Designing a Model of Science, Technology and Innovation Policy in the Regional Innovation System (Case Study: Yazd Province Special Science and Technology Zone)
Subject Areas :علی صفاری دربرزی 1 , habib zare ahmadabadi 2 , seyed reza salami 3 , Davood Andalib Ardakani 4
1 - yazd university
2 - yazd university
3 - allame tabatabayi university
4 - yazd university
Keywords: Science and Technology Policy, Innovation, Regional Innovation System, Interpretive Structural Modeling.,
Abstract :
Due to the complexity of science, technology and innovation system, policymakers and decision-makers are concerned by designing a comprehensive model for policy making in this field. Therefore, it is essential to understand and extract relationships of science, technology and innovation policy indices. The purpose of this research is to identify and establish the link between indices in the form of regional innovation system. For this purpose, in the first step, using the review of the literature of research as well as the use of experts' opinions, the most important dimensions of the model of policymaking of science, technology and innovation were identified. Then, in the next step, interpretive structural modeling technique was used to communicate and sequence between the main dimensions and presenting the relational model. According to the results, 56 indicators in eight main dimensions were ranked in five levels. With the validation of the model, using structural equation modeling, it was determined that the two dimensions of the institutions and resources of science and technology are the basic foundations of science, technology and innovation policy in the special field of science and technology in Yazd province that the policymaking process is practically from these two dimensions of the beginning gets.
Alawamleh, M., & Popplewell, K. (2011). Interpretive structural modelling of risk sources in a virtual organisation. International Journal of Production Research, 49(20), 6041-6063.
Asheim, B. T. and A. Isaksen (2002). Regional Innovations Systems: The Integration of Local `sticky’ and Global `Ubiquitious Knowledge’. The Journal of Technological Transfer 27: 77–88
Asheim, B. T., Smith, H. L., & Oughton, C. (2011). Regional innovation systems: theory, empirics and policy. Regional studies, 45(7), 875-891.
Asheim, B., Isaksen, A., Nauwelaers, C., T¨odtling, F. (Eds.), 2003. Regional Innovation Policy For Small–Medium Enterprises. Edward Elgar, Cheltenham.
Attri, R., Dev, N., & Sharma, V. (2013). Interpretive structural modelling (ISM) approach: an overview. Research Journal of Management Sciences, 2319, 1171.
Bottazzi, L., Peri, G., 2003. Innovation and spillovers in regions: Evidence from European patent data. European Economic Review 47, 687–710.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Chung H (2006) A study on the creative national innovation system in South Korea: focusing on the improvement of regional innovation capability toward balanced national development.
Cooke P, Schienstock G (2000), Structural competitiveness and learning regions. Enterp Innov Manag Stud 1(3):265–280.
Cooke, P. and K. Morgan. (1991). The Network Paradigm: New Departures in Corporate and Regional Development. Environment and Planning D: Society and Space 11(5): 543–564.
Cooke, p.( 2002). Regional Innovation Systems: General Findings and Some New Evidence from Biotechnology Clusters. The Journal of Technology Transfer
Cooke, p.( 2002). Regional Innovation Systems: General Findings and Some New Evidence from Biotechnology Clusters. The Journal of Technology Transfer
Cooke, P., Uranga, M., Etxebarria, G., 1997. Regional innovation systems: Institutional and organizational dimensions, Research Policy (26) 475-491.
Foray, D. (2014). Smart specialisation: Opportunities and challenges for regional innovation policy. Routledge.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 382-388.
Fritsch, M., & Slavtchev, V. (2010). How does industry specialization affect the efficiency of regional innovation systems?. The Annals of Regional Science, 45(1), 87-108.
Isaacson, W. 2011. Steve Jobs: The exclusive biography. London: Hachette Digital, Little Brown Book Group
Jann, Werner and Wegrich, Kai. (2006). Theories Of The Policy Cycle, in: Fischer, Frank; Miller, Gerald J. & Sidney, Mara S. (eds.), "Handbook of Public Policy Analysis: Theory, Methods, and Politics". New York : Marcel Dekker Inc. pp. 43-62
Koo, B. H., & Perkins, D. H. (Eds.). (2016). Social capability and long-term economic growth. Springer.
Lagendijk, A., 2000. Learning in non-core regions: towards ‘Intelligent Clusters’; addressing business and regional needs. In: Boekema, F., Morgan, K., Bakkers, S., Rutten, R. (Eds.), Knowledge, Innovation and Economic Growth. Edward Elgar, Cheltenham, pp. 165–191
Lewis, W. A. (2013). Theory of economic growth. Routledge
Mangla, S. K., Kumar, P., & Barua, M. K. (2014). Flexible decision approach for analysing performance of sustainable supply chains under risks/uncertainty. Global Journal of Flexible Systems Management, 15(2), 113-130.
Moodysson, J., Trippl, M., & Zukauskaite, E. (2018). Policy learning and smart specialization: balancing policy change and continuity for new regional industrial paths. Science and Public Policy, 44(3), 382-391
Nauwelaers, C. and R. Wintjes (2003). Towards a new paradigm for innovation policies?
Padilla-Pérez, R., & Gaudin, Y. (2014). Science, technology and innovation policies in small and developing economies: The case of Central America. Research Policy, 43(4), 749-759.
Power, D., & Malmberg, A. (2008). The contribution of universities to innovation and economic development: in what sense a regional problem?. Cambridge journal of regions, economy and society, 1(2), 233-245.
PytlikZillig, L. M., & Tomkins, A. J. (2011). Public engagement for informing science and technology policy: What do we know, what do we need to know, and how will we get there?. Review of policy research, 28(2), 197-217.
Salami, R., & Soltanzadeh, J. (2012). Comparative analysis for science, technology and innovation policy; lessons learned from some selected countries (Brazil, India, China, South Korea and South Africa) for other LdCs Like Iran. Journal of technology management & innovation, 7(1), 211-227.
Silva, E.D., Silberglitt, R., Machado, L.C., Maia, J.M., Cagnin, C.H., 2017. A portfolio analysis methodology to inform.
Soukup, J. (2017). The Impact of Innovation on Competitiveness and Economic Growth in EU Countries. ICFE 2017, 295.
Tamtik, M. (2018). Policy coordination challenges in governments’ innovation policy—The case of Ontario, Canada. Science and public policy, 44(3), 417-427.
Wolin, S. S. (2016). Politics and vision: Continuity and innovation in Western political thought. Princeton University Press.
Soti, A., Shankar, R., & Kaushal, O. P. (2010). Modeling the enablers of Six Sigma using interpreting structural modeling. Journal of Modelling in Management, 5(2), 124-141.
Soukup, J. (2017). The Impact of Innovation on Competitiveness and Economic Growth in EU Countries. ICFE 2017, 295.
Tamtik, M. (2018). Policy coordination challenges in governments’ innovation policy—The case of Ontario, Canada. Science and public policy, 44(3), 417-427.
Wolin, S. S. (2016). Politics and vision: Continuity and innovation in Western political thought. Princeton University Press.
