Revealed Preference Theory: From Classical Foundations to Fuzzy Paradigms – A Bibliometric Analysis of Evolution and Applications

Abstract

This study examines the transformation of revealed preference theory through the integration of fuzzy logic, enabling the modeling of partial and ambiguous preferences. The aim is to map the intellectual structure and thematic development of this interdisciplinary field using quantitative bibliometric techniques. A dataset of 6,460 peer-reviewed articles (19752024) from the Web of Science was analyzed with the Bibliometrix R package. The results show a sharp increase in research after 2005, with a peak of over 600 publications in 2023. China, the United States, and India are the top contributors, while Sichuan University leads with 215 articles. Main clusters include fuzzy decision-making, preference modeling, and group decision support. Even if theoretical contributions are strong, real-world applications such as smart systems and sustainable policy design remain limited. This study is among the first to comprehensively visualize and assess the evolution of fuzzy revealed preference theory, offering a direction for future interdisciplinary research.

Keywords

Fuzzy logic / decision science / revealed preferences / bibliometric analysis / uncertainty modeling

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