Intelligent building information modeling applications in real estate development: a scientometric mapping with implications for decision support and implementation

Abstract

Research on intelligent Building Information Modeling (BIM) applications in real estate development spans construction engineering, energy and carbon assessment, geospatial analysis, property valuation, project delivery, and asset management, yet its decision-support functions and implementation conditions remain fragmented. This study synthesizes English-language publications indexed in Web of Science Core Collection and Scopus from 2020 to 2025 using a BIM-centred, rather than title-restricted, eligibility framework. Direct BIM studies formed the core evidence, while adjacent digital or spatial studies were retained only when screening identified a clear information, sensing, modelling, analytical, environmental, infrastructure, or decision-support function relevant to built-asset decisions; these records were not treated as direct evidence of BIM adoption or effectiveness. Of 2,641 records, 1,758 were retained after deduplication and staged screening. Analyses combined publication and citation trends, year-normalized citation weighting, geographic and disciplinary mapping, keyword co-occurrence, author-keyword biclustering, thematic timelines, highly cited studies, and citation-weighted content coding. Six external experts assessed thematic relevance and coding validity, yielding ordinal Krippendorff’s alpha values of 0.830 and 0.815. Three overlapping periods emerged: digital foundations in 2020–2021, broader technological and life-cycle integration in 2022–2023, and increasing emphasis on intelligent analytics and governance in 2024–2025. Machine and deep learning mainly supported prediction, classification, recognition, and generation, whereas rule-based methods and optimization supported checking and alternative selection. Major barriers involved interoperability, data quality, organizational capability, cost, accountability, and SME adoption. A BIM-centred “1 + 3 + N” framework synthesizes these relationships while requiring project-level validation.