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Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach
Industry 4.0 has the potential of growing industrialization and, on the other hand, disrupting the sustainability of prevailing manufacturing supply chains through inducing great challenges such as higher resource consumption that, in turn, results in global warming and climate change. As a result,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092048/ http://dx.doi.org/10.1007/s12063-021-00243-7 |
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author | Xin, Lulu Lang, Shuai Mishra, Arunodaya Raj |
author_facet | Xin, Lulu Lang, Shuai Mishra, Arunodaya Raj |
author_sort | Xin, Lulu |
collection | PubMed |
description | Industry 4.0 has the potential of growing industrialization and, on the other hand, disrupting the sustainability of prevailing manufacturing supply chains through inducing great challenges such as higher resource consumption that, in turn, results in global warming and climate change. As a result, researchers working in the area of sustainable supply chain 4.0 need to make deep evaluations on the challenges arising for manufacturing supply chains contemplating the improvement of their sustainability levels and having a digital transformation toward Industry 4.0. To fill this gap, the current paper designs an innovative framework on the basis of the Stepwise Weight Assessment Ratio Analysis (SWARA) technique and the Complex Proportional Assessment (COPRAS) approach to evaluate the challenges that may arise for supply chain 4.0 in the q-Rung Orthopair Fuzzy Sets (q-ROFSs) setting. The proposed method uses an extended SWARA process to determine the criteria importance degrees considering the experts’ preferences. The performance of the proposed method was assessed by conducting an empirical case study under the q-ROFSs condition. Further, a sensitivity analysis was executed to check whether the proposed method is stable enough to be relied on parameter values. Finally, the results obtained were compared to those of currently used methods to verify the obtained results’ reliability. As revealed by the comparative results, the framework proposed in this article was of higher consistency and strength compared to other prevailing approaches. |
format | Online Article Text |
id | pubmed-9092048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-90920482022-05-11 Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach Xin, Lulu Lang, Shuai Mishra, Arunodaya Raj Oper Manag Res Article Industry 4.0 has the potential of growing industrialization and, on the other hand, disrupting the sustainability of prevailing manufacturing supply chains through inducing great challenges such as higher resource consumption that, in turn, results in global warming and climate change. As a result, researchers working in the area of sustainable supply chain 4.0 need to make deep evaluations on the challenges arising for manufacturing supply chains contemplating the improvement of their sustainability levels and having a digital transformation toward Industry 4.0. To fill this gap, the current paper designs an innovative framework on the basis of the Stepwise Weight Assessment Ratio Analysis (SWARA) technique and the Complex Proportional Assessment (COPRAS) approach to evaluate the challenges that may arise for supply chain 4.0 in the q-Rung Orthopair Fuzzy Sets (q-ROFSs) setting. The proposed method uses an extended SWARA process to determine the criteria importance degrees considering the experts’ preferences. The performance of the proposed method was assessed by conducting an empirical case study under the q-ROFSs condition. Further, a sensitivity analysis was executed to check whether the proposed method is stable enough to be relied on parameter values. Finally, the results obtained were compared to those of currently used methods to verify the obtained results’ reliability. As revealed by the comparative results, the framework proposed in this article was of higher consistency and strength compared to other prevailing approaches. Springer US 2022-05-11 2022 /pmc/articles/PMC9092048/ http://dx.doi.org/10.1007/s12063-021-00243-7 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Xin, Lulu Lang, Shuai Mishra, Arunodaya Raj Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
title | Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
title_full | Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
title_fullStr | Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
title_full_unstemmed | Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
title_short | Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
title_sort | evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092048/ http://dx.doi.org/10.1007/s12063-021-00243-7 |
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