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Purpose This study develops an integrative framework for understanding the convergence of Digital Twin (DT), Building Information Modeling (BIM), and Generative Artificial Intelligence (GAI) in the construction industry. While these technologies are transforming construction practices, existing research lacks a comprehensive framework that explains their synergistic integration patterns and enabling factors across the project lifecycle. Design/methodology/approach A bibliometric-systematic literature review (B-SLR) methodology was employed, analysing 40 carefully selected journal articles from Scopus and Web of Science databases. The analysis combined quantitative bibliometric techniques with qualitative content analysis to identify convergence patterns, map theoretical foundations, and develop an integrative framework. Findings The study presents a multi-dimensional framework revealing: (1) five primary technology integration patterns (BIM-DT, DT-AI, BIM-AI, BIM-DT-AI, and BIM-DT-Blockchain); (2) four dimensions of synergy (design and planning, construction and monitoring, operation and maintenance, and sustainability and energy efficiency); (3) ten specific synergy areas enabled by GAI integration; and (4) a comprehensive taxonomy of technological, organisational, and regulatory enabling factors. The framework demonstrates how DT is the central convergence point, with implementation challenges equally distributed across interoperability, data security, skills gaps, and regulatory compliance. Originality/value This study contributes an original integrative framework that advances the theoretical understanding of multi-technology convergence in construction. Unlike previous reviews, it provides a structured model for analysing technology integration patterns, identifies specific enabling factors for each integration type, and offers a roadmap for practitioners and policymakers. The framework addresses critical gaps in understanding how BIM, DT, and GAI can be synergistically implemented to enhance construction project outcomes.
SCHERY et al. (Tue,) studied this question.