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Definition of a methodology to analyze and measure interactions inside Regional Innovation Systems

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  • Jon Mikel Zabala Iturriagagoitia

    (Institute of Innovation & Knowledge Management. INGENIO CSIC-UPV)

Abstract

The aim of the present thesis proposal is to define a methodology to measure the interactions among the agents involved in a System of Innovation, due to the fact that the literature agrees in a lack of measures in this respect. The conceptualization of Regional Innovation Systems (Cooke and Morgan, 1993) can be understood like an extension and adaptation arisen from the concept of National Innovation Systems defined in the works of Freeman (1987), Nelson (ed., 1993) and Lundvall (ed., 1992) and in the subsequent development of Edquist (ed., 1997). It consist of analyzing the existence of actors (institutions, clusters, universities, industries…) and regional competences, and the interactions into Innovation Networks among them, providing regional authorities with a tool to define policies to increase competitiveness. A first stream work in which relations and flows among the main agents of an Innovation System are shown, is the one made up by the works of Scherer, (1982), Pavitt (1984), Archibugi (1988), Galli and Teubal (1997), DeBresson (ed., 1996). Another is due to Andersen (1992, 1996) on Innovation Systems, using “graph theory” and simulation models (Andersen and Lundvall, 1997). Recently, some different research projects can be found in which relations established among the agents in Innovation Systems are studied (European Planning Studies, Vol. 8, Not. 4, 2000). Besides, diverse simulation models created to measure the characteristics of Innovation Systems in different environments (Simulating Self-Organizing innovation networks” -SEIN-) are also detailed. There is a growing need to elaborate indicators that allow to predict changes in the regional innovation capacity beyond those employed in the linear model. We have also noticed the need to measure other processes such as those related to institutional relations and the creation of networks, in order to evaluate innovation policies (Zenker, 2001; Landabaso, Oughton, Morgan, 2001; Saviotti, 1997; Archibugi, Howells and Michie, eds., 1999). This is supported by the fact that several policies fostering innovation have been defined, such as RIS, RTP, RITTS, etc… In this context, and due to the importance of co-operation practices within Regional Innovation Systems, the present research project tries to contribute with a model as well as an Indicator Scoreboard which helps quantify the interrelations that occur among the agents in an Innovation System.

Suggested Citation

  • Jon Mikel Zabala Iturriagagoitia, 2005. "Definition of a methodology to analyze and measure interactions inside Regional Innovation Systems," Development and Comp Systems 0503002, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpdc:0503002
    Note: Type of Document - pdf; pages: 20. Paper presented at the Augustin Cournot Doctoral Days on Economics, Management and Science & Technology Studies Strasbourg, April 15 -17 2004
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    References listed on IDEAS

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    1. Andreas Pyka & Paolo Saviotti, 2001. "Innovation Networks in the Biotechnology-Based Sectors," Discussion Paper Series 205, Universitaet Augsburg, Institute for Economics.
    2. Carlsson, B & Stankiewicz, R, 1991. "On the Nature, Function and Composition of Technological Systems," Journal of Evolutionary Economics, Springer, vol. 1(2), pages 93-118, April.
    3. Pavitt, Keith, 1984. "Sectoral patterns of technical change: Towards a taxonomy and a theory," Research Policy, Elsevier, vol. 13(6), pages 343-373, December.
    4. Freeman, C., 1991. "Networks of innovators: A synthesis of research issues," Research Policy, Elsevier, vol. 20(5), pages 499-514, October.
    5. Arne Isaksen & Bjørn T. Asheim, "undated". "Location, agglomeration and innovation: Towards regional innovation systems in Norway?," STEP Report series 199613, The STEP Group, Studies in technology, innovation and economic policy.
    6. Pier Paolo Saviotti (ed.), 2003. "Applied Evolutionary Economics," Books, Edward Elgar Publishing, number 2560.
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    JEL classification:

    • O - Economic Development, Innovation, Technological Change, and Growth
    • P - Political Economy and Comparative Economic Systems

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