The study aimed to provide a comprehensive review and bibliometric analysis of City Information Modelling (CIM) research, focusing on its development, key contributions, and future directions.
The methodology combined bibliometric analysis and systematic review to critically examine the research gaps and future directions in CIM utilising the Web of Science (WoS), Scopus and Emerald Insight databases. The bibliometric analysis performed using VOSviewer combined the three databases to analyse 446 documents to identify publication trends, citation patterns and research hotspots combined the three databases. The bibliometric analysis is essential to understanding the field’s structure and identifying key contributions to CIM research. The study utilised the PRISMA systematic review method to analyse 89 documents to uncover the research gaps and future directions.
The study revealed that despite the upward growth of CIM research in 2023, CIM research remains fragmented, lacking a unified theoretical framework. Much of the existing work focuses on the technical integration of Building Information Modelling (BIM), Geographic information modelling (GIS), and the Internet of Things (IoT), often at the expense of socioeconomic and environmental considerations. A heavy reliance on limited case studies, small datasets, and past data hampers the generalizability of findings. While infrastructure, construction, and facility management dominate the discourse, there is comparatively little attention to governance, mobility, public-private partnerships, and social equity. To advance the field, the study identifies key areas for future research, such as developing governance frameworks, innovative asset management strategies, enhanced data security measures, and improved system interoperability. Emphasizing holistic and interdisciplinary approaches can enhance CIM’s relevance and impact, enabling it to effectively address a wider range of urban challenges.
This study addresses the fragmented state of CIM research by consolidating knowledge from diverse domains through the integration of bibliometric analysis and systematic review methods. It provides a framework for understanding CIM’s potential in smart, sustainable urban development. The findings underscore the need for holistic, data-driven approaches to inform policy and practice, offering new insights into the field’s trajectory.
