IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v342y2024i1d10.1007_s10479-023-05680-0.html
   My bibliography  Save this article

An integrated group fuzzy inference and best–worst method for supplier selection in intelligent circular supply chains

Author

Listed:
  • Madjid Tavana

    (La Salle University
    University of Paderborn)

  • Shahryar Sorooshian

    (University of Gothenburg)

  • Hassan Mina

    (Saito University College)

Abstract

Circular supplier evaluation aims at selecting the most suitable suppliers with zero waste. Sustainable circular supplier selection also considers socio-economic and environmental factors in the decision process. This study proposes an integrated method for evaluating sustainable suppliers in intelligent circular supply chains using fuzzy inference and multi-criteria decision-making. In the first stage of the proposed method, supplier evaluation sub-criteria are identified and weighted from economic, social, circular, and Industry 4.0 perspectives using a fuzzy group best–worst method followed by scoring the suppliers on each criterion. In the second stage, the suppliers are ranked and selected according to an overall score determined by a fuzzy inference system. Finally, the applicability of the proposed method is demonstrated using data from a public–private partnership project at an offshore wind farm in Southeast Asia.

Suggested Citation

  • Madjid Tavana & Shahryar Sorooshian & Hassan Mina, 2024. "An integrated group fuzzy inference and best–worst method for supplier selection in intelligent circular supply chains," Annals of Operations Research, Springer, vol. 342(1), pages 803-844, November.
    • Handle: RePEc:spr:annopr:v:342:y:2024:i:1:d:10.1007_s10479-023-05680-0
    DOI: 10.1007/s10479-023-05680-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05680-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-023-05680-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Melih Yucesan & Suleyman Mete & Faruk Serin & Erkan Celik & Muhammet Gul, 2019. "An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection," Mathematics, MDPI, vol. 7(2), pages 1-19, February.
    2. Zahra Ebrahim Qazvini & Mohammad Reza Maleki, 2022. "A triple bottom line multi-criteria decision making framework for supplier selection," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 21(2), pages 144-160.
    3. Karasan, Ali & Erdogan, Melike & Cinar, Melih, 2022. "Healthcare service quality evaluation: An integrated decision-making methodology and a case study," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    4. Sina Salimian & Seyed Meysam Mousavi & Jurgita Antucheviciene, 2022. "An Interval-Valued Intuitionistic Fuzzy Model Based on Extended VIKOR and MARCOS for Sustainable Supplier Selection in Organ Transplantation Networks for Healthcare Devices," Sustainability, MDPI, vol. 14(7), pages 1-21, March.
    5. Meiri Triani & Handrea Bernando Tambunan & Kania Dewi & Addina Shafiyya Ediansjah, 2023. "Review on Greenhouse Gases Emission in the Association of Southeast Asian Nations (ASEAN) Countries," Energies, MDPI, vol. 16(9), pages 1-17, May.
    6. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
    7. Miguel Ortiz-Barrios & Juan Cabarcas-Reyes & Alessio Ishizaka & Maria Barbati & Natalia Jaramillo-Rueda & Giovani Jesús Carrascal-Zambrano, 2021. "A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry," Annals of Operations Research, Springer, vol. 307(1), pages 443-481, December.
    8. Chandra Prakash Garg & Archana Sharma, 2020. "Sustainable outsourcing partner selection and evaluation using an integrated BWM–VIKOR framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 1529-1557, February.
    9. 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).
    10. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang & Chen-Ming Lu, 2021. "A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    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. Mohammed, Ahmed & Lopes de Sousa Jabbour, Ana Beatriz & Koh, Lenny & Hubbard, Nicolas & Chiappetta Jabbour, Charbel Jose & Al Ahmed, Teejan, 2022. "The sourcing decision-making process in the era of digitalization: A new quantitative methodology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    2. Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    3. Chandra Prakash Garg & Vishal Kashav & Xuemuge Wang, 2023. "Evaluating sustainability factors of green ports in China under fuzzy environment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 7795-7821, August.
    4. Dong, Ciwei & Huang, Qianzhi & Pan, Yuqing & Ng, Chi To & Liu, Renjun, 2023. "Logistics outsourcing: Effects of greenwashing and blockchain technology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    5. 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.
    6. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    7. Alaa Alden Al Mohamed & Sobhi Al Mohamed, 2023. "Application of fuzzy group decision-making selecting green supplier: a case study of the manufacture of natural laurel soap," Future Business Journal, Springer, vol. 9(1), pages 1-20, December.
    8. Alexandra Nicoleta Ciucu-Durnoi & Camelia Delcea & Aurelia Stănescu & Cosmin Alexandru Teodorescu & Vanesa Mădălina Vargas, 2024. "Beyond Industry 4.0: Tracing the Path to Industry 5.0 through Bibliometric Analysis," Sustainability, MDPI, vol. 16(12), pages 1-26, June.
    9. Jiuh‐Biing Sheu & Tsan‐Ming Choi, 2023. "Can we work more safely and healthily with robot partners? A human‐friendly robot–human‐coordinated order fulfillment scheme," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 794-812, March.
    10. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    11. Amin Mahmoudi & Saad Ahmed Javed, 2022. "Probabilistic Approach to Multi-Stage Supplier Evaluation: Confidence Level Measurement in Ordinal Priority Approach," Group Decision and Negotiation, Springer, vol. 31(5), pages 1051-1096, October.
    12. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang, 2023. "Sustainable Evaluation of Major Third-Party Logistics Providers: A Framework of an MCDM-Based Entropy Objective Weighting Method," Mathematics, MDPI, vol. 11(19), pages 1-27, October.
    13. Miguel Reyna-Castillo & Alejandro Santiago & Salvador Ibarra Martínez & José Antonio Castán Rocha, 2022. "Social Sustainability and Resilience in Supply Chains of Latin America on COVID-19 Times: Classification Using Evolutionary Fuzzy Knowledge," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    14. Shahzad, Khuram & Zhang, Qingyu & Zafar, Abaid Ullah & Ashfaq, Muhammad & Rehman, Shafique Ur, 2023. "The role of blockchain-enabled traceability, task technology fit, and user self-efficacy in mobile food delivery applications," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    15. Niu, Baozhuang & Ruan, Yiyuan & Xu, Haotao, 2023. "Turn a blind eye? E-tailer's blockchain participation considering upstream competition between copycats and brands," International Journal of Production Economics, Elsevier, vol. 265(C).
    16. 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).
    17. Alekh Gour & Shikha Aggarwal & Subodha Kumar, 2022. "Lending ears to unheard voices: An empirical analysis of user‐generated content on social media," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2457-2476, June.
    18. Tavana, Madjid & Khalili Nasr, Arash & Mina, Hassan & Michnik, Jerzy, 2022. "A private sustainable partner selection model for green public-private partnerships and regional economic development," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    19. Hu, Shaolong & Dong, Zhijie Sasha & Dai, Rui, 2024. "A machine learning based sample average approximation for supplier selection with option contract in humanitarian relief," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    20. Gupta, Shivam & Modgil, Sachin & Choi, Tsan-Ming & Kumar, Ajay & Antony, Jiju, 2023. "Influences of artificial intelligence and blockchain technology on financial resilience of supply chains," International Journal of Production Economics, Elsevier, vol. 261(C).

    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:spr:annopr:v:342:y:2024:i:1:d:10.1007_s10479-023-05680-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.