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A Hybrid Prospect–Regret Decision-Making Method for Green Supply Chain Management Under the Interval Type-2 Trapezoidal Fuzzy Environment

Author

Listed:
  • Shaodong Zhou

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China)

  • Zilong Meng

    (Chongqing Key Laboratory of Vehicle Emission and Economizing Energy, Chongqing 401122, China
    Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), School of Mechanical Engineering, Shandong University, Jinan 250061, China)

  • Zhongwei Huang

    (Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), School of Mechanical Engineering, Shandong University, Jinan 250061, China)

  • Honghao Zhang

    (Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), School of Mechanical Engineering, Shandong University, Jinan 250061, China)

  • Danqi Wang

    (Chongqing Key Laboratory of Vehicle Emission and Economizing Energy, Chongqing 401122, China
    College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha 410205, China)

Abstract

The concept of green supply chain management (GSCM) describes how to reduce the negative impact of the supply chain on the environment while balancing the economic and social benefits of a company being in the supply chain. Selecting the optimal multi-dimensional GSCM scheme, a typical multi-criteria decision-making (MCDM) problem, is a crucial step in implementing the GSCM concept. Therefore, this paper constructs a multi-dimensional GSCM index system for the comprehensive analysis of the important influencing factors of GSCM. Then, cross-entropy combining the interval type-2 trapezoidal fuzzy set (IT2TFS) is adopted to determine the weight distribution of GSCM indices, and a hybrid MCDM method integrating the IT2TFS prospect–regret method is proposed to analyze the psychological behaviors of decision makers who are selecting the best GSCM scheme. Moreover, the case study, comparative analysis, and sensitivity analysis are presented to verify the effectiveness and reasonableness of the proposed MCDM method. The results affirm the validity of the proposed MCDM method, with A 4 identified as the optimal GSCM scheme, demonstrating its effectiveness and applicability in MCDM problems.

Suggested Citation

  • Shaodong Zhou & Zilong Meng & Zhongwei Huang & Honghao Zhang & Danqi Wang, 2025. "A Hybrid Prospect–Regret Decision-Making Method for Green Supply Chain Management Under the Interval Type-2 Trapezoidal Fuzzy Environment," Sustainability, MDPI, vol. 17(8), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3323-:d:1630646
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    References listed on IDEAS

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