Digital twin and BIM adoption in construction project management: a quantitative expert-based study
Journal: RUDN Journal of Public Administration (Vol.12, No. 4)Publication Date: 2025-12-25
Authors : Luan Nguyen; Luat Nguyen; Kien Vu; Ngoc Pham;
Page : 509-519
Keywords : virtual replica; information modeling systems; project delivery in construction; innovation diffusion; data-driven assessment; digital shift in AEC;
Abstract
This study investigates the role of Digital Twin (DT) services in facilitating the adoption of Building Information Modeling (BIM) in construction project management. Despite growing interest in digital transformation within the Architecture, Engineering, and Construction (AEC) industry, empirical evidence on how DT influences BIM implementation remains limited. To address this gap, a structured questionnaire was developed through an extensive literature review and distributed to 53 professionals actively engaged in BIM and DT applications, including contractors, consultants, and academics. The collected data were analyzed using SPSS with reliability tests (Cronbach’s Alpha), Pearson correlation, independent-samples t-tests, and one-way ANOVA with post-hoc analysis. The results revealed strong internal consistency of the survey instrument (Cronbach’s Alpha = 0.944), confirming the robustness of the measurement scale. Correlation analysis showed significant positive associations between DT service factors and BIM adoption (p < 0.01). Group comparisons demonstrated that perceptions of DT’s contribution to BIM adoption varied across organizational roles, with notable differences between contractors, consultants, and research institutions (p < 0.05). These findings highlight the synergistic relationship between DT and BIM, suggesting that integrating DT services can enhance BIM utilization and overall project performance. The study contributes to academic knowledge and professional practice by providing empirical evidence of DT’s enabling role in digital transformation. Practical implications include guiding policymakers, project managers, and technology providers in making informed decisions regarding DT-enabled BIM adoption. Although limited by its sample size and geographic scope, this research lays the groundwork for future studies employing larger international datasets and advanced statistical modeling. The results confirm the critical importance of DT services in accelerating successful BIM implementation across the construction sector.
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