Recent statistics suggest that the construction industry continues to experience poor project performance. Specifically, construction productivity has witnessed a meager annual growth of 1% over the past 20 years while the industry constantly records both a high number of fatalities and a high fatality rates relative to other industries. The lack of sufficient progress is primarily associated with the characteristics of the construction industry. According to reports, effective integration of technology into construction operations could potentially increase construction performance by approximately 15%. Research trends suggest a growing awareness surrounding the application and the usefulness of technology in the construction industry. Regardless of the increasing investment in technology use in the construction industry, recent studies indicate that the level of technology adoption and utilization is severely lagging behind most industries. Existing literature suggests that the cost and time associated with integrating a technology alongside the technology’s potential failure to diffuse across an organization are primary concerns that retard the growth of technology utilization. One way to enhance strategic planning and execution -such as technology integration – is to utilize robust decision support systems. However, limited studies have focused on developing effective decision support tools aimed at facilitating technology integration.
To fill this research gap, this dissertation utilizes a range of research methodologies and data analysis techniques to develop and evaluate novel decision support tools for enhancing the integration of technology into construction work processes. Five manuscripts focused on identifying processes for improving the adoption, implementation, and acceptance of technology are presented in this dissertation. First, important factors that could predict the adoption of construction technology are identified and validated. The second manuscript investigates the impact of the predictors on safety technologies. Based on the result, the researcher developed and validated a framework termed construction safety technology adoption framework (C-STAF). The third manuscript proposes and applies a framework for evaluating the effectiveness of work zone safety technologies (WZSTs). The fourth manuscript focused on developing an index-construction safety technology adoption index (C-STAI)-for measuring and predicting the potential acceptance of a safety technology. The last manuscript proposes and implements a model for choosing between safety technologies. Findings from this dissertation will benefit construction researchers and practitioners by providing repeatable, reproducible, and practical processes for making informed technology integration decision that can improve project performance.
Funding Statement (additional comments about funding)
This dissertation was funded, in part, by a Small Study Grant (No. 17‐4‐PS) from the Center for Construction Research and Training (CPWR), and a research grant (SPR 790) from Oregon Department of Transportation (ODOT).