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Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool

Given the crucial role of the supplier selection problem (SSP) in today’s competitive business environment, the present study investigates the SSP by considering the leagile, sustainability, and Industry 4.0 (I4.0) indicators for the medical devices industry (MDI). In this regard, at the outset, the...

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Autor principal: ForouzeshNejad, Ali Akbar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491258/
https://www.ncbi.nlm.nih.gov/pubmed/36129658
http://dx.doi.org/10.1007/s11356-022-22916-x
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author ForouzeshNejad, Ali Akbar
author_facet ForouzeshNejad, Ali Akbar
author_sort ForouzeshNejad, Ali Akbar
collection PubMed
description Given the crucial role of the supplier selection problem (SSP) in today’s competitive business environment, the present study investigates the SSP by considering the leagile, sustainability, and Industry 4.0 (I4.0) indicators for the medical devices industry (MDI). In this regard, at the outset, the list of criteria and sub-criteria is provided based on the literature and experts’ opinions. Then, the importance of the indicators is measured utilizing the rough best–worst method (RBWM). In the next step, the potential suppliers are ranked employing the multi-attributive border approximation area comparison (IR-MABAC) method. Due to the crucial role of medical devices during the COVID-19 outbreak, the present work selects a project-based organization in this industry as a case study. The obtained results show that agility and sustainability are the most important criteria, and manufacturing flexibility, cost, reliability, smart factory, and quality are the most important sub-criteria. The main theoretical contributions of this study are considering the leagile, sustainability, and I4.0 criteria in the SSP and employing the hybrid RBWM-IR-MABAC method in this area for the first time. On the other side, The results of this research can help supply chain managers to become more familiar with the sustainability, agility, leanness, and I4.0 criteria in the business environment.
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spelling pubmed-94912582022-09-21 Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool ForouzeshNejad, Ali Akbar Environ Sci Pollut Res Int Research Article Given the crucial role of the supplier selection problem (SSP) in today’s competitive business environment, the present study investigates the SSP by considering the leagile, sustainability, and Industry 4.0 (I4.0) indicators for the medical devices industry (MDI). In this regard, at the outset, the list of criteria and sub-criteria is provided based on the literature and experts’ opinions. Then, the importance of the indicators is measured utilizing the rough best–worst method (RBWM). In the next step, the potential suppliers are ranked employing the multi-attributive border approximation area comparison (IR-MABAC) method. Due to the crucial role of medical devices during the COVID-19 outbreak, the present work selects a project-based organization in this industry as a case study. The obtained results show that agility and sustainability are the most important criteria, and manufacturing flexibility, cost, reliability, smart factory, and quality are the most important sub-criteria. The main theoretical contributions of this study are considering the leagile, sustainability, and I4.0 criteria in the SSP and employing the hybrid RBWM-IR-MABAC method in this area for the first time. On the other side, The results of this research can help supply chain managers to become more familiar with the sustainability, agility, leanness, and I4.0 criteria in the business environment. Springer Berlin Heidelberg 2022-09-21 2023 /pmc/articles/PMC9491258/ /pubmed/36129658 http://dx.doi.org/10.1007/s11356-022-22916-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 Research Article
ForouzeshNejad, Ali Akbar
Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
title Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
title_full Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
title_fullStr Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
title_full_unstemmed Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
title_short Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
title_sort leagile and sustainable supplier selection problem in the industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491258/
https://www.ncbi.nlm.nih.gov/pubmed/36129658
http://dx.doi.org/10.1007/s11356-022-22916-x
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