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A Profit Distribution Model of Reverse Logistics Based on Fuzzy DEA Efficiency—Modified Shapley Value

Author

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  • Jiekun Song

    (School of Economics and Management, China University of Petroleum, Qingdao 266580, China)

  • Xiaoping Ma

    (School of Economics and Management, China University of Petroleum, Qingdao 266580, China)

  • Rui Chen

    (School of Economics and Management, China University of Petroleum, Qingdao 266580, China)

Abstract

Reverse logistics is an important way to realize sustainable production and consumption. With the emergence of professional third-party reverse logistics service providers, the outsourcing model has become the main mode of reverse logistics. Whether the distribution of cooperative profit among multiple participants is fair or not determines the quality of the implementation of the outsourcing mode. The traditional Shapley value model is often used to distribute cooperative profit. Since its distribution basis is the marginal profit contribution of each member enterprise to different alliances, it is necessary to estimate the profit of each alliance. However, it is difficult to ensure the accuracy of this estimation, which makes the distribution lack of objectivity. Once the actual profit share deviates from the expectation of member enterprise, the sustainability of the reverse logistics alliance will be affected. This study considers the marginal efficiency contribution of each member enterprise to the alliance and applies it to replace the marginal profit contribution. As the input and output data of reverse logistics cannot be accurately separated from those of the whole enterprise, they are often uncertain. In this paper, we assume that each member enterprise’s input and output data are fuzzy numbers and construct an efficiency measurement model based on fuzzy DEA. Then, we define the characteristic function of alliance and propose a modified Shapley value model to fairly distribute cooperative profit. Finally, an example comprising of two manufacturing enterprises, one sales enterprise, and one third-party reverse logistics service provider is put forward to verify the model’s feasibility and effectiveness. This paper provides a reference for the profit distribution of the reverse logistics.

Suggested Citation

  • Jiekun Song & Xiaoping Ma & Rui Chen, 2021. "A Profit Distribution Model of Reverse Logistics Based on Fuzzy DEA Efficiency—Modified Shapley Value," Sustainability, MDPI, vol. 13(13), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7354-:d:586094
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    Cited by:

    1. Yanmin Guan & Na Wang, 2023. "Automatic modelling of networked innovation outsourcing-oriented talent competency in the era of artificial intelligence," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 408-414, February.
    2. Ziyu Chen & Jili Kong, 2023. "Research on Shared Logistics Decision Based on Evolutionary Game and Income Distribution," Sustainability, MDPI, vol. 15(11), pages 1-24, May.
    3. Xiaoyan Zhuo & Hongbing Li, 2022. "A Study on Cost Allocation in Renovation of Old Urban Residential Communities," Sustainability, MDPI, vol. 14(11), pages 1-20, June.
    4. Habib Zare Ahmadabadi & Fatemeh Zamzam & Ali Emrouznejad & Alireza Naser Sadrabadi & Ali Morovati Sharifabadi, 2024. "A modified distance friction minimization model with optimistic–pessimistic target orientation for OECD sustainable performance measurement," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 23113-23149, September.

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