Zhou Wen, Koptyug Nikita, Ye Shutao, Jia Yifan, Lu Xiaolong
School of Computer Engineering and Science, Shanghai University, Shanghai, China.
Kellogg School of Management, Northwestern Institute on Complex Systems (NICO), Northwestern University, Evanston, Illinois, United States of America.
PLoS One. 2016 Jan 8;11(1):e0145407. doi: 10.1371/journal.pone.0145407. eCollection 2016.
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.
随着计算机科学和复杂网络理论的发展，非合作博弈及其在复杂网络上的形成与应用一直是重要的研究课题。在企业间创新网络中，企业对其联盟伙伴进行投资是一种典型的博弈行为。考虑到企业可能受到资源限制的可能性，本文以纳什讨价还价解作为企业间创新网络中企业间的分配规则，分析了一个协调博弈。我们基于非理想化条件构建了一个扩展的企业间n人博弈，描述了四种投资策略，并在企业间创新网络上对这些策略进行模拟，以比较它们的性能。通过分析我们的实验结果，我们发现我们提出的贪婪策略在大多数情况下表现最佳。我们希望这项研究能为企业如何做出投资决策提供理论见解。
