Assessing the adoption and impact of construction automation technologies on project management efficiency: A case study of Cebu City

Abstract

This study rigorously assessed the adoption and impact of construction automation technologies on project management efficiency within the urban infrastructure context of Cebu City, Philippines. Grounded in the Technology Acceptance Model (TAM), the research examined the influence of three key constructs; Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Behavioral Intention to Use (BIU) on the integration of automation technologies, including Building Information Modeling (BIM), Artificial Intelligence (AI), and the Internet of Things (IoT). Utilizing a quantitative-descriptive and correlational design, data were collected from 40 purposively selected construction professionals through validated survey instruments. Statistical analyses included descriptive statistics, Pearson’s correlation, and internal consistency testing via Cronbach’s Alpha. The findings revealed that only PEOU exhibited a statistically significant relationship with the level of influence of automation adoption. At the same time, PU and BIU did not demonstrate significant associations with project management efficiency or procedural effectiveness. This outcome suggests that external structural barriers, such as regulatory gaps, limited financial capacity, and inadequate workforce readiness, remain significant impediments to the implementation of automation. Despite favorable perceptions of automation’s utility in enhancing coordination, cost estimation, and real-time monitoring, actual usage remained suboptimal. The study concluded that construction automation can substantially contribute to improved project management efficiency if institutionalized through policy incentives, standardized digital frameworks, and comprehensive workforce upskilling programs. These findings offered critical implications for stakeholders seeking to accelerate digital transformation in the Philippine construction sector. They proposed directions for future research focused on automation, scalability, and BIM compliance enforcement across varying firm sizes.