Integrated Fuzzy-MSGP Methods for Clothing and Textiles Supplier Evaluation and Selection in the COVID-19 Era
Hsin Kao
Abstract
Supplier selection is an important issue in supply chain management (SCM) which, as with most dimensions of business, has been strongly impacted by the COVID-19 pandemic. Previous research on the clothing and textiles (C&T) industry has overlooked efforts to provide a regular reference method for addressing the problem of supplier selection. This study discusses the COVID-19 pandemic’s impact on, and the relative importance of, supplier selection implementation. This study applied fuzzy techniques for order preference by similarity to ideal solution (TOPSIS) and multisegment goal programming (MSGP) method to the problem of supplier selection and combined these two methods to propose a novel multicriteria decision-making (MCDM) method to be used by C&T companies. It proposes a simple method to provide decision-makers (DMs) with guidelines for supplier selection considering existing constraints on business resources. The advantage of this method is the incorporation of both qualitative and quantitative criteria (e.g., both tangible and intangible resources), which allows DMs to set multisegment aspiration levels (MSALs) for supplier selection. A case study of a C&T manufacturer’s application of the model is also presented.