BIM Applications in Transportation Infrastructure: A Bibliometric and Systematic Literature Review

Abstract

This study presents a comprehensive bibliometric analysis combined with a Systematic Literature Review (SLR) to examine the global research landscape of Building Information Modeling (BIM) applications in transportation infrastructure. The motivation of this study arises from the increasing complexity of modern infrastructure systems, including railways, tunnels, bridges, roads, and airports, which require advanced digital solutions to address challenges related to interoperability, lifecycle management, and data integration. A total of 1,615 peer-reviewed articles published between 2010 and July 2025 were retrieved from the Scopus database. Bibliometric techniques, including keyword co-occurrence and citation analysis, were applied using Visualization of Similarities viewer (VOSviewer), followed by an in-depth systematic review of the most influential publications. The results indicate a substantial increase in research activity after 2018, with railway infrastructure emerging as a major application domain. Five principal thematic clusters are identified: Geographic Information Systems (GIS) integration, Digital Twins (DT), tunnel and bridge engineering, lifecycle sustainability, and smart monitoring technologies. Keyword evolution analysis further reveals a transition from design-oriented studies prior to 2020 toward asset management and digital intelligence after 2022. The study also identifies leading journals and key technologies shaping current research trends, while recent publications in 2025 demonstrate increasing attention to immersive DT, robotic manufacturing, and multi-criteria decision-making frameworks. This study contributes by systematically mapping the development of BIM knowledge in transportation infrastructure and identifying underexplored areas, particularly in operation and maintenance applications and regional disparities in research output. Limitations include the reliance on Scopus-indexed, English-language publications and the use of citation-based selection criteria, which may introduce bias toward older, highly cited studies. Despite these limitations, the findings provide valuable insights for researchers, practitioners, and policymakers seeking to align future efforts with ongoing digital transformation in transportation infrastructure.