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An Extended N-player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network

Author

Listed:
  • Zhou, Wen

    () (School of Computer Engineering and Science)

  • Koptyug, Nikita

    () (Research Institute of Industrial Economics (IFN))

  • Ye, Shutao

    (School of Computer Engineering and Science)

  • Jia, Yifan

    (School of Computer Engineering and Science)

  • Lu, Xiaolong

    (School of Computer Engineering and Science)

Abstract

As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.

Suggested Citation

  • Zhou, Wen & Koptyug, Nikita & Ye, Shutao & Jia, Yifan & Lu, Xiaolong, 2015. "An Extended N-player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network," Working Paper Series 1097, Research Institute of Industrial Economics.
  • Handle: RePEc:hhs:iuiwop:1097
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    References listed on IDEAS

    as
    1. Von Stengel, Bernhard, 2002. "Computing equilibria for two-person games," Handbook of Game Theory with Economic Applications,in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 3, chapter 45, pages 1723-1759 Elsevier.
    2. Carayol, Nicolas & Roux, Pascale, 2005. "Self-organizing Innovation Networks: When do Small Worlds Emerge?," European Journal of Economic and Social Systems, Lavoisier, vol. 18(2), pages 307-332.
    3. Freeman, C., 1991. "Networks of innovators: A synthesis of research issues," Research Policy, Elsevier, vol. 20(5), pages 499-514, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Complex Networks; Game Theory; Innovation; Innovation Network; Nash Equilibrium;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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