Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review

Chuyou Fu , Jun Wang*, Ziyi Qu , Martin Skitmore, Jiaxin Yi, Jianli Chen

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

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Considering the emergence and adoption of various innovative technologies, the construction industry has undergone transformation into a more secure, highly efficient, and ecologically sustainable landscape. An increasing number of studies uses the structural equation modeling (SEM) method to explore the dynamics of technology adoption and use within the construction sector. Previous studies have mainly focused on qualitative analysis using the SEM method to analyze technology adoption and usage in the construction industry. This study, however, dis-tinguishes itself from previous research by focusing on the SEM method itself and conducting a systematic analysis using scientometric methods. Based on a total of 140 relevant journal articles, this study adopts a scientometric analysis approach to conduct a holistic review encompassing sources, researchers, keywords, and highly cited documents. The research findings are as follows: (1) the primary focus of the current research topics is on BIM technology; (2) most studies employ cross-sectional SEM instead of longitudinal SEM; (3) there is a deficiency in the theoretical foundation for designing SEM in current research; and (4) the selection of either reflective or formative measures lacks sufficient rigor. Qualitative analysis is used to examine prevailing issues in research design and address the intricate technicalities and potential challenges inherent in the SEM method. Three research gaps and future directions are presented: diversifying regions of study and research topics, incorporating theoretical support for research design, and carefully choosing reflective or formative measures. The findings provide a comprehensive roadmap and valuable reference for future research in this field
Original languageEnglish
Article number3824
Pages (from-to)1-21
Number of pages21
Issue number9
Publication statusPublished - 2 May 2024


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