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Diversity of innovative strategy as a source of technological performance

Author

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  • Vanessa Oltra

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

  • Patrick Llerena

Abstract

This paper explores the impact of diversity of innovative strategies of firms upon the industrial dynamics through a micro-simulation model. We consider two types of firms each one being characterised by a specific innovative strategy. Basically we assume that some cumulative firms adopt an internal learning by searching strategy, while noncumulative firms adopt an external learning strategy aiming at absorbing external sources of knowledge. The results show that the co-existence of the two types of firms leads to an oligopolistic structure characterised by asymmetries in the size of firms and high technological performances. Thus the diversity of innovative strategies generates a diversity in firms market shares and is a source of dynamic efficiency in the long run.
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Suggested Citation

  • Vanessa Oltra & Patrick Llerena, 2002. "Diversity of innovative strategy as a source of technological performance," Post-Print hal-00162913, HAL.
  • Handle: RePEc:hal:journl:hal-00162913
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00162913
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    References listed on IDEAS

    as
    1. Malerba, Franco, 1992. "Learning by Firms and Incremental Technical Change," Economic Journal, Royal Economic Society, vol. 102(413), pages 845-859, July.
    2. Cohen, Wesley M. & Levin, Richard C., 1989. "Empirical studies of innovation and market structure," Handbook of Industrial Organization,in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 2, chapter 18, pages 1059-1107 Elsevier.
    3. Jonard, N. & Yfldizoglu, M., 1998. "Technological diversity in an evolutionary industry model with localized learning and network externalities," Structural Change and Economic Dynamics, Elsevier, vol. 9(1), pages 35-53, March.
    4. J. Stanley Metcalfe, 1992. "Variety, Structure and Change : an evolutionary perspective on the compétitive process," Revue d'Économie Industrielle, Programme National Persée, vol. 59(1), pages 46-61.
    5. Giulio Bottazzi & Giovanni Dosi & Marco Lippi & Fabio Pammolli & Massimo Riccaboni, 2000. "Processes of corporate growth in the evolution of an innovation-driven industry. The case of pharmaceuticals," LEM Papers Series 2000/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Henry G. Grabowski & John M. Vernon, 1987. "Pioneers, Imitators, and Generics — a Simulation Model of Schumpeterian Competition," The Quarterly Journal of Economics, Oxford University Press, vol. 102(3), pages 491-525.
    7. Silverberg, Gerald & Dosi, Giovanni & Orsenigo, Luigi, 1988. "Innovation, Diversity and Diffusion: A Self-organisation Model," Economic Journal, Royal Economic Society, vol. 98(393), pages 1032-1054, December.
    8. Dosi, Giovanni, 1988. "Sources, Procedures, and Microeconomic Effects of Innovation," Journal of Economic Literature, American Economic Association, vol. 26(3), pages 1120-1171, September.
    9. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    10. Malerba, Franco & Orsenigo, Luigi, 1997. "Technological Regimes and Sectoral Patterns of Innovative Activities," Industrial and Corporate Change, Oxford University Press, vol. 6(1), pages 83-117.
    11. Malerba, Franco & Orsenigo, Luigi, 1996. "Schumpeterian patterns of innovation are technology-specific," Research Policy, Elsevier, vol. 25(3), pages 451-478, May.
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    More about this item

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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