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Smart logistics ecological cooperation with data sharing and platform empowerment: an examination with evolutionary game model

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  • Weihua Liu
  • Shangsong Long
  • Shuang Wei
  • Dong Xie
  • Jingkun Wang
  • Xinyun Liu

Abstract

With the application of advanced technology, smart logistics ecological cooperation is in development, characterised by data sharing and platform empowerment. In order to explore the trend of ecological cooperation between the logistics platform and the supplier from the perspective of business ecosystem, this study uses evolutionary game theory to describe the multi-period game between the two parties, and obtains the equilibrium where the two parties both choose ecological cooperation and its preconditions. Through sensitivity analysis, we obtain the specific paths to convert other evolutionary stable strategies (ESSs) into the ideal ESS by adjusting certain parameters, and provide suggestions for the platform to induce its supplier to choose ecological cooperation. The platform should charge a reasonable agency fee to reach the ecological cooperation. The relationship between the agency fee, empowerment cost, and service price elasticity coefficient determines the platform's ultimate evolutionary stable strategy. This study finds the butterfly effect of ecological cooperation. There are different combinations of the initial probabilities between the two parties making them both choose ecological cooperation or both not choose under the same condition.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:13:p:4295-4315
    DOI: 10.1080/00207543.2021.1925173
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    Cited by:

    1. Lyu, Zhengwei & Lan, Hongjie & Hua, Guowei & Cheng, T.C.E. & Xu, Yadong, 2024. "How to promote Chinese food waste-to-energy program? An evolutionary game approach," Energy, Elsevier, vol. 293(C).
    2. Zhitao Xu & Adel Elomri & Roberto Baldacci & Laoucine Kerbache & Zhenyong Wu, 2024. "Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective," Annals of Operations Research, Springer, vol. 338(2), pages 1359-1401, July.
    3. Guangmei Cao & Yuesen Wang & Honghu Gao & Hao Liu & Haibin Liu & Zhigang Song & Yuqing Fan, 2023. "Coordination Decision-Making for Intelligent Transformation of Logistics Services under Capital Constraint," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    4. 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.

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