| Autor: |
Jui-Chung Kao, Chia-Nan Wang, Viet Tinh Nguyen, Syed Tam Husain |
| Předmět: |
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| Zdroj: |
Intelligent Automation & Soft Computing; 2022, Vol. 31 Issue 3, p1451-1466, 16p |
| Abstrakt: |
According to a new study by the International Labor Organization (ILO), the COVID-19 pandemic has had a strong impact on the garment industry in the Asia-Pacific region. A sharp drop in retail sales in key export markets has affected workers and businesses across supply chains. To ensure the effectiveness and efficiency of garment supply chain, choosing a sustainable supplier should be a main concern of all businesses. The supplier selection problem in garment industry involves multiple quantitative and qualitative criteria. There have been many research and literatures about the development and application of Multicriteria Decision Making (MCDM) models in solving decision-making problems in different industry sectors such as supplier selection or investment assessment. Many different MCDM models have been introduced over the years, and each model is uniquely dedicated into solving a particular problem. There is very little MCDM models incorporated with fuzzy set theory to support decision makers with decision-making problem in uncertain environments. This paper introduces a Fuzzy MCDM-based approach to the problem by utilizing Fuzzy-Analytic Hierarchical Process (FAHP) and Weighted Aggregated Sum Product Assessment (WASPAS) methods to support the decision makers. The aim of the paper is developing a decision-making tool that supports the decision maker in deciding the suitable supplier in garment industry under fuzzy environment. The proposed MCDM model is applied to a real-world case study to demonstrate the application steps of the model as well as its feasibility. The model assisted in successfully its proposed goals that resulted in an optimal supplier in garment industry. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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