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A Hesitant Fuzzy Method for Evaluating Risky Cold Chain Suppliers Based on an Improved TODIM

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  • Yongzheng Zhang

    (Business School, University of Shanghai for Science of Technology, Shanghai 200093, China)

  • Chunming Ye

    (Business School, University of Shanghai for Science of Technology, Shanghai 200093, China)

  • Xiuli Geng

    (Business School, University of Shanghai for Science of Technology, Shanghai 200093, China)

Abstract

Enterprises need sustainable development in order to reduce costs and increase income. The cold chain logistics industry needs to promote sustainable supply chains more. As the beginning of the supply chain, the choice of suppliers is particularly important. Considering the risky attitude of decision-makers, an improved hesitant fuzzy TODIM approach is adopted to select suppliers. In order to calculate a more objective indicator weight, the generalized Shapley function of the hesitant fuzzy measure is adopted by analyzing the relationships among indicators. The uncertain supplier evaluation information given by decision-makers is obtained by using hesitant fuzzy information. The improved Interactive and Multi-criteria Decision-Making (TODIM) method based on hesitant fuzzy numbers is used to analyze the psychological behavior of decision-makers under different market prospects and comprehensively rank the candidate suppliers. Finally, a case study of selecting cold chain logistics suppliers is provided to verify the effectiveness and feasibility of the method in this paper.

Suggested Citation

  • Yongzheng Zhang & Chunming Ye & Xiuli Geng, 2022. "A Hesitant Fuzzy Method for Evaluating Risky Cold Chain Suppliers Based on an Improved TODIM," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10152-:d:889385
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    References listed on IDEAS

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    1. Bian, Tian & Hu, Jiantao & Deng, Yong, 2017. "Identifying influential nodes in complex networks based on AHP," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 422-436.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Hang Liu & Shilin Nie, 2019. "Low Carbon Scheduling Optimization of Flexible Integrated Energy System Considering CVaR and Energy Efficiency," Sustainability, MDPI, vol. 11(19), pages 1-27, September.
    4. Hédi Essid & Janet Ganouati & Stephane Vigeant, 2018. "A mean-maverick game cross-efficiency approach to portfolio selection: An application to Paris stock exchange," Post-Print hal-01916529, HAL.
    5. Michel Grabisch & Christophe Labreuche, 2010. "A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid," Annals of Operations Research, Springer, vol. 175(1), pages 247-286, March.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Huiru Zhao & Sen Guo, 2014. "Selecting Green Supplier of Thermal Power Equipment by Using a Hybrid MCDM Method for Sustainability," Sustainability, MDPI, vol. 6(1), pages 1-19, January.
    8. Aida Rezaei & Amir Aghsami & Masoud Rabbani, 2021. "Supplier selection and order allocation model with disruption and environmental risks in centralized supply chain," 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. 12(6), pages 1036-1072, December.
    9. Yazhou Xiong & Jie Zhao & Jie Lan, 2019. "Performance Evaluation of Food Cold Chain Logistics Enterprise Based on the AHP and Entropy," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 12(2), pages 57-67, April.
    10. Xiaoli Tian & Meiling Niu & Jiangshui Ma & Zeshui Xu, 2020. "A Novel TODIM with Probabilistic Hesitant Fuzzy Information and Its Application in Green Supplier Selection," Complexity, Hindawi, vol. 2020, pages 1-26, December.
    11. Yanjuan Hu & Lizhe Wu & Chao Shi & Yilin Wang & Feifan Zhu, 2020. "Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS," International Journal of Production Research, Taylor & Francis Journals, vol. 58(3), pages 748-757, February.
    12. Ngoc Bao Tu Nguyen & Gu-Hong Lin & Thanh-Tuan Dang, 2021. "A Two Phase Integrated Fuzzy Decision-Making Framework for Green Supplier Selection in the Coffee Bean Supply Chain," Mathematics, MDPI, vol. 9(16), pages 1-22, August.
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