Fuzzy set-based decision-making methods in business management and finance research: a systematic literature review

Abstract This study conducted a SLR to examine how fuzzy set-based decision-making methods have been applied within the domains of business management and finance. Although these methods have become increasingly important for managing uncertainty and complexity, there had been no comprehensive review that systematically synthesized their use across business and financial contexts. The purpose of this study was to identify the main fuzzy set-based methods used, examine their areas of application, and explore research trends. The review followed a structured and replicable approach using data retrieved from the Scopus database for the years 2014 to 2025. Articles were screened using Rayyan, and only those that directly focused on fuzzy decision-making within business and finance were included. The findings showed a marked increase in publications after 2014, signaling growing scholarly attention. Methods such as Fuzzy AHP and Fuzzy TOPSIS were the most frequently applied, reflecting their suitability for handling multi-criteria decision problems. These methods were particularly prominent in financial risk assessment and investment decision-making. These results offered a foundation for future research and provided guidance for practitioners seeking to adopt more effective and adaptive decision support tools in uncertain and complex environments.