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The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection

Author

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  • Yayi Yuan

    (Sichuan University)

  • Zeshui Xu

    (Sichuan University)

  • Yixin Zhang

    (Sichuan University)

Abstract

With the emergence of outsourcing logistics and the rapid development of the e-commerce business, Third Party Logistics (TPL) plays an indispensable role in modern business. In the TPL provider selection process, uncertain information brings more challenges to decision makers. This paper uses probabilistic linguistic term sets (PLTSs) to describe uncertain decision making information. Firstly, we propose an improved Decision Making Trial and Evaluation Laboratory method, which allows a certain relationship between decision criteria and calculates criteria weights in multi-criteria decision making (MCDM) problems. Then, in order to make full use of uncertain TPL provider information and maximize the values of data, the probabilistic linguistic complex proportional assessment method is proposed and applied to solve the MCDM problems under probabilistic linguistic environment, which needs much less computation than other MCDM methods. Finally, an application example of TPL provider selection is presented to demonstrate the proposed method. A comparative analysis is further conducted to validate the effectiveness of the proposed method.

Suggested Citation

  • Yayi Yuan & Zeshui Xu & Yixin Zhang, 2022. "The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection," Fuzzy Optimization and Decision Making, Springer, vol. 21(1), pages 137-156, March.
  • Handle: RePEc:spr:fuzodm:v:21:y:2022:i:1:d:10.1007_s10700-021-09358-9
    DOI: 10.1007/s10700-021-09358-9
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    References listed on IDEAS

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    1. Zeshui Xu, 2015. "Uncertain Multi-Attribute Decision Making," Springer Books, Springer, edition 127, number 978-3-662-45640-8, December.
    2. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    3. Xiaolu Zhang & Xiaoming Xing, 2017. "Probabilistic Linguistic VIKOR Method to Evaluate Green Supply Chain Initiatives," Sustainability, MDPI, vol. 9(7), pages 1-18, July.
    4. Xiqin Wen & Mingchao Yan & Jieyu Xian & Rui Yue & Anhua Peng, 2016. "Supplier selection in supplier chain management using Choquet integral-based linguistic operators under fuzzy heterogeneous environment," Fuzzy Optimization and Decision Making, Springer, vol. 15(3), pages 307-330, September.
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    Cited by:

    1. Ling Gai & Hu-chen Liu & Yanjun Wang & Yuping Xing, 2023. "Green supplier selection and order allocation using linguistic Z-numbers MULTIMOORA method and bi-objective non-linear programming," Fuzzy Optimization and Decision Making, Springer, vol. 22(2), pages 267-288, June.
    2. Bing Yan & Yuan Rong & Liying Yu & Yuting Huang, 2022. "A Hybrid Intuitionistic Fuzzy Group Decision Framework and Its Application in Urban Rail Transit System Selection," Mathematics, MDPI, vol. 10(12), pages 1-26, June.
    3. Mohamed Rafik Noor Mohamed Qureshi, 2022. "A Bibliometric Analysis of Third-Party Logistics Services Providers (3PLSP) Selection for Supply Chain Strategic Advantage," Sustainability, MDPI, vol. 14(19), pages 1-25, September.
    4. Faruk Görçün, Ömer. & Chatterjee, Prasenjit. & Stević, Željko. & Küçükönder, Hande., 2024. "An integrated model for road freight transport firm selection in third-party logistics using T-spherical Fuzzy sets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    5. Mete, Suleyman & Yucesan, Melih & Gul, Muhammet & Ozceylan, Eren, 2023. "An integrated hybrid MCDM approach to evaluate countries’ COVID-19 risks," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).

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