This study examines how Building Information Modelling (BIM) and Digital Twin (DT) practices can be systematically extended into City Information Modelling (CIM) to enable evidence-based, bottom-up urban planning. Objectives were to map the BIM–DT–CIM literature, identify interoperable architectures that integrate GIS, IoT, and analytics, evaluate mechanisms for embedding citizen participation, and quantify persistent research gaps. We conducted a reproducible systematic review using staged searches across major databases (Scopus, Web of Science, IEEE Xplore, ACM, SpringerLink), exported and deduplicated results, and screened 1,124 records to a final corpus of 68 peer-reviewed studies; data were extracted using a standardised template and appraised with a technical maturity checklist. Key findings show that only 21% of included studies reported implemented citizen-participation mechanisms and 15% addressed cross-domain standard models; pilot projects that operationalised CIM reported an average planning-efficiency improvement of 18% (±4% SE) compared to baseline workflows. Major error sources include heterogeneity in metrics, inconsistent reporting of evaluation methods, and limited longitudinal evidence, which constrain meta-analytic synthesis. We conclude with a reproducible framework and an agenda prioritising standards, participatory evaluation, and data-governance experiments.
Adeola et al. (Tue,) studied this question.