Applications of VIKOR Methodin Supplier Selection: A Meta-Regression Analysis

Abstract

This study attempts to systematically analyze empirical studies using VIKOR method in solving supplier selection problem and to identify the factors affecting mean S (MS) scores through use of meta-regression analysis.Design/methodology/approach -The sample size of this meta-analysis study consisted of 44 empirical papers obtained from nine databases and meeting the inclusion criteria.Findings -Systematic review results revealed that the use of VIKOR method has been increasing rapidly in the solution of supplier selection problems. Meta-regression analysis results suggested that the number of decision makers, number of alternatives, number of criteria, country and sector variables did not affect MS scores.Discussion -Using the fuzzy VIKOR method to solve the supplier selection problem were identified to provide a lower MS score, while using the integrated VIKOR method ensured a higher MS score. Detailed studies will provide a better understanding of the relationship between MS scores and the qualities of studies reporting these scores.Recently, the number of researchers using VIse Kriterijumsa Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) methods are rapidly increasing in the solution of the supplier selection problem. Using these two methods helps in choosing the best supplier based on different criteria, considering their relative importance (Prasad, 2017). The VIKOR method is known as a convenient and useful decision-making approach that concentrates on selecting from a set of alternatives in the presence of conflicting criteria that may help decision makers make a final decision (Opricovic & Tzeng, 2004).One reason for the growing interest in MCDM methods used in supplier selection and an increase in empirical studies is the heterogeneity of the results. The relevant literature holds a large number of studies A. Anafarta -N.