Technology Acceptance and Behavioral Adaptation in Construction Automation: Catalyzing Project Management Efficiency
Abstract
The rapid advancement of automation is reshaping the construction sector, offering measurable improvements in project efficiency, cost-effectiveness, and sustainability. This study assessed the adoption and impact of construction automation technologies in Cebu City, Philippines focusing on perceived benefits, constraints, and industry readiness. A quantitative descriptive–correlational design was employed, surveying 40 construction professionals using validated questionnaires. Data were analyzed using descriptive statistics, weighted means, multiple regression, and analysis of variance (ANOVA). Findings revealed limited adoption, with only 17.5% of respondents implementing automation tools, while 55% had not, and 27.5% remainedundecided. Despite low uptake, more than half reported efficiency gains, particularly in coordination and error reduction, with a mean effectiveness score of 4.041 (highly effective). Regression results showed no significant predictive relationships among Technology Acceptance Model (TAM) constructs, except that perceived ease of use significantly influenced organizational impact (p < 0.01). ANOVA results confirmed that automation improved project management effectiveness, operational efficiency, and procedural outcomes (p < 0.05). However, financial constraints, skill shortages, and regulatory gaps continued to hinder largescaleintegration. The study concludes that comprehensive workforce training, standardized accreditation, and targeted government incentives are essential to accelerate adoption and maximize the long-term benefits of automation in the Philippine construction industry.
Keywords:
Construction automation, project management efficiency, Building Information Modeling (BIM), technology adoption, digital transformation
References
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Civils.ai. (2024, May 9). AI in construction certification. Civils.ai. https://civils.ai/ai-in-construction-training-course
Dusty Robotics. (2023, July 31). What are the barriers to adopting robotics in construction? https://www.dustyrobotics.com/articles/what-are-the-barriers-to-adopting-robotics-in-construction
Elhajjar, S., Yacoub, L., & Yaacoub, H. (2023). Automation in business research: A systematic literature review. Information Systems and e-Business Management, 21(3), 675–698. https://doi.org/10.1007/s10257-023-00645-z
Ferreira, B., & Reis, J. (2023). A systematic literature review on automation and digital transformation. Logistics, 7(4), 80. https://doi.org/10.3390/logistics7040080
Fridkin, S., Greenstein, G., Cohen, A., & Damari, A. (2024). Perceived usefulness of a mandatory information system. Applied Sciences, 14(16), 7413. https://doi.org/10.3390/app14167413
Houghton, S., Adams, A., Nielsen, E. M., Ang, C., & de Carvalho Gomes, H. (2023). Overcoming the challenges of using automated technologies for public health evidence synthesis. Eurosurveillance, 28(45), 2300183. https://doi.org/10.2807/1560-7917.ES.2023.28.45.2300183
International Association for Automation and Robotics in Construction (IAARC). (2024, June 3). Advancing automation and robotics in construction. https://www.iaarc.org/
International Society of Automation (ISA). (2025). Certified Automation Professional (CAP) certification. https://www.isa.org/certification/cap
JCV & Associates. (2023, August 15). How AI and automation are changing the construction industry. https://jcvassociates.com/how-ai-and-automation-are-changing-the-construction-industry
Jesus, J. B. (2024). Revealing contrasting outlooks: A critical review of training programs for improved workplace behavior. Psychology and Education.
Rasull, A., Jantan, A. H., Ali, M. H., Jaharudin, N. S., & Mansor, Z. D. (2020). Benefit and sacrifice factors determining technology adoption. Journal of International Business and Management, 3(1), 1–20.
Reiff, J., & Schlegel, D. (2022). Hybrid project management: A systematic literature review. International Journal of Information Systems and Project Management, 10(2), 45–63. https://doi.org/10.12821/ijispm100203
Republic Act No. 10173. (2012). Data Privacy Act of 2012. Official Gazette of the Republic of the Philippines. https://www.privacy.gov.ph/data-privacy-act/
Salar, H. C., & Hamutoglu, N. B. (2022). The role of perceived ease of use and usefulness in technology adoption. Journal of Educational Technology, 20(1), 245–266. https://doi.org/10.1108/JEDT-12-2020-0481
Smolarek, B. B., & Scrivener, L. (2021). Examining business-driven workforce development initiatives. Journal of Education Policy, 36(3), 349–366. https://doi.org/10.1080/02680939.2019.1686539
Strickland, L., Farrell, S., Wilson, M. K., Hutchinson, J., & Loft, S. (2024). How do humans learn about automated systems? Human Factors. https://doi.org/10.1177/001872082423500533
Tahar, A., Riyadh, H. A., Sofyani, H., & Purnomo, W. E. (2020). Perceived ease of use, perceived usefulness, perceived trust, and intention to use. Journal of Asian Finance, Economics and Business, 7(9), 537–547.
Toros, E., Asiksoy, G., & Sürücü, L. (2024). Refreshment student learning through technology. Humanities and Social Sciences Communications, 11(1), 1–10.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.
Published
2025-12-20
Section
Articles
Copyright (c) 2025 Asia Pacific Journal of Social and Behavioral Sciences
Copyright holder is the Bukidnon State University.
