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A model for evaluating green credit rating and its impact on sustainability performance
The development of economic activities and social progress index leads to the governmental considerations for the environmental challenge’s issues. The Green Credit Policy (GCP) in China for manufacturing, as a part of a sustainable finance package, initiatives restrictions with suppliers to reduce...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521472/ https://www.ncbi.nlm.nih.gov/pubmed/33020685 http://dx.doi.org/10.1016/j.jclepro.2020.124299 |
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author | Nabeeh, Nada A. Abdel-Basset, Mohamed Soliman, Gawaher |
author_facet | Nabeeh, Nada A. Abdel-Basset, Mohamed Soliman, Gawaher |
author_sort | Nabeeh, Nada A. |
collection | PubMed |
description | The development of economic activities and social progress index leads to the governmental considerations for the environmental challenge’s issues. The Green Credit Policy (GCP) in China for manufacturing, as a part of a sustainable finance package, initiatives restrictions with suppliers to reduce harmful pollution for the environment. The study mainly validates the impact of GCP on manufacturing for diminishing the emerged pollution to the environment. The study develops Neutrosophic Multiple-Criteria Decision-Making Framework (N-MCDMF) according to neutrosophic theory and various MCDM methods of grey relational analysis (GRA), analytic network process (ANP), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to support the decision-makers with highly systematic procedures in the uncertain and inconsistent environmental conditions. The N-MCDMF evaluates the conditions of GCP and recommends the optimal Supply Chain Management (SCM) in manufacturing alternatives. A case study is presented for the validation of the issues of applicability and flexibility for the proposed N-MCDMF. The results obtained from the implementation of the N-MCDMF indicates the applicability and flexibility of the proposed approach. In addition, results show that SCM in manufacturing can provide more cooperation for the environment to reduce harmful pollution and to attain sustainability for achieving motivations under the restrictions of GCP. |
format | Online Article Text |
id | pubmed-7521472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75214722020-09-29 A model for evaluating green credit rating and its impact on sustainability performance Nabeeh, Nada A. Abdel-Basset, Mohamed Soliman, Gawaher J Clean Prod Article The development of economic activities and social progress index leads to the governmental considerations for the environmental challenge’s issues. The Green Credit Policy (GCP) in China for manufacturing, as a part of a sustainable finance package, initiatives restrictions with suppliers to reduce harmful pollution for the environment. The study mainly validates the impact of GCP on manufacturing for diminishing the emerged pollution to the environment. The study develops Neutrosophic Multiple-Criteria Decision-Making Framework (N-MCDMF) according to neutrosophic theory and various MCDM methods of grey relational analysis (GRA), analytic network process (ANP), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to support the decision-makers with highly systematic procedures in the uncertain and inconsistent environmental conditions. The N-MCDMF evaluates the conditions of GCP and recommends the optimal Supply Chain Management (SCM) in manufacturing alternatives. A case study is presented for the validation of the issues of applicability and flexibility for the proposed N-MCDMF. The results obtained from the implementation of the N-MCDMF indicates the applicability and flexibility of the proposed approach. In addition, results show that SCM in manufacturing can provide more cooperation for the environment to reduce harmful pollution and to attain sustainability for achieving motivations under the restrictions of GCP. Elsevier Ltd. 2021-01-20 2020-09-28 /pmc/articles/PMC7521472/ /pubmed/33020685 http://dx.doi.org/10.1016/j.jclepro.2020.124299 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Nabeeh, Nada A. Abdel-Basset, Mohamed Soliman, Gawaher A model for evaluating green credit rating and its impact on sustainability performance |
title | A model for evaluating green credit rating and its impact on sustainability performance |
title_full | A model for evaluating green credit rating and its impact on sustainability performance |
title_fullStr | A model for evaluating green credit rating and its impact on sustainability performance |
title_full_unstemmed | A model for evaluating green credit rating and its impact on sustainability performance |
title_short | A model for evaluating green credit rating and its impact on sustainability performance |
title_sort | model for evaluating green credit rating and its impact on sustainability performance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521472/ https://www.ncbi.nlm.nih.gov/pubmed/33020685 http://dx.doi.org/10.1016/j.jclepro.2020.124299 |
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