IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i9p4615-d540313.html
   My bibliography  Save this article

A Conceptual Hybrid Approach from a Multicriteria Perspective for Sustainable Third-Party Reverse Logistics Provider Identification

Author

Listed:
  • Mohamed Abdel-Basset

    (Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt)

  • Abduallah Gamal

    (Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt)

  • Mohamed Elhoseny

    (Department of Computer Science, American University in the Emirates, Dubai 503000, United Arab Emirates)

  • Ripon K. Chakrabortty

    (Capability Systems Centre, School of Engineering and IT, University of New South Wales, Canberra 2052, Australia)

  • Michael Ryan

    (Capability Systems Centre, School of Engineering and IT, University of New South Wales, Canberra 2052, Australia)

Abstract

Reverse logistics (RL) is considered the reverse manner of gathering and redeploying goods at the end of their lifetime span from consumers to manufacturers in order to reutilize, dispose, or remanufacture. Whereas RL has many economic benefits, it presents compromises to businesses that wish to remain competitive but be responsible global citizens in terms of social, environmental, risk, and safety aspects of sustainable development. Managing RL systems therefore is considered a multifaceted mission that necessities a significant level of technology, infrastructure, experience, and competence. Consequently, various commerce institutions are looking to outsourcing their RL actions to third-party reverse logistics providers (3PRLPs). In this work, a novel hybrid multiple-criteria decision-making (MCDM) framework is proposed to classify and choose 3PRLPs, which comprises the analytic hierarchy process (AHP) technique, and technique for order of preference by similarity to ideal solution (TOPSIS) technique under neutrosophic environment. Accordingly, AHP is availed for defining weights of key dimensions and their subindices. In addition, TOPSIS was adopted for ranking the specified 3PRLPs. The efficiency of the proposed approach is clarified through application on a considered car parts manufacturing industry case in Egypt, which shows the features of the combined MCDM methods. A comparative and sensitivity analyses were performed to highlight the benefits of the incorporated MCDM methods and for clarifying the effect of changing weights in selecting the sustainable 3PRLP alternative, respectively. The suggested framework is also shown to present more functional execution when dealing with uncertainties and qualitative inputs, demonstrating applicability to a broad range of applications. Ultimately, the best sustainable 3PRLPs were selected and results show that social, environmental, and risk and safety sustainability factors have the greatest influence when determining 3PRLPs alternatives.

Suggested Citation

  • Mohamed Abdel-Basset & Abduallah Gamal & Mohamed Elhoseny & Ripon K. Chakrabortty & Michael Ryan, 2021. "A Conceptual Hybrid Approach from a Multicriteria Perspective for Sustainable Third-Party Reverse Logistics Provider Identification," Sustainability, MDPI, vol. 13(9), pages 1-29, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4615-:d:540313
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/9/4615/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/9/4615/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nima Kazemi & Nikunja Mohan Modak & Kannan Govindan, 2019. "A review of reverse logistics and closed loop supply chain management studies published in IJPR: a bibliometric and content analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4937-4960, August.
    2. Rakesh D. Raut & Bhaskar B. Gardas & Shamik Pushkar & Balkrishna E. Narkhede, 2019. "Third-party logistics service providers selection and evaluation: a hybrid AHP-DEA-COPRAS-G group decision-making approach," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 12(6), pages 632-651.
    3. Govindan, Kannan & Kadziński, Miłosz & Ehling, Ronja & Miebs, Grzegorz, 2019. "Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA," Omega, Elsevier, vol. 85(C), pages 1-15.
    4. Govindan, Kannan & Palaniappan, Murugesan & Zhu, Qinghua & Kannan, Devika, 2012. "Analysis of third party reverse logistics provider using interpretive structural modeling," International Journal of Production Economics, Elsevier, vol. 140(1), pages 204-211.
    5. Ghadimi, Pezhman & Ghassemi Toosi, Farshad & Heavey, Cathal, 2018. "A multi-agent systems approach for sustainable supplier selection and order allocation in a partnership supply chain," European Journal of Operational Research, Elsevier, vol. 269(1), pages 286-301.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joash Mageto, 2022. "Current and Future Trends of Information Technology and Sustainability in Logistics Outsourcing," Sustainability, MDPI, vol. 14(13), pages 1-27, June.
    2. Ahmed Dabees & Mahmoud Barakat & Sahar Sobhy Elbarky & Andrej Lisec, 2023. "A Framework for Adopting a Sustainable Reverse Logistics Service Quality for Reverse Logistics Service Providers: A Systematic Literature Review," Sustainability, MDPI, vol. 15(3), pages 1-16, January.

    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. 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.
    2. Salehi-Amiri, Amirhossein & Zahedi, Ali & Akbapour, Navid & Hajiaghaei-Keshteli, Mostafa, 2021. "Designing a sustainable closed-loop supply chain network for walnut industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    3. Mansoureh Beheshti Nejad & Seyed Mahmoud Zanjirchi & Seyed Mojtaba Hosseini Bamakan & Negar Jalilian, 2024. "Blockchain Adoption in Operations Management: A Systematic Literature Review of 14 Years of Research," Annals of Data Science, Springer, vol. 11(4), pages 1361-1389, August.
    4. 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.
    5. Govindan, Kannan & Salehian, Farhad & Kian, Hadi & Hosseini, Seyed Teimoor & Mina, Hassan, 2023. "A location-inventory-routing problem to design a circular closed-loop supply chain network with carbon tax policy for achieving circular economy: An augmented epsilon-constraint approach," International Journal of Production Economics, Elsevier, vol. 257(C).
    6. Zanon, Lucas Gabriel & Munhoz Arantes, Rafael Ferro & Calache, Lucas Daniel Del Rosso & Carpinetti, Luiz Cesar Ribeiro, 2020. "A decision making model based on fuzzy inference to predict the impact of SCOR® indicators on customer perceived value," International Journal of Production Economics, Elsevier, vol. 223(C).
    7. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2020. "Assessment of community sustainable livelihoods capitals for the implementation of alternative energy technologies in Uganda – Africa," Renewable Energy, Elsevier, vol. 160(C), pages 886-902.
    8. Haji Vahabzadeh, Ali & Asiaei, Arash & Zailani, Suhaiza, 2015. "Reprint of “Green decision-making model in reverse logistics using FUZZY-VIKOR method”," Resources, Conservation & Recycling, Elsevier, vol. 104(PB), pages 334-347.
    9. M. Masanta & B. C. Giri, 2022. "A manufacturing–remanufacturing supply chain model with learning and forgetting in inspection under consignment stock agreement," Operational Research, Springer, vol. 22(4), pages 4093-4117, September.
    10. Marty, Justine & Ruel, Salomée, 2024. "Why is “supply chain collaboration” still a hot topic? A review of decades of research and a comprehensive framework proposal," International Journal of Production Economics, Elsevier, vol. 273(C).
    11. Ebrahimi Bajgani, Sahar & Saberi, Sara & Toyasaki, Fuminori, 2023. "Designing a reverse supply chain network with quality control for returned products: Strategies to mitigate free-riding effect and ensure compliance with technology licensing requirements," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    12. Toktaş-Palut, Peral & Baylav, Ecem & Teoman, Seyhan & Altunbey, Mustafa, 2014. "The impact of barriers and benefits of e-procurement on its adoption decision: An empirical analysis," International Journal of Production Economics, Elsevier, vol. 158(C), pages 77-90.
    13. Amin, Gholam R. & Ibn Boamah, Mustapha, 2023. "Modeling business partnerships: A data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 305(1), pages 329-337.
    14. Agrawal, Saurabh & Singh, Rajesh K. & Murtaza, Qasim, 2016. "Outsourcing decisions in reverse logistics: Sustainable balanced scorecard and graph theoretic approach," Resources, Conservation & Recycling, Elsevier, vol. 108(C), pages 41-53.
    15. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    16. Jaya Priyadarshini & Rajesh Kr Singh & Ruchi Mishra & Surajit Bag, 2022. "Investigating the interaction of factors for implementing additive manufacturing to build an antifragile supply chain: TISM-MICMAC approach," Operations Management Research, Springer, vol. 15(1), pages 567-588, June.
    17. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    18. Jain, Vineet & Raj, Tilak, 2016. "Modeling and analysis of FMS performance variables by ISM, SEM and GTMA approach," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 84-96.
    19. Bai, Chunguang & Sarkis, Joseph, 2013. "A grey-based DEMATEL model for evaluating business process management critical success factors," International Journal of Production Economics, Elsevier, vol. 146(1), pages 281-292.
    20. Niloofar Jefroy & Mathew Azarian & Hao Yu, 2022. "Moving from Industry 4.0 to Industry 5.0: What Are the Implications for Smart Logistics?," Logistics, MDPI, vol. 6(2), pages 1-27, April.

    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:jsusta:v:13:y:2021:i:9:p:4615-:d:540313. 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.