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The Game Analysis among Governments, the Public and Green Smart Supply Chain Enterprises in Necessity Purchase and Supply during COVID-19 Pandemic

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  • Ruzhi Xu

    (School of Economics and Management, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China)

  • Chenglong Yan

    (School of Economics and Management, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China)

  • Chenlong Wang

    (School of Economics and Management, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China)

  • Huawei Zhao

    (School of Economics and Management, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China)

Abstract

During the COVID-19 pandemic, panic buying, price inflation, and the pollution of production processes led to economic and social unrest. In response to the current situation, the current research takes less account of the subjective perception of public panic buying and the lack of reference to the reality of effective governance. First, this paper uses prospect theory to portray the public’s perceived value of goods in panic buying and non-panic buying situations. Then, drawing on the experience of effective governance in China, a tripartite evolutionary game model of local government, the public and green smart supply chain enterprises is constructed under the reward and punishment mechanism of the central government. Then, this paper analyzes the strategic choices of each game player and the stability of the system equilibrium. The structure of the study suggests the following. (1) Improving local government subsidies and penalties, the cost of positive response and the probability of response can lead to an evolutionary direction where the public chooses not to panic buy and green smart supply chain enterprises choose to ensure a balance between supply and demand and increase pollution control in the production process. (2) Our study yields three effective combinations of evolutionary strategies, of which an ideal combination of evolutionary strategies exists. Non-ideal evolutionary strategy combinations can occur due to improper incentives and penalties of local governments and misallocation of limited resources. However, we find four paths that can transform the non-ideal evolutionary strategy combination into an ideal evolutionary strategy combination. (3) The central government’s reward and punishment mechanism is an important tool to stabilize the tripartite strategy, but the central government cannot achieve effective governance by replacing incentives with punishment.

Suggested Citation

  • Ruzhi Xu & Chenglong Yan & Chenlong Wang & Huawei Zhao, 2023. "The Game Analysis among Governments, the Public and Green Smart Supply Chain Enterprises in Necessity Purchase and Supply during COVID-19 Pandemic," Sustainability, MDPI, vol. 15(9), pages 1-30, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7229-:d:1133550
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    References listed on IDEAS

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    1. Nainsi Gupta & Gunjan Soni & Sameer Mittal & Indrajit Mukherjee & Bharti Ramtiyal & Devesh Kumar, 2023. "Evaluating Traceability Technology Adoption in Food Supply Chain: A Game Theoretic Approach," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    2. Weihua Liu & Shangsong Long & Shuang Wei & Dong Xie & Jingkun Wang & Xinyun Liu, 2022. "Smart logistics ecological cooperation with data sharing and platform empowerment: an examination with evolutionary game model," International Journal of Production Research, Taylor & Francis Journals, vol. 60(13), pages 4295-4315, July.
    3. Ruguo Fan & Yibo Wang & Jinchai Lin, 2021. "Study on Multi-Agent Evolutionary Game of Emergency Management of Public Health Emergencies Based on Dynamic Rewards and Punishments," IJERPH, MDPI, vol. 18(16), pages 1-22, August.
    4. Yuen, Kum Fai & Tan, Lydia Sonia & Wong, Yiik Diew & Wang, Xueqin, 2022. "Social determinants of panic buying behaviour amidst COVID-19 pandemic: The role of perceived scarcity and anticipated regret," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    5. Hui Zhang & Xin Su, 2021. "The Applications and Complexity Analysis Based on Supply Chain Enterprises’ Green Behaviors under Evolutionary Game Framework," Sustainability, MDPI, vol. 13(19), pages 1-19, October.
    6. Kum Fai Yuen & Xueqin Wang & Fei Ma & Kevin X. Li, 2020. "The Psychological Causes of Panic Buying Following a Health Crisis," IJERPH, MDPI, vol. 17(10), pages 1-14, May.
    7. Chen, Tinggui & Jin, Yumei & Yang, Jianjun & Cong, Guodong, 2022. "Identifying emergence process of group panic buying behavior under the COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
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