Technology Readiness and Acceptance as Predictors of Bim Adoption Intention: A Tram Study an a Project Management Consultancy

  • Harrie Awan Setya Pamunkkaz Master of Technology Management, Sepuluh Nopember Institute of Technology, Indonesia, Project Management Center, State Electricity Company (PT PLN Persero), Indonesia
  • Tri Joko Wahyu Adi Department of Civil Engineering, Sepuluh Nopember Institute of Technology, Indonesia
Keywords: Building Information Modeling, Technology Readiness, Technology Acceptance, TRAM, Project Management Consultancy

Abstract

Building Information Modeling (BIM) is a critical digital innovation for improving coordination and decision-making in construction project management; however, its adoption among project management consultancies in Indonesia remains limited. This study examines how technology readiness and technology acceptance influence BIM adoption intention in a pre-adoption consultancy context using the Technology Readiness and Acceptance Model (TRAM). A confirmatory survey was conducted at a state-owned project management consultancy involving 85 respondents from management and project site teams. Data were analyzed using the Relative Importance Index (RII) and Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results show that BIM adoption intention is mainly driven by perceived usefulness (β = 0.531, p < 0.001), followed by perceived ease of use (β = 0.263, p = 0.037). The TRAM model explains 55.7% of the variance in adoption intention (R² = 0.557). Innovativeness plays an important enabling role by positively influencing perceived usefulness (β = 0.387, p = 0.002) and perceived ease of use (β = 0.481, p = 0.001), while optimism and insecurity do not show significant effects. Descriptive analysis further indicates that BIM is highly valued for its long-term organizational benefits (RII = 0.925) and early problem detection capability (RII = 0.915). No significant perceptual differences are found between management and project site teams. These findings suggest that BIM adoption intention in project management consultancies is primarily shaped by performance-related and usability perceptions, underscoring the importance of targeted training, infrastructure readiness, and organizational support to translate intention into effective implementation.

References

Azhar, S. (2011). Building Information Modeling (BIM): Trends, benefits, risks, and challenges for the AEC industry. Leadership and Management in Engineering.

British Standards Institution. (2014). PAS 1192-2:2013 Specification for information management for the capital/delivery phase of construction projects using building information modelling*. BSI.

Bryde, D., Broquetas, M., & Volm, J. M. (2013). The project benefits of building information modelling (BIM). International Journal of Project Management, 31(7), 971–980. https://doi.org/10.1016/j.ijproman.2012.12.001

Cao, D., Shao, S., Huang, B., & Wang, G. (2022). Multidimensional behavioral responses to the implementation of BIM in construction projects: an empirical study in China. Engineering, Construction and Architectural Management, 29(2), 819-841. https://doi.org/10.1108/ECAM-09-2020-0735

Chatsuwan, M., Manajitt, B., Ichinose, M., & Alkhalaf, H. (2024). A Review of BIM Maturity in Standards and Guidelines Across Asia. In Proceedings of the 41st International Conference of CIB W (Vol. 78).

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

Eastman, C. M., Teicholz, P., Sacks, R., & Liston, K. (2011). BIM Handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors (2nd ed.).

Elghaish, F., Matarneh, S. T., Edwards, D. J., Pour Rahimian, F., El-Gohary, H., & Ejohwomu, O. (2022). Applications of Industry 4.0 digital technologies towards a construction circular economy: gap analysis and conceptual framework. Construction Innovation, 22(3), 647-670. https://doi.org/10.1108/CI-03-2022-0062

Faisal Shehzad, H. M., Binti Ibrahim, R., Yusof, A. F., Mohamed khaidzir, K. A., Shawkat, S., & Ahmad, S. (2022). Recent developments of BIM adoption based on categorization, identification and factors: a systematic literature review. International Journal of Construction Management, 22(15), 3001-3013. https://doi.org/10.1080/15623599.2020.1837719

Fundra, I. W., Susanto, A., & Widjaja, A. (2021). Analisis faktor-faktor yang mempengaruhi implementasi BIM pada proyek konstruksi di Indonesia. Jurnal Teknik Sipil, 28(1), 45-58.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.

Hardin, B. (2009). BIM and construction management: proven tools, methods, and workflows.

Hosseini, M. R., Maghrebi, M., Akbarnezhad, A., Martek, I., & Arashpour, M. (2018). Analysis of citation networks in building information modeling research. Journal of Construction Engineering and Management.

Huang, J. (2023). Digital engineering transformation with trustworthy AI towards industry 4.0: emerging paradigm shifts. Journal of Integrated Design and Process Science, 26(3-4), 267-290. https://doi.org/10.3233/JID-229010

Jung, Y., & Joo, M. (2011). Building information modelling (BIM) framework for practical implementation. Automation in Construction.

Kobi, J. (2024). Developing dashboard analytics and visualization tools for effective performance management and continuous process improvement. International Journal of Innovative Science and Research Technology (IJISRT), 9(10.38124).

Koca, D., & van Deursen, A. (2025). Exploring labor market dynamics in digital transformations: The perspective of Dutch SMEs. Journal of the International Council for Small Business, 1-36. https://doi.org/10.1080/26437015.2025.2538182

Lembangan, M. O., & Nurdiah, E. A. (2025). A Review of BIM Implementation in Indonesia's Smart Cities: Challenges and Opportunities. Advances in Civil Engineering and Sustainable Architecture, 7(1), 46-59. https://doi.org/10.9744/acesa.v7i1.14569

Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657.

Mashinini, P. C., Mahachi, J., Gumbo, T., & Mphambukeli, T. N. (2025). A critical review of BIM adoption in public infrastructure projects: global trends and lessons for South Africa. Frontiers in Built Environment, 11, 1685353. https://doi.org/10.3389/fbuil.2025.1685353

Oesterreich, T. D., & Teuteberg, F. (2016). Understanding the implications of digitization and automation in the construction industry: A systematic literature review. Computers in Industry, 83, 121–139. https://doi.org/10.1016/j.compind.2016.09.006

Parasuraman, A. (2000). Technology readiness index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320.

Rane, N. (2023). Integrating building information modelling (BIM) and artificial intelligence (AI) for smart construction schedule, cost, quality, and safety management: challenges and opportunities. Cost, Quality, and Safety Management: Challenges and Opportunities (September 16, 2023).

Sacks, R., Radosavljevic, M., & Barak, R. (2010). Requirements for building information modeling based lean production management systems for construction. Automation in Construction, 19(5), 641–655.

Sarigul, F. H., & Gunaydin, H. M. (2025). Integrated BIM, GIS and interoperable digital technologies in lifecycle management of building construction projects: systematic literature review. Smart and Sustainable Built Environment. https://doi.org/10.1108/SASBE-08-2024-0312

Sepasgozar, S. M., Khan, A. A., Smith, K., Romero, J. G., Shen, X., Shirowzhan, S., ... & Tahmasebinia, F. (2023). BIM and digital twin for developing convergence technologies as future of digital construction. Buildings, 13(2), 441. https://doi.org/10.3390/buildings13020441

Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in Construction, 18(3), 357–375.

Succar, B. (2010). The five components of BIM performance measurement. In CIB World Congress 2010. CIB.

Thomas, A. (2024). Digitally transforming the organization through knowledge management: A socio-technical system (STS) perspective. European Journal of Innovation Management, 27(9), 437-460. https://doi.org/10.1108/EJIM-02-2024-0114

Wang, K., Guo, M., Di Sarno, L., & Sun, Y. (2024). Decoding BIM adoption: a meta-analysis of 10 years of research—exploring the influence of sample size, economic level, and national culture. Buildings, 14(4), 920. https://doi.org/10.3390/buildings14040920

Wang, X., & Lin, J. (2019). Applying the technology readiness and acceptance model to investigate the determinants of BIM adoption in Taiwan's construction industry. Construction Management and Economics, 37(7), 359-377.

Wong, K.D. and Fan, Q. (2013) Building Information Modelling (BIM) for Sustainable Building Design. Facilities, 31, 138-157. http://dx.doi.org/10.1108/02632771311299412

Zizic, M. C., Mladineo, M., Gjeldum, N., & Celent, L. (2022). From industry 4.0 towards industry 5.0: A review and analysis of paradigm shift for the people, organization and technology. Energies, 15(14), 5221. https://doi.org/10.3390/en15145221

Published
2026-02-10
How to Cite
Pamunkkaz, H. A. S., & Adi, T. J. W. (2026). Technology Readiness and Acceptance as Predictors of Bim Adoption Intention: A Tram Study an a Project Management Consultancy. Journal La Multiapp, 7(2), 472-485. https://doi.org/10.37899/journallamultiapp.v7i2.2969