A conceptual framework to explain the role of building information modeling in smart cities

The expansion of data-driven technologies in smart cities has highlighted the need to examine the role of Building Information Modeling (BIM) beyond building-scale information management, in relation to urban information integration and decision support. A considerable part of the existing literature focuses on the relationships between BIM, geographic information systems (GIS), the Internet of Things (IoT), City Information Modeling (CIM), digital twins, and artificial intelligence (AI), while the evolving role of building information has rarely been explained within an integrated conceptual framework. Adopting a narrative-analytical approach, this study analyzes and synthesizes the relevant literature along nine dimensions: scale, information sources, integration, semantic interoperability, urban information environment, intelligence mechanisms, decision support, application domains, and cross-cutting challenges. Based on this synthesis, a five-layer conceptual framework is proposed, comprising the building information base, information integration, the urban information environment, urban intelligence, and decision support and institutional coordination are treated as cross-cutting conditions; in Iran, the policy context of these conditions relates to data-driven governance requirements in upstream documents such as Article 107 of the Seventh Development Plan Law. The synthesis indicates that BIM is neither a standalone solution for making cities smart nor a mandatory stage before the formation of an urban information environment or a digital twin; rather, its information can contribute to evidence generation and decision support through linkage with complementary sources, organization within an urban information environment, and participation in analytical processes. The proposed framework provides a conceptual basis for guiding future research.