IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i10p1444-d1390201.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/10/1444/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/10/1444/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    2. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    3. Guo, Yan & Yu, Xinning & Zhou, Caifeng & Lyu, Gaoyan, 2021. "Government subsidies for preventing supply disruption when the supplier has an outside option under competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    4. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    5. Manu Sharma & Sudhanshu Joshi & Sunil Luthra & Anil Kumar, 2022. "Managing disruptions and risks amidst COVID-19 outbreaks: role of blockchain technology in developing resilient food supply chains," Operations Management Research, Springer, vol. 15(1), pages 268-281, June.
    6. Li, Yuhong & Zobel, Christopher W. & Seref, Onur & Chatfield, Dean, 2020. "Network characteristics and supply chain resilience under conditions of risk propagation," International Journal of Production Economics, Elsevier, vol. 223(C).
    7. Nocera, Fabrizio & Contento, Alessandro & Gardoni, Paolo, 2024. "Risk analysis of supply chains: The role of supporting structures and infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    9. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    10. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    11. Liu, Ming & Lin, Tao & Chu, Feng & Ding, Yueyu & Zheng, Feifeng & Chu, Chengbin, 2023. "Bi-objective optimization for supply chain ripple effect management under disruption risks with supplier actions," International Journal of Production Economics, Elsevier, vol. 265(C).
    12. Fattahi, Mohammad & Govindan, Kannan & Maihami, Reza, 2020. "Stochastic optimization of disruption-driven supply chain network design with a new resilience metric," International Journal of Production Economics, Elsevier, vol. 230(C).
    13. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    14. Kaur, Harpreet & Prakash Singh, Surya, 2021. "Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies," International Journal of Production Economics, Elsevier, vol. 231(C).
    15. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    16. Muhammad Rahies Khan & Amir Manzoor, 2021. "Application and Impact of New Technologies in the Supply Chain Management During COVID-19 Pandemic: A Systematic Literature Review," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 277-292.
    17. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    18. Maciej Urbaniak & Piotr Rogala & Piotr Kafel, 2023. "Expectations of manufacturing companies regarding future priorities of improvement actions taken by their suppliers," Operations Management Research, Springer, vol. 16(1), pages 296-310, March.
    19. Shraddha Mishra & Surya Prakash Singh, 2022. "Designing dynamic reverse logistics network for post-sale service," Annals of Operations Research, Springer, vol. 310(1), pages 89-118, March.
    20. Yi Zheng & Li Liu & Victor Shi & Wenxing Huang & Jianxiu Liao, 2022. "A Resilience Analysis of a Medical Mask Supply Chain during the COVID-19 Pandemic: A Simulation Modeling Approach," IJERPH, MDPI, vol. 19(13), pages 1-21, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:10:p:1444-:d:1390201. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.