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Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach
Selecting the suppliers in a green supply chain (GSC) improves supply chain capabilities by considering environmental policies. On the other hand, considering the development of technology and intelligence of the Internet of Things (IoT) and their help to meet goals better, it is essential to study...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10182561/ http://dx.doi.org/10.1007/s41660-023-00336-9 |
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author | Bafandegan Emroozi, Vahideh Roozkhosh, Pardis Modares, Azam Roozkhosh, Farnoosh |
author_facet | Bafandegan Emroozi, Vahideh Roozkhosh, Pardis Modares, Azam Roozkhosh, Farnoosh |
author_sort | Bafandegan Emroozi, Vahideh |
collection | PubMed |
description | Selecting the suppliers in a green supply chain (GSC) improves supply chain capabilities by considering environmental policies. On the other hand, considering the development of technology and intelligence of the Internet of Things (IoT) and their help to meet goals better, it is essential to study them in this area. So, it is crucial to identify the influential factors of the IoT in selecting a green supplier and find its most important criteria for further monitoring and control. This paper aims to illustrate the ability of four different combinatorial multi-criteria decision-making (CMCDM) techniques in determining the best supplier in the rubber GSC. The suppliers are weighted using the fuzzy hierarchical analysis (FAHP) method, then ranked using four methods: VIKOR, TOPSIS, ELECTERE, and WASPAS. Then, their ranks are compared with each other. Eventually, Spearman’s rank correlation was examined to compare CMCDM methods. The results indicate that there is a similar ranking between all four CMCDM methods. Finally, it was found the second supplier is the best alternative for rubber companies looking for environmentally friendly suppliers. Also, FAHP-ELECTERE and FAHP-WASPAS methods have a high correlation with each other. The developed method can help decision-makers to make prompt decisions with less environmental pollution, which helps to achieve sustainable performance in the entire supply chain. |
format | Online Article Text |
id | pubmed-10182561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-101825612023-05-14 Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach Bafandegan Emroozi, Vahideh Roozkhosh, Pardis Modares, Azam Roozkhosh, Farnoosh Process Integr Optim Sustain Original Research Paper Selecting the suppliers in a green supply chain (GSC) improves supply chain capabilities by considering environmental policies. On the other hand, considering the development of technology and intelligence of the Internet of Things (IoT) and their help to meet goals better, it is essential to study them in this area. So, it is crucial to identify the influential factors of the IoT in selecting a green supplier and find its most important criteria for further monitoring and control. This paper aims to illustrate the ability of four different combinatorial multi-criteria decision-making (CMCDM) techniques in determining the best supplier in the rubber GSC. The suppliers are weighted using the fuzzy hierarchical analysis (FAHP) method, then ranked using four methods: VIKOR, TOPSIS, ELECTERE, and WASPAS. Then, their ranks are compared with each other. Eventually, Spearman’s rank correlation was examined to compare CMCDM methods. The results indicate that there is a similar ranking between all four CMCDM methods. Finally, it was found the second supplier is the best alternative for rubber companies looking for environmentally friendly suppliers. Also, FAHP-ELECTERE and FAHP-WASPAS methods have a high correlation with each other. The developed method can help decision-makers to make prompt decisions with less environmental pollution, which helps to achieve sustainable performance in the entire supply chain. Springer Nature Singapore 2023-05-13 /pmc/articles/PMC10182561/ http://dx.doi.org/10.1007/s41660-023-00336-9 Text en © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. 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 | Original Research Paper Bafandegan Emroozi, Vahideh Roozkhosh, Pardis Modares, Azam Roozkhosh, Farnoosh Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach |
title | Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach |
title_full | Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach |
title_fullStr | Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach |
title_full_unstemmed | Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach |
title_short | Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach |
title_sort | selecting green suppliers by considering the internet of things and cmcdm approach |
topic | Original Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10182561/ http://dx.doi.org/10.1007/s41660-023-00336-9 |
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