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Self–organizing innovation networks : When do Small Worlds emerge ?

Author

Listed:
  • Nicolas Carayol

    (BETA - Bureau d'Économie Théorique et Appliquée - INRA - Institut National de la Recherche Agronomique - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique)

  • Pascale Roux

    (BETA - Bureau d'Économie Théorique et Appliquée - INRA - Institut National de la Recherche Agronomique - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper, we present a model of `collective innovation' built upon the network formation formalism. In our model, agents localized on a circle benefit from knowledge flows from other agents with whom they are directly or indirectly connected. They support costs for direct connections which are linearly increasing with geographic distance. The dynamic process of network formation exhibits preferential meeting for close agents (in the relational network and in the geographic metrics). We show how the set of emergent networks selected in the long run is affected by the degree of knowledge transferability. We find critical values of this parameter for which stable small world networks are dynamically selected.

Suggested Citation

  • Nicolas Carayol & Pascale Roux, 2005. "Self–organizing innovation networks : When do Small Worlds emerge ?," Post-Print hal-00278708, HAL.
    • Handle: RePEc:hal:journl:hal-00278708
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    Cited by:

    1. Tavis Barr, 2009. "With Friends Like These: Endogenous Labor Market Segregation with Homogeneous, Nonprejudiced Agents," American Journal of Economics and Sociology, Wiley Blackwell, vol. 68(3), pages 703-746, July.
    2. Wen Zhou & Nikita Koptyug & Shutao Ye & Yifan Jia & Xiaolong Lu, 2016. "An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-18, January.
    3. Duarte Leite & Pedro Campos & Isabel Mota, 2011. "Computational Results on Membership in R&D Cooperation Networks: To Be or Not To Be in a Research Joint Venture," FEP Working Papers 420, Universidade do Porto, Faculdade de Economia do Porto.
    4. Asef Karimi & Haniye Rezaei & Morteza Akbari & Pantea Foroudi, 2021. "The concept of innovation network: an application of the meta-synthesis approach," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 11(1), pages 399-419, December.
    5. Barr, Tavis & Roy, Udayan, 2008. "The effect of labor market monopsony on economic growth," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1446-1467, December.
    6. Cowan, Robin, 2004. "Network models of innovation and knowledge diffusion," Research Memorandum 016, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).

    More about this item

    Keywords

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    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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