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
    ---><---

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.