As a disruptive information and communication technology (ICT) in the architecture, engineering, construction, and operation (AECO) industry, building information modeling (BIM) enables project teams to manage a project via a model-based cooperative approach. Although it has a widespread impact on the industry, the systematic implementation of BIM in projects faces challenges. This study integrated BIM into the lifecycle of a building project with the introduction of a conceptual framework constituted by BIM Information Flow, BIM Model Chain, BIM Workflow, BIM Institutional Environment, and BIM-based Project Management Information System (PMIS). This conceptual framework identifies the key areas for integrating BIM into the project lifecycle and explains how BIM works for project management practice. Through an ethnographic action research approach, the study developed a BIM roadmap for the project lifecycle by systematically implementing BIM in the building project. The major findings and pieces of evidence derived via the implementation support the conceptual framework. The following discussions explain how BIM disrupts the project from the view of organization design and clarify the contributions of this study in project management, as well as BIM adoption and integration. Finally, the conclusions focus on the development of this research, the role of the conceptual framework to underlie the BIM roadmap, and the research limitations. Recommendations are provided toward future research works.

The production of the architecture engineering and construction (AEC) industry is organized by projects. With the diffusion of information and communication technology in the industry, building information modeling (BIM) is widely adopted in AEC projects. However, the systematic implementation of BIM in AEC projects experiences challenges. This study aims to identify critical strategies for enhancing BIM implementation within the AEC project context. Initially, 17 strategies are drawn from a comprehensive review of the relevant literature. Through a questionnaire survey with 116 effective responses from the practitioners, ten critical strategies are identified, with the top five being clearly defined plans and objectives for BIM implementation, financial support, capabilities and skills in BIM technology, availability and interoperability of engineering information and data, and the aligned objective of BIM implementation with the project goal. The study also investigates the possible discrepancy in the different actors’ assessments on the criticality of the strategies to validate the survey. The further principal component analysis groups the strategies and finds five latent factors of the strategies, including institutional governance, change accommodation, technical environment, cooperation, and resources. This finding reveals that systematic BIM implementation is inevitably associated with the AEC project context and indicates that the enhancement of current BIM implementation in projects covers the strategies of the technical, institutional, and managerial aspects to accommodate changes brought by BIM. An international comparison of the top drivers with the found peer studies from Nigeria, Singapore, and Turkey classifies leadership as a driving force to incorporate BIM into the AEC projects. The results provide implications for enhancing BIM implementation in AEC projects and may help improve the efficiency of the industry.

Although building information modelling (BIM) applies widely in the architecture, engineering, and construction (AEC) industry, its systematic implementation in AEC projects still experiences challenges. While most previous studies have investigated general BIM implementation, the present study precisely focuses on the barriers to BIM implementation at the AEC project level and explores their sources in the Chinese project context. Based on a questionnaire survey with 166 valid responses from experienced BIM practitioners as empirical evidence from the Chinese construction context, the data were processed using descriptive statistical analysis, non-parametric analysis and principal component analysis. The results of the descriptive analysis classified 14 critical barriers. The international comparison of the top five barriers indicated that the most critical barriers were similar but ranked differently in different countries. The following principal component analysis revealed six underlying factors for all the barriers, which were experience and capabilities, technical conditions, system inertia, extra input, change of work routines, and implementation risks. The findings of this study may help the practitioners to understand BIM implementation barriers, allocate resources, and prioritize efforts in project practices. This study can also provide implications for BIM deployment and governance in the AEC industry.