Trends of GIS-based Multi-Criteria Decision-Making (GIS-MCDM) in site selection for electric vehicle charging stations: A bibliometric analysis

Abstract

With the rapid expansion of electric vehicles (EVs), optimizing charging infrastructure has become essential for advancing sustainable transportation. The integration of Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) methods provides a robust scientific framework for selecting electric vehicle charging station (EVCS) locations. This bibliometric study analyses 1336 WoS Core Collection records (2016–2025; 2025 partial-year) and highlights four thematic clusters. Annual output peaks in 2022 (18.039%) and 2024 (18.563%), with leading national shares from China (18.713%), India (16.692%), and Iran (13.323%). VOSviewer network mapping delineates four cohesive clusters—EVCS layout/planning, GIS–MCDM methods, spatial sustainability, and uncertainty/risk—providing a structured lens for evidence-based synthesis. A focused mapping restricted to GIS and MCDM for EVCS siting—read directly from VOSviewer co-occurrence structures and clusters—yields EVCS-specific evidence that domain-wide surveys do not resolve with comparable clarity. The analysis includes keyword co-occurrence, author collaboration networks, country and institutional influence, journal contributions, and citation networks. The study identifies core research themes, key contributors, and high-impact journals in this field. We position the contribution as an EVCS-specific, cluster-wise interpretation of GIS–MCDM developed within a transparent WoS-only pipeline with verbatim query disclosure, which strengthens traceability and is intended to facilitate reproducibility for planning-oriented evidence. The research insights aim to support the development of intelligent and sustainable charging networks.