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A Novel Hybrid Gray MCDM Model for Resilient Supplier Selection Problem

Author

Listed:
  • Alptekin Ulutaş

    (Department of International Trade and Business, Inonu University, 44210 Malatya, Turkey)

  • Mladen Krstić

    (Logistics Department, Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Belgrade, Serbia
    Department of Economic Sciences, University of Salento, Via Monteroni snc, 73100 Lecce, Italy)

  • Ayşe Topal

    (Department of Business, Nigde Omer Halisdemir University, 51240 Nigde, Turkey)

  • Leonardo Agnusdei

    (Department of Innovation Engineering, University of Salento, Via Monteroni snc, 73100 Lecce, Italy)

  • Snežana Tadić

    (Logistics Department, Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Belgrade, Serbia)

  • Pier Paolo Miglietta

    (Department of Biological and Environmental Sciences and Technologies, University of Salento, Via Monteroni snc, 73100 Lecce, Italy)

Abstract

The current business climate has generated considerable uncertainty and disrupted supply chain processes. Suppliers have frequently been identified as the primary source of hazards responsible for supply chain disruptions. Using a strategic approach to supplier selection that prioritizes providers with resilience features, mitigating the risk exposure inherent in supply chains is possible. This study proposes a comprehensive gray multiple-criteria decision making (MCDM) method incorporating resilience attributes to supplier selection. To determine criteria weights, the gray PSI and gray BWM methodologies were used, and to evaluate and prioritize resilient providers, the gray MCRAT and gray COBRA methodologies were applied. According to the results obtained by the suggested methodology, the supplier that demonstrated the greatest degree of resilience was determined to be the provider categorized as SPIR 4. The sequential sequence of the SPIR numbers is as follows: SPIR 5, SPIR 1, SPIR 3, SPIR 2, and SPIR 6. The data demonstrate that the developed approach produced accurate results.

Suggested Citation

  • Alptekin Ulutaş & Mladen Krstić & Ayşe Topal & Leonardo Agnusdei & Snežana Tadić & Pier Paolo Miglietta, 2024. "A Novel Hybrid Gray MCDM Model for Resilient Supplier Selection Problem," Mathematics, MDPI, vol. 12(10), pages 1-22, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:10:p:1444-:d:1390201
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    References listed on IDEAS

    as
    1. Lei Xiong & Shuqi Zhong & Sen Liu & Xiao Zhang & Yanfeng Li, 2020. "An Approach for Resilient-Green Supplier Selection Based on WASPAS, BWM, and TOPSIS under Intuitionistic Fuzzy Sets," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-18, July.
    2. Tadeusz Sawik & Bartosz Sawik, 2024. "Risk-averse decision-making to maintain supply chain viability under propagated disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 62(8), pages 2853-2867, April.
    3. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    4. Çağatay KARAKÖY & Alptekin ULUTAŞ & Darjan KARABASEVIC & Salim ÜRE & Ali Oğuz BAYRAKÇIL, 2023. "The Evaluation of Economic Freedom Indexes of EU Countries with a GREY Hybrid MCDM Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 129-144, March.
    5. Jiawu Gan & Shuqi Zhong & Sen Liu & Dan Yang, 2019. "Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-14, April.
    6. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
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