Three Decades of Fuzzy AHP: A Bibliometric Analysis

Abstract

For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field’s agenda to advise the editors of high-impact journals on gaps and new research trends.

The pathway towards circular economy: Measuring circular advantage of eco‐innovations

“…Given its ability to capture the multidimensional nature of decision-making problems as well as the possibility to deal with quantitative and qualitative criteria while ensuring the stakeholder centrality in the evaluation process, AHP has been widely applied to help decision-makers in sustainability decisions (Diaz-Balteiro et al, 2017;Kwatra et al, 2021;Tošovi c-Stevanovi c et al, 2020). To handle the intrinsic vagueness inherent in the subjective evaluations that characterize sustainability evaluations, AHP is commonly integrated with fuzzy logic (Castell o-Sirvent et al, 2022). However, considering that AHP, as well as the fuzzy extension, requires a very large number of pairwise comparisons when the number of items to be compared increases, the use of fuzzy ARAS as a continuation of fuzzy AHP has been successfully applied to minimize the need to collect experts' judgments and better deal with subjectivity (Nguyen et al, 2016).…”