IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i16p7194-d1720634.html
   My bibliography  Save this article

An Evolutionary Game Study of Multi-Agent Collaborative Disaster Relief Mechanisms for Agricultural Natural Disasters in China

Author

Listed:
  • Panke Zhang

    (Business School, Henan University of Science and Technology, Luoyang 471023, China)

  • Nan Li

    (Business School, Henan University of Science and Technology, Luoyang 471023, China)

  • Hong Han

    (Business School, Henan University of Science and Technology, Luoyang 471023, China)

Abstract

Natural disasters in agriculture considerably threaten food security and the implementation of the rural revitalization strategy. With the rapid development of new approaches in organizing agricultural production, traditional disaster relief mechanisms are encountering new adaptive dilemmas. Particularly, the active participation of farmers in disaster relief is remarkably insufficient in the context of the reduction in the proportion of agricultural production income. Thus, it is urgent to establish a modernized agricultural disaster relief synergy mechanism. In this study, an agricultural disaster relief synergistic model was constructed with the participation of the government, agricultural service enterprises, and farmers based on the evolutionary game theory, and the strategy interaction law of each subject and its evolution path was systematically analyzed. The following results were revealed: First, the government, agricultural service enterprises, and farmers tended toward an equilibrium state under three different modes. Second, the cost of farmers’ concern and complaint behavior was the crucial driving factor of the three-party synergy. Third, the increasing cost of agricultural service enterprises’ participation in disaster relief significantly affected the evolution path of the system. Additionally, a three-dimensional synergistic optimization path of “incentive-constraint-information” was proposed, laying a quantitative foundation for improving the agricultural disaster relief mechanism and promoting the transition from “passive emergency response” to “active synergy”. This research is of great practical significance to improve the resilience of agricultural disaster response and resource allocation efficiency.

Suggested Citation

  • Panke Zhang & Nan Li & Hong Han, 2025. "An Evolutionary Game Study of Multi-Agent Collaborative Disaster Relief Mechanisms for Agricultural Natural Disasters in China," Sustainability, MDPI, vol. 17(16), pages 1-28, August.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7194-:d:1720634
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/16/7194/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/16/7194/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhen Shi & Huinan Huang & Yingju Wu & Yung-Ho Chiu & Shijiong Qin, 2020. "Climate Change Impacts on Agricultural Production and Crop Disaster Area in China," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    2. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
    3. Lingyan Xu & Zhuoyun Zhou & Jianguo Du, 2020. "An Evolutionary Game Model for the Multi-Agent Co-Governance of Agricultural Non-Point Source Pollution Control under Intensive Management Pattern in China," IJERPH, MDPI, vol. 17(7), pages 1-19, April.
    4. repec:fth:iniesr:487 is not listed on IDEAS
    5. repec:hhs:iuiwop:487 is not listed on IDEAS
    6. Yusheng Chen & Zhaofa Sun & Yanmei Wang & Ye Ma & Weili Yang, 2024. "Seeds of Cross-Sector Collaboration: A Multi-Agent Evolutionary Game Theoretical Framework Illustrated by the Breeding of Salt-Tolerant Rice," Agriculture, MDPI, vol. 14(2), pages 1-21, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dufwenberg, Martin, 1997. "Some relationships between evolutionary stability criteria in games," Economics Letters, Elsevier, vol. 57(1), pages 45-50, November.
    2. Lichi Zhang & Yanyan Jiang & Junmin Wu, 2022. "Evolutionary Game Analysis of Government and Residents’ Participation in Waste Separation Based on Cumulative Prospect Theory," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    3. Tom Johnston & Michael Savery & Alex Scott & Bassel Tarbush, 2023. "Game Connectivity and Adaptive Dynamics," Papers 2309.10609, arXiv.org, revised Jun 2025.
    4. Gu, Tianqi & Xu, Weiping & Liang, Hua & He, Qing & Zheng, Nan, 2024. "School bus transport service strategies’ policy-making mechanism – An evolutionary game approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    5. Petrohilos-Andrianos, Yannis & Xepapadeas, Anastasios, 2017. "Resource harvesting regulation and enforcement: An evolutionary approach," Research in Economics, Elsevier, vol. 71(2), pages 236-253.
    6. Philippe Jehiel, 2022. "Analogy-Based Expectation Equilibrium and Related Concepts:Theory, Applications, and Beyond," Working Papers halshs-03735680, HAL.
    7. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    8. Meng Ding & Hui Zeng, 2022. "Multi-Agent Evolutionary Game in the Recycling Utilization of Sulfate-Rich Wastewater," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    9. Kulsum, Umma & Alam, Muntasir & Kamrujjaman, Md., 2024. "Modeling and investigating the dilemma of early and delayed vaccination driven by the dynamics of imitation and aspiration," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    10. Guohui Song & Yongbin Wang, 2021. "Mainstream Value Information Push Strategy on Chinese Aggregation News Platform: Evolution, Modelling and Analysis," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    11. Gaudeul, Alexia & Keser, Claudia & Müller, Stephan, 2021. "The evolution of morals under indirect reciprocity," Games and Economic Behavior, Elsevier, vol. 126(C), pages 251-277.
    12. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    13. Angelo Antoci & Simone Borghesi & Marcello Galeotti, 2013. "Environmental options and technological innovation: an evolutionary game model," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 247-269, April.
    14. Hui Yu & Wei Wang & Baohua Yang & Cunfang Li, 2019. "Evolutionary Game Analysis of the Stress Effect of Cross-Regional Transfer of Resource-Exhausted Enterprises," Complexity, Hindawi, vol. 2019, pages 1-16, November.
    15. Galor, Oded & Klemp, Marc, 2014. "The Biocultural Origins of Human Capital Formation," IZA Discussion Papers 8433, Institute of Labor Economics (IZA).
    16. Moreira, Helmar Nunes & Araujo, Ricardo Azevedo, 2011. "On the existence and the number of limit cycles in evolutionary games," MPRA Paper 33895, University Library of Munich, Germany.
    17. Xie, Yunya & Zhang, Shuhua & Zhang, Zhipeng & Bu, Hongyu, 2020. "Impact of binary social status with hierarchical punishment on the evolution of cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    18. Li, Jingjing & Wang, Zhaoxin & Li, Hui & Jiao, Jianling, 2024. "Which policy can effectively promote the formal recycling of power batteries in China?," Energy, Elsevier, vol. 299(C).
    19. Müller, Stephan, 2014. "The evolution of inequality aversion in a simplified game of life," University of Göttingen Working Papers in Economics 219, University of Goettingen, Department of Economics.
    20. Amit Te’eni & Bar Y Peled & Eliahu Cohen & Avishy Carmi, 2023. "Study of entanglement via a multi-agent dynamical quantum game," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-18, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    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:gam:jsusta:v:17:y:2025:i:16:p:7194-:d:1720634. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.