IDEAS home Printed from
   My bibliography  Save this paper

Policy Simulation of Firms Cooperation in Innovation


  • Heshmati, Almas

    () (Centre of Excellence for Science and Innovation Studies (CESIS), & Department of Economics, Sogang University)

  • Lenz-Cesar, Flávio

    () (Ministry of Communications, Esplanada dos Ministério)


This study utilizes results from an agent-based simulation model to conduct public policy simulation of firms’ networking and cooperation in innovation. The simulation game investigates the differences in sector responses to internal and external changes, including cross-sector spillovers, when applying three different policy strategies to promote cooperation in innovation. The public policy strategies include clustering to develop certain industries, incentives to encourage cooperative R&D and spin-off policies to foster entrepreneurship among R&D personnel. These policies are compared with the no-policy alternative evolving from the initial state serving as a benchmark to verify the gains (or loses) in the number of firms cooperating and networking. Firms’ behavior is defined according to empirical findings from analysis of determinants of firms’ participation in cooperation in innovation with other organizations using the Korean Innovation Survey. The analysis based on manufacturing sector data shows that firms’ decision to cooperate with partners is primarily affected positively by firm’s size and the share of employees involved in R&D activities. Then, each cooperative partnership is affected by a different set of determinants. The agent-based models are found to have a great potential to be used in decision support systems for policy makers. The findings indicate possible appropriate policy strategies to be applied depending on the target industries. We have applied few examples and showed how the results may be interpreted. Guidelines are provided on how to generalize the model to include a number of extensions that can serve as an optimal direction for future research in this area.

Suggested Citation

  • Heshmati, Almas & Lenz-Cesar, Flávio, 2014. "Policy Simulation of Firms Cooperation in Innovation," Working Paper Series in Economics and Institutions of Innovation 357, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
  • Handle: RePEc:hhs:cesisp:0357

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. d'Aspremont, Claude & Jacquemin, Alexis, 1988. "Cooperative and Noncooperative R&D in Duopoly with Spillovers," American Economic Review, American Economic Association, vol. 78(5), pages 1133-1137, December.
    2. David J. Teece, 2003. "Competition, Cooperation, and Innovation Organizational Arrangements for Regimes of Rapid Technological Progress," World Scientific Book Chapters,in: Essays In Technology Management And Policy Selected Papers of David J Teece, chapter 16, pages 447-474 World Scientific Publishing Co. Pte. Ltd..
    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. Piergiuseppe Morone & Richard Taylor, 2012. "Proximity, knowledge integration and innovation: an agenda for agent-based studies," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 19-47, January.
    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. Nigel Gilbert & Andreas Pyka & Petra Ahrweiler, 2001. "Innovation Networks - a Simulation Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(3), pages 1-8.
    9. Belderbos, Rene & Carree, Martin & Lokshin, Boris, 2004. "Cooperative R&D and firm performance," Research Policy, Elsevier, vol. 33(10), pages 1477-1492, December.
    10. Albino, Vito & Carbonara, Nunzia & Giannoccaro, Ilaria, 2006. "Innovation in industrial districts: An agent-based simulation model," International Journal of Production Economics, Elsevier, vol. 104(1), pages 30-45, November.
    11. 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.
    12. 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.
    13. 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.
    14. Jon Sigurdson, 1998. "Industry and State Partnership: The Historical Role of Theengineering Research Associations in Japan," Industry and Innovation, Taylor & Francis Journals, vol. 5(2), pages 209-241.
    15. Flávio Lenz-Cesar & Almas Heshmati, 2012. "An econometric approach to identify determinants of cooperation for innovation among firms," Applied Economics Letters, Taylor & Francis Journals, vol. 19(3), pages 227-235, February.
    16. Matteo Richiardi, 2007. "Agent-based Computational Economics. A Short Introduction," LABORatorio R. Revelli Working Papers Series 69, LABORatorio R. Revelli, Centre for Employment Studies.
    17. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    Full references (including those not matched with items on IDEAS)

    More about this item


    agent-based simulation; collaborative R&D; innovation networks; simulation game; policy strategy;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:cesisp:0357. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vardan Hovsepyan). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.