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Evolutionary Game Analysis of Complex Networks in Enterprise Green Technology Innovation From a Prospect Theory Perspective

Author

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  • Wu Guancen
  • Chen Xuan
  • Niu Xing

Abstract

Green technological innovation in enterprises is a key driving force for achieving sustainable development and industrial transformation. However, how enterprises formulate effective innovation strategies by integrating subjective factors with objective market conditions within complex industrial networks remains an area requiring further exploration. This study aims to construct a complex network evolution model based on prospect theory and examines how subjective factors, such as reference points, risk preferences, and loss aversion, influence the adoption of green technology innovation in different network environments. It further explores how network characteristics, including topology, size, and node degree, affect the diffusion of innovation. Numerical analysis results indicate that in scale‐free networks, lowering reference points for enterprise gains, reducing loss aversion, increasing risk preference, expanding network size, and raising average node degree generally promote higher adoption of green technology innovation. In small‐world networks, the dependence on reference points is relatively lower, risk preference and average node degree demonstrate more complex impacts. Additionally, a moderate rewiring probability can enhance green technology innovation adoption in small‐world networks. These findings provide new insights and practical implications for understanding the driving mechanisms of green technological innovation in enterprises. They further emphasize the importance of government interventions tailored to the specific characteristics of industrial networks to effectively facilitate the diffusion of green technological innovation.

Suggested Citation

  • Wu Guancen & Chen Xuan & Niu Xing, 2025. "Evolutionary Game Analysis of Complex Networks in Enterprise Green Technology Innovation From a Prospect Theory Perspective," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(3), pages 1774-1791, April.
    • Handle: RePEc:wly:mgtdec:v:46:y:2025:i:3:p:1774-1791
    DOI: 10.1002/mde.4468
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    References listed on IDEAS

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    1. Du, Kerui & Cheng, Yuanyuan & Yao, Xin, 2021. "Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities," Energy Economics, Elsevier, vol. 98(C).
    2. Lupeng Zhang & Wenbo Chen & Yi Su, 2021. "How Do Innovation Network Structures Affect Knowledge Sharing? A Simulation Analysis of Complex Networks," Complexity, Hindawi, vol. 2021, pages 1-17, January.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
    5. Jamali, Mohammad-Bagher & Rasti-Barzoki, Morteza & Khosroshahi, Hossein & Altmann, Jörn, 2022. "An evolutionary game-theoretic approach to study the technological transformation of the industrial sector toward renewable electricity procurement: A case study of Iran," Applied Energy, Elsevier, vol. 318(C).
    6. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    7. Huang, Xingjun & Lin, Yun & Lim, Ming K. & Zhou, Fuli & Liu, Feng, 2022. "Electric vehicle charging station diffusion: An agent-based evolutionary game model in complex networks," Energy, Elsevier, vol. 257(C).
    8. Luo, Guoliang & Liu, Yingxuan & Zhang, Liping & Xu, Xuan & Guo, Yiwei, 2021. "Do governmental subsidies improve the financial performance of China’s new energy power generation enterprises?," Energy, Elsevier, vol. 227(C).
    9. repec:fth:iniesr:487 is not listed on IDEAS
    10. Yan Li & Jiale Zhang, 2024. "Evolutionary Game Analysis of Low-Carbon Incentive Behaviour of Power Battery Recycling Based on Prospect Theory," Sustainability, MDPI, vol. 16(7), pages 1-24, March.
    11. Chen, Feng & Wu, Bin & Lou, Wen-qian & Zhu, Bo-wen, 2024. "Impact of dual-credit policy on diffusion of technology R & D among automakers: Based on an evolutionary game model with technology-spillover in complex network," Energy, Elsevier, vol. 303(C).
    12. Hosseini-Motlagh, Seyyed-Mahdi & Choi, Tsan-Ming & Johari, Maryam & Nouri-Harzvili, Mina, 2022. "A profit surplus distribution mechanism for supply chain coordination: An evolutionary game-theoretic analysis," European Journal of Operational Research, Elsevier, vol. 301(2), pages 561-575.
    13. Di Ye & Linlin Zheng & Peixu He, 2021. "Industry Cluster Innovation Upgrading and Knowledge Evolution: A Simulation Analysis Based on Small-World Networks," SAGE Open, , vol. 11(3), pages 21582440211, July.
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    Cited by:

    1. Wang, Jianghang & Zhang, Lifei, 2026. "Innovation networks, financial innovation, and enterprise technology diffusion," International Review of Financial Analysis, Elsevier, vol. 109(C).

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