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Determinants of Firms Cooperation in Innovation


  • Flavio Lenz-Cesar
  • Almas Heshmati

    () (Technology Management, Economics and Policy Program(TEMEP), Seoul National University)


R&D cooperation has received great attention among industrialists, decision makers and researchers as it facilitates research collaboration, information sharing, reduced R&D cost, and affects R&D resource allocation, advancement and competitiveness of the national industry, employment and survival of firms. This paper introduces an econometric approach for identifying the factors that lead firms to cooperative innovation. The determinants of firms cooperation in innovation were defined according to empirical findings on a dataset from the internationally standardized Korean Innovation Survey 2005, captured in a multivariate probit regression model. The model identified the determinants on firms¡¯ likelihood to participate in cooperation with other organizations when conducting innovation activities. The aim of this model was to subsidize further research applying agent-based modeling to simulate innovation networks in the Korean manufacturing sector in order to test different policy strategies on fostering cooperation in innovation.

Suggested Citation

  • Flavio Lenz-Cesar & Almas Heshmati, 2009. "Determinants of Firms Cooperation in Innovation," TEMEP Discussion Papers 200927, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
  • Handle: RePEc:snv:dp2009:200927

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    References listed on IDEAS

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    2. Hagedoorn, John & Link, Albert N. & Vonortas, Nicholas S., 2000. "Research partnerships1," Research Policy, Elsevier, vol. 29(4-5), pages 567-586, April.
    3. Bernhard Dachs & Bernd Ebersberger & Andreas Pyka, 2004. "Why do Firms Co-operate for Innovation? - A comparison of Austrian and Finnish CIS 3 results," Discussion Paper Series 255, Universitaet Augsburg, Institute for Economics.
    4. Junfu Zhang, 2004. "Growing Silicon Valley On A Landscape: An Agent-Based Approach To High-Tech Industrial Clusters," World Scientific Book Chapters,in: Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 13, pages 259-283 World Scientific Publishing Co. Pte. Ltd..
    5. Belderbos, Rene & Carree, Martin & Diederen, Bert & Lokshin, Boris & Veugelers, Reinhilde, 2004. "Heterogeneity in R&D cooperation strategies," International Journal of Industrial Organization, Elsevier, vol. 22(8-9), pages 1237-1263, November.
    6. Sakakibara, Mariko, 2001. "Cooperative research and development: who participates and in which industries do projects take place?," Research Policy, Elsevier, vol. 30(7), pages 993-1018, August.
    7. Tesfatsion, Leigh, 2001. "Introduction to the special issue on agent-based computational economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 281-293, March.
    8. Miotti, Luis & Sachwald, Frederique, 2003. "Co-operative R&D: why and with whom?: An integrated framework of analysis," Research Policy, Elsevier, vol. 32(8), pages 1481-1499, September.
    9. Czarnitzki, Dirk & Fier, Andreas, 2003. "Publicly Funded R&D Collaborations and Patent Outcome in Germany," ZEW Discussion Papers 03-24, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    10. Bayona, Cristina & Garcia-Marco, Teresa & Huerta, Emilio, 2001. "Firms' motivations for cooperative R&D: an empirical analysis of Spanish firms," Research Policy, Elsevier, vol. 30(8), pages 1289-1307, October.
    11. Bruno Cassiman & Reinhilde Veugelers, 2002. "R&D Cooperation and Spillovers: Some Empirical Evidence from Belgium," American Economic Review, American Economic Association, vol. 92(4), pages 1169-1184, September.
    12. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    13. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
    14. Heshmati, Almas & Kim, Yee-Kyoung & Kim, Hyesung, 2006. "The Effects of Innovation on Performance of Korean Firms," Ratio Working Papers 90, The Ratio Institute.
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    Cited by:

    1. Stoetzer, Matthias-Wolfgang & Pfeil, Silko & Kaps, Katharina & Sauer, Thomas, 2011. "Regional dispersion of cooperation activities as success factor of innovation oriented SME," Jena Contributions to Economic Research 2011,4, University of Applied Sciences Jena, Department of Business Administration.
    2. Flavio Lenz-Cesar & Almas Heshmati, 2010. "Agent-based Simulation of Cooperative Innovation," TEMEP Discussion Papers 201052, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2010.

    More about this item


    Collaborative R&D; multivariate probit models; Korean innovation survey;

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • D20 - Microeconomics - - Production and Organizations - - - 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

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