Evolution, trends, and research frontiers of multi-criteria decision-making in sustainability: Analyses of articles (1993–2025)

Multi-criteria decision-making (MCDM) has been successful in managing the complex trade-offs in sustainability challenges. Despite numerous studies combining MCDM and sustainability, no thorough bibliometric study has mapped the development, structure, and key areas of this field from its beginnings to now. This study fills that gap by performing a large-scale bibliometric analysis of 16,970 articles published between 1993 and 2025, retrieved from the Web of Science Core Collection (SCI-Expanded and SSCI). By using Bibliometrix (biblioshiny) and VOSviewer, annual scientific output, distribution of sources, author productivity and collaboration, contributions from institutions and countries, keyword co-occurrence, thematic mapping, co-citation networks, and bibliographic coupling are evaluated. The results show a notable 28.5% compound annual growth rate (CAGR), indicating that the field remains firmly in its growth phase, with 42.2% of anticipated saturation. China leads in output, followed by India, Iran, Turkey, and Spain. Dragan Pamucar, Liu Y., and Kumar A. rise as the most productive authors, while Kannan Govindan ranks among the most influential. Analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are the main methods, while fuzzy extensions make up the largest thematic cluster, which is 26.4% of the total. Thematic mapping identifies AHP combined with geographic information systems (GIS) as a niche motor theme, along with new areas such as green hydrogen, Industry 5.0, machine learning hybridization, and spatiotemporal MCDM approaches. Co-citation analysis links the intellectual foundations to Lotfi A Zadeh (1965), Saaty (1977, 1980), and Opricovic and Tzeng (2004). These outcomes provide solid evidence for researchers, practitioners, and policymakers aiming to navigate the MCDM-sustainability connection and find productive paths for future research.