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Research on Stochastic Evolution Game of Green Technology Innovation Alliance of Government, Industry, University, and Research with Fuzzy Income

Author

Listed:
  • Qing Zhong

    (School of Ethnology and History, Guizhou Minzu University, Guiyang 550025, China)

  • Haiyang Cui

    (School of Ethnology and History, Guizhou Minzu University, Guiyang 550025, China)

  • Mei Yang

    (School of Mathematics and Statistics, Guizhou University, Guiyang 550025, China)

  • Cheng Ling

    (School of Economics, Guizhou University, Guiyang 550025, China)

Abstract

At present, the high complexity of the environment, the uncertainty of income, and the choice of strategies have attracted extensive attention from all walks of life who are committed to studying the game of collaborative innovation between government and industry–university–research. Based on this, first of all, with the help of stochastic evolutionary game theory and fuzzy theory, this paper constructs a multi-party stochastic evolutionary game model of green technology innovation about the government guidelines and the joint promotion of industry, universities, and research institutes. Secondly, it discusses the evolution law of behavior strategies of each game subject and the main factors to maintain the alliance’s stability under fuzzy income. The numerical simulation results show the following: (1) Reputation gains have a significant positive correlation with the evolution stability of alliance behavior, and the incorporation of reputation gains or losses will effectively maintain the cooperation stability of the alliance. (2) Under the influence of product greenness, government subsidies, and long-term benefits, it will promote the pace consistency of cooperative decision-making between industry, universities, and research institutes, and accelerate the evolution of alliances. (3) The enterprise’s ability and the research party’s ability will restrict each other. When one party’s ability is low, its willingness to choose a cooperation strategy may be slightly low due to technology spillover and other reasons. When the two parties’ abilities match, their behavior strategies will increase their willingness to cooperate with their abilities. Compared with the traditional evolutionary game, this study fully considers the uncertainty of the environment and provides theoretical support and practical guidance for the high-quality development strategy of the industry–university–research green technology innovation alliance.

Suggested Citation

  • Qing Zhong & Haiyang Cui & Mei Yang & Cheng Ling, 2025. "Research on Stochastic Evolution Game of Green Technology Innovation Alliance of Government, Industry, University, and Research with Fuzzy Income," Sustainability, MDPI, vol. 17(5), pages 1-21, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:2294-:d:1606595
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    References listed on IDEAS

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    1. Binmore, Ken, 2007. "Playing for Real: A Text on Game Theory," OUP Catalogue, Oxford University Press, number 9780195300574.
    2. Cabrales, Antonio, 2000. "Stochastic Replicator Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(2), pages 451-481, May.
    3. Wallace, Chris & Young, H. Peyton, 2015. "Stochastic Evolutionary Game Dynamics," Handbook of Game Theory with Economic Applications,, Elsevier.
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    Cited by:

    1. Ye Tian, 2026. "Green innovation through government-bank-enterprise collaboration: perspective of evolutionary game with randomly disturbance," Operational Research, Springer, vol. 26(1), pages 1-33, January.

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