Enabling BIM Innovation Through Knowledge-Driven Legal-Contractual Risk Management: A Strategic Risk Breakdown Structure

Building Information Modelling (BIM) represents a technological and organisational innovation transforming the architecture, engineering, and construction (AEC) industry by embedding data-rich collaboration into project delivery. However, the diffusion of this innovation is constrained by unresolved legal-contractual complexities, where conventional frameworks fail to manage BIM-specific risks such as unclear responsibilities, intellectual property, and dispute resolution. This study advances knowledge and practice by conceptualising a novel legal-contractual amalgamated dimensional factor that links identified risks with tailored management strategies, thereby enabling BIM innovation to be embedded more effectively into organisational processes. A mixed-methods design was adopted. An integrative review of Scopus- and Google Scholar-indexed studies, supported by thematic analysis in NVivo, generated a comprehensive Risk Breakdown Structure (RBS) that organises fragmented knowledge of legal-contractual risks. Qualitative content analysis, combined with survey and expert interview data, enabled triangulated validation and the development of the BIM-RBS Matrix and BIM-RBS–MS Nexus. These tools operationalise risk knowledge by ranking severity (SPSS) and aligning management strategies with specific risk categories. The results highlight actionable innovations such as QR-code protocols to strengthen cyber/data security and shared risk–reward mechanisms to address contractual design ambiguities. The study contributions are: (1) conceptualising a structured legal-contractual knowledge spectrum for BIM innovation, (2) advancing methodological integration for risk knowledge creation and validation, and (3) providing actionable frameworks that support industry, policymakers, and researchers in embedding BIM innovation more reliably. Framing legal-contractual risk knowledge as critical enabler of innovation extends theoretical understanding, offering globally relevant pathways for knowledge-based transformation of the AEC sector.