of any research to IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 5 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 identify the conceptual content of the field, and gives guidance towards theory development (Luthra et al., 2014). In the present research, we propose to use an AHP approach for prioritizing the importance of various CFs for effective III in India. The AHP is a multi-criterion decision making (MCDM) approach which was developed by Thomas L. Saaty in 1980. It assists in the decomposition, organization and analysis of a complex problem, and its conversion into a multi-level hierarchical structure comprised of an objective function, criteria and sub-criteria (Saaty, 1980; Luthra et al., 2015). The results may be used to compare and rank the alternatives and, hence, assist the decision maker in making a choice (Saaty, 2008; Kumar et al., 2009). 2. Literature review The university may play an increasingly important role in the innovation of knowledge- based societies as explained in the triple helix theory (Etzkowitz & Leydesdorff, 2000).This triple-helix model of university-industry-government interactions and its contribution to entrepreneurship, and economic and social development has been outlined in Etzkowitz (2011). Different possible resolutions of the relations and interactions among these three spheres may help to generate alternative strategies for economic growth, social transformation and sustainable development (Etzkowitz and Leydesdorff, 2000). The evolution of innovation systems and research and probable solutions for effective university–industry interactions and relations may be reflected in the varying institutional arrangements of university–industry–government relations (Wixted & Holbrook, 2013). Some important contributions for effective Industry-Institute Interactions from research papers published from 2007 to 2014 are presented in Table 1. IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 6 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Table 1 Important contributions in the area of effective Industry-Institute Interactions Researcher/s and their Contributions Bercivitz and Feldman (2007): This paper examined how innovation strategy influences firm’s level of involvement with university-based research. The results suggested that firms with internal R&D strategies more heavily weighted toward exploratory activities allocate a greater share of their R&D resources to exploratory university research and develop deeper multifaceted relationships with their university research partners. Tether and Tajar (2008): This paper explored the use of specialist knowledge providers as sources of information in the innovation activities of manufacturing and service firms. Perkmann and Walsh (2009): This paper analyzed the impact of university–industry relationships on public research. Their learning-centered interpretation qualified the notion of entrepreneurial science as a driver of applied university–industry collaboration. Jia et al. (2010): This paper suggested cellular automaton model to analyze the diffusion of innovation in industrial clusters. The result of the simulation suggested that industry-university- institute cooperation is better especially when enterprise’s R&D capability is very weak or the technology is very difficult. Intensifying the external support from local government, industry associations and financial institutions has a positive effect on the diffusion of innovation in industrial clusters. Lai (2011): This paper analyzed the willingness to engage in technology transfer (TT) in industry university collaborations (IUCs) from three vantage points: technology transferor (university), technology transferee (industry), and the TT intermediary institute. From the vantage point of universities, this study showed that the “transferor's incentive” and “capability of transferor” variables positively influence willingness to participate in TT in an IUC. From the vantage point of industry, the results indicated that “capability of transferee” and “incentive for establishing technological resources” have major influence on willingness to participate in TT in an IUC. From the vantage point of TT intermediary institutes, the results showed that “intermediary's fundamental resources” and “intermediary's transferring process” have a positive impact on willingness to participate in TT. Perkmann et al. (2011): This paper investigated how university research quality shapes their engagement with industry. They found that in technology-oriented disciplines, departmental faculty quality is positively related to industry involvement. In the medical and biological sciences they found a positive effect of departmental faculty quality but establish that this does not apply to star scientists. In the social sciences they found some support for a negative relationship between faculty quality and particularly the more applied forms of industry involvement. The implication for science policy makers and university managers was also suggested. Vauterin et al. (2012): The paper employed interpretive phenomenological research methods, an investigative case-based approach to study the boundaries, boundary roles and processes involved in university-industry collaborative interaction in the context of Finnish international higher education. The findings suggested that conceptualization of the university-industry boundary- spanning processes in international higher education needs to be extended to incorporate elements concerning the power, impact and management of the boundary roles. A better understanding and adequate managing of the boundary roles may help to decrease the perceived market demand uncertainty surrounding international higher education. Xias and Jin (2012): This paper analyzed the impact of organizational features and context variables on the proneness of university-industry cooperation in the R&D and engineering process. They suggested that the probability of cooperation with university significantly depends on various organizational factors including firm size and enterprise absorptive capacity. They also suggested that the actual pay tax the collection of business-to-market and technical information, and market position are also important driving factors to the engineering research cooperation between enterprises and universities, but their influences vary with the type of product innovation and process innovation. http://www.sciencedirect.com/science/article/pii/S0048733308000784 http://www.sciencedirect.com/science/article/pii/S0048733308000784 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 7 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Researcher/s and their Contributions Şendoğduand Diken (2013): Industry sector needs to be in collaboration with university in order to reach the information that will contribute its performance. This paper investigated the level at which the university and industry collaboration exists in Konya province, to ascertain the frequency of collaboration subjects and the problems encountered during this collaboration. Salleh and Omar (2013): This paper proposed a successful model for university-industry collaboration focusing on the interaction between university, government, and industry. They emphasized the role of university, government, and industry to work mutually to achieve successful collaboration. Guan and Zhao (2013): This paper investigated the effects of multiplicative interaction between clustering and reach on members' knowledge creation and patent value based on complex network analysis in nano bio pharmaceuticals field. Fiaz (2013): This paper investigated the growing phenomenon of university-industry (U–I) collaboration in high-tech strategic projects in China. He explored the U–I collaboration patterns among Chinese universities and high-tech industry on the basis of quantitative analysis using a research instrument. The results showed that U–I collaboration is established and encouraged due to factors such as: R&D tendency, R&D risks and R&D promotion factors such as state incentives. Liew et al. (2013): This paper presented the strategic and tactical approaches on university and industry collaboration in the contemporary commercial climate. This paper provided a commercial approach which may be adopted by the university in propagating the collaboration resulting in a win-win situation. Jung (2014): This paper examined the National Nanotechnology Initiative of U.S. government science and technology (S&T) program, affects the nature of university research in nanotechnology. The findings suggested that, at least in the case of the NNI, targeted government S&T programs may increase the efficiency of university research, but potentially do so at a price. 3. Critical Factors (CFs) identified for effective Industry-Institute Interactions (III) To accomplish the task of identifying Critical Factors (CFs) for effective III, a literature survey was conducted by searching various key words like critical factors of III in India, factors important for successful III, key factors for III in India etc. Google search and Google scholar search engines were used for collecting supporting literature from national and international journals, proceedings of national and international conferences, authentic websites of government and non-government organizations, and reports published by various government/non-government departments and research organizations. Forty three CFs for effective III were identified from the literature review. Nine experts (five from academia and four from the manufacturing industry) participated in an idea engineering workshop to validate these critical factors. In the first session of the workshop, the utility of the identified CFs was confirmed, and after a long brainstorming session, the forty three CFs were classified into nine dimensions through expert’s judgments based upon their similarity. These dimensions are as follows: financial interactions, government/nation/regulatory perspectives, technical interactions, markets and customer’s interactions, social interactions, green and environmental interactions, intellectual properties perspectives, human resource interactions and motivation from mutual benefits. In the second session of the workshop, experts were asked to rate the identified dimension and CFs (other details regarding data collection have been provided in Section 4).The identified dimensions of CFs and the CFs that are important for effective III from an Indian perspective are shown in Table 2. IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 8 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Table 2 Critical Factors important for effective III in an Indian perspective CFs S.N. Dimensions of CFs identified for effective III(Reference) CFs S.N. CFs identified for effective III References 1 Financial interactions (Gidley et al., 2010; Fiaz, 2013) 1.1 Maintained/improved business margins Korres (2012) 1.2 Increased market share Czarnitzki et al. (2011) 1.3 Increase of shareholder returns and goodwill Muscio et al. (2013) 1.4 Higher profits Korres (2012) 1.5 Incentives and subsidies Salter and Martin (2001) 1.6 Fund allocation for nation’s R&D Mowery (2012); Fiaz (2013) 1.7 Fund allocation for industry’s/institute’s R&D Santoro and Chakrabarti (2002) 2 Government/nation/regulatory perspectives (Bozeman, 2000) 2.1 Government policies Parthaand David (1994); Bruneel et al. (2010); Dai et al. (2013) 2.2. Improved image of nation Bodas Freitas et al. (2012); Fiaz (2013) 2.3 Stability of centre and state government Ostrom (2007) 2.4 Coordination and cooperation among centre/state governments Etzkowitz and Leydesdorff (2000) 2.5 Visionary and strategically able leadership Dai et al. (2013) 2.6 Improvement in national education system Dai et al. (2013) 3 Technical interactions (Numprasertchai and Igel, 2005) 3.1 Improved efficiency Albury (2005); Faems et al. (2005); Peng et al. (2013) 3.2 Technological innovations Kaufmann and Tödtling (2001) 3.3 Technology adaptation towards adoption Archibugi and Pietrobelli (2003) 3.4 Technical advancement stage of country Santoro and Chakrabarti (2002) 3.5 IT enablement and communication systems Siegel et al., (2003); Numprasertchai and Igel (2005); Fontana et al. (2006) IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 9 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 CFs S.N. Dimensions of CFs identified for effective III (Reference) CFs S.N. CFs identified for effective III References 4 Markets’ and customers’ interactions (JIA et al., 2010; Wilson, 2012) 4.1 Access to new costumer’s and market Muscio and Nardone (2012) 4.2 Improved timing for market introduction Barney (1991) 4.3 Customer satisfaction Siegel et al. (2003) 4.4 Managing demand and supply balance Polt et al. (2001); Xias and Jin (2012) 4.5 Eagerness to test innovative products Sawhney et al. (2005); Nambisan (2009) 4.6 Income and education level of customers Straughan and Roberts (1999); Diamantopoulos et al. (2003); Hartono (2009) 4.7 Role of media, advertisement & marketing agencies Wells (2007) 5 Social interactions (Wilson, 2012) 5.1 Better utilization of social resources Siegel et al. (2003); Laursen et al. (2011) 5.2 Social justice Orecchini et al. (2012) 5.3 Better standard of life Peng et al. (2013) 5.4 Caste system towards specialized workforce Yeravdekar and Tiwari (2012) 5.5 Belief and values Bruneel et al. (2010) 6 Green and environmental interactions (Luthra et al., 2011) 6.1 Encouragement to green efforts Erkuş-Öztürk and Eraydın (2010); Zhu et al. (2012) 6.2 Environment organizations’ efforts Kumar et al. (2013); Kumar et al. (2014) 6.3 Pollution and environment regulations and legislation Chien and Shih (2007); Mudgal et al. (2010); Kumar et al. (2013); Luthra et al. (2013); 7 Intellectual properties perspectives(Bruneel et al., 2010) 7.1 Better opportunities for interactions Bruneel et al. (2010) 7.2 Regular workshops, seminar, conferences Lagendijkand Cornford (2000); Cummings and Kiesler (2005); Cummingsand Kiesler (2007) 7.3 Encouragement to knowledge and innovation management Meyer-Krahmer and Schmoch (1998); Edmondson et al. (2012) http://scholar.google.co.in/citations?user=mpaVyFgAAAAJ&hl=en&oi=sra http://www.sciencedirect.com/science/article/pii/S0016718599000317 http://www.sciencedirect.com/science/article/pii/S0016718599000317 http://sss.sagepub.com/search?author1=Jonathon+N.+Cummings&sortspec=date&submit=Submit http://sss.sagepub.com/search?author1=Sara+Kiesler&sortspec=date&submit=Submit http://www.sciencedirect.com/science/article/pii/S0048733307001734 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 10 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 CFs S.N. Dimensions of CFs identified for effective III (Reference) CFs S.N. CFs identified for effective III References 8 Human resource interactions (Laine, 2008) 8.1 Support and quality Of human resource Maslach et al. (2001) 8.2 Better employment opportunities Afonso et al. (2012) 8.3 Training programs Salleh and Omar (2013) 8.4 Research based incentive/promotion system COM (2007) 9 Motivation from mutual benefits(Mohan, 2011; Vauterin et al., 2012) 9.1 Better positioning and brand image Khanna et al. (2014) 9.2 Long term competitive advantage Bruneel et al. (2010);Şendoğdu and Diken (2013) 9.3 Top and middle management commitment and support Cameron and Quinn (2005); Edmondson et al. (2012) IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 11 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 4. Methodology The methodology adopted in this paper utilized two well established approaches:  Literature review - relevant literature was reviewed to establish the background of the research and identify CFs.  Idea engineering workshop and Analytical Hierarchy Process - a work shop was conducted in two sessions. The first session was conducted to validate CFs and identify appropriate dimensions of CFs for effective III. In the second session of the workshop nine experts brainstormed to make pair wise comparisons among the identified dimensions and CFs for effective III according to Saaty’s scale (Saaty, 1980). Based on the ratings, matrices were formed and the priorities were synthesized appropriately using the step wise procedure of the AHP technique. An AHP framework of CFs for effective III in the Indian perspective was structured as a hierarchy which included three levels: goal of achieving effective III in India, nine dimensions of CFs, and the CFs under each dimension. The Analytic Hierarchy Process (AHP) was an appropriate technique to rank the dimensions and CFs for effective III in India because of its methodical and systematic approach. It is a well-established multi attribute decision support tool which uses a multilevel hierarchical structure of objectives, criteria, sub-criteria and alternatives. AHP technique evaluates and ranks the alternatives with respect to various criteria in a natural, pair-wise mode and also compares criteria, or alternatives with respect to a criterion, in a natural, pair-wise mode (Saaty, 1980). To do so, it uses a fundamental scale of absolute numbers that has been proven in practice and validated by physical and decision problem experiments. It converts individual preferences into ratio scale weights that can be combined into a linear additive weight for each alternative. The resultant can be used to compare and rank the alternatives and, hence, assist the decision maker in making a choice (Saaty, 2000, 2008; Kumar et al., 2009; Luthra et al., 2015b). 5. Data analysis and results 5.1 Constructing the hierarchy of dimensions of CFs important for effective III: 2 nd level In the second level of the hierarchy, nine identified dimensions of CFs for effective III were identified. Table 3 shows the weights that were given by the experts to the dimensions of CFs. IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 12 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Table 3 Ranking of dimensions of CFs important for effective III from an Indian perspective Maximum Eigen Value=9.40178; C.I. = 0.0502219 Pair wise comparison matrix of dimensions of CFs 1 2 3 4 5 6 7 8 9 Global Priority Weighting Rank 1 1 2 1 1 4 2 2 1 1 0.1568 2nd 2 0.5 1 1 2 1 1 0.3333 0.3333 0.25 0.0720 8th 3 1 1 1 1 2 1 1 0.5 0.333333 0.0928 5th 4 1 0.5 1 1 1 1 0.5 0.5 0.5 0.0780 6th 5 0.25 1 0.5 1 1 1 0.5 0.5 0.5 0.0643 9th 6 0.5 1 1 1 1 1 0.5 0.5 0.5 0.0734 7th 7 0.5 3 1 2 2 2 1 1 1 0.1362 4th 8 1 3 2 2 2 2 1 1 1 0.1545 3rd 9 1 4 3 2 2 2 1 1 1 0.1720 1st From the results shown in Table 3, ‘Motivation from mutual benefits (0.1720)’ is the most important dimension for effective III followed by ‘Financial interactions(0.1568)’, ‘Human resource interactions’(0.1545), ‘Intellectual properties perspectives (0.1362)’, ‘Technical interactions (0.0928)’,‘Market’s and customer’s interactions (0.0780)’,‘Green and environmental interactions (0.0734)’,‘Government/nation/regulatory perspectives (0.0720) ’and ‘Social interactions (0.0643)’. 5.2 Constructing the hierarchy of CFs of dimensions important for effective III: 3 rd level In the third level of the hierarchy, the CFs under each dimension were rated by experts. The maximum Eigenvalues, C.I. and pair wise comparison matrix of CFs under various dimensions for effective III have been shown in Appendix II. Consistency ratio (C.R.) values are well within the acceptable range for all CFs of the dimensions matrices, which ensure the decision-makers reliability (see Appendix II). Global preference weights of CFs were obtained by multiplying the preference weight values of each dimension with the relative weight of each specific CF. Based upon the global preference weights of CFs, the dimensions of CFs that are important for effective III were ranked. The overall ranking of dimensions and CFs important for effective III in an Indian perspective is summarized in Table 4. IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 13 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Table 4 Overall ranking of dimensions and CFs important for effective III in an Indian perspective S. No. Dimensions of CFs identified for effective III Preference weight of the dimensions Rank CFs S. No. CFs identified for effective III Relative weight of CFs Global weight of CFs Overall ranking of CFs 1 Financial interactions 0.1568 2 nd 1.1 Maintained/improved margins 0.0723 0.0113 31 th 1.2 Increased market share 0.1045 0.0164 23 rd 1.3 Increase of shareholder’ returns 0.0637 0.0100 33 th 1.4 Higher profits 0.1452 0.0228 16 th 1.5 Incentives and subsidies 0.1891 0.0297 10 th 1.6 Fund allocation for nation’s R&D 0.1694 0.0267 15 th 1.7 Fund allocation for industry’s/institute’s R&D 0.2558 0.0401 6 th 2 Government/nation/ regulatory perspectives 0.0720 8 th 2.1 Government policies 0.0726 0.0052 40 th 2.2 Improved image of nation 0.0801 0.0058 39 th 2.3 Stability of centre and state government 0.2625 0.0189 18 th 2.4 Coordination cooperation among centre/state governments 0.2415 0.0174 22 nd 2.5 Visionary and strategically able leadership 0.2109 0.0152 25 th 2.6 Improvement in national education system 0.1324 0.0096 34 th 3 Technical interactions 0.0928 5 th 3.1 Improved efficiency 0.1352 0.0125 27 th 3.2 Technological innovations 0.1934 0.0179 19 th 3.3 Technology adaptation towards adoption 0.1686 0.0156 24 th IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 14 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 S. No. Dimensions of CFs identified for effective III Preference weight of the dimensions Rank CFs S. No. CFs identified for effective III Relative weight of CFs Global weight of CFs Overall ranking of CFs 3.4 Technical advancement stage of country 0.1910 0.0177 20 th 3.5 IT enablement and communication systems 0.3118 0.0289 12 th 4 Markets’ and customers’ interactions 0.0780 6 th 4.1 Access to new costumers and market 0.0974 0.0076 37 th 4.2 Improved timing for market introduction 0.1218 0.0096 34 th 4.3 Customer satisfaction 0.1466 0.0114 30 th 4.4 Managing demand and supply balance 0.1098 0.0086 36 th 4.5 Eagerness to test innovative products 0.1299 0.0101 32 th 4.6 Income and education level of customers 0.1707 0.0133 26 th 4.7 Role of media, advertisement and marketing agencies 0.2238 0.0175 21 st 5 Social interactions 0.0643 9 th 5.1 Better utilization of social resources 0.1469 0.0094 35 th 5.2 Social justice 0.1897 0.0122 29 th 5.3 Better standard of life 0.4777 0.0307 9 th 5.4 Caste system towards specialized workforce 0.0697 0.0045 41 th 5.5 Belief and values 0.1160 0.0075 38 th IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 15 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 S. No. Dimensions of CFs identified for effective III Preference weight of the dimensions Rank CFs S. No. CFs identified for effective III Relative weight of CFs Global weight of CFs Overall ranking of CFs 6 Green and environmental interactions 0.0734 7 th 6.1 Encouragement to green efforts 0.1692 0.0124 28 th 6.2 Environment organizations’ efforts 0.3874 0.0284 13 th 6.3 Pollution and environment regulations and legislation 0.4434 0.0325 8 th 7 Intellectual properties perspectives 0.1362 4 th 7.1 Better opportunities for interactions 0.400 0.0545 4 th 7.2 Regular workshops, seminar, conferences 0.200 0.0272 14 th 7.3 Encouragement to knowledge and innovation management 0.400 0.0545 4 th 8 Human resource interactions 0.1545 3 rd 8.1 Support and quality Of human resource 0.2326 0.0359 7 th 8.2 Better employment opportunities 0.1238 0.0191 17 th 8.3 Training programs 0.2778 0.0429 5 th 8.4 Research based incentive/promotion systems 0.3658 0.0565 3 rd 9 Motivation from mutual benefits 0.1720 1 st 9.1 Better positioning and brand image 0.1692 0.0291 11 th 9.2 Long term competitive advantage 0.3874 0.0666 2 nd 9.3 Top and middle management commitment and support 0.4434 0.0763 1 st IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 16 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 The results have been compiled as follows:  ‘Fund allocation for industry’s/institute’s R&D’ was the highest ranked CF and ‘Increase of shareholder returns’ was the lowest ranked CF in dimension 1 (Financial interactions).  Similarly, ‘Stability of centre and state government’ was the most important CF and ‘Government policies’ was the least important CF in dimension 2 (Government/nation/regulatory perspectives).  In dimension 3 (Technical interactions), ‘IT enablement and communication systems’ obtained the highest rank and ‘Improved efficiency’ obtained the lowest rank.  ‘Role of media, advertisement and marketing agencies’ was ranked highest and ‘Access to new customers and market’ was ranked lowest in dimension 4 (Markets and customers).  ‘Better standard of life’ was the highest ranked CF and ‘Caste system towards specialized workforce’ was the lowest ranked CF in dimension 5 (Social interactions).  ‘Pollution and environment regulations and legislation’ was the most important CF and ‘Encouragement to green efforts’ was the least important CF in dimension 6 (Green and environmental interactions).  ‘Better opportunity for interaction’ was the highest ranked CF and ‘Regular workshops, seminar and conferences’ was the lowest ranked CF in dimension 7 (Intellectual properties perspectives).  ‘Research based incentive/promotion system’ was the highest ranked CF and ‘Better employment opportunities’ was the lowest ranked CF in dimension 8 (Human resource interactions).  ‘Top and middle management commitment and support’ was the highest ranked CF and ‘Better positioning and brand image’ was the lowest ranked CF in dimension 9 (Motivation from mutual benefits). The overall ranking of these forty three CFs is as follows:  ‘Top and middle management commitment and support (0.0763)’, ‘Long term competitive advantage (0.0666)’ and ‘Research based incentive/promotion systems (0.0565)’are the top ranked three CFs; and  ‘Improved image of nation (0.0058)’, ‘Government policies (0.0052’) and ‘Caste system towards specialized workforce (0.0045)’are the bottom three CFs; 6. Sensitivity Analysis In this research, the ‘Motivation from mutual benefits’ dimension of CFs for effective III in an Indian perspective had the highest preference weight (Table 4), and therefore influences the other dimensions of CFs. For that reason, the ‘Motivation from mutual benefits’ dimension has been selected with its value varying from 0.1 to 0.9 with 0.1 as the increment and this change has been reflected in the other dimensions. The changes in other dimensions of CFs for effective III in an Indian perspective have been tabulated in Table 5. IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 17 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Table 5 Dimension values when increasing ‘Motivation from mutual benefits’ dimension of CFs for effective III in an Indian perspective Listed dimensions Values of preference weights for listed dimensions of CFs for effective III 1 0.1568 0.1704 0.1515 0.1280 0.1136 0.0947 0.0755 0.0568 0.0379 0.0189 2 0.0720 0.0783 0.0696 0.0609 0.0522 0.0435 0.0347 0.0261 0.0174 0.0087 3 0.0928 0.1009 0.0897 0.0784 0.0672 0.0560 0.0447 0.0336 0.0224 0.0112 4 0.0780 0.0848 0.0754 0.0659 0.0565 0.0471 0.0376 0.0283 0.0188 0.0094 5 0.0643 0.0699 0.0621 0.0543 0.0466 0.0388 0.0310 0.0233 0.0155 0.0078 6 0.0734 0.0798 0.0709 0.0620 0.0532 0.0443 0.0353 0.0266 0.0177 0.0089 7 0.1362 0.1480 0.1316 0.1151 0.0987 0.0822 0.0656 0.0493 0.0329 0.0164 8 0.1545 0.1679 0.1493 0.1306 0.1120 0.0933 0.0744 0.0560 0.0373 0.0186 9 0.1720 0.1000 0.2000 0.3002 0.4000 0.5000 0.6013 0.7000 0.8000 0.9001 Total 1 1 1 1 1 1 1 1 1 1 Further, due to variation in dimension weights, specific CF’s weights also change accordingly. At the 0.1 value of ‘Motivation from mutual benefits’dimension, the CF ‘Research based incentive/promotion system (8.4)’ holds the highest value and the CF ‘Caste system towards specialized workforce (5.4)’ holds the lowest value. The CF ‘Research based incentive/promotion system (8.4)’ retains the highest weight value until the normal value (0.1720) of ‘Motivation from mutual benefits’dimension. When the ‘Motivation from mutual benefits’ dimension weights value is varied (from 0.1720 to 0.9), the CF ‘Top and middle management commitment and support (9.3)’ holds the highest weight value, and the weight values of other CFs also vary accordingly. The changes in the values of other CFs in order to promote III in an Indian perspective have been tabulated in Appendix III. Global preference weights for specific CFs based on the sensitivity analysis are presented in Appendix IV. It can be inferred that, global preference weights of the specific CFs vary with respect to the change in weight values of the ‘Motivation from mutual benefits’ dimension. Therefore, it may be concluded that the ‘Motivation from mutual benefits’ dimension is very important for effective III in an Indian perspective. 7. Discussion and managerial implications Due to globalization, intense global competition, rapid technological changes, shorter product life cycles, and environment and social issues Indian industries are under tremendous pressure to incorporate changes into their business practices and are exploring innovative methods to reduce environmental and social impacts, operating costs, lead time, and inventory to sustain their growth in the market. Institute research may be beneficial to Indian industries by facilitating the advancement of knowledge and new technologies to increase sustainability in today’s business environment. Government/regulatory bodies and universities are making efforts to increase academic engagement to solve economic, environmental and other societal issues and to raise revenue for universities (Perkmann et al., 2013). This paper provided the identification and ranking of various dimensions of CFs and CFs under each dimension for effective III in an Indian perspective. A comprehensive literature review and idea engineering workshop were carried out to identify and rank these dimensions and the CFs under each dimension. Nine dimensions and forty three CFs for effective III were identified from extensive literature review and expert’s input. AHP methodology was used to rank these IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 18 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 identified dimensions and CFs for effective III in an Indian perspective. The ‘Motivation from mutual benefits’ dimension had the highest global weight, and the ‘Social interactions’ dimension was weighted the lowest. These dimensions were ranked 1 st and 9 th respectively. Further, ranking of various CFs under each dimension was done. In order to recognize, identify and exploit opportunities from a global perspective, it is critically important to understand what boundaries stand between university-industry partnering initiatives in international higher education and what interaction processes span these boundaries (Vauterin et al., 2012). Research projects are usually long term and future oriented ‘series of activities’ systematically planned and executed to gain a competitive advantage through:  Reduction of cost by involving innovations in raw material types and usage, and processes;  Introduction of truly innovative products and services capable of: a) attracting new segments of prospective customers, and b) maintaining existing customers;  Sharing of R&D costs and cutting down many consultancy expenditures; and many more. Perceived expected better positioning and enhanced brand image may motivate industry players and institutes (organizations involved in research) to collaborate and share the benefits resulting from this agreement to move together towards achieving research goals. India is a democratic country with no condition for limiting the maximum number of political parties leading to the possibility of many uncertainties/instabilities. These uncertainties include:  Conflicts of interest may arise from governments composed of two different political parties in states and at the centre.  Difficulty in reaching consensus because the chances of governments of different political parties in Indian states (28 states) are high.  In the case where no political party has a clear majority, there are two possibilities: a) formation of government by more than one political party; b) re- election. All of these situations/consequences may hamper long-lasting, stable, cordial and fruitful ‘interactions and relations’ among institutes and industries in their efforts to carry out collaborative research, share knowledge and management, and produce innovative management. In fact, stable government funding to universities may complement funding from research contracts and consultations, which may further contribute to a considerable increase in university’s collaborations with industry towards accelerating the knowledge transfer processes (Muscio et al., 2013). Budget announcements, annual and periodic, reveal fund allocation for various fields, where the team of ministers, planners and experts from finance and economics contribute to understand, perceive, plan, analyze, and refine the recommendations on the basis of information. This information is gathered through collecting primary data (by using techniques like questionnaire based survey etc.), considering secondary data (government reports, organization’s annual report, comparative reports etc.), comparison of cases of IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 19 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 developed countries and countries passing through the same development phase, and conducting various conferences, workshops and sessions (Sanders et al., 2015).In fact, all actors involved must be actively involved in efforts to find appropriate methods for effective III. Our research has implications for international and national bodies, policy makers, industrial organizations and practitioners/managers with an interest in effective industry institute interactions to motivate research and innovation. This research also has implications for scholars who may use the framework and propositions to direct new theoretical and empirical analyses of III. Top managers are concerned with policy- making and the establishment of procedures to facilitate research and innovation activities (Zohar, 2010). Sufficient fund allocation may help to procure appropriate technology, machinery and research equipment and to hire research experts, scientists and analysts at the national and international level. A variety of skills (technical, professional, administrative, and managerial) are required to carry out the implementation and completion of collaborative- research and innovation projects, which may open up new opportunities for employment of trained and skilled professionals. Financial objectives and measures for the growth stage will stem from the development and growth of the organization which will lead to increased sales volumes, acquisition of new customers, growth in revenues etc. The economic, social, political, and cultural results of III are a long process (Ayla and İşgören, 2010). 8. Conclusions Effective III may create new opportunities for academia and business to collaborate for mutual advantage. In this research study, an attempt was made to identify various dimensions and CFs for effective III in an Indian perspective from an extensive literature review. An idea engineering workshop was conducted for pair wise comparison of dimensions and CFs. The AHP methodology was utilized for ranking these identified dimensions and CFs. In conclusion, the robustness of the proposed solution model for this research was monitored through a sensitivity analysis test. The ‘Motivation from mutual benefits’ dimension was ranked first. This paper may play an important role in understanding various CFs and ranking them will help to achieve effective III in India. Systematically designed and critically planned and effectively implemented training and skill enhancing programs, in fact, may lead to successful collaboration for achieving certain preset goals towards research and innovation. All pair comparisons in AHP were made on the basis of expert’s opinions (selected from academia and industry). It is natural that the opinions of experts may be biased. It should also be noted that the experts were not selected randomly. Based on the literature review and expert opinions, various dimensions and CFs under each dimension for effective III in an Indian perspective were identified and ranked. Different multi-criteria decision making models may be applied for the same problem and results can be compared in future studies. Further, questionnaire based surveys and case studies may be conducted to validate our research work. Also, the interactions among the dimensions and CFs may be examined using CIAHP approach proposed by Kumar (2014). IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 20 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 REFERENCES Afonso, A., Ramírez, J. J., &Díaz-Puente, J. M. (2012).University-industry cooperation in the education domain to foster competitiveness and employment. Procedia-Social and Behavioral Sciences, 46, 3947-3953. doi:10.1016/j.sbspro.2012.06.177 Albury, D. (2005). Fostering innovation in public services. Public Money and Management, 25(1), 51-56. All India Council of Technical Education (AICTE). Online available at: www.aicte-india.org (Accessed: December 13, 2013). Alrawi, K., &Alrawi, W. (2011). Knowledge management for marketing management: Implementing information technology to distribution channel performance. Journal of Knowledge & Human Resource Management, 3(4), 37-50. Archibugi, D., &Pietrobelli, C. (2003). The globalization of technology and its implications for developing countries: Windows of opportunity or further burden? Technological Forecasting and Social Change, 70(9), 861-883. doi:10.1016/S0040-1625(02)00409-2 Association of Indian Universities (AIU). Online available at: www.aiuweb.org (Accessed: December 12, 2013). Ayla, C. D., &İşgören, N. Ç. (2010).University-industry cooperation in terms of textile- apparel education. Procedia-Social and Behavioral Sciences, 2(2), 3437-3441. doi:10.1016/j.sbspro.2010.03.530 Barney, J. B. (1991). Firm resources and sustainable competitive advantage.Journal of Management 17(1), 99–120. doi: 10.1177/014920639101700108 Bercovitz, J. E., & Feldman, M. P. (2007). Fishing upstream: Firm innovation strategy and university research alliances. Research Policy, 36(7), 930-948. doi:10.1016/j.respol.2007.03.002 Bozeman, B. (2000). Technology transfer and public policy: A review of research and theory. Research Policy, 29(4), 627-655. doi:10.1016/S0048-7333(99)00093-1 Bruneel, J., d’Este, P., & Salter, A. (2010).Investigating the factors that diminish the barriers to university–industry collaboration. Research Policy, 39(7), 858-868. doi:10.1016/j.respol.2010.03.006 Cameron, K. S., & Quinn, R. E. (2005). Diagnosing and changing organizational culture: Based on the competing values framework. New York: John Wiley & Sons. Central Board of Secondary Education (CBSE), New Delhi. Online available at: www.cbse.nic.in (Accessed: December 25, 2013). Central Electronics Engineering Research Institute (CEERI). Online available at: http:// http://www.ceerichennai.org/ (Accessed: December 19, 2013). http://dx.doi.org/10.1016/j.sbspro.2012.06.177 http://www.aicte-india.org/ http://dx.doi.org/10.1016/S0040-1625(02)00409-2 http://www.aiuweb.org/ http://dx.doi.org/10.1016/j.sbspro.2010.03.530 http://dx.doi.org/10.1016/j.respol.2007.03.002 http://dx.doi.org/10.1016/S0048-7333(99)00093-1 http://dx.doi.org/10.1016/j.respol.2010.03.006 http://www.cbse.nic.in/ http://www.ceerichennai.org/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 21 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Central Tibetan Schools Administration (CTSA), Delhi. Online available at: www.ctsa.nic.in (Accessed: December 25, 2013). Centre for Studies in Civilization, Project of History of Indian Science, Philosophy and Culture (PHISPC). Online available at: www.phispc.nic.in (Accessed: December 12, 2013). Chakrabarti, A. K., & Lester, R. K. (2002). Regional economic development: Comparative case studies in the US and Finland. In Engineering Management Conference, 2002.IEMC'02. 2002 IEEE International,(2), 635-642. doi:10.1109/IEMC.2002.1038510 Chen, C. J., & Huang, J. W. (2007). How organizational climate and structure affect knowledge management—The social interaction perspective. International Journal of Information Management, 27(2), 104-118. doi:10.1016/j.ijinfomgt.2006.11.001 Chien, M. K., & Shih, L. H. (2007). An empirical study of the implementation of green supply chain management practices in the electrical and electronic industry and their relation to organizational performances. International Journal of Environmental Science and Technology, 4(3), 383-394. COM, E. (2007). Improving knowledge transfer between research institutions and industry across Europe: embracing open innovation. Brussels, 4, 2007. Council of Architecture (COA), India. Online available at: www.coa.gov.in (Accessed: December 13, 2013). Cummings, J. N., &Kiesler, S. (2005). Collaborative research across disciplinary and organizational boundaries. Social Studies of Science, 35(5), 703-722. doi: 10.1177/0306312705055535 Cummings, J. N., &Kiesler, S. (2007). Coordination costs and project outcomes in multi- university collaborations. Research Policy, 36(10), 1620-1634. doi:10.1016/j.respol.2007.09.001 Czarnitzki, D., Hanel, P., & Rosa, J. M. (2011).Evaluating the impact of R&D tax credits on innovation: A micro econometric study on Canadian firms.Research Policy, 40(2), 217-229. doi:10.1016/j.respol.2010.09.017 Dai, Y., Kong, D., & Wang, M. (2013). Investor reactions to food safety incidents: Evidence from the Chinese milk industry. Food Policy, 43, 23-31. doi:10.1016/j.foodpol.2013.08.004 Department of Technical Education (DTE), Haryana. Online available at: http://techeduhry.nic.in (Accessed: December 13, 2013). Diamantopoulos, A., Schlegelmilch, B. B., Sinkovics, R. R., & Bohlen, G. M. (2003). Can socio-demographics still play a role in profiling green consumers? A review of the evidence and an empirical investigation. Journal of Business Research, 56(6), 465-480. doi:10.1016/S0148-2963(01)00241-7 http://www.ctsa.nic.in/ http://www.phispc.nic.in/ http://dx.doi.org/10.1109/IEMC.2002.1038510 http://dx.doi.org/10.1016/j.ijinfomgt.2006.11.001 http://www.coa.gov.in/ http://dx.doi.org/10.1016/j.respol.2007.09.001 http://dx.doi.org/10.1016/j.respol.2010.09.017 http://dx.doi.org/10.1016/j.foodpol.2013.08.004 http://techeduhry.nic.in/ http://dx.doi.org/10.1016/S0148-2963(01)00241-7 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 22 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Edmondson, G., Valigra, L., Kenward, M., Hudson, R. L., & Belfield, H. (2012). Making industry-university partnerships work: Lessons from successful collaborations. Science Business Innovation Board AISBL. Erkuş-Öztürk, H., &Eraydın, A. (2010). Environmental governance for sustainable tourism development: Collaborative networks and organization building in the Antalya tourism region. Tourism Management, 31(1), 113-124. doi:10.1016/j.tourman.2009.01.002 Etzkowitz, H. (2011). The triple helix: Science, technology and the entrepreneurial spirit. Journal of Knowledge-Based Innovation in China, 3(2), 76-90. doi: http://dx.doi.org/10.1108/17561411111138937 Etzkowitz, H., &Leydesdorff, L. (2000). The dynamics of innovation: From national systems and “Mode 2” to a triple helix of university–industry–government relations. Research policy, 29(2), 109-123. doi:10.1016/S0048-7333(99)00055-4 Faems, D., Van Looy, B., &Debackere, K. (2005). Inter-organizational collaboration and innovation: Toward a portfolio approach*. Journal of Product Innovation Management, 22(3), 238-250. doi: 10.1111/j.0737-6782.2005.00120.x Fiaz, M. (2013). An empirical study of university–industry R&D collaboration in China: Implications for technology in society. Technology in Society, 35(3), 191-202. doi:10.1016/j.techsoc.2013.03.005 Fombrun, C. (1996). Reputation: Realizing value from the corporate image. Boston: Harvard Business School Press. doi: 10.1002/npr.4040150212 Fontana, R., Geuna, A., & Matt, M. (2006). Factors affecting university–industry R&D projects: The importance of searching, screening and signaling. Research Policy, 35(2), 309- 323. doi:10.1016/j.respol.2005.12.001 Freitas, I. M. B., Geuna, A., & Rossi, F. (2013).Finding the right partners: Institutional and personal modes of governance of university–industry interactions. Research Policy, 42(1), 50-62. doi:10.1016/j.respol.2012.06.007 Gidley, J. M., Hampson, G. P., Wheeler, L., &Bereded-Samuel, E. (2010). From access to success: An integrated approach to quality higher education informed by social inclusion theory and practice. Higher Education Policy, 23(1), 123-147. doi:10.1057/hep.2009.24 Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., &Kyriakidou, O. (2004). Diffusion of innovations in service organizations: Systematic review and recommendations. Milbank Quarterly, 82(4), 581-629. doi: 10.1111/j.0887-378X.2004.00325.x Guan, J., & Zhao, Q. (2013). The impact of university–industry collaboration networks on innovation in nanobiopharmaceuticals. Technological Forecasting and Social Change, 80(7), 1271-1286. doi:10.1016/j.techfore.2012.11.013 http://dx.doi.org/10.1016/j.tourman.2009.01.002 http://dx.doi.org/10.1016/S0048-7333(99)00055-4 http://dx.doi.org/10.1016/j.techsoc.2013.03.005 http://dx.doi.org/10.1016/j.respol.2005.12.001 http://dx.doi.org/10.1016/j.respol.2012.06.007 http://dx.doi.org/10.1016/j.techfore.2012.11.013 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 23 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Hartono, A. (2008). Adopting socio-demographic characteristics in profiling green consumers: A review of hypotheses. Jurnal Siasat Bisnis, 12(1), 55-62. Indian Council of Historical Research (ICHR), New Delhi. Online available at: www.ichrindia.org (Accessed: December 12, 2013). Indian Council of Philosophical Research (ICPR), New Delhi. Online available at: www.icpr.nic.in (Accessed: December 12, 2013). Indian Council of Social Science Research (ICSSR), New Delhi. Online available at: www.icssr.org (Accessed: December 12, 2013). Indian Institute of Advance Study (IIAS), Shimla. Online available at: www.iias.org (Accessed: December 12, 2013). Indian Institute of Chemical Biology (IICB).Online available at: http://www.iicb.res.in/iicb1.htm (Accessed: December 19, 2013). Indian Space Research Organization (ISRO). Online available at: http://www.isro.org (Accessed: December 19, 2013). Jung, H. J. (2014). The impacts of science and technology policy interventions on university research: Evidence from the US National Nanotechnology Initiative. Research Policy, 43(1), 74-91.Doi:10.1016/j.respol.2013.07.001 Kaufmann, A., &Tödtling, F. (2001). Science–industry interaction in the process of innovation: The importance of boundary-crossing between systems. Research Policy, 30(5), 791-804. doi:10.1016/S0048-7333(00)00118-9 KendriyaVidyalayaSangathan, New Delhi. Online available at: www.kvsangathan.nic.in (Accessed: December 25, 2013). Khanna, M., Jacob, I., & Yadav, N. (2014). Identifying and analyzing touchpoints for building a higher education brand. Journal of Marketing for Higher Education, 24(1), 122- 143. doi:10.1080/08841241.2014.920460 Korres, M. G. M. (2012). Technical change and economic growth: Inside the knowledge based economy. United Kingdom: Ashgate Publishing, Ltd. Kulkarni, J. A., Pachpande, A., Pachpande, S, & Kulkarni, J. A. (2011). Case studies in management. New Delhi, India: Pearson Education. Kumar, S. (2014). Contextual interactions analytic hierarchy process (CIAHP): Introduction and application to analyze interactions among knowledge management implementation capability (KMIC) factors. International Journal of Knowledge and Learning, 9(3), 242-263. doi: http://dx.doi.org/10.1504/IJKL.2014.068926 http://www.ichrindia.org/ http://www.icpr.nic.in/ http://www.icssr.org/ http://www.iias.org/ http://dx.doi.org/10.1016/j.respol.2013.07.001 http://dx.doi.org/10.1016/S0048-7333(00)00118-9 http://www.kvsangathan.nic.in/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 24 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Kumar, S., Luthra, S., & Haleem, A. (2013). Customer involvement in greening the supply chain: An interpretive structural modeling methodology. Journal of Industrial Engineering International, 9(1), 1-13. doi:10.1186/2251-712X-9-6 Kumar, S., Luthra, S., & Haleem, A. (2014). Critical success factors of customer involvement in greening the supply chain: An empirical study. International Journal of Logistics Systems and Management, 19(3), 283-310. doi: http://dx.doi.org/10.1504/IJLSM.2014.065498 Kumar, S., Parashar, N., & Haleem, A. (2009). Analytical hierarchy process applied to vendor selection problem: Small scale, medium scale and large scale industries. Business Intelligence Journal, 2(2), 355-362. Lagendijk, A., & Cornford, J. (2000).Regional institutions and knowledge–tracking new forms of regional development policy. Geoforum, 31(2), 209-218. doi:10.1016/S0016- 7185(99)00031-7 Lai, W. H. (2011). Willingness-to-engage in technology transfer in industry–university collaborations. Journal of Business Research, 64(11), 1218-1223. doi:10.1016/j.jbusres.2011.06.026 Laine, K. (2008). A Finnish concept for academic entrepreneurship: The case of Satakunta University of Applied Sciences. Industry and Higher Education, 22(1), 19-28. doi: http://dx.doi.org/10.5367/000000008783877002 Laursen, K., & Salter, A. (2004). Searching high and low: What types of firms use universities as a source of innovation? Research Policy, 33(8), 1201-1215. Laursen, K., Reichstein, T., & Salter, A. (2011).Exploring the effect of geographical proximity and university quality on university–industry collaboration in the United Kingdom. Regional Studies, 45(4), 507-523. doi:10.1016/j.respol.2004.07.004 Liew, M. S., Shahdan, T. T., & Lim, E. S. (2013).Enablers in enhancing the relevancy of university-industry collaboration. Procedia-Social and Behavioral Sciences, 93, 1889-1896. doi:10.1016/j.sbspro.2013.10.135 Luthra, S., Kumar, V., Kumar, S., & Haleem, A. (2011). Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique: An Indian perspective. Journal of Industrial Engineering and Management, 4(2), 231-257. doi:10.3926/jiem.2011.v4n2.p231-257 Luthra, S., Garg, D., & Haleem, A. (2013). Identifying and ranking of strategies to implement green supply chain management in Indian manufacturing industry using analytical hierarchy process. Journal of Industrial Engineering and Management, 6(4), 930-962. doi: http://dx.doi.org/10.3926/jiem.693 Luthra, S., Garg, D., & Haleem, A. (2014). Green supply chain management: Implementation and performance–a literature review and some issues. Journal of Advances in Management Research, 11(1), 20-46. doi: http://dx.doi.org/10.1108/JAMR-07-2012-0027 http://dx.doi.org/10.1016/S0016-7185(99)00031-7 http://dx.doi.org/10.1016/S0016-7185(99)00031-7 http://dx.doi.org/10.1016/j.jbusres.2011.06.026 http://dx.doi.org/10.5367/000000008783877002 http://dx.doi.org/10.1016/j.respol.2004.07.004 http://dx.doi.org/10.1016/j.sbspro.2013.10.135 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 25 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Luthra, S., Kumar, S., Garg, D., & Haleem, A. (2015a). Barriers to renewable/sustainable energy technologies adoption: Indian perspective. Renewable and Sustainable Energy Reviews, 41, 762-776. Luthra, S., Mangla, S. K., &Kharb, R. K. (2015b).Sustainable assessment in energy planning and management in Indian perspective. Renewable and Sustainable Energy Reviews, 47, 58- 73. doi:10.1016/j.rser.2015.03.007 Majumdar, S. (2008). Industry-institute interaction to public-private partnership: A journey to excellence. In International Symposium on Public-Private Partnership in TVET-Challenges, Opportunities and Best Practices, Manila, 1-11. Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001).Job burnout. Annual Review of Psychology, 52(1), 397-422. doi: 10.1146/annurev.psych.52.1.397 Meyer-Krahmer, F., &Schmoch, U. (1998). Science-based technologies: University–industry interactions in four fields. Research Policy, 27(8), 835-851. doi:10.1016/S0048- 7333(98)00094-8 Ministry of Human Resources Development (MHRD). Online available at: http://mhrd.gov.in/schemes_technical_eng (Accessed: December 11, 2013). Mohan, S. R. (2011). Understanding interactions between research institutes and industry: Indian perspective. Journal of Technology Management for Growing Economies, 2(2), 113- 138. Mowery, D. C. (2012).Defense-related R&D as a model for “Grand Challenges” technology policies. Research Policy, 41(10), 1703-1715. doi:10.1016/j.respol.2012.03.027 Mudgal, R. K., Shankar, R., Talib, P., & Raj, T. (2010).Modelling the barriers of green supply chain practices: An Indian perspective. International Journal of Logistics Systems and Management, 7(1), 81-107. doi: http://dx.doi.org/10.1504/IJLSM.2010.033891 Muscio, A., &Nardone, G. (2012).The determinants of university–industry collaboration in food science in Italy. Food Policy, 37(6), 710-718. doi:10.1016/j.foodpol.2012.07.003 Muscio, A., Quaglione, D., &Vallanti, G. (2013). Does government funding complement or substitute private research funding to universities?. Research Policy, 42(1), 63-75. doi:10.1016/j.respol.2012.04.010 Nambisan, S. (2009). Virtual customer environments: IT-enabled customer co-innovation and value co-creation. Springer US. doi: 10.1007/978-1-4419-1081-3_6 National Council for Educational Research and Training (NCERT) New Delhi. Online available at: www.ncert.nic.in (Accessed: December 25, 2013). National Council for Teachers, India. Online available at: www.ncte-india.org (Accessed: December 25, 2013). http://dx.doi.org/10.1016/j.rser.2015.03.007 http://dx.doi.org/10.1016/S0048-7333(98)00094-8 http://dx.doi.org/10.1016/S0048-7333(98)00094-8 http://mhrd.gov.in/schemes_technical_eng http://dx.doi.org/10.1016/j.respol.2012.03.027 http://dx.doi.org/10.1016/j.foodpol.2012.07.003 http://dx.doi.org/10.1016/j.respol.2012.04.010 http://www.ncert.nic.in/ http://www.ncte-india.org/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 26 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 National Council of Rural Institutes (NCRI), Hyderabad. Online available at: www.ncri.in (Accessed: December 12, 2013). National Institute of Open Schooling, Noida, Uttar Pradesh. Online available at: www.nos.org (Accessed: December 25, 2013). National Knowledge Commission.(2008). Report of working group on engineering education. Working Group on Engineering Education. Available at: http://knowledgecomm ission.gov.in downloads/documents/wg_engineer.pdf (Accessed: December 13, 2013). National Research Development Corporation (NRDC), India. Online available at: http://www.nrdcindia.com (Accessed: December 21, 2013). NavodayaVidyalayaSamiti, New Delhi. Online available at: www.navodaya.nic.in (Accessed: December 25, 2013). Numprasertchai, S., &Igel, B. (2005). Managing knowledge through collaboration: Multiple case studies of managing research in university laboratories in Thailand. Technovation, 25(10), 1173-1182. doi:10.1016/j.technovation.2004.03.001 Official website of Haryana Government (2013). Online available at: haryana.gov.in(Accessed: December 11, 2013). Orecchini, F., Valitutti, V., &Vitali, G. (2012). Industry and academia for a transition towards sustainability: advancing sustainability science through university–business collaborations. Sustainability science, 7(1), 57-73. doi: 10.1007/s11625-011-0151-3 Ostrom, E. (2007). A general framework for analyzing sustainability of. In Proc. R. Soc. London Ser. B, (274), 1931. Partha, D., & David, P. A. (1994).Toward a new economics of science.Research policy, 23(5), 487-521. doi:10.1016/0048-7333(94)01002-1 Peng, T., Lu, F. J., Wang, G. Y., San, F. B., & Zhao, X. W. (2013). Study on the Optimization Mechanism about Behavior Selection of Healthy Pig Industry Chain. IERI Procedia, 5, 161-165. doi:10.1016/j.ieri.2013.11.086 Perkmann, M., & Walsh, K. (2009). The two faces of collaboration: Impacts of university- industry relations on public research. Industrial and Corporate Change, 18(6), 1033- 1065.Doi: 10.1093/icc/dtp015 Perkmann, M., King, Z., &Pavelin, S. (2011). Engaging excellence? Effects of faculty quality on university engagement with industry. Research Policy, 40(4), 539-552. doi:10.1016/j.respol.2011.01.007 Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., &Sobrero, M. (2013). Academic engagement and commercialisation: A review of the literature on http://www.ncri.in/ http://www.nos.org/ http://www.nrdcindia.com/ http://www.navodaya.nic.in/ http://dx.doi.org/10.1016/j.technovation.2004.03.001 http://dx.doi.org/10.1016/0048-7333(94)01002-1 http://dx.doi.org/10.1016/j.ieri.2013.11.086 http://dx.doi.org/10.1016/j.respol.2011.01.007 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 27 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 university–industry relations. Research Policy, 42(2), 423-442. doi:10.1016/j.respol.2012.09.007 Polt, W., Gassler, H., Schibany, A., Rammer, C., &Schartinger, D. (2001). Benchmarking industry—science relations: The role of framework conditions. Science and Public Policy, 28(4), 247-258. Saaty T. L. (2000). Fundamentals of decision making and priority theory. Pittsburgh, PA: RWS Publications. Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resources allocation. New York: McGraw Hill. Saaty, T. L. (2008). Decision making with the analytic hierarchy process.International Journal of Services Sciences, 1(1), 83-98. doi: http://dx.doi.org/10.1504/IJSSCI.2008.017590 Salleh, M. S., & Omar, M. Z. (2013). University-industry Collaboration Models in Malaysia. Procedia-Social and Behavioral Sciences, 102, 654-664. doi:10.1016/j.sbspro.2013.10.784 Salter, A. J., & Martin, B. R. (2001). The economic benefits of publicly funded basic research: A critical review. Research policy, 30(3), 509-532. doi:10.1016/S0048- 7333(00)00091-3 Sanders, M., Clark, R., Davidson, B., &Jayaraman, S. (2015). GT journey: The importance of accessible rich data sources to enable innovation. In Human-Computer Interaction: Users and Contexts. Springer International Publishing. doi: 10.1007/978-3-319-21006-3_9 Santoro, M. D., &Chakrabarti, A. K. (2002).Firm size and technology centrality in industry– university interactions. Research Policy, 31(7), 1163-1180. doi:10.1016/S0048- 7333(01)00190-1 Sawhney, M., Verona, G., &Prandelli, E. (2005).Collaborating to create: The Internet as a platform for customer engagement in product innovation. Journal of Interactive Marketing, 19(4), 4-17. doi:10.1002/dir.20046 Şendoğdu, A. A., &Diken, A. (2013). A research on the problems encountered in the collaboration between university and industry. Procedia-Social and Behavioral Sciences, 99, 966-975. doi:10.1016/j.sbspro.2013.10.570 Siegel, D. S., Waldman, D. A., Atwater, L. E., & Link, A. N. (2003). Commercial knowledge transfers from universities to firms: Improving the effectiveness of university–industry collaboration. The Journal of High Technology Management Research, 14(1), 111-133. doi:10.1016/S1047-8310(03)00007-5 Straughan, R. D., & Roberts, J. A. (1999). Environmental segmentation alternatives: A look at green consumer behavior in the new millennium. Journal of Consumer Marketing, 16(6), 558-575. doi: http://dx.doi.org/10.1108/07363769910297506 http://dx.doi.org/10.1016/j.respol.2012.09.007 http://dx.doi.org/10.1016/j.sbspro.2013.10.784 http://dx.doi.org/10.1016/S0048-7333(00)00091-3 http://dx.doi.org/10.1016/S0048-7333(00)00091-3 http://dx.doi.org/10.1016/S0048-7333(01)00190-1 http://dx.doi.org/10.1016/S0048-7333(01)00190-1 http://dx.doi.org/10.1002/dir.20046 http://dx.doi.org/10.1016/j.sbspro.2013.10.570 http://dx.doi.org/10.1016/S1047-8310(03)00007-5 http://dx.doi.org/10.1108/07363769910297506 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 28 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Tether, B. S., &Tajar, A. (2008). Beyond industry–university links: Sourcing knowledge for innovation from consultants, private research organizations and the public science- base. Research Policy, 37(6), 1079-1095. doi:10.1016/j.respol.2008.04.003 University Grant Commission of India (2013). Online available at: www.ugc.ac.in (Accessed: December 11, 2013). Vauterin, J. J., Linnanen, L., &Marttila, E. (2012). Value creation in international higher education: The role of boundary spanning in university-industry collaboration. International Journal of Quality and Service Sciences, 4(3), 283-298. doi: http://dx.doi.org/10.1108/17566691211269594 Vest, C. M. (2005). Educating engineers for 2020 and beyond. National Academy of Engineering, 160-169. Wallin, J., Isaksson, O., Larsson, A., &Elfström, B. O. (2014). Bridging the Gap Between University and Industry: Three Mechanisms for Innovation Efficiency. International Journal of Innovation and Technology Management, 11(1), 1-18. doi: 10.1142/S0219877014400057 Wei, J. I. A., LIU, L. R., & XIE, X. M. (2010). Diffusion of technical innovation based on industry-university-institute cooperation in industrial clusters. The Journal of China Universities of Posts and Telecommunications, 17, 45-50. doi:10.1016/S1005- 8885(09)60583-5 Wells, W., Spence-Stone, R., Crawford, R., Moriarty, S., & Mitchell, N. (2011).Advertising: Principles and practices. Pearson Higher Education AU. Wixted, B., & Holbrook, J. A. (2013). Reconfiguring National Science and Research Systems: The Role of Charities. Centre for Policy Research on Science and Technology. Online available at: http://www.sfu.ca/cprost/?p=569 Xias, F., &Jin, W. (2012). On the factors that affect the proneness of university-industry cooperation: A system engineering perspective. Systems Engineering Procedia, 3, 275-281. doi:10.1016/j.sepro.2011.11.030 Yeravdekar, V. R., & Tiwari, G. (2012).The higher education system in India and its impact on the economy. Available at SSRN 2139894. Zhu, Q., Sarkis, J., & Lai, K. H. (2012).Examining the effects of green supply chain management practices and their mediations on performance improvements. International Journal of Production Research, 50(5), 1377-1394. doi:10.1080/00207543.2011.571937 Zohar, D. (2010). Thirty years of safety climate research: Reflections and future directions. Accident Analysis & Prevention, 42(5), 1517-1522. doi:10.1016/j.aap.2009.12.019 http://dx.doi.org/10.1016/j.respol.2008.04.003 http://www.ugc.ac.in/ http://dx.doi.org/10.1108/17566691211269594 http://dx.doi.org/10.1016/S1005-8885(09)60583-5 http://dx.doi.org/10.1016/S1005-8885(09)60583-5 http://summit.sfu.ca/collection/205 http://www.sfu.ca/cprost/?p=569 http://dx.doi.org/10.1016/j.sepro.2011.11.030 http://dx.doi.org/10.1016/j.aap.2009.12.019 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 29 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 APPENDIX I Organizations involved in education/research in India Authority/ organizations involved in education/research in India Hierarchy Focus Description/Role/ Functions Reference/ Website Central Government The Ministry of Human Resource Development (MHRD) is under the overall charge of the human resource development minister. Formulation, implementatio n and control of educational and research policies The central government continues to play a leading role in the formulation and implementation of educational policies and programs such as National Policy on Education (NPE), 1986 (modified in 1992). Other initiatives include: providing universal access, ensuring retention and improving quality in elementary education, special emphasis on education of girls, establishment of pacesetting schools, inter-disciplinary research, starting more open universities in the states, strengthening of AICTE, encouraging sports, physical education, Yoga and adoption of an effective evaluation method, etc. http://mhrd.go v.in Ministry of Human Resource Development (MHRD) The Ministry of Human Resource Development has two Departments i.e. Department of School Education & Literacy and the Department of Higher Education. All-round development of Indian citizens The essence of HRD is education. The all-round development of Indian citizens can be achieved by building strong foundations in education. In pursuance of this mission, the MHRD was created on September 26, 1985, through the 174th amendment to the Government of India (allocation of business) Rules, 1961. The main objectives of the ministry would be: formulating the national policy on education and ensuring its implementation; planned development, including expanding access and improving quality of educational institutions throughout the country; paying special attention to poor, females and the minorities; provide financial help in the form of scholarships, loan subsidy to deserving students from deprived sections of the society; encouraging international cooperation in the field of education. http://mhrd.go v.in IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 30 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Authority/ organizations involved in education/research in India Hierarchy Focus Description/Role/ Functions Reference/ Website Department of School Education and Literacy Headed by a Secretary to the Government of India. Education of equitable quality for all citizens of India The vision of the department of school education & literacy is to ensure education of equitable quality for all in order to fully harness the nation's human potential. It has its eyes set on the “universalization of education” and making better citizens out of our young brigade. For this, various new schemes and initiatives are taken up regularly and recently, those schemes and initiatives have also started paying dividends in the form of growing enrolment in schools. http://mhrd.go v.in Department of Higher Education Headed by a Secretary to the Government of India. World class opportunities of higher education and research to the country The vision of the department of higher education is to realize India's human resource potential to its fullest in the education sector, with equity and excellence. The department of higher education is engaged in bringing world class opportunities of higher education and research to the country so that Indian students are not found lacking when facing an international platform. For this, the Government has launched joint ventures and signed MoUs to help the Indian student benefit from the world opinion. http://mhrd.go v.in State Government HRD Minister is assisted by two Ministers of State. Promote education & research in state State government plays an important role in the formulation, implementation and control of educational and research policies in state in accordance with central government policies haryana.gov.in /‎ University Grant Commission (UGC) The UGC has a mandate for coordination and determination of standards in higher educational institutions Academic and research environment in the university system To improve the academic environment in the university system by promoting collaboration and formal linkages with other Universities, National Laboratories, Institutes of national importance and Industrial R & D Laboratories in all branches of knowledge through programme of teaching, training and research. www.ugc.ac.in http://www.ugc.ac.in/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 31 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Authority/ organizations involved in education/research in India Hierarchy Focus Description/Role/ Functions Reference/ Website Other Apex Bodies in Universities and Higher Education These perform under the Department of Higher Education (DHE), Ministry of Human Resource Development Various academic and research issues There are seven other apex bodies in universities and higher education: Indian Council of Historical Research (ICHR), New Delhi; Indian Council of Social Science Research (ICSSR), New Delhi; Indian Council of Philosophical Research (ICPR), New Delhi; National Council of Rural Institutes (NCRI), Hyderabad; Indian Institute of Advance Study(IIAS), Shimla; Association of Indian Universities(AIU); Centre for Studies in Civilization, Project of History of Indian Science, Philosophy and Culture(PHISPC) www.ichrindia .org www.icssr.org www.icpr.nic.i n www.ncri.in www.iias.org www.aiuweb.o rg www.phispc.ni c.in All India Council for Technical Education (AICTE) and Council of Architecture Apex bodies in technical education Promote technical education and research in the country The AICTE has also framed various norms and standards to regulate the technical institutions in the country for maintaining quality in these institutions. These norms and standards are uniformly applicable to all the college. Similarly Council of Architecture frames norms and regulations for architecture education imparting colleges. www.aicte- india.org www.coa.gov.i n Department of Technical Education (DTE) of State Reports to State Government To promote technical education and research in the state Technical education is the supreme component of HRD with an infinite potential for supplementing greater value to products and services and for improving the quality of life of the people. The DTE explicitly provides technically trained manpower in various fields of engineering & technology encompassing diploma, post diploma, degree & post graduate level courses conducted through technical Institutions like polytechnics/engineering colleges/ institutions of management/ computer/pharmacy. http://techeduh ry.nic.in Central Government Universities Work under MHRD, DHE and UGC Academic and research in university Forty central universities have been involved in imparting higher education at university level. http://mhrd.go v.in http://www.ichrindia.org/ http://www.ichrindia.org/ http://www.icssr.org/ http://www.icpr.nic.in/ http://www.icpr.nic.in/ http://www.ncri.in/ http://www.iias.org/ http://www.aiuweb.org/ http://www.aiuweb.org/ http://www.phispc.nic.in/ http://www.phispc.nic.in/ http://www.aicte-india.org/ http://www.aicte-india.org/ http://www.coa.gov.in/ http://www.coa.gov.in/ https://www.google.co.in/search?biw=994&bih=626&q=polytechnics/+Engineering+Colleges/+Institutions+of+Management/+Computer/&spell=1&sa=X&ei=gAHFUvPbLciMrQebwIG4CA&ved=0CCgQBSgA https://www.google.co.in/search?biw=994&bih=626&q=polytechnics/+Engineering+Colleges/+Institutions+of+Management/+Computer/&spell=1&sa=X&ei=gAHFUvPbLciMrQebwIG4CA&ved=0CCgQBSgA http://techeduhry.nic.in/ http://techeduhry.nic.in/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 32 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Authority/ organizations involved in education/research in India Hierarchy Focus Description/Role/ Functions Reference/ Website State Government Universities UGC Academic and research in university State universities are run by the state government of each of the states and territories of India and are usually established by a local legislative assembly act. As of 30 November 2011, the UGC lists 285 state universities have been involved in imparting higher education at state level. www.ugc.ac.in ; Deemed Universities- Private Self Financing UGC Academic and research in university The UGC list from 23 June 2008 lists 130 deemed universities and the UGC list of private universities from 7 June 2012 lists 112 private universities. These are involved in imparting higher education. www.ugc.ac.in Government Colleges and Organizations State Government/ Universities Academic and research in college under university This category includes Indian Institutes of Technology (sixteen), Indian Institutes of Management (thirteen), National Institutes of Technology (thirty), Indian Institutes of Information Technology (four), Indian Institute of Science & Indian Institute of Science Education & Research (six), National Institute of Technical Teachers' Training & Research (four), four Boards of Apprenticeship Training and other technical & language institutes. www.aicte- india.org; www.ugc.ac.in Private Self Financing Colleges State Government/ University Academic and research in college under university The higher education system in India includes both private and publicly funded universities. These private self-financing college works under state universities to impart higher education in the state. Government Research Organizations Government of India Motivate research and innovation in the country The government of India has set up many research organizations like Indian space research organization (ISRO), Central Electronics Engineering Research Institute (CEERI); Indian Institute of Chemical Biology; Indian Institute of Tropical Meteorology; Indira Gandhi Centre for Atomic Research and Industrial Engineering and Operations Research. Space commission and department of space (DOS) in June 1972. http://www.isr o.org http://www.ce erichennai.org/ http://www.iic b.res.in/iicb1.h tm http://www.ugc.ac.in/ http://www.ugc.ac.in/ http://www.ugc.ac.in/ http://www.aicte-india.org/ http://www.aicte-india.org/ http://www.ugc.ac.in/ http://www.isro.org/ http://www.isro.org/ http://www.ceerichennai.org/ http://www.ceerichennai.org/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 33 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Authority/ organizations involved in education/research in India Hierarchy Focus Description/Role/ Functions Reference/We bsite Private Research Organizations National Research Development Corporation under Government of India Motivate research and innovation in the country The government of India has set up many research organizations like Hi-Tech Bio Laboratories, Shriram Institute for Industrial Research, DCM Limited, Varanasi Glucose Company, Madhu Chemicals Limited. NRDC also acts on behalf of large companies who develop technologies in their R&D laboratories and choose to license them out for commercialization. http://www.nr dcindia.com Central Board of Secondary Education and others Work under Department of school Education & Literacy Promote education There are seven bodies: Central Board of Secondary Education, New Delhi; National Council for Educational Research and Training (NCERT) New Delhi; National Institute of Open Schooling, Noida, Uttar Pradesh; Central Tibetan Schools Administration (CTSA), Delhi; NavodayaVidyalayaSamiti, New Delhi; KendriyaVidyalayaSangathan, New Delhi; National Council for Teachers . www.cbse.nic. in www.ncert.nic .in www.nos.org www.ctsa.nic.i n www.navoday a.nic.in www.kvsangat han.nic.in www.ncte- india.org http://www.nrdcindia.com/ http://www.nrdcindia.com/ http://www.cbse.nic.in/ http://www.cbse.nic.in/ http://www.ncert.nic.in/ http://www.ncert.nic.in/ http://www.nos.org/ http://www.ctsa.nic.in/ http://www.ctsa.nic.in/ http://www.navodaya.nic.in/ http://www.navodaya.nic.in/ http://www.kvsangathan.nic.in/ http://www.kvsangathan.nic.in/ http://www.ncte-india.org/ http://www.ncte-india.org/ IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 34 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 APPENDIX II Ranking of CFs under various dimensions for effective III Ranking of CFs of “Financial interactions” dimension Maximum Eigen Value= 7.32176; C.I. = 0.0536266 Pair wise comparison matrix of CFs of “Financial interactions” dimension 1.1 1.2 1.3 1.4 1.5 1.6 1.7 Global Priority Weighting Rank 1.1 1 0.5 1 1 0.25 0.5 0.25 0.0723 6th 1.2 2 1 1 1 0.5 0.5 0.5 0.1045 5th 1.3 1 1 1 0.5 0.25 0.25 0.25 0.0637 7th 1.4 1 1 2 1 1 1 1 0.1452 4th 1.5 4 2 4 0.5 1 1 0.5 0.1891 2nd 1.6 2 2 4 0.5 1 1 0.5 0.1694 3rd 1.7 4 2 4 1 2 2 1 0.2558 1st Ranking of CFs of “Government/nation/regulatory perspectives” dimension Maximum Eigen Value= 6.25234; C.I. = 0.0504681 Pair wise comparison matrix of CFs of “Government/nation/regulatory perspectives” dimension 2.1 2.2 2.3 2.4 2.5 2.6 Global Priority Weighting Rank 2.1 1 1 0.25 0.25 0.2 1 0.0726 6th 2.2 1 1 0.5 0.333 0.333 0.5 0.0801 5th 2.3 4 2 1 1 2 2 0.2625 1st 2.4 4 3 1 1 1 2 0.2415 2nd 2.5 5 3 0.5 1 1 1 0.2109 3rd 2.6 1 2 0.5 0.5 1 1 0.1324 4th Ranking of CFs of “Technical interactions” dimension Maximum Eigen Value= 5.23553; C.I. = 0.0588814 Pair wise comparison matrix of CFs of “Technical interactions” dimension 3.1 3.2 3.3 3.4 3.5 Global Priority Weighting Rank 3.1 1 1 0.5 1 0.333 0.1352 5th 3.2 1 1 2 1 0.5 0.1934 2nd 3.3 2 0.5 1 1 0.5 0.1686 4th 3.4 1 1 1 1 1 0.1910 3rd 3.5 3 2 2 1 1 0.3118 1st Ranking of CFs of “Markets’ and customers’ interactions” dimension Maximum Eigen Value= 7.77297; C.I. = 0.128829 Pair wise comparison matrix of CFs of “Markets’ and customers’ interactions” dimension 4.1 4.2 4.3 4.4 4.5 4.6 4.7 Global Priority Weighting Rank 4.1 1 0.5 0.333 1 1 0.5 1 0.0974 7th 4.2 2 0.5 1 1 0.5 0.5 1 0.1218 5th 4.3 3 1 1 0.5 1 1 1 0.1466 3rd 4.4 1 1 2 1 1 0.333 0.2 0.1098 6th 4.5 1 2 1 1 1 1 0.5 0.1299 4th 4.6 2 2 1 3 1 1 0.5 0.1707 2nd 4.7 1 1 1 5 2 2 1 0.2238 1st IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 35 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 Ranking of CFs of “Social interactions” dimension Maximum Eigen Value= 5.50371; C.I. = 0.125927 Pair wise comparison matrix of CFs of “Social interactions” dimension 5.1 5.2 5.3 5.4 5.5 Global Priority Weighting Rank 5.1 1 0.5 0.167 2 3 0.1469 3rd 5.2 2 1 0.25 3 2 0.1897 2nd 5.3 6 4 1 4 2 0.4777 1st 5.4 0.5 0.333 0.25 1 0.5 0.0697 5th 5.5 0.333 0.5 0.5 2 1 0.1160 4th Ranking of CFs of “Green and environmental interactions” dimension Maximum Eigen Value=3.01829; C.I. =0.00914735 Pair wise comparison matrix of CFs of “Green and environmental interactions” dimension 6.1 6.2 6.3 Global Priority Weighting Rank 6.1 1 0.5 0.333 0.1692 3rd 6.2 2 1 1 0.3874 2nd 6.3 3 1 1 0.4434 1st Ranking of CFs of “Intellectual properties perspectives” dimension Maximum Eigen Value=3; C.I. = 2.22045e-16 Pair wise comparison matrix of CFs of “Intellectual properties perspectives” dimension 7.1 7.2 7.3 Global Priority Weighting Rank 7.1 1 2 1 0.4 1st 7.2 0.5 1 0.5 0.2 2nd 7.3 1 2 1 0.4 1st Ranking of CFs of “Human resource interactions” dimension Maximum Eigen Value=4.04582; C.I. = 0.0152731 Pair wise comparison matrix of CFs of “Human resource interactions” dimension Ranking of CFs of “Motivation from mutual benefits” dimension Maximum Eigen Value= 3.01829; C.I. =0.00914735 9.1 9.2 9.3 Global Priority Weighting Rank 9.1 1 0.5 0.333 0.1692 3rd 9.2 2 1 1 0.3874 2nd 9.3 3 1 1 0.4434 1st 8.1 8.2 8.3 8.4 Global Priority Weighting Rank 8.1 1 2 1 0.5 0.2326 3rd 8.2 0.5 1 0.5 0.333 0.1238 4th 8.3 1 2 1 1 0.2778 2nd 8.4 2 3 1 1 0.3658 1st IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 36 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 APPENDIX III Global preference weights for CFs by sensitivity analysis when ‘increasing “Dimension 9 (Motivation from mutual benefits)” of CFs changes from 0.1 to 0.9’ CFs for effective III 9=0.1 9=0.1720 (Normal) 9=0.2 9=0.3 9=0.4 9=0.5 9=0.6 9=0.7 9=0.8 9=0.9 1.1 0.0123 0.0113 0.0110 0.0093 0.0082 0.0068 0.0055 0.0041 0.0027 0.0014 1.2 0.0178 0.0164 0.0158 0.0134 0.0119 0.0099 0.0079 0.0059 0.0040 0.0020 1.3 0.0109 0.0100 0.0097 0.0082 0.0072 0.0060 0.0048 0.0036 0.0024 0.0012 1.4 0.0247 0.0228 0.0220 0.0186 0.0165 0.0137 0.0110 0.0082 0.0055 0.0027 1.5 0.0322 0.0297 0.0286 0.0242 0.0215 0.0179 0.0143 0.0107 0.0072 0.0036 1.6 0.0289 0.0266 0.0257 0.0217 0.0192 0.0160 0.0128 0.0096 0.0064 0.0032 1.7 0.0436 0.0401 0.0388 0.0328 0.0291 0.0242 0.0193 0.0145 0.0097 0.0048 2.1 0.0057 0.0052 0.0051 0.0044 0.0038 0.0032 0.0025 0.0019 0.0013 0.0006 2.2 0.0063 0.0058 0.0056 0.0049 0.0042 0.0035 0.0028 0.0021 0.0014 0.0007 2.3 0.0205 0.0189 0.0183 0.0160 0.0137 0.0114 0.0091 0.0068 0.0046 0.0023 2.4 0.0189 0.0174 0.0168 0.0147 0.0126 0.0105 0.0084 0.0063 0.0042 0.0021 2.5 0.0165 0.0152 0.0147 0.0128 0.0110 0.0092 0.0073 0.0055 0.0037 0.0018 2.6 0.0104 0.0095 0.0092 0.0081 0.0069 0.0058 0.0046 0.0035 0.0023 0.0012 3.1 0.0136 0.0125 0.0121 0.0106 0.0091 0.0076 0.0060 0.0045 0.0030 0.0015 3.2 0.0195 0.0179 0.0173 0.0152 0.0130 0.0108 0.0086 0.0065 0.0043 0.0022 3.3 0.0170 0.0156 0.0151 0.0132 0.0113 0.0094 0.0075 0.0057 0.0038 0.0019 3.4 0.0193 0.0177 0.0171 0.0150 0.0128 0.0107 0.0085 0.0064 0.0043 0.0021 3.5 0.0315 0.0289 0.0280 0.0245 0.0210 0.0175 0.0139 0.0105 0.0070 0.0035 4.1 0.0083 0.0076 0.0073 0.0064 0.0055 0.0046 0.0037 0.0028 0.0018 0.0009 4.2 0.0103 0.0095 0.0092 0.0080 0.0069 0.0057 0.0046 0.0034 0.0023 0.0011 4.3 0.0124 0.0114 0.0110 0.0097 0.0083 0.0069 0.0055 0.0041 0.0028 0.0014 4.4 0.0093 0.0086 0.0083 0.0072 0.0062 0.0052 0.0041 0.0031 0.0021 0.0010 4.5 0.0110 0.0101 0.0098 0.0086 0.0073 0.0061 0.0049 0.0037 0.0024 0.0012 4.6 0.0145 0.0133 0.0129 0.0113 0.0096 0.0080 0.0064 0.0048 0.0032 0.0016 4.7 0.0190 0.0175 0.0169 0.0148 0.0126 0.0105 0.0084 0.0063 0.0042 0.0021 5.1 0.0103 0.0094 0.0091 0.0080 0.0068 0.0057 0.0045 0.0034 0.0023 0.0011 5.2 0.0133 0.0122 0.0118 0.0103 0.0088 0.0074 0.0059 0.0044 0.0029 0.0015 5.3 0.0334 0.0307 0.0297 0.0260 0.0223 0.0185 0.0148 0.0111 0.0074 0.0037 5.4 0.0049 0.0045 0.0043 0.0038 0.0032 0.0027 0.0022 0.0016 0.0011 0.0005 5.5 0.0081 0.0075 0.0072 0.0063 0.0054 0.0045 0.0036 0.0027 0.0018 0.0009 6.1 0.0135 0.0124 0.0120 0.0105 0.0090 0.0075 0.0060 0.0045 0.0030 0.0015 6.2 0.0309 0.0284 0.0275 0.0240 0.0206 0.0172 0.0137 0.0103 0.0069 0.0034 6.3 0.0354 0.0325 0.0314 0.0275 0.0236 0.0197 0.0157 0.0118 0.0079 0.0039 7.1 0.0592 0.0545 0.0526 0.0460 0.0395 0.0329 0.0262 0.0197 0.0132 0.0066 7.2 0.0296 0.0272 0.0263 0.0230 0.0197 0.0164 0.0131 0.0099 0.0066 0.0033 7.3 0.0592 0.0545 0.0526 0.0460 0.0395 0.0329 0.0262 0.0197 0.0132 0.0066 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 37 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 8.1 0.0391 0.0359 0.0347 0.0304 0.0260 0.0217 0.0173 0.0130 0.0087 0.0043 8.2 0.0208 0.0191 0.0185 0.0162 0.0139 0.0116 0.0092 0.0069 0.0046 0.0023 8.3 0.0467 0.0429 0.0415 0.0363 0.0311 0.0259 0.0207 0.0156 0.0104 0.0052 8.4 0.0614 0.0565 0.0546 0.0478 0.0410 0.0341 0.0272 0.0205 0.0137 0.0068 9.1 0.0169 0.0291 0.0338 0.0508 0.0677 0.0846 0.1017 0.1184 0.1354 0.1523 9.2 0.0387 0.0666 0.0775 0.1163 0.1550 0.1937 0.2330 0.2712 0.3099 0.3487 9.3 0.0443 0.0763 0.0887 0.1331 0.1774 0.2217 0.2666 0.3104 0.3547 0.3991 IJAHP Article: Kumar, Luthra, Haleem/Critical factors important for effective industry-institute interactions (III): An Indian perspective International Journal of the Analytic Hierarchy Process 38 Vol. 8 Issue 1 2016 ISSN 1936-6744 http://dx.doi.org/10.13033/ijahp.v8i1.319 APPENDIX IV Sensitivity analysis of CFs for effective III in an Indian perspective 0.0000 0.0500 0.1000 0.1500 0.2000 0.2500 0.3000 0.3500 0.4000 0.4500 1.1 1.3 1.5 1.7 2.2 2.4 2.6 3.2 3.4 4.1 4.3 4.5 4.7 5.2 5.4 6.1 6.3 7.2 8.1 8.3 9.1 9.3 9=0.1 9=Normal 9=0.2 9=0.3 9=0.4 9=0.5 9=0.6 9=0.7 9=0.8 9=0.9