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Network-based policies and innovation networks in two Italian regions: a comparison through a social selection model
Titolo Rivista: STUDI ECONOMICI  
Autori/Curatori: Ivan Cucco 
Anno di pubblicazione:  2014 Fascicolo: 114  Lingua: Inglese 
Numero pagine:  19 P. 78-96 Dimensione file:  154 KB
DOI:  10.3280/STE2014-114004
Il DOI è il codice a barre della proprietà intellettuale: per saperne di più:  clicca qui   qui 


This paper compares the innovation networks generated by two network-based policies (NBPs) implemented in two Italian regions. Social Network Analysis was used to understand whether the networks differ in their local configurations and in the role played by research institutions. To this aim, Exponential Random Graph Models (ERGMs) were estimated on relational data recording joint participation in collaborative R&D projects. Results indicate that the two networks emerge from different local-level processes. In the first case a core-periphery structure arises from degree centralization driven by one focal actor. In the second case, although transitive closure across projects cannot be realized, the overall structure is more balanced. In the first network, however, companies and research organizations show a higher propensity towards joint participation in collaborative projects. Further research is required to understand whether these characteristics can be ascribed to the policy design or to the greater sectoral diversification of the first network.


Keywords: Innovation policies; technological districts; Triple Helix; Social Network Analysis; Exponential Random Graph Models; Social Selection Model
Jel Code: O38, R58

  1. Cantner U., Meder A., Ter Wal A.L.J. (2010), Innovator networks and regional knowledge base, Technovation, 30, 9-10, 496-507.
  2. Cooke P., Leydesdorff L. (2006), Regional Development in the Knowledge-Based Economy: The Construction of Advantage, Journal of Technology Transfer, 31, 5 -15.
  3. Cooke P., Uranga M.G., Etxebarria G. (1997), Regional innovation systems: Institutional and organisational dimensions, Research Policy, 26, 4-5, 475-491.
  4. Dolfsma W., Seo D. (2013), Government policy and technological innovation – a suggested typology, Technovation, 33, 6-7, 173-179.
  5. Etzkowitz H., Leydesdorff L. (eds.) (1997), Universities and the global knowledge economy: A Triple Helix of university-industry-government relations, Cassell, London.
  6. 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, 109-123.
  7. Freeman C. (1997), The diversity of national research systems, in Barre R. (ed.), Science in Tomorrow’s Europe, pp. 5-32, Economica International, Paris.
  8. Gibbons M., Limoges C., Nowotny H., Schwartzman S., Scott P., Trow M. (1994), The new production of knowledge: The dynamics of science and research in contemporary societies, Sage, London.
  9. Glückler J. (2007), Economic geography and the evolution of networks, Journal of Economic Geography, 7, 619-634.
  10. Handcock M.S., Hunter D.R., Butts C.T., Goodreau S.M., Krivitsky P.N., Morris M. (2013), ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks. The Statnet Project. R package version 3.1-0.
  11. Hessels L.K., van Lente H. (2008), Re-thinking new knowledge production: A literature review and a research agenda, Research Policy, 37, 740-760.
  12. Hunter D.R. (2007), Curved Exponential Family Models for Social Networks, Social Networks, 81, 29, 216-230.
  13. Hunter D.R., Handcock M.S., Butts C.T., Goodreau S.M., Morris M. (2008), ergm: A package to fit, simulate and diagnose exponential-family models for networks, Journal of Statistical Software, 24, 3. Leydesdorff L., Meyer M. (2003), The Triple Helix of university-industrygovernment relations, Scientometrics, 58, 2, 191-203.
  14. Leydesdorff L., Meyer M. (2006), Triple Helix indicators of knowledge-based innovation systems Introduction to the special issue, Research Policy, 35, 1441-1449.
  15. Leydesdorff L., Zawdie G. (2010), The Triple Helix Perspective of Innovation Systems, Technology Analysis and Strategic Management, 22, 7.
  16. Lundvall B.-Å. (1988), Innovation as an interactive process: From user-producer interaction to the national system of innovation, in Dosi G., Freeman C., Nelson R., Silverberg G., Soete L. (eds.), Technical Change and Economic Theory, pp. 349-369, Pinter, London.
  17. Nowotny H., Scott P., Gibbons M. (2001), Re-Thinking Science: Knowledge and the Public in an Age of Uncertainty, Polity Press, Cambridge.
  18. Pattison P.E., Wasserman S. (1999), Logit models and logistic regressions for social networks: II. Multivariate relations, British Journal of Mathematical and Statistical Psychology, 52, 169-194.
  19. Philpott K., Dooley L., O’Reilly C., Lupton G. (2011), The entrepreneurial university: Examining the underlying academic tensions, Technovation, 31, 4: 161-170.
  20. Robins G.L., Elliott P., Pattison P.E. (2001), Network models for social selection processes, Social Networks, 23, 1: 1-30.
  21. Robins G., Pattison P., Kalish Y., Lusher D. (2007), An introduction to exponential random graph (p*) models for social networks, Social Networks, 29, 2: 173-191.
  22. Robins G.L., Pattison P.E., Wasserman S. (1999), Logit models and logistic regressions for social networks, III. Valued relations, Psychometrika, 64: 371-394.
  23. Robins G.L., Pattison P.E., Woolcock J. (2005), Small and other worlds: Global network structures from local processes, American Journal of Sociology, 110, 4: 894-936.
  24. Robins G., Snijders T., Wang P., Handcock M., Pattison P. (2007), Recent developments in exponential random graph (p*) models for social networks, Social Networks, 29, 2: 192-215.
  25. Salavisa I., Sousa C., Fontes M. (2012), Topologies of innovation networks in knowledge-intensive sectors: Sectoral differences in the access to knowledge and complementary assets through formal and informal ties, Technovation, 32, 6: 380-399.
  26. Ter Wal A.L.J., Boschma, R.A. (2009), Applying social network analysis in economic geography: Framing some key analytic issues, Annals in Regional Science, 43: 739-756.
  27. Viale R., Campo dall’Orto S. (2002), An evolutionary triple helix to strengthen academy-industry relations: suggestions from european regions, Science and Public Policy, 29: 154-168.
  28. Viale R., Pozzoli A. (2010), Complex adaptive systems and the evolutionary triple helix, Critical Sociology, 36, 4.
  29. Wasserman S., Pattison P.E. (1996), Logit models and logistic regressions for social networks: I. An introduction to Markov graphs and p*, Psychometrika, 61: 401-425.

Ivan Cucco, in "STUDI ECONOMICI " 114/2014, pp. 78-96, DOI:10.3280/STE2014-114004

   

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