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Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics
Although the global green supply chain management (GSCM) practice has attracted considerable scholarly attention, its efficacy for environmental management systems (EMS) and market competitiveness during Covid-19 has not been fully capitalized. Therefore, the existing literature indicates that the i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439874/ https://www.ncbi.nlm.nih.gov/pubmed/36090699 http://dx.doi.org/10.1016/j.techsoc.2022.102021 |
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author | Zhang, Qingyu Gao, Bohong Luqman, Adeel |
author_facet | Zhang, Qingyu Gao, Bohong Luqman, Adeel |
author_sort | Zhang, Qingyu |
collection | PubMed |
description | Although the global green supply chain management (GSCM) practice has attracted considerable scholarly attention, its efficacy for environmental management systems (EMS) and market competitiveness during Covid-19 has not been fully capitalized. Therefore, the existing literature indicates that the important link between GSCM, EMS, and market competitiveness is missing as supply management is crucial to maintaining market competitiveness. To fill this research gap, the current study examines whether EMS affects the relationship between GSCM practices and market competitiveness. We also propose the moderating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility on these associations from a Covid-19 perspective. We tested a proposed model using the primary data (N = 283) from regression-based structural equation modeling (SEM). The results provide empirical support for the impact of GSCM on ESM and market competitiveness. Furthermore, the results show that BDA-AI and environmental visibility strengthen the positive relationship between GSCM-EMS and EMS and market competitiveness, respectively. Current research provides thoughtful insights for supply chain practitioners, policymakers, managers, and academics that organizations should opt for formal EMS, BDA-AI, and environmental visibility to achieve market competitiveness, even in times of crisis such as Covid-19. |
format | Online Article Text |
id | pubmed-9439874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94398742022-09-06 Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics Zhang, Qingyu Gao, Bohong Luqman, Adeel Technol Soc Article Although the global green supply chain management (GSCM) practice has attracted considerable scholarly attention, its efficacy for environmental management systems (EMS) and market competitiveness during Covid-19 has not been fully capitalized. Therefore, the existing literature indicates that the important link between GSCM, EMS, and market competitiveness is missing as supply management is crucial to maintaining market competitiveness. To fill this research gap, the current study examines whether EMS affects the relationship between GSCM practices and market competitiveness. We also propose the moderating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility on these associations from a Covid-19 perspective. We tested a proposed model using the primary data (N = 283) from regression-based structural equation modeling (SEM). The results provide empirical support for the impact of GSCM on ESM and market competitiveness. Furthermore, the results show that BDA-AI and environmental visibility strengthen the positive relationship between GSCM-EMS and EMS and market competitiveness, respectively. Current research provides thoughtful insights for supply chain practitioners, policymakers, managers, and academics that organizations should opt for formal EMS, BDA-AI, and environmental visibility to achieve market competitiveness, even in times of crisis such as Covid-19. Elsevier Ltd. 2022-08 2022-06-17 /pmc/articles/PMC9439874/ /pubmed/36090699 http://dx.doi.org/10.1016/j.techsoc.2022.102021 Text en © 2022 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 Zhang, Qingyu Gao, Bohong Luqman, Adeel Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics |
title | Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics |
title_full | Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics |
title_fullStr | Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics |
title_full_unstemmed | Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics |
title_short | Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics |
title_sort | linking green supply chain management practices with competitiveness during covid 19: the role of big data analytics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439874/ https://www.ncbi.nlm.nih.gov/pubmed/36090699 http://dx.doi.org/10.1016/j.techsoc.2022.102021 |
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