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Multi-criteria risk classification to enhance complex supply networks performance
Management of complex supply networks is a fundamental business topic today. Especially in the presence of many and diverse stakeholders, identifying and assessing those risks having a potential negative impact on the performance of supply processes is of utmost importance and, as a result, implemen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8561686/ http://dx.doi.org/10.1007/s12597-021-00568-8 |
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author | Carpitella, Silvia Mzougui, Ilyas Izquierdo, Joaquín |
author_facet | Carpitella, Silvia Mzougui, Ilyas Izquierdo, Joaquín |
author_sort | Carpitella, Silvia |
collection | PubMed |
description | Management of complex supply networks is a fundamental business topic today. Especially in the presence of many and diverse stakeholders, identifying and assessing those risks having a potential negative impact on the performance of supply processes is of utmost importance and, as a result, implementing focused risk management actions is a current lively field of research. The possibility of supporting Supply Chain Risks Management (SCRM) is herein explored from a Multi-Criteria Decision-Making (MCDM)-based perspective. The sorting method ELimination Et Choix Traduisant la REalité (ELECTRE) TRI is proposed as a structural procedure to classify Supply Chain Risks (SCRs) into proper risk classes expressing priority of intervention so as to ease the implementation of prevention and protection measures. This approach is intended to offer structured management insights by means of an immediate identification of the most highly critical risks in a wide set of previously identified SCRs. A real-world case study in the field of the automotive industry is implemented to show the applicability and usefulness of the approach. |
format | Online Article Text |
id | pubmed-8561686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-85616862021-11-02 Multi-criteria risk classification to enhance complex supply networks performance Carpitella, Silvia Mzougui, Ilyas Izquierdo, Joaquín OPSEARCH Application Article Management of complex supply networks is a fundamental business topic today. Especially in the presence of many and diverse stakeholders, identifying and assessing those risks having a potential negative impact on the performance of supply processes is of utmost importance and, as a result, implementing focused risk management actions is a current lively field of research. The possibility of supporting Supply Chain Risks Management (SCRM) is herein explored from a Multi-Criteria Decision-Making (MCDM)-based perspective. The sorting method ELimination Et Choix Traduisant la REalité (ELECTRE) TRI is proposed as a structural procedure to classify Supply Chain Risks (SCRs) into proper risk classes expressing priority of intervention so as to ease the implementation of prevention and protection measures. This approach is intended to offer structured management insights by means of an immediate identification of the most highly critical risks in a wide set of previously identified SCRs. A real-world case study in the field of the automotive industry is implemented to show the applicability and usefulness of the approach. Springer India 2021-11-02 2022 /pmc/articles/PMC8561686/ http://dx.doi.org/10.1007/s12597-021-00568-8 Text en © Operational Research Society of India 2021 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 | Application Article Carpitella, Silvia Mzougui, Ilyas Izquierdo, Joaquín Multi-criteria risk classification to enhance complex supply networks performance |
title | Multi-criteria risk classification to enhance complex supply networks performance |
title_full | Multi-criteria risk classification to enhance complex supply networks performance |
title_fullStr | Multi-criteria risk classification to enhance complex supply networks performance |
title_full_unstemmed | Multi-criteria risk classification to enhance complex supply networks performance |
title_short | Multi-criteria risk classification to enhance complex supply networks performance |
title_sort | multi-criteria risk classification to enhance complex supply networks performance |
topic | Application Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8561686/ http://dx.doi.org/10.1007/s12597-021-00568-8 |
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