Theoretical foundation and justification of the six strategic pillars for AI-BIM adoption
| Strategic pillar | Theoretical foundation | Key focus in literature | Relevance to AI-BIM adoption | Justification for inclusion |
|---|---|---|---|---|
| Policy | Institutional Theory | Regulatory frameworks, governance structures, and institutional pressure | Shapes organisational behaviour, compliance, and strategic direction in public-sector adoption | Included to capture the regulatory and governance environment influencing adoption decisions, particularly critical in public-sector road agencies |
| Budget (Resources) | Resource-Based View (RBV) | Financial capacity, organisational resources, and capability development | Determines availability of funding, technical infrastructure, and long-term sustainability | Selected to reflect the role of financial and organisational capacity constraints in enabling or limiting AI-BIM adoption |
| Technology | Technology-Organisation-Environment (TOE) Framework | Technological readiness, system compatibility, and infrastructure availability | Influences system integration, interoperability, and technical feasibility | Included to address core technological requirements and readiness necessary for AI-BIM adoption |
| People | Technology Acceptance Model (TAM) | User perception, ease of use, behavioural intention, acceptance | Affects user adoption, resistance to change, and skills utilisation | Essential for capturing human factors, including user acceptance, skills, and organisational culture |
| Data | DIKW Hierarchy | Data quality, information processing, knowledge creation, decision-making | Supports data-driven decision-making, analytics, and intelligent system functionality | Included to emphasise the foundational role of data quality, governance, and transformation into actionable insights |
| Processes | Agile and Continuous Improvement Principles | Process optimisation, adaptability, iterative improvement, workflow integration | Enables efficient lifecycle management and adaptive implementation | Selected to represent operational workflows, process integration, and adaptability in dynamic infrastructure environments |
| Strategic pillar | Theoretical foundation | Key focus in literature | Relevance to AI-BIM adoption | Justification for inclusion |
|---|---|---|---|---|
| Policy | Institutional Theory | Regulatory frameworks, governance structures, and institutional pressure | Shapes organisational behaviour, compliance, and strategic direction in public-sector adoption | Included to capture the regulatory and governance environment influencing adoption decisions, particularly critical in public-sector road agencies |
| Budget (Resources) | Resource-Based View (RBV) | Financial capacity, organisational resources, and capability development | Determines availability of funding, technical infrastructure, and long-term sustainability | Selected to reflect the role of financial and organisational capacity constraints in enabling or limiting AI-BIM adoption |
| Technology | Technology-Organisation-Environment (TOE) Framework | Technological readiness, system compatibility, and infrastructure availability | Influences system integration, interoperability, and technical feasibility | Included to address core technological requirements and readiness necessary for AI-BIM adoption |
| People | Technology Acceptance Model (TAM) | User perception, ease of use, behavioural intention, acceptance | Affects user adoption, resistance to change, and skills utilisation | Essential for capturing human factors, including user acceptance, skills, and organisational culture |
| Data | DIKW Hierarchy | Data quality, information processing, knowledge creation, decision-making | Supports data-driven decision-making, analytics, and intelligent system functionality | Included to emphasise the foundational role of data quality, governance, and transformation into actionable insights |
| Processes | Agile and Continuous Improvement Principles | Process optimisation, adaptability, iterative improvement, workflow integration | Enables efficient lifecycle management and adaptive implementation | Selected to represent operational workflows, process integration, and adaptability in dynamic infrastructure environments |
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