How to cite this paper
Mosayebi, A., Ghorbani, S & Masoomi, B. (2020). Applying fuzzy delphi and best-worst method for identifying and prioritizing key factors affecting on university-industry collaboration.Decision Science Letters , 9(1), 107-118.
Refrences
Agrawal, A. K. (2001). University‐to‐industry knowledge transfer: Literature review and unanswered questions. International Journal of Management Reviews, 3(4), 285-302.
Amabile, T. M., Patterson, C., Mueller, J., Wojcik, T., Odomirok, P. W., Marsh, M., & Kramer, S. J. (2001). Academic-practitioner collaboration in management research: A case of cross-profession collaboration. Academy of Management Journal, 44(2), 418-431.
Baba, Y., Shichijo, N., & Sedita, S. R. (2009). How do collaborations with universities affect firms’ innovative performance? The role of “Pasteur scientists” in the advanced materials field. Research Policy, 38(5), 756-764.
Bäck, I., & Kohtamäki, M. (2015). Boundaries of R&D collaboration. Technovation, 45, 15-28.
Barnes, T., Pashby, I., & Gibbons, A. (2002). Effective university–industry interaction:: A multi-case evaluation of collaborative r&d projects. European Management Journal, 20(3), 272-285.
Bedwell, W. L., Wildman, J. L., DiazGranados, D., Salazar, M., Kramer, W. S., & Salas, E. (2012). Collaboration at work: An integrative multilevel conceptualization. Human Resource Management Review, 22(2), 128-145.
Bercovitz, J., & Feldman, M. (2008). Academic entrepreneurs: Organizational change at the individual level. Organization Science, 19(1), 69-89.
Brockliss, L. (2000). Gown and town: The university and the city in Europe, 1200–2000. Minerva, 38(2), 147-170.
Charles, D. (2003). Universities and territorial development: reshaping the regional role of UK universities. Local Economy, 18(1), 7-20.
Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152.
Dalkey, N., & Helmer, O. (1963). An experimental application of the Delphi method to the use of experts. Management Science, 9(3), 458-467.
D’Este, P., & Patel, P. (2007). University–industry linkages in the UK: What are the factors underlying the variety of interactions with industry?. Research Policy, 36(9), 1295-1313.
Duru, O., Bulut, E., & Yoshida, S. (2012). A fuzzy extended DELPHI method for adjustment of statistical time series prediction: An empirical study on dry bulk freight market case. Expert Systems with Applications, 39(1), 840-848.
Etzkowitz, H. (2001). The second academic revolution and the rise of entrepreneurial science. IEEE Technology and Society Magazine, 20(2), 18-29.
Etzkowitz, H., Webster, A., Gebhardt, C., & Terra, B. R. C. (2000). The future of the university and the university of the future: evolution of ivory tower to entrepreneurial paradigm. Research Policy, 29(2), 313-330.
Eun, J. H., Lee, K., & Wu, G. (2006). Explaining the “University-run enterprises” in China: A theoretical framework for university–industry relationship in developing countries and its application to China. Research Policy, 35(9), 1329-1346.
Franklin, S. J., Wright, M., & Lockett, A. (2001). Academic and surrogate entrepreneurs in university spin-out companies. The Journal of Technology Transfer, 26(1-2), 127-141.
Giuliani, E., & Arza, V. (2009). What drives the formation of ‘valuable’university–industry linkages?: Insights from the wine industry. Research policy, 38(6), 906-921..
Iqbal, A. M., Khan, A. S., Iqbal, S., & Senin, A. A. (2011). Designing of success criteria-based evaluation model for assessing the research collaboration between university and industry. International Journal of Business Research and Management, 2(2), 59-73.
Kardaras, D. K., Karakostas, B., & Mamakou, X. J. (2013). Content presentation personalisation and media adaptation in tourism web sites using Fuzzy Delphi Method and Fuzzy Cognitive Maps. Expert Systems with Applications, 40(6), 2331-2342.
Kaufmann, A., & Gupta, M. M. (1988). Fuzzy mathematical models in engineering and management science. Elsevier Science Inc.
Langford, C. H., Hall, J., Josty, P., Matos, S., & Jacobson, A. (2006). Indicators and outcomes of Canadian university research: Proxies becoming goals?. Research policy, 35(10), 1586-1598.
Lundberg, J., Tomson, G., Lundkvist, I., Sk? r, J., & Brommels, M. (2006). Collaboration uncovered: Exploring the adequacy of measuring university-industry collaboration through co-authorship and funding. Scientometrics, 69(3), 575-589.
Luoma, P., Raivio, T., Tommila, P., Lunabba, J., Halme, K., Viljamaa, K., & Lahtinen, H. (2011). Better results, more value. A framework for Analysing the societal impact of Research and Innovation. Tekes review, 288, 2011.
Ma, Z., Shao, C., Ma, S., & Ye, Z. (2011). Constructing road safety performance indicators using fuzzy delphi method and grey delphi method. Expert Systems with Applications, 38(3), 1509-1514.
Park, H. W., & Leydesdorff, L. (2010). Longitudinal trends in networks of university–industry–government relations in South Korea: The role of programmatic incentives. Research policy, 39(5), 640-649.
Perkmann, M., Neely, A., & Walsh, K. (2011). How should firms evaluate success in university–industry alliances? A performance measurement system. R&D Management, 41(2), 202-216.
Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., ... & Krabel, S. (2013). Academic engagement and commercialisation: A review of the literature on university–industry relations. Research policy, 42(2), 423-442.
Rasmussen, E., & Borch, O. J. (2010). University capabilities in facilitating entrepreneurship: A longitudinal study of spin-off ventures at mid-range universities. Research Policy, 39(5), 602-612.
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130.
Saaty, T. L. (2004). Decision making—the analytic hierarchy and network processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1-35.
Santoro, M. D. (2000). Success breeds success: The linkage between relationship intensity and tangible outcomes in industry–university collaborative ventures. The Journal of High Technology Management Research, 11(2), 255-273.
Santoro, M. D., & Chakrabarti, A. K. (2002). Firm size and technology centrality in industry–university interactions. Research Policy, 31(7), 1163-1180.
Seppo, M., & Lilles, A. (2012). Indicators measuring university-industry cooperation. Journal of Instrumentation, 204-225.
Siegel, D. S., Waldman, D., & Link, A. (2003). Assessing the impact of organizational practices on the relative productivity of university technology transfer offices: an exploratory study. Research Policy, 32(1), 27-48.
Steinmo, M., & Rasmussen, E. (2016). How firms collaborate with public research organizations: The evolution of proximity dimensions in successful innovation projects. Journal of Business Research, 69(3), 1250-1259.
Tijssen, R. J., Van Leeuwen, T. N., & Van Wijk, E. (2009). Benchmarking university-industry research cooperation worldwide: performance measurements and indicators based on co-authorship data for the world's largest universities. Research Evaluation, 18(1), 13-24.
Tsasis, P. (2009). The social processes of interorganizational collaboration and conflict in nonprofit organizations. Nonprofit Management and Leadership, 20(1), 5-21.
Tuunainen, J., & Knuuttila, T. (2009). Intermingling academic and business activities: A new direction for science and universities?. Science, Technology, & Human Values, 34(6), 684-704.
Venkataraman, S. (1997). The distinctive domain of entrepreneurship research: an editor's perspective. In: Katz, J.A. (Ed.), Advances in Entrepreneurship, Firm Emergence and Growth. JAI Press, Greenwich, CT.
Villani, E., Rasmussen, E., & Grimaldi, R. (2017). How intermediary organizations facilitate university–industry technology transfer: A proximity approach. Technological Forecasting and Social Change, 114, 86-102.
Vohora, A., Wright, M., & Lockett, A. (2004). Critical junctures in the development of university high-tech spinout companies. Research Policy, 33(1), 147-175.
Amabile, T. M., Patterson, C., Mueller, J., Wojcik, T., Odomirok, P. W., Marsh, M., & Kramer, S. J. (2001). Academic-practitioner collaboration in management research: A case of cross-profession collaboration. Academy of Management Journal, 44(2), 418-431.
Baba, Y., Shichijo, N., & Sedita, S. R. (2009). How do collaborations with universities affect firms’ innovative performance? The role of “Pasteur scientists” in the advanced materials field. Research Policy, 38(5), 756-764.
Bäck, I., & Kohtamäki, M. (2015). Boundaries of R&D collaboration. Technovation, 45, 15-28.
Barnes, T., Pashby, I., & Gibbons, A. (2002). Effective university–industry interaction:: A multi-case evaluation of collaborative r&d projects. European Management Journal, 20(3), 272-285.
Bedwell, W. L., Wildman, J. L., DiazGranados, D., Salazar, M., Kramer, W. S., & Salas, E. (2012). Collaboration at work: An integrative multilevel conceptualization. Human Resource Management Review, 22(2), 128-145.
Bercovitz, J., & Feldman, M. (2008). Academic entrepreneurs: Organizational change at the individual level. Organization Science, 19(1), 69-89.
Brockliss, L. (2000). Gown and town: The university and the city in Europe, 1200–2000. Minerva, 38(2), 147-170.
Charles, D. (2003). Universities and territorial development: reshaping the regional role of UK universities. Local Economy, 18(1), 7-20.
Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152.
Dalkey, N., & Helmer, O. (1963). An experimental application of the Delphi method to the use of experts. Management Science, 9(3), 458-467.
D’Este, P., & Patel, P. (2007). University–industry linkages in the UK: What are the factors underlying the variety of interactions with industry?. Research Policy, 36(9), 1295-1313.
Duru, O., Bulut, E., & Yoshida, S. (2012). A fuzzy extended DELPHI method for adjustment of statistical time series prediction: An empirical study on dry bulk freight market case. Expert Systems with Applications, 39(1), 840-848.
Etzkowitz, H. (2001). The second academic revolution and the rise of entrepreneurial science. IEEE Technology and Society Magazine, 20(2), 18-29.
Etzkowitz, H., Webster, A., Gebhardt, C., & Terra, B. R. C. (2000). The future of the university and the university of the future: evolution of ivory tower to entrepreneurial paradigm. Research Policy, 29(2), 313-330.
Eun, J. H., Lee, K., & Wu, G. (2006). Explaining the “University-run enterprises” in China: A theoretical framework for university–industry relationship in developing countries and its application to China. Research Policy, 35(9), 1329-1346.
Franklin, S. J., Wright, M., & Lockett, A. (2001). Academic and surrogate entrepreneurs in university spin-out companies. The Journal of Technology Transfer, 26(1-2), 127-141.
Giuliani, E., & Arza, V. (2009). What drives the formation of ‘valuable’university–industry linkages?: Insights from the wine industry. Research policy, 38(6), 906-921..
Iqbal, A. M., Khan, A. S., Iqbal, S., & Senin, A. A. (2011). Designing of success criteria-based evaluation model for assessing the research collaboration between university and industry. International Journal of Business Research and Management, 2(2), 59-73.
Kardaras, D. K., Karakostas, B., & Mamakou, X. J. (2013). Content presentation personalisation and media adaptation in tourism web sites using Fuzzy Delphi Method and Fuzzy Cognitive Maps. Expert Systems with Applications, 40(6), 2331-2342.
Kaufmann, A., & Gupta, M. M. (1988). Fuzzy mathematical models in engineering and management science. Elsevier Science Inc.
Langford, C. H., Hall, J., Josty, P., Matos, S., & Jacobson, A. (2006). Indicators and outcomes of Canadian university research: Proxies becoming goals?. Research policy, 35(10), 1586-1598.
Lundberg, J., Tomson, G., Lundkvist, I., Sk? r, J., & Brommels, M. (2006). Collaboration uncovered: Exploring the adequacy of measuring university-industry collaboration through co-authorship and funding. Scientometrics, 69(3), 575-589.
Luoma, P., Raivio, T., Tommila, P., Lunabba, J., Halme, K., Viljamaa, K., & Lahtinen, H. (2011). Better results, more value. A framework for Analysing the societal impact of Research and Innovation. Tekes review, 288, 2011.
Ma, Z., Shao, C., Ma, S., & Ye, Z. (2011). Constructing road safety performance indicators using fuzzy delphi method and grey delphi method. Expert Systems with Applications, 38(3), 1509-1514.
Park, H. W., & Leydesdorff, L. (2010). Longitudinal trends in networks of university–industry–government relations in South Korea: The role of programmatic incentives. Research policy, 39(5), 640-649.
Perkmann, M., Neely, A., & Walsh, K. (2011). How should firms evaluate success in university–industry alliances? A performance measurement system. R&D Management, 41(2), 202-216.
Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., ... & Krabel, S. (2013). Academic engagement and commercialisation: A review of the literature on university–industry relations. Research policy, 42(2), 423-442.
Rasmussen, E., & Borch, O. J. (2010). University capabilities in facilitating entrepreneurship: A longitudinal study of spin-off ventures at mid-range universities. Research Policy, 39(5), 602-612.
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130.
Saaty, T. L. (2004). Decision making—the analytic hierarchy and network processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1-35.
Santoro, M. D. (2000). Success breeds success: The linkage between relationship intensity and tangible outcomes in industry–university collaborative ventures. The Journal of High Technology Management Research, 11(2), 255-273.
Santoro, M. D., & Chakrabarti, A. K. (2002). Firm size and technology centrality in industry–university interactions. Research Policy, 31(7), 1163-1180.
Seppo, M., & Lilles, A. (2012). Indicators measuring university-industry cooperation. Journal of Instrumentation, 204-225.
Siegel, D. S., Waldman, D., & Link, A. (2003). Assessing the impact of organizational practices on the relative productivity of university technology transfer offices: an exploratory study. Research Policy, 32(1), 27-48.
Steinmo, M., & Rasmussen, E. (2016). How firms collaborate with public research organizations: The evolution of proximity dimensions in successful innovation projects. Journal of Business Research, 69(3), 1250-1259.
Tijssen, R. J., Van Leeuwen, T. N., & Van Wijk, E. (2009). Benchmarking university-industry research cooperation worldwide: performance measurements and indicators based on co-authorship data for the world's largest universities. Research Evaluation, 18(1), 13-24.
Tsasis, P. (2009). The social processes of interorganizational collaboration and conflict in nonprofit organizations. Nonprofit Management and Leadership, 20(1), 5-21.
Tuunainen, J., & Knuuttila, T. (2009). Intermingling academic and business activities: A new direction for science and universities?. Science, Technology, & Human Values, 34(6), 684-704.
Venkataraman, S. (1997). The distinctive domain of entrepreneurship research: an editor's perspective. In: Katz, J.A. (Ed.), Advances in Entrepreneurship, Firm Emergence and Growth. JAI Press, Greenwich, CT.
Villani, E., Rasmussen, E., & Grimaldi, R. (2017). How intermediary organizations facilitate university–industry technology transfer: A proximity approach. Technological Forecasting and Social Change, 114, 86-102.
Vohora, A., Wright, M., & Lockett, A. (2004). Critical junctures in the development of university high-tech spinout companies. Research Policy, 33(1), 147-175.