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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
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    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.

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