Adoption of Digital Technologies in Construction Measurement and Estimation: Strategies for the Malaysian Construction Industry

The adoption of digital technologies in construction measurement and estimation has become increasingly important in enhancing accuracy, efficiency, and overall project performance within the Malaysian construction industry. Despite these benefits, the industry continues to face several challenges, including reliance on traditional practices, high implementation costs, lack of skilled personnel, and resistance to organisational change. This study aims to identify effective strategies to support the successful adoption of digital technologies in construction measurement and estimation. A quantitative research approach was employed, involving a structured questionnaire survey distributed to quantity surveyors in Selangor. A total of 116 valid responses were obtained, representing a response rate of 49.15%. The collected data were analysed using Statistical Package for the Social Sciences (SPSS) based on a 5-point Likert scale. The findings reveal that enhancing skills development and training is the most critical strategy for facilitating digital adoption. This is followed by other significant strategies, including strengthening government policies and financial incentives, increasing investment in research and development (R&D), standardising processes and systems, and promoting collaboration and knowledge sharing among industry stakeholders. The results emphasise the importance of human capital development and strong institutional support in overcoming existing barriers. In conclusion, the study highlights the need for a comprehensive and integrated approach to accelerate digital transformation in construction measurement and estimation. The implementation of these strategies can significantly improve cost accuracy, reduce inefficiencies, and enhance the overall competitiveness of the Malaysian construction industry. This aligns with the national agenda of advancing towards Construction 4.0 and achieving the objectives outlined in the Construction Industry Transformation Programme (CITP).

Digital technologies, construction measurement, cost estimation, adoption strategies

1. Abdulqader, M., Alias, A. H., Haron, N. A., & Yusoff, M. Z. M. (2025). Advancing BIM adoption in Malaysia’s construction industry. International Journal of Sustainable Development and Planning. [Google Scholar] [Crossref]

2. Azhar, S. (2011). Building information modeling (BIM): Trends, benefits, risks, and challenges. Leadership and Management in Engineering, 11(3), 241–252. [Google Scholar] [Crossref]

3. Cheok, K. Y., Seow, T. W., Goh, K. C., & Masrom, M. A. N. (2025). Enhancing cost estimation with building information modeling (BIM) in construction industry: A case study in Kuala Lumpur. Research in Management of Technology and Business, 6(1), 602–616. [Google Scholar] [Crossref]

4. CIDB. (2020). Construction 4.0 strategic plan (2021–2025). Construction Industry Development Board Malaysia. [Google Scholar] [Crossref]

5. CIDB Malaysia. (2021). Construction 4.0 strategic plan (2021–2025). [Google Scholar] [Crossref]

6. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. SAGE Publications. [Google Scholar] [Crossref]

7. Davies, R., & Harty, C. (2013). Measurement and exploration of individual beliefs about the consequences of building information modelling use. Construction Management and Economics, 31(11), 1110–1127. [Google Scholar] [Crossref]

8. Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2018). BIM handbook: A guide to building information modeling. Wiley. [Google Scholar] [Crossref]

9. Jamalulil, S.N.N.S., Mustaffa, M.H., Hussin, S.N., Wahid, A.M.A., Salleh, N.M. (2025). A Review on Digital Transformation in Construction Measurement and Estimation in Malaysia. International Journal of Business and Technology Management, Vol. 7, No. 5(e-ISSN: 2682-7646), 46–56. https://doi.org/10.55057/ijbtm.2025.7.5.5 [Google Scholar] [Crossref]

10. Kassem, M., & Succar, B. (2017). Macro BIM adoption: Comparative market analysis. Automation in Construction, 81, 286–299. [Google Scholar] [Crossref]

11. Monteiro, A., & Martins, J. P. (2013). A survey on modeling guidelines for quantity takeoff-oriented BIM-based design. Automation in Construction, 35, 238–253. [Google Scholar] [Crossref]

12. Oesterreich, T. D., & Teuteberg, F. (2016). Understanding the implications of digitisation in the construction industry. Computers in Industry, 83, 121–139. [Google Scholar] [Crossref]

13. Pan, Y., & Zhang, L. (2021). Roles of artificial intelligence in construction engineering and management: A critical review. Automation in Construction, 122, 103517. [Google Scholar] [Crossref]

14. Raman, F., & Husain, S. H. (2025). Identifying key barriers in BIM adoption among building surveyors in Malaysia. [Google Scholar] [Crossref]

15. Raosoft. (2004). Sample size calculator. [Google Scholar] [Crossref]

16. Succar, B., & Kassem, M. (2015). Macro-BIM adoption: Conceptual structures. Automation in Construction, 57, 64–79. [Google Scholar] [Crossref]

17. Volk, R., Stengel, J., & Schultmann, F. (2014). Building information modeling (BIM) for existing buildings. Automation in Construction, 38, 109–127. [Google Scholar] [Crossref]

18. Yusof, A. M., Johar, S., & Rahmat, I. (2020). Understanding digital transformation in Malaysian construction SMEs. Journal of Construction in Developing Countries, 25(1), 89–106. [Google Scholar] [Crossref]

19. Zhang, C., et al. (2024). Financial mechanisms and digital transformation in construction industry. [Google Scholar] [Crossref]

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