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The endogenous formation of scientific research coalitions

Author

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  • Paul David
  • Louise Keely

Abstract

The paper develops a formal model of coalition-building ("network" formation) among research units that seek competitive funding from a supra-regional program, while also drawing support from their respective regional funding agencies. This analysis is motivated by the absence of frameworks of analysis applicable to problems of design of public R&D funding arrangements in the European Union, and in other regional systems were independent programs of "federal and state" support for research co-exists. The model assumes a fixed finite population of research units and an associated distribution of reputed quality, or scientific reputation, which may be modified as a consequence of research results. Non-cooperative games of coalition formation developed by Bloch (1995), and Ray and Vohra (1999), provides a useful single-period framework for this part of the analysis. Collaborations are formed in the expectation of attracting incremental research funding, given the selection criteria of the agency that offers funding for "networks". Invitations to join proposals for networks are initiated and acted upon following a specific ordering procedure. This gives rise to a repeated non-cooperative game of coalition (or collaboration) formation, in which the distribution of payoffs within the collaboration is governed by a fixed rule. Following Keely (2002), this type of game is applied to a multi-period setting in which a distribution of coalitions is tracked, along with the levels of funding received. The latter are determined according to a rule comparing the distribution of reputations within proposed collaborations, and the effects upon the distribution of reputations in the entire population are analysed. Alternative possible external funding rules are evaluated with the help of a numerical example, to determine how their impacts upon collaboration formation, and the resulting evolution of the reputation distribution (as that will be affected by the allocation of funding).

Suggested Citation

  • Paul David & Louise Keely, 2003. "The endogenous formation of scientific research coalitions," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 12(1), pages 93-116.
    • Handle: RePEc:taf:ecinnt:v:12:y:2003:i:1:p:93-116
    DOI: 10.1080/10438590303121
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    Citations

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    Cited by:

    1. Defazio, Daniela & Lockett, Andy & Wright, Mike, 2009. "Funding incentives, collaborative dynamics and scientific productivity: Evidence from the EU framework program," Research Policy, Elsevier, vol. 38(2), pages 293-305, March.
    2. Jackie Krafft & Francesco Quatraro, 2011. "The Dynamics of Technological Knowledge: From Linearity to Recombination," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 7, Edward Elgar Publishing.
    3. Cristiano Antonelli & Gianluigi Ferraris, 2011. "Innovation as an Emerging System Property: An Agent Based Simulation Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(2), pages 1-1.
    4. Cristiano, Antonelli & Ferraris, Gianluigi, 2009. "Innovation as an Emerging System Property: an Agent Based Model," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 200911, University of Turin.
    5. Antonelli, Cristiano, 2010. "From population thinking to organization thinking: Coalitions for innovation. A review article of Complexity perspectives in innovation and social change, by Lane, D.A., van Der Leeuw, S.E., Pumain, D," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201002, University of Turin.
    6. Cristiano Antonelli, 2011. "The Economic Complexity of Technological Change: Knowledge Interaction and Path Dependence," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 1, Edward Elgar Publishing.
    7. Jackie Krafft & Francesco Quatraro, 2011. "The dynamics of technological knowledge," Post-Print halshs-00727633, HAL.

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