ITcon Vol. 28, pg. 39-69,

A systematic review of technology acceptance models and theories in construction research

submitted:November 2021
revised:January 2023
published:February 2023
editor(s):Žiga Turk
authors:Chukwuma Nnaji, Assistant Professor
Department of Construction Science,
Texas A&M University, College Station, TX 77840;

Ifeanyi Okpala, Ph.D. Candidate,
Department of Civil, Construction, and Environmental Engineering,
The University of Alabama, 3043 HM Comer, Tuscaloosa, AL 35487

Ibukun Awolusi, Assistant Professor
School of Civil & Environmental Engineering, and Construction Management,
The University of Texas at San Antonio, 501 W. César E. Chávez Blvd, San Antonio, TX 78207,

John Gambatese, Professor
School of Civil and Construction Engineering,
Oregon State University, Corvallis, OR 97331,
summary:Technology use in the construction industry fosters improvements in schedule, safety, cost, productivity, and quality. In this domain, the construction technologies adoption highly depends on stakeholders, who may exhibit some resistance to operational use. This underscores the importance of determining technology integration success using effective methods such as predictive and explanatory modelling. Although existing literature has provided some critical insight into the use of these models and theories, there is no domain-based synthesis on the utility of these models and theories as tools to facilitate the integration of emerging construction technologies. Therefore, this paper provides a systematic review and content analysis showcasing different methods and theories for investigating technology acceptance and generates insights expected to guide future technology acceptance studies. Using a three-phase systematic review process, 35 relevant articles were identified and analysed. This review identified perceived ease of use, perceived usefulness, social norm, attitude, perceived behavioural control, and facilitating conditions as key constructs impacting workers’ intention to accept a construction technology. TAM, TPB, and UTAUT were identified as popular choices for developing hybrid models, while UTAUT provided a relatively higher predictive power. Finally, seven areas for further exploration were discussed. This study contributes to construction knowledge by providing a better understanding of technology acceptance research and generating fundamental insights needed to develop robust and effective predictive and explanatory models for advancing technology acceptance research which would support successful technology integration.
keywords:Construction management; Technology adoption; Predictive modelling; Explanatory modelling; Critical review; Content analysis. Acceptance model
full text: (PDF file, 0.641 MB)
citation:Nnaji C, Okpala I, Awolusi I, Gambatese J (2023). A systematic review of technology acceptance models and theories in construction research, ITcon Vol. 28, pg. 39-69,