Supplier Selection during the COVID-19 Pandemic Situation by Applying Fuzzy TOPSIS: A Case Study

Iman Ajripour

doi:10.2478/auseb-2022-0006

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Supplier Selection during the COVID-19 Pandemic Situation by Applying Fuzzy TOPSIS: A Case Study

Acta Universitatis Sapientiae, Economics and Business

Volume 10 (2022): Issue 1 (September 2022)

By: Iman Ajripour

Open Access

|Oct 2022

Abstract

During the COVID-19 pandemic situation, many factories, companies, and organizations faced difficulties supplying raw materials. Multi-criteria decision-making techniques (MCDM) could be a proper solution that helps managers to make an appropriate and fast decision in supplier selection in such unusual situation. The goal of my research is not only to employ the technique for order of preference by similarity to ideal solution (TOPSIS) in a fuzzy environment but also to use a new criterion, namely “number of employees”, for evaluating suppliers during the COVID-19 pandemic situation. Applying fuzzy logic during unstable conditions helps decision makers to make a logical and more precise decision. In this study, five criteria, that is, quality, delivery, price, number of employees, and lead time, are considered to compare and select an appropriate supplier. The results show that “number of employees” is an essential criterion in supplier selection during abnormal conditions like the COVID-19 pandemic situation.

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Articles in this issue

DOI: https://doi.org/10.2478/auseb-2022-0006 | Journal eISSN: 2360-0047 (formerly 2343-8894)

Journal RSS Feed

Language: English

Page range: 91 - 105

Published online: Oct 13, 2022

Published in print: Sep 1, 2022

Published by: Sapientia Hungarian University of Transylvania

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

multi-criteria decision-making,

alternatives,

number of employees

JEL:

C44,

D70

Related subjects:

Business and economics,

Political economics,

Economic theory, systems and structures

© 2022 Iman Ajripour, published by Sapientia Hungarian University of Transylvania
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 10 (2022): Issue 1 (September 2022)