Document Type : Original Article

Authors

1 PhD Student in Science and Technology Policy, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

2 Professor, Department of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

The aim of this research is structural modeling the properties and factors affecting the science and technology collaborative policy network in Iran. The research data were collected in both qualitative and quantitative stages. In the qualitative phase, exploratory and semi-structured interviews were conducted with 20 experts, and in the quantitative phase, 100 questionnaires were distributed among the experts. Structural equation modeling using partial least squares (PLS) method has also been used to analyze the data. The results of the research show that the Science and Technology Collaborative Policy Network in Iran has 17 features in four dimensions, in order of importance: actors, codes of conduct, relationships between actors and network structure. There are also eight factors affecting the network in three dimensions, in order of importance: specific science and technology policy factors, national factors, and international factors. The most important policy recommendation of this study is attention to these factors by two groups of audiences: the government and the S&T policymakers.

Keywords

[1]          deLeon, P., Varda, D.M., (2009), Toward a theory of collaborative policy networks: identifying structural tendencies, The policy studies journal, 37(1): 59- 74.
[2]          Kriesi, H., Adam, S. (2007). Network Approach, in Theories of Policy Process, edited by Sabatire, P.A. New York: Westview Press.
[3]          Kalantari E, Montazer G. (2018). Converging evolutions in the future of science and technology: A comparative study of United States, Russia and China. Management Research in Iran; 22 (1):241-274
[4]          Asadifard, R., Tabatabaeian, S.H., Sofi, J.B., Taghva, M.R. (2017). A model for investigating the stability factors in formal science and technology collaborative networks: A case study of Iran, Technological forecasting and social change, 122: 139-150.
[5]          Soofi, A.S., (2017), A comparative study of Chinese and Iranian science and technology and technology industrial development policies, Technological forecasting and social change, 122: 107-118.
[6]          UNCTAD, (2016), Science, technology and innovation policy review: The Islamic Republic of Iran, New York and Geneva: United Nations Publications.
[7]          Zaker-Salehi G. A Survey of Science and Technology Status Quo in Iran and in its Development Plans. JPBUD. 2012; 16 (4):3-47
[8]          Gilchrist, A. (2009). The well-connected community: a networking approach to community development: Policy Press.
[9]          Sabet Sarvestani, M., Moghbel Baarz, A., Afsar, A. (2020). Comparative analysis of the structural attributes of supply network firms in auto industry (social network analysis approach. Modern Researches in Decision Making. 4(4): 59-80.
[10]       Kim, K.D., Hossain, L., (2013), Policy network apprpach to coordinated disaster response, arXiv:1312.3693.
[11]       Peters, D., Klijn E.H., Stronks, K., Harting, J. (2016). Policy coordination and integration, trust, management and performance in public health related policy networks: a survey. International Review of Administrative Sciences.
[12]       Rogelja, T., Shannon, M.A., (2017), Structural power in Serbian anti-corruption forest policy network, Forest Policy and Economics: 1- 9.
[13]       Weishaar, H., Amos, A., Collin, J., (2015), Best of enemies: using social network analysis to explore a policy network in European smoke-free policy, Social science & medicine, 133: 85- 92.
[14]       Sandstrom, A., Carlsson, L., (2008), The performance of policy networks: The relation between network structure and network performance, The policy studies journal, 36(4): 497- 524.
[15]       March, D., Smith, M., (2000), Understanding policy networks: towards a dialectical approach, Political studies, 48: 4- 21.
[16]       Kisby, B., (2007), Analysing policy networks, Policy studies, 28(1): 71- 90.
[17]       Moschitz, H., Stolze, M. (2010). The influence of policy networks on policy output: a comparison of organic farming policy in the Czech Republic and Poland, Food policy, 35: 247- 255.
[18]       Henry, A.D., (2011), Ideology, power, and the structure of policy networks, The policy studies journal, 39(3): 361- 383.
[19]       Henry, A.D., Lubell, M., MaCoy, M., (2010), Bilief systems and social capital as drivers of policy network structure: the case of California regional planning, Journal of public administration research and theory, 21: 419- 444.
[20]       Koranteng, R.O., Larbi, G.A., (2008), Policy networks, politics and decentralization policies in Ghana, Public administration and development, 28: 212- 222.
[21]       Yun, S.J., Ku, D., Han, J.Y., (2014), Climate policy networks in South Korea: alliances and conflicts, Climate Policy, 14(2): 283- 301.
[22]       Moschitz, H., Stolze, M. (2009). Organic farming policy networks in Europe: context, actors and variation, Food policy, 34: 258- 264.
[23]       Rizopoulos, Y., Sergakis, D., (2010), MNEs and policy networks: Institutional embeddedness and strategic choice, Journal of World Business, 45.
[24]       Morris, T.B. (2009). Social networks within policy networks: the case of maine`s climate change action plan, Thesis of Doctor of Philosophy in public policy, The University of Southern Maine.
[25]       Elgin, D.J., (2014), Examining the role of resources, beliefs and behavior in the policy process: a study of Colorado climate and energy politics and policy, Thesis of Doctor of Philosophy, University of Colorado in partial fulfillment,
[26]       Abolhassani, S., Attar, S. (2013). Network analysis, social capitan and politics: an introduction to network politics. Political quarterly, 43(2): 139-157.
[27]       Jahandideh, S., Khanifar, H., Farzan, N. (2015). Creating tourism policy network of Iran. Tourism management studies. 10(30): 1-24.
[28]       Khaje Naieni A., Ashtarian K., Mohammadi Kangarani H. (2014). Network Analysis of Decision Making in Iran’s Nanotechnology Policy Making; Case Study of Nanotechnology Plan. Management Research in Iran. 18 (2):25-54
[29]       Barclay, D., Higgins, C., Thompson, R. (1995). The Partial Least Squares (PLS) approach to causal modeling: personal computer adoption and use as an illustration. Technologies studies. 2(2): 285-309.
[30]       Sarabadani, A., Tabatabaian, S.H., Mir Moezi, S.H., Amiri, M. (2016). Improving the Quality of Policymaking in Science and Technology by an Islamic-Iranian Approach: A Qualitative Study. Modern Researches in Decision Making. 1(1): 167-188.