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Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model

The global spread of COVID-19, international trade protectionism, geopolitical conflicts, and climate change presents challenges and risks to sustainable supply chains (SSCs). In recent years, scholarly interest in sustainable supply chain risk management (SSCRM) has continued to rise. A helpful lit...

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Detalles Bibliográficos
Autores principales: Wang, Liang, Cheng, Yiming, Wang, Zeyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342943/
https://www.ncbi.nlm.nih.gov/pubmed/35915306
http://dx.doi.org/10.1007/s11356-022-22255-x
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author Wang, Liang
Cheng, Yiming
Wang, Zeyu
author_facet Wang, Liang
Cheng, Yiming
Wang, Zeyu
author_sort Wang, Liang
collection PubMed
description The global spread of COVID-19, international trade protectionism, geopolitical conflicts, and climate change presents challenges and risks to sustainable supply chains (SSCs). In recent years, scholarly interest in sustainable supply chain risk management (SSCRM) has continued to rise. A helpful literature review is necessary to enable supply chain practitioners to apply empirical findings from academic research or conceptual frameworks to their operations to maintain the stability and competitiveness of sustainable supply chains. The knowledge map of SSCRM is explored in this study using both quantitative and qualitative analysis. A total of 793 articles were retrieved to reveal the knowledge map of SSCRM. Scientometric and context analysis are combined in quantitative analysis to identify the intellectual structure of risk management research related to SSC. Then, a critical review is conducted in qualitative analysis to summarize and analyze the motivations, strategies, approaches, and tools of SSCRM. Combining the quantitative and qualitative analysis results, a conceptual model is constructed for SSCRM from three aspects: (1) risk identification, (2) risk assessment, and (3) risk mitigating and responding. Finally, future research directions are suggested based on the conceptual model for guiding the theories and practice of SSCRM. This study can work as a roadmap for providing appropriate risk management policies and toolkits to SSC, which could advance theoretical thinking on how to mitigate SSC risks.
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spelling pubmed-93429432022-08-02 Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model Wang, Liang Cheng, Yiming Wang, Zeyu Environ Sci Pollut Res Int Review Article The global spread of COVID-19, international trade protectionism, geopolitical conflicts, and climate change presents challenges and risks to sustainable supply chains (SSCs). In recent years, scholarly interest in sustainable supply chain risk management (SSCRM) has continued to rise. A helpful literature review is necessary to enable supply chain practitioners to apply empirical findings from academic research or conceptual frameworks to their operations to maintain the stability and competitiveness of sustainable supply chains. The knowledge map of SSCRM is explored in this study using both quantitative and qualitative analysis. A total of 793 articles were retrieved to reveal the knowledge map of SSCRM. Scientometric and context analysis are combined in quantitative analysis to identify the intellectual structure of risk management research related to SSC. Then, a critical review is conducted in qualitative analysis to summarize and analyze the motivations, strategies, approaches, and tools of SSCRM. Combining the quantitative and qualitative analysis results, a conceptual model is constructed for SSCRM from three aspects: (1) risk identification, (2) risk assessment, and (3) risk mitigating and responding. Finally, future research directions are suggested based on the conceptual model for guiding the theories and practice of SSCRM. This study can work as a roadmap for providing appropriate risk management policies and toolkits to SSC, which could advance theoretical thinking on how to mitigate SSC risks. Springer Berlin Heidelberg 2022-08-01 2022 /pmc/articles/PMC9342943/ /pubmed/35915306 http://dx.doi.org/10.1007/s11356-022-22255-x Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor 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 Review Article
Wang, Liang
Cheng, Yiming
Wang, Zeyu
Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
title Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
title_full Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
title_fullStr Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
title_full_unstemmed Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
title_short Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
title_sort risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342943/
https://www.ncbi.nlm.nih.gov/pubmed/35915306
http://dx.doi.org/10.1007/s11356-022-22255-x
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