Emerging trends and applications of fuzzy decision-making techniques in financial supply chains: a comprehensive dual-source bibliometric analysis

The purpose of this paper is to examine the evolution and usefulness of fuzzy decision-making techniques in Financial Supply Chain (FSC) research, specifically, how fuzzy methods address uncertainty, complexity, and sustainability in the financial decision space. A dual source bibliometric analysis of 230 peer-reviewed articles published from 2004 until 3 June 2025 was completed, drawn from Scopus and Web of Science. The PRISMA methodology was implemented for data screening. The R-based Bibliometrix package was utilized for citation, co-word, and thematic mapping analyses to highlight leading authors, countries, and methods such as Fuzzy AHP, TOPSIS, Delphi, DEMATEL, and hybrid AI-blockchain models. The study established that the level of research activity has significantly increased following 2016, especially three major thematic shifts: moving from developing methodologies to developing fuzzy MCDM models to more applied studies, specifically to credit risk, supplier selection, and sustainable finance, and hybrid and intelligent data-driven FSC systems embedding AI and blockchain. China and India were leaders across interdisciplinary domains within Computer Science, Engineering, and Management. To summarize, this study presents the first comprehensive research map regarding fuzzy-FSC studies and assists the field by harnessing methodological advancement and providing pathways for practical and practitioners identifying opportunities in adaptive, data-driven, and sustainable FSC.