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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
ID_Doc 66775
Authors Nejad, AAF
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
Year 2023
Published Environmental Science And Pollution Research, 30, 5
DOI 10.1007/s11356-022-22916-x
Abstract 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.
Author Keywords Supplier selection problem; Sustainability; Agility; Industry 4.0; Medical devices
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000858352300006
WoS Category Environmental Sciences
Research Area Environmental Sciences & Ecology
PDF https://link.springer.com/content/pdf/10.1007/s11356-022-22916-x.pdf
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