Risk paths in BIM adoption: empirical study of China

Abstract

Purpose The purpose of this paper is to model the paths of risks associated with building information modeling (BIM) adoption in the Chinese architecture, engineering and construction industry. Design/methodology/approach A total of 16 risks were identified from the literature review and grouped into nine categories. The data were collected through a questionnaire survey with 95 professionals in China. The partial least square structural equation modeling was used to analyze the data. Findings The results suggested the risk categorization was confirmed, and that 15 hypothetical risk paths were statistically significant, which formed 13 chains of risk paths. “Inadequate relevant knowledge and expertise” was the primary root risk category of all the 13 chains of risk paths. Additionally, “technological issues,” “poor information sharing and collaboration,” and “liability for data input” had direct effect on the “cost overrun with BIM,” while all the other risks indirectly influence cost via these three risk categories. Research limitations/implications Most of the respondents were designers because few clients and contractors have adopted BIM. In addition, the impact and likelihood of risks were accessed by respondents’ judgment based on their experience, which is a common problem of risk management research. As this study focuses on the Chinese architecture, engineering and construction industry, there would be geographical limitation on the findings. Practical implications This study provides practitioners with a clear understanding of the risks associated with BIM adoption and enables practitioners to take measures to mitigate the root risks and assure the potential benefits of BIM. Originality/value Although there have been studies on the risks associated with BIM adoption, most of them lacked empirical evidence and failed to examine the interactions between risks. This study is different from these prior studies, because it focuses on the interrelationships between risks and identifies the risk paths and root risks using the empirical data. Therefore, this study expands the literature relating to both BIM and risk management. Also, this study enables practitioners to take measures to mitigate the root risks and assure the potential benefits produced by BIM, thereby contributing to the practice.