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Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment

Given the critical importance of green technology implementation (GTI) is important for production process improvement and an eco-friendly environment. The present study investigates the connection between GTI and the knowledge management (KM) process to minimize manufacturing risk. This research al...

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Autores principales: Alam, Sajjad, Zhang, Jianhua, Khan, Naveed, Ali, Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947890/
https://www.ncbi.nlm.nih.gov/pubmed/36820977
http://dx.doi.org/10.1007/s11356-023-25945-2
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author Alam, Sajjad
Zhang, Jianhua
Khan, Naveed
Ali, Ahmad
author_facet Alam, Sajjad
Zhang, Jianhua
Khan, Naveed
Ali, Ahmad
author_sort Alam, Sajjad
collection PubMed
description Given the critical importance of green technology implementation (GTI) is important for production process improvement and an eco-friendly environment. The present study investigates the connection between GTI and the knowledge management (KM) process to minimize manufacturing risk. This research also validates that an assured combination of green implementation and KM can lead to minimizing manufacturing risk. The sample data (153) was taken from those manufacturing companies that utilize green technologies. Smart PLS 3.2.9 analyzes the relationship between certain variables of GTI and the KM process. Furthermore, fuzzy set qualitative comparative analysis (fsQCA) is used for a combined configurational approach to examine manufacturing risk minimization. The study’s outcome validated that green implementation positively correlated with KM to minimize production risk. fsQCA approach, KM, and green implementation outcome indicated that production risks are minimized. This study contributes to bridging research gaps in the literature and advances understanding of the interrelationship between green implementation and KM processes to minimize manufacturing risk. In addition, research is vital to combine direct and configurational methodologies to highlight two distinct facets of green implementation and the KM process for minimizing manufacturing risk.
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spelling pubmed-99478902023-02-23 Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment Alam, Sajjad Zhang, Jianhua Khan, Naveed Ali, Ahmad Environ Sci Pollut Res Int Research Article Given the critical importance of green technology implementation (GTI) is important for production process improvement and an eco-friendly environment. The present study investigates the connection between GTI and the knowledge management (KM) process to minimize manufacturing risk. This research also validates that an assured combination of green implementation and KM can lead to minimizing manufacturing risk. The sample data (153) was taken from those manufacturing companies that utilize green technologies. Smart PLS 3.2.9 analyzes the relationship between certain variables of GTI and the KM process. Furthermore, fuzzy set qualitative comparative analysis (fsQCA) is used for a combined configurational approach to examine manufacturing risk minimization. The study’s outcome validated that green implementation positively correlated with KM to minimize production risk. fsQCA approach, KM, and green implementation outcome indicated that production risks are minimized. This study contributes to bridging research gaps in the literature and advances understanding of the interrelationship between green implementation and KM processes to minimize manufacturing risk. In addition, research is vital to combine direct and configurational methodologies to highlight two distinct facets of green implementation and the KM process for minimizing manufacturing risk. Springer Berlin Heidelberg 2023-02-23 2023 /pmc/articles/PMC9947890/ /pubmed/36820977 http://dx.doi.org/10.1007/s11356-023-25945-2 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 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 Research Article
Alam, Sajjad
Zhang, Jianhua
Khan, Naveed
Ali, Ahmad
Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
title Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
title_full Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
title_fullStr Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
title_full_unstemmed Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
title_short Mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
title_sort mechanism of knowledge management process towards minimizing manufacturing risk under green technology implementation: an empirical assessment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947890/
https://www.ncbi.nlm.nih.gov/pubmed/36820977
http://dx.doi.org/10.1007/s11356-023-25945-2
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