Financial Performance Evaluation of Leading Retail Companies in BIST Utilizing Decomposed Fuzzy TOPSIS

Abstract

Evaluation of the financial performance of companies has a wide range of applications and indicators. The evaluation process has become much more complicated and crucial especially during and after the pandemics. Fuzzy sets were first introduced to be able to cope with uncertainty and vagueness in real-world applications. Since its introduction, various extensions of fuzzy sets have developed. In this paper, decomposed fuzzy sets (DFS) which were recently proposed fuzzy set extensions have been utilized. In this study, the Decomposed Fuzzy Technique for Order Preference by Similarities to Ideal Solution (DF TOPSIS) has been applied to assess leading retail companies in Borsa Istanbul (BIST). According to this approach, the criteria set has been determined by literature review and experts' opinions and the leading companies in ISE have been evaluated based on the determined criteria set. Considering the vagueness and imprecise information in the decision-making environment, we believe this study will create a strong roadmap for those such as stakeholders and investors who are interested in analyzing the financial performance of the companies.