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12/12/2025
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Thai, N. T., Le, V. C., & Bui, N. T. (2025). Validating the measurement model of factors influencing BIM adoption in construction project management in Vietnam using confirmatory factor analysis (CFA). Journal of Water Resources & Environmental Engineering, 97, 132-138. https://dev.vojs.vn/index.php/jwree/article/view/28
Validating the measurement model of factors influencing BIM adoption in construction project management in Vietnam using confirmatory factor analysis (CFA)
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Abstract
This study validates the measurement model of factors influencing the adoption of Building Information Modeling (BIM) in construction project management in Vietnam using Confirmatory Factor Analysis (CFA) with a sample of 200 experts. Six latent constructs were examined, including Institutional - Policy, Human Resources, Management, Technology, Economics, and Environment. The results indicate that the measurement model achieved a good overall model fit (χ²/df = 1.925; GFI = 0.901; CFI = 0.932; TLI = 0.918; RMSEA = 0.054). The measurement scales demonstrated satisfactory composite reliability (CR ≥ 0.89), convergent validity (AVE ≥ 0.57), and discriminant validity. This research contributes a statistically validated measurement instrument tailored to the Vietnamese context, providing a solid academic foundation for subsequent causal relationship analyses in future studies.
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BIM, CFA, measurement model, construction project management, Vietnam
References
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Abdirad H., Lin K. Y. (2025), Organizational readiness and BIM-enabled project performance: Empirical evidence from emerging economies, Engineering, Construction and Architectural Management, Early Access 2025.
Succar B. (2009), Building information modelling framework: A research and delivery foundation for industry stakeholders, Automation in Construction, Vol. 18, No. 3, pp. 357–375.
Ghaffarianhoseini A. et al. (2017), Building information modelling (BIM) uptake: Clear benefits, understanding its implementation, risks, and challenges, Renewable and Sustainable Energy Reviews, Vol. 75, pp. 1046–1053.
Nguyen T. V. et al. (2021), Barriers to BIM adoption in building projects: A case study in Vietnam, International Journal of Building Pathology and Adaptation, Vol. 39, No. 3, pp. 456–472.
Mui T. V. and Hoang V. G. (2018), Study on BIM application in construction project management in Vietnam, Journal of Science and Technology in Civil Engineering, Vol. 12, No. 4, pp. 45–56.
Zhang L., Chen Y., and Li Q. (2020), Factors influencing BIM adoption in construction projects: A review, Advances in Civil Engineering, Vol. 2020, Article No. 8825710.
Hair J. F., Black W. C., Babin B. J., and Anderson R. E. (2019), Multivariate Data Analysis, 8th edition, Cengage Learning, Hampshire, U.K.
Hu L. and Bentler P. M. (1999), Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling, Vol. 6, No. 1, pp. 1–55.
Fornell C. and Larcker D. F. (1981), Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, Vol. 18, No. 1, pp. 39–50.
Marsh H. W., Hau K. T., and Wen Z. (2004), In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s findings, Psychological Bulletin, Vol. 114, No. 3, pp. 371–385.
Lu Y., Li Y., Skibniewski M. J., Wu Z. (2024), Digital transformation and BIM adoption in construction projects: A systematic review and future research agenda, Automation in Construction, Vol. 156, Article No. 105107.
Abdirad H., Lin K. Y. (2025), Organizational readiness and BIM-enabled project performance: Empirical evidence from emerging economies, Engineering, Construction and Architectural Management, Early Access 2025.