PMID- 37090494
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230425
IS  - 2212-8271 (Print)
IS  - 2212-8271 (Electronic)
IS  - 2212-8271 (Linking)
VI  - 100
DP  - 2021
TI  - Designing supplier selection strategies under COVID-19 constraints for industrial 
      environments.
PG  - 589-594
LID - 10.1016/j.procir.2021.05.128 [doi]
AB  - COVID-19 has been impacting worldwide supply chains causing interruption, closure 
      of production and distribution. This impact has been drastic on the supplier side 
      and, as a consequence of disruptions, strong reductions of production have been 
      estimated. Such a circumstance forces companies to propose innovative best 
      practices of supply chain risk management aimed at facing vulnerability generated 
      by COVID-19 and pursuing industrial improvements in manufacturing and production 
      environments. As a part of supply chain strategy, supplier selection criteria 
      should be revised to include pandemic-related risks. This article aims to propose 
      an answer to such a problem. In detail, a comprehensive tool designed as a hybrid 
      combination of multi-criteria decision-making (MCDM) methods is suggested to 
      manage important stages connected to the production development cycle and to 
      provide companies with a structured way to rank risks and easily select their 
      suppliers. The main criteria of analysis will be first identified from the 
      existent literature. Risks related to COVID-19 will be then analysed in order to 
      elaborate a comprehensive list of potential risks in the field of interest. The 
      Best Worst Method (BWM) will be first used to calculate criteria weights. The 
      Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) 
      will be then applied to rank and prioritize risks affecting suppliers. The 
      effectiveness of the approach will be tested through a case study in the sector 
      of automotive industry. The applicability of the designed MCDM framework can be 
      extended also to other industrial sectors of interest.
CI  - (c) 2021 The Author(s). Published by Elsevier B.V.
FAU - Ilyas, Mzougui
AU  - Ilyas M
AD  - Faculty of Science and Technologies, Abdelmalek Essaadi University, Tangier, 
      90000, Morocco.
FAU - Carpitella, Silvia
AU  - Carpitella S
AD  - Department of Decision-Making Theory, Institute of Information Theory and 
      Automation, Czech Academy of Sciences, Prague, 18208, Czech Republic.
FAU - Zoubir, ElFelsoufi
AU  - Zoubir E
AD  - Faculty of Science and Technologies, Abdelmalek Essaadi University, Tangier, 
      90000, Morocco.
LA  - eng
PT  - Journal Article
DEP - 20210602
PL  - Netherlands
TA  - Procedia CIRP
JT  - Procedia CIRP
JID - 101704659
PMC - PMC10110395
OTO - NOTNLM
OT  - BWM
OT  - COVID-19
OT  - FTOPSIS
OT  - Supplier risks
OT  - Supplier selection
EDAT- 2021/01/01 00:00
MHDA- 2021/01/01 00:01
PMCR- 2021/06/02
CRDT- 2023/04/24 03:42
PHST- 2021/01/01 00:01 [medline]
PHST- 2021/01/01 00:00 [pubmed]
PHST- 2023/04/24 03:42 [entrez]
PHST- 2021/06/02 00:00 [pmc-release]
AID - S2212-8271(21)00602-8 [pii]
AID - 10.1016/j.procir.2021.05.128 [doi]
PST - ppublish
SO  - Procedia CIRP. 2021;100:589-594. doi: 10.1016/j.procir.2021.05.128. Epub 2021 Jun 
      2.