The dynamic evolution laws and trends of multi-attribute decision-making research from an international perspective: a knowledge mapping analysis based on CiteSpace

Multi-attribute decision-making (MADM) has expanded rapidly in engineering, management, and public policy, yet a systematic quantitative overview of its global evolution, collaboration patterns, and research frontiers remains lacking. To address this gap, this study conducts a bibliometric analysis of 5208 MADM-related publications indexed in the Web of Science (WOS) core collection (1978–2024), using CiteSpace and Origin to examine: temporal development, international and institutional collaboration, and the shifting intellectual base and research hotspots. The result reveals the following findings: (1) The development of the field exhibits a three-phase characteristic (foundation, explosive growth, and subsequent deepening), with the trend highly fitting the Boltzmann function, indicating continued growth in the future; (2) International collaboration is widespread but loosely connected, with China leading in publication output, while research institutions are dispersed with insufficient coordination; (3) The dominant disciplines are computer science and artificial intelligence, with a gradual expansion into multiple fields such as regional and urban planning, architecture, and marine engineering; (4) Co-authorship and co-citation analyses identify influential authors, journals, and seminal papers, and reveal a hotspot shift from basic methodological optimization (e.g., AHP, fuzzy sets) to advanced decision models and aggregation operators, and more recently to applications in renewable energy, geographic information systems, and industrial development. This research provides a quantitative basis for understanding the development patterns and frontier directions of international MADM.