Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach
The objective of this research is to identify and rank the solutions to mitigate the sustainable remanufacturing supply chain (RSC) risks effectively. Risks and the solutions are identified based on a literature survey and discussion with the expert’s panel. A hybrid multi-criteria decision making (...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-11-01
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| Series: | International Journal of Sustainable Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/19397038.2020.1758973 |
| _version_ | 1827810898889146368 |
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| author | Zulfiquar N. Ansari Ravi Kant Ravi Shankar |
| author_facet | Zulfiquar N. Ansari Ravi Kant Ravi Shankar |
| author_sort | Zulfiquar N. Ansari |
| collection | DOAJ |
| description | The objective of this research is to identify and rank the solutions to mitigate the sustainable remanufacturing supply chain (RSC) risks effectively. Risks and the solutions are identified based on a literature survey and discussion with the expert’s panel. A hybrid multi-criteria decision making (MCDM) framework using fuzzy step-wise weight assessment ratio analysis (SWARA) and fuzzy complex proportional assessment of alternatives (COPRAS) is applied to analyse the risks and the solutions. Fuzzy SWARA is used to obtain relative weights of each risk and fuzzy COPRAS is used to rank and select the most efficient solution to manage the risks. The proposed framework was numerically applied to a case organisation involved in manufacturing/remanufacturing activities. The results indicate that initiatives from the management and modification in organisation goals is the top-ranked solution that would mitigate the majority of risks. Government, manufacturer and distributor collaboration to develop action plans and setting up international standards are also prominent solutions to overcome the risks. Further, this research performs a sensitivity analysis to check the robustness of the proposed fuzzy SWARA-fuzzy COPRAS framework. The findings and implications of this research will help the practitioners and researchers for decision-making in RSC. |
| first_indexed | 2024-03-11T22:57:47Z |
| format | Article |
| id | doaj.art-a93b3a38571a456abc57217369ee874c |
| institution | Directory Open Access Journal |
| issn | 1939-7038 1939-7046 |
| language | English |
| last_indexed | 2024-03-11T22:57:47Z |
| publishDate | 2020-11-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Sustainable Engineering |
| spelling | doaj.art-a93b3a38571a456abc57217369ee874c2023-09-21T15:17:03ZengTaylor & Francis GroupInternational Journal of Sustainable Engineering1939-70381939-70462020-11-0113647349410.1080/19397038.2020.17589731758973Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approachZulfiquar N. Ansari0Ravi Kant1Ravi Shankar2S.V. National Institute of TechnologyS.V. National Institute of TechnologyIndian Institute of Technology, DelhiThe objective of this research is to identify and rank the solutions to mitigate the sustainable remanufacturing supply chain (RSC) risks effectively. Risks and the solutions are identified based on a literature survey and discussion with the expert’s panel. A hybrid multi-criteria decision making (MCDM) framework using fuzzy step-wise weight assessment ratio analysis (SWARA) and fuzzy complex proportional assessment of alternatives (COPRAS) is applied to analyse the risks and the solutions. Fuzzy SWARA is used to obtain relative weights of each risk and fuzzy COPRAS is used to rank and select the most efficient solution to manage the risks. The proposed framework was numerically applied to a case organisation involved in manufacturing/remanufacturing activities. The results indicate that initiatives from the management and modification in organisation goals is the top-ranked solution that would mitigate the majority of risks. Government, manufacturer and distributor collaboration to develop action plans and setting up international standards are also prominent solutions to overcome the risks. Further, this research performs a sensitivity analysis to check the robustness of the proposed fuzzy SWARA-fuzzy COPRAS framework. The findings and implications of this research will help the practitioners and researchers for decision-making in RSC.http://dx.doi.org/10.1080/19397038.2020.1758973sustainableremanufacturing supply chainriskfuzzy swarafuzzy copras |
| spellingShingle | Zulfiquar N. Ansari Ravi Kant Ravi Shankar Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach International Journal of Sustainable Engineering sustainable remanufacturing supply chain risk fuzzy swara fuzzy copras |
| title | Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach |
| title_full | Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach |
| title_fullStr | Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach |
| title_full_unstemmed | Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach |
| title_short | Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach |
| title_sort | evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks a hybrid fuzzy swara fuzzy copras framework approach |
| topic | sustainable remanufacturing supply chain risk fuzzy swara fuzzy copras |
| url | http://dx.doi.org/10.1080/19397038.2020.1758973 |
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